Investigation of structural requirements of anticancer activity at the paclitaxel/tubulin binding site using CoMFA and CoMSIA

CoMFA and CoMSIA analysis were utilized in this investigation to define the important interacting regions in paclitaxel/tubulin binding site and to develop selective paclitaxel-like active compounds. The starting geometry of paclitaxel analogs was taken from the crystal structure of docetaxel. A total of 28 derivatives of paclitaxel were divided into two groups—a training set comprising of 19 compounds and a test set comprising of nine compounds. They were constructed and geometrically optimized using SYBYL v6.6. CoMFA studies provided a good predictability (q2 = 0.699, r2 = 0.991, PC = 6, S.E.E. = 0.343 and F = 185.910). They showed the steric and electrostatic properties as the major interacting forces whilst the lipophilic property contribution was a minor factor for recognition forces of the binding site. These results were in agreement with the experimental data of the binding activities of these compounds. Five fields in CoMSIA analysis (steric, electrostatic, hydrophobic, hydrogen-bond acceptor and donor properties) were considered contributors in the ligand–receptor interactions. The results obtained from the CoMSIA studies were: q2 = 0.535, r2 = 0.983, PC = 5, S.E.E. = 0.452 and F = 127.884. The data obtained from both CoMFA and CoMSIA studies were interpreted with respect to the paclitaxel/tubulin binding site. This intuitively suggested where the most significant anchoring points for binding affinity are located. This information could be used for the development of new compounds having paclitaxel-like activity with new chemical entities to overcome the existing pharmaceutical barriers and the economical problem associated with the synthesis of the paclitaxel analogs. These will boost the wide use of this useful class of compounds, i.e. in brain tumors as the most of the present active compounds have poor blood–brain barrier crossing ratios and also, various tubulin isotypes has shown resistance to taxanes and other antimitotic agents.

Inhaled particle surface area dose: Stationary vs personal monitoring

The aim of this paper is to determine the suitability of solely stationary measurements for exposure assessment and management applications. For this purpose, quantified inhaled particle surface area (IPSA) doses using both stationary and personal particle exposure monitors were evaluated and compared.

The structural basis of DNA binding by the single-stranded DNA-binding protein from Sulfolobus solfataricus

Canonical single-stranded DNA-binding proteins (SSBs) from the oligosaccharide/oligonucleotide-binding (OB) domain family are present in all known organisms and are critical for DNA replication, recombination and repair. The SSB from the hyperthermophilic crenarchaeote Sulfolobus solfataricus (SsoSSB) has a ‘simple’ domain organization consisting of a single DNA-binding OB fold coupled to a flexible C-terminal tail, in contrast with other SSBs in this family that incorporate up to four OB domains. Despite the large differences in the domain organization within the SSB family, the structure of the OB domain is remarkably similar all cellular life forms. However, there are significant differences in the molecular mechanism of ssDNA binding. We have determined the structure of the SsoSSB OB domain bound to ssDNA by NMR spectroscopy. We reveal that ssDNA recognition is modulated by base-stacking of three key aromatic residues, in contrast with the OB domains of human RPA and the recently discovered human homologue of SsoSSB, hSSB1. We also demonstrate that SsoSSB binds ssDNA with a footprint of five bases and with a defined binding polarity. These data elucidate the structural basis of DNA binding and shed light on the molecular mechanism by which these ‘simple’ SSBs interact with ssDNA.

How an urban Aboriginal and Torres Strait Islander primary health care service improved access to mental health care

Aboriginal and Torres Strait Islander people experience higher levels of psychological distress and mental ill health than their non-Indigenous counterparts, but underuse mental health services. Interventions are required to address the structural and functional access barriers that cause this underuse. In 2012, the Southern Queensland Centre of Excellence in Aboriginal and Torres Strait Islander Primary Health Care employed a psychologist and a social worker to integrate mental health care into its primary health care services. This research study examines the impact of this innovation.

