RE: https://bsky.app/profile/did:plc:wf4t57jfj6xbvv4j7ebpy5z6/post/3mkntjym5r22f
Aidez ร prรฉserver l'efficacitรฉ des antibiotiques ๐ pour tous:
โ
Ne prenez que les antibiotiques qui vous ont รฉtรฉ prescrits
โ
Demandez si cette prescription est le traitement recommandรฉ de 1รจre intention
โ
Lavez-vous les mains & faites-vous vacciner
Ministerstvo zdravotnictvรญ ๐๐ @[email protected]:
Vyhlaลกujeme vรฝtvarnou soutฤลพ pro dฤti Zastavme superbakterie! , urฤenรก pro zรกkladnรญ ลกkoly. Dฤti se seznรกmรญ s problรฉmem antibiotickรฉ rezistence a vytvoลรญ obrรกzky, komiksy nebo pลรญbฤhy o bakteriรญch.
Nejlepลกรญ dรญla odmฤnรญme a vystavรญme v ลรญjnu 2026!
๐ค ๋ก๋ด+AI ๋ค ๊ฐ์ก๋ค! LSํฐ๋ผ์ ํ ์ฃผ๊ฐ ์ ๋ง, ์ง๊ธ์ด๋ผ๋ ํ์ผ ํ๋ ์ด์ (์์ต๋ฅ 20% ๊ณต๋ต๋ฒ) โ
LSํฐ๋ผ์ ํ (322180)์ ์ค๋งํธํฉํ ๋ฆฌ ์๋ฃจ์ ๋ฐ ์์จ์ฃผํ ๋ก๋ด(AMR) ๋ถ์ผ์ ์ ๋ ๊ธฐ์ ์ผ๋ก์, ์ต๊ทผ LS๊ทธ๋ฃน์ผ๋ก์ ํธ์ ๊ณผ ํ์ดํ ํฌ ์ฐ์ ๊ตฐ์ ์๋ํ ์์ ์ฆ๊ฐ์ ํ์ ์ด ์์ฅ์ ๋จ๊ฑฐ์ด ๊ด์ฌ์ ๋ฐ๊ณ ์์ต๋๋ค
2026๋ 5์ 8์ผ ๊ธฐ์ค, ์ต๊ทผ 10๊ฑฐ๋์ผ๊ฐ์ ์ฃผ๊ฐ ํ๋ฆ์ ๋จ์ํ ๊ธฐ์ ์ ๋ฐ๋ฑ์ ๋์ด์ ์ ์๋ฏธํ ์๊ทธ๋์ ๋ณด์ฌ์ฃผ๊ณ ์์ผ๋ฉฐ, ์ต์ ๋ฐ์ดํฐ์ ์์ฅ ๋ํฅ์ ์ ๋ฐ ๋ถ์ํ์ฌ, ํฌ์ ํ๋จ์ ์ค์ง์ ์ธ ๋์์ด ๋ ์ ์๋ ์๋ฃ ๊ณต์ ,
LSํฐ๋ผ์ ํ ์ผ๋ด ์ฐจํธ [์๋ฃ:๋ค์ด๋ฒ]1. LSํฐ๋ผ์ ํ ์ต๊ทผ ์ฃผ๊ฐ ์์น ์์ธ ๋ถ์
์ต๊ทผ 10๊ฑฐ๋์ผ ๋์ LSํฐ๋ผ์ ํ ์ ์ฃผ๊ฐ๋ ๊ฒฌ์กฐํ ์ฐ์ํฅ ๊ณก์ ์ ๊ทธ๋ฆฌ๋ฉฐ ์์ฅ์ ์ฃผ๋์ฃผ๋ก ๋ถ๊ฐ๋์์ผ๋ฉฐ, ์ด ์์น์ ํต์ฌ ๋๋ ฅ์ ๋ค์๊ณผ ๊ฐ์ด ์์ฝ๋ฉ๋๋ค
