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	<description>Brain Food for Biologists</description>
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		<title>How to Choose Filter Plates for Automated Cell-based Assays: Biological and Hardware Considerations </title>
		<link>https://bitesizebio.com/87738/choose-the-right-filter-plates/</link>
		
		<dc:creator><![CDATA[Merck KGaA, Darmstadt, Germany]]></dc:creator>
		<pubDate>Fri, 08 May 2026 08:45:00 +0000</pubDate>
				<category><![CDATA[Equipment Mastery and Hacks]]></category>
		<category><![CDATA[Merck KGaA, Darmstadt, Germany]]></category>
		<category><![CDATA[cell-based assays]]></category>
		<category><![CDATA[ELISPOT]]></category>
		<category><![CDATA[Filter plates]]></category>
		<category><![CDATA[sponsored]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=87738</guid>

					<description><![CDATA[Choosing the right filter plate starts with understanding your assay biology. What must happen at the membrane determines everything that follows. Choose filter plates according to membrane chemistry (binding vs non-binding) and the correct pore size for your target (cells, proteins, or small molecules). Finally, ensure plate architecture and automation compatibility support consistent flow, minimal crosstalk, and reproducible results at scale.]]></description>
		
		
		
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		<item>
		<title>qPCR Troubleshooting: How to Diagnose and Fix Common Failures</title>
		<link>https://bitesizebio.com/88006/qpcr-troubleshooting/</link>
		
		<dc:creator><![CDATA[Zara Puckrin]]></dc:creator>
		<pubDate>Tue, 05 May 2026 15:05:25 +0000</pubDate>
				<category><![CDATA[qPCR]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=88006</guid>

					<description><![CDATA[qPCR Troubleshooting involves identifying and resolving common issues such as contamination, pipetting variability, reagent integrity, and reaction setup errors. This guide provides a clear framework to diagnose symptoms, optimize conditions systematically, and ensure reliable, reproducible qPCR results. It emphasizes the importance of proper primer handling, cycling conditions, and normalization for trustworthy data interpretation.]]></description>
		
		
		
			</item>
		<item>
		<title>qPCR or RNA-seq for DGE studies: How 3’ end counting eliminates the compromise between speed and scale </title>
		<link>https://bitesizebio.com/87719/choosing-qpcr-or-rna-seq/</link>
		
		<dc:creator><![CDATA[Plasmidsaurus]]></dc:creator>
		<pubDate>Tue, 28 Apr 2026 13:45:00 +0000</pubDate>
				<category><![CDATA[Genomics and Epigenetics]]></category>
		<category><![CDATA[Plasmidsaurus]]></category>
		<category><![CDATA[3' end counting]]></category>
		<category><![CDATA[3' RNA-seq]]></category>
		<category><![CDATA[Genome-wide]]></category>
		<category><![CDATA[qPCR]]></category>
		<category><![CDATA[RNA-Seq]]></category>
		<category><![CDATA[sponsored]]></category>
		<category><![CDATA[Transcriptome]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=87719</guid>

					<description><![CDATA[Choosing between qPCR or RNA-seq often means balancing speed and scope. qPCR is quick but limited to a small set of pre-selected genes, while RNA-seq offers a full transcriptome view but you typically wait weeks to get results. This article explores how 3′ RNA-seq bridges that gap, delivering genome-wide insights in days.]]></description>
		
		
		
			</item>
		<item>
		<title>How to Detect Low-affinity Protein Binding Without Surface Plasmon Resonance</title>
		<link>https://bitesizebio.com/86658/detect-low-affinity-binding/</link>
		
		<dc:creator><![CDATA[Sartorius]]></dc:creator>
		<pubDate>Tue, 14 Apr 2026 09:39:14 +0000</pubDate>
				<category><![CDATA[Chemistry for Biologists]]></category>
		<category><![CDATA[Sartorius]]></category>
		<category><![CDATA[biolayer interferometry]]></category>
		<category><![CDATA[biosensor]]></category>
		<category><![CDATA[microfluidics]]></category>
		<category><![CDATA[sponsored]]></category>
		<category><![CDATA[SPR]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=86658</guid>

					<description><![CDATA[Find out how to detect low-affinity protein binding without using SPR. The Octet® R8e BLI system bridges the gap between speed, simplicity, and sensitivity, transforming drug discovery workflows. ]]></description>
		
		
		
			</item>
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		<title>Your qPCR Primer Design Workflow: From Target Gene to Working Primer Set</title>
		<link>https://bitesizebio.com/87763/qpcr-primer-design/</link>
		
		<dc:creator><![CDATA[Zara Puckrin]]></dc:creator>
		<pubDate>Wed, 08 Apr 2026 13:41:30 +0000</pubDate>
				<category><![CDATA[qPCR]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=87763</guid>

					<description><![CDATA[qPCR Primer design involves a five-stage process ensuring specific, efficient amplification. Key steps include checking for validated primers, choosing detection chemistry, setting primer parameters, addressing mRNA-specific needs, and deciding on singleplex or multiplex assays. Proper design reduces errors and improves assay success, especially when targeting mRNA or multiplexing. This practical guide helps researchers create reliable primer sets tailored to their experimental goals.]]></description>
		
		
		
			</item>
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		<title>Your qPCR Analysis Guide: From Raw Cq Values to a Trustworthy Result</title>
		<link>https://bitesizebio.com/87931/qpcr-analysis/</link>
		
		<dc:creator><![CDATA[Zara Puckrin]]></dc:creator>
		<pubDate>Wed, 01 Apr 2026 11:44:08 +0000</pubDate>
				<category><![CDATA[qPCR]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=87931</guid>

