Mel Mann, MBA, M.Ed engagement report
@MelDMann - 476K followers on X
Measured over 33 original posts from a 30-day window, last computed on October 23, 2026.
Engagement
A typical post picks up 3 interactions against 476K followers, an engagement rate of 0.001%. Measured over 33 original posts, its engagement rate beats 8% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 412 times each, and 0.728% of those impressions turn into an interaction. That is about 0.086% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 12:00 UTC, and Thursday is the busiest day of the week. Of the 33 posts sampled, 61% carry an image or video and 39% link out. The account's strongest tracked post pulled 37K interactions, about 12307x its own typical post.
Measured over 33 original posts from a 30-day window, last computed on October 23, 2026.
Compared with accounts its own size
Mel Mann, MBA, M.Ed's engagement rate beats 8% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 39% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.001%, Mel Mann, MBA, M.Ed sits below the 10th percentile of the 204,956 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 12:00 UTC, and Thursday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 61% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 39% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 61% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 39% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 424 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Oct 21, 201512307x their median
20 yrs ago, I had terminal #Cancer with no cure in sight. Read about my miracle! https://t.co/MfHdMK7BSa #Retweet https://t.co/kWXiiOKQw3
- Aug 21, 20264792x their median
Buck Martinez announced today that he is now cancer free So happy for Buck https://t.co/h0okFWUeIz
- Apr 29, 2026745x their median
A Mayo Clinic-developed artificial intelligence (AI) model can help specialists detect pancreatic cancer on routine abdominal CT scans up to three years before clinical diagnosis. It identifies subtle signs of disease before tumors are visible, when curative treatment may still be possible. The findings, published in Gut, mark a milestone in Mayo Clinic's multiyear research effort to enable earlier detection of one of the deadliest cancers. Learn more: https://t.co/EJySSkaW3P
- Jul 12, 2023242x their median
Today we honor Cleveland Clinic heart surgeon René Favaloro on what would have been his 100th birthday. Dr. Favaloro introduced coronary artery bypass surgery into clinical practice. It's a procedure that has saved countless lives since. https://t.co/t8CqUF3vQe
- Aug 21, 2026820x their median
The world's oldest living person is celebrating turning 117 years old. Read more: https://t.co/NqJlNVVwQI https://t.co/pE9IZmTDpc
- Aug 21, 2026465x their median
Stomach pain location can give important clues. This map breaks down common causes by area - from acid reflux between the ribs to appendicitis on the lower right. Educational only; see a doctor for persistent pain. https://t.co/xIwV2CGhWS
- Oct 22, 2026409x their median
Breaking: Moderna shares plunged 25% after details of its breakthrough mRNA-based cancer vaccine were shared on social media https://t.co/CkU7alJw3n
- Aug 20, 2026371x their median
He never charged copays, often covered medications out of his own pocket, and gave out his personal phone number so families could reach him anytime. His dedication to the community was unwavering. Then, in a cruel twist of fate, Dr. Z was diagnosed with two different forms of cancer. A paperwork issue caused him to lose his own health insurance, leaving him facing radiation treatments costing more than $150,000. When his patients learned of his situation, they rallied together. More than 3,400 people contributed to a GoFundMe campaign, raising over $250,000 to help cover his medical bills. Even while battling cancer, Dr. Z continued seeing patients every day. His remarkable story of compassion and community reciprocity was later honored in the official U.S. Congressional Record.
