Laboratory Work
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#1
Good morning, Hana. Welcome to the biochemistry lab — your playground for the term.
早安，Hana。歡迎來到生物化學實驗室——這將是你這學期的遊樂場。
#2
Thanks, Professor. I have to say, I expected it to look more like what I see on TikTok.
謝謝教授。我必須說，我原以為這裡看起來會更像我在 TikTok 上看到的樣子。
#3
Ah, you mean dramatic explosions and colour-changing potions? Reality is rather more meticulous, I'm afraid.
啊，你是說那些戲劇性的爆炸和會變色的藥水嗎？恐怕現實要嚴謹得多。
#4
Fair enough. So where do we even begin?
說得也是。那我們到底該從哪裡開始呢？
#5
We begin with safety, naturally. Every piece of equipment in this room can harm you if mishandled.
我們自然是從安全開始。這間實驗室裡的每一件設備如果操作不當，都可能對你造成傷害。
#6
Even the glass stirring rods? They look pretty harmless to me.
連玻璃攪拌棒也是嗎？它們在我看來相當無害。
#7
A shard of borosilicate glass in your eye would swiftly disabuse you of that notion.
一塊碎裂的硼矽酸鹽玻璃進入你的眼睛，會迅速消除你那種（它無害的）念頭。
#8
Point taken. I'll put the goggles on without complaint.
我明白你的意思了。我會毫無怨言地戴上護目鏡。
#9
Splendid. Goggles, lab coat, nitrile gloves — non-negotiable, every single session.
太棒了。護目鏡、實驗袍、丁腈手套——這些是不可商量的，每一堂課都必須配戴。
#10
Now, today's experiment concerns enzyme kinetics. Have you formulated a hypothesis yet?
現在，今天的實驗涉及酶動力學。妳已經構思出假設了嗎？
#11
I read the pre-lab notes. My hypothesis is that increasing substrate concentration will accelerate the reaction — up to a saturation point.
我讀了實驗前筆記。我的假設是增加底物濃度會加速反應——直到達到飽和點為止。
#12
Excellent. That reflects a nuanced understanding of Michaelis-Menten kinetics.
太棒了。這反映出妳對米氏動力學有著細緻入微的理解。
#13
I may have gone down a Wikipedia rabbit hole last night, honestly.
老實說，我昨晚可能在維基百科上鑽研得太深，停不下來了。
#14
However you arrived at the insight, what matters is that you can now test it empirically.
無論你是如何得出這個見解的，重要的是你現在可以透過實驗來驗證它。
#15
Alright, so I pipette different concentrations into these cuvettes and measure absorbance, correct?
好的，所以我將不同濃度的液體移液到這些比色皿中並測量吸光度，對嗎？
#16
Precisely. Ensure you calibrate the spectrophotometer with a blank solution first, though.
正是如此。不過，請務必確保先用空白溶液校準分光光度計。
#17
Got it. And how do we know when the result is statistically meaningful rather than just noise?
明白了。那我們要如何判斷結果是具有統計學意義，而不僅僅是隨機雜訊呢？
#18
You'll run triplicates and calculate standard deviation. Any anomalous data point warrants scrutiny, not dismissal.
你將進行三重複實驗並計算標準差。任何異常的數據點都值得仔細審查，而非直接排除。
#19
So we don't just delete the outliers and pretend they never happened?
所以我們不只是刪除離群值，然後假裝它們從未發生過嗎？
#20
Absolutely not. An outlier may be the most instructive result of the entire experiment.
絕對不行。離群值可能是整個實驗中最具啟發性的結果。
#21
I think I'm starting to see why real science feels so different from scrolling through flashy lab videos.
我想我開始明白為什麼真正的科學感覺與瀏覽那些浮誇的實驗室影片如此不同了。
#22
The rigour is what distinguishes genuine inquiry from mere spectacle, wouldn't you agree?
嚴謹正是區分真正的探究與單純奇觀的關鍵，難道你不認同嗎？
#23
Completely. I'll write up my hypothesis, run the triplicates, and report every result — outliers included.
完全同意。我會寫下我的假設、進行三次重複實驗，並回報每一項結果——包含離群值在內。
#24
That's the spirit. Science, at its finest, is an exercise in intellectual honesty.
這就對了。科學在其最極致的狀態下，是一場對智識誠實的實踐。
#25
Thanks, Professor. I'm actually looking forward to getting my hands on that equipment now.
謝謝教授。我現在真的很期待能親自操作那些設備。
#26
Then let's not keep the spectrophotometer waiting. Off you go.
那麼，我們就別讓分光光度計久等了。去吧。