eChapters

Present study was undertaken to unravel the influence of experimentally induced pre- existing diabetes on survival time and/or mortality pattern in septic animals and how diabetes and sepsis, when occur concurrently, alter vascular reactivity of aorta. Type-1 diabetes was induced following intraperitoneal injection of streptozotocin (STZ: @ 65 mg/kg) for 5 consecutive days while sepsis was induced by caecal ligation and puncture (CLP). Streptozotocin produced a sustained hyperglycaemia in mice and there was decrease in body weight with progression of hyperglycaemic state. CLP caused hyperglycaemia followed by euglycaemia and hypoglycaemia, while in diabeto-sepsis hypoglycaemia was set earlier, leading to early mortality. Alteration in vascular reactivity and endothelial dysfunction was observed.

Notch signalling is an evolutionary conserved pathway that allows cell communication through cell-to-cell interactions. Besides its established role in embryonic development, recent reports have shown its involvement in different infections and inflammations of different body systems including cardiovascular system. Sepsis, a systemic inflammatory response syndrome against microbial infection, causes multiple organ failure resulting in death worldwide in human and animals. Vascular hyporeactivity and reduced peripheral resistance is considered to be the leading cause of death in sepsis. Though Notch signalling has been studied especially in macrophages during inflammation including endotoxaemia, its role in vascular beds in sepsis is yet to be explored. Thus, present study was undertaken to evaluate the effect of sepsis on aortic Notch signalling and its involvement in regulating vascular functions during late phage of sepsis. Sepsis was induced by caecal ligation and puncture (CLP) in mice and thoracic aorta was collected for mRNA expression, western blot and immune-histochemical (IHC) study. Functional study on isolated aortic rings from different groups was also performed to assess the vascular reactivity to different vasoconstrictors.

The objective of the present study was to explore the therapeutic potential of hot alcoholic (100%), hydroalcoholic (70%) and cold aqueous extracts of Pterocarpus marsupium and hot aqueous extract of ITK formulation (mixture of gum acacia, black cumin, wheat and barley) against obese streptozotocin induced type 2 diabetes in male Wistar rats. In Phase I study, tested extracts were observed to possess carbohydrates, alkaloids, proteins and amino acids, tannins, flavonoids, saponins, fixed oils and resins with additional glycosides in ITK formulation after screening by qualitative tests and further confirmed by semiquantitative analysis (by Gas Chromatography-Mass Spectrometry) to possess active principles having antidiabetic, antioxidant, nephroprotective, cardioprotective and anti-inflammatory properties. The extracts were evaluated for in vitro antioxidant (2, 2-Diphenyl-1-picrylhydrazyl (DPPH) and 2, 2’-Azino bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical scavenging assay) and antidiabetic (α-amylase and α-glucosidase inhibitory activity) was determined. Aqueous and hydroalcoholic extracts have potent antioxidant and alcoholic extract of P. Marsupium showed superior antidiabetic activity over ITK formulation. Further in Phase II study, 48 obese male Wistar rats were divided into eight groups viz. group I (Healthy Control), group II (Obese), group III (Obese Diabetic), group IV (Obese Diabetic + Metformin @ 50 mg/ kg b.wt.), group V (Obese Diabetic + ITK @ 435 mg/kg b.wt), group VI (Obese Diabetic + Aqueous P.marsupium @ 1 g/kg b.wt) and group VII and VIII were treated with hydroalcoholic and alcoholic @ 300 mg/kg b.wt.

The present study was undertaken to investigate the antibacterial effect of Eucalyptus robusta leaves extract loaded-solid lipid nanoparticles. Eucalyptus robusta leaves extract loaded SLNs was prepared and characterized. The particle size of SLNs was around 200 nm, zeta potential was 566.93 mV and the entrapping efficiency was 81%. Prepared nanoformulation was spherical in shape. Eucalyptus robusta leaves extract loaded SLNs did not exhibit any promising antibacterial activity against clinical isolates of E. coli and Staphylococcus aureus as determined by Agar well diffusion method. Therefore, further studies were undertaken only on crude extract of Eucalyptus robusta leaves. Experimental endometritis in rats was developed by inoculating the clinical isolate of E. coli (1x107 cfu/ml) in to the uterine horns during diestrus stage followed by cervical ligation. Endometritis in rats was confirmed based on presence of visible pus in the uterus, edematous uterine horns, thinning of endometrial lining and presence of bacterial load in uterine tissue homogenate. Eucalyptus robusta leaves crude extract (25 mg/ml) and Ciprofloxacin (50 mg/ ml) were administered orally found to significantly reduce uterine weight and uterine secretion index. But bacterial load in the uterine tissue homogenate was not significantly reduced by both the treatments. Histopathological lesions in uterus also showed efficient induction of endometritis based on presence of inflammatory cells (neutrophils count) in uterine microscopic sections and their number was markedly reduced after treatment with Eucalyptus robusta leaves crude extract and ciprofloxacin. Compared with the effect of ciprofloxacin, Eucalyptus robusta produced almost similar curative and protective effects against endometritis. Cyclooxygenase 2 (COX-2) gene expression was found to be markedly reduced after treatment with Eucalyptus robusta leaves crude extract as compared with ciprofloxacin treatment. Based on our findings, it may be inferred that Eucalyptus robusta leaves crude extract possesses promising anti-inflammatory activity against experimental endometritis in rats and, therefore, it can be exploited in drug development program for treatment of endometritis in animals.

