The Association between TRP Channels Expression and Clinicopathological Characteristics of Patients with Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PDAC) has low survival rates worldwide due to its tendency to be detected late and its characteristic desmoplastic reaction, which slows the use of targeted therapies. As such, the discovery of new connections between genes and the clinicopathological parameters contribute to the search for new biomarkers or targets for therapy. Transient receptor potential (TRP) channels are promising tools for cancer therapy or markers for PDAC. Therefore, in this study, we selected several genes encoding TRP proteins previously reported in cellular models, namely, Transient Receptor Potential Cation Channel Subfamily V Member 6 (TRPV6), Transient receptor potential ankyrin 1 (TRPA1), and Transient receptor potential cation channel subfamily M (melastatin) member 8 (TRPM8), as well as the TRPM8 Channel Associated Factor 1 (TCAF1) and TRPM8 Channel Associated Factor 2 (TCAF2) proteins, as regulatory factors. We analyzed the expression levels of tumors from patients enrolled in public datasets and confirmed the results with a validation cohort of PDAC patients enrolled in the Clinical Institute Fundeni, Romania. We found significantly higher expression levels of TRPA1, TRPM8, and TCAF1/F2 in tumoral tissues compared to normal tissues, but lower expression levels of TRPV6, suggesting that TRP channels have either tumor-suppressive or oncogenic roles. The expression levels were correlated with the tumoral stages and are related to the genes involved in calcium homeostasis (Calbindin 1 or S100A4) or to proteins participating in metastasis (PTPN1). We conclude that the selected TRP proteins provide new insights in the search for targets and biomarkers needed for therapeutic strategies for PDAC treatment.     

Gut Microbiome Changes in Gestational Diabetes

Gestational diabetes mellitus (GDM), one of the most common endocrine pathologies during pregnancy, is defined as any degree of glucose intolerance with onset or first discovery in the perinatal period. Physiological changes that occur in pregnant women can lead to inflammation, which promotes insulin resistance. In the general context of worldwide increasing obesity in young females of reproductive age, GDM follows the same ascending trend. Changes in the intestinal microbiome play a decisive role in obesity and the development of insulin resistance and chronic inflammation, especially in patients with type 2 diabetes mellitus (T2D). To date, various studies have also associated intestinal dysbiosis with metabolic changes in women with GDM. Although host metabolism in women with GDM has not been fully elucidated, it is of particular importance to analyze the available data and to discuss the actual knowledge regarding microbiome changes with potential impact on the health of pregnant women and newborns. We analyzed peer-reviewed journal articles available in online databases in order to summarize the most recent findings regarding how variations in diet and metabolic status of GDM patients can contribute to alteration of the gut microbiome, in the same way that changes of the gut microbiota can lead to GDM. The most frequently observed alteration in the microbiome of patients with GDM was either an increase of the Firmicutes phylum, respectively, or a decrease of the Bacteroidetes and Actinobacteria phyla. Gut dysbiosis was still present postpartum and can impact the development of the newborn, as shown in several studies. In the evolution of GDM, probiotic supplementation and regular physical activity have the strongest evidence of proper blood glucose control, favoring fetal development and a healthy outcome for the postpartum period. The current review aims to summarize and discuss the most recent findings regarding the correlation between GDM and dysbiosis, and current and future methods for prevention and treatment (lifestyle changes, pre- and probiotics administration). To conclude, by highlighting the role of the gut microbiota, one can change perspectives about the development and progression of GDM and open up new avenues for the development of innovative therapeutic targets in this disease.     

Targeting PI3K/AKT/mTOR Signaling Pathway in Pancreatic Cancer: From Molecular to Clinical Aspects

Although pancreatic cancer (PC) was considered in the past an orphan cancer type due to its low incidence, it may become in the future one of the leading causes of cancer death. Pancreatic ductal adenocarcinoma (PDAC) is the most frequent type of PC, being a highly aggressive malignancy and having a 5-year survival rate of less than 10%. Non-modifiable (family history, age, genetic susceptibility) and modifiable (smoking, alcohol, acute and chronic pancreatitis, diabetes mellitus, intestinal microbiota) risk factors are involved in PC pathogenesis. Chronic inflammation induced by various factors plays crucial roles in PC development from initiation to metastasis. In multiple malignant conditions such as PC, cytokines, chemokines, and growth factors activate the class I phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) (PI3K/AKT/mTOR) signaling pathway, which plays key roles in cell growth, survival, proliferation, metabolism, and motility. Currently, mTOR, AKT, and PI3K inhibitors are used in clinical studies. Moreover, PI3K/mTOR dual inhibitors are being tested in vitro and in vivo with promising results for PC patients. The main aim of this review is to present PC incidence, risk factors, tumor microenvironment development, and PI3K/AKT/mTOR dysregulation and inhibitors used in clinical, in vivo, and in vitro studies.     

