Applying the Huntington’s Disease Integrated Staging System (HD-ISS) to Observational Studies

Background: The Huntington’s Disease Integrated Staging System (HD-ISS) has four stages that characterize disease progression. Classification is based on CAG length as a marker of Huntington’s disease (Stage 0), striatum atrophy as a biomarker of pathogenesis (Stage 1), motor or cognitive deficits as HD signs and symptoms (Stage 2), and functional decline (Stage 3). One issue for implementation is the possibility that not all variables are measured in every study, and another issue is that the stages are broad and may benefit from progression subgrouping./ Objective: Impute stages of the HD-ISS for observational studies in which missing data precludes direct stage classification, and then define progression subgroups within stages./ Methods: A machine learning algorithm was used to impute stages. Agreement of the imputed stages with the observed stages was evaluated using graphical methods and propensity score matching. Subgroups were defined based on descriptive statistics and optimal cut-point analysis./ Results: There was good overall agreement between the observed stages and the imputed stages, but the algorithm tended to over-assign Stage 0 and under-assign Stage 1 for individuals who were early in progression./ Conclusion: There is evidence that the imputed stages can be treated similarly to the observed stages for large-scale analyses. When imaging data are not available, imputation can be avoided by collapsing the first two stages using the categories of Stage≤1, Stage 2, and Stage 3. Progression subgroups defined within a stage can help to identify groups of more homogeneous individuals.

The vitamin D grey areas in pediatric primary care. Very low serum 25-hydroxyvitamin D levels in asymptomatic children living in northeastern Italy

The principal questions about the vitamin D topic are far to be resolved: in which children 25-hydroxyvitamin D blood testing is appropriate and how much cholecalciferol should be given in the absence of the test? Analyzing vitamin D status in a group of children cared by a "family pediatrician" in northeastern Italy we noted a high incidence of deficiency in asymptomatic preschool children without risk factors. As routine vitamin D testing is not recommended in the average risk population the supplementation with cholecalciferol represents a "grey area" mostly in pediatric primary care

Predictors of vitamin D status and its association with parathyroid hormone in young New Zealand children.

BACKGROUND: Despite increased awareness of the adverse health effects of low vitamin D status, few studies have evaluated 25-hydroxyvitamin D [25(OH)D] status in young children. OBJECTIVES: We aimed to assess vitamin D status on the basis of 25(OH)D and its relation with parathyroid hormone (PTH) and to identify possible predictors of 25(OH)D status in young children living in a country with minimal vitamin D fortification. DESIGN: Serum 25(OH)D and PTH concentrations were measured in a cross-sectional sample of children aged 12-22 mo [n = 193 for 25(OH)D, n = 144 for PTH] living in Dunedin, New Zealand (latitude: 45 degrees S). Anthropometric, dietary, and sociodemographic data were collected. RESULTS: The majority of children sampled in the summer (94%; 47 of 50) had 25(OH)D >50 nmol/L; however, nearly 80% of children sampled in the winter (43 of 55) had serum concentrations 60-65 nmol/L, a plateau in PTH was evident. CONCLUSIONS: Seasonal variation in 25(OH)D concentration implies that postsummer vitamin D stores were insufficient to maintain status >50 nmol/L year-round. Examination of the predictors of 25(OH)D in our model shows few modifiable risk factors, and thus effective dietary strategies may be required if future research determines that children with 25(OH)D concentrations <50 nmol/L are at significant health risk. This trial was registered at www.actr.org.au as ACTRN12605000487617

Discovery of Self-Assembling π\pi-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically-active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from $\pi$-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence-structure-function relations remain poorly characterized. In this work, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically-active $\pi$-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylene vinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20$^3$ = 8,000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems

Pharmacological Investigations of the Dissociative ‘Legal Highs’ Diphenidine, Methoxphenidine and Analogues

1,2-Diarylethylamines including lanicemine, lefetamine, and remacemide have clinical relevance in a range of therapeutic areas including pain management, epilepsy, neurodegenerative disease and depression. More recently 1,2-diarylethylamines have been sold as ‘legal highs’ in a number of different forms including powders and tablets. These compounds are sold to circumvent governmental legislation regulating psychoactive drugs. Examples include the opioid MT-45 and the dissociative agents diphenidine (DPH) and 2-methoxy-diphenidine (2-MXP). A number of fatal and non-fatal overdoses have been linked to abuse of these compounds. As with many ‘legal highs’, little is known about their pharmacology. To obtain a better understanding, the effects of DPH, 2-MXP and its 3- and 4-MeO- isomers, and 2-Cl-diphenidine (2-Cl-DPH) were investigated using binding studies at 46 central nervous system receptors including the N-methyl-D-aspartate receptor (NMDAR), serotonin, dopamine, norepinephrine, histamine, and sigma receptors as well as the reuptake transporters for serotonin, dopamine and norepinephrine. Reuptake inhibition potencies were measured at serotonin, norepinephrine and dopamine transporters. NMDAR antagonism was established in vitro using NMDAR-induced field excitatory postsynaptic potential (fEPSP) experiments. Finally, DPH and 2-MXP were investigated using tests of pre-pulse inhibition of startle (PPI) in rats to determine whether they reduce sensorimotor gating, an effect observed with known dissociative drugs such as phencyclidine (PCP) and ketamine. The results suggest that these 1,2-diarylethylamines are relatively selective NMDAR antagonists with weak off-target inhibitory effects on dopamine and norepinephrine reuptake. DPH and 2-MXP significantly inhibited PPI. DPH showed greater potency than 2-MXP, acting with a median effective dose (ED50) of 9.5 mg/kg, which is less potent than values reported for other commonly abused dissociative drugs such as PCP and ketamine