- Aug 20, 2026363x their median
Most exercise and aging studies can't answer a basic question: is muscle deterioration from aging itself, or just from decades of moving less? A new Nature Aging study solved this by recruiting older adults who moved as much as people in their twenties. The researchers from Amsterdam UMC and Maastricht University recruited four distinct groups: young adults in their twenties, older adults whose daily step counts and high-intensity activity matched the young group, older adults who had trained consistently for years (three structured hour-long sessions per week for over a year), and older adults with early physical impairment. They took muscle biopsies before and after a one-hour cycling session, then measured over 24,000 gene transcripts, 135 metabolites, and 1,383 lipid species. By matching activity levels between young and older groups, any molecular differences couldn't be blamed on the older adults simply moving less. This isolated aging from inactivity for the first time at this molecular depth. Key findings: • The defining molecular signature of muscle aging is an energy crisis. Comparing young adults to activity-matched older adults, 1,106 genes were downregulated with age. These genes build the mitochondrial machinery that produces cellular energy: ATP synthase, cytochrome c oxidase, and NADH dehydrogenase subunits. Mitochondria are the power plants of cells, converting nutrients into ATP, the energy currency cells use to function. When these genes decline, cells lose their ability to generate energy efficiently. • NAD+ levels declined and triglycerides accumulated inside aging muscle. NAD+ is a molecule required for energy production and cellular repair. Lower NAD+ means less capacity to convert fuel into usable energy. Triglycerides are stored fats, their accumulation inside muscle indicates unburned fuel piling up as the tissue loses its ability to process it. • More than half the molecular signature of muscle aging was absent in trained older adults. Specifically, 57.1% of age-related gene downregulation and 55.9% of upregulation were missing in the trained group. Their muscle resembled young adults far more than their chronological age would predict. • The changes training preserved were specifically the energy metabolism ones. Genes like NDUFS1 and COX5A, which were depleted in normally active and impaired older adults, sat at youthful levels in the trained group across all five mitochondrial respiratory complexes. The single most prominent feature of muscle aging turned out to be the single most preventable. • Being generally active was not enough. Structured training was the difference. The normally active older adults walked as much as young adults, and their energy metabolism genes declined anyway. What preserved the youthful molecular profile was structured, sustained training. Filling a step counter and being genuinely trained are not equivalent at the molecular level. • Roughly half of muscle aging persisted regardless of training. Changes in genes controlling synaptic transmission (how nerves communicate with muscle) and WNT signaling (a pathway regulating tissue maintenance and stem cell function) appeared in all older adults, trained or not. This unavoidable half is where drugs will have to work. • The fittest muscle mounted the largest inflammatory response to exercise. All groups activated stress and immune genes after exercise, including IL6, IL1B, and TNF. But the magnitude scaled with fitness. Trained older adults most closely resembled young adults in their response, followed by normally active, with impaired older adults showing the most blunted response. The stress response to exercise appears to be the mechanism of adaptation, not damage to be minimized. This raises a concern about anti-inflammatory longevity strategies. If the inflammatory stress response is how exercise produces its benefits, chronically suppressing inflammation may blunt the adaptation that exercise depends on. It doesn't mean inflammation is beneficial in general, but the timing and context matter. A separate discovery: the proteasome appears to regulate NAD+. The proteasome is the cellular machinery that breaks down damaged proteins. When researchers inhibited it, NAD+ levels rose in both muscle and liver cells to a degree comparable to NAD+ precursor supplements. This opens a new route to understanding NAD+ decline that operates through protein turnover rather than just supplying more raw material. The study draws a clear line between what lifestyle can address and what will require therapeutics. The energy metabolism decline, mitochondrial deterioration, and NAD+ depletion that define muscle aging are largely preventable through structured training. The synaptic and signaling changes that persist in all older adults represent the unavoidable half where drugs will need to work. The decisions made about structured training in midlife determine which molecular trajectory muscle follows in later decades. Half of muscle aging is optional. The other half isn't. Knowing which changes belong to each category is knowing where behavior ends and biology takes over.
- Aug 28, 2026318x their median
On the way to check into the hospital, I took Super Bubba on a dinosaur hunt. He picked out a new T-Rex. 🦖 Tomorrow he has surgery to place a chemotherapy port for the second time in his short life. His first port was removed a couple of months ago because he was cancer-free. Unfortunately, things change. Change is the one guarantee in life. A trip to the store for a new toy isn’t a consolation prize for brain cancer. A new toy to open up and play with when we arrive makes the hospital stay a little more bearable for him. The hospital stay will consist of pain, poking, prodding, and doing things we both don’t want to do but have to do for his cure. I do my best to make as many happy moments for him as possible. He had a good time at the store. I’m so proud of this three-year-old cancer warrior who teaches me about resilience and endurance every day. I pray for his second miracle: to be completely cured of brain cancer. 🙏💪🎗️💛 #prayers #cancer @RevAJKingdom
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 3 interactions against 476K followers, an engagement rate of 0.001%. Measured over 33 original posts, its engagement rate beats 8% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 412 times each, and 0.728% of those impressions turn into an interaction. That is about 0.086% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 12:00 UTC, and Thursday is the busiest day of the week. Of the 33 posts sampled, 61% carry an image or video and 39% link out. The account's strongest tracked post pulled 37K interactions, about 12307x its own typical post.
- What is Mel Mann, MBA, M.Ed's engagement rate on X?
- Mel Mann, MBA, M.Ed (@MelDMann) has an engagement rate of 0.001%, based on the median interactions across 33 original posts from the last 30 days against 476,379 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.001%, Mel Mann, MBA, M.Ed sits below the 10th percentile of the 204,956 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @MelDMann have real engagement?
- Its engagement rate beats 8% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the bottom 10% for its size group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @MelDMann post?
- Most posts go out around 12:00 UTC, and Thursday is its busiest day, at roughly 1.47 posts per day across the measured window.