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astronomy

Klarisa Rikova

Klarisa Rikova is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Klarisa Rikova rather than just read about it. In short: Klarisa Rikova is a senior scientist at Cell Signaling Technology, Inc. (CST) in Danvers, Massachusetts.

Key takeaways

  • Klarisa Rikova belongs to astronomy; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Klarisa Rikova to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Klarisa Rikova from memory before moving on to harder problems.

Reference excerpt

Klarisa Rikova is a senior scientist at Cell Signaling Technology, Inc. (CST) in Danvers, Massachusetts. She has worked at CST since 2000, and worked as a scientist at CST's sister company, Bluefin Biomedicine in Beverly, Massachusetts, from 2015 to 2019.

Early life and education

Rikova was raised in Tashkent, Uzbekistan. She attended the National University of Uzbekistan where she received her M.Sc. in chemistry. Rikova was hired in 2000 as a scientist at Cell Signaling Technology, Inc. From 2015 to 2019, she worked as a scientist at Bluefin Biomedicine before joining CST once again as a senior scientist.

Research and career Cell Signaling Technology, Inc. utilized a new form of probability-based mass spectroscopy to analyze post-translational modifications among peptides taken from tumor cell lines. This approach to liquid chromatography-mass spectrometry (LC-MS/MS) included a probability score, or an "Ascore," which measures the probability of a correct phosphorylation site by measuring the presence of specific ions indicative of phosphorylation sites on a peptide sequence. Using this method, scientists at Cell Signaling Technology were able to generate pY antibodies that function to pull down phosphorylated tyrosine residues through immunoprecipitation. Rikova utilized this phosphoproteomic technique with tissue samples from patients with non-small cell lung cancer (NSCLC) and found excess phosphorylation in the tumor cell lines and surveyed tyrosine kinase signaling in these cancer lines. Tyrosine kinase receptors present putative diagnostic targets as they are themselves phosphorylated at tyrosine residues upon activation, thereby indicating the receptor is active. Analyzing NSCLC tissue samples identified oncogenic tyrosine kinases based on their phosphorylation profile and identified the novel ALK and ROS fusion proteins in NSCLC. To determine the genetic profile of these proteins, Rikova performed RT-PCR and discovered ALK to be fused to EML4, a microtubule protein, triggering perpetual activation of the ALK tyrosine kinase. She proposed that a coiled-coil domain fused to the kinase domain of ALK is likely to permit oligomerization and consequently, constitutive activation of ALK kinase in these cancer types. Similarly, the ROS tyrosine kinase was determined to be fused to SLC34A2, a transmembrane carrier protein, such that the N-terminal domain of SLC34A2 is fused to the transmembrane domain in ROS, also found to have constitutive activation. Focusing on cell signaling and post-transcriptional modifications (PTMs) enabled this novel screening technique that identifies specific oncogenic mutations in patients.

Most-cited publications Rikova K, Guo A, Zeng Q, Possemato A, Yu J, Haack H, Nardone J, Lee K, Reeves C, Li Y, Hu Y. Global survey of phosphotyrosine signaling identifies oncogenic kinases in lung cancer. Cell. 2007 Dec 14;131(6):1190-203. (open access) (Cited 2443times, according to Google Scholar ) Guo A, Villén J, Kornhauser J, Lee KA, Stokes MP, Rikova K, Possemato A, Nardone J, Innocenti G, Wetzel R, Wang Y. Signaling networks assembled by oncogenic EGFR and c-Met. Proceedings of the National Academy of Sciences. 2008 Jan 15;105(2):692-7. [2] Archived 2022-01-05 at the Wayback Machine (open access) (Cited 563 times, according to Google Scholar.) Carretero J, Shimamura T, Rikova K, Jackson AL, Wilkerson MD, Borgman CL, Buttarazzi MS, Sanofsky BA, McNamara KL, Brandstetter KA, Walton ZE. Integrative genomic and proteomic analyses identify targets for Lkb1-deficient metastatic lung tumors. Cancer cell. 2010 Jun 15;17(6):547-59. [3] (open access) (Cited 235 times, according to Google Scholar.)

References

Worked examples

Example 1 — a first encounter with Klarisa Rikova

Start with the simplest possible case. Write down what Klarisa Rikova claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Klarisa Rikova before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Klarisa Rikova ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Klarisa Rikova

In research
Klarisa Rikova appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Klarisa Rikova in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Klarisa Rikova is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cancer researchers, Living people, National University of Uzbekistan alumni, so understanding it makes those chapters shorter.
In everyday life
Look for Klarisa Rikova outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Klarisa Rikova in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Klarisa Rikova means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Klarisa Rikova out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Klarisa Rikova in simple terms?

Klarisa Rikova is a senior scientist at Cell Signaling Technology, Inc. (CST) in Danvers, Massachusetts.

Why does Klarisa Rikova matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Klarisa Rikova?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Klarisa Rikova.

Tags

  • Cancer researchers
  • Living people
  • National University of Uzbekistan alumni
  • People from Beverly, Massachusetts
  • People from Tashkent
  • Scientists from Massachusetts
  • Scientists from Tashkent
  • Uzbekistani scientists
  • Women cancer researchers

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