An Investigation of the Behavioral Mechanisms of Antipsychotic Action Using a Drug-Drug Conditioning Paradigm

Antipsychotic drugs at noncataleptic doses selectively suppress conditioned avoidance response in rats. In our previous study, we had used a two-way active avoidance response paradigm to show that the antipsychotic-induced interoceptive state is one of the mechanisms underlying the avoidance-disruptive effect of antipsychotics. In this study, we sought to further examine this mechanism using a novel drug-drug conditioning procedure. We made use of the fact that both the typical neuroleptic haloperidol and the atypical neuroleptic olanzapine disrupt conditioned avoidance responding, whereas chlordiazepoxide (an anxiolytic) does not. We reasoned that if the antipsychotic interoceptive state is important in causing a disruption on avoidance responding (an index of antipsychotic efficacy), pairing chlordiazepoxide (a cueing drug conditional stimulus) with haloperidol or olanzapine (a cued drug unconditional stimulus) should engender chlordiazepoxide to exhibit this property and behave like an antipsychotic drug. Chlordiazepoxide exhibited an acquired antipsychotic-like property in disrupting avoidance responding after being repeatedly paired with haloperidol, but not with olanzapine. In contrast, it significantly attenuated the antiavoidance efficacy of olanzapine but not haloperidol after being repeatedly paired with these drugs. This study suggests that the haloperidol-induced interoceptive drug state is directly involved in its antiavoidance action, and chlordiazepoxide may attenuate the antiavoidance efficacy of antipsychotics (especially olanzapine). To the extent that the antiavoidance effect predicts clinical effects of antipsychotic treatment, this study suggests that the antipsychotic-induced interoceptive drug state may be an important behavioral mechanism mediating the clinical effects of antipsychotic treatments

Olanzapine and Risperidone Disrupt Conditioned Avoidance Responding in Phencyclidine-Pretreated or Amphetamine-Pretreated Rats by Selectively Weakening Motivational Salience of Conditioned Stimulus

The rat conditioned avoidance response model is a well-established preclinical behavioral model predictive of antipsychotic efficacy. All clinically approved antipsychotic drugs disrupt conditioned avoidance responding – a feature that distinguishes them from other psychotherapeutics. We previously showed that the typical antipsychotic drug haloperidol disrupts avoidance responding by progressively attenuating the motivational salience of the conditioned stimulus (CS) in normal rats. In this study, using two pharmacological rat models of schizophrenia [e.g. phencyclidine (PCP) or amphetamine sensitization], we examined whether atypicals such as olanzapine or risperidone disrupt avoidance responding through the same behavioral mechanism. Rats were first pretreated with PCP, amphetamine, or saline under one of two different injection schedules for either 1 or 3 weeks. They were then trained to acquire avoidance responding to two types of CS (CS1 and CS2) that differed in their ability to predict the occurrence of the unconditioned stimulus. Finally, rats were tested repeatedly under olanzapine (1.0 mg/kg, subcutaneously) or risperidone (0.33 mg/kg, subcutaneously) daily for 5 or 7 consecutive days. We found that repeated olanzapine or risperidone treatment produced a progressive across-session decline in avoidance responding to both CS1 and CS2. Olanzapine and risperidone disrupted the CS2 (a less salient CS) avoidance to a greater extent than the CS1 avoidance. Pretreatment with PCP and amphetamine did not affect the disruptive effect of olanzapine or risperidone on avoidance responding. On the basis of these findings, we suggest that the atypical drugs olanzapine and risperidone, like the typical drug haloperidol, also disrupt avoidance responding primarily by attenuating the motivational salience of the CS

Advances in Antimicrobial Peptide Discovery via Machine Learning and Delivery via Nanotechnology

Antimicrobial peptides (AMPs) have been investigated for their potential use as an alternative to antibiotics due to the increased demand for new antimicrobial agents. AMPs, widely found in nature and obtained from microorganisms, have a broad range of antimicrobial protection, allowing them to be applied in the treatment of infections caused by various pathogenic microorganisms. Since these peptides are primarily cationic, they prefer anionic bacterial membranes due to electrostatic interactions. However, the applications of AMPs are currently limited owing to their hemolytic activity, poor bioavailability, degradation from proteolytic enzymes, and high-cost production. To overcome these limitations, nanotechnology has been used to improve AMP bioavailability, permeation across barriers, and/or protection against degradation. In addition, machine learning has been investigated due to its time-saving and cost-effective algorithms to predict AMPs. There are numerous databases available to train machine learning models. In this review, we focus on nanotechnology approaches for AMP delivery and advances in AMP design via machine learning. The AMP sources, classification, structures, antimicrobial mechanisms, their role in diseases, peptide engineering technologies, currently available databases, and machine learning techniques used to predict AMPs with minimal toxicity are discussed in detail

The Arabidopsis Chromatin-Modifying Nuclear siRNA Pathway Involves a Nucleolar RNA Processing Center