11.1 Learning Objectives
After comprehending this unit, we will be capable to:
i) Understand the conception of probability distribution;
ii) Appreciate the significance and applications of Binomial distribution;
iii) Understand the importance and uses of Poisson distribution;
iv) Know about the normal distribution and its’ applications.

11.2 Introduction

A probability distribution is a mathematical function that describes the likelihood of obtaining the possible outcomes of a random variable. In other words, it provides the probabilities of different events or values that a random variable can take. The sum of all probabilities in a probability distribution is equal to 1.

10.1 Learning Objectives
After reading this chapter, you will be able to:
i) Understand the concept and types of hypotheses in hypothesis testing;
ii) Differentiate between one-tailed and two-tailed tests and recognize their applications;
iii) Grasp the implications of Type I and Type II errors in hypothesis testing;
iv) Explore the significance level and its connection to confidence limits;
v) Understand the concept of degrees of freedom in hypothesis testing;
vi) Familiarize yourself with the stepwise approach to hypothesis testing for effective application.

10.2 Introduction

In this chapter, we explore the fundamental concept of hypothesis testing, a cornerstone in statistical analysis. We begin by exploring the nature of hypotheses and their types, distinguishing between one-tailed and two-tailed tests and understanding their respective applications. We then explain the intricacies of Type I and Type II errors, crucial pitfalls to avoid in hypothesis testing. Additionally, we probe into the significance level, its relationship to confidence limits, and its role in determining the strength of our conclusions. Furthermore, we explain the concept of degrees of freedom, an essential factor in hypothesis testing that affects the reliability of our results. Finally, we guide you through a stepwise approach to hypothesis testing, ensuring a comprehensive understanding and effective application of these concepts in practical scenarios. Through this journey, you will not only grasp the mechanics but also appreciate the profound impact of hypothesis testing in drawing meaningful conclusions from data in our data-driven society.

9.1 Learning Objectives
After completing this chapter, you should be able to:
i) Understand the concept of Sample, Population, Sampling Frame, Sample Size, etc.;
ii) Differentiate between Probability and Non-Probability Sampling methods;
iii) Understand the various methods of sampling;
iv) Recognize Sampling and Non-Sampling errors;
v) Determine Sample Size.

8.1 Learning Objectives
After completing this chapter, you should be able to:
i) Understand the concept and significance of index numbers;
ii) Identify different construction methods;
iii) Understand the importance of selecting appropriate base and current periods;
iv) Recognize the properties and tests of adequacy;
v) Recognize the challenges and limitations of index numbers;
vi) Stay informed of recent advances;
vii) Synthesize practical examples and calculations for creating index numbers.

8.2 Introduction

In this chapter, we embark on a journey through the intricate world of index numbers, a cornerstone in the realm of statistics. We will explore what index numbers are; their various types; and the methodologies employed in their construction. Delving into real-world applications, we’ll uncover how these numerical tools are pivotal in measuring economic trends, informing policy decisions, and shaping our understanding of complex data sets. By the chapter’s end, you’ll gain insights into not only the mechanics but also the profound impact of index numbers in our data-driven society.

7.1 Learning Objectives
After comprehending this unit, we will be capable to:
i) Understand the conception of regression;
ii) Appreciate the significance of regression;
iii) Understand the difference between regression and correlation;
iv) Know about the regression lines;
v) Anticipate the difference between simple regression and multiple regression.

7.2 Introduction

Correlation is followed by linear regression. Regression is applied for forecasting the value of an unknown variable with the help of a known variable. The forecasted variable is called the dependent variable. On the contrary, an independent variable is used for forecasting the value of a dependent variable. If you desire to know, for instance, if exam achievement can be anticipated based on review time, whether cigarette consumption can be predicted based on smoking length, and so on, you may use linear regression. You must utilize multiple regressions if we deal with more than one independent variable rather than simply one.

