Melasma and reflectance confocal microscopy: from baseline to treatment monitoring.

Melasma is a frequent condition worldwide, and it represents one of the most challenging disorders to treat in cosmetic dermatology. One of the critical factors for treatment prognosis is the assessment of the depth and distribution of pigment within the hyperpigmented area. Nowadays, non-invasive skin imaging techniques, such as reflectance confocal microscopy (RCM), have been used to estimate pigment distribution and depth within different skin layers. This article aims to provide a systematic review of RCM applications in melasma, providing terminology and investigating characteristics of melasma at baseline and after medical and laser treatment. Our results support the recognition of two main types of melasma, epidermal and mixed type, thanks to the role of RCM in highlighting the precise pigment depth location in the skin non-invasively. RCM treatment monitoring enables the objectification of pigment variations after treatment and the identification of prognostic factors for different treatment modalities. After the era of the application of RCM as a technique applied strictly to skin cancers, additional cosmetic applications are emerging, such as the application of melasma treatment monitoring.

Incidental thyroid carcinoma in an endemic goiter area in Italy: histopathological features and predictors of a common finding.

PURPOSE: The occurrence and histopathological features of incidental thyroid carcinoma (ITC) vary considerably among populations from different geographical regions. The aim of this study is to assess the prevalence and histopathological characteristics of ITC in patients who underwent thyroid surgery for apparently benign thyroid diseases in an endemic goiter area in Italy. METHODS: A total of 649 consecutive patients (531 females and 118 males; mean age, 52.9 ± 11.0 years), who underwent thyroid surgery at the Endocrine Surgery Unit of the tertiary care "Renato Dulbecco" University Hospital (Catanzaro, Italy) in the period between years 2017 and 2022, were included in this retrospective study. A comprehensive histopathological examination was performed on surgically excised thyroid tissue. Logistic regression analysis was employed to identify potential predictors of ITC. RESULTS: The histopathological examination revealed the presence of ITC in 81 patients, accounting for 12.5% of the total study population. The female to male ratio was found to be 6.4 to 1. Among the patients with ITC, 72 had papillary carcinoma (PTC), with 53 of these tumors being microcarcinomas (microPTC). Additionally, 5 patients had follicular thyroid carcinoma, 2 patients had low-risk follicular cell-derived thyroid neoplasms, 1 patient had an oncocytic carcinoma, and 1 patient had a medullary thyroid carcinoma. Logistic regression analysis demonstrated a significant association between female sex and incidental microPTC. CONCLUSIONS: These findings provide further evidence of the common occurrence of ITC, typically in the form of microPTC, among individuals who undergo thyroid surgery for apparently benign thyroid diseases.

Coexistence of Hashimoto's Thyroiditis in Differentiated Thyroid Cancer: Post-Operative Monitoring of Anti-Thyroglobulin Antibodies and Assessment of Treatment Response.

INTRODUCTION: Differentiated thyroid carcinoma (DTC) is frequently found in conjunction with autoimmune thyroid disorders, particularly Hashimoto's thyroiditis (HT). This study investigates the impact of coexisting HT on the persistence of an indeterminate response to therapy due to positive anti-thyroglobulin antibodies (AbTg), measured via competitive immunoassay, in a consecutive patient series from Calabria, Southern Italy. METHODS: This retrospective longitudinal study analyzed 259 consecutive DTC patients managed at the Endocrinology Unit of Renato Dulbecco Hospital (Catanzaro, Italy) up to 2023. Patients with medullary and undifferentiated thyroid carcinoma, partial thyroidectomy, less than six months of post-operative monitoring, or missing clinical data were excluded. Demographic information, histological findings, initial tumor stage, and ATA risk category were collected. The response to therapy was assessed based on ATA guidelines. RESULTS: Among the 259 patients, 29% had coexisting HT. Patients with HT exhibited distinct characteristics: a higher proportion of females (87.0% vs. 74.7%), a shorter post-operative monitoring duration (median 3 vs. 5 years), and a higher prevalence of papillary thyroid carcinoma (PTC) (97.4% vs. 86.3%). The tumor size, lymph node involvement, and distant metastasis were similar between the groups, with patients without HT having a higher incidence of extrathyroidal tumor extension. However, the initial TNM stage and ATA risk category did not differ significantly. At the six-month follow-up, HT patients showed a higher rate of indeterminate responses, primarily due to positive AbTg. After 12 months, the response categories aligned, with decreasing AbTg levels in the HT group. After 24 months, most patients with long-term follow-up demonstrated an excellent response to DTC therapy, irrespective of HT coexistence. CONCLUSIONS: While HT does not worsen DTC prognosis, it may result in indeterminate responses. AbTg measurements in the peri-operative period should be encouraged to facilitate post-operative monitoring, emphasizing the importance of using standardized assays. Further research in larger populations with extended follow-up is needed to comprehensively understand the HT-DTC relationship.

