Harvesting the Power of Green Synthesis: Gold Nanoparticles Tailored for Prostate Cancer Therapy.

Biosynthetic gold nanoparticles (bAuNPs) present a promising avenue for enhancing bio-compatibility and offering an economically and environmentally responsible alternative to traditional production methods, achieved through a reduction in the use of hazardous chemicals. While the potential of bAuNPs as anticancer agents has been explored, there is a limited body of research focusing on the crucial physicochemical conditions influencing bAuNP production. In this study, we aim to identify the optimal growth phase of Pseudomonas aeruginosa cultures that maximizes the redox potential and coordinates the formation of bAuNPs with increased efficiency. The investigation employs 2,6-dichlorophenolindophenol (DCIP) as a redox indicator. Simultaneously, we explore the impact of temperature, pH, and incubation duration on the biosynthesis of bAuNPs, with a specific emphasis on their potential application as antitumor agents. Characterization of the resulting bAuNPs is conducted using ATR-FT-IR, TEM, and UV-Vis spectroscopy. To gain insights into the anticancer potential of bAuNPs, an experimental model is employed, utilizing both non-neoplastic (HPEpiC) and neoplastic (PC3) epithelial cell lines. Notably, P. aeruginosa cultures at 9 h/OD600 = 1, combined with biosynthesis at pH 9.0 for 24 h at 58 °C, produce bAuNPs that exhibit smaller, more spherical, and less aggregated characteristics. Crucially, these nanoparticles demonstrate negligible effects on HPEpiC cells while significantly impacting PC3 cells, resulting in reduced viability, migration, and lower IL-6 levels. This research lays the groundwork for the development of more specialized, economical, and ecologically friendly treatment modalities.

Statistically sound comparison of standardized and simulation methods for oil spill source identification in real spill scenarios.

The comparison of oil patterns of a spill (Sp) and suspected spill source (SS) samples is based on ratios between correlated GC-MS signals of oil-discriminating compounds, i.e., diagnostic ratios (DR). The Student's t statistics (S-t) and a maximum relative difference (SC), proposed in standard methods, have been used for DR comparison due to their simplicity. An alternative methodology based on Monte Carlo Method (MCM) simulations of correlated signals, capable of accurately defining DR comparison criteria, proved that S-t and SC assumptions regarding DR normality and precision are frequently not valid, affecting comparison reliability. The performance of the approaches was accurately compared from independent signals of the same oil sample from a perfect match between Sp and SS. The present study describes the comparison of the approaches in real oil spill scenarios reproduced in International Round Robin Tests. Since as the number of compared DR increases, also rises the probability of not all equivalent DR being actually considered equivalent, the decision of oil pattern equivalence was based on two comparisons of independent sets of Sp and SS signals. The risk of true oil standard equivalency claims is compared for the three oil spill scenarios studied, which are different considering oil types, DR sets and spill weathering. The ability of the approaches to distinguish the Sp sample from an oil sample known not to be the source of the spill was also assessed. The MCM based on two independent DR comparison trials was the only one consistently producing fingerprint comparison risks of correct equivalence claims larger than 98 %. MCM also performed better in distinguishing different oil patterns. It was concluded that comparing >22 DR does not change the risk of correct oil pattern equivalence assessment significantly. The complexity of the MCM approach is overcome by using user-friendly and validated software.

Impact of umbilical cord mesenchymal stromal/stem cell secretome and cord blood serum in prostate cancer progression.

Prostate cancer (PCa) is the second most common malignancy in men, and the fifth leading cause of death worldwide. Mesenchymal stromal/stem cells (MSC) have been identified in PCa, although contradictory effects in malignant transformation and tumor progression have been described. Since umbilical cord (UC) MSC and cord blood serum (CBS) are rich in numerous growth and anti-inflammatory factors, UC-MSC secretome and CBS are able to modulate tumor cell proliferation and survival as well as immunity and angiogenesis. In the present study, we address this relationship and investigate the influence of UC-MSC secretome and CBS on two human PCa cell lines (PC3 and LNCaP) and a normal epithelial prostate cell line (HPEpiC). Our results disclosed that upon exposure to UC-MSC-conditioned medium or CBS, both PC3 and LNCaP cells exhibited reduced viability, proliferation, and motility while non-malignant epithelial prostate cells were unaffected. These findings were corroborated by expression analysis of AKT/PI3K signaling pathway, p53 and interleukin genes. UC-MSC and CBS factors decreased the expression of growth-stimulating AKT and PI3K effectors and simultaneously up-regulated the expression of tumor-suppressor p53. Moreover, a more anti-inflammatory expression profile was found in both malignant PCa cell lines. Altogether, these results shed light into possible mechanisms by which UC-MSC and CBS reduce PCa progression, further reinforcing their potential use as novel therapeutic agents in PCa.

