HN210 Lecture Notes - Lecture 6: Beta Blocker, Adrenergic Receptor, Nadolol

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lucidz

23 Mar 2023

School

WLU

Department

Health Sciences

Course

HN210

Professor

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Document Summary

Side effects, uses, types, and examples a class of drug known as beta blockers prevents the body"s response to the hormone adrenaline. In addition to high blood pressure, angina (chest discomfort), heart failure, and irregular cardiac rhythms, they are used to treat a number of other illnesses. Beta blockers function by obstructing the beta receptors in the body that cause adrenaline"s actions on the heart and blood vessels. Beta blockers come in a variety of forms, including as non-selective beta blockers, which impact all beta receptors, and selective beta blockers, which only affect certain beta receptors. Atenolol, metoprolol, and bisoprolol are a few examples of selective beta blockers. The non-selective beta blockers propranolol and nadolol are two examples. Beta blockers are often used to treat hypertension, or high blood pressure. They function by lowering blood pressure and heart rate, which may aid in lowering the risk of heart attack and stroke.

Related Questions

In this checkpoint, use human population data and other evidence to make a connection between human population and the issue you have

Global Issues Network

CP2: Human Population Growth

[Student Name] [Class Block/Period]

Student Work: Making Connections

Student Work: Interpreting Population Pyramids

Self-Assessment: Making Connections and Inferences

Level

Rationale - Write a short paragraph justifying the numerical level score you chose using key terms from the rubric and examples from your work.

Self-Assessment: Interpreting Data/Info to Make Valid Claims

Level

Rationale - Write a short paragraph justifying the numerical level score you chose using key terms from the rubric and examples from your work.

Checkpoint Directions

Check for Resources and Activities under this checkpoint that will help you complete this checkpoint.

Write a connection between human population growth for each of the 5 environmental issues identified by GIN. There should be a clear cause and effect relationship identified for each.

Complete the activity in class, Power of Populations.

Choose a selection of population pyramids, global population graphs, and/or the demographic transition graph. Analyze each and then explain the connections between them.

Checkpoint Checklist

Done

These things must be done or included for this CP to be completed.

Use the rubric for additional guidance.

There is a clear and detailed cause and effect connection made between human population growth and each of the 5 GIN environmental issues. The explanations are clearly written in complete sentences.

Images of the data being analyzed are included and readable.

Each representation of data is analyzed.

Connections between the data are clearly explained.

123

John, a healthy twenty-eight year old electrical engineer, was driving home from work one evening when he experienced sudden stabbing pain in his right pectoral and right lateral axillary regions. He began to feel out of breath and both his respiratory rate and heart rate increased dramatically. As luck would have it, John passed a hospital each day on his way home and was able to get himself to the hospital’s emergency room.

The emergency room physician listened to John's breathing with a stethoscope and requested blood gas analysis and a chest x-ray. John answered a few of the doctor's questions. The doctor noted that John had no history of respiratory problems but was a heavy smoker.

After viewing the chest radiograph, the doctor informed John that he had experienced a spontaneous pneumothorax, or what is commonly called a collapsed lung. The doctor explained that a hole had opened in John's right lung and that this hole had allowed air to leak into the cavity surrounding the lung.

Then, as a result of the lung's own elastic nature, the lung had collapsed. The doctor said he could not be certain of the cause of the pneumothorax, but smoking cigarettes had certainly increased the likelihood of it happening. He told John he was fortunate the pneumothorax was small, which meant that relatively little air had escaped from the lung into the surrounding cavity, and it should heal on its own.

He instructed John to quit smoking, avoid high altitudes, flying in non-pressurized aircraft, and scuba diving. He also had John make an appointment for a re-check and another chest x-ray.

Case Background

The pneumothorax decreases the efficiency of the respiratory system, which in turn results in decreased blood oxygen concentration, increased respiratory rate, and increased heart rate. If the pneumothorax is small, the air that escapes into the pleural cavity can be reabsorbed into the lung once the opening has sealed shut. If the pneumothorax is large, a needle or chest tube may have to be inserted into the pleural cavity to draw the air out and allow for the re-expansion of the lung.

Questions

1. Define the following terms and explain how they may have been affected by John’s spontaneous pneumothorax.

a. Visceral pleura

b. Parietal pleura

c. Pleural cavity

2. As a result of a pneumothorax, the lung tissues recoil, and the lung collapses. Explain how recoil and collapse are prevented in a healthy lung?

3. How does elastic recoil function in breathing?

4. Why was John instructed to avoid high altitudes and flying in non-pressurized aircraft?

sanggavi0907

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

HN210 Lecture Notes - Lecture 6: Beta Blocker, Adrenergic Receptor, Nadolol

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