An Explainable Radiogenomic Framework to Predict Mutational Status of KRAS and EGFR in Lung Adenocarcinoma Patients.

The complex pathobiology of lung cancer, and its spread worldwide, has prompted research studies that combine radiomic and genomic approaches. Indeed, the early identification of genetic alterations and driver mutations affecting the tumor is fundamental for correctly formulating the prognosis and therapeutic response. In this work, we propose a radiogenomic workflow to detect the presence of KRAS and EGFR mutations using radiomic features extracted from computed tomography images of patients affected by lung adenocarcinoma. To this aim, we investigated several feature selection algorithms to identify the most significant and uncorrelated sets of radiomic features and different classification models to reveal the mutational status. Then, we employed the SHAP (SHapley Additive exPlanations) technique to increase the understanding of the contribution given by specific radiomic features to the identification of the investigated mutations. Two cohorts of patients with lung adenocarcinoma were used for the study. The first one, obtained from the Cancer Imaging Archive (TCIA), consisted of 60 cases (25% EGFR, 23% KRAS); the second one, provided by the Azienda Ospedaliero-Universitaria 'Ospedali Riuniti' of Foggia, was composed of 55 cases (16% EGFR, 28% KRAS). The best-performing models proposed in our study achieved an AUC of 0.69 and 0.82 on the validation set for predicting the mutational status of EGFR and KRAS, respectively. The Multi-layer Perceptron model emerged as the top-performing model for both oncogenes, in some cases outperforming the state of the art. This study showed that radiomic features can be associated with EGFR and KRAS mutational status in patients with lung adenocarcinoma.

Prediction of gastrointestinal cancers in the ONCONUT cohort study: comparison between logistic regression and artificial neural network.

Background: Artificial neural networks (ANNs) and logistic regression (LR) are the models of chosen in many medical data classification tasks. Several published articles were based on summarizing the differences and similarities of these models from a technical point of view and critically assessing the quality of the models. The aim of this study was to compare ANN and LR the statistical techniques to predict gastrointestinal cancer in an elderly cohort in Southern Italy (ONCONUT study). Method: In 1992, ONCONUT was started with the aim of evaluating the relationship between diet and cancer development in a Southern Italian elderly population. Patients with gastrointestinal cancer (ICD-10 from 150.0 to 159.9) were included in the study (n = 3,545). Results: This cohort was used to train and test the ANN and LR. LR was evaluated separately for macro- and micronutrients, and the accuracy was evaluated based on true positives and true negatives versus the total (97.15%). Then, ANN was trained and the accuracy was evaluated (96.61% for macronutrients and 97.06% for micronutrients). To further investigate the classification capabilities of ANN, k-fold cross-validation and genetic algorithm (GA) were used after balancing the dataset among classes. Conclusions: Both LR and ANN had high accuracy and similar performance. Both models had the potential to be used as decision clinical support integrated into clinical practice, because in many circumstances, the use of a simple LR model was likely to be adequate for real-world needs, but in others in which there were large amounts of data, the application of advanced analytic tools such as ANNs could be indicated, and the GA optimizer needed to optimize the accuracy of ANN.

The role of unpaired image-to-image translation for stain color normalization in colorectal cancer histology classification.

BACKGROUND: Histological assessment of colorectal cancer (CRC) tissue is a crucial and demanding task for pathologists. Unfortunately, manual annotation by trained specialists is a burdensome operation, which suffers from problems like intra- and inter-pathologist variability. Computational models are revolutionizing the Digital Pathology field, offering reliable and fast approaches for challenges like tissue segmentation and classification. With this respect, an important obstacle to overcome consists in stain color variations among different laboratories, which can decrease the performance of classifiers. In this work, we investigated the role of Unpaired Image-to-Image Translation (UI2IT) models for stain color normalization in CRC histology and compared to classical normalization techniques for Hematoxylin-Eosin (H&E) images. METHODS: Five Deep Learning normalization models based on Generative Adversarial Networks (GANs) belonging to the UI2IT paradigm have been thoroughly compared to realize a robust stain color normalization pipeline. To avoid the need for training a style transfer GAN between each pair of data domains, in this paper we introduce the concept of training by exploiting a meta-domain, which contains data coming from a wide variety of laboratories. The proposed framework enables a huge saving in terms of training time, by allowing to train a single image normalization model for a target laboratory. To prove the applicability of the proposed workflow in the clinical practice, we conceived a novel perceptive quality measure, which we defined as Pathologist Perceptive Quality (PPQ). The second stage involved the classification of tissue types in CRC histology, where deep features extracted from Convolutional Neural Networks have been exploited to realize a Computer-Aided Diagnosis system based on a Support Vector Machine (SVM). To prove the reliability of the system on new data, an external validation set composed of N = 15,857 tiles has been collected at IRCCS Istituto Tumori "Giovanni Paolo II". RESULTS: The exploitation of a meta-domain consented to train normalization models that allowed achieving better classification results than normalization models explicitly trained on the source domain. PPQ metric has been found correlated to quality of distributions (Fréchet Inception Distance - FID) and to similarity of the transformed image to the original one (Learned Perceptual Image Patch Similarity - LPIPS), thus showing that GAN quality measures introduced in natural image processing tasks can be linked to pathologist evaluation of H&E images. Furthermore, FID has been found correlated to accuracies of the downstream classifiers. The SVM trained on DenseNet201 features allowed to obtain the highest classification results in all configurations. The normalization method based on the fast variant of CUT (Contrastive Unpaired Translation), FastCUT, trained with the meta-domain paradigm, allowed to achieve the best classification result for the downstream task and, correspondingly, showed the highest FID on the classification dataset. CONCLUSIONS: Stain color normalization is a difficult but fundamental problem in the histopathological setting. Several measures should be considered for properly assessing normalization methods, so that they can be introduced in the clinical practice. UI2IT frameworks offer a powerful and effective way to perform the normalization process, providing realistic images with proper colorization, unlike traditional normalization methods that introduce color artifacts. By adopting the proposed meta-domain framework, the training time can be reduced, and the accuracy of downstream classifiers can be increased.

The anticancer effects of Metformin in the male germ tumor SEM-1 cell line are mediated by HMGA1.

