LabrulezLCMS-EN

• How do cells decide — and how can cancer begin? 🔬🧬
• Teams at CEITEC and Masaryk University uncovered a molecular tipping point in the Wnt signalling pathway: Dishevelled (DVL) acts as a switch, not a dial. 🎚️
• CK1-driven phosphorylation stacks negative charge on DVL until a threshold flips its shape; DVL then detaches from Frizzled, sending a clear go/no-go signal downstream (Wnt/β-catenin). ⚡
• This on/off logic reframes how tissues coordinate growth and why dysregulation can trigger uncontrolled proliferation. ⚠️
• Understanding these decision points opens avenues to slow or stop tumour‑promoting signals. 🚀

• Published in Science Advances (DOI: 10.1126/sciadv.aed8899). 📖
• Lead scientists: Miroslav Micka (CEITEC); Konstantinos Tripsianes (CEITEC MUNI); Vítězslav Bryja (Faculty of Science, Masaryk University). 👩‍🔬👨‍🔬

How Cancer May Begin: A Cellular Tipping Point Researchers identified a molecular switch in Wnt signalling that regulates cell behaviour and may contribute to understanding cancer development.

🚀 DNA as catalyst is here! Researchers at IOCB Prague led by Edward Curtis unveil deoxyribozyme breakthroughs that make sensing faster, cheaper, and smarter 🧬🔬

• Supernova shines 💡: a chemiluminescent deoxyribozyme that glows blue to detect DNA‑editing enzymes. New assays are ~3× faster and >5× cheaper than standard methods ⚡💰
• Smart switching 🧠: configurable “turn‑on” and “turn‑off” sensors enable precise readouts, including for APOBEC3A—accelerating high‑throughput screening and inhibitor discovery 🎯🧪
• Aurora learns 🎇: using artificial evolution + machine learning, the team mapped how four mutations reprogram Aurora’s substrate preference (4‑MUP vs diFMUP) while avoiding pNPP and ELF 🤖📊
• From lab to impact 🌍: robust, low‑cost catalytic DNA tools point to powerful diagnostics, drug discovery, and future personalized medicine.

Backed by two ACS Chem. Biol. 2026 studies by Jakubec, Svoboda, Kurfürst, Svehlova, Veverka, Curtis and by Kráľová, Isler, Volek, Jandová, Kurfürst, Curtis. Institution: Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences (IOCB Prague).

Deoxyribozymes for Sensing and AI-Guided Discovery IOCB Prague researchers advance deoxyribozyme technology for DNA sensing, enzyme screening, and machine learning-guided discovery.

Make your PT results work for you! 🧪📊 Eurachem explains how providers set assigned values, uncertainty, and dispersion—so labs can interpret proficiency testing correctly.

• 🔍 Selection tip: The Eurachem Guide (eds. B. Brookman & I. Mann) urges you to review a PT provider’s statistical approach before you join.
• 📍 Location (xpt): Providers may use mean, median, or robust estimators. ISO 13528:2022 recommends robust methods when outliers or asymmetry exist. Small datasets can make any estimator unreliable. Different analytical methods may get method-specific locations. A gap vs. a reference can signal method bias.
• 📈 Dispersion (σpt): Standard deviation or robust measures (MADe, nIQR, Algorithm A, Qn, Q). Reported in measurand units or %. Classical SD usually follows outlier removal. Beware small N.
• 📏 Uncertainty u(xpt): For the arithmetic mean, calculate as s divided by sqrt(p). For robust estimators, ISO 13528 suggests a conservative 1.25 multiplier with s*.

• ✅ Takeaway: Know how xpt, u(xpt), and σpt are derived—your conclusions depend on it.

Understanding PT statistics Understand the key statistical parameters used in proficiency testing schemes, including assigned values, uncertainty, and dispersion estimates.