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関連する概念動画

Rate-Determining Steps03:08

Rate-Determining Steps

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Relating Reaction Mechanisms
In a multistep reaction mechanism, one of the elementary steps progresses significantly slower than the others. This slowest step is called the rate-limiting step (or rate-determining step). A reaction cannot proceed faster than its slowest step, and hence, the rate-determining step limits the overall reaction rate.
The concept of rate-determining step can be understood from the analogy of a 4-lane freeway with a short-stretch of traffic-bottleneck caused due to...
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Energy-releasing Steps of Glycolysis01:28

Energy-releasing Steps of Glycolysis

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Glycolysis is divided into two phases based on whether energy is utilized or released. While the first phase consumes ATP, the second phase produces energy in the form of ATP and NADH. The energy is released over a sequence of reactions that turns G3P into pyruvate. The energy-releasing phase—steps 6-10 of glycolysis—occurs twice, once for each of the two 3-carbon sugars produced during steps 1-5 of the first phase.
The first energy-releasing step—the 6th step of glycolysis...
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Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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Steps in the Modeling Process01:14

Steps in the Modeling Process

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Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
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meta-Directing Deactivators: –NO2, –CN, –CHO, –⁠CO2R, –COR, –CO2H01:13

meta-Directing Deactivators: –NO2, –CN, –CHO, –⁠CO2R, –COR, –CO2H

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All meta-directing substituents are deactivating groups. These substituents withdraw electrons from the aromatic ring, making the ring less reactive toward electrophilic substitution. For example, the nitration of nitrobenzene is 100,000 times slower than that of benzene because of the deactivating effect of the nitro group. The first step in an electrophilic aromatic substitution is the addition of an electrophile to form a resonance-stabilized carbocation. The energy diagrams for...
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Steps for Free-Body Diagram01:22

Steps for Free-Body Diagram

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When it comes to studying the behavior of objects in mechanics, one of the most important tools available is the free-body diagram. Consider a simple example of a system of two blocks coupled by a massless string over a frictionless pulley. Block 1 is sliding over a table pulled by block 2 as block 2 falls under gravity.
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Versatile CO2 Transformations into Complex Products: A One-pot Two-step Strategy
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USMLE Step 2のパフォーマンスの予測要因

Mandeep Kaur1, Matthew Y C Lin2, Adnan Alseidi2,3

  • 1University of California San Francisco School of Medicine, San Francisco, CA, United States.

Academic medicine : journal of the Association of American Medical Colleges
|February 14, 2026
PubMed
まとめ

USMLE Step 1が合格/不合格になった今,MCATやNBMEの科目試験のような以前の標準化されたテストスコアは,USMLE Step 2 CKのパフォーマンスを予測しています. 外科,神経学,精神科のNBME試験は,重要な予測指標です.

キーワード:
NBMEは,NBMEは,NBMEは,NBMEは,NBMEは,NBMEは,NBMEは,NBMEは,NBMEは,NBMEは,NBMEは,アメリカ合衆国医療免許試験第2ステップライセンスまたは認証に関する問題標準化されたテストテスト医学の学士課程を修了しました.

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科学分野:

  • 医療教育 医療教育について
  • 標準化されたテスト
  • 医療免許試験 医療免許試験について

背景:

  • 米国医療免許試験 (USMLE) ステップ2 臨床知識 (CK) のスコアは,トレーニング中の試験成績を予測します.
  • USMLE Step 1は2022年に合格/不合格の格付けに移行しました.
  • ステップ2 CKの予測要因を特定することは,医学生の評価に不可欠です.

研究 の 目的:

  • USMLE Step 2 CKスコアを予測する要因を特定する.
  • 以前の標準化テストのスコアの予測力を比較する.
  • 潜在的に成績が低い生徒に対する介入の情報提供.

主な方法:

  • 600人の医学部学生 (UCSF,入学 2016-2019) の横断的な研究.
  • 医療大学入学試験 (MCAT),総合基礎科学試験 (CBSE),社内ブロック試験 (OEQ) および国家医学審査員委員会 (NBME) 科目試験の得点収集.
  • 多変数回帰モデルを使用して,スコア予測性を評価しました.

主要な成果:

  • MCATパーセンチル,CBSEスコア,NBME学科試験 (神経学,精神科,外科),および社内ブロック試験を含むモデルは,ステップ2 CKスコア変動の45%を説明しました.
  • 手術におけるNBME被験者試験では,最も強い予測値 (β = 0.212,P < .001) が示されました.
  • 神経学,精神医学,外科のNBME試験スコアは,ステップ2のパフォーマンスの最も重要な予測指標として浮上しました.

結論:

  • 以前の標準化テストの成績,特にNBME科目試験の成績は,USMLE Step 2 CKスコアを予測する.
  • 研究結果は,成績が低い生徒に対する早期介入を支援しています.
  • テストスコアを最適化することで,強力なカリキュラム・バイトと並行して,レジデンスマッチの成功を高めることができます.