Introduction: Germ cell tumors (GCTs) are the most common type of cancer in young men. These tumors usually originate from the testis, but they can occasionally develop from extragonadal sites probably due to primordial germ cells (PGCs) migration errors. Cisplatin-based chemotherapy is usually effective for male GCTs, but the risk of toxicity is high and new therapeutic strategies are needed. Although Metformin (Met) has been widely studied as a potential cancer treatment over the past decades, there is limited evidence to support its use in treating male GCTs. Additionally, the mechanism by which it acts on tumor cells is still not entirely understood. Methods: SEM-1 cells, a newly established human cell line of extragonadal origin, were treated with Met. Cell viability was studied by MTT assay, while cell migration and invasion were studied by the wound healing assay and the transwell assay, respectively. The effect of Met on 3D spheroid formation was determined by seeding SEM-1 cells in appropriate cell suspension culture conditions, and cell cycle was characterized by flow cytometry. Factors involved in PGCs migration and GCT invasion, such as IGFBP1, IGF1R, MMP-11 and c-Kit, together with cyclin D1 (a key regulator of cell cycle progression), and the upstream factor, HMGA1, were determined by immunoblots. Results: Treatment of SEM-1 cells with Met resulted in a potent and dose-dependent reduction of cell proliferation, as evidenced by decreased nuclear abundance of cyclin D1 and cell cycle arrest in G1 phase. Also, Met prevented the formation of 3D spheroids, and blocked cell migration and invasion by reducing the expression of IGFBP1, IGF1R and MMP-11. Both, IGFBP1 and MMP-11 are under control of HMGA1, a chromatin-associated protein that is involved in the regulation of important oncogenic, metabolic and embryological processes. Intriguingly, an early reduction in the nuclear abundance of HMGA1 occurred in SEM-1 cells treated with Met. Conclusions: Our results document the antiproliferative and antimigratory effects of Met in SEM-1 cells, providing new insights into the potential treatments for male GCTs. The anticancer properties of Met in SEM-1 cells are likely related to its ability to interfere with HMGA1 and downstream targets, including cyclin D1, the IGFs system, and MMP-11.

NDG-CAM: Nuclei Detection in Histopathology Images with Semantic Segmentation Networks and Grad-CAM.

Nuclei identification is a fundamental task in many areas of biomedical image analysis related to computational pathology applications. Nowadays, deep learning is the primary approach by which to segment the nuclei, but accuracy is closely linked to the amount of histological ground truth data for training. In addition, it is known that most of the hematoxylin and eosin (H&E)-stained microscopy nuclei images contain complex and irregular visual characteristics. Moreover, conventional semantic segmentation architectures grounded on convolutional neural networks (CNNs) are unable to recognize distinct overlapping and clustered nuclei. To overcome these problems, we present an innovative method based on gradient-weighted class activation mapping (Grad-CAM) saliency maps for image segmentation. The proposed solution is comprised of two steps. The first is the semantic segmentation obtained by the use of a CNN; then, the detection step is based on the calculation of local maxima of the Grad-CAM analysis evaluated on the nucleus class, allowing us to determine the positions of the nuclei centroids. This approach, which we denote as NDG-CAM, has performance in line with state-of-the-art methods, especially in isolating the different nuclei instances, and can be generalized for different organs and tissues. Experimental results demonstrated a precision of 0.833, recall of 0.815 and a Dice coefficient of 0.824 on the publicly available validation set. When used in combined mode with instance segmentation architectures such as Mask R-CNN, the method manages to surpass state-of-the-art approaches, with precision of 0.838, recall of 0.934 and a Dice coefficient of 0.884. Furthermore, performance on the external, locally collected validation set, with a Dice coefficient of 0.914 for the combined model, shows the generalization capability of the implemented pipeline, which has the ability to detect nuclei not only related to tumor or normal epithelium but also to other cytotypes.

A Fusion Biopsy Framework for Prostate Cancer Based on Deformable Superellipses and nnU-Net.

In prostate cancer, fusion biopsy, which couples magnetic resonance imaging (MRI) with transrectal ultrasound (TRUS), poses the basis for targeted biopsy by allowing the comparison of information coming from both imaging modalities at the same time. Compared with the standard clinical procedure, it provides a less invasive option for the patients and increases the likelihood of sampling cancerous tissue regions for the subsequent pathology analyses. As a prerequisite to image fusion, segmentation must be achieved from both MRI and TRUS domains. The automatic contour delineation of the prostate gland from TRUS images is a challenging task due to several factors including unclear boundaries, speckle noise, and the variety of prostate anatomical shapes. Automatic methodologies, such as those based on deep learning, require a huge quantity of training data to achieve satisfactory results. In this paper, the authors propose a novel optimization formulation to find the best superellipse, a deformable model that can accurately represent the prostate shape. The advantage of the proposed approach is that it does not require extensive annotations, and can be used independently of the specific transducer employed during prostate biopsies. Moreover, in order to show the clinical applicability of the method, this study also presents a module for the automatic segmentation of the prostate gland from MRI, exploiting the nnU-Net framework. Lastly, segmented contours from both imaging domains are fused with a customized registration algorithm in order to create a tool that can help the physician to perform a targeted prostate biopsy by interacting with the graphical user interface.

