Due to the adverse effects of unpredictable environmental disturbances on real control systems, robustness of control performance becomes a substantial asset for control system design. This study introduces a v-domain optimal design scheme for Fractional Order Proportional-Integral-Derivative (FOPID) controllers with adoption of Genetic Algorithm (GA) optimization. The proposed design scheme performs placement of system pole with minimum angle to the first Riemann sheet in order to obtain improved disturbance rejection control performance. In this manner, optimal placement of the minimum angle system pole is conducted by fulfilling a predefined reference to disturbance rate (RDR) design specification. For a computer-aided solution of this optimal design problem, a multi-objective controller design strategy is presented by adopting GA. Illustrative design examples are demonstrated to evaluate performance of designed FOPID controllers.

• Keywords
• Computer aided optimal controller design, Disturbance rejection control, FOPID controller, Fractional order control system, Stability,
• Publication type
• Journal Article MeSH
• Review MeSH

The paper describes a novel control strategy for simultaneous manipulation of several microscale particles over a planar microelectrode array using dielectrophoresis. The approach is based on a combination of numerical nonlinear optimization, which gives a systematic computational procedure for finding the voltages applied to the individual electrodes, and exploitation of the intrinsic noise, which compensates for the loss of controllability when two identical particles are exposed to identical forces. Although interesting on its own, the proposed functionality can also be seen as a preliminary achievement in a quest for a technique for separation of two particles. The approach is tested experimentally with polystyrene beads (50 microns in diameter) immersed in deionized water on a flat microelectrode array with parallel electrodes. A digital camera and computer vision algorithm are used to measure the positions. Two distinguishing features of the proposed control strategy are that the range of motion is not limited to interelectrode gaps and that independent manipulation of several particles simultaneously is feasible even on a simple microelectrode array.

• Keywords
• Dielectrophoresis, Feedback control, Micromanipulation, Parallel manipulation, Visual feedback,
• MeSH
• Algorithms MeSH
• Equipment Design MeSH
• Electrodes MeSH
• Electrophoresis methods   MeSH
• Noise MeSH
• Micromanipulation instrumentation   methods   MeSH
• Microspheres MeSH
• Signal Processing, Computer-Assisted instrumentation   MeSH
• Models, Theoretical MeSH
• Feedback * MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

This study aimed to reveal interactions of the stress response sigma subunits (factors) σD and σH of RNA polymerase and promoters in Gram-positive bacterium Corynebacterium glutamicum by combining wet-lab obtained data and in silico modeling. Computer modeling-guided point mutagenesis of C. glutamicum σH subunit led to the creation of a panel of σH variants. Their ability to initiate transcription from naturally occurring hybrid σD/σH-dependent promoter Pcg0441 and two control canonical promoters (σD-dependent PrsdA and σH-dependent PuvrD3) was measured and interpreted using molecular dynamics simulations of homology models of all complexes. The results led us to design the artificial hybrid promoter PD35H10 combining the -10 element of the PuvrD3 promoter and the -35 element of the PrsdA promoter. This artificial hybrid promoter PD35-rsdAH10-uvrD3 showed almost optimal properties needed for the bio-orthogonal transcription (not interfering with the native biological processes).

• Keywords
• Bio-orthogonal transcription, Corynebacterium, Promoter, Sigma factor,
• MeSH
• Bacterial Proteins * genetics   metabolism   chemistry   MeSH
• Point Mutation * MeSH
• Corynebacterium glutamicum * genetics   MeSH
• DNA-Directed RNA Polymerases genetics   metabolism   chemistry   MeSH
• Stress, Physiological genetics   MeSH
• Transcription, Genetic MeSH
• Computer Simulation MeSH
• Promoter Regions, Genetic * MeSH
• Gene Expression Regulation, Bacterial MeSH
• Sigma Factor * genetics   metabolism   chemistry   MeSH
• Molecular Dynamics Simulation * MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Bacterial Proteins * MeSH
• DNA-Directed RNA Polymerases MeSH
• Sigma Factor * MeSH