Using decision trees to understand structure in missing data

Objectives Demonstrate the application of decision trees – classification and regression trees (CARTs), and their cousins, boosted regression trees (BRTs) – to understand structure in missing data. Setting Data taken from employees at three different industry sites in Australia. Participants 7915 observations were included. Materials and Methods The approach was evaluated using an occupational health dataset comprising results of questionnaires, medical tests, and environmental monitoring. Statistical methods included standard statistical tests and the ‘rpart’ and ‘gbm’ packages for CART and BRT analyses, respectively, from the statistical software ‘R’. A simulation study was conducted to explore the capability of decision tree models in describing data with missingness artificially introduced. Results CART and BRT models were effective in highlighting a missingness structure in the data, related to the Type of data (medical or environmental), the site in which it was collected, the number of visits and the presence of extreme values. The simulation study revealed that CART models were able to identify variables and values responsible for inducing missingness. There was greater variation in variable importance for unstructured compared to structured missingness. Discussion Both CART and BRT models were effective in describing structural missingness in data. CART models may be preferred over BRT models for exploratory analysis of missing data, and selecting variables important for predicting missingness. BRT models can show how values of other variables influence missingness, which may prove useful for researchers. Conclusion Researchers are encouraged to use CART and BRT models to explore and understand missing data.

Capnography monitoring during procedural sedation and analgesia: A systematic review protocol

Background An important potential clinical benefit of using capnography monitoring during procedural sedation and analgesia (PSA) is that this technology could improve patient safety by reducing serious sedation-related adverse events, such as death or permanent neurological disability, which are caused by inadequate oxygenation. The hypothesis is that earlier identification of respiratory depression using capnography leads to a change in clinical management that prevents hypoxaemia. As inadequate oxygenation/ventilation is the most common reason for injury associated with PSA, reducing episodes of hypoxaemia would indicate that using capnography would be safer than relying on standard monitoring alone. Methods/design The primary objective of this review is to determine whether using capnography during PSA in the hospital setting improves patient safety by reducing the risk of hypoxaemia (defined as an arterial partial pressure of oxygen below 60 mmHg or percentage of haemoglobin that is saturated with oxygen [SpO2] less than 90 %). A secondary objective of this review is to determine whether changes in the clinical management of sedated patients are the mediating factor for any observed impact of capnography monitoring on the rate of hypoxaemia. The potential adverse effect of capnography monitoring that will be examined in this review is the rate of inadequate sedation. Electronic databases will be searched for parallel, crossover and cluster randomised controlled trials comparing the use of capnography with standard monitoring alone during PSA that is administered in the hospital setting. Studies that included patients who received general or regional anaesthesia will be excluded from the review. Non-randomised studies will be excluded. Screening, study selection and data extraction will be performed by two reviewers. The Cochrane risk of bias tool will be used to assign a judgment about the degree of risk. Meta-analyses will be performed if suitable. Discussion This review will synthesise the evidence on an important potential clinical benefit of capnography monitoring during PSA within hospital settings. Systematic review registration: PROSPERO CRD42015023740

Functional and structural of the erector spinae muscle during isometric lumbar extension

Study Design Cross-sectional study. Objectives To compare erector spinae (ES) muscle fatigue between chronic non-specific lower back pain (CNLBP) sufferers and healthy subjects from a biomechanical perspective during fatiguing isometric lumbar extensions. Background Paraspinal muscle maximal contraction and fatigue are used as a functional predictor for disabilities. The simplest method to determine muscle fatigue is by evaluating the evolution during specific contractions, such as isometric contractions. There are no studies that evaluate the evolution of the ES muscle during fatiguing isometric lumbar extensions and analyse functional and architectural variables. Methods In a pre-calibrated system, participants performed a maximal isometric extension of the lumbar spine for 5 and 30 seconds. Functional variables (torque and muscle activation) and architecture (pennation angle and muscle thickness) were measured using a load cell, surface electromyography and ultrasound, respectively. The results were normalised and a reliability study of the ultrasound measurement was made. Results: The ultrasound measurements were highly reliable, with Cronbach’s alpha values ranging from 0.951 0.981. All measured variables shown significant differences before and after fatiguing isometric lumbar extension. Conclusion During a lumbar isometric extension test, architecture and functional variables of the ES muscle could be analised using ultrasound, surface EMG and load cell. In adition, during an endurance test, ES muscle suffers an acute effect on architectural and functional variables.

