HB-EGF Plasmatic Level Contributes to the Development of Early Risk Prediction Nomogram for Severe COVID-19 Cases.

(1) Background: Heparin-Binding Epidermal Growth Factor-like Growth Factor (HB-EGF) is involved in wound healing, cardiac hypertrophy, and heart development processes. Recently, circulant HB-EGF was reported upregulated in severely hospitalized COVID-19 patients. However, the clinical correlations of HB-EGF plasma levels with COVID-19 patients' characteristics have not been defined yet. In this study, we assessed the plasma HB-EGF correlations with the clinical and paraclinical patients' data, evaluated its predictive clinical value, and built a risk prediction model for severe COVID-19 cases based on the resulting significant prognostic markers. (2) Methods: Our retrospective study enrolled 75 COVID-19 patients and 17 control cases from May 2020 to September 2020. We quantified plasma HB-EGF levels using the sandwich ELISA technique. Correlations between HB-EGF plasma levels with clinical and paraclinical patients' data were calculated using two-tailed Spearman and Point-Biserial tests. Significantly upregulated parameters for severe COVID-19 cases were identified and selected to build a multivariate logistic regression prediction model. The clinical significance of the prediction model was assessed by risk prediction nomogram and decision curve analyses. (3) Results: HB-EGF plasma levels were significantly higher in the severe COVID-19 subgroup compared to the controls (p = 0.004) and moderate cases (p = 0.037). In the severe COVID-19 group, HB-EGF correlated with age (p = 0.028), pulse (p = 0.016), dyspnea (p = 0.014) and prothrombin time (PT) (p = 0.04). The multivariate risk prediction model built on seven identified risk parameters (age p = 0.043, HB-EGF p = 0.0374, Fibrinogen p = 0.009, PT p = 0.008, Creatinine p = 0.026, D-Dimers p = 0.024 and delta miR-195 p < 0.0001) identifies severe COVID-19 with AUC = 0.9556 (p < 0.0001). The decision curve analysis revealed that the nomogram model is clinically relevant throughout a wide threshold probability range. (4) Conclusions: Upregulated HB-EGF plasma levels might serve as a prognostic factor for severe COVID-19 and help build a reliable risk prediction nomogram that improves the identification of high-risk patients at an early stage of COVID-19.

Analysis of MicroRNA-Transcription Factors Co-Regulatory Network Linking Depression and Vitamin D Deficiency.

Depression and vitamin D deficiency are often co-occurring pathologies, the common pathogenetic ground of which includes an augmented inflammatory response. However, the molecular details of this relationship remain unclear. Here, we used a bioinformatic approach to analyze GEO transcriptome datasets of major depressive disorder (MDD) and vitamin D deficiency (VDD) to identify the hub genes within the regulatory networks of commonly differentially expressed genes (DEGs). The MDD-VDD shared regulatory network contains 100 DEGs (71 upregulated and 29 downregulated), with six hub genes (PECAM1, TLR2, PTGS2, LRRK2, HCK, and IL18) all significantly upregulated, of which PTGS2 (also known as COX2) shows the highest inference score and reference count. The subsequent analysis of the miRNA-transcription factors network identified COX2, miR-146a-5p, and miR-181c-5p as key co-regulatory actors in the MDD-VDD shared molecular pathogenic mechanisms. Subsequent analysis of published MDD and VDD transcriptome data confirmed the importance of the identified hub genes, further validating our bioinformatic analytical pipeline. Our study demonstrated that PTGS2 was highly upregulated in both depressive patients and patients with low vitamin D plasma levels. Therefore, regulators targeting PTGS2, like miR-146a-5p and miR181c-5p, may have great potential in controlling both diseases simultaneously, accentuating their role in future research.

Involvement of the Expression of G Protein-Coupled Receptors in Schizophrenia.

The expression of GPCRs has been associated with schizophrenia, and their expression may induce morphological changes in brain regions responsible for schizophrenia and disease-specific behavioral changes. The articles included in this review were selected using keywords and databases of scientific research websites. The expressions of GPRs have different involvements in schizophrenia, some increase the risk while others provide protection, and they may also be potential targets for new treatments. Proper evaluation of these factors is essential to have a better therapeutic response with a lower rate of chronicity and thus improve the long-term prognosis.

Clinical Variables Influence the Ability of miR-101, miR-150, and miR-21 to Predict Ventricular Remodeling after ST-Elevation Myocardial Infarction.

Left ventricle remodeling (LVR) after acute myocardial infarction (MI) leads to impairment of both systolic and diastolic function, a significant contributor to heart failure (HF). Despite extensive research in the field, predicting post-MI LVR and HF is still a challenge. Several circulant microRNAs have been proposed as LVR predictors; however, their clinical value is controversial. Here, we used real-time quantitative PCR to quantify the plasma levels of hsa-miR-101, hsa-miR-150, and hsa-miR-21 on the first day of hospital admission of MI patients with ST-elevation (STEMI). We analyzed their correlation to the patient's clinical and paraclinical variables and evaluated their ability to discriminate between post-MI LVR and non-LVR. We show that, despite being excellent MI discriminators, none of these microRNAs can distinguish between LVR and non-LVR patients. Furthermore, we found that diabetes mellitus (DM), Hb level, and the number of erythrocytes significantly influence all three plasma microRNA levels. This suggests that plasma microRNAs' diagnostic and prognostic value in STEMI patients should be reevaluated and interpreted in the context of associated pathologies.

Plasma hsa-miR-22-3p Might Serve as an Early Predictor of Ventricular Function Recovery after ST-Elevation Acute Myocardial Infarction.

Left ventricle remodeling (LVR) after acute myocardial infarction (aMI) leads to impairment of both systolic and diastolic function, a major contributor to heart failure (HF). Despite extensive research, predicting post-aMI LVR and HF is still a challenge. Several circulant microRNAs have been proposed as LVR predictors; however, their clinical value is controversial. Here, we used real-time quantitative polymerase chain reaction (qRT-PCR) to quantify hsa-miR-22-3p (miR-22) plasma levels on the first day of hospital admission of ST-elevation aMI (STEMI) patients. We analyzed miR-22 correlation to the patients' clinical and paraclinical variables and evaluated its ability to discriminate between post-aMI LVR and non-LVR. We show that miR-22 is an excellent aMI discriminator and can distinguish between LVR and non-LVR patients. The discriminative performance of miR-22 significantly improves the predictive power of a multiple logistic regression model based on four continuous variables (baseline ejection fraction and end-diastolic volume, CK-MB, and troponin). Furthermore, we found that diabetes mellitus, hematocrit level, and the number of erythrocytes significantly influence its levels. These data suggest that miR-22 might be used as a predictor of ventricular function recovery in STEMI patients.

Plasma miR-195-5p predicts the severity of Covid-19 in hospitalized patients.

Predicting the clinical course of Covid-19 is a challenging task, given the multi-systemic character of the disease and the paucity of minimally invasive biomarkers of disease severity. Here, we evaluated the early (first two days post-admission) level of circulating hsa-miR-195-5p (miR-195, a known responder to viral infections and SARS-CoV-2 interactor) in Covid-19 patients and assessed its potential as a biomarker of disease severity. We show that plasma miR-195 correlates with several clinical and paraclinical parameters, and is an excellent discriminator between the severe and mild forms of the disease. Our Gene Ontology analysis of miR-195 targets differentially expressed in Covid-19 indicates a strong impact on cardiac mitochondria homeostasis, suggesting a possible role in long Covid and chronic fatigue syndrome (CFS) syndromes.

Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling.

Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive biomarkers for the diagnosis of PCa, as well as therapeutic targets. Mounting evidence shows that cancer cells express an altered metabolism in their early stages, making metabolomics a promising tool for the discovery of altered pathways and potential biomarker molecules. In this study, we first performed untargeted metabolomic profiling on 48 PCa plasma samples and 23 healthy controls using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-[ESI+]-MS) for the discovery of metabolites with altered profiles. Secondly, we selected five molecules (L-proline, L-tryptophan, acetylcarnitine, lysophosphatidylcholine C18:2 and spermine) for the downstream targeted metabolomics and found out that all the molecules, regardless of the PCa stage, were decreased in the PCa plasma samples when compared to the controls, making them potential biomarkers for PCa detection. Moreover, spermine, acetylcarnitine and L-tryptophan had very high diagnostic accuracy, with AUC values of 0.992, 0.923 and 0.981, respectively. Consistent with other literature findings, these altered metabolites could represent future specific and non-invasive candidate biomarkers for PCa detection, which opens novel horizons in the field of metabolomics.

The Impact of Therapeutic Plasma Exchange on Inflammatory Markers and Acute Phase Reactants in Patients with Severe SARS-CoV-2 Infection.

Background and Objectives: Due to the poor prognosis and the very high mortality rate associated with severe SARS-CoV-2 infections, various regimens have been tried to stop the evolution of the inflammatory cascade, such as immunomodulatory therapy and plasma clearance of the acute phase reactants involved. Therefore, the objective of this review was to analyze the effects of using therapeutic plasma exchange (TPE), also known as plasmapheresis, on the inflammatory markers of critically ill COVID-19 patients admitted to the intensive care unit (ICU). Materials and Methods: A thorough scientific database search was performed, and it included a review of articles published on PubMed, Cochrane Database, Scopus, and Web of Science from the beginning of the COVID-19 pandemic in March 2020 until September 2022 that focused on the treatment of SARS-CoV-2 infections using plasma exchange for patients admitted to the ICU. The current study included original articles, reviews, editorials, and short or special communications regarding the topic of interest. Results: A total of 13 articles were selected after satisfying the inclusion criterion of three or more patients enrolled with clinically severe COVID-19 that were eligible for TPE. From the included articles, it was observed that TPE was used as a last-resort salvage therapy that can be regarded as an alternative treatment method when the standard management for these patients fails. TPE significantly decreased the inflammatory status as measured by Interleukin-6 (IL-6), C-reactive protein (CRP), lymphocyte count, and D-dimers, as well as improving the clinical status measured with PaO2/FiO2 and duration of hospitalization. The pooled mortality risk reduction after TPE was 20%. Conclusions: There are sufficient studies and evidence to show that TPE reduces inflammatory mediators and improves coagulation function and the clinical/paraclinical status. Nevertheless, although it was shown that TPE decreases the severe inflammatory status without significant complications, the improvement of survival rate remains unclear.

Assessing the Outcomes of Patients with Severe SARS-CoV-2 Infection after Therapeutic Plasma Exchange by Number of TPE Sessions.