Predictive rules of efflux inhibition and avoidance in Pseudomonas aeruginosa

Antibiotic-resistant bacteria rapidly spread in clinical and natural environments and challenge our modern lifestyle. A major component of defense against antibiotics in Gram-negative bacteria is a drug permeation barrier created by active efflux across the outer membrane. We identified molecular determinants defining the propensity of small peptidomimetic molecules to avoid and inhibit efflux pumps in Pseudomonas aeruginosa, a human pathogen notorious for its antibiotic resistance.Combining experimental and computational protocols, we mapped the fate of the compounds from structure-activity relationships through their dynamic behavior in solution, permeation across both the inner and outer membranes, and interaction with MexB, the major efflux transporter of P. aeruginosa. We identified predictors of efflux avoidance and inhibition and demonstrated their power by using a library of traditional antibiotics and compound series and by generating new inhibitors of MexB. The identified predictors will enable the discovery and optimization of anti-bacterial agents suitable for treatment of P. aeruginosa infections

Modulation of Tcf7l2 Expression Alters Behavior in Mice

The comorbidity of type 2 diabetes (T2D) with several psychiatric diseases is well established. While environmental factors may partially account for these co-occurrences, common genetic susceptibilities could also be implicated in the confluence of these diseases. In support of shared genetic burdens, TCF7L2, the strongest genetic determinant for T2D risk in the human population, has been recently implicated in schizophrenia (SCZ) risk, suggesting that this may be one of many loci that pleiotropically influence both diseases. To investigate whether Tcf7l2 is involved in behavioral phenotypes in addition to its roles in glucose metabolism, we conducted several behavioral tests in mice with null alleles of Tcf7l2 or overexpressing Tcf7l2. We identified a role for Tcf7l2 in anxiety-like behavior and a dose-dependent effect of Tcf7l2 alleles on fear learning. None of the mutant mice showed differences in prepulse inhibition (PPI), which is a well-established endophenotype for SCZ. These results show that Tcf7l2 alters behavior in mice. Importantly, these differences are observed prior to the onset of detectable glucose metabolism abnormalities. Whether these differences are related to human anxiety-disorders or schizophrenia remains to be determined. These animal models have the potential to elucidate the molecular basis of psychiatric comorbidities in diabetes and should therefore be studied further

Anti-Helicobacter pylori activity and immunostimulatory effect of extracts from Byrsonima crassa Nied. (Malpighiaceae)

<p>Abstract</p> <p>Background</p> <p>Several <it>in vitro </it>studies have looked at the effect of medicinal plant extracts against <it>Helicobacter pylori </it>(<it>H. pylori</it>). Regardless of the popular use of <it>Byrsonima crassa </it>(<it>B. crassa</it>) as antiemetic, diuretic, febrifuge, to treat diarrhea, gastritis and ulcers, there is no data on its effects against <it>H. pylori</it>. In this study, we evaluated the anti-<it>H. pylori </it>of <it>B. crassa </it>leaves extracts and its effects on reactive oxygen/nitrogen intermediates induction by murine peritoneal macrophages.</p> <p>Methods</p> <p>The minimal inhibitory concentration (MIC) was determined by broth microdilution method and the production of hydrogen peroxide (H₂O₂) and nitric oxide (NO) by the horseradish peroxidase-dependent oxidation of phenol red and Griess reaction, respectively.</p> <p>Results</p> <p>The methanolic (MeOH) and chloroformic (CHCl₃) extracts inhibit, <it>in vitro</it>, the growth of <it>H. pylori </it>with MIC value of 1024 μg/ml. The MeOH extract induced the production H₂O₂and NO, but CHCl₃extract only NO.</p> <p>Conclusion</p> <p>Based in our results, <it>B. crassa </it>can be considered a source of compounds with anti-<it>H. pylori </it>activity, but its use should be done with caution in treatment of the gastritis and peptic ulcers, since the reactive oxygen/nitrogen intermediates are involved in the pathogenesis of gastric mucosal injury induced by ulcerogenic agents and <it>H. pylori </it>infections.</p

Bacterial Signatures of Paediatric Respiratory Disease : An Individual Participant Data Meta-Analysis

Introduction: The airway microbiota has been linked to specific paediatric respiratory diseases, but studies are often small. It remains unclear whether particular bacteria are associated with a given disease, or if a more general, non-specific microbiota association with disease exists, as suggested for the gut. We investigated overarching patterns of bacterial association with acute and chronic paediatric respiratory disease in an individual participant data (IPD) meta-analysis of 16S rRNA gene sequences from published respiratory microbiota studies.Methods: We obtained raw microbiota data from public repositories or via communication with corresponding authors. Cross-sectional analyses of the paediatric (10 case subjects were included. Sequence data were processed using a uniform bioinformatics pipeline, removing a potentially substantial source of variation. Microbiota differences across diagnoses were assessed using alpha- and beta-diversity approaches, machine learning, and biomarker analyses.Results: We ultimately included 20 studies containing individual data from 2624 children. Disease was associated with lower bacterial diversity in nasal and lower airway samples and higher relative abundances of specific nasal taxa including Streptococcus and Haemophilus. Machine learning success in assigning samples to diagnostic groupings varied with anatomical site, with positive predictive value and sensitivity ranging from 43 to 100 and 8 to 99%, respectively.Conclusion: IPD meta-analysis of the respiratory microbiota across multiple diseases allowed identification of a non-specific disease association which cannot be recognised by studying a single disease. Whilst imperfect, machine learning offers promise as a potential additional tool to aid clinical diagnosis.Peer reviewe