Oleuropein Counteracts Both the Proliferation and Migration of Intra- and Extragonadal Seminoma Cells.

Recent and growing literature has reported that oleuropein (OLE), the main polyphenol in olive leaf extract, inhibits tumor cell proliferation and reduces the invasiveness properties of cancer cells; therefore, OLE may play a significant role in the development of new drugs for cancer treatment. These antineoplastic properties have been reported in many experimental cancer models, but the effect of OLE on seminoma cells is yet to be evaluated. In the present study, we demonstrate, for the first time, that OLE reduces cell viability in both intra- and extragonadal TCAM-2 and SEM-1 seminoma cells, respectively, in a dose-dependent manner. As shown by Western-blot analysis, OLE exposure reduced cyclin-D1 expression and upregulated p21Cip/WAF1, concomitantly affecting the upstream pathway of NF-κB, leading to the reduction of its nuclear content, thereby suggesting that OLE could modulate cell-cycle regulators by inhibiting NF-κB. Moreover, Annexin V staining revealed that OLE induced apoptosis in cancer cells and upregulated the pro-apoptotic factor BAX. Through wound-healing scratch and transmigration assays, we also demonstrated that OLE significantly reduced the migration and motility of TCAM-2 and SEM-1 cells, and downregulated the expression of TGFß-1, which is known to be the main pro-fibrotic factor involved in the acquisition of the migratory and invasive properties of cancer cells. Collectively, our results indicate that OLE reduces seminoma cell proliferation, promotes apoptosis, and counteracts cell migration and motility. Further studies are needed to explore the molecular mechanisms underlying these observed effects.

Movement observation activates motor cortex in fibromyalgia patients: a fNIRS study.

Scientific evidence points to a shared neural representation between performing and observing an action. The action observation notoriously determines a modulation of the observer's sensorimotor system, a phenomenon called Motor Resonance (MR). Fibromyalgia (FM) patients suffer from a condition characterized by generalized musculoskeletal pain in which even simple movement can exacerbate their symptoms. Maladaptive functioning of the primary motor cortex is a common finding in patients with chronic pain. Activation of the motor cortex is known to induce an analgesic effect in patients with chronic pain. In this exploratory study, we intend to verify if the mere observation of a movement could elicit activation of the motor cortical areas in patients with FM. Therefore, the purpose of this study was to examine the presence of MR in patients affected by fibromyalgia. We adopted a behavioral paradigm known for detecting the presence of MR and a neurophysiological experiment. Participants watched videos showing gripping movements towards a graspable or an ungraspable object, respectively, and were asked to press a button the instant the agent touched the object (Time-to-contact detection session). In a different experimental session, participants were only requested to observe and pay attention to the videos (Observation-only session). During each experimental session, the participants' cerebral hemodynamic activity was recorded using the functional Near-Infrared Spectroscopy method. The behavioral task analysis revealed the presence of MR in both FM patients and healthy controls. Moreover, neurophysiological findings suggested that the observation of movement during the Observation-only session provoked activation and modulation of the cortical motor networks of FM patients. These results could represent evidence of the possible beneficial effects of movement observation in restarting motor activation, notoriously reduced, in FM patients.

Identification of glomerulosclerosis using IBM Watson and shallow neural networks.

