An Evaluation of 10 Percent and 20 Percent Benzocaine Gels in Patients With Acute Toothaches: Efficacy, Tolerability and Compliance With Label Dose Administration Directions

Background The authors evaluated the efficacy and tolerability of 10 percent and 20 percent benzocaine gels compared with those of a vehicle (placebo) gel for the temporary relief of toothache pain. They also assessed the compliance with the label dose administration directions on the part of participants with toothache pain. Methods Under double-masked conditions, 576 participants self-applied study gel to an open tooth cavity and surrounding oral tissues. Participants evaluated their pain intensity and pain relief for 120 minutes. The authors determined the amount of gel the participants applied. Results The responders’ rates (the primary efficacy parameter), defined as the percentage of participants who had an improvement in pain intensity as exhibited by a pain score reduction of at least one unit on the dental pain scale from baseline for two consecutive assessments any time between the five- and 20-minute points, were 87.3 percent, 80.7 percent and 70.4 percent, respectively, for 20 percent benzocaine gel, 10 percent benzocaine gel and vehicle gel. Both benzocaine gels were significantly (P ≤ .05) better than vehicle gel; the 20 percent benzocaine gel also was significantly (P ≤ .05) better than the 10 percent benzocaine gel. The mean amount of gel applied was 235.6 milligrams, with 88.2 percent of participants applying 400 mg or less. Conclusions Both 10 percent and 20 percent benzocaine gels were more efficacious than the vehicle gel, and the 20 percent benzocaine gel was more efficacious than the 10 percent benzocaine gel. All treatments were well tolerated by participants. Practical Implications Patients can use 10 percent and 20 percent benzocaine gels to temporarily treat toothache pain safely

RON5 is critical for organization and function of the Toxoplasma moving junction complex

Apicomplexans facilitate host cell invasion through formation of a tight-junction interface between parasite and host plasma membranes called the moving junction (MJ). A complex of the rhoptry neck proteins RONs 2/4/5/8 localize to the MJ during invasion where they are believed to provide a stable anchoring point for host penetration. During the initiation of invasion, the preformed MJ RON complex is injected into the host cell where RON2 spans the host plasma membrane while RONs 4/5/8 localize to its cytosolic face. While much attention has been directed toward an AMA1-RON2 interaction supposed to occur outside the cell, little is known about the functions of the MJ RONs positioned inside the host cell. Here we provide a detailed analysis of RON5 to resolve outstanding questions about MJ complex organization, assembly and function during invasion. Using a conditional knockdown approach, we show loss of RON5 results in complete degradation of RON2 and mistargeting of RON4 within the parasite secretory pathway, demonstrating that RON5 plays a key role in organization of the MJ RON complex. While RON8 is unaffected by knockdown of RON5, these parasites are unable to invade new host cells, providing the first genetic demonstration that RON5 plays a critical role in host cell penetration. Although invasion is not required for injection of rhoptry effectors into the host cytosol, parasites lacking RON5 also fail to form evacuoles suggesting an intact MJ complex is a prerequisite for secretion of rhoptry bulb contents. Additionally, while the MJ has been suggested to function in egress, disruption of the MJ complex by RON5 depletion does not impact this process. Finally, functional complementation of our conditional RON5 mutant reveals that while proteolytic separation of RON5 N- and C-terminal fragments is dispensable, a portion of the C-terminal domain is critical for RON2 stability and function in invasion

The developmental impact of prenatal stress, prenatal dexamethasone and postnatal social stress on physiology, behaviour and neuroanatomy of primate offspring: studies in rhesus macaque and common marmoset

RATIONALE: Exposure of the immature mammalian brain to stress factors, including stress levels of glucocorticoids, either prenatally or postnatally, is regarded as a major regulatory factor in short- and long-term brain function and, in human, as a major aetiological factor in neuropsychiatric disorders. Experimental human studies are not feasible and animal studies are required to demonstrate causality and elucidate mechanisms. A number of studies have been conducted and reviewed in rodents but there are relatively few studies in primates. OBJECTIVES: Here we present an overview of our published studies and some original data on the effects of: (1) prenatal stress on hypothalamic-pituitary-adrenal (HPA) re/activity and hippocampus neuroanatomy in juvenile-adolescent rhesus macaques; (2) prenatal dexamethasone (DEX) on HPA activity, behaviour and prefrontal cortex neuroanatomy in infant-adolescent common marmosets; (3) postnatal daily parental separation stress on HPA re/activity, behaviour, sleep and hippocampus and prefrontal cortex neuroanatomy in infant-adolescent common marmoset. RESULTS: Prenatal stress increased basal cortisol levels and reduced neurogenesis in macaque. Prenatal DEX was without effect on HPA activity and reduced social play and skilled motor behaviour in marmoset. Postnatal social stress increased basal cortisol levels, reduced social play, increased awakening and reduced hippocampal glucocorticoid and mineralocorticoid receptor expression in marmoset. CONCLUSIONS: Perinatal stress-related environmental events exert short- and long-term effects on HPA function, behaviour and brain status in rhesus macaque and common marmoset. The mechanisms mediating the enduring effects remain to be elucidated, with candidates including increased basal HPA function and epigenetic programming

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead