Channel
@saimsara_mlhs
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
5subscribers
+0 since we began measuring on 10 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003600945681 |
|---|---|
| Type | Channel |
| Username | @saimsara_mlhs |
| Description | independent medicine and life-science database — machine-generated, human-reviewed, and built as an evidence layer for research, clinical-support, and educational AI/RAG workflows. |
| Created | Between 1 December 2025 and 30 May 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 13 August 2026 |
| Last confirmed live | 25 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/saimsara_mlhs |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 03:46 | 5 | no change |
| 10 Aug 2026, 16:16 | 5 | first reading |
20 posts held, back to 30 May 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 1 page of 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 20 posts for this entry, the most recent from 24 June 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
2 reactions across 2 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 100.0% |
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 2 of the 20 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 2 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 30 May 2026 to 24 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.
What does the academic evidence really show about Ethereum blockchain? The latest SAIMSARA review explores scientific findings on blockchain security, smart-contract vulnerabilities, gas fees, fraud detection, MEV, censorship, DeFi, NFTs, scalability, privacy, governance, and real-world applications. Bringing together 250 references and 488 original studies, it provides the largest consolidated academic evidence su…
Can digital democracy expand participation without deepening polarization, exclusion, and manipulation? This SAIMSARA review maps 66 references, 85 original studies, and 14,053,701 participant/sample observations. Read the full evidence map: https://doi.org/10.62487/saimsara83270bae #DigitalDemocracy #AI #CivicEngagement #SAIMSARA
Rowing offers far more than cardiovascular fitness. This evidence map explores mortality, metabolic health, rehabilitation, mental well-being, injury risk, RED-S, and waterborne illness across 88 references, 129 original studies, and 397,842 participant/sample observations. Full review: https://doi.org/10.62487/saimsara07e15486 #Rowing #SportsMedicine #ExerciseScience #Rehabilitation #SAIMSARA
Fear of missing out (FOMO) is more than a social-media habit. This scoping review maps how FOMO relates to mental health, sleep, problematic digital use, impulsive buying, investment decisions, workplace strain, and risk behavior. The evidence map was built from 351 references, 722 original studies, and 313,672 topic-deduplicated participant/sample observations. Read the full SAIMSARA scoping review and explore th…
❤1
Thin-cap fibroatheroma identifies dangerous coronary plaques that may trigger major cardiovascular events even when the artery is not severely narrowed and routine blood-flow testing appears normal. The full review reveals how TCFA can refine risk stratification, how lipid-lowering therapy may stabilize vulnerable plaques, and whether imaging-guided intervention could change outcomes. Built from 225 references, 457…
Jogging can improve cardiorespiratory fitness, blood pressure, lipid profiles, metabolic health, and longevity. However, it may also trigger rare serious cardiovascular events in susceptible individuals, making exercise dose and pre-participation risk assessment important. Our new SAIMSARA scoping review maps the benefits, risks, mechanisms, and clinical implications of jogging using 59 references, 86 original studi…
Why do patients miss healthcare appointments? Not just forgetfulness. No-shows are often driven by access barriers, appointment delays, competing life priorities, and weak follow-up systems. SAIMSARA mapped 242 references and 456 original studies — readable by humans and machines: https://doi.org/10.62487/saimsarabe3a427b #MissedAppointments #NoShowRates #HealthcareAccess #PatientEngagement #DigitalHealth #Health…
Inhaled insulin Diabetes treatment still often depends on insulin injections. An inhaled alternative is now a real option—offering faster mealtime control and fewer injections, while pulmonary safety remains unresolved. 159 original studies mapped: https://doi.org/10.62487/saimsara989b2320 #InhaledInsulin #Diabetes #SAIMSARA
The glymphatic system may be one of the brain’s key waste-clearance pathways—and its dysfunction is now linked to sleep disorders, stroke, Alzheimer’s disease, Parkinson’s disease, inflammation, and systemic illness. We mapped the evidence across more than 1,000 original studies and 592 linked references. Read the full evidence review: https://doi.org/10.62487/saimsara1f2993f5 #GlymphaticSystem #Neuroscience #Brai…
🅔🅧🅞🅢🅚🅔🅛🅔🅣🅞🅝🅢 Medical and industrial human augmentation has become a reality, and the evidence base is growing at enormous speed. We mapped it in a review with more than 1,000 linked references, available both as a full read and as machine-readable JSON for AI/LLM workflows: https://doi.org/10.62487/saimsara376ef1fa #Exoskeletons #WearableRobotics #Rehabilitation #HumanAugmentation #OccupationalHealth #AssistiveTec…
🅔🅑🅞🅛🅐 virus disease is not only a lethal infection — it is a full public-health stress test. Survival depends on viral load, age, rapid care, vaccination, therapeutics, community trust, and health-system resilience. Built on 810 linked references, this SAIMSARA review maps the evidence on Ebola virus disease — from vaccines and monoclonal antibodies to relapse, viral persistence, survivor sequelae, diagnostics, out…
🅟🅒🅢🅚➒ is no longer just about “bad cholesterol.” The topic has become a real scientific hotspot, with thousands of research papers already published — from cardiovascular outcomes to inflammation, thrombosis, kidney disease, neurobiology, pregnancy, and cancer immunity. We screened 7,229 PubMed records, mapped 3,450 original studies, and linked 642 references into one SAIMSARA evidence paper — readable as a review …
Showing the 12 most recent of 20 posts we hold for @saimsara_mlhs. 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 — 728,326 of 1,629,518 entries 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.
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.
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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“☸️SAIMSARA” (@saimsara_mlhs), 5 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/saimsara_mlhs.
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.