Development and Characterization of Novel Films Based on Sulfonamide-Chitosan Derivatives for Potential Wound Dressing

The objective of this study was to develop new films based on chitosan functionalized with sulfonamide drugs (sulfametoxydiazine, sulfadiazine, sulfadimetho-xine, sulfamethoxazol, sulfamerazine, sulfizoxazol) in order to enhance the biological effects of chitosan. The morphology and physical properties of functionalized chitosan films as well the antioxidant effects of sulfonamide-chitosan derivatives were investigated. The chitosan-derivative films showed a rough surface and hydrophilic properties, which are very important features for their use as a wound dressing. The film based on chitosan-sulfisoxazol (CS-S6) showed the highest swelling ratio (197%) and the highest biodegradation rate (63.04%) in comparison to chitosan film for which the swelling ratio was 190% and biodegradation rate was only 10%. Referring to the antioxidant effects the most active was chitosan-sulfamerazine (CS-S5) which was 8.3 times more active than chitosan related to DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging ability. This compound showed also a good ferric reducing power and improved total antioxidant capacity.     

Nonlinear four-way kinetic-excitation-emission fluorescence data processed by a variant of parallel factor analysis and by a neural network model achieving the second-order advantage: malonaldehyde determination in olive oil samples

Four-way data were obtained by recording the kinetic evolution of excitation-emission fluorescence matrices for the product of the Hantzsch reaction between the analyte malonaldehyde and methylamine. The reaction product, 1,4-disubstituted-1,4-dihydropyridine-3,5-dicarbaldehyde, is a highly fluorescent compound. The nonlinear nature of the kinetic fluorescence data has been demonstrated, and therefore the four-way data were processed with parallel factor analysis combined with a nonlinear pseudounivariate regression, based on a quadratic polynomial fit, and also with a recently introduced neural network methodology, based on the combination of unfolded principal component analysis, residual trilinearization, and radial basis functions. The applied chemometric strategies are not only able to adequately model the nonlinear data but also to successfully determine malonaldehyde in olive oil samples. This is possible since the experimentally recorded four-way data, modeled with the above-mentioned advanced chemometric approaches, permit the achievement of the second-order advantage. This allows us to predict the analyte concentration in a complex background, in spite of the nonlinear behavior and in the presence of uncalibrated interferences. The present work is a new example of the use of higher-order data for the resolution of a complex nonlinear system, successfully employed in the context of food chemical analysis.     

Influence of composition and particle size on spin dynamics and thermodynamic properties of magnetoresistive perovskites

The thermodynamic behavior and spin dynamics of the colossal magnetoresistive (CMR) perovskites of general formula La(1-x)(A)xMn(1-y)(B)yO3 (where A is an alkaline earth, and B = Al, In) have been studied in order to evidence the effect of composition and the influence of nanocrystallinity on the thermodynamic and magnetic characteristics. By using electron paramagnetic resonance (EPR) spectroscopy, the behavior of the exchange coupling integral (J) between Mn spins and the polaron activation energy (Ea) have been investigated. The thermodynamic properties represented by the relative partial molar free energies, enthalpies and entropies of oxygen dissolution in the perovskite phase, as well as the equilibrium partial pressures of oxygen have been obtained by using solid electrolyte electrochemical cells method. The influence of the oxygen stoichiometry change on the thermodynamic properties was examined using the data obtained by a coulometric titration technique coupled with measurements of the electromotive force (EMF). The results were correlated with the average Mn valence values as determined by redox titration. The properties of the rare-earth manganites are strongly affected by the A- and B-site substitution and by the oxygen nonstoichiometry. New features related to the modifications in properties connected with the nanocrystalline state were evidenced. The correlation existing between the magnetic and thermodynamic characteristics were discussed in relation to significant changes in the overall concentration of defects.     

