Jori

"How on earth did my reviewer miss it? Its stated clearly on page-4. Do they not read?" 📝 When you are new to writing papers, there is a strong compulsion to write down every important thought as they appear in whatever section you are currently writing at that time. 👻 Soon, your results are in intro, literature survey in results, plots appear first followed next by nuances in the experimental methodology used. 🙃 All of this puts the burden on the reviewer to extract details from parts of your paper.The result? Reviewers get tired and click reject. ⛔ It does not matter how good your work is. If you can’t put information where the reader expects to find it, your work will never see the light of the day. Handy guide attached for getting this right. If you are working on cancer cure, try Tailwind >> https://buff.ly/3VczfdZ

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We’ve downloaded AND read them all. If you are curing cancer, let’s start writing. Tailwind lets you: 💡 come up with high impact ideas that are right for YOU + your lab 📚 comprehensive literature review for all things cancer (yeah, we read it all) 🔬experimental methodology catered to your lab 📝 first drafts that are so polished you'd probably cry ⏩ Get some Tailwind https://buff.ly/3D03QFG

These tips 3x the chances of your paper getting accepted. After reviewing 100s of papers and talking to peers who reviewed 1000s - these are patterns that simplify writing and make your reviewers journey easy. (Wish this advice is commonplace, esp for new comers) 1. Active voice sells ideas better than passive. Always. 2. Live for your OWN truth, never for other scholars' approval 3. Write the methods section before conducting experiments 4. Break complex ideas into simple formal language 5. Citations should be a taste of truth → use them thoroughly 6. Your abstract is your paper's movie trailer 7. The discussion isn't a results remix → this is where you DISARM your reviewers by going through potential objections one by one 8. Tables whisper wisdom that paragraphs shout gruffly 9. No one reads your paper start to finish → always design for skimming. Pay attention to section titles, sub-sections, figure captions, and literally anything that sticks out like barbs to help the scan. 10. My best writing happens between 5 AM - 10 AM. Find yours. 11. Your title is not unrelated to your citation success 12. Tweak tenaciously → cut 30% of your first draft. And then, some more. 13. Strong verbs always beat fancy adjectives 14. Make text-to-speech AI your read-aloud buddy 15. One paragraph = one idea (NO exceptions) ⏩ Tailwind avoids these mistakes. If you are curing cancer, we got you covered https://buff.ly/3D03QFG

The peer-review process has slowly curated a level of perversion in the publication industry that is hard to ignore. If you have reviewed over a 100 submissions, and received some the most bizarre reviewer#2’s for years, it slowly sinks in. This actually got published. See for yourself —>

Of the 18.1 million Cancer Survivors in the US, nearly half have lived 10 or more years after their diagnosis, while 19% have lived 20 or more years, as reported in a JNCI Now study led by NCI researchers. These stats are truly encouraging and highlight the progress in cancer research and treatment. It's inspiring to see such significant survival rates among cancer survivors. The next decade will usher precision medicine. Cannot wait for survivorship to rise even further. The future is bright. Source: https://buff.ly/4ilj4Fa

Congrats to all newly matched 2025 hem-onc fellows 🎉

How to write a good grant? 1. Write it for the reviewer, not you, the applicant. 2. Communicate in stories. 3. Make your story cohesive—leave no puzzling gaps. 4. Make your story resonate to keep the reviewer reading. 5. Accept chance and noise in peer-review.

Exercise is medicine. Your gym membership is the best health insurance you will pay for. Don’t like gyms? Put on those running shoes - roads are open 24x7. Start now. Start where you are. Start on a Sunday at 5 pm. Walk. Run. Pump. https://buff.ly/4fIHrdM

Advancing drug discovery hinges upon our ability to predict cellular responses to new compounds. 🧪 This is massively time intensive. There simply aren’t enough traditional labs & resources needed to endlessly test compound combinations. 🌟 Enter PRNet - a massive step forward in Gen AI. Recently introduced in Nature Communications by Qi and coauthors, this model named PRnet leverages a perturbation-conditioned generative model—a type of model trained to generate predictions conditioned on specific perturbations, such as the introduction of a new compound. PRnet predicts transcriptional responses to novel chemical compounds across various cell types and disease pathways. Wow! But it gets better. PRnet can perform in-silico compound screening. It can also create a "perturbation atlas" that maps predicted cellular responses across 88 cell lines, 52 tissues, and tens of thousands of compounds. https://buff.ly/49iEe2B