6.1 Learning Objectives
After going through this chapter, you will be able to:
i) Understand the meaning, significance, and properties of correlation;
ii) Know the various types of correlation;
iii) Comprehend the computation process of various types of correlation;
iv) Appreciate the limitations of correlation.

6.2 Introduction

Correlation is a fundamental statistical concept that measures the degree of association or relationship between two or more variables. Correlation helps us to understand how changes in one variable correspond to changes in another. Correlation values range from -1 to 1; where -1 indicates a perfect negative correlation, +1 represents a perfect positive correlation and 0 suggests no linear correlation between the variables. The sign and magnitude of the correlation coefficient provide information about the strength and direction of the relationship between the variables. Correlation analysis is a multipurpose tool with various applications, such as identifying the strength of relationships between stock prices and market indices, assessing the impact of education on income levels, or determining the association between weather conditions and crop yields. Understanding correlation is essential for making informed decisions, drawing conclusions from data, and developing predictive models in numerous fields of study and practice.

5.1 Learning Objectives
By the end of this chapter, you will be able to:
i) Understand and apply Absolute Measures of Dispersion;
ii) Explore Relative Measures of Dispersion;
iii) Understand the importance of these measures in comparing the variability of data sets;
iv) Familiarize with the concept of moments in statistical distributions;
v) Learn about skewness and kurtosis as measures of distribution shape;
vi) Develop the ability to apply these concepts to real-world data.

5.2 Introduction

Nowadays, understanding the dispersion and shape of data distributions is as crucial as knowing their central tendency. This chapter, ‘Measures of Dispersion and Shape of Distribution,’ delves into the essential statistical tools that quantify the spread and shape of data sets. It covers key concepts such as range, variance, standard deviation, skewness, and kurtosis. These measures provide deeper insights into the consistency, reliability, and nature of business data, enabling professionals to make more nuanced and informed decisions. Through this chapter, readers will learn not just to describe data, but to understand the facts it tells about variability and distribution trends in a business context.

4.1 Learning Objectives
By the end of this chapter, you will be able to:
i) Understand the concepts of Central Tendency and Partition Values;
ii) Identify appropriate measures for different data sets;
iii) Distinguish between different types of means;
iv) Apply Partition Values in data analysis.

4.2 Introduction

Nowadays, the ability to proficiently analyze and interpret data sets is indispensable for strategic decision-making. This chapter, ‘Measures of Central Tendency and Partition Values,’ extends beyond the basics of mean, median, and mode to explore the deeper layers of data analysis through quartiles, deciles, and percentiles. These measures offer a more comprehensive understanding of data distribution, crucial for identifying trends and making precise business predictions. We will unravel how these statistical tools can be effectively employed to dissect and interpret complex data sets, providing business professionals with an enhanced toolkit for informed analysis and decision-making in various business scenarios.

3.1 Learning Objectives
After completing this chapter, you should be able to:
i) Define primary data and secondary data and their applications in various contexts;
ii) Identify and briefly explain the various methods used for collecting primary data;
iii) Recognize the significance of secondary data and its advantages and disadvantages;
iv) Create a pie chart, histogram, bar chart, column chart, and line chart using appropriate data sets;
v) Evaluate the advantages and limitations of each data presentation method.

3.2 Introduction

Presently, the role of data has transcended from mere numbers and figures to a powerful driving force behind informed decision-making, efficient problem solving, and insightful analysis. This chapter delves into the crucial aspects of data collection and presentation and it will help in unraveling their significance across a spectrum of professional fields. The chapter will help to explore the fundamental concepts of data collection and its differentiation into primary and secondary categories. We will learn about the methods employed to gather firsthand data and from existing sources. Furthermore, we will delve into the realm of data presentation, understanding how various visualization techniques such as pie charts, histograms, bar and column charts, and line charts transform data into digestible and meaningful representations

2.1 Learning Objectives
After completing this chapter, you should be able to:
i) Understand the concept and importance of nominal, ordinal, interval, and ratio scales;
ii) Identify the characteristics and uses of each scale type;
iii) Learn to select the right scale for different data and research needs;
v) Recognize the properties and tests for each scale’s adequacy;
v) Understand the challenges and limitations of using different scales;
vi) Stay updated on recent advancements in scale development;
vii) Apply nominal, ordinal, interval, and ratio scales in research with practical examples and calculations;
viii) Understand different types of data structure.

1.1 Learning Objectives
After going through this chapter, you will be able to:
i) Understand the meaning, scope, functions, and limitations of statistics;
ii) Know the various types of statistics and their importance;
iii) Comprehend the various types of variables;
iv) Appreciate the role of the various statistical organizations.

1.2 Introduction

Statistics is a powerful and essential field of study with substantial importance in various aspects of life, science, business, and society. Its significance lies in its ability to provide a systematic framework for collecting, analyzing, interpreting, and presenting data. Statistics is a universal language of data that empowers individuals, organizations, and societies to make informed decisions, solve problems, and gain deeper insights into the world around us.