SummaryIn Arabidopsis thaliana, small interfering RNAs (siRNAs) direct cytosine methylation at endogenous DNA repeats in a pathway involving two forms of nuclear RNA polymerase IV (Pol IVa and Pol IVb), RNA-DEPENDENT RNA POLYMERASE 2 (RDR2), DICER-LIKE 3 (DCL3), ARGONAUTE4 (AGO4), the chromatin remodeler DRD1, and the de novo cytosine methyltransferase DRM2. We show that RDR2, DCL3, AGO4, and NRPD1b (the largest subunit of Pol IVb) colocalize with siRNAs within the nucleolus. By contrast, Pol IVa and DRD1 are external to the nucleolus and colocalize with endogenous repeat loci. Mutation-induced loss of pathway proteins causes downstream proteins to mislocalize, revealing their order of action. Pol IVa acts first, and its localization is RNA dependent, suggesting an RNA template. We hypothesize that maintenance of the heterochromatic state involves locus-specific Pol IVa transcription followed by siRNA production and assembly of AGO4- and NRPD1b-containing silencing complexes within nucleolar processing centers

Spenders and Tightwads Among Newlyweds: Perceptions of Partner Financial Behaviors and Relational Well-Being

Finances, and how couples manage their finances, can have important implications for couples’ relational well-being. Using data from 1,585 couples that participated in the CREATE study (a nationally representative dyadic dataset of U.S. newlywed couples), we examined how perceiving one’s spouse as a financial spender (i.e., spending more than they ideally would) or financial tightwad (i.e., spending less than they ideally would) was associated with several measures of relational well-being (i.e., satisfaction, commitment, and power) through actor-partner interdependence structural equation models. Results showed that perceiving one’s partner as a spender was detrimental for both the individual’s and the partner’s marital satisfaction, marital commitment, and marital power. Perceiving one’s partner as a tightwad was detrimental for both the individual’s and the partner’s marital commitment and marital power. The findings suggest that interventions focused on perceptions of financial management behaviors may help strengthen relational well-being among newlyweds

TVL₁ Planarity Regularization for 3D Shape Approximation

The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within. This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy

Improving Potato Stress Tolerance and Tuber Yield Under a Climate Change Scenario – A Current Overview

Global climate change in the form of extreme heat and drought poses a major challenge to sustainable crop production by negatively affecting plant performance and crop yield. Such negative impact on crop yield is likely to be aggravated in future because continued greenhouse gas emissions will cause further rise in temperature leading to increased evapo-transpiration and drought severity, soil salinity as well as insect and disease threats. This has raised a major challenge for plant scientists on securing global food demand, which urges an immediate need to enhance the current yield of major food crops by two-fold to feed the increasing population. As a fourth major food crop, enhancing potato productivity is important for food security of an increasing population. However, potato plant is highly prone to high temperature, drought, soil salinity, as well as insect and diseases. In order to maintain a sustainable potato production, we must adapt our cultivation practices and develop stress tolerant potato cultivars that are appropriately engineered for changing environment. Yet the lack of data on the underlying mechanisms of potato plant resistance to abiotic and biotic stress and the ability to predict future outcomes constitutes a major knowledge gap. It is a challenge for plant scientists to pinpoint means of improving tuber yield under increasing CO2, high temperature and drought stress including the changing patterns of pest and pathogen infestations. Understanding stress-related physiological, biochemical and molecular processes is crucial to develop screening procedures for selecting crop cultivars that can better adapt to changing growth conditions. Elucidation of such mechanism may offer new insights into the identification of specific characteristics that may be useful in breeding new cultivars aimed at maintaining or even enhancing potato yield under changing climate. This paper discusses the recent progress on the mechanism by which potato plants initially sense the changes in their surrounding CO2, temperature, water status, soil salinity and consequently respond to these changes at the molecular, biochemical and physiological levels. We suggest that future research needs to be concentrated on the identification and characterization of signaling molecules and target genes regulating stress tolerance and crop yield potential

Observation of Parametric Instability in Advanced LIGO

Parametric instabilities have long been studied as a potentially limiting effect in high-power interferometric gravitational wave detectors. Until now, however, these instabilities have never been observed in a kilometer-scale interferometer. In this work we describe the first observation of parametric instability in an Advanced LIGO detector, and the means by which it has been removed as a barrier to progress

Genomics of Divergence along a Continuum of Parapatric Population Differentiation

MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1)

Comparison of results from tests of association in unrelated individuals with uncollapsed and collapsed sequence variants using tiled regression

Tiled regression is an approach designed to determine the set of independent genetic variants that contribute to the variation of a quantitative trait in the presence of many highly correlated variants. In this study, we evaluate the statistical properties of the tiled regression method using the Genetic Analysis Workshop 17 data in unrelated individuals for traits Q1, Q2, and Q4. To increase the power to detect rare variants, we use two methods to collapse rare variants and compare the results with those from the uncollapsed data. In addition, we compare the tiled regression method to traditional tests of association with and without collapsed rare variants. The results show that collapsing rare variants generally improves the power to detect associations regardless of method, although only variants with the largest allelic effects could be detected. However, for traditional simple linear regression, the average estimated type I error is dependent on the trait and varies by about three orders of magnitude. The estimated type I error rate is stable for tiled regression across traits