Health & wellness — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 87% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
24 measurements spanning 36 days, net +47. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 14,498–14,600 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 24
Measured (UTC)
Subscribers
Change
11 Sept 2026, 12:19
14,562
-10
8 Sept 2026, 16:19
14,572
-6
5 Sept 2026, 12:18
14,578
-10
3 Sept 2026, 15:17
14,588
+27
1 Sept 2026, 05:06
14,561
-5
30 Aug 2026, 04:47
14,566
+1
29 Aug 2026, 03:59
14,565
+6
28 Aug 2026, 07:04
14,559
+1
27 Aug 2026, 03:55
14,558
+5
26 Aug 2026, 03:36
14,553
+4
25 Aug 2026, 00:23
14,549
+19
23 Aug 2026, 12:05
14,530
+2
20 Aug 2026, 13:15
14,528
+3
19 Aug 2026, 12:02
14,525
+3
18 Aug 2026, 12:03
14,522
+1
17 Aug 2026, 13:33
14,521
+8
16 Aug 2026, 07:37
14,513
+1
14 Aug 2026, 21:27
14,512
+2
12 Aug 2026, 11:07
14,510
-1
11 Aug 2026, 07:55
14,511
first reading
Engagement
48 posts held, back to 13 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 51 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
15.2%
avg views ÷ 14,562 subscribers
Avg views / post
2,210
18 posts measured
Reaction rate
0.923%
reactions ÷ views · ER floor
Posts in window
18
of 48 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 2 September 2026
Posts held
48 (13 July 2026 – 2 September 2026)
Views total
39,860
Reactions total
368
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
2 Sept 2026, 18:32 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
13m 34s
Average length
1m 08s
Measured directly from 12 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
1,081 reactions across 48 posts, in 20 distinct kinds. The most used accounts for 67.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
727
67.3%
👍
164
15.2%
🔥
34
3.15%
👌
24
2.22%
🙏
23
2.13%
💯
22
2.04%
😁
19
1.76%
👏
18
1.67%
🥰
13
1.20%
🙈
8
0.74%
🤔
7
0.648%
✍
4
0.37%
🙊
4
0.37%
❤🔥
3
0.278%
🤣
3
0.278%
👀
2
0.185%
😍
2
0.185%
🤨
2
0.185%
💘
1
0.093%
🤩
1
0.093%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 48 of the 48 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 1,081 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 48 most recent posts we hold, published 13 July 2026 to 2 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🧬 Was hat Sauerstoff mit dem Milieu unserer Zellen zu tun?
Bereits der Nobelpreisträger Otto Warburg beschäftigte sich intensiv mit dem Stoffwechsel von Zellen und beobachtete Besonderheiten im Energiestoffwechsel von Tumorzellen.
Doch was passiert eigentlich, wenn Zellen nicht ausreichend über den aeroben Stoffwechsel arbeiten? Welche Rolle spielen Sauerstoff, Glykolyse, Säuren, Mineralstoffe und Spurenelemente? Und…
🌳✨ DU BIST DAS ERGEBNIS EINER UNGLAUBLICHEN GESCHICHTE ✨🌳
Damit DU heute hier sein kannst, brauchte es vor dir:
👩❤️👨 2 Eltern
👵👴 4 Großeltern
🌿 8 Urgroßeltern
🌿 16 Ururgroßeltern
🌳 32 Vorfahren der nächsten Generation
🌳 64 der darauffolgenden
🌳 128
🌳 256
🌳 512
🌳 1.024
🌳 2.048 …
🧬 Rein mathematisch führt diese Verdopplung über 11 Generationen zu 4.094 Ahnenpositionen – und mit jeder weiteren Generation wächst die…
⚡️ Eine Million Blitze pro Tag – und was hat das mit der Schumannfrequenz zu tun?
Die Natur arbeitet permanent mit Energie, Frequenzen und Resonanzen. Doch was passiert dabei eigentlich zwischen Erde und Atmosphäre – und warum ist die Schumann-Resonanz so spannend?
Arthur Tränkle erklärt die Zusammenhänge und zeigt, was wir uns dabei von der Natur abschauen können. 🌍⚡️
🎥 Das komplette Video jetzt auf dem YouTube-Kana…
👂 Geheimdienste könnten künftig sogar in Arztpraxen mithören
Die Bundesregierung will BND und Verfassungsschutz deutlich mehr Überwachungsbefugnisse geben.
Das Brisante:
Ärzte und Psychotherapeuten sollen nach dem aktuellen Entwurf nicht zu den absolut geschützten Berufsgruppen gehören.