• The axial skeleton is comprised of several key structures that form the central core of the animal skeleton.

• This includes the bones of the skull, which encase and protect the brain, the vertebral column or spine, which provides support and houses the spinal cord, as well as the ribs and the sternum, which together form the rib cage, protecting vital organs such as the heart and lungs.

• These components work together to provide structural support and protection for the body’s central organs.

Skull Bones

The skull is a complex structure that varies greatly across different animal species, reflecting their unique evolutionary adaptations, dietary habits, and ecological niches.

Generally, the skull serves several critical functions: protecting the brain, supporting facial structures, and providing attachment points for muscles involved in feeding and expression.

The cattle skeleton, like that of other mammals, is a complex structure that provides support, protection, and mobility. The skeleton for study purposes is divided into two main parts: the axial skeleton and the appendicular skeleton. The axial skeleton forms the central axis of the body and includes bones such as the skull, vertebral column, ribs, and sternum. The appendicular skeleton comprises the bones of the forelimb (scapula, humerus, radius-ulna, carpals, metacarpals and phalanges) and hindlimb (os coxae, femur, patella, tibia-fibula, tarsals, metatarsals and phalanges).

Wound healing is a complex phenomenon with three distinctive yet overlapping phases i.e. Inflammatory, proliferative and remodeling phases. Present study was conducted to unravel the molecular insights of Mangiferin in immunocompromised excisional rat model. Firstly, immunocompromised state was established following hydrocortisone injection @80 mg/kg body weight through intra muscular route and determining the immunocompromised state with neutrophilia, lymphocytopenia and reduced splenic weight in adult male rats weighing 200-250 grams. Then, 120 animals were randomly and equally divided into five groups i.e. group I served as Healthy control, group II served as Immunocompromised control, group III served as Immunocompromised group treated with silver sulphadiazine and group IV and V served as Immunocompromised group treated with 2.5 % Mangiferin and Immunocompromised group treated with 5 % Mangiferin, respectively. Study was conducted for a period of 28 days. Six animals were humanely sacrificed at weekly interval till day 28th of study. Wound healing efficacy and molecular cascading of pharmacodynamics of Mangiferin was determined following gross studies including digital photography, wound area measurement and per cent wound contraction and biochemical indices viz. hydroxyproline, DNA content, total protein and LPO assay.

Endometritis is one of the leading causes of reproductive inefficiency, infertility and decreased milk yield in high yielding dairy cows and buffaloes as well as in other species of animals and are associate with severe economic loss. Indiscriminate use of antimicrobial agents has resulted in development of resistance to the available antimicrobials. Plant-derived active principles have promising potential to act as an alternative to conventional antimicrobial agents. In the present study, an attempt was made to investigate the mechanism of action of Eucalyptus robusta leaves (ER) extract against resistant bacterial isolates. Out of 70 clinical samples of uterine discharges from cattle and buffaloes having history of uterine infection, we have identified one isolate as methicillin-resistant Staphylococcus. As per the CLSI guideline, this isolate (S4) was found to be catalase +ve, oxidase –ve and possess mecA and coaA genes along with shown resistance to cefoxitin and MIC breakpoint for oxacillin was >4 µg/ml. Methanolic extract of ER reconstituted in water showed presence of eucalyptol (marker compound) along with other major bioactive phytoconstituents following GC-MS analysis. ER extract exhibited marked in vitro antibacterial effect against S4 isolate and MRSA (ATCC 33591) as evidenced by agar well diffusion test with MIC value of 0.3125 mg/ml.

Present study was undertaken to evaluate the ameliorative effect of α-tocopherol(100 mg/kg) against cartap (16.25 mg/kg and 32.5 mg/kg) induced toxicity following 28days oral exposure in adult male Wistar rats. Cartap exposure did not produce any clinicalsigns of toxicity in rats at both the doses. Weekly Average body weight gain wassignificantly reduced following cartap (32.5 mg/kg). Both absolute and relative organweights did not differ significantly between different treatment groups. Hematologicalparameters did not differ significantly in any of the treatment groups. Plasma Glucose,Total Cholesterol, Triglycerides, AST, ALT, BUN levels were found to be markedlyincreased in cartap alone treatment groups. Plasma calcium levels showed irregular butnon-significant change in response to cartap doses. α-tocopherol co-treatment with cartapproduced non-significant decrease in the plasma levels of Glucose, AST and ALT but thelevels of Total Cholesterol Triglycerides and Calcium were found to be significantlydecreased in both the co-treated groups. BUN levels remained unaffected following α-tocopherol co-treatment.