The high mortality risk in severe SARS-CoV-2 infections is tightly correlated to the extreme elevation of inflammatory markers. This acute accumulation of inflammatory proteins can be cleared using plasma exchange (TPE), commonly known as plasmapheresis, although the available data on performing TPE in COVID-19 patients is limited regarding the optimal treatment protocol. The purpose for this study was to examine the efficacy and outcomes of TPE based on different treatment methods. A thorough database search was performed to identify patients from the Intensive Care Unit (ICU) of the Clinical Hospital of Infectious Diseases and Pneumology between March 2020 and March 2022 with severe COVID-19 that underwent at least one session of TPE. A total of 65 patients satisfied the inclusion criteria and were eligible for TPE as a last resort therapy. Of these, 41 patients received 1 TPE session, 13 received 2 TPE sessions, and the remaining 11 received more than 2 TPE sessions. It was observed that IL-6, CRP, and ESR decreased significantly after all sessions were performed in all three groups, with the highest decrease of IL-6 in those who received >2 TPE sessions (from 305.5 pg/mL to 156.0 pg/mL). Interestingly, there was a significant increase in leucocyte levels after TPE, but there was no significant difference in MAP changes, SOFA score, APACHE 2 score, or the PaO2/FiO2 ratio. The ROX index was significantly higher among the patients who underwent more than two TPE sessions, with an average of 11.4, compared to 6.5 in group 1 and 7.4 in group 2, which increased significantly after TPE. Nevertheless, the mortality rate was very high (72.3%), and the Kaplan-Meier analysis identified no significant difference in survival according to the number of TPE sessions. TPE can be used as last resort salvage therapy that can be regarded as an alternative treatment method when the standard management of these patients fails. It significantly decreases the inflammatory status measured via IL-6, CRP, and WBC, as well as demonstrating an improvement of the clinical status measured via PaO2/FiO2, and duration of hospitalization. However, the survival rate does not seem to change with the number of TPE sessions. Based on the survival analysis, one session of TPE as last resort treatment in patients with severe COVID-19 proved to have the same effect as repeated TPE sessions of 2 or more.

Synthesis, Characterization, and Antiproliferative Properties of New Bio-Inspired Xanthylium Derivatives.

Xanthylium derivatives are curcumin analogs showing photochromic properties. Similarly, to anthocyanins, they follow the same multistate network of chemical species that are reversibly interconverted by external stimuli. In the present work, two new asymmetric monocarbonyl analogues of curcumin, 4-(4-hydroxy-3-metoxybenzylidene)-1,2,3,4-tetrahydroxanthylium chloride (compound 3) and 4-(4-hydroxybenzylidene)-6-methoxy-1,2,3,4-tetrahydroxanthylium chloride (compound 4) were synthesized, and their photochromic and biological properties were investigated. The UV-Vis spectroscopy and the direct and reverse pH-jumps studies confirmed the halochromic properties and the existence of different molecular species. A network of chemical reactions of these species was proposed. Furthermore, the antiproliferative properties of both compounds were evaluated using P19 murine embryocarcinoma cells and compared with each other. The results demonstrate that both new xanthylium derivatives modify the progression through the cell cycle of P19 cells, which translates into a significant antiproliferative effect. The effect of the methoxy group position is discussed and several checkpoint proteins are advanced as putative targets.

Fecal microbiota transplantation in non-communicable diseases: Recent advances and protocols.

Fecal microbiota transplant (FMT) is a therapeutic method that aims to restore normal gut microbial composition in recipients. Currently, FMT is approved in the USA to treat recurrent and refractory Clostridioides difficile infection and has been shown to have great efficacy. As such, significant research has been directed toward understanding the potential role of FMT in other conditions associated with gut microbiota dysbiosis such as obesity, type 2 diabetes mellitus, metabolic syndrome, neuropsychiatric disorders, inflammatory bowel disease, irritable bowel syndrome, decompensated cirrhosis, cancers and graft-versus-host disease. This review examines current updates and efficacy of FMT in treating conditions other than Clostridioides difficile infection. Further, protocols for administration of FMT are also discussed including storage of fecal samples in stool banks, inclusion/exclusion criteria for donors, fecal sample preparation and methods of treatment administration. Overall, understanding the mechanisms by which FMT can manipulate gut microbiota to provide therapeutic benefit as well as identifying potential adverse effects is an important step in clarifying its long-term safety and efficacy in treating multiple conditions in the future.

Efficacy of Therapeutic Plasma Exchange in Severe Acute Respiratory Distress Syndrome in COVID-19 Patients from the Western Part of Romania.

