Here's an example of what's due today

Dialysis and matching simulation

Tue, Dec 15, 2026 · Week 17 · Genetics of Disease (Medical Interventions)

Today's goal: Simulate dialysis and HLA crossmatching to model how patients are kept alive and matched.

Learn first

What a finished product looks like

This is a model of the work you should turn in today. Use it to check your own: match the structure and the level of detail, do not copy it. Your data and wording should be your own.

Dialysis and crossmatch results table on a parallel case
Completes: Models the simulation data table on a parallel practice recipient: waste levels across a dialysis session, each donor's HLA match count and crossmatch result read positive or negative, and the rejection flags with a reason.

Parallel practice case, not today's data (recipient Q-9, made-up numbers).

Dialysis waste-level time series (blood urea nitrogen, BUN):

  • Start (0 min): 84 mg/dL
  • 60 min: 63 mg/dL
  • 120 min: 47 mg/dL
  • 180 min: 36 mg/dL
  • 240 min: 28 mg/dL

Reading: BUN fell by two thirds over four hours, fastest at the start when the gap between blood and dialysate was largest. The machine is doing the filtering the failed nephrons cannot, but only while it runs.

Matching results for Q-9:

  • Donor W: HLA match count 2 of 6; crossmatch negative.
  • Donor X: HLA match count 5 of 6; crossmatch positive.
  • Donor Y: HLA match count 4 of 6; crossmatch negative.

The match count and the crossmatch are two different tests. The count compares HLA types; the crossmatch mixes Q-9's serum with the donor's cells and reads positive or negative.

Rejection-risk flag:

  • Donor X flagged: a positive crossmatch means Q-9 already has antibodies against Donor X's cells, which predicts rapid rejection, even with 5 of 6 HLA matches.

(Tip: read every crossmatch as positive or negative before you look at the match counts.)

Why this matters

This model shows the level of evidence and organization needed to complete: Models the simulation data table on a parallel practice recipient: waste levels across a dialysis session, each donor's HLA match count and crossmatch result read positive or negative, and the rejection flags with a reason.

Build yours step by step
  1. Name the variables and include units.
  2. Enter observations without changing the raw values.
  3. Check labels, calculations, and patterns before interpreting the data.
Change it for a new task

Keep the structure. Replace the question, facts, measurements, and evidence. Then recheck units, vocabulary, and whether the conclusion goes beyond the evidence.

Also due today: turns in the completed simulation table in Schoology under today's data-table assignment.

Turn in: Simulation data table: dialysis waste-level time series, each donor-recipient pair's HLA match count and crossmatch result (positive or negative), and rejection-risk flags with explanations.

Go to Schoology to turn this in.

Submit one PDF. Schoology attaches your name to your upload; on the page itself, write your period and code. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf.

Open Schoology PDF upload help

If you cannot get in, see Mr. Mendoza. Do not skip the work.

Claim ceiling: Today's evidence supports a classroom claim about today's lesson. It cannot prove causation, diagnose a real patient, or justify action outside this room.

Check yourself

WebXam problem for today's skill

One exam-style question that uses exactly what you practiced today. Try it before you reveal the answer, then read why each choice is right or wrong.

WebXam-style domain: Molecular and Genetic TechnologySelf-check skill: Reading an HLA crossmatch and predicting rejection risk
In a crossmatch, a recipient's serum is mixed with a donor's cells and shows a strong positive reaction. What is the best interpretation for transplant planning?

Tap an answer to see the full explanation. Nothing is recorded or graded.

Why this practice matters

It builds this reusable test skill: Reading an HLA crossmatch and predicting rejection risk.

Use it on a new WebXam question
  1. Name the concept or data pattern being tested.
  2. Cross out choices that violate that rule or the evidence.
  3. Justify the best remaining choice before checking the answer.