BACKGROUND: Advanced stages of different renal diseases feature glomerular sclerosis at a histological level which is observed by light microscopy on tissue samples obtained by performing a kidney biopsy. Computer-aided diagnosis (CAD) systems leverage the potential of artificial intelligence (AI) in healthcare to support physicians in the diagnostic process. METHODS: We propose a novel CAD system that processes histological images and discriminates between sclerotic and non-sclerotic glomeruli. To this goal, we designed, tested, and compared two artificial neural network (ANN) classifiers. The former implements a shallow ANN classifying hand-crafted features extracted from Regions of Interest (ROIs) by means of image-processing procedures. The latter, instead, employs the IBM Watson Visual Recognition System, which uses a deep artificial neural network making decisions taking the images as input, without the need to design any procedure for describing images with features. The input dataset consisted of 428 sclerotic glomeruli and 2344 non-sclerotic glomeruli derived from images of kidney biopsies scanned by the Aperio ScanScope System. RESULTS: Both AI approaches allowed to very accurately distinguish (mean MCC 0.95 and mean Accuracy 0.99) between sclerotic and non-sclerotic glomeruli. Although the systems may seem interchangeable, the approach based on feature extraction and classification would allow clinicians to gain information on the most discriminating features. In fact, further procedures could explain the classifier's decision by analysing which subset of features impacted the most on the final decision. CONCLUSIONS: We developed a customizable support system that can facilitate the work of renal pathologists both in clinical and research settings.

A neural network for glomerulus classification based on histological images of kidney biopsy.

BACKGROUND: Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results. CAD systems play an important role in digital pathology supporting pathologists in analyzing biopsy slides by means of standardized and objective workflows. In the proposed work, we designed and tested a novel CAD system module based on image processing techniques and machine learning, whose objective was to classify the condition affecting renal corpuscles (glomeruli) between sclerotic and non-sclerotic. Such discrimination is useful for the biopsy slides evaluation performed by pathologists. RESULTS: We collected 26 digital slides taken from the kidneys of 19 donors with Periodic Acid-Schiff staining. Expert pathologists have conducted the slides preparation, digital acquisition and glomeruli annotations. Before setting the classifiers, we evaluated several feature extraction techniques from the annotated regions. Then, a feature reduction procedure followed by a shallow artificial neural network allowed discriminating between the glomeruli classes. We evaluated the workflow considering an independent dataset (i.e., processing images not used in the training procedure). Ten independent runs of the training algorithm, and evaluation, allowed achieving MCC and Accuracy of 0.95 (± 0.01) and 0.99 (standard deviation < 0.00), respectively. We also obtained good precision (0.9844 ± 0.0111) and recall (0.9310 ± 0.0153). CONCLUSIONS: Results on the test set confirm that the proposed workflow is consistent and reliable for the investigated domain, and it can support the clinical practice of discriminating the two classes of glomeruli. Analyses on misclassifications show that the involved images are usually affected by staining artefacts or present partial sections due to slice preparation and staining processes. In clinical practice, however, pathologists discard images showing such artefacts.

Insulin Resistance and Cancer: In Search for a Causal Link.

Insulin resistance (IR) is a condition which refers to individuals whose cells and tissues become insensitive to the peptide hormone, insulin. Over the recent years, a wealth of data has made it clear that a synergistic relationship exists between IR, type 2 diabetes mellitus, and cancer. Although the underlying mechanism(s) for this association remain unclear, it is well established that hyperinsulinemia, a hallmark of IR, may play a role in tumorigenesis. On the other hand, IR is strongly associated with visceral adiposity dysfunction and systemic inflammation, two conditions which favor the establishment of a pro-tumorigenic environment. Similarly, epigenetic modifications, such as DNA methylation, histone modifications, and non-coding RNA, in IR states, have been often associated with tumorigenesis in numerous types of human cancer. In addition to these observations, it is also broadly accepted that gut microbiota may play an intriguing role in the development of IR-related diseases, including type 2 diabetes and cancer, whereas potential chemopreventive properties have been attributed to some of the most commonly used antidiabetic medications. Herein we provide a concise overview of the most recent literature in this field and discuss how different but interrelated molecular pathways may impact on tumor development.