Background and Objectives: The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has surprised the medical world with its devastating effects such as severe acute respiratory distress syndrome (ARDS) and cytokine storm, but also with the scant therapeutic solutions which have proven to be effective against the disease. Therapeutic plasma exchange (TPE) has been proposed from the very beginning as a possible adjuvant treatment in severe cases. Our objective was to analyze the evolution of specific biological markers of the COVID-19 disease before and one day after a therapeutic plasma exchange session, how a change in these parameters influences the patient's respiratory status, as well as the impact of TPE on the survival rate. Materials and Methods: In this retrospective study, we include 65 patients with COVID-19 admitted to the intensive care unit department of our hospital between March 2020 and December 2021, and who received a total of 120 sessions of TPE. Results: TPE significantly reduced the following inflammation markers (p < 0.001): interleukin-6 (IL-6), C-reactive protein (CRP), lactate dehydrogenase (LDH), fibrinogen, ferritin, and erythrocyte sedimentation rate. This procedure significantly increased the number of lymphocytes and decreased D-dimers levels (p = 0.0024). TPE significantly improved the PaO2/FiO2 ratio (p < 0.001) in patients with severe acute respiratory distress syndrome (PaO2/FiO2 < 100). Survival was improved in intubated patients who received TPE. Conclusions: TPE involved the reduction in inflammatory markers in critical patients with COVID-19 disease and the improvement of the PaO2/FiO2 ratio in patients with severe ARDS and had a potential benefit on the survival of patients with extremely severe COVID-19 disease.

Identification of Genomic Variants of SARS-CoV-2 Using Nanopore Sequencing.

Background and Objectives: SARS-CoV-2 is the first global threat and life-changing event of the twenty-first century. Although efficient treatments and vaccines have been developed, due to the virus's ability to mutate in key regions of the genome, whole viral genome sequencing is needed for efficient monitoring, evaluation of the spread, and even the adjustment of the molecular diagnostic assays. Materials and Methods: In this study, Nanopore and Ion Torrent sequencing technologies were used to detect the main SARS-CoV-2 circulating strains in Timis County, Romania, between February 2021 and May 2022. Results: We identified 22 virus lineages belonging to seven clades: 20A, 20I (Alpha, V1), 21B (Kappa), 21I (Delta), 21J (Delta), 21K (Omicron), and 21L (Omicron). Conclusions: Results obtained with both methods are comparable, and we confirm the utility of Nanopore sequencing in large-scale epidemiological surveillance due to the lower cost and reduced time for library preparation.

The Use of Biopolymers as a Natural Matrix for Incorporation of Essential Oils of Medicinal Plants.

The benefits of using biopolymers for the development of films and coatings are well known. The enrichment of these material properties through various natural additions has led to their applicability in various fields. Essential oils, which are well-known for their beneficial properties, are widely used as encapsulating agents in films based on biopolymers. In this study, we developed biopolymer-based films and tested their properties following the addition of 7.5% and 15% (w/v) essential oils of lemon, orange, grapefruit, cinnamon, clove, chamomile, ginger, eucalyptus or mint. The samples were tested immediately after development and after one year of storage in order to examine possible long-term property changes. All films showed reductions in mass, thickness and microstructure, as well as mechanical properties. The most considerable variations in physical properties were observed in the 7.5% lemon oil sample and the 15% grapefruit oil sample, with the largest reductions in mass (23.13%), thickness (from 109.67 µm to 81.67 µm) and density (from 0.75 g/cm3 to 0.43 g/cm3). However, the microstructure of the sample was considerably improved. Although the addition of lemon essential oil prevented the reduction in mass during the storage period, it favored the degradation of the microstructure and the loss of elasticity (from 16.7% to 1.51% for the sample with 7.5% lemon EO and from 18.28% to 1.91% for the sample with 15% lemon EO). Although the addition of essential oils of mint and ginger resulted in films with a more homogeneous microstructure, the increase in concentration favored the appearance of pores and modifications of color parameters. With the exception of films with added orange, cinnamon and clove EOs, the antioxidant capacity of the films decreased during storage. The most obvious variations were identified in the samples with lemon, mint and clove EOs. The most unstable samples were those with added ginger (95.01%), lemon (92%) and mint (90.22%).

