A green Hibiscus cannabinus oil emollient cream for potential topical applications

A green emollient cream with Hibiscus cannabinus seed oil and an alkyl polyglucoside surfactant has been formulated. It can serve as biological alternatives to synthetic formulations that normally incorporate chemical constituents as surfactants and stabilizers mainly to increase consumer compliance in terms of textural and visual aesthetics. FAME analysis of the oil showed the presence octanoic and decanoic acids. The cream after formulation and ultrasonication, presented a smooth and soft appearance with visual and textural appeal. It showed a mean particle size of 138 nm with a zeta potential of -59.2 mV and an electrophoretic mobility of -0.000459 cm2/Vs. Its SEM image projected well dispersed oil globules in water. FTIR spectrum showed extensive hydrogen bonding. Accelerated stability tests under conditions of freeze thawing, heating cooling and centrifugation revealed no cracking, creaming or phase separation. Similar results were observed during the shelf life studies. It is concluded that this Hibiscus cannabinus cream can be utilized as an emollient base for loading cosmopharmaceutic ingredients for their topical delivery, without any toxicity concerns, as it is formulated from completely natural constituents

Multimodal information processing and associative learning in the insect brain

The study of sensory systems in insects has a long-spanning history of almost an entire century. Olfaction, vision, and gustation are thoroughly researched in several robust insect models and new discoveries are made every day on the more elusive thermo- and mechano-sensory systems. Few specialized senses such as hygro- and magneto-reception are also identified in some insects. In light of recent advancements in the scientific investigation of insect behavior, it is not only important to study sensory modalities individually, but also as a combination of multimodal inputs. This is of particular significance, as a combinatorial approach to study sensory behaviors mimics the real-time environment of an insect with a wide spectrum of information available to it. As a fascinating field that is recently gaining new insight, multimodal integration in insects serves as a fundamental basis to understand complex insect behaviors including, but not limited to navigation, foraging, learning, and memory. In this review, we have summarized various studies that investigated sensory integration across modalities, with emphasis on three insect models (honeybees, ants and flies), their behaviors, and the corresponding neuronal underpinnings

Optimization of CMT Welding Parameters of Stellite-6 on AISI316L Alloy Using TOPSIS Method

This article discusses the welding parameters optimization to find the quality of stellite-6 cladding on AISI304L austenite alloy using a new optimization method called Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The experiments (31 nos.) were carried out with the cold metal arc transfer welding method (CMT) based on the central composite design (CCD). The cladding material is the stellite-6 alloy which is appreciated for its corrosion and wear resistance. Four factors (welding current, voltage, welding speed and torch angle) and five levels were considered for the experiment and the optimization. It is necessary to find the optimized parameters for the industrial applications as a huge number of experiments are not recommended. The optimization results showed that the 2nd experiment had the 1st rank with high relative closeness and the 19th experiment was in the last rank. Higher current and low welding speed yielded good results and a low corrosion rate of 0.004582 mm/yr. Furthermore, the Micro-structural, Corrosion study and the SEM-EDS of the specimen produced by the 2nd experiment are discussed here. EDS study showed the presence of Cr and Co elements in the cladding region with maximum

Optimization of CMT Welding Parameters of Stellite-6 on AISI316L Alloy Using TOPSIS Method

This article discusses the welding parameters optimization to find the quality of stellite-6 cladding on AISI304L austenite alloy using a new optimization method called Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The experiments (31 nos.) were carried out with the cold metal arc transfer welding method (CMT) based on the central composite design (CCD). The cladding material is the stellite-6 alloy which is appreciated for its corrosion and wear resistance. Four factors (welding current, voltage, welding speed and torch angle) and five levels were considered for the experiment and the optimization. It is necessary to find the optimized parameters for the industrial applications as a huge number of experiments are not recommended. The optimization results showed that the 2nd experiment had the 1st rank with high relative closeness and the 19th experiment was in the last rank. Higher current and low welding speed yielded good results and a low corrosion rate of 0.004582 mm/yr. Furthermore, the Micro-structural, Corrosion study and the SEM-EDS of the specimen produced by the 2nd experiment are discussed here. EDS study showed the presence of Cr and Co elements in the cladding region with maximum

Spatial fluctuations at vertices of epithelial layers: quantification of regulation by Rho pathway

In living matter, shape fluctuations induced by acto-myosin are usually studied in vitro via reconstituted gels, whose properties are controlled by changing the concentrations of actin, myosin and cross-linkers. Such an approach deliberately avoids to consider the complexity of biochemical signaling inherent to living systems. Acto-myosin activity inside living cells is mainly regulated by the Rho signaling pathway which is composed of multiple layers of coupled activators and inhibitors. We investigate how such a pathway controls the dynamics of confluent epithelial tissues by tracking the displacements of the junction points between cells. Using a phenomenological model to analyze the vertex fluctuations, we rationalize the effects of different Rho signaling targets on the emergent tissue activity by quantifying the effective diffusion coefficient, the persistence time and persistence length of the fluctuations. Our results reveal an unanticipated correlation between layers of activation/inhibition and spatial fluctuations within tissues. Overall, this work connects the regulation via biochemical signaling with mesoscopic spatial fluctuations, with potential application to the study of structural rearrangements in epithelial tissues.Comment: 8 pages, 3 figure

The Inferred Cardiogenic Gene Regulatory Network in the Mammalian Heart

Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was applied to time-course microarray data obtained from the developing mouse heart. Approximately 200 genes of interest were input into the algorithm to generate putative network topologies that are capable of explaining the experimental data via model simulation. To cull specious network interactions, thousands of putative networks are merged and filtered to generate scale-free, hierarchical networks that are statistically significant and biologically relevant. The networks are validated with known gene interactions and used to predict regulatory pathways important for the developing mammalian heart. Area under the precision-recall curve and receiver operator characteristic curve are 9% and 58%, respectively. Of the top 10 ranked predicted interactions, 4 have already been validated. The algorithm is further tested using a network enriched with known interactions and another depleted of them. The inferred networks contained more interactions for the enriched network versus the depleted network. In all test cases, maximum performance of the algorithm was achieved when the purely data-driven method of network inference was combined with a data-independent, functional-based association method. Lastly, the network generated from the list of approximately 200 genes of interest was expanded using gene-profile uniqueness metrics to include approximately 900 additional known mouse genes and to form the most likely cardiogenic gene regulatory network. The resultant network supports known regulatory interactions and contains several novel cardiogenic regulatory interactions. The method outlined herein provides an informative approach to network inference and leads to clear testable hypotheses related to gene regulation