Mind what you say-general and specific mechanisms for monitoring in speech production

For most people, speech production is relatively effortless and error-free. Yet it has long been recognized that we need some type of control over what we are currently saying and what we plan to say. Precisely how we monitor our internal and external speech has been a topic of research interest for several decades. The predominant approach in psycholinguistics has assumed monitoring of both is accomplished via systems responsible for comprehending others' speech. This special topic aimed to broaden the field, firstly by examining proposals that speech production might also engage more general systems, such as those involved in action monitoring. A second aim was to examine proposals for a production-specific, internal monitor. Both aims require that we also specify the nature of the representations subject to monitoring.

Development of brain structural connectivity between ages 12 and 30: A 4-Tesla diffusion imaging study in 439 adolescents and adults

Understanding how the brain matures in healthy individuals is critical for evaluating deviations from normal development in psychiatric and neurodevelopmental disorders. The brain's anatomical networks are profoundly re-modeled between childhood and adulthood, and diffusion tractography offers unprecedented power to reconstruct these networks and neural pathways in vivo. Here we tracked changes in structural connectivity and network efficiency in 439 right-handed individuals aged 12 to 30 (211 female/126 male adults, mean age=23.6, SD=2.19; 31 female/24 male 12 year olds, mean age=12.3, SD=0.18; and 25 female/22 male 16 year olds, mean age=16.2, SD=0.37). All participants were scanned with high angular resolution diffusion imaging (HARDI) at 4 T. After we performed whole brain tractography, 70 cortical gyral-based regions of interest were extracted from each participant's co-registered anatomical scans. The proportion of fiber connections between all pairs of cortical regions, or nodes, was found to create symmetric fiber density matrices, reflecting the structural brain network. From those 70 × 70 matrices we computed graph theory metrics characterizing structural connectivity. Several key global and nodal metrics changed across development, showing increased network integration, with some connections pruned and others strengthened. The increases and decreases in fiber density, however, were not distributed proportionally across the brain. The frontal cortex had a disproportionate number of decreases in fiber density while the temporal cortex had a disproportionate number of increases in fiber density. This large-scale analysis of the developing structural connectome offers a foundation to develop statistical criteria for aberrant brain connectivity as the human brain matures.

Test-retest reliability of graph theory measures of structural brain connectivity

The human connectome has recently become a popular research topic in neuroscience, and many new algorithms have been applied to analyze brain networks. In particular, network topology measures from graph theory have been adapted to analyze network efficiency and 'small-world' properties. While there has been a surge in the number of papers examining connectivity through graph theory, questions remain about its test-retest reliability (TRT). In particular, the reproducibility of structural connectivity measures has not been assessed. We examined the TRT of global connectivity measures generated from graph theory analyses of 17 young adults who underwent two high-angular resolution diffusion (HARDI) scans approximately 3 months apart. Of the measures assessed, modularity had the highest TRT, and it was stable across a range of sparsities (a thresholding parameter used to define which network edges are retained). These reliability measures underline the need to develop network descriptors that are robust to acquisition parameters.