Gene network analysis of the transcriptome impact of methylated microRNAs on oral squamous cell carcinoma.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is one of the most common head and neck squamous cell tumors. MicroRNAs and DNA methylation, as epigenetic mechanisms, regulate the expression of oncogenes and tumor suppressor genes, contributing to the carcinogenic development. However, the current knowledge on the genetic and epigenetic landscape of OSCC is still limited. OBJECTIVES: To assess the transcriptomic impact of microRNAs found to be methylated through Infinium genome-wide methylation profiling of archived OSCC tissues, and to analyze their biological role using gene network analysis. MATERIAL AND METHODS: We used the Infinium array-based methylation assay to assess the genome-wide methylation status at the single-CpG-site level of DNA purified from archived OSCC tissue samples. After quality control, filtering out poorly performing probes and normalization of data, we identified the differentially methylated microRNA loci. We performed a literature-based analysis of OSCC transcriptomic data to identify the predicted target genes for each microRNA, followed by individual network and pathway enrichment analyses. RESULTS: The analysis of Infinium methylation array data revealed 1469 differentially hypomethylated loci, 4 of which were of interest, namely hsa-microRNA-124-3, hsa-microRNA-24-1, hsa-microRNA-769, and hsa-microRNA-4500. Network and pathway enrichment analyses revealed multiple pathways modulated through DNA methylation-microRNA expression axes. CONCLUSIONS: We describe the transcriptomic impact of 4 differentially methylated microRNAs in OSCC tissues samples and discuss their role in the pathology of OSCC. These results may contribute to a better understanding of how epigenetic mechanisms such as DNA methylation and microRNAs cooperate to impact the development of OSCC.

Gene Network Analysis of the Transcriptome Impact of SARS-CoV-2 Interacting MicroRNAs in COVID-19 Disease.

According to the World Health Organization (WHO), as of June 2022, over 536 million confirmed COVID-19 disease cases and over 6.3 million deaths had been globally reported. COVID-19 is a multiorgan disease involving multiple intricated pathological mechanisms translated into clinical, biochemical, and molecular changes, including microRNAs. MicroRNAs are essential post-transcriptional regulators of gene expression, being involved in the modulation of most biological processes. In this study, we characterized the biological impact of SARS-CoV-2 interacting microRNAs differentially expressed in COVID-19 disease by analyzing their impact on five distinct tissue transcriptomes. To this end, we identified the microRNAs' predicted targets within the list of differentially expressed genes (DEGs) in tissues affected by high loads of SARS-CoV-2 virus. Next, we submitted the tissue-specific lists of the predicted microRNA-targeted DEGs to gene network functional enrichment analysis. Our data show that the upregulated microRNAs control processes such as mitochondrial respiration and cytokine and cell surface receptor signaling pathways in the heart, lymph node, and kidneys. In contrast, downregulated microRNAs are primarily involved in processes related to the mitotic cell cycle in the heart, lung, and kidneys. Our study provides the first exploratory, systematic look into the biological impact of the microRNAs associated with COVID-19, providing a new perspective for understanding its multiorgan physiopathology.

Diagnostic Value of microRNA-375 as Future Biomarker for Prostate Cancer Detection: A Meta-Analysis.

Background and Objectives: Responding to the need for additional biomarkers for the diagnosis of prostate cancer (PCa), mounting studies show that microRNAs (miRNAs/miRs) possess great potential as future promising diagnostic tools. However, the usefulness of these miRNAs is still highly debated, as the degree of inconsistency between study designs and results is still elevated. Herein, we present a meta-analysis evaluating the diagnostic value and accuracy of circulating miR-375, as it is one of the most studied types of miRs in PCa. Materials and Methods: The diagnostic accuracy of miR-375 was evaluated using the QUADAS-2 tool, analyzing different statistical parameters. The seven studies (from six articles) that matched our selection included 422 PCa patients and 212 controls (70 healthy volunteers + 142 with benign prostate diseases). Results and Conclusion: We obtained a p-value of 0.76 for sensitivity, 0.83 for specificity, 16 for DOR, 4.6 for LR+, 0.29 for LR-, and 0.87 for AUC (95% CI 0.83-0.89). Our results confirm that miRNA-375 has high diagnostic potential for PCa, suggesting its usefulness as a powerful biomarker. More comprehensive studies are warranted to better assess its true value as a diagnostic biomarker for this urologic disease.