Die Kassenärztliche Bundesvereinigung warnt deshalb ausdrücklich davor, dass unter bestimmten Voraussetzungen sogar vertrauliche…
💧 WASSER IST OFFENBAR NICHT EINFACH NUR WASSER
Eine neue Studie in Nature Physics liefert bemerkenswerte Hinweise darauf, dass flüssiges Wasser auf molekularer Ebene nicht als völlig einheitliche Flüssigkeit betrachtet werden sollte.
Forscher um Liwen Li und Xiao Cheng Zeng untersuchten mithilfe umfangreicher Molekulardynamik-Simulationen und unüberwachtem Deep Learning die lokale Struktur von Wasser.
Das Ergebnis…
🔥 BREAKING: Jens Spahn setzt wieder auf bewährte Krisenlösungen!
Nachdem Masken das Coronavirus bekanntlich so zuverlässig aufgehalten haben, soll das Erfolgsmodell jetzt auf Waldbrände übertragen werden:
😷 Corona: Masken
🔥 Waldbrand: Löschpapier
Nur konsequent. 😂
Gerüchten zufolge werden bereits die ersten 10 Milliarden Euro bereitgestellt. Natürlich im Eilverfahren – denn mitten in einer Krise kann man schließl…
🔹 TEIL 3/3 – DIE ENTSCHEIDENDE FRAGE ⚡💧
Die entscheidende wissenschaftliche Frage lautet deshalb nicht:
„Kann man Krebs einfach mit Hochfrequenz heilen?“
Dafür gibt es bislang keinen entsprechenden klinischen Nachweis.
Die viel interessantere Frage lautet:
Wie hängen Wasser, Bioelektrizität, elektromagnetische Wechselwirkungen und die Fähigkeit unserer Zellen zusammen, sich als Teil eines größeren biologischen G…
🔋Teil 2/3
Wurde diese Depolarisation experimentell durch hyperpolarisierende Ionenkanäle verhindert, konnte die Tumorbildung trotz Onkogenexpression unterdrückt werden.
Das bedeutet nicht, dass Krebs einfach durch „Spannung aufladen“ geheilt werden kann.
Aber es zeigt etwas Grundsätzliches:
Der elektrische Zustand einer Zelle kann ihr biologisches Verhalten mitbestimmen.
Gene sind also nicht die einzige Informat…
⚡💧 DER WASSERAKKU DER ZELLE
Bioelektrizität, Wasser und die verlorene Ordnung
Vielleicht wird manches, was heute noch ungewöhnlich klingt, im Jahr 2126 völlig selbstverständlich sein.
Heute betrachten wir den menschlichen Körper überwiegend biochemisch: Gene, Proteine, Hormone, Enzyme und Stoffwechselwege.
Doch Leben ist nicht nur Chemie.
Leben ist auch Elektrizität, Wasser, Information und räumliche Organisatio…
🔥 KUPFER – DER ERSTE DOMINOSTEIN IM MINERALSTOFFWECHSEL? 🟠
Wenn von „Detox“ gesprochen wird, denken viele sofort an Zeolith, Aktivkohle, Chlorella, Koriander oder andere Binder.
Doch vielleicht beginnt die entscheidende Frage viel früher:
Wie gut funktionieren eigentlich die körpereigenen Systeme, die Mineralien transportieren, regulieren und recyceln?
Und hier spielt KUPFER eine erstaunlich wichtige Rolle. 🟠
Ku…
🧬⚡ MITOCHONDRIEN: HABEN FORSCHER EINEN „SCHALTER“ DES ALTERNS GEFUNDEN?
Mitochondrien sind die „Kraftwerke“ unserer Zellen. Doch mit zunehmendem Alter verlieren sie an Leistungsfähigkeit.
🔬 Eine neue Studie des Leibniz-Instituts für Alternsforschung liefert einen spannenden Hinweis auf einen möglichen Mechanismus:
👉 Phosphatidylcholin (PC)
Die Forscher fanden heraus, dass die PC-Synthese mit zunehmendem Alter abn…
❤15👍1🥰1😍1
Showing the 12 most recent of 48 posts we hold for @wassermatrixinfo. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Posts edited after publishing
@wassermatrixinfo edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
13 August 2026
Most recent edit
13 August 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 8 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
🇨🇭QS24 | Schweizer Gesundheitsfernsehen - Eine Perspektive mehr Gesundheit & Persönlichkeitsentwicklung. @QS24_tv · 27,103 Telegram ranks this channel #54 of 73 here — alongside 72 others — read 11 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 11 September 2026 — this
entry's latest reading, not the date you are reading this.
“Wassermatrix” (@wassermatrixinfo), 14,562 subscribers as measured 11 September 2026. Telegram Register, tgregister.com/channel/wassermatrixinfo.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.