Why is it so easy to regain weight after losing it?

Fat cells hold a grudge—they retain an 'obesity memory'! Spend just a hundred or so yuan on an EGCG metabolism supplement to block this obesity memory and boost your body’s fat metabolism. Once energy expenditure exceeds intake, nothing can stop you from slimming down. For example, I personally lost 40 jin (20 kg), my belly flattened, my limbs became slimmer—and crucially, there was no rebound! I spend every day in the lab, poring over research papers to understand the mechanisms of fat metabolism—only then could I achieve such outstanding results. Among all the literature I’ve studied, the most pivotal finding comes from a groundbreaking study published in Nature by a team at ETH Zurich—a study that completely overturned my understanding: frequent weight regain after fat loss isn’t due to weak willpower or a slowed basal metabolic rate; rather, it’s because 'fat memory cells' retain their obesity-associated memory even after weight loss. In simple terms: Even after you lose weight through dieting and exercise, these fat cells continue operating with the same metabolic habits they had during obesity. 1. High fat-synthesis efficiency: Cells with obesity memory preferentially store energy as fat. 2. Slow fat-breakdown rate: When the body needs fatty acids for energy, these fat cells resist releasing stored fat. So, when you resume your original eating and exercise habits—and caloric intake once again exceeds expenditure—these fat memory cells activate their fat-storage program, causing rapid weight regain. Moreover, these fat cells retain 'location memory', preferentially depositing new fat in areas where you previously accumulated fat—such as the abdomen and thighs. That’s why sometimes your weight increases only slightly, yet you visibly appear much heavier. Even more alarming: this obesity memory in fat cells can persist for several years. If you fail to maintain long-term discipline, you’ll reactivate their fat-storage program—disrupting your fat-loss rhythm and inevitably triggering weight rebound and body-shape deterioration. To defuse this 'obesity time bomb', follow authoritative science. A landmark study published in the Journal of Agricultural and Food Chemistry (JAFC) demonstrated that EGCG acts on gastric endocrine cells and the hypothalamic feeding center, simultaneously reducing the number of memory cells and inhibiting their fat-synthesis activity—thereby curbing fat accumulation. Combined with extracts from Phyllanthus emblica (amla) and mulberry leaf, plus B vitamins: — One component suppresses the activity of fat memory cells, — And prevents excess sugar from being deposited specifically in the abdomen and thighs.

Airppb (Beijing Minti) Research Methodology Observation #4 | For quantitative online breath analysis, why must calibration gas be added 'in real time into exhaled breath'?

Airppb (Beijing Minti) Research Methodology Observation #4 | For quantitative online breath analysis, why must calibration gas be added 'in real time into exhaled breath'? Based on publicly available research from ETH Zurich, this article dissects the data chain: 'controlled vaporization → online spiking → real-time mixing with exhaled breath → SESI-MS quantification'. Online breath analysis enables continuous sampling directly from natural exhalation into a mass spectrometer—eliminating the need for breath collection bags or sample pre-processing. Yet one easily overlooked issue remains: detecting a compound does not guarantee accurate quantification. If a calibration curve is prepared externally—e.g., using bottled dry standard gas—and then used to calculate the concentration of a given analyte in breath, the resulting values may suffer large errors. This is because exhaled breath is a highly complex matrix, nearly saturated with humidity and rich in diverse chemical components. The ionization efficiency of any given substance differs significantly across different matrices. In 2024, the Zenobi group at ETH Zurich published a technical note in Analytical Chemistry, describing a custom-built internal standard addition system: low-concentration (7–30 ppb) standards—including pyridine and butyric acid—are added stepwise and in real time into volunteers’ exhaled breath. Quantification is performed via the standard addition method; the same system also enables online dilution of breath samples, helping distinguish whether detected signals originate from breath itself or from background contamination. Paper link: ACS original article, PMC free full text. This observation addresses the following question: When calibration must be performed 'within the exact same matrix as the sample', what requirements must the gas-mixing step fulfill? I. Although SESI-MS can directly measure breath, why can’t we directly calculate concentrations? There are three main online breath-MS techniques. SESI-MS is especially suitable for relatively heavy, polar molecules and is widely used in exploratory breath biomarker studies—but its ionization mechanism remains incompletely understood. Online technique Ionization/reaction mechanism Quantification pathway SIFT-MS Well-characterized reaction mechanism Concentration calculated from kinetic rate constants PTR-MS Well-characterized reaction mechanism Concentration calculated from kinetic rate constants SESI-MS Mechanism still under investigation, not fully resolved Requires standard gases and calibration curves; standard addition recommended for complex matrices The paper notes that SESI ion suppression depends on both the gas-phase basicity and concentration of involved compounds. Given the highly variable chemical composition and fluctuating concentrations in exhaled breath, external calibration—performed outside the breath matrix—is likely insufficient: the sensitivity measured for a standard compound in a non-breath matrix cannot reliably represent its true sensitivity within the actual breath matrix. Therefore, the research team adopted the standard addition method: known amounts of target analytes are added incrementally to authentic breath samples, and mass spectrometric signal intensities are plotted against the added amounts to generate a linear regression. The original concentration in breath is then extrapolated from the y-intercept of this regression line. In short: SIFT-MS and PTR-MS operate via 'well-understood mechanisms enabling direct calculation'; SESI-MS delivers strong signals but lacks a fully elucidated mechanism—so quantification requires introducing the standard directly into the very environment occupied by the sample. II. What is the difference between external calibration and the standard addition method? Comparison item External calibration (standard gas curve prepared separately from breath) This study’s online standard addition Calibration matrix Bottled standard gas or independently prepared standard gas Volunteer’s authentic exhaled breath Humidity & coexisting components No breath background—even if humidified, lacks the complex mixture of coexisting components found in real breath Preserves full breath background and ion-suppression environment Ionization efficiency Efficiency measured in non-breath matrix Actual efficiency within the breath matrix Concentration calculation Direct conversion using external calibration curve Linear regression of signal vs. added amount; concentration derived by extrapolating to zero-addition intercept Key limitation Systematic bias due to matrix mismatch Requires multi-level online spiking within a single exhalation sequence

ETH Zurich Develops Breathalyzer to Monitor Fat Burning

Jul 22, 2026

Researchers at ETH Zurich created a handheld breathalyzer measuring exhaled acetone to indicate whether the body is burning fat or carbohydrates.

cen

2026-07-22

ETH Zurich Develops Breathalyzer to Monitor Fat Burning

2026-10-23

ETH Zurich Researchers Develop Implant to Convert Blood Glucose in Mice

ETH Zurich Develops Breathalyzer to Monitor Fat Burning

FAQ