Development and validation of statistically sound criteria for the match of unweathered GC-MS fingerprints in oil spill forensics.

The investigation of an oil spill's origin frequently relies on determining the equivalence of oil component patterns in samples from the contaminated environment and suspected oil source. This comparison benefits if based on the ratio of the abundance of unweathered characteristic components of the oil product, Diagnostic Ratios, DR. Replicate determinations of DR from one sample are used to set limits for the second sample's DR. The composition equivalence of oil patterns in both samples is indicated if all compared DR are statistically equivalent with a high confidence level. Some studies define DR limits assuming their normality and using Student's t statistics (S-t). However, since the ratio of correlated abundances can be not normally distributed, this criterion can drive to more false comparisons than predicted by the test confidence level. This work developed a computational tool for the reliable description of the non-normal distribution of the DR based on the Monte Carlo Method (MCM), aiming to allow the accurate control of the confidence of DR comparison. This work concluded that S-t defines 95% or 98% confidence limits with probabilities of falsely rejecting samples equivalence, φ, that can be up to 4.3% higher than predicted by the confidence level of the S-t test (i.e., 5% and 2%). The fragilities of the S-t limits significantly reduce the probability (1-θ) of two samples with the same oil producing equivalent values of all compared DR. For the studied 69 DR from unweathered components, the (1-θ) for 98% confidence level limits, set by the MCM and S-t from triplicate injections of one sample, are 94.8% and 91.7%, respectively. These values are below the confidence level (P) defined for each DR because DR are correlated with a correlation coefficient lower than 1. The (1-θ) can be increased to above P by using MCM limits and accepting composition equivalence if at least one of two sample extract injections produces values within limits set from the other sample's replicate injection. The validated user-friendly MS-Excel file used to set and access comparison criteria is made available as Supplementary Material and was checked experimentally. However, it is not feasible to estimate model confidence exclusively from experimentation because it would require too much independent analysis.

Optimisation of the uncertainty of oil spill identification from replicate comparative analyses: Comparison of standardised and novel identification methods.

Oil spill identifications involve the comparison of oil fingerprints between the oil spill and suspected oil sources, defined by ratios between the abundances of oil-discriminating compounds, Diagnostic Ratios (DR). The normalised Nordtest and EN 15522-2 methodologies use Student's t statistic (S-t) or a maximum relative difference (SC) to compare mean DR from replicate sample analysis. While the S-t method assumes the normality of DR distribution, the SC method is based on controlled DR dispersion. However, when false, the assumptions and approximations adopted can lead to low true identification rates. This work presents a novel computational tool for the statistically sound oil spill identification that allows following requirements defined by EN 15522-2, the comparison of replicate DR determinations, and the use of different DR sets and formats. The tool uses the Monte Carlo Method (MCM) to describe the probability distribution of the difference of mean DR, allowing estimating the probability of the true acceptance of fingerprints equivalence. The studied methods were applied to the comparison of signals from the same oil and to a real scenario reproduced in an International Round Robin Test. The methods were compared considering the probabilities of true acceptance of oil patterns equivalence based on a single, γ, or various, δ, DR. The MCM method performs identifications with γ equivalent to the defined confidence level for the comparison, P. Since the various DR studied are not perfectly correlated, the δ is below P. The number of replicate analyses performed and the DR considered in the comparison affect identification performance. The S-t produces comparison criteria with a γ lower than P. The SC criteria for duplicate analysis is associated with a δ lower than the obtained by the MCM. A user-friendly MS-Excel spreadsheet is available to perform oil pattern comparisons using various methods and conditions.

Glycolytic Inhibitors Potentiated the Activity of Paclitaxel and Their Nanoencapsulation Increased Their Delivery in a Lung Cancer Model.

Antiglycolytic agents inhibit cell metabolism and modify the tumor's microenvironment, affecting chemotherapy resistance mechanisms. In this work, we studied the effect of the glycolytic inhibitors 3-bromopyruvate (3BP), dichloroacetate (DCA) and 2-deoxyglucose (2DG) on cancer cell properties and on the multidrug resistance phenotype, using lung cancer cells as a model. All compounds led to the loss of cell viability, with different effects on the cell metabolism, migration and proliferation, depending on the drug and cell line assayed. DCA was the most promising compound, presenting the highest inhibitory effect on cell metabolism and proliferation. DCA treatment led to decreased glucose consumption and ATP and lactate production in both A549 and NCI-H460 cell lines. Furthermore, the DCA pretreatment sensitized the cancer cells to Paclitaxel (PTX), a conventional chemotherapeutic drug, with a 2.7-fold and a 10-fold decrease in PTX IC50 values in A549 and NCI-H460 cell lines, respectively. To increase the intracellular concentration of DCA, thereby potentiating its effect, DCA-loaded poly(lactic-co-glycolic acid) nanoparticles were produced. At higher DCA concentrations, encapsulation was found to increase its toxicity. These results may help find a new treatment strategy through combined therapy, which could open doors to new treatment approaches.

Enhanced 3T3-L1 Differentiation into Adipocytes by Pioglitazone Pharmacological Activation of Peroxisome Proliferator Activated Receptor-Gamma (PPAR-γ).

Despite the primary function of pioglitazone in antidiabetic treatment, this drug is a potent inducer of PPAR-γ, a crucial receptor that is involved in adipocyte differentiation. In this work, we propose an optimized methodology to enhance the differentiation of 3T3-L1 fibroblasts into adipocytes. This process is crucial for adipocyte secretome release, which is fundamental for understanding the molecular mechanisms that are involved in obesity for in vitro studies. To achieve this, a pioglitazone dose-response assay was determined over a range varying from 0 to 10 µM. Lipid accumulation was evaluated using Oil-Red-O. The results showed that 10 µM pioglitazone enhanced differentiation and increased secretome production. This secretome was then added into two cell lines: PC3 and RAW264.7. In the PC3 cells, an increase of aggressiveness was observed in terms of viability and proliferation, with the increase of anti-inflammatory cytokines. Conversely, in RAW264.7 cells, a reduction of viability and proliferation was observed, with a decrease in the overexpression of pro-inflammatory cytokines. Overall, the present work constitutes an improved method for adipocyte secretome production that is suitable for experimental biology studies and that could help with our understanding of the molecular mechanisms underlying adiposity influence in other cells.

Cannabidiol and Terpene Formulation Reducing SARS-CoV-2 Infectivity Tackling a Therapeutic Strategy.

In late 2019, COVID-19 emerged in Wuhan, China. Currently, it is an ongoing global health threat stressing the need for therapeutic compounds. Linking the virus life cycle and its interaction with cell receptors and internal cellular machinery is key to developing therapies based on the control of infectivity and inflammation. In this framework, we evaluate the combination of cannabidiol (CBD), as an anti-inflammatory molecule, and terpenes, by their anti-microbiological properties, in reducing SARS-CoV-2 infectivity. Our group settled six formulations combining CBD and terpenes purified from Cannabis sativa L, Origanum vulgare, and Thymus mastichina. The formulations were analyzed by HPLC and GC-MS and evaluated for virucide and antiviral potential by in vitro studies in alveolar basal epithelial, colon, kidney, and keratinocyte human cell lines. Conclusions and Impact: We demonstrate the virucide effectiveness of CBD and terpene-based formulations. F2TC reduces the infectivity by 17%, 24%, and 99% for CaCo-2, HaCat, and A549, respectively, and F1TC by 43%, 37%, and 29% for Hek293T, HaCaT, and Caco-2, respectively. To the best of our knowledge, this is the first approach that tackles the combination of CBD with a specific group of terpenes against SARS-CoV-2 in different cell lines. The differential effectiveness of formulations according to the cell line can be relevant to understanding the pattern of virus infectivity and the host inflammation response, and lead to new therapeutic strategies.