Integration of thin-film-fracture-based nanowires into microchip fabrication

One-step device fabrication through the integration of nanowires (NWs) into silicon microchips is still under intensive scientific study as it has proved difficult to obtain a reliable and controllable fabrication technique. So far, the techniques are either costly or suffer from small throughput. Recently, a cost-effective method based on thin-film fracture that can be used as a template for NW fabrication was suggested. Here, a way to integrate NWs between microcontacts is demonstrated. Different geometries of microstructured photoresist formed by using standard photolithography are analyzed. Surprisingly, a very simple "stripe" geometry is found to yield highly reproducible fracture patterns, which are convenient templates for fault-tolerant NW fabrication. Microchips containing integrated Au, Pd, Ni, and Ti NWs and their suitability for studies of conductivity and oxidation behavior are reported, and their suitability as a hydrogen sensor is investigated. Details of the fabrication process are also discussed.     

Electrosynthesis of nitroso compounds from (<Emphasis Type="Italic">1</Emphasis><Emphasis Type="Bold">S</Emphasis>, <Emphasis Type="Italic">2</Emphasis><Emphasis Type="Bold">S</Emphasis>)-2-amino-l-(4-nitrophenyl)-propane-1,3-diol derivatives

Nitroso compounds were electrogenerated from (1S, 2S)-2-amino-1-(4-nitrophenyl)-propane-1,3-diol derivatives (derivatives of p-nitrophenylserinol) in a “redox” flow cell equipped with two consecutive porous electrodes of opposite polarities. In spite. of the relative instability in methanol-acetate buffer of the hydroxylamine intermediates produced at the first porous electrode (cathode), the nitroso derivatives were prepared in good yields at the second one (anode). A coupling reaction between some nitroso derivatives and p-toluenesulphinic acid led to N-sulphonylphenylhydroxylamines.     

Electrical Conductivity and Thermodynamic Properties of Some Alkaline Earth-Doped Lanthanum Chromites

Alkaline-earth doped lanthanum chromites are currently the interconnecting materials of choice for solid oxide fuel cells (SOFCs). Since these materials in SOFC operating conditions are under a large oxygen potential gradient and at high temperature (1273 K), a thorough knowledge of their physical and thermochemical properties is very important. In the present study, the alkaline-earth doped lanthanum chromites La_1-xSr_xCrO₃ (x=0–0.3) and La_0.7Ca_0.3CrO₃ were prepared from complex precursors isolated from the La(NO₃)₃–Cr(NO₃)₃–urea system. The oxide powders were characterized by means of X-ray diffraction (XRD). The DC electrical conductivities of the samples were measured in the temperature range of 295–1273 K in air. The thermodynamic properties represented by the relative partial molar free energies, enthalpies, and entropies of oxygen dissolution in the perovskite phase, as well as the partial pressures of oxygen, have been investigated by the solid electrolyte galvanic cells method coupled with the solid-state coulometric titration technique, within the temperature range of 1073–1273 K and in a reducing atmosphere (10^–5 Pa). The variation of the electrical conductivities and thermodynamic properties with changing oxygen stoichiometry is discussed. The study demonstrates new correlations existing between the structural, electrical, and thermodynamic properties in the doped lanthanum chromites.Paper presented at the Sixteenth European Conference on Thermophysical Properties, September 1–4, 2002, London, United Kingdom.     

Unsupervised word sense disambiguation with N-gram features

The present paper concentrates on the issue of feature selection for unsupervised word sense disambiguation (WSD) performed with an underlying Naïve Bayes model. It introduces web N-gram features which, to our knowledge, are used for the first time in unsupervised WSD. While creating features from unlabeled data, we are “helping” a simple, basic knowledge-lean disambiguation algorithm to significantly increase its accuracy as a result of receiving easily obtainable knowledge. The performance of this method is compared to that of others that rely on completely different feature sets. Test results concerning nouns, adjectives and verbs show that web N-gram feature selection is a reliable alternative to previously existing approaches, provided that a “quality list” of features, adapted to the part of speech, is used.