Reducing structural variation to determine the genetics of white matter integrity across hemispheres - a dti study of 100 twins

Studies of cerebral asymmetry can open doors to understanding the functional specialization of each brain hemisphere, and how this is altered in disease. Here we examined hemispheric asymmetries in fiber architecture using diffusion tensor imaging (DTI) in 100 subjects, using high-dimensional fluid warping to disentangle shape differences from measures sensitive to myelination. Confounding effects of purely structural asymmetries were reduced by using co-registered structural images to fluidly warp 3D maps of fiber characteristics (fractional and geodesic anisotropy) to a structurally symmetric minimal deformation template (MDT). We performed a quantitative genetic analysis on 100 subjects to determine whether the sources of the remaining signal asymmetries were primarily genetic or environmental. A twin design was used to identify the heritable features of fiber asymmetry in various regions of interest, to further assist in the discovery of genes influencing brain micro-architecture and brain lateralization. Genetic influences and left/right asymmetries were detected in the fiber architecture of the frontal lobes, with minor differences depending on the choice of registration template.

A 1H MRS study of probable Alzheimer's disease and normal aging: Implications for longitudinal monitoring of dementia progression

In order to evaluate the capability of 1H MRS to monitor longitudinal changes in subjects with probable Alzheimer's disease (AD), the temporal stability of the metabolite measures N-acetylaspartate and N- acetylaspartylglutamate (NA), total Creatine (Cr), myo-Inositol (mI), total Choline (Chol), NA/Cr, mI/Cr, Chol/Cr and NA/mI were investigated in a cohort of normal older adults. Only the metabolite measures NA, mI, Cr, NA/Cr, mI/Cr, and NA/mI were found to be stable after a mean interval of 260 days. Relative and absolute metabolite measures from a cohort of patients with probable AD were subsequently compared with data from a sample of normal older adult control subjects, and correlated with mental status and the degree of atrophy in the localized voxel. Concentrations of NA, NA/Cr, and NA/mI were significantly reduced in the AD group with concomitant significant increases in mI and mI/Cr. There were no differences between the two groups in measures of Cr, Chol, or Chol/Cr. Significant correlations between mental status as measured by the Mini-Mental State Examination and NA/mI, mI/Cr and NA were found. These metabolite measures were also significantly correlated with the extent of atrophy (as measured by CSF and GM composition) in the spectroscopy voxel.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

The ADMIN-ICU survey: A survey on antimicrobial dosing and monitoring in ICUs

Objectives: There is little evidence and few guidelines to inform the most appropriate dosing and monitoring for antimicrobials in the ICU. We aimed to survey current practices around the world. Methods: An online structured questionnaire was developed and sent by e-mail to obtain information on local antimicrobial prescribing practices for glycopeptides, piperacillin/tazobactam, carbapenems, aminoglycosides and colistin. Results: A total of 402 professionals from 328 hospitals in 53 countries responded, of whom 78% were specialists in intensive care medicine (41% intensive care, 30% anaesthesiology, 14% internal medicine) and 12% were pharmacists. Vancomycin was used as a continuous infusion in 31% of units at a median (IQR) daily dose of 25 (25–30) mg/kg. Piperacillin/tazobactam was used as an extended infusion by 22% and as a continuous infusion by 7%. An extended infusion of carbapenem (meropenem or imipenem) was used by 27% and a continuous infusion by 5%. Colistin was used at a daily dose of 7.5 (3.9–9) million IU (MIU)/day, predominantly as a short infusion. The most commonly used aminoglycosides were gentamicin (55%) followed by amikacin (40%), with administration as a single daily dose reported in 94% of the cases. Gentamicin was used at a daily dose of 5 (5–6) mg/day and amikacin at a daily dose of 15 (15–20) mg/day. Therapeutic drug monitoring of vancomycin, piperacillin/tazobactam and meropenem was used by 74%, 1% and 2% of the respondents, respectively. Peak aminoglycoside concentrations were sampled daily by 28% and trough concentrations in all patients by 61% of the respondents. Conclusions: We found wide variability in reported practices for antibiotic dosing and monitoring. Research is required to develop evidence-based guidelines to standardize practices.

Meta-analysis of structural imaging findings in Attention-Deficit/Hyperactivity Disorder

Background Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues. Methods We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author. Results Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference equal to .408, p less than .001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences. Conclusions This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies.