INFLUENCE OF STRESS AND FLUOXETINE ON IMMOBILITY PERIOD OF MICE IN TAIL SUSPENSION TEST AND FORCED SWIM TEST

ABSTRACTObjective: To investigate the influence of immobilization stress of 2 hrs and FLX on the immobility period of unstressed and stressed mice and todetermine how stress and FLX modulates the effect of each other.Methods: Mice were stressed by immobilization for 2 hrs and the immobility period of both unstressed and stressed mice were determined by usingtail suspension test (TST) and forced swim test (FST).Results: Immobilization stress of 2 hrs increased the immobility period of mice in both TST and FST. FLX reduced the immobility period of bothunstressed and stressed mice in both TST and FST. Both immobilization stress of 2 hrs and FLX modulated the effect of each other. Immobility periodof mice in which FLX was administered before the immobilization stress of 2 hrs had no significant difference from the immobility period of mice inwhich FLX was administered after the immobilization stress of 2 hrs.Conclusion: It has been concluded that the immobility period of mice in which FLX was administered before the immobilization stress of 2 hrs had nosignificant difference from the immobility period of mice in which FLX was administered after the immobilization stress of 2 hrs.Keywords: Stress, Depression, Fluoxetine, Immobility

INFLUENCE OF GENDER DIFFERENCE IN THE ANTIDEPRESSANT EFFECT OF FLUOXETINE IN MICE IN TAIL SUSPENSION TEST

Aim: To determine the effect of gender difference in the antidepressant effect of fluoxetine (FLX) in mice in tail suspension test (TST).Methods: Swiss albino mice of either sex were used and the depression-like behavior was measured by TST.Results: The present study showed that there was a significant difference in the immobility period of male mice and female mice in TST. However, the antidepressant effect of FLX differs significantly in male mice and female mice in TST.Conclusion: It has been concluded that the antidepressant effect of FLX in TST was affected by the gender difference as suggested by the results of the present study.Keywords: Depression, Estrogen, Female, Fluoxetine, Mice, Serotonin

NITRIC OXIDE MEDIATED NEURODEGENERATION IN PARKINSON'S DISEASE

Nitric oxide (NO) is an endogenous molecule which functions as a neurotransmitter, hormone, free radical, etc. NO has been found to regulate the release of neurotransmitters, synaptic transmission, cell death, etc. NO is involved in the pathogenesis of various neuropsychiatric and neurodegenerativedisorders. NO plays a key role in cellular apoptosis and neuronal degeneration. Parkinson' disease (PD) is a neurodegenerative disorder characterizedby motor dysfunction that can be seen in the patients suffering from PD. The motor dysfunction is due to the progressive degeneration of dopaminergicneurons in mid brain. Dopamine (DA) is highly reactive molecule and is prone to the oxidation very much. The oxidation of DA is accompanied by the production of the reactive oxygen species that activates microglia cells. Upon activation, microglia cells cause the upregulation of inducible NO synthase, the enzyme involved in the production of NO. NO thus plays a key role in the neurodegeneration process implicated in PD. Thus, the aim of the present manuscript is to describe the possible role of NO in PD.Keywords: Dopamine, Neuromelanin, Nitric oxide, Parkinson

Beneficial Effect of Oryzanol on Transient Middle Artery Occlusion Induced Ischemic Stroke in Atherosclerotic Rats. Improvement in Behavioural and Biochemical Parameters

The present study was designed to determine the beneficial effect of oryzanol treatment in the ischemic stroke in atherosclerotic rats. Atherosclerosis was induced in rats using high fat diet (containing 20% ground nut oil, 0.5% cholesterol, 1% cholic acid) for 32 days. Ischemic stroke was induced in the atherosclerotic rat (AT rats) on 33rd day using tMCAO model. In the oryzanol treatment group, oryzanol (100 mg/kg, po) was administered on the very first day (day rats were fed with high fat diet), ischemic stroke was induced on 33rd day and oryzanol treatment was continued after the induction of ischemia from 34th day to 40th day. The neurological score was determined for 7days with gap of 24 hrs between the testing procedure. Rats were sacrificed followed by the blood collection and excision of whole brain for the determination of various parameters including brain damage (infarct volume, brain hemisphere weight difference, and Na+-K+-ATPase activity) and oxidative stress parameter (SOD activity, reduced GSH level, MDA level, nitrite level and LDH level). It was observed that ischemia-reperfusion (IR rats) in atherosclerotic rats increased the neurological score, increase in infarct volume, brain hemisphere weight difference and reduced activity of Na+-K+-ATPase. Further IR rats showed the decreased activity of SOD activity and GSH, whereas the level of MDA, nitrite and LDH activity was found to be increased in the atherosclerotic-IR rats. Further it was observed that the oryzanol treatment in the atherosclerotic counteracted the high fat induced rise in the TG, LDL, and VLDL level and increased the level of HDL in the treated animals. Further the administration of oryzanol improved the neurological score, reduce the infarct volume, brain hemisphere weight difference and improve the activity of Na+-K+-ATPase. Oryzanol treatment further improved the SOD activity, increased the level of GSH, reduced the level of MDA, nitrite and LDH activity in atherosclerotic-IR rat

