Vehicle movements in roundabouts

This article describes a research study that used a new method based on image processing for analyzing vehicle movements in traffic circles (roundabouts). The study had three stages: a field survey to collect vehicular flow images captured by video cameras; the processing of these images using a proprietary software (VeTRA—Vehicle Tracking for Roundabout Analysis); and the analysis of the collected data. The authors note that the software allows the automatic computation of the main variables necessary to rank and evaluate a generic roundabout: the entry/exit (E/E) matrix with classification of vehicles (e.g., heavy, light, and motorcycles), vehicle trajectories, and vehicular speed diagrams along the paths of the traffic circle. The processing system can overcome classic problems affecting image processing such as variable wind conditions, cloud cover, shadows, and obstructions. The authors manually compared data on entry and exits generated by VeTRA to those manually counted on the corresponding video images. They also present a case study of an existing roundabout in an urban Italian environment. The authors conclude that the software has a high capability of generating the E/E matrix and that the analysis of vehicular trajectories enable the accurate evaluation of driver behavior in the roundabout

The Multifaceted Role of GPCRs in Amyotrophic Lateral Sclerosis: A New Therapeutic Perspective?

Amyotrophic lateral sclerosis (ALS) is a degenerating disease involving the motor neurons, which causes a progressive loss of movement ability, usually leading to death within 2 to 5 years from the diagnosis. Much effort has been put into research for an effective therapy for its eradication, but still, no cure is available. The only two drugs approved for this pathology, Riluzole and Edaravone, are onlyable to slow down the inevitable disease progression. As assessed in the literature, drug targets such as protein kinases have already been extensively examined as potential drug targets for ALS, with some molecules already in clinical trials. Here, we focus on the involvement of another very important and studied class of biological entities, G protein-coupled receptors (GPCRs), in the onset and progression of ALS. This workaimsto give an overview of what has been already discovered on the topic, providing useful information and insights that can be used by scientists all around the world who are putting efforts into the fight against this very important neurodegenerating disease

An innovative approach to select urban-rural sites for Urban Heat Island analysis: the case of Turin (Italy)

A novel metric – the Mean Temperature Difference (MTD) – is proposed for the selection of urban-rural pairs of stations needed in the Urban Heat Island (UHI) quantification. This metric highlights the thermal pattern typical of each weather station with respect to the average one of the area of interest. Afterwards, Principal Component Analysis is adopted to cluster stations into subsets exhibiting similar thermal behaviors. The joint use of MTD and PCA allows one to classify stations objectively and without the need of preliminary assumptions about the station landscapes. An application to the metropolitan area of Turin (Italy) and a comparison with validated methods to select urban-rural pairs demonstrate that the proposed approach is easily interpretable and reliable also when the study area exhibits a non-trivial landscape categorization

Discovery of the 3-Amino-1,2,4-triazine-Based Library as Selective PDK1 Inhibitors with Therapeutic Potential in Highly Aggressive Pancreatic Ductal Adenocarcinoma

Pyruvate dehydrogenase kinases (PDKs) are serine/threonine kinases, that are directly involved in altered cancer cell metabolism, resulting in cancer aggressiveness and resistance. Dichloroacetic acid (DCA) is the first PDK inhibitor that has entered phase II clinical; however, several side effects associated with weak anticancer activity and excessive drug dose (100 mg/kg) have led to its limitation in clinical application. Building upon a molecular hybridization approach, a small library of 3-amino-1,2,4-triazine derivatives has been designed, synthesized, and characterized for their PDK inhibitory activity using in silico, in vitro, and in vivo assays. Biochemical screenings showed that all synthesized compounds are potent and subtype-selective inhibitors of PDK. Accordingly, molecular modeling studies revealed that a lot of ligands can be properly placed inside the ATP-binding site of PDK1. Interestingly, 2D and 3D cell studies revealed their ability to induce cancer cell death at low micromolar doses, being extremely effective against human pancreatic KRAS mutated cancer cells. Cellular mechanistic studies confirm their ability to hamper the PDK/PDH axis, thus leading to metabolic/redox cellular impairment, and to ultimately trigger apoptotic cancer cell death. Remarkably, preliminary in vivo studies performed on a highly aggressive and metastatic Kras-mutant solid tumor model confirm the ability of the most representative compound 5i to target the PDH/PDK axis in vivo and highlighted its equal efficacy and better tolerability profile with respect to those elicited by the reference FDA approved drugs, cisplatin and gemcitabine. Collectively, the data highlights the promising anticancer potential of these novel PDK-targeting derivatives toward obtaining clinical candidates for combatting highly aggressive KRAS-mutant pancreatic ductal adenocarcinomas

Structural Manipulations of Marine Natural Products Inspire a New Library of 3-Amino-1,2,4-Triazine PDK Inhibitors Endowed with Antitumor Activity in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the main aggressive types of cancer, characterized by late prognosis and drug resistance. Among the main factors sustaining PDAC progression, the alteration of cell metabolism has emerged to have a key role in PDAC cell proliferation, invasion, and resistance to standard chemotherapeutic agents. Taking into account all these factors and the urgency in evaluating novel options to treat PDAC, in the present work we reported the synthesis of a new series of indolyl-7-azaindolyl triazine compounds inspired by marine bis-indolyl alkaloids. We first assessed the ability of the new triazine compounds to inhibit the enzymatic activity of pyruvate dehydrogenase kinases (PDKs). The results showed that most of derivatives totally inhibit PDK1 and PDK4. Molecular docking analysis was executed to predict the possible binding mode of these derivatives using ligand-based homology modeling technique. Evaluation of the capability of new triazines to inhibit the cell growth in 2D and 3D KRAS-wild-type (BxPC-3) and KRAS-mutant (PSN-1) PDAC cell line, was carried out. The results showed the capacity of the new derivatives to reduce cell growth with a major selectivity against KRAS-mutant PDAC PSN-1 on both cell models. These data demonstrated that the new triazine derivatives target PDK1 enzymatic activity and exhibit cytotoxic effects on 2D and 3D PDAC cell models, thus encouraging further structure manipulation for analogs development against PDA

Application, evaluation, and improvement of computational methodologies in drug discovery

The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of “Computer-Aided Drug Design” (CADD), and they now constitute one of the pillars in the drug discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing to proficiently and rationally choose proper compounds for a desired therapeutic need among the extreme vastity of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. As a result of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can be also obtained with other computer-based techniques. In this Ph.D. work, we extensively applied state-of-the-art Computer-Aided Drug Design methods in different scenarios of pharmaceutical and biological interest, highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work combines the practical implementation of computational approaches with the development of their methods, about which we focused mainly on the field of novel filtration and scoring methods for candidate selection.The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of “Computer-Aided Drug Design” (CADD), and they now constitute one of the pillars in the drug discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing to proficiently and rationally choose proper compounds for a desired therapeutic need among the extreme vastity of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. As a result of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can be also obtained with other computer-based techniques. In this Ph.D. work, we extensively applied state-of-the-art Computer-Aided Drug Design methods in different scenarios of pharmaceutical and biological interest, highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work combines the practical implementation of computational approaches with the development of their methods, about which we focused mainly on the field of novel filtration and scoring methods for candidate selection

Sodium or Not Sodium: Should Its Presence Affect the Accuracy of Pose Prediction in Docking {GPCR} Antagonists?

The function of the allosteric sodium ion in stabilizing the inactive form of GPCRs has been extensively described in the past decades. Its presence has been reported to be essential for the binding of antagonist molecules in the orthosteric site of these very important therapeutical targets. Among the GPCR-antagonist crystal structures available, in most cases, the sodium ion could not be experimentally resolved, obliging computational scientists using GPCRs as targets for virtual screening to ask: "Should the sodium ion affect the accuracy of pose prediction in docking GPCR antagonists?" In the present study, we examined the performance of three orthogonal docking programs in the self-docking of GPCR antagonists to try to answer this question. The results of the present work highlight that if the sodium ion is resolved in the crystal structure used as the target, it should also be taken into account during the docking calculations. If the crystallographic studies were not able to resolve the sodium ion then no advantage would be obtained if this is manually inserted in the virtual target. The outcomes of the present analysis are useful for researchers exploiting molecular docking-based virtual screening to efficiently identify novel GPCR antagonists