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| Research Topics: |
| INDEX |
| AI-chat 4 |
| MCS 1 |
| PRIME 19 |
| PRIO 1 |
| aging 13 |
| brain 12 |
| cancer 7 |
| climate 1 |
| cognition 6 |
| covid-19 3 |
| culture 1 |
| dental 1 |
| diabetes 5 |
| diagnostics 4 |
| gender 1 |
| genetics 5 |
| gut 1 |
| heart 10 |
| herbs 2 |
| immune 5 |
| language 1 |
| lungs 1 |
| metabolism 2 |
| microbiome 3 |
| nutrition 7 |
| pain 2 |
| politics 4 |
| pollution 1 |
| population 1 |
| practice 1 |
| psychology 6 |
| reproduction 2 |
| sleep 3 |
| soc-media |
| tech 1 |
| unk |
| war-confl |
|
Scanned: 2728 Evaluated: 299 Selected: 66 |
| PRIME   DIABETES HEART   NUTRITION   | ||||||||
Aab04-002 | High Dose NAC | |||||||
| Quote: | Boosts glutathione production. 600mg low dose long term support. 1200mg 30 - 90 dayshelps overcome issues. 14 days, 2,000 aggressive support of healing. not every supplement is right for every person. | |||||||
| Comment: | Some MCS victems swear by it. Not all benefit from it. it jsut depends where you are biochemically broken inside. | |||||||
| Article: | http://youtube.com/watch?v9foOavZyLrg | |||||||
| Search Similar: | Brave Mojeek Startpage Dogpile Bing Googl Lycos Utub Yaho | |||||||
| DIABETES MICROBIOME   | ||||||||
Mdb04-004 | Stage-specific gut microbiome shifts across the Type 2 Diabetes Mellitus spectrum: A systematic review and meta-analysis | |||||||
| Quote: | Conclusion Gut microbiome alterations are subtle and inconsistent in early dysglycemia but become pronounced and reproducible with diabetic complications, suggesting microbiome-based biomarkers may be most clinically useful for identifying disease progression rather than early detection. Limitations include heterogeneity of sequencing methods and reliance on 16S rRNA data, which may restrict taxonomic and functional resolution. To our knowledge, this is the first meta-analysis to systematically evaluate gut microbiome alterations across multiple clinical stages of type 2 diabetes progression. | |||||||
| Abstract: | https://www.medrxiv.org/content/10.64898/2026.01.20.25341999v1 | |||||||
| Full Text: | https://www.medrxiv.org/content/10.64898/2026.01.20.25341999v1.full-text | |||||||
| Search Similar: | Brave Mojeek Startpage Dogpile Bing Googl Lycos Utub Yaho | |||||||
| Search Authors: | Sanaa Harrass Shaimaa Ali Mariam Elshweikh Ricardo Franco-Duarte Thilini N. Jayasinghe, | |||||||
| DIABETES | ||||||||
Mdb04-024 | Characterisation of diabetes-associated adipose tissue dysfunction across the spectrum of body mass index | |||||||
| Abstract: | https://www.medrxiv.org/content/10.64898/2026.01.26.26344859v1 | |||||||
| Full Text: | https://www.medrxiv.org/content/10.64898/2026.01.26.26344859v1.full-text | |||||||
| Search Similar: | Brave Mojeek Startpage Dogpile Bing Googl Lycos Utub Yaho | |||||||
| Search Authors: | Oliver Brown Derek Magee Michael Drozd Marcella Conning-Rowland Marilena Giannoudi Aya Shouma Alexander-Francisco Bruns Natalie J Haywood Lee D Roberts Joanna Kalucka Samuel Relton Mark T Kearney Kathryn J Griffin Richard M Cubbon, | |||||||
| DIABETES | ||||||||
Mdb04-026 | Continuous Glucose Monitoring in Older In-patients with Type 2 Diabetes and Cognitive Impairment: A feasibility study | |||||||
| Quote: | Conclusion CGM use in older in-patients with T2DM and cognitive impairment is highly feasible and acceptable for patients. Future studies and trials are now needed to evaluate the clinical use of CGM for glucose monitoring in hospitalised or community-dwelling older individuals with T2DM and cognitive impairment. | |||||||
| Abstract: | https://www.medrxiv.org/content/10.64898/2026.01.26.26344013v1 | |||||||
| Full Text: | https://www.medrxiv.org/content/10.64898/2026.01.26.26344013v1.full-text | |||||||
| Search Similar: | Brave Mojeek Startpage Dogpile Bing Googl Lycos Utub Yaho | |||||||
| Search Authors: | Busra Donat Ergin Katharina Mattishent Anne M Minihane Richard Holt Helen R Murphy Ketan Dhatariya Michael Hornberger, | |||||||
| DIABETES GENETICS   | ||||||||
Mge04-002 | Disentangling Type 2 Diabetes Risk and Comorbidity Using Genomic Structural Equation Modeling | |||||||
| Quote: | Phenome-wide and comorbidity analyses revealed that each latent factor PGS associated with specific T2D-related complications and provided broader or distinct associations compared with conventional metabolic PGSs, with the obesity and lifestyle-related factor showing the widest impact. These findings illustrate how multivariate genetic approaches can disentangle the biological heterogeneity of T2D, refine polygenic risk prediction, and reveal mechanistic pathways driving divergent patterns of disease and comorbidity. | |||||||
| Abstract: | https://www.medrxiv.org/content/10.64898/2026.01.26.26344825v1 | |||||||
| Full Text: | https://www.medrxiv.org/content/10.64898/2026.01.26.26344825v1.full-text | |||||||
| Search Similar: | Brave Mojeek Startpage Dogpile Bing Googl Lycos Utub Yaho | |||||||
| Search Authors: | Merli Koitme Kristi Lll Mrt Mls Andrew P Morris Krista Fischer Reedik Mgi, | |||||||
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Updated weekly.
01/31/2026-02:32:41 AM
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