Dialysis and matching simulation
Open your materials, follow the steps, then turn in your work.
Simulate dialysis and HLA crossmatching to model how patients are kept alive and matched.
1. Open your materials
Use the materials named in the first step below. Open lesson resources.
2. Start the work
Read the simulation protocol in the PLTW course shell and define dialysis and crossmatch.
Show all 6 required steps
- Read the simulation protocol in the PLTW course shell and define dialysis and crossmatch.
- Run the dialysis model and record how waste levels change across the session.
- Compare donor and recipient HLA cards and score each crossmatch as compatible or not.
- Flag any crossmatch that predicts rejection and explain why.
- Record your dialysis and matching results in the simulation data table.
- Submit your completed simulation results.
Lost your place? Reopen today's Dialysis and matching simulation record. Find the last completed evidence ID, check it against the claim ceiling, and continue with the first unfinished step rather than restarting the whole task.
Check your work before submitting
- You'll be able to model how dialysis lowers blood waste.
- You'll be able to score an HLA crossmatch and predict rejection risk.
Before lab work: read the safety rules
- All simulations are virtual; no physical biological materials or chemicals are used.
- Ensure your device is charged and connected before beginning the timed simulation.
3. Turn in your work
DueCheck Schoology- Hand in
- Simulation data table: dialysis waste-level time series, HLA crossmatch scores for each donor-recipient pair, and rejection-risk flags with explanations.
How to submit and name your file
Use the submission route shown on today's today's page.
In Schoology, open your course and the assignment for this lesson. Attach your file, select Submit, and check that it appears in the submission.
PDF upload helpYou get two school days for every day you were absent, so this deadline moves with you.
How this lesson connects
Keep using what you learned last class: A defensible biomedical decision separates scientific evidence from value judgments, identifies who may benefit or be burdened, and states the uncertainty and tradeoffs that remain. Today: Organ-replacement decisions integrate organ function, compatibility, urgency, expected benefit, risks, and organ-specific allocation rules rather than relying on one laboratory value or matching feature.
Optional: listen or watch a unit review▸
Need help? Warm-up, timing, and directions▸
💡 Big idea: Organ-replacement decisions integrate organ function, compatibility, urgency, expected benefit, risks, and organ-specific allocation rules rather than relying on one laboratory value or matching feature.
- 0-8Read simulation protocol; define and
- 8-30Run virtual model; record waste levels at each time point
- 30-52Compare donor/recipient HLA cards; score all crossmatches
- 52-62Flag incompatible crossmatches; write explanation
- 62-72Complete simulation
- 72-80Submit results to the class site; async post if remote
- • keeps the patient alive; HLA matching decides whether a transplant will be rejected.
- • Today you model both, using virtual tools, so you can see the data behind clinical decisions.
- • These are VIRTUAL simulations done from your computer, so treat the simulator data as real lab data.
- • Simulation data recording is a Lab SOPs skill directly tested on the WebXam.
- • Hemodialysis passes blood across a semipermeable membrane to remove waste by diffusion.
- • HLA antigens on cell surfaces are the primary targets of the recipient's immune system after transplant.
- • A positive (antibodies react with donor cells) predicts high risk and usually disqualifies the donor.
PLTW connection and today's work
Open Activity 4.3.1 Who Should Receive the Organ? in myPLTW, then complete the virtual dialysis and HLA crossmatch simulation.
Today's stopping point: Nephron diagram should be done (Tuesday); dialysis and HLA simulation data table due today.
PLTW activity titles identify the course connection. If your account will not open, use the posted materials for today and tell Mr. Mendoza. Do not mark an online activity complete unless you completed it.
Course connection
- Activity 4.3.1 Who Should Receive the Organ?
Use the turn-in directions at the top of this page. Do not create a second submission unless your teacher asks for one.
Show another explanation or a smaller first step
Need help? Choose a starting point
Finish the assigned lab safely before starting extra practice.
Lesson resources: reading, slides, and vocabulary▸
The deck carries the prior idea forward, lets you inspect an analogy, maps the rule to biology, and ends with the same evidence decision and exit ticket used on this page.
Generated from this lesson's canonical data with a red-team citation check.
A defensible biomedical decision separates scientific evidence from value judgments, identifies who may benefit or be burdened, and states the uncertainty and tradeoffs that remain.
Organ-replacement decisions integrate organ function, compatibility, urgency, expected benefit, risks, and organ-specific allocation rules rather than relying on one laboratory value or matching feature.
A review board sorts scientific evidence, stakeholder needs, possible benefits, possible burdens, and uncertainty before choosing a policy.
- Which statements are scientific evidence?
- Which statements express a value or priority?
- Who receives the benefit and who carries the burden?
Use science to estimate consequences, then state the value judgment and tradeoff that determine the decision.
A review-board model organizes reasoning but does not make one ethical principle automatically outweigh every other principle.
- • Evidence cards map to source-backed findings.
- • Stakeholder cards map to affected people and priorities.
- • The recommendation maps to an explicit tradeoff with a named uncertainty.
Driving question: Simulate and HLA crossmatching to model how patients are kept alive and matched.
What you already know: A defensible biomedical decision separates scientific evidence from value judgments, identifies who may benefit or be burdened, and states the uncertainty and tradeoffs that remain.
New idea: Organ-replacement decisions integrate organ function, compatibility, urgency, expected benefit, risks, and organ-specific allocation rules rather than relying on one laboratory value or matching feature.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Dialysis and matching simulation. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled testing, treatment, or biological process and identify where evidence limits the decision.
- Observe or measure the relevant feature in today's lesson.
- Organize the observation with a stable evidence ID.
- Apply this rule: Use science to estimate consequences, then state the value judgment and tradeoff that determine the decision.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Today the medical interventions team uses and matching simulation to make a bounded evidence decision. A classroom simulation omits many clinical and allocation variables and cannot rank or recommend care for real patients.
What the evidence supports: E1-E3 and F1 support the daily take-home when the response meets the stated success criteria.
What it cannot prove: The package does not support claims beyond this lesson's or any real patient diagnosis.
- • : The kidney's microscopic filtering unit that cleans the blood, reabsorbs needed substances, and forms urine.
- • : A process that filters waste and excess fluid from blood across a semipermeable membrane, used clinically when the kidneys cannot do this job.
- • HLA: Human antigens, proteins on cell surfaces that mark cells as self, helping the immune system spot foreign cells and guiding transplant matching.
- • : A lab test that checks whether a recipient's immune system will attack a donated organ by mixing recipient serum with donor cells.
- • : The immune system's attack on a transplanted organ or that it recognizes as foreign rather than part of the body.
- • : A reduced ability of the immune system to fight infection, caused by disease, medication, or treatment such as after an organ transplant.
Use it now: Choose one decision option. Cite E1 and E3, then explain how the rule connects the evidence to your choice.
Go further, optional: The source links below are optional enrichment. Every fact required for today's local evidence decision appears in this lesson package.
Health Resources and Services Administration is the source this lesson's claim is checked against: How Organ Allocation Works
Limit: A classroom simulation omits many clinical and allocation variables and cannot rank or recommend care for real patients.
Use science to estimate consequences, then state the value judgment and tradeoff that determine the decision.
Limit: A review-board model organizes reasoning but does not make one ethical principle automatically outweigh every other principle.
You can model how lowers blood waste.
Limit: E3 defines the classroom product or success criterion. It is not independent scientific evidence and cannot justify a clinical or causal claim.
PLTW-GEND-2026-12-15 · Simulated classroom evidence scenario
Your role: medical interventions team member
Decision: Your team must decide what the evidence from today's lesson supports before submitting the labeled and result claim named on today's page.
- • Ask whether scores like ours actually predicted in real transplants, because our simulation never checks its own prediction.
- • Judge the simulated match using function, compatibility, urgency, and risk together instead of leaning on one score.
