Phase Shifts of the Circadian Locomotor Rhythm Induced by Pigment-Dispersing Factor in the Cricket Gryllus bimaculatus

Pigment-dispersing factors (PDFs) are octadeca-peptides widely distributed in insect optic lobes and brain. In this study, we have purified PDF and determined its amino acid sequence in the cricket Gryllus bimaculatus. Its primary structure was NSEIINSLLGLPKVLNDA-NH2, homologous to other PDH family members so far reported. When injected into the optic lobe of experimentally blinded adult male crickets, Gryllus-PDF induced phase shifts in their activity rhythms in a phase dependent and dose dependent manner. The resulted phase response curve (PRC) showed delays during the late subjective night to early subjective day and advances during the mid subjective day to mid subjective night. The PRC was different in shape from those for light, serotonin and temperature. These results suggest that PDF plays a role in phase regulation of the circadian clock through a separate pathway from those of other known phase regulating agents

I/O Workload in Virtualized Data Center Using Hypervisor

Cloud computing [10] is gaining popularity as it’s the way to virtualize the datacenter and increase flexibility in the use of computation resources. This virtual machine approach can dramatically improve the efficiency, power utilization and availability of costly hardware resources, such as CPU and memory. Virtualization in datacenter had been done in the back end of Eucalyptus software and Front end was installed on another CPU. The operation of performance measurement had been done in network I/O applications environment of virtualized cloud. Then measurement was analyzed based on performance impact of co-locating applications in a virtualized cloud in terms of throughput and resource sharing effectiveness, including the impact of idle instances on applications that are running concurrently on the same physical host. This project proposes the virtualization technology which uses the hypervisor to install the Eucalyptus software in single physical machine for setting up a cloud computing environment. By using the hypervisor, the front end and back end of eucalyptus software will be installed in the same machine. The performance will be measured based on the interference in parallel processing of CPU and network intensive workloads by using the Xen Virtual Machine Monitors. The main motivation of this project is to provide the scalable virtualized datacenter

Evaluation of Abelmoschus moschatus seed extract in psychiatric and neurological disorders

Background: Abelmoschus moschatus is an aromatic and medicinal plant, used as traditional medicine in the Thirunelveli district and distributed in many parts of Asia, including India. The present study was aimed to evaluate central nervous system (CNS) activities of ethanolic seed extract of A. moschatus (AEAM).Methods: Oral administration of AEAM at doses of 200 and 400 mg/kg on various behavioral models forced swim, tail suspension, light-dark box, hole-board, elevated-plus-maze, locomotor, strychnine, maximal electroshock induced seizure, pentylenetetrazole (PTZ), rotarod, climbing an inclined screen models were utilized.Results: In the open field test, AEAM (200 and 400 mg/kg) increased the numbers of rearing. However, the number of central motor and ambulation were reduced. The number of entries and the time spent in the open arm were increased, whereas the number of locomotion was decreased (p<0.001) in elevated-plus-maze and actophotometer test, respectively. AEAM (200 and 400 mg/kg) protected the mice against the PTZ and strychnine-induced convulsions; it causes significant dose-dependent increase in latency of convulsion. Treatment with AEAM reduced the duration of the tonic hind limb extension, increased the hypnotics time and decreased motor co-ordination of experimental animals.Conclusion: This study concludes A. moschatus is an alternative source for CNS drug development

Relationship between period and phase angle differences in Mus booduga under abrupt versus gradual light-dark transitions

This article does not have an abstract

Chronobiotic effect of melatonin following phase shift of light/dark cycles in the field mouse Mus booduga

The objective of this study was to assess whether melatonin accelerates the re-entrainment of locomotor activity after 6 h of advance and delay phase shifts following exposure to LD 12:12 cycle (simulating jet-lag/shift work). An experimental group of adult male field mice Mus booduga were subjected to melatonin (1 mg/kg) through i.p. and the control group were treated with 50 % DMSO. The injections were administered on three consecutive days following 6h of phase advance and delay, at the expected time of "lights off". The results show that melatonin accelerates the re-entrainment after phase advance (29%) when compared with control mice. In the 6 h phase delay study, the experimental mice (melatonin administered) take more cycles for re-entrainment (51%) than the control. Further, the results suggest that though melatonin may be useful for the treatment of jet-lag caused by eastward flight (phase advance) it may not be useful for westward flight (phase delay) jet-lag

Optimization of machining parameters in turning operation using combined TOPSIS and AHP method

Optimizacija s više ciljeva važno je pitanje u složenim industrijskim problemima. U ovom eksperimentalnom istraživanju, optimalni parametri obrade određivani su pri tokarenju EN25 čelika s alatima od tvrdog metalnog karbida primjenom kombinacije metode TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) i AHP (Analytic Hierarchy Process). To je metoda optimizacije s više ciljeva, primijenjena kako bi se istovremeno do minimuma smanjila mikro tvrdoća, površinska tvrdoća, a do maksimuma povećao učinak odvajanja čestica (MRR). Rezultat pokazuje učinkovitost tog pristupa. Ova se metoda može primijeniti u svim postupcima obrade s istovremeno većim brojem ciljeva.Multi objective optimization is an important issue in complex industrial problems. In this experimental study, optimum machining parameters are determined in turning operation of EN25 steel with coated carbide tools using combined Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) method. This technique is a multi-objective optimization method which has been adopted to simultaneously minimize micro hardness, surface roughness and maximize material removal rate (MRR). The result indicates the effectiveness of this approach. This method is applicable to all machining operations with greater number of objectives simultaneously

