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The ATR-FTIR spectral data represent a valuable source of information in a wide range of pathologies, including neurological disorders, and can be used for disease discrimination. To this end, the identification of the potential spectral biomarkers among all possible candidates is needed, but the amount of information characterizing the spectral dataset and the presence of redundancy among data could make the selection of the more informative features cumbersome. Here, a novel approach is proposed to perform feature selection based on redundant information among spectral data. In particular, we consider the Partition Around Medoids algorithm based on a dissimilarity matrix obtained from mutual information measure, in order to obtain groups of variables (wavenumbers) having similar patterns of pairwise dependence. Indeed, an advantage of this grouping algorithm with respect to other more widely used clustering methods, is to facilitate the interpretation of results, since the centre of each cluster, the so-called medoid, corresponds to an observed data point. As a consequence, the obtained medoid can be considered as representative of the whole wavenumbers belonging to the same cluster and retained in the subsequent statistical methods for disease prediction. An application on real data is finally reported to show the ability of the proposed approach in discriminating between patients affected by multiple sclerosis and healthy subjects.

Background Hypoxia plays a relevant role in tumor-related inflammation toward the metastatic spread and cancer aggressiveness. The pro-inflammatory cytokine interleukin-1β (IL-β) and its cognate receptor IL1R1 contribute to the initiation and progression of breast cancer determining pro-tumorigenic inflammatory responses. The transcriptional target of the hypoxia inducible factor-1α (HIF-1α) namely the G protein estrogen receptor (GPER) mediates a feedforward loop coupling IL-1β induction by breast cancer-associated fibroblasts (CAFs) to IL1R1 expression by breast cancer cells toward the regulation of target genes and relevant biological responses. Methods In order to ascertain the correlation of IL-β with HIF-1α and further hypoxia-related genes in triple-negative breast cancer (TNBC) patients, a bioinformatics analysis was performed using the information provided by The Invasive Breast Cancer Cohort of The Cancer Genome Atlas (TCGA) project and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets. Gene expression correlation, statistical analysis and gene set enrichment analysis (GSEA) were carried out with R studio packages. Pathway enrichment analysis was evaluated with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. TNBC cells and primary CAFs were used as model system. The molecular mechanisms implicated in the regulation of IL-1β by hypoxia toward a metastatic gene expression profile and invasive properties were assessed performing gene and protein expression studies, PCR arrays, gene silencing and immunofluorescence analysis, co-immunoprecipitation and ChiP assays, ELISA, cell spreading, invasion and spheroid formation. Results We first determined that IL-1β expression correlates with the levels of HIF-1α as well as with a hypoxia-related gene signature in TNBC patients. Next, we demonstrated that hypoxia triggers a functional liaison among HIF-1α, GPER and the IL-1β/IL1R1 signaling toward a metastatic gene signature and a feed-forward loop of IL-1β that leads to proliferative and invasive responses in TNBC cells. Furthermore, we found that the IL-1β released in the conditioned medium of TNBC cells exposed to hypoxic conditions promotes an invasive phenotype of CAFs. Conclusions Our data shed new light on the role of hypoxia in the activation of the IL-1β/IL1R1 signaling, which in turn triggers aggressive features in both TNBC cells and CAFs. Hence, our findings provide novel evidence regarding the mechanisms through which the hypoxic tumor microenvironment may contribute to breast cancer progression and suggest further targets useful in more comprehensive therapeutic strategies.

The physiological responses to estrogen hormones are mediated within specific tissues by at least two distinct receptors, ERα and ERβ. Several natural and synthetic molecules show activity by interacting with these proteins. In particular, a number of vegetal compounds known as phytoestrogens shows estrogenic or anti-estrogenic activity. The majority of these compounds belongs to the isoflavones family and the most representative one, genistein, shows anti-proliferative effects on various hormone-sensitive cancer cells, including breast, ovarian and prostate cancer. In this work we describe the identification of structurally related homoisoflavones isolated from Leopoldia comosa (L.) Parl. (L. comosa), a perennial bulbous plant, potentially useful as hormonal substitutes or complements in cancer treatments. Two of these compounds have been selected as potential ligands of estrogen receptors (ERs) and the interaction with both isoforms of estrogen receptors have been investigated through molecular docking on their crystallographic structures. The results provide evidence of the binding of these compounds to the target receptors and their interactions with key residues of the active sites of the two proteins, and thus they could represent suitable leads for the development of novel tools for the dissection of ER signaling and the development of new pharmacological treatments in hormone-sensitive cancers.

Multiple sclerosis (MS) is one of the most common neurodegenerative diseases showing various symptoms both of physical and cognitive type. In this work, we used attenuated total reflection Fourier transformed infrared (ATR-FTIR) spectroscopy to analyze plasma samples for discriminating MS patients from healthy control individuals, and identifying potential spectral biomarkers helping the diagnosis through a quick non-invasive blood test. The cohort of the study consists of 85 subjects, including 45 MS patients and 40 healthy controls. The differences in the spectral features both in the fingerprint region (1800–900 cm −1 ) and in the high region (3050–2800 cm −1 ) of the infrared spectra were highlighted also with the support of different chemometric methods, to capture the most significant wavenumbers for the differentiation. The results show an increase in the lipid/protein ratio in MS patients, indicating changes in the level (metabolism) of these molecular components in the plasma. Moreover, the multivariate tools provided a promising rate of success in the diagnosis, with 78% sensitivity and 83% specificity obtained through the random forest model in the fingerprint region. The MS diagnostic tools based on biomarkers identification on blood (and blood component, like plasma or serum) are very challenging and the specificity and sensitivity values obtained in this work are very encouraging. Overall, the results obtained suggest that ATR-FTIR spectroscopy on plasma samples, requiring minimal or no manipulation, coupled with statistical multivariate approaches, is a promising analytical tool to support MS diagnosis through the identification of spectral biomarkers.

Background The chemical carcinogen 3-methylcholanthrene (3MC) binds to the aryl hydrocarbon receptor (AHR) that regulates the expression of cytochrome P450 (CYP) enzymes as CYP1B1, which is involved in the oncogenic activation of environmental pollutants as well as in the estrogen biosynthesis and metabolism. 3MC was shown to induce estrogenic responses binding to the estrogen receptor (ER) α and stimulating a functional interaction between AHR and ERα. Recently, the G protein estrogen receptor (GPER) has been reported to mediate certain biological responses induced by endogenous estrogens and environmental compounds eliciting an estrogen-like activity. Methods Molecular dynamics and docking simulations were performed to evaluate the potential of 3MC to interact with GPER. SkBr3 breast cancer cells and cancer-associated fibroblasts (CAFs) derived from breast tumor patients were used as model system. Real-time PCR and western blotting analysis were performed in order to evaluate the activation of transduction mediators as well as the mRNA and protein levels of CYP1B1 and cyclin D1. Co-immunoprecipitation studies were performed in order to explore the potential of 3MC to trigger the association of GPER with AHR and EGFR. Luciferase assays were carried out to determine the activity of CYP1B1 promoter deletion constructs upon 3MC exposure, while the nuclear shuttle of AHR induced by 3MC was assessed through confocal microscopy. Cell proliferation stimulated by 3MC was determined as biological counterpart of the aforementioned experimental assays. The statistical analysis was performed by ANOVA. Results We first ascertained by docking simulations the ability of 3MC to interact with GPER. Thereafter, we established that 3MC activates the EGFR/ERK/c-Fos transduction signaling through both AHR and GPER in SkBr3 cells and CAFs. Then, we found that these receptors are involved in the up-regulation of CYP1B1 and cyclin D1 as well as in the stimulation of growth responses induced by 3MC. Conclusions In the present study we have provided novel insights regarding the molecular mechanisms by which 3MC may trigger a physical and functional interaction between AHR and GPER, leading to the stimulation of both SkBr3 breast cancer cells and CAFs. Altogether, our results indicate that 3MC may engage both GPER and AHR transduction pathways toward breast cancer progression.

