Telegram RegisterThe public register of Telegram

Channel

自我療愈圖書館

@MMSLibrary

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

6,943subscribers

-5 since we began measuring on 8 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001779251874
TypeChannel
Username@MMSLibrary
CreatedBetween 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live12 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/MMSLibrary

Growth

6,9436,9486,945.58 August 2026 — 6,948 subscribers9 August 2026 — 6,947 subscribers12 August 2026 — 6,943 subscribers8 August 202612 August 2026
3 measurements spanning 4 days, net -5. 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 6,942–6,949 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 05:066,943-4
9 Aug 2026, 14:176,947-1
8 Aug 2026, 15:316,948first reading

Engagement

10 posts held, back to 11 September 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 5 pagesof Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 10 posts for this entry, the most recent from 3 June 2026. An engagement rate over an empty window would be a number about nothing.

What this channel posts

Video runtime
1h 04m
Average length
1h 04m

Measured directly from 1 video 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

268 reactions across 10 posts, in 7 distinct kinds. The most used accounts for 52.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍14152.6%
9836.6%
🎉165.97%
😁51.87%
🙏51.87%
🥰20.746%
🤩10.373%

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 10 of the 10 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 268reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 10 most recent posts we hold, published 11 September 2025 to 3 June 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.

Recent posts

3 Jun 2026, 08:23 UTC≈2,520 views35 reactionsread 12 August 2026

頻道已開通私訊 (直接跟群主對話) t.me/MMSLibrary?direct 群主不是你們的私人健康顧問,平時請在群組討論,共同學習❤️ 如有疑難、遇到難以開口的問題,想提供有爭議的新療法、療法學術探討,歡迎先在群組打招呼,得到群主回應後再私訊,否則恕不回應。

👍285🥰2

30 May 2026, 01:12 UTC≈2,910 views37 reactionsread 12 August 2026
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題外話:【防疫】日常食療 抗輻射、健骨骼、修復DNA的防治湯配方 能夠理解這個食療配方為何發揮作用,需要很多知識層面和知識含量作基底。建議納入經常性飲食。 1. 防疫 = 防輻射傷害 輻射會損害人體的DNA修復,降低紅血球的攜氧量等;同時輻射會和人體內的重金屬、與寄生蟲和真菌細菌互相增效、倍加傷害。如COVID 輻射是引爆點,引爆長期在體內的各種毒素,令寄生蟲真菌細菌大量繁殖。而毒素和重金屬是寄生蟲真菌的食物,輻射造就身體缺氧環境。 這跟他們長期用飛機尾凝器在空氣中噴灑有毒重金屬、強迫注射疫苗、食物中的農藥重金屬、含氟的水和牙膏、化妝品中的重金屬、化纖衣服增加人體電荷、各種食物添加劑、用氫化種子油煮食等等長期洗腦+直接毒害有關,每次大疫情都是由輻射引起,回顧歷史參考: https://t.me/c/1684756562/233 2. 食材成份功能 裙帶菜、海帶、非基改味噌、海鹽、硼砂,按味噌湯做法即可。份量隨意,納

27👍8🤩1🙏1

18 Apr 2026, 07:55 UTC≈3,920 views43 reactionsread 12 August 2026
Photo

96歲老人進了搶救室、下了三次病危通知書,被mms救回來! 起初老人是因為嗆咳無法進食,之後肺部感染在家吸氧,隨後送往北京三甲醫院。 醫生用鼻管胃飼、使用無創呼吸機提供純氧,結果越來越嚴重演變成半邊白肺。 一度氧氣濃度加到100%,血氧仍降到90%以下,一半肺失去功能,被醫生下了三次病危通知書、進了搶救室及宣判不可能康復(沒得救)。 群友果斷用鼻管喂了老人7滴mms(Mms是要稀釋的),一小時內血氧升到96。喂了三次以後,血氧升到99-100。群友一直喂mms,之後醫生把純氧調低到80%,當晚就把純氧降到50%。到第三天,照胸片顯示半邊肺已經張開、白肺消失了。 群友使用劑量及次數 Mms是要稀釋的,滴數只是mms劑量,並不另外列出水量 第一天:每次5-7滴,早晚共喂了13次 第二天:每次5-7滴,早晚共喂了13次 第三天:每次5-7滴,早晚共喂了10次 群主有話要說 1. 呼吸機是奪命的,看連結 https://

👍2317🙏2😁1

17 Apr 2026, 10:35 UTC≈2,630 views17 reactionsread 12 August 2026

Telegram重大設定 ! 設定 → 中文/簡體介面 Telegram已開通 中文搜索功能 很感謝群友Faye提供這麼實用的資訊❤️

🎉10👍32😁2

13 Apr 2026, 14:27 UTC≈3,230 views13 reactionsread 12 August 2026

其他群组 🔹通用解毒剂视频及见证分享 (此群组与TUA聊天室不同) https://t.me/theuniversalantidote 🔹二氧化氯科学文献 https://t.me/ChlorineDioxideScience 🔹吉姆·汉布尔MMS1方案 https://t.me/JimHumbleProtocols 🔹CDS方案 https://t.me/AndreasKalckerProtocols 🔹MMS与CDS供应商链接 https://t.me/mmsCDSlinks 🔹亚甲蓝 https://t.me/+FhnNqp0q920zMWJh 🔹禁食 https://t.me/fastingbenefits 🔹营养补充剂 https://t.me/suppsforhealth 🔹替代药物 https://t.me/alternateMedsMMSCDS 🔹芬苯达唑和伊维菌素 https://t.me/

👍10🙏21

4 Apr 2026, 09:34 UTC≈3,790 views18 reactionsread 12 August 2026
Video

通用解藥 二氧化氯紀錄片 Part4 二氧化氯作為萬能通用解藥的案例見證! 特別鳴謝:群友ET辛苦幫忙翻譯及較對,感謝付出❤️ 來源及PDF下載:https://theuniversalantidote.com/ 參考資料:https://www.sciencedirect.com/topics/medicine-and-dentistry/chlorine-dioxide 紀錄片系列回顧 通用解藥 二氧化氯紀錄片 Part1 通用解藥 二氧化氯紀錄片 Part2 通用解藥 二氧化氯紀錄片 Part3 ----------------------------------------- MMS能解突刺蛋白的毒和去除絕大多數的寄生蟲,能治療疫苗後遺症如血栓、心肌炎、癌症、愛滋病、神經系統及免疫系統疾病等,已經有超過百萬人的治療經驗和案例!也是備受陰謀集團強力打壓的療法! 🔙返回目錄 請關注頻道 https://t.me/MM

👍117

14 Feb 2026, 15:24 UTC≈4,840 views30 reactionsread 12 August 2026
Photo

2026美國司法部文件證實 疫情獻祭殺人虐待性侵兒童 ❌陰謀論 ⭕️現實 題外話但非常重要! 揭露僅是冰山一角 2026年美國司法部公佈了300多萬頁文件、2000部影片,以及18萬張影像,所謂虐待性侵兒童、殺人吃人、策劃疫情等 “陰謀論”一一被證實。由全球最有權力人士共同推進的議程 無論你接不接受、相不相信,你就是在遊戲中,你,逃離不了被精英操控的命運,直至你願意去面對或死去。 Welcome to the cruel world. From this moment on, you are the one who is awake. 懶人包影片,有字幕 https://youtu.be/g1WhBvJc-fc 如需更多資料,直接去看文件!要下載的就盡快,文件已經有部分消失/變更。 美國司法部文件 https://www.justice.gov/epstein/doj-disclosures

👍217😁2

3 Oct 2025, 07:55 UTC≈7,620 views54 reactionsread 12 August 2026
Photo

辦公室泡腳記 生活繁忙,要每天抽空15分鐘泡腳已成不可能的事。但每天一到兩次邊工作邊泡腳非常可行,省水省材料+高效不浪費一丁點時間。 準備工具 1. 塑膠袋(圖那種最好,便宜好用又貼腳,次拋不心痛) 2. 玻璃量杯50ml 3. 涼鞋(必須有後跟帶) 泡腳配方 自行配搭,下面配方及份量僅供參考 A. MMS 8滴+60ml水/每隻腳 B. 姜粉 5g+60ml水/每隻腳 C. 排毒配方(膨潤土&硫酸鎂/氯化鎂&硼&小蘇打) 15g +60ml水/每隻腳 D. 硼砂+鎂溶液,泡腳底 步驟 1. 腳先套塑膠袋,在穿上鞋 2. 弄好泡腳材料(最好用温熱水),在沿塑膠袋邊緣倒進去,之後要鬆一下後腳跟的塑膠袋,務求整腳都有液體泡着 3. 泡15~30分鐘,結束 祝各位泡腳愉快!😆

👍3316🎉5

11 Sept 2025, 12:07 UTC≈7,100 views20 reactionsread 12 August 2026
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療法核心:啟動身體最強大的自噬——每个细胞中对抗衰老的管家 非常有用的文章!極力推薦研讀,包括裏面其他文章的連結。很多自然療法真正發揮作用,其部分原因是---激發了自噬,比任何療法都更有效,因為這是身體天生自帶的強大清掃、修復及再生系統 原文節錄: 自噬是细胞清除功能失调或错误折叠蛋白质的主要方法之一。 自噬可以清除任何类型的“垃圾”:细胞内病毒、细菌、受损蛋白质、蛋白质聚集体以及亚细胞器。 自噬在一定程度上解释了热量限制、咖啡因、绿茶、雷帕霉素、白藜芦醇、二甲双胍、亚精胺、锂、运动、缺氧、Torin-1、海藻糖以及许多其他天然和合成化合物的有益作用。 相比其他任何长寿干预措施,例如补充外源性抗氧化剂、上调内源性抗氧化剂、微量营养素替代疗法、激素替代疗法、抗炎疗法、激活端粒酶或干细胞疗法,自噬激活与长寿之间的关联性证据更为有力…… ____________ 文章真真真真真長,需要花不少時間閱讀及消化。 上圖就是懶

16👍3🎉1

Showing the 10 most recent of 10 posts we hold for @MMSLibrary. 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.

Citation-graph rank

Citation-graph rank — 917,031 of 1,345,403entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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 1 registered channel — 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.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“自我療愈圖書館” (@MMSLibrary), 6,943 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/MMSLibrary.

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.