Overexpression of p75NTR in Human Seminoma: A New Biomarker?

Several studies have demonstrated that the p75NTR low-affinity receptor of Nerve Growth Factor (NGF), is produced in abnormally large amounts in several human cancer types. However, the role of p75NTR varies substantially depending on cell context, so that a dual role of this receptor protein in tumor cell survival and invasion, as well as cell death, has been supported in recent studies. Herein we explored for the first time the expression of p75NTR in human specimens (nr = 40) from testicular germ cell tumors (TGCTs), mostly seminomas. Nuclear overexpression of p75NTR was detected by immunohistochemistry in seminoma tissue as compared to normal tissue, whereas neither NGF nor its high-affinity TrkA receptor was detected. An increased nuclear staining of phospho-JNK, belonging to the p75NTR signaling pathway and its pro-apoptotic target gene, p53, was concomitantly observed. Interestingly, our analysis revealed that decreased expression frequency of p75NTR, p-JNK and p53 was related to staging progression, thus suggesting that p75NTR may represent a specific marker for seminoma and staging in TGCTs.

Methods to Study Protein-Binding to Pseudogene Transcripts.

One of the most commonly described biological feature of processed pseudogenes is the ability to influence the expression of their parental coding genes. As evidenced in several studies, the high sequence similarity between these RNA pairs sets up a certain level of competition for posttranscriptional regulators, including, among others, RNA-binding proteins (RBPs). RBPs may affect, positively or negatively, the stability of bound mRNAs, so that, if an overexpressed pseudogene competes with its homologous coding gene, the downstream protein synthesis would change, with potential pathological consequences. Given these premises, a rigorous and comprehensive understanding of interactions between pseudogene-parental gene RNA pairs and RBPs could provide further insights into the biological bases of complex diseases, such as cancer, cardiovascular disease, and type 2 diabetes, identifying novel predictive and/or prognostic biomarkers.Herein, we detail easily adaptable protocols of plasmid-based molecular cloning and RNA-electrophoretic mobility shift assay (EMSA) used in our laboratory for determining the interaction between a cytoplasmatic stabilizing protein (αCP1) and the pseudogene-parental gene RNA pair HMGA1-p /HMGA1. We also offer a general overview of RNA immunoprecipitation procedures and present novel bioinformatic tools for predicting RBPs binding sites on pseudogene transcripts.

The penile duplex ultrasound: How and when to perform it?

BACKGROUND: Because it is a superficial structure, the penis is ideally suited to ultrasound imaging. A number of disease processes, including Peyronie's disease, penile fractures and tumors, are clearly visualized with ultrasound. Baseline and dynamic assessment of cavernosal arterial changes after pharmaco-stimulation with alprostadil allows standardized diagnosis of arterial and venogenic causes of erectile dysfunction (ED). OBJECTIVE: To illustrate how to correctly perform flaccid and dynamic penile duplex ultrasound (D-PDU) and in which patients to recommend it. MATERIALS/METHODS: An extensive search of the literature was carried out on Pubmed with the insertion of the following Medical Subjects Headings (MeSH) terms and keywords "penile color Doppler ultrasound" "peak systolic velocity" "end-diastolic velocity", "acceleration time", "resistance index". EVIDENCE: In our experience, arterial erectile dysfunction is identified after standardized intracavernous injection (ICI) of alprostadil (10 mcg) when values of peak systolic velocity (PSV) are <35 cm/s and, in the most severe forms, for values <25 cm/s. Arterial insufficiency can also be identified by increased acceleration time (AT) values (>110 ms) and/or by a lack of visualization of helicine arteries at power Doppler mode along with incomplete achievement of penile rigidity. The veno-occlusive incompetence is determined when end-diastolic velocity (EDV) values are >4.5-5 cm/s or in the case of resistance index (RI) values <0.75. The assessment of additional surrogate markers of endothelial dysfunction, that is, intima-media thickness, mean platelet volume (MPV), endothelial progenitor cells (EPC), endothelial cell specific molecule-1(endocan) are also useful in assessing the patient's cardiovascular risk but are still considered investigational in the interpretation of D-PDU results. CONCLUSION: D-PDU scan after ICI with vasoactive drugs is a safe procedure and represents the gold standard for the diagnostics of penile pathologies and should be performed in men with ED not responding to oral conventional therapies and/or in those requiring accurate stratification of cardiovascular risk.