Neuroblastoma, the commonest paediatric extra-cranial tumour, remains a leading cause of death from cancer in children. There is an urgent need to develop new drugs to improve cure rates and reduce long-term toxicity and to incorporate molecularly targeted therapies into treatment. Many potential drugs are becoming available, but have to be prioritised for clinical trials due to the relatively small numbers of patients. Areas covered: The current drug development model has been slow, associated with significant attrition, and few new drugs have been developed for neuroblastoma. The Neuroblastoma New Drug Development Strategy (NDDS) has: 1) established a group with expertise in drug development; 2) prioritised targets and drugs according to tumour biology (target expression, dependency, pre-clinical data; potential combinations; biomarkers), identifying as priority targets ALK, MEK, CDK4/6, MDM2, MYCN (druggable by BET bromodomain, aurora kinase, mTORC1/2) BIRC5 and checkpoint kinase 1; 3) promoted clinical trials with target-prioritised drugs. Drugs showing activity can be rapidly transitioned via parallel randomised trials into front-line studies. Expert opinion: The Neuroblastoma NDDS is based on the premise that optimal drug development is reliant on knowledge of tumour biology and prioritisation. This approach will accelerate neuroblastoma drug development and other poor prognosis childhood malignancies.

• Keywords
• Neuroblastoma, clinical trials, drug development, phase I, preclinical testing,
• MeSH
• Time Factors MeSH
• Molecular Targeted Therapy MeSH
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Neuroblastoma drug therapy   pathology   MeSH
• Drug Evaluation, Preclinical methods   MeSH
• Prognosis MeSH
• Antineoplastic Agents adverse effects   pharmacology   MeSH
• Drug Design * MeSH
• Randomized Controlled Trials as Topic MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• Antineoplastic Agents MeSH

Pharmacotherapy during pregnancy is often inevitable for medical treatment of the mother, the fetus or both. The knowledge of drug transport across placenta is, therefore, an important topic to bear in mind when deciding treatment in pregnant women. Several drug transporters of the ABC and SLC families have been discovered in the placenta, such as P-glycoprotein, breast cancer resistance protein, or organic anion/cation transporters. It is thus evident that the passage of drugs across the placenta can no longer be predicted simply on the basis of their physical-chemical properties. Functional expression of placental drug transporters in the trophoblast and the possibility of drug-drug interactions must be considered to optimize pharmacotherapy during pregnancy. In this review we summarize current knowledge on the expression and function of ABC and SLC transporters in the trophoblast. Furthermore, we put this data into context with medical conditions that require maternal and/or fetal treatment during pregnancy, such as gestational diabetes, HIV infection, fetal arrhythmias and epilepsy. Proper understanding of the role of placental transporters should be of great interest not only to clinicians but also to pharmaceutical industry for future drug design and development to control the degree of fetal exposure.

• MeSH
• ATP-Binding Cassette Transporters metabolism   MeSH
• Biological Transport MeSH
• Pregnancy Complications drug therapy   physiopathology   MeSH
• Pharmaceutical Preparations administration & dosage   metabolism   MeSH
• Drug Interactions MeSH
• Humans MeSH
• Maternal-Fetal Exchange physiology   MeSH
• Membrane Transport Proteins metabolism   MeSH
• Placenta metabolism   MeSH
• Drug Design MeSH
• Pregnancy MeSH
• Trophoblasts metabolism   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Pregnancy MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• ATP-Binding Cassette Transporters MeSH
• Pharmaceutical Preparations MeSH
• Membrane Transport Proteins MeSH

