Ligand-based virtual screening using binary kernel discrimination

This paper discusses the use of a machine-learning technique called binary kernel discrimination (BKD) for virtual screening in drug- and pesticide-discovery programmes. BKD is compared with several other ligand-based tools for virtual screening in databases of 2D structures represented by fragment bit-strings, and is shown to provide an effective, and reasonably efficient, way of prioritising compounds for biological screening

The right of access under the Police Directive:Small steps forward

The present article sets out to examine the right of access under Directive 2016/680, which regulates the processing of personal data by EU Member States’ law enforcement authorities. The article analyses in detail the provisions on the right of access. More precisely, it looks at whether the right provides for sufficient transparency towards the data subject and whether its scope allows for a harmonized data protection across the law enforcement sector in the EU. The article concludes that while the provisions on the right of access make a significant step towards more transparency, they also suffer from defi- ciencies. Also, the limited scope of the Directive takes away from the harmo- nization attempts

Effect of helium pre- or postconditioning on signal transduction kinases in patients undergoing coronary artery bypass graft surgery

Background: The noble gas helium induces pre- and postconditioning in animals and humans. Volatile anesthetics induce cardioprotection in humans undergoing coronary artery bypass graft (CABG) surgery. We hypothesized that helium induces pre-and postconditioning in CABG-patients, affecting signaling molecules protein kinase C-epsilon (PKC-epsilon), p38 mitogen activated protein kinase (p38 MAPK), extracellular signal-regulated kinase 1/2 (ERK-1/2) and heat shock protein 27 (HSP-27) within cardiac tissue, and reducing postoperative troponin levels. Methods: After ethical approval and informed consent, 125 elective patients undergoing CABG surgery were randomised into this prospective, placebo controlled, investigator blinded, parallel arm single-centre study. Helium preconditioning (3 x 5 min of 70 % helium and 30 % oxygen) was applied before aortic cross clamping; postconditioning (15 min of helium) was applied before release of the aortic cross clamp. Signaling molecules were measured in right atrial appendix specimens. Troponin-T was measured at 4, 12, 24 and 48 h postoperatively. Results: Baseline characteristics of all groups were similar. Helium preconditioning did not significantly alter the primary outcome (molecular levels of kinases PKC-e and HSP-27, ratio of activated p38 MAPK or ERK 1/2). Postoperative troponin T was 11 arbitrary units [5, 31; area-under-the-curve (interquartile range)] for controls, and no statistically significant changes were observed after helium preconditioning [He-pre: 11 (6, 18)], helium postconditioning [He-post: 11 (8, 15)], helium pre-and postconditioning [He-PP: 14 (6, 20)] and after sevoflurane preconditioning [APC: 12 (8, 24), p = 0.13]. No adverse effects related to study treatment were observed in this study. Conclusions: No effect was observed of helium preconditioning, postconditioning or the combination thereof on activation of p38 MAPK, ERK 1/2 or levels of HSP27 and PKC-e in the human heart. Helium pre-and postconditioning did not affect postoperative troponin release in patients undergoing CABG surgery

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

Multimorbidity in bipolar disorder and under-treatment of cardiovascular disease: a cross sectional study

Background: Individuals with serious mental disorders experience poor physical health, especially increased rates of cardiometabolic morbidity and premature morbidity. Recent evidence suggests that individuals with schizophrenia have numerous comorbid physical conditions which may be under-recorded and under-treated but to date very few studies have explored this issue for bipolar disorder. Methods:We conducted a cross-sectional analysis of a dataset of 1,751,841 registered patients within 314 primary-care practices in Scotland, U.K. Bipolar disorder was identified using Read Codes recorded within electronic medical records. Data on 32 common chronic physical conditions were also assessed. Potential prescribing inequalities were evaluated by analyzing prescribing data for coronary heart disease (CHD) and hypertension. Results: Compared to controls, individuals with bipolar disorder were significantly less likely to have no recorded physical conditions (OR 0.59, 95% CI 0.54-0.63) and significantly more likely to have one physical condition (OR 1.27, 95% CI 1.16-1.39), two physical conditions (OR 1.45, 95% CI 1.30-1.62) and three or more physical conditions (OR 1.44, 95% CI 1.30-1.64). People with bipolar disorder also had higher rates of thyroid disorders, chronic kidney disease, chronic pain, chronic obstructive airways disease and diabetes but, surprisingly, lower recorded rates of hypertension and atrial fibrillation. People with bipolar disorder and comorbid CHD or hypertension were significantly more likely to be prescribed no antihypertensive or cholesterol-lowering medications compared to controls, and bipolar individuals with CHD or hypertension were significantly less likely to be on 2 or more antihypertensive agents. Conclusions: Individuals with bipolar disorder are similar to individuals with schizophrenia in having a wide range of comorbid and multiple physical health conditions. They are also less likely than controls to have a primary-care record of cardiovascular conditions such as hypertension and atrial fibrillation. Those with a recorded diagnosis of CHD or hypertension were less likely to be treated with cardiovascular medications and were treated less intensively. This study highlights the high physical healthcare needs of people with bipolar disorder, and provides evidence for a systematic under-recognition and under-treatment of cardiovascular disease in this group

BLASTing small molecules—statistics and extreme statistics of chemical similarity scores

Motivation: Small organic molecules, from nucleotides and amino acids to metabolites and drugs, play a fundamental role in chemistry, biology and medicine. As databases of small molecules continue to grow and become more open, it is important to develop the tools to search them efficiently. In order to develop a BLAST-like tool for small molecules, one must first understand the statistical behavior of molecular similarity scores

Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed

Data protection in elderly health care platforms

Ambient Assisted Living provides solutions to the increasing cognitive problems that affect the elderly population. To provide all features possible, Ambient Assisted Living projects require access to personal and private information of their users. Currently, the legal issues arisen in Ambient Assisted Living are a hot topic in the European Union, especially aspects regarding unsupervised data processing and cross-sharing of personal information. In this paper it is presented the iGenda project, which is a Cognitive Assistant inserted in the Ambient Assisted Living area which aims to build safe environments that adapt themselves to one’s individual needs. However, one of the issues is the protection of the data flowing within the system and the protection of user’s fundamental rights. It is also presented the principles and legal guarantees of data protection and transmission, and legal aspects are explained, embracing appropriate solutions to technological features that may be a threat.FEDER - Federación Española de Enfermedades Raras(TIN2015-65515-C4-1-R). COMPETE: POCI-01-0145-FEDER-007043 and FCT-Fundação para a Ciência e Tecnologia within the Project Scope UID/ CEC/00319/2013. A. Costa thanks the Fundação para a Ciência e a Tecnologia (FCT) the Post-Doc scholarship with the Ref. SFRH/BPD/102696/2014. This work is also partially supported by the MINECO/FEDER TIN2015-65515-C4-1-R