MicroRNAs-The Heart of Post-Myocardial Infarction Remodeling.

Myocardial infarction (MI) is one of the most frequent cardiac emergencies, with significant potential for mortality. One of the major challenges of the post-MI healing response is that replacement fibrosis could lead to left ventricular remodeling (LVR) and heart failure (HF). This process involves canonical and non-canonical transforming growth factor-beta (TGF-ß) signaling pathways translating into an intricate activation of cardiac fibroblasts and disproportionate collagen synthesis. Accumulating evidence has indicated that microRNAs (miRNAs) significantly contribute to the modulation of these signaling pathways. This review summarizes the recent updates regarding the molecular mechanisms underlying the role of the over 30 miRNAs involved in post-MI LVR. In addition, we compare the contradictory roles of several multifunctional miRNAs and highlight their potential use in pressure overload and ischemia-induced fibrosis. Finally, we discuss their attractive role as prognostic biomarkers for HF, highlighting the most relevant human trials involving these miRNAs.

Plasma hsa-mir-19b is a potential LevoDopa therapy marker.

Parkinson's disease (PD) is the second most common neurodegenerative disorder among the elderly, the diagnostic and prognostic of which is based mostly on clinical signs. LevoDopa replacement is the gold standard therapy for PD, as it ameliorates the motor symptoms. However, it does not affect the progression of the disease and its long-term use triggers severe complications. There are no bona fide biomarkers for monitoring the patients' response to LevoDopa and predicting the efficacy of levodopa treatment. Here, we have combined qPCR microRNA array screening with analysis of validated miRs in naïve versus Levodopa-treated PD patients. We have identified plasma miR-19b as a possible biomarker for LevoDopa therapy and validated this result in human differentiated dopaminergic neurons exposed to LevoDopa. In silico analysis suggests that the LevoDopa-induced miR-19b regulates ubiquitin-mediated proteolysis.

Long Noncoding RNA NEAT1 as a Potential Candidate Biomarker for Prostate Cancer.

Background: Prostate cancer (PCa) remains one of the leading causes of cancer-related mortality in men worldwide, mainly due to unsatisfactory diagnostic methods used at present, which lead to overdiagnosis, unnecessary biopsies and treatment, or misdiagnosis in early asymptomatic stages. New diagnostic biomarkers are needed for a correct and early diagnosis. Long noncoding RNAs (lncRNAs) have been broadly studied for their involvement in PCa biology, as well as for their potential role as diagnostic biomarkers. Methods: We conducted lncRNA profiling in plasma and microdissected formalin-fixed paraffin-embedded (FFPE) tissues of PCa patients and attempted validation for commonly dysregulated individual lncRNAs. Results: Plasma profiling revealed eight dysregulated lncRNAs, while microarray analysis revealed 717 significantly dysregulated lncRNAs, out of which only nuclear-enriched abundant transcript 1 (NEAT1) was commonly upregulated in plasma samples and FFPE tissues. NEAT1's individual validation revealed statistically significant upregulation (FC = 2.101, p = 0.009). Receiver operating characteristic (ROC) analysis showed an area under the curve (AUC) value of 0.7298 for NEAT1 (95% CI = 0.5812-0.8785), suggesting a relatively high diagnostic value, thus having a potential biomarker role for this malignancy. Conclusions: We present herein data suggesting that NEAT1 could serve as a diagnostic biomarker for PCa. Additional studies of larger cohorts are needed to confirm our findings, as well as the oncogenic mechanism of NEAT1 in the development of PCa.