Cardiac lipotoxicity is an important contributor to cardiovascular complications during obesity. Given the fundamental role of the endoplasmic reticulum (ER)-resident Selenoprotein T (SELENOT) for cardiomyocyte differentiation and protection and for the regulation of glucose metabolism, we took advantage of a small peptide (PSELT), derived from the SELENOT redox-active motif, to uncover the mechanisms through which PSELT could protect cardiomyocytes against lipotoxicity. To this aim, we modeled cardiac lipotoxicity by exposing H9c2 cardiomyocytes to palmitate (PA). The results showed that PSELT counteracted PA-induced cell death, lactate dehydrogenase release, and the accumulation of intracellular lipid droplets, while an inert form of the peptide (I-PSELT) lacking selenocysteine was not active against PA-induced cardiomyocyte death. Mechanistically, PSELT counteracted PA-induced cytosolic and mitochondrial oxidative stress and rescued SELENOT expression that was downregulated by PA through FAT/CD36 (cluster of differentiation 36/fatty acid translocase), the main transporter of fatty acids in the heart. Immunofluorescence analysis indicated that PSELT also relieved the PA-dependent increase in CD36 expression, while in SELENOT-deficient cardiomyocytes, PA exacerbated cell death, which was not mitigated by exogenous PSELT. On the other hand, PSELT improved mitochondrial respiration during PA treatment and regulated mitochondrial biogenesis and dynamics, preventing the PA-provoked decrease in PGC1-α and increase in DRP-1 and OPA-1. These findings were corroborated by transmission electron microscopy (TEM), revealing that PSELT improved the cardiomyocyte and mitochondrial ultrastructures and restored the ER network. Spectroscopic characterization indicated that PSELT significantly attenuated infrared spectral-related macromolecular changes (i.e., content of lipids, proteins, nucleic acids, and carbohydrates) and also prevented the decrease in membrane fluidity induced by PA. Our findings further delineate the biological significance of SELENOT in cardiomyocytes and indicate the potential of its mimetic PSELT as a protective agent for counteracting cardiac lipotoxicity.

Among the prognostic and predictive biomarkers of breast cancer (BC), the role of estrogen receptor (ER)α wild‐type has been acknowledged, although the action of certain ERα splice variants has not been elucidated. Insulin/insulin receptor (IR) axis has also been involved in the progression and metastasis of BC. For instance, hyperinsulinemia, which is often associated with obesity and type 2 diabetes, may be a risk factor for BC. Similarly, an aberrant expression of IR or its hyperactivation may correlate with aggressive BC phenotypes. In the present study, we have shown that a novel naturally immortalized BC cell line (named BCAHC‐1) is characterized by a unique expression of 46 kDa ERα splice variant (ERα46) along with IR. Moreover, we have shown that a multifaceted crosstalk between ERα46 and IR occurs in BCAHC‐1 cells upon estrogen and insulin exposure for growth and pulmonary metastasis. Through high‐throughput RNA sequencing analysis, we have also found that the cytokine interleukin‐11 (IL11) is the main factor linking BCAHC‐1 cells to breast cancer‐associated fibroblasts (CAFs). In particular, we have found that IL11 induced by estrogens and insulin in BCAHC‐1 cells regulates pro‐tumorigenic genes of the “extracellular matrix organization” signaling pathway, such as ICAM‐1 and ITGA5, and promotes both migratory and invasive features in breast CAFs. Overall, our results may open a new scientific avenue to identify additional prognostic and therapeutic targets in BC. –The crosstalk between ERα46 and IR signaling is involved in the growth and pulmonary metastasis of BCAHC‐1 cells. –IL11 is the most induced gene by E2 and insulin stimulation in BCAHC‐1 cells, as assessed by high‐throughput RNA sequencing analysis. –IL11 produced by BCAHC‐1 cells promotes gene expression changes and invasive features in CAFs