Proinflammatory profile of visceral adipose tissue and oxidative stress in severe obese patients carrying the variant rs4612666 C of NLRP3 gene.

BACKGROUND: The activation of NLRP3 inflammasome machinery has a central role in obesity-induced inflammation. Genetic studies well support the involvement of functional variants of NLRP3 and its negative regulator, CARD8, in the pathogenesis of complex diseases with an inflammatory background. We have investigated the influence of NLRP3 (rs4612666; rs10754558) and CARD8 (rs204321) genetic variants in both the inflammatory status of visceral adipose tissue (VAT) from patients with severe obesity and in the systemic oxidative stress before and after sleeve-gastrectomy (SLG). METHODS: Twenty-three consecutive severe obese patients candidate to SLG were enrolled in the study. Visceral adipose tissue (VAT) biopsies, obtained during SLG, were used to evaluate the expression of NLRP3, IL-1ß, IL-6, and MCP-1 by real-time RT-PCR. DNA was extracted from peripheral blood lymphocytes and genotyped by RFLP analysis. Before and 3 months after SLG, all patients underwent the assessment of oxidative stress, biochemical parameters, and body composition as measured by bioelectrical impedance analysis (BIA). RESULTS: Increased expression of NLRP3, IL-6, IL-1ß, and MCP-1 mRNA was observed in VAT of rs4612666 C variant carriers, in which higher oxidative stress was also detected as compared to non-carrier individuals. In all patients, oxidative stress, biochemical and BIA parameters improved after SLG, regardless of genotype. No significant correlations were found with the other genetic variants. CONCLUSIONS: Our results suggest that the NLRP3 rs4612666 C variant may promote a worse pro-inflammatory milieu and higher oxidative stress, thus leading patients to a more severe obesity phenotype. A larger study is needed to confirm this assumption and to investigate the impact of the NLRP3 rs4612666 C variant on severe obesity.

Phosphodiesterase Type-5 Inhibitor Tadalafil Modulates Steroid Hormones Signaling in a Prostate Cancer Cell Line.

BACKGROUND: The androgen receptor (AR) plays a key role in normal prostate homeostasis and in prostate cancer (PCa) development, while the role of aromatase (Cyp19a1) is still unclear. We evaluated the effects of a treatment with Tadalafil (TAD) on both these proteins. METHODS: Androgen-sensitive human PCa cell line (LnCAP) was incubated with/without TAD (10-6 M) and bicalutamide (BCT) (10-4 M) to evaluate a potential modulation on cell proliferation, protein and mRNA expression of Cyp19a, AR and estrogen receptor-ß (ERß), respectively. RESULTS: TAD increased early AR nuclear translocation (p < 0.05, after 15 min of exposure), and increased AR transcriptional activity (p < 0.05) and protein expression (p < 0.05) after 24 h. Moreover, after 24 h this treatment upregulated Cyp19a1 and ERß mRNA (p < 0.05 and p < 0.005 respectively) and led to an increase in protein expression of both after 48 h (p < 0.05). Interestingly, TAD counteracted Cyp19a1 stimulation induced by BCT (p < 0.05) but did not alter the effect induced by BCT on the AR protein expression. CONCLUSION: We demonstrate for the first time that TAD can significantly modulate AR expression and activity, Cyp19a1 and ERß expression in PCa cells, suggesting a specific effect of these proteins. In addition, TAD potentiates the antiproliferative activity of BCT, opening a new clinical scenario in the treatment of PCa.