Enhancing clinical decision-making with cloud-enabled integration of image-driven insights

Using the complementary strengths of Bayesian networks, decision trees, artificial neural networks (ANNs), and Markov models, this endeavor intends to completely revamp clinical decision-making. In order to provide instantaneous access to image-driven insights and clinical decision support systems (CDSS), want to create a revolutionary framework that merges these cutting-edge methods with cloud-enabled technologies. The proposed framework gives a comprehensive perspective of patient data by merging the probabilistic reasoning of Bayesian networks with the interpretability of decision trees, the pattern recognition abilities of ANNs, and the temporal interdependence of Markov models. This helps doctors to make more educated judgments based on a larger spectrum of information, leading to better patient outcomes. Healthcare workers can get to vital data from any place because to the cloud-enabled architecture's seamless scalability and accessibility. This not only increases the efficiency of decision-making, but also improves communication and cooperation between different medical professionals. This uses cutting-edge modeling strategies and cloud computing to pave a new path in clinical decision-making. This system has the potential to greatly enhance healthcare by integrating image-driven insights with CDSS, to the advantage of both patients and healthcare practitioners

The Effect Of Polyherbal Formulation -PHF On Experimentally Induced Reflux Esophagitis In Rats

ABSTRACT The science of life-Ayurveda is practiced in India since time immemorial. Besides being cheap and easily available, Ayurvedic drugs are considered as safe. Moreover, there is surge in the interest in Ayurveda due to quest of alternative medicines. In Ayurvedic system of medicine, Polyherbal formulations were frequently used to enhance the activity or counteract the toxic effect of compounds, from other plants, but may also act synergistically with other constituents from the same plants. Gastro esophageal reflux disease is a disorder of defense mechanism at the esophageal junction, caused by regurgitation of the gastric contents especially of gastric acid. The purpose of the study was to investigate the effect of Poly Herbal Formulation (PHF) on experimentally induced reflux esophagitis and gastrointestinal motility in animals. The PHF consists of seven medicinal plants namely Aegle marmelos, Elettaria cardamomum, Glycyrrhiza glabra , Citrus aurantifolia, Rosa damascena, Cissus quadrangularis and Saccharum officinarum. Based on acute toxicity study the PHF was considered as safe and 3 dose (100, 200 and 400 mg/kg) levels were employed for pharmacological evaluation. The test drugs were administered orally by suspending in 1% carboxy methyl cellulose solution. The PHF exhibited (P&lt;0.001) significant decrease in lesion index and enhance the % protection of lesion in experimentally induced reflux esophagitis at all the 3 doses in rats. In charcoal meal gastrointestinal transit test, PHF dose-dependently propelled the charcoal meal travel through the small intestines in mice. The study indicates that the PHF has protective effect against surgically induced reflux esophagitis

Leveraging Genomic Associations in Precision Digital Care for Weight Loss: Cohort Study

Background: The COVID-19 pandemic has highlighted the urgency of addressing an epidemic of obesity and associated inflammatory illnesses. Previous studies have demonstrated that interactions between single-nucleotide polymorphisms (SNPs) and lifestyle interventions such as food and exercise may vary metabolic outcomes, contributing to obesity. However, there is a paucity of research relating outcomes from digital therapeutics to the inclusion of genetic data in care interventions. Objective: This study aims to describe and model the weight loss of participants enrolled in a precision digital weight loss program informed by the machine learning analysis of their data, including genomic data. It was hypothesized that weight loss models would exhibit a better fit when incorporating genomic data versus demographic and engagement variables alone. Methods: A cohort of 393 participants enrolled in Digbi Health’s personalized digital care program for 120 days was analyzed retrospectively. The care protocol used participant data to inform precision coaching by mobile app and personal coach. Linear regression models were fit of weight loss (pounds lost and percentage lost) as a function of demographic and behavioral engagement variables. Genomic-enhanced models were built by adding 197 SNPs from participant genomic data as predictors and refitted using Lasso regression on SNPs for variable selection. Success or failure logistic regression models were also fit with and without genomic data. Results: Overall, 72.0% (n=283) of the 393 participants in this cohort lost weight, whereas 17.3% (n=68) maintained stable weight. A total of 142 participants lost 5% bodyweight within 120 days. Models described the impact of demographic and clinical factors, behavioral engagement, and genomic risk on weight loss. Incorporating genomic predictors improved the mean squared error of weight loss models (pounds lost and percent) from 70 to 60 and 16 to 13, respectively. The logistic model improved the pseudo R 2 value from 0.193 to 0.285. Gender, engagement, and specific SNPs were significantly associated with weight loss. SNPs within genes involved in metabolic pathways processing food and regulating fat storage were associated with weight loss in this cohort: rs17300539_G (insulin resistance and monounsaturated fat metabolism), rs2016520_C (BMI, waist circumference, and cholesterol metabolism), and rs4074995_A (calcium-potassium transport and serum calcium levels). The models described greater average weight loss for participants with more risk alleles. Notably, coaching for dietary modification was personalized to these genetic risks. Conclusions: Including genomic information when modeling outcomes of a digital precision weight loss program greatly enhanced the model accuracy. Interpretable weight loss models indicated the efficacy of coaching informed by participants’ genomic risk, accompanied by active engagement of participants in their own success. Although large-scale validation is needed, our study preliminarily supports precision dietary interventions for weight loss using genetic risk, with digitally delivered recommendations alongside health coaching to improve intervention efficac