VANA 101 Chapter Notes -Central Nervous System, Pia Mater, Peripheral Nervous System

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peleniojosephen

21 Jan 2022

School

Visayas State University

Department

Animal Science

Course

VANA 101

Professor

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Document Summary

Module 10 nervous system and sense organs of the dog. Contains a very small amount of fluid: subarachnoid contain cerebrospinal fluid; this is where the arterioles and venules are being house that supplies the neuroaxis, which is the brain. Subdural administration in veterinary medicine the application of drug medication to the subdural space. Nervous system: topographical components: central nervous system (cns, neuroaxis, brain, brainstem, cerebellum, cerebrum, spinal cord, peripheral nervous system (pns, nerves, peripheral ganglia. Diencephalon, mesecephalon, metencephalon, and myelecephalon forms the brainstem. Telencephalon: largest part of the brain, divided by the median fissure into two cerebral hemispheres, carries out higher brain functions, It is connected by the corpus callosum: medial longitudinal fissure, transverse fissure deep groove that separates the cerebellum from the cerebral hemisphere. Lobes: frontal lobe rostral part, occipital lobe caudal part, temporal lobe caudoventral on the lateral side, parietal lobe dorsal part.

Related Questions

22. Recall that virtualization allows a guest operating system (OS) to run on a virtual machine inside a host operating system. Which of the following statements is true? a) Applications running on a virtual machine do experience performance degradation compared to running on a real machine. x b) A virtual machine typically lacks the functionalities of a real machine. c) A virtual machine cannot run multiple applications simultaneously i.e. do multitasking). d) A virtual machine does not need RAM to run. e) None of the above

What are prions?

In cell, there are subcellular organelles. They are not full organism. Prions are just proteins. They don't have any other macromolecules. Prions have capacity to form copies through replication. They replicate through free radical and chain mechanism.

Doctor Stainly pruisne work on prions and show it's relation with disease called mad cow disease. ( This is neurodegenerative disease and responsible for harmful effects on brain).

In Australia sheep was infected with prions, caused scarpie disease in sheep. Organs of sloghed sheep were used in cow feedd. When cow consume feed, prions were transmitted to cow and cow start to show unusual behavior.

Symptoms of prions infection are like that of some disease

Kurulyprosy
Insomnia
Dimensia

Detection of prions: Prions can be detected by Western bloting.

Normal prions:

Normal prions are present in our body. They don't have tendency to form rigid aggregate. They are quite less in number. They have following functions

Cellular differentiation
Store elemental surplus that is used in future
Memory enhancement

Molecular basis of prions:There is some difference in structure of Normal and abnormal prions.

Normal prions have molecular weight 33-35KD while abnormal prions have molecular weight 27-30KD
In normal prions at position 178 amino acid aspartate is present while in abnormal prions at 178 position asparagine is present.

Prions diagnosis and analysis:

Brain biopsy....in past for taking sample brain biopsy was used but now a days tonsils biopsy is used for sampling.

Immuno fluorescence:Biopsy sample is taken on slide and it is treated with antibody ( of abnormal prions) which is against normal prions. Speciality of antibody is that when it bind with abnormal prion it will glow. If we capture fluroscene it's mean abnormal prion is present in sample. As abnormal prion antibody was label with fluroscene probe. So patient sample will show fluroscene while normal sample will not show fluroscene.

Transmission of prions: Normally prions can't Cross specie barrier they transmitted through different ways. Like as formite

If a person is effected with prions and he has wound in head and his comb is used by another person so prions can be transferred to other individual. Comb is Carrier of prion.

Prions are very slow acting immune system can't destroy them.

skyalpaca180

In this assignment, we build a simple ANN model for a dataset and we explore some methods to optimize model parameters.

Dependencies

Python > 2.7
Scikit Learn package
Pandas toolkit (If it is needed) Numpy toolkit (If it is needed)

Dataset

This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.

Note: You do not need to download the data. Two subsets of data for training and test is created and posted for downloading. The original data set also is included for your further testing and experimenting.

The list of the fields in order of columns in the data file is:
PregnanciesNumber of times pregnant
GlucosePlasma glucose concentration 2 hours in an oral glucose tolerance test BloodPressureDiastolic blood pressure (mm Hg)
SkinThicknessTriceps skin fold thickness (mm)
Insulin2-Hour serum insulin (mu U/ml)
BMIBody mass index (weight in kg/(height in m)^2)
DiabetesPedigreeFunctionDiabetes pedigree function
Age (years)
OutcomeClass variable (0 No Diabetes or 1 Diabetes) 268 of 768 are 1, the others are 0.

ANNprojectdescription
– Loading the required libraries and modules
To finish this assignment, you may use any module that you think is necessary. These modules includes:
1- Pandas
2- Numpy
3- Matplotlib
4- Sklearn

– Reading the data and performing basic data checks

1- Use describe() method of the dataframe (e.g df.describe()) to output the data dimensions and fields basic stats.

– Creating the train and test datasets

1- Splityourdataintotrain,testand,validation.
2- Splityourdatabasedontheratiooftrain=0.75,validation=0.15and,test=0.10
3- Printoutthetotalnumberofrowsandthenumberofrowsallocatedforeach

category above.
Note1: There are many ways you can achieve splitting dataset.
You can use any method as long as you have a balanced ratio of classes in each category.
4- Useyourtestdatasetonlyforfinaltesting.Youshouldnotusetestdatasetfor adjusting parameters.

– Building your model

1- Useneural_networkclassifiertobuildyournetwork.
2- Thereareafewparametersneedstobeadjustedinthismodel:

a. Hidden_layer_sizes b. Activation
c. Solver
d. Batch_size

e. Learning_rate
f. Learning_rate_init
3- Mostofparametersabovehavedefaultvalues.Youmayrunyournetworkon default values to get an idea about your network
4- Youmayadjustparametersbasedwhatwetalkedintheclassetc

– Network metric and plots

1- To evaluate your network, calculate confusion matrix. For that you may use confusion_matrix function from sklearn.metrics library.
How do you interpret precision and recall?
2- Plot error plot for each iteration (epoch) for both validate and train.
Based on your parameter setting you may see an overfitting problem. Try to spot it if that’s happened.
3- Once you finish your parameter tunning, run your model on your test data set and create a plot for your test the same as previous step

Whatareyourdeliverables?

a. A Jupyter document containing your model and experiment results.

dha2021

VANA 101 Chapter Notes -Central Nervous System, Pia Mater, Peripheral Nervous System

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