2. ์ต๊ทผ ํธ์ฌ ๋ด์ค ์์ฝ
์์ฅ ํ์ฅ์์ ์ ํด์ง ์ฃผ์ ์์๋ค์ ๋์ฌ์ ํ๋๋ฉํธ ๊ฐํ์ ์ง์ ์ ์ผ๋ก ์ฐ๊ฒฐ๋์ด ์์ต๋๋ค
3. ์ต๊ทผ ์ ์ฉ๊ฑฐ๋ ๋น์ค๊ณผ ์๊ณ ๋ํฅ ๋ถ์
์ ์ฉ์๊ณ ๋ ํฌ์์๋ค์ ๋จ๊ธฐ ํฅ๋ฐฉ์ ๊ฐ๋ ํ๋ ์ฒ๋์ ๋๋ค
4. ์ต๊ทผ ๊ณต๋งค๋ ๋น์ค๊ณผ ๋ํฅ ๋ถ์
์ฝ์ค๋ฅ ์ค์ํ์ฃผ์ธ ๋์ฌ์๊ฒ ๊ณต๋งค๋ ๋ํฅ์ ์ฃผ๊ฐ ์๋ฐฉ์ ์ ํํ๋ ์ฃผ์ ๋ณ์์ ๋๋ค
5. ์ต๊ทผ ์์ฅ์ฌ๋ฆฌ์ ๋ฆฌ์คํฌ ์์ธ ๋ถ์
์ฌ๋ฆฌ์ ์งํ์ ์ ์ฌ์ ์ํ ์์๋ฅผ ๋์์ ๊ณ ๋ คํด์ผ ํฉ๋๋ค
6. ํฅํ ์ฃผ๊ฐ ์์น ์ง์๊ฐ๋ฅ์ฑ ๋ถ์
์์น์ธ๊ฐ โ๋ฐ์ง ๋ฐ๋ฑโ์ ๊ทธ์น ์ง, โ๋์ธ ์์นโ์ ์๋ง์ผ์ง์ ๋ํ ๋ถ์์ ๋๋ค
7. ํฅํ ์ฃผ๋ชฉํด์ผ ํ ์ด์ ๋ถ์
ํฌ์์๋ค์ด LSํฐ๋ผ์ ํ ์ ํฌํธํด๋ฆฌ์ค์ ๋ด์์ผ ํ ํต์ฌ ๋ ผ๊ฑฐ์ ๋๋ค
8. ํฅํ ํฌ์ ์ ํฉ์ฑ ํ๋จ
9. LSํฐ๋ผ์ ํ ์ฃผ๊ฐ ์ ๋ง๊ณผ ํฌ์ ์ ๋ต
์ข ํฉ์ ์ธ ํ๋จ์ ๋ฐํ์ผ๋ก ํฅํ ์ฃผ๊ฐ ์ ๋ง๊ณผ ๊ตฌ์ฒด์ ์ธ ๋์ ์ ๋ต์ ์ ์,
[์ฃผ๊ฐ ์ ๋ง]
[ํฌ์ ์ ๋ต]
LSํฐ๋ผ์ ํ ์ ๋จ์ํ ํ ๋ง์ฃผ๋ฅผ ๋์ด ์ค์ง์ ์ธ โ์ ์กฐ ํ์ โ์ ์์ด์ฝ์ผ๋ก ๊ฑฐ๋ญ๋๊ณ ์์ต๋๋ค. ์์ฅ์ ๋ณ๋์ฑ์ ์ผํฌ์ผ๋นํ๊ธฐ๋ณด๋ค๋ ๋์ฌ๊ฐ ๊ฐ์ง ๊ธฐ์ ๋ ฅ๊ณผ ๊ทธ๋ฃน์ฌ ๋ด ์ ์ง, ๊ทธ๋ฆฌ๊ณ ํ์ดํ ํฌ ์ฐ์ ์ ์ฑ์ฅ์ ์ด์ ์ ๋ง์ถ๋ค๋ฉด ์ข์ ์ฑ๊ณผ๋ฅผ ๊ฑฐ๋์ค ์ ์์ ๊ฒ์ ๋๋ค
LSํฐ๋ผ์ ํ (322180) ํต์ฌ ์์ฝ
LSํฐ๋ผ์ ํ (322180)์ ๋ถ์ ๋ด์ฉ์ ํต์ฌ ์ค์ฌ์ผ๋ก ์์ฝ,
1. ์ฃผ๊ฐ ์์น์ ํต์ฌ ๋๋ ฅ (์ต๊ทผ 10๊ฑฐ๋์ผ)
2. ์์ฅ ํ๊ฒฝ ๋ฐ ๋ด๋ถ ์งํ
3. ํฅํ ์ ๋ง ๋ฐ ํฌ์ ๋ฑ๊ธ
4. ํฌ์ ์ ๋ต ๊ฐ์ด๋
ํต์ฌ ๊ฒฐ๋ก : LSํฐ๋ผ์ ํ ์ ๋จ์ ํ ๋ง๋ฅผ ๋์ด ์ค์ง์ ์ธ ์์ฃผ์ ๊ทธ๋ฃน์ฌ ๋ฐฐ๊ฒฝ์ ๊ฐ์ถ ์ข ๋ชฉ์ ๋๋ค
๋จ๊ธฐ ๊ธ๋ฑ์ ๋ฐ๋ฅธ ๋๋ฆผ๋ชฉ์ ํ์ฉํด ๋น์ค์ ํ๋ณดํด ๋๊ฐ๋ ์ ๋ต์ด ์ ํจํด ๋ณด์ ๋๋ค.