- • Trust the simulation's clean result, since a well run model gives an answer good enough to rank real patients.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the labeled and result claim.
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.
Reason for review: Your team must decide what the evidence from today's lesson supports before submitting the labeled and result claim named on today's page.
Context: Today the medical interventions team uses and matching simulation to make a bounded evidence decision. A classroom simulation omits many clinical and allocation variables and cannot rank or recommend care for real patients.
- • T1: Read the simulation protocol in the PLTW course shell and define and .
- • T2: Run the model and record how waste levels change across the session.
- • T3: Compare donor and recipient HLA cards and score each as compatible or not.
- • T4: Flag any that predicts and explain why.
- • T5: Record your and matching results in the simulation .
- • T6: Submit your completed simulation results.
- • E1: Health Resources and Services Administration is the source this lesson's claim is checked against: How Organ Allocation Works
- • E2: Use science to estimate consequences, then state the value judgment and tradeoff that determine the decision.
- • E3: You can model how lowers blood waste.
Measurements: Use only the measurements, units, graph, or counts supplied in today's task. No additional patient measurement is implied.
Figure finding: Teaching diagram for and matching simulation. Trace the labeled testing, treatment, or biological process and identify where evidence limits the decision. This is a teaching model, not patient or experimental data.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
Rate or percent = part / comparison total x 100%. Percent change = (new - comparison) / comparison x 100%.
If 18 of 60 records meet a condition, the frequency is 18 / 60 x 100% = 30%.
Name the comparison total. A percent describes the supplied group and does not automatically predict an individual's outcome.
Use today's supplied counts to calculate one rate, risk, frequency, or percent change. Show the denominator and interpretation.
Students often think A polished answer about and matching simulation is trustworthy even when its evidence source, comparison, or limitation is missing.. The trap: Presentation quality cannot raise the evidence level. A classroom simulation omits many clinical and allocation variables and cannot rank or recommend care for real patients.
Dialysis waste-level time series (recipient R):
- Start (0 min): urea 110 mg/dL
- 60 min: urea 78 mg/dL
- 120 min: urea 51 mg/dL
- 180 min: urea 33 mg/dL
- 240 min: urea 22 mg/dL
Reading: Dialysis pulled urea down from 110 to 22 mg/dL over four hours, modeling how the machine does the filtering the failed nephrons cannot.
HLA crossmatch scores (recipient R vs three donors):
- Donor A: 5 of 6 antigens match, no reaction in the well = COMPATIBLE
- Donor B: 3 of 6 match, weak reaction = BORDERLINE
- Donor C: 1 of 6 match, strong reaction = INCOMPATIBLE
Rejection-risk flags:
- Donor C flagged: a strong crossmatch reaction means the recipient already has antibodies against the donor tissue, so the immune system would attack the kidney quickly.
(Tip: a positive or strong crossmatch reaction is a stop sign, not a detail; it predicts fast rejection even if a few antigens match.)
This model shows the level of evidence and organization needed to complete: Records a data table showing how modeled blood-waste levels drop across a dialysis session, scores each donor-recipient HLA crossmatch as compatible or not, and flags crossmatches that predict rejection with a short reason.
- Name the variables and include units.
- Enter observations without changing the raw values.
- Check labels, calculations, and patterns before interpreting the data.
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 on Schoology under today's data-table assignment.
- CER:
- Claim, Evidence, Reasoning: make a claim, back it with evidence, explain your reasoning.
- SOP:
- Standard Operating Procedure, the exact steps to follow (especially in a lab).
- Tracker:
- Your PLTW progress log where you record completed evidence.
- myPLTW:
- The PLTW course site where you do the online activities. Find it in Clever with your Microsoft sign-in, right next to Schoology.
Tap the speaker to hear a term. Add two of these to your notebook glossary with a definition and an example in your own words.
Pick just 2 or 3 words from today and make them yours: write what each one means in your own words, name the context clue or evidence that helped, then give one example from what you actually did in Dialysis and matching simulation. Try your own words first; the glossary is there if you get stuck. This is voluntary and counts as extra credit, so keep it short.
Saved on this device. Show Mr. Mendoza or add these to your notebook glossary to claim the extra credit.
Classroom documents for this lesson are posted in Schoology. Open Clever, then Schoology, and find each one by the name shown on its card.
Use this for optional reserve or extra-credit work after the required class lesson is complete.
Placement rationale
Matched Transplant matching and allocation ethics by path:Medical-Interventions/Unit-4_When-Organs-Fail/4.3_Transplant; keywords:transplant, hla, allocation, organ. Score 158. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this for optional reserve or extra-credit work after the required class lesson is complete.
Placement rationale
Matched Transplant matching and allocation ethics by path:Medical-Interventions/Unit-4_When-Organs-Fail/4.3_Transplant; keywords:transplant, allocation, organ. Score 146. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this for optional reserve or extra-credit work after the required class lesson is complete.
Placement rationale
Matched Transplant matching and allocation ethics by path:Medical-Interventions/Unit-4_When-Organs-Fail/4.3_Transplant; keywords:transplant, allocation, organ. Score 146. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Sign in to Clever with your district Microsoft account to open Schoology or myPLTW. Follow today's posted steps. If myPLTW will not open, use the posted alternative and tell Mr. Mendoza. Turn in your completed work through the Schoology assignment.
Practice: try a question, then check your answer▸
Claim ceiling for this check: 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.
A student makes a certain conclusion about Dialysis and matching simulation from one classroom result. What must the student add before the conclusion is defensible?
Write an answer and pick a confidence to unlock the key.
Fast retrieval with instant answers, not the commit-then-reveal check above. Try each from memory first: write what you remember about the earlier units, then check yourself here.
Missed class or ready for more?▸
Run this before you touch the bench. It is built from the real lab procedure, so the decisions you make here are the ones you will make with the equipment in your hands.
I can name the virtual station sequence and evidence. My device and connection are ready. My data table is open before I start.
Finish the checklist before you handle any material.
- • All simulations are virtual; no physical biological materials or chemicals are used.
- • Ensure your device is charged and connected before beginning the timed simulation.
- 1Read the simulation protocol in the PLTW course shell and define dialysis and crossmatch.
- 2Run the dialysis model and record how waste levels change across the session.
- 3Compare donor and recipient HLA cards and score each crossmatch as compatible or not.
- 4Flag any crossmatch that predicts rejection and explain why.
- 5Record your dialysis and matching results in the simulation data table.
- 6Submit your completed simulation results.
| Trial or sample ID | Independent condition | Measured result with units | Observation before interpretation | Quality-control note |
|---|---|---|---|---|
Before the procedure, predict the result and cite the rule behind the prediction.
After the procedure, compare the result with the prediction and name one limitation or source of uncertainty.
What today's skills lead to. These are real health-science careers this course builds toward. Tap one to see, on the US Department of Labor's O*NET site, what the job actually involves, what it pays, and how fast it is growing.
Complete the virtual and HLA- simulation linked on the class site, recording waste-level changes and match scores, then submit your simulation .
MedlinePlus: DialysisUse the submission route shown on today's today's page.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
MedlinePlus: DialysisYou've passed Unit 2, so the optional extra-credit track is open. Complete reserved-unit work from home, including virtual labs, for extra credit. Each item shows its correct submission route.
Open the extra-credit track- CompleteEvery required part of the artifact is present, nothing left blank.
- AccurateThe science and the data are correct and match the evidence.
- Scientific reasoningYou explain your claim with evidence and reasoning (CER), not just an answer.
- Professional communicationClear, organized, labeled, and written the way a clinician or scientist would.
- SubmittedGo to Schoology to turn this in. Submit one PDF. Put your first and last name in the document header. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf. If you cannot get in, see Mr. Mendoza. Do not skip the work.
- Error analysis and method · counts doubleName a specific limit of the method and how it moved your result, and compare what you predicted to what happened. "Human error" does not count; say what about the procedure or instrument caused it.
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