Two-pulse, echo-detected (ED) electron paramagnetic resonance (EPR) spectroscopy was used to study the librational motions of spin-labeled lipids in membranes of dipalmitoylphosphatidylcholine + 50 mol % cholesterol. The temperature dependence, over the range 77–240 K, and the dependence on position of spin-labeling in the sn-2 chain ( n = 5, 7, 10, 12, and 14) of the phospholipid, were characterized in detail. The experimental ED-spectra were corrected for instantaneous spin diffusion arising from static spin-spin interactions, by using spectra recorded at 77 K, where motional contributions are negligible. Simulations according to a model of rapid, small-amplitude librations about an axis whose direction is randomly distributed are able to describe the experimental spectra. Calibrations, in terms of the amplitude-correlation time product, 〈 α 2〉 τ c, were constructed for diagnostic spectral line-height ratios at different echo delay times, and for relaxation spectra obtained from the ratio of ED-spectra recorded at two different echo delays. The librational amplitude, 〈 α 2〉, was determined for a spin label at the 14-C position of the lipid chain from the partially motionally averaged hyperfine splitting in the conventional EPR spectra. The librational correlation time, τ c, which is deduced from combination of the conventional and ED-EPR results, lies in the subnanosecond regime and depends only weakly on temperature. The temperature dependence of the ED-EPR spectra arises mainly from an increase in librational amplitude with increasing temperature, and position down the lipid chain. A gradual transition takes place at higher temperatures, from a situation in which segmental torsional librations are cumulative, i.e., the contributions of the individual segments add up progressively upon going down the chain, to one of concerted motion only weakly dependent on chain position. Such librational motions are important for glass-like states and are generally relevant to high lipid packing densities, e.g., in cholesterol-containing raft domains and condensed complexes.

Using ultrasound-assisted extraction, we obtained a chlorophyll-rich extract from Opuntia ficus-indica cladodes (OFI) characterized through thin-layer chromatography (TLC), Fourier-transform infrared spectroscopy (FTIR), and spectrophotometric absorption analysis. The dye exhibited a strong fluorescence response in the visible range (400–800 nm) with a pronounced red emission when excited with a UV source. Antioxidant ability was evaluated via DPPH assay, showing an IC50 of 185 µg/mL, highlighting its potential for reactive oxygen species scavenging. The extract was incorporated into polymethyl methacrylate (PMMA), polyvinylpyrrolidone (PVP), and polyvinyl alcohol (PVA), leading to fluorescence intensity enhancements of up to 40 times compared to the dye alone depending on matrix polarity, consistent with aggregation and polarity effects. Stability tests confirmed the dye’s resistance to CO2 exposure, pH variations, and prolonged storage, positioning it as a viable alternative to synthetic fluorophores. These findings suggest that the OFI extract provides a functionally relevant, bio-derived dye platform promoting the valorization of agricultural by-products in high-value technological applications, highlighting a circular and scalable approach to developing ecofriendly fluorescent materials, aligning with sustainability and green technology goals.

Multiple sclerosis (MS) is a neurodegenerative disease of the central nervous system that can lead to long-term disability. The diagnosis of MS is not simple and requires many instrumental and clinical tests. Sampling easily collected biofluids using spectroscopic approaches is becoming of increasing interest in the medical field to integrate and improve diagnostic procedures. Here we present a statistical approach where we combine a number of spectral biomarkers derived from the ATR-FTIR spectra of blood plasma samples of healthy control subjects and MS patients, to obtain a linear predictor useful for discriminating between the two groups of individuals. This predictor provides a simple tool in which the contribution of different molecular components is summarized and, as a result, the sensitivity (80%) and specificity (93%) of the identification are significantly improved compared to those obtained with typical classification algorithms. The strategy proposed can be very helpful when applied to the diagnosis of diseases whose presence is reflected in a minimal way in the analyzed biofluids (blood and its derivatives), as it is for MS as well as for other neurological disorders.