Effectiveness of Human Error Taxonomy during Requirements Inspection: An Empirical Investigation

Software inspections are an effective method for achieving high quality software. We hypothesize that inspections focused on identifying errors (i.e., root cause of faults) are better at finding requirements faults when compared to inspection methods that rely on checklists created using lessons-learned from historical fault-data. Our previous work verified that, error based inspections guided by an initial requirements errors taxonomy (RET) performed significantly better than standard fault-based inspections. However, RET lacked an underlying human information processing model grounded in Cognitive Psychology research. The current research reports results from a systematic literature review (SLR) of Software Engineering and Cognitive Science literature - Human Error Taxonomy (HET) that contains requirements phase human errors. The major contribution of this paper is a report of control group study that compared the fault detection effectiveness and usefulness of HET with the previously validated RET. Results of this study show that subjects using HET were not only more effective at detecting faults, but they found faults faster. Post-hoc analysis of HET also revealed meaningful insights into the most commonly occurring human errors at different points during requirements development. The results provide motivation and feedback for further refining HET and creating formal inspection tools based on HET

Incorporating Human Error Education into Software Engineering Courses via Error-based Inspections

In spite of the human-centric aspect of software engineering (SE) discipline, human error knowledge has been ignored by SE educators as it is often thought of as something that belongs in the realm of Psychology. SE curriculum is also severely devoid of educational content on human errors, while other human-centric disciplines (aviation, medicine, process control) have developed human error training and other interventions. To evaluate the feasibility of using such interventions to teach students about human errors in SE, this paper describes an exploratory study to evaluate whether requirements inspections driven by human errors can be used to deliver both requirements validation knowledge (a key industry skill) and human error knowledge to students. The results suggest that human error based inspections can enhance the fault detection abilities of students, a primary learning outcome of inspection exercises conducted in software engineering courses. Additionally, results showed that students found human error information useful for understanding the underlying causes of requirement faults

Training Industry Practitioners to Investigate the Human Error Causes of Requirements Faults

This paper reports an industrial study that was conducted to evaluate whether human error training procedures and instrumentation created by authors can be used to train industry software practitioners on human errors that occur during requirements engineering process. Industry practitioners were trained (using an on-line audio-visual package) to analyze requirements faults and map them to underlying human errors (i.e., the root causes of faults). Results of the study show that even though our training helped practitioners in gaining knowledge about requirements phase human errors, parts of the training procedures need to be improved. Additionally, practitioners also reported mechanisms to prevent human errors from happening during the requirements engineering process. These mechanisms can help organizations create interventions (like checklists) that can help software developers avoid committing human errors, thereby preventing faults that are caused due to these errors

Validating Requirements Reviews By Introducing Fault-Type Level Granularity: A Machine Learning Approach

Inspections are a proven approach for improving software requirements quality. Owing to the fact that inspectors report both faults and non-faults (i.e., false-positives) in their inspection reports, a major chunk of work falls on the person who is responsible for consolidating the reports received from multiple inspectors. We aim at automation of fault-consolidation step by using supervised machine learning algorithms that can effectively isolate faults from non-faults. Three different inspection studies were conducted in controlled environments to obtain real inspection data from inspectors belonging to both industry and from academic backgrounds. Next, we devised a methodology to separate faults from non-faults by first using ten individual classifiers from five different classification families to categorize different fault-types (e.g., omission, incorrectness, and inconsistencies). Based on the individual performance of classifiers for each fault-type, we created targeted ensembles that are suitable for identification of each fault-type. Our analysis showed that our selected ensemble classifiers were able to separate faults from non-faults with very high accuracy (as high as 85-89% for some fault-types), with a notable result being that in some cases, individual classifiers performed better than ensembles. In general, our approach can significantly reduce effort required to isolate faults from false-positives during the fault consolidation step of requirements inspections. Our approach also discusses the percentage possibility of correctly classifying each fault-type

Error Abstraction Accuracy and Fixation During Error-Based Requirements Inspections

Software inspections are widely used as a requirements verification technique. Our research uses the tried-and-tested perspective of cognitive failures (i.e., human errors) to improve the effectiveness of fault detection during requirements inspections. We have previously shown that inspection effectiveness can be significantly improved by augmenting the current fault-based inspection technique with the proposed Error Abstraction and Inspection (supported by a Human Error Taxonomy). This paper investigates the impact of an inspector\u27s ability to accurately abstract human errors on their fault-detection effectiveness

Issues and Opportunities for Human Error-Based Requirements Inspections: An Exploratory Study

[Background] Software inspections are extensively used for requirements verification. Our research uses the perspective of human cognitive failures (i.e., human errors) to improve the fault detection effectiveness of traditional fault-checklist based inspections. Our previous evaluations of a formal human error based inspection technique called Error Abstraction and Inspection (EAI) have shown encouraging results, but have also highlighted a real need for improvement. [Aims and Method] The goal of conducting the controlled study presented in this paper was to identify the specific tasks of EAI that inspectors find most difficult to perform and the strategies that successful inspectors use when performing the tasks. [Results] The results highlighted specific pain points of EAI that can be addressed by improving the training and instrumentation