Non-interactive Action Research Articles

Synthesis and characterization of smart stimuli-responsive herbal drug-encapsulated nanoniosome particles for efficient treatment of breast cancer

Abstract Extraction from the herbs was performed using the Soxhlet method. Various formula was synthesized for niosomes containing the extracts through thin film synthesis technique, and the most efficient formulation was selected. Afterwards, physicochemical properties of niosomes, including size, polydispersity index (PDI), zeta potential, morphology, encapsulation efficacy (EE%), extract release rate, non-interactive action between the extracts and niosomes, antibacterial potential, and cellular uptake were assessed. Finally, the toxicity level of the niosomes to breast cancer cells was compared and their impact on the expression of p53 and MCL-1 was evaluated. Our data demonstrated that the synthesized niosomes were sensitive to the temperature and pH. Also, the niosomes containing Hedera Helix extract (Nio-HHE) sized 97.7 nm, with a zeta potential of −19.9 ± 6.7 mV, PDI of 0.35, and 58 ± 2.4% encapsulation efficacy showed more toxicity to the cancer cells than the niosomes of Glycyrrhiza glabra extract (Nio-GGE) with the size of 111 ± 8.5 nm, zeta potential of −23.5 ± 4.5 mV, PDI of 0.113, and 69 ± 1.2% encapsulation efficacy. The former system proved to have more antibacterial potential, and affect the expression of the oncogenes more than the latter. Meanwhile, both niosomal systems demonstrated an acceptable cellular uptake, and no chemical interaction with the extracts was observed. Furthermore, useful function of the synthesized niosomes was confirmed by morphological assessments. Our data confirmed that encapsulation of herbal extracts improves their anticancer and antibacterial potential. We concluded that Nio-HHE has more significant antitumor effects on breast cancer cells than Nio-GGE. Consequently, applying nano drug delivery systems based on herbal therapy could mitigate the side effects resulting from chemotherapy and radiotherapy, and offer promising perspectives for treatment of breast cancer.

Evidence for a dyadic motor plan in joint action

What mechanisms distinguish interactive from non-interactive actions? To answer this question we tested participants while they took turns playing music with a virtual partner: in the interactive joint action condition, the participants played a melody together with their partner by grasping (C note) or pressing (G note) a cube-shaped instrument, alternating in playing one note each. In the non-interactive control condition, players’ behavior was not guided by a shared melody, so that the partner’s actions and notes were irrelevant to the participant. In both conditions, the participant’s and partner’s actions were physically congruent (e.g., grasp-grasp) or incongruent (e.g., grasp-point), and the partner’s association between actions and notes was coherent with the participant’s or reversed. Performance in the non-interactive condition was only affected by physical incongruence, whereas joint action was only affected when the partner’s action-note associations were reversed. This shows that task interactivity shapes the sensorimotor coding of others’ behaviors, and that joint action is based on active prediction of the partner’s action effects rather than on passive action imitation. We suggest that such predictions are based on Dyadic Motor Plans that represent both the agent’s and the partner’s contributions to the interaction goal, like playing a melody together.

Neural responses to visually observed social interactions

Success in the social world requires the ability to perceive not just individuals and their actions, but pairs of people and the interactions between them. Despite the complexity of social interactions, humans are adept at interpreting those interactions they observe. Although the brain basis of this remarkable ability has remained relatively unexplored, converging functional MRI evidence suggests the posterior superior temporal sulcus (pSTS) is centrally involved. Here, we sought to determine whether this region is sensitive to both the presence of interactive information, as well as to the content of qualitatively different interactions (i.e. competition vs. cooperation). Using point-light human figure stimuli, we demonstrate that the right pSTS is maximally activated when contrasting dyadic interactions vs. dyads performing independent, non-interactive actions. We then used this task to localize the same pSTS region in an independent participant group, and tested responses to non-human moving shape stimuli (i.e. two circles’ movements conveying either interactive or non-interactive behaviour). We observed significant support vector machine classification for both the presence and type of interaction (i.e. interaction vs. non-interaction, and competition vs. cooperation, respectively) in the pSTS, as well as neighbouring temporo-parietal junction (TPJ). These findings demonstrate the important role that these regions play in perceiving and understanding social interactions, and lay the foundations for further research to fully characterize interaction responses in these areas.

Social Interactions Receive Priority to Conscious Perception.

Humans are social animals, constantly engaged with other people. The importance of social thought and action is hard to overstate. However, is social information so important that it actually determines which stimuli are promoted to conscious experience and which stimuli are suppressed as invisible? To address this question, we used a binocular rivalry paradigm, in which the two eyes receive different action stimuli. In two experiments we measured the conscious percept of rival actions and found that actions engaged in social interactions are granted preferential access to visual awareness over non-interactive actions. Lastly, an attentional task that presumably engaged the mentalizing system enhanced the priority assigned to social interactions in reaching conscious perception. We also found a positive correlation between human identification of interactive activity and the promotion of socially-relevant information to visual awareness. The present findings suggest that the visual system amplifies socially-relevant sensory information and actively promotes it to consciousness, thereby facilitating inferences about social interactions.

Distant Human Interaction Recognition with Kinect

Detecting human interactions in a public place where no physical touch occurs has important applications in many surveillance tasks. In this paper, we explore the possibilities to automatically detect such distant human interactions without recognizing the specific human actions. Specifically, we use a highly simplified formulation of the interaction in this paper: 1) when a person does not interact with others, he always performs a non-interactive action that is largely periodical, such as walking, 2) when two persons interact with each other, they both perform a same short-duration interactive action, such as waving hand, that are different from their non-interactive actions. Based on this formulation, we develop a new approach to localize the subvideos that describes the interactive actions from Kinect videos, which provide both the RGB and depth information. We then develop a new approach to compare the pose and kinematic features in these subvideos (from different people) to see whether they describe a same interactive action. Without any supervised learning and action recognition, the proposed approaches are not limited to a specified set of interactive and non-interactive actions. In the experiments, we justify the performance of the proposed approaches on 100 Kinect videos with 10 different interactive actions.

A Unified Theory for Quantal Responses to Mixtures of Drugs: Non-Interactive Action

In 1952 we considered how the quantal responses in groups of organisms can be expressed as functions of the doses of two poisons administered together, and what we wrote applies to drugs in general. Our aim was a general theory for the interpretation of data of this kind, a theory properly related to the underlying mechanisms of joint drug action. So far as we know, advance in this field has since been confined to Ashford's [1958] alternative method of deriving an equation for simple similar action. Sampford [1952] made progress in the allied field of response-time distributions for drug mixtures. Despite criticisms (see discussion) we maintain that our approach to the problem was sound, though now think that it was not sustained adequately because, as explained below, the results lacked unity. This paper is the first of a series in which a unified theory is presented. Many of the equations obtained before remain, but as special cases of new ones; the latter clear away difficulties, and should enable a wider variety of data to be interpreted. The biological mechanism of joilnt action can vary according to the pair of drugs, and the relation between the quantal response and the jointly applied doses differs according to this mechanism. Thus in our previous paper (Plackett and Hewlett [1952]) we set up biological models of joint action, and deduced the relations, i.e. mathematical models, from them. The s;et of biological models sprang from a twoway classification. The joint action was defined as similar or dissimilar according as the sites of primary action in the organism were the same