Clinical procedure for mild cognitive impairment (MCI) is mainly based on clinical records and short cognitive tests. However, low suspicion and difficulties in understanding test cut-offs make diagnostic accuracy being low, particularly in primary care. Artificial neural networks (ANNs) are suitable to design computed aided diagnostic systems because of their features of generating relationships between variables and their learning capability. The main aim pursued in that work is to explore the ability of a hybrid ANN-based system in order to provide a tool to assist in the clinical decision-making that facilitates a reliable MCI estimate. The model is designed to work with variables usually available in primary care, including Minimental Status Examination (MMSE), Functional Assessment Questionnaire (FAQ), Geriatric Depression Scale (GDS), age, and years of education. It will be useful in any clinical setting. Other important goal of our study is to compare the diagnostic rendering of ANN-based system and clinical physicians. A sample of 128 MCI subjects and 203 controls was selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The ANN-based system found the optimal variable combination, being AUC, sensitivity, specificity, and clinical utility index (CUI) calculated. The ANN results were compared with those from medical experts which include two family physicians, a neurologist, and a geriatrician. The optimal ANN model reached an AUC of 95.2%, with a sensitivity of 90.0% and a specificity of 84.78% and was based on MMSE, FAQ, and age inputs. As a whole, physician performance achieved a sensitivity of 46.66% and a specificity of 91.3%. CUIs were also better for the ANN model. The proposed ANN system reaches excellent diagnostic accuracy although it is based only on common clinical tests. These results suggest that the system is especially suitable for primary care implementation, aiding physicians work with cognitive impairment suspicions.

• MeSH
• Databases, Factual statistics & numerical data   MeSH
• Diagnosis, Computer-Assisted methods   statistics & numerical data   MeSH
• Cognitive Dysfunction diagnosis   psychology   MeSH
• Humans MeSH
• Neural Networks, Computer * MeSH
• Neuropsychological Tests * statistics & numerical data   MeSH
• Area Under Curve MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Sensitivity and Specificity MeSH
• Case-Control Studies MeSH
• Decision Support Systems, Clinical * statistics & numerical data   MeSH
• Computational Biology MeSH
• Check Tag
• Humans MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH

The cell division cycle is controlled by cyclin-dependent kinases (cdk), which consist of a catalytic subunit (cdk1-cdk8) and a regulatory subunit (cyclin A-H). Purine-like inhibitors of cyclin-dependent kinases have recently been found to be of potential use as anticancer drugs. Rigid and flexible docking techniques were used for analysis of binding mode and design of new inhibitors. X-ray structures of three (ATP, olomoucine, roscovitine) cdk2 complexes were available at the beginning of the study and were used to optimize the docking parameters. The new potential inhibitors were then docked into the cdk2 enzyme, and the enzyme/inhibitor interaction energies were calculated and tested against the assayed activities of cdk1 (37 compounds) and cdk2 (9 compounds). A significant rank correlation between the activity and the rigid docking interaction energy has been found. This implies that (i) the rigid docking can be used as a tool for qualitative prediction of activity and (ii) values obtained by the rigid docking technique into the cdk2 active site can also be used for the prediction of cdk1 activity. While the resulting geometries obtained by the rigid docking are in good agreement with the X-ray data, the flexible docking did not always produce the same inhibitor conformation as that found in the crystal.

• MeSH
• Cyclin-Dependent Kinase 2 MeSH
• Cyclin-Dependent Kinases antagonists & inhibitors   chemistry   MeSH
• Enzyme Inhibitors chemical synthesis   chemistry   MeSH
• Catalytic Domain MeSH
• CDC2-CDC28 Kinases * MeSH
• Ligands MeSH
• Molecular Conformation MeSH
• Models, Molecular MeSH
• Protein Serine-Threonine Kinases antagonists & inhibitors   chemistry   MeSH
• CDC2 Protein Kinase antagonists & inhibitors   chemistry   MeSH
• Purines chemistry   MeSH
• Drug Design MeSH
• Structure-Activity Relationship MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Cyclin-Dependent Kinase 2 MeSH
• Cyclin-Dependent Kinases MeSH
• Enzyme Inhibitors MeSH
• CDC2-CDC28 Kinases * MeSH
• Ligands MeSH
• Protein Serine-Threonine Kinases MeSH
• CDC2 Protein Kinase MeSH
• Purines MeSH