Bioprospective Role of Ocimum sanctum and Solanum xanthocarpum against Emerging Pathogen: Mycobacterium avium Subspecies paratuberculosis: A Review

Mycobacterium avium subspecies paratuberculosis (MAP) is a chronic, contagious, and typically life-threatening enteric disease of ruminants caused by a bacterium of the genus Mycobacterium, but it can also affect non-ruminant animals. MAP transmission occurs through the fecal-oral pathway in neonates and young animals. After infection, animals generate IL-4, IL-5, and IL-10, resulting in a Th2 response. Early detection of the disease is necessary to avoid its spread. Many detection methods, viz., staining, culture, and molecular methods, are available, and numerous vaccines and anti-tuberculosis drugs are used to control the disease. However, the prolonged use of anti-tuberculosis drugs leads to the development of resistance. Whereas vaccines hamper the differentiation between infected and vaccinated animals in an endemic herd. This leads to the identification of plant-based bioactive compounds to treat the disease. Bioactive compounds of Ocimum sanctum and Solanum xanthocarpum have been evaluated for their anti-MAP activity. Based on the MIC50 values, Ursolic acid (12 µg/mL) and Solasodine (60 µg/mL) were found to be suitable for anti-MAP activity.

Ursolic Acid and Solasodine as Potent Anti-Mycobacterial Agents for Combating Paratuberculosis: An Anti-Inflammatory and In Silico Analysis

Mycobacterium avium subspecies paratuberculosis (MAP) infection in domestic livestock causes persistent diarrhea, weight loss, and death and is also a potential cause of Crohn's disease (CD) in humans; notably, treatments against MAP are insufficient, costly, and can cause adverse reactions. Hence, plant-derived bioactive constituents have been taken into consideration in this regard. Herein, we present the results of two bioactive constituents (Solasodine and Ursolic acid) that were evaluated for their safety and efficacy against MAP protein (Dephospho-Coenzyme A kinase (DPCK) by utilizing in vitro assays and different tools of in silico biology. The ADME/t-test, the drug-likeness property test, pharmacophore modelling, and PASS prediction have proven that both the constituents have better binding capacities than the available antibiotic drugs used to target protein inhibition pathways. Through our observations, it can be inferred that these two phytochemicals can be adequately used to treat paratuberculosis, thereby combating inflammatory bowel disorders (IBD) of an autoimmune nature.

Category effects on stimulus estimation: Shifting and skewed frequency distributions-A reexamination

Duffy, Huttenlocher, Hedges, and Crawford (Psychonomic Bulletin & Review, 17(2), 224-230, 2010) report on experiments where participants estimate the lengths of lines. These studies were designed to test the category adjustment model (CAM), a Bayesian model of judgments. The authors report that their analysis provides evidence consistent with CAM: that there is a bias toward the running mean and not recent stimuli. We reexamine their data. First, we attempt to replicate their analysis, and we obtain different results. Second, we conduct a different statistical analysis. We find significant recency effects, and we identify several specifications where the running mean is not significantly related to judgment. Third, we conduct tests of auxiliary predictions of CAM. We do not find evidence that the bias toward the mean increases with exposure to the distribution. We also do not find that responses longer than the maximum of the distribution or shorter than the minimum become less likely with greater exposure to the distribution. Fourth, we produce a simulated dataset that is consistent with key features of CAM, and our methods correctly identify it as consistent with CAM. We conclude that the Duffy et al. (2010) dataset is not consistent with CAM. We also discuss how conventions in psychology do not sufficiently reduce the likelihood of these mistakes in future research. We hope that the methods that we employ will be used to evaluate other datasets.

Suboptimality in perceptual decision making

Human perceptual decisions are often described as optimal. Critics of this view have argued that claims of optimality are overly flexible and lack explanatory power. Meanwhile, advocates for optimality have countered that such criticisms single out a few selected papers. To elucidate the issue of optimality in perceptual decision making, we review the extensive literature on suboptimal performance in perceptual tasks. We discuss eight different classes of suboptimal perceptual decisions, including improper placement, maintenance, and adjustment of perceptual criteria; inadequate tradeoff between speed and accuracy; inappropriate confidence ratings; misweightings in cue combination; and findings related to various perceptual illusions and biases. In addition, we discuss conceptual shortcomings of a focus on optimality, such as definitional difficulties and the limited value of optimality claims in and of themselves. We therefore advocate that the field drop its emphasis on whether observed behavior is optimal and instead concentrate on building and testing detailed observer models that explain behavior across a wide range of tasks. To facilitate this transition, we compile the proposed hypotheses regarding the origins of suboptimal perceptual decisions reviewed here. We argue that verifying, rejecting, and expanding these explanations for suboptimal behavior - rather than assessing optimality per se - should be among the major goals of the science of perceptual decision making.