					<description><![CDATA[This guide on qPCR analysis outlines the essential workflow from raw Cq values to reliable gene expression results. It covers defining Cq units, organizing data, validating assays with standard curves, normalizing with stable reference genes, calculating fold changes using ΔΔCt or Pfaffl methods, and interpreting results with appropriate statistics. Following these steps ensures accurate, defensible qPCR data for bioscience research.]]></description>
		
		
		
			</item>
		<item>
		<title>Using Scientific Animation to Present Complex Biological Mechanisms</title>
		<link>https://bitesizebio.com/87226/scientific-animation/</link>
		
		<dc:creator><![CDATA[Simon Reid]]></dc:creator>
		<pubDate>Tue, 31 Mar 2026 10:45:32 +0000</pubDate>
				<category><![CDATA[Writing, Publishing and Presenting]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=87226</guid>

					<description><![CDATA[Biological mechanisms are, by their nature, dynamic. They involve interaction, causality, and specific sequences that unfold over time. Standard scientific communication, however, tends to use static media that cannot represent time. This means that when you show a complex signalling pathway on a slide, your audience must first decode the spatial relationships, then infer the...]]></description>
		
		
		
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			<media:title type="plain">Genomic Medicine</media:title>
			<media:description type="html"><![CDATA[DNA Repair After Genome Editing

“DNA’s Moment of Repair” is a standalone sequence extracted from a broader mechanism of action (MOA) animation focused on gene editing therapies. This segment highlights the cellular DNA repair response following a targeted double-strand break (DSB), a critical determinant of therapeutic outcome in genome editing approaches.
Following nuclease-induced DNA cleavage, cells predominantly engage either non-homologous end joining (NHEJ) or homology-directed repair (HDR) pathways to restore genomic integrity. The efficiency, timing, and fidelity of these repair mechanisms directly influence the success of gene correction or disruption strategies in both somatic and germline editing contexts. [1,2]
This clip visualizes the repair phase in isolation, offering a molecular-level perspective on the processes that underpin genomic stability and therapeutic precision in emerging gene editing platforms.

References:
1.     Scully R, Panday A, Elango R, Willis NA. DNA double-strand break repair-pathway choice in somatic mammalian cells. Nat Rev Mol Cell Biol. 2019;20(11):698–714. https://doi.org/10.1038/s41580-019-0152-0
2.       Yeh CD, Richardson CD, Corn JE. Advances in genome editing through control of DNA repair pathways. Nat Cell Biol. 2019;21(12):1468–1478. https://doi.org/10.1038/s41556-019-0425-z]]></media:description>
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	</item>
		<item>
		<title>The Evolution of Gel and Blot Imaging From Film to Lasers</title>
		<link>https://bitesizebio.com/86597/evolution-of-blot-imaging/</link>
		
		<dc:creator><![CDATA[Azure Biosystems]]></dc:creator>
		<pubDate>Tue, 17 Mar 2026 11:06:18 +0000</pubDate>
				<category><![CDATA[Azure Biosystems]]></category>
		<category><![CDATA[Basic Lab Skills and Know-how]]></category>
		<category><![CDATA[DNA gel]]></category>
		<category><![CDATA[imaging]]></category>
		<category><![CDATA[laser imaging]]></category>
		<category><![CDATA[sponsored]]></category>
		<category><![CDATA[Western blot]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=86597</guid>

					<description><![CDATA[Gel and blot imaging has come a long way. Film gave you sensitivity but slowed you down with darkrooms and inconsistent results. Camera systems sped things up but still left you fighting noise and limited dynamic range. Laser imaging now gives you cleaner signals, sharper focus, and far more flexibility across sample types.]]></description>
		
		
		
			</item>
		<item>
		<title>Interpreting Cellular Metabolism Assays: How Metabolic Crossroads Reveal What Cells Are Really Doing</title>
		<link>https://bitesizebio.com/87214/interpreting-cellular-metabolism-assays/</link>
		
		<dc:creator><![CDATA[Promega]]></dc:creator>
		<pubDate>Fri, 27 Feb 2026 12:45:00 +0000</pubDate>
				<category><![CDATA[Promega]]></category>
		<category><![CDATA[Techniques]]></category>
		<category><![CDATA[cellular metabolism]]></category>
		<category><![CDATA[metabolic assays]]></category>
		<category><![CDATA[mitochondrial function]]></category>
		<category><![CDATA[pyruvate metabolism]]></category>
		<category><![CDATA[sponsored]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=87214</guid>

					<description><![CDATA[When interpreting cellular metabolism assays, focusing on single pathways can be misleading, as metabolism operates as a connected network. Metabolites such as pyruvate, malate, glycogen, branched-chain amino acids, and β-hydroxybutyrate sit at key metabolic crossroads, where changes reflect shifts in energy routing, redox balance, and stress adaptation. Understanding these junctions helps you evaluate metabolic data more accurately and design experiments that capture the true cellular state.]]></description>
		
		
		
			</item>
		<item>
		<title>Career Planning for Bioscientists in a Changing Job Market</title>
		<link>https://bitesizebio.com/87125/career-planning/</link>
		
		<dc:creator><![CDATA[Gertrude Nonterah]]></dc:creator>
		<pubDate>Tue, 17 Feb 2026 09:33:58 +0000</pubDate>
				<category><![CDATA[Career Development and Networking]]></category>
		<guid isPermaLink="false">https://bitesizebio.com/?p=87125</guid>

					<description><![CDATA[The traditional career pathway for most scientists is to get a degree, a postdoc, and then a permanent position. But in the 21st century, a PhD no longer ensures security or a smooth career path. Your career plan&#160;is in your hands, and this means you must proactively control your professional identity. Two forces are challenging...]]></description>
		
		
		
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