(* ๋ณธ ๊ธ์ ์ ๋ณด ์ ๊ณต ๋ชฉ์ ์ด๋ฉฐ, ํฌ์ ๊ถ์ ๊ฐ ์๋๋๋ค. ํฌ์ ๊ฒฐ์ ์ ๋ณธ์ธ ์ฑ ์ํ์ ์ ์คํ ํ์๊ธฐ ๋ฐ๋๋๋ค)
๋จ์ ๋ฐ๋ฑ ์๋ ์ฐ ์์น! ํ์ฑ(093370) ํฅํ ํฌ์ ์ ๋ต.. ์ด ์ซ์๋ง ๊ธฐ์ตํ์ธ์! ๐งจ์์ฝํ๋ก๋จธํฐ, ๋ ํ ๋ฒ์ 2๋ฐฐ ๊ฐ๋ฅ? ์ ๊ตฌ์ฒดยทํ์ค๊ตญ ๋ชจ๋ฉํ ์์ ํด๋ถ๊ธ
๐ฉ ํฐ์ด์ ์จ ํญ๋ฑ! 2026๋ ๋ฐ๋์ฒด ๋์ฅ์ฃผ๊ฐ ๋ ์ ๋ฐ์ ์๋ ์ด์ 3๊ฐ์ง
5์ 11, 2026ํฐ์๋น 9๋ง์ ๋ํ! ์ง๊ธ ์ฌ๋๋ฆ์ง ์์์๊น? ๋ชฉํ๊ฐ 13๋ง์ ์๋๋ฆฌ์ค๐
5์ 11, 2026๐งซ Over-prescription of antibiotics is a major contributor to the rise in #AMR. IMI project VALUE-Dx investigated whether point-of-care (POC) testing could reduce antibiotic prescription.
๐The result? Having POC tests available did not lead to a reduction in prescriptions, and both clinician and patient perspectives play an important role in antibiotic prescriptions.
๐ https://link.europa.eu/DDgnw7
#IHITransformingHealth #HorizonEU #health #research #AntimicrobialResistance
๐ Die WHO stuft Antibiotikaresistenz #AMR als eine der 10 grรถรten globalen Bedrohungen ein.
Wie ist die AMR-Lage in Deutschland? RKI-Forschende haben Daten aus 104 Laboren, 750 Allgemeinkrankenhรคusern und 30.000 Praxen ausgewertet.
Die Analyse im #Bundesgesundheitsblatt
๐ https://link.springer.com/article/10.1007/s00103-026-04234-6
๐ฆ Could we outsmart antibiotic resistance by turning bacteria against themselves?
๐ Rational Targeting and gRNA Design for Enhancing Quorum Quenching in Pseudomonas aeruginosa PAO1. Computational and Structural Biotechnology Journal (CSBJ). DOI: https://doi.org/10.34133/csbj.0089
๐ CSBJ - A Science Partner Journal: https://spj.science.org/journal/csbj
#AntimicrobialResistance #AMR #CRISPR #GeneEditing #SyntheticBiology #SystemsBiology #Microbiology #Biotechnology #DrugResistance #QuorumSensing #Biofilms #Genomics

Antimicrobial resistance (AMR) is a worldwide health concern that compromises the successful treatment of a growing array of infectious diseases, particularly in low- and middle-income countries. AMR is exaggerated by the spread of antimicrobial resistance genes (ARGs) across humans, animals, and environmental reservoirs like water and soil. Hospital wastewater (HWW) is the main source of antimicrobial resistance in the environment. The current study used high throughput metagenomic nanopore sequencing to investigate the microbial abundance and ARGs associated with both HWW and tap water in five different hospitals in Cairo, Egypt. The bacterial community composition of the HWW microbiome identified 25 taxonomic families. The most abundant genera in HWW were Acinetobacter (6%) and Propioniciclav (5%) out of 101 unique genera while, the most abundant in tap water were Enterococcus (53%), Escherichia (15%), and Francisella (14%) out of 89 unique genera. Alpha diversity analysis revealed significantly greater microbial diversity in the HWW samples than in the tap water samples (P valueโ>โ0.05), moreover beta diversity analysis revealed a significant difference in the microbial community composition between the tap water and HWW samples (P valueโ>โ0.05) using Chao metric for richness estimation and Shannon metric for richness and evenness estimation. Total ARG analysis revealed absence of ARGs in tap water using the three databases, while comparable levels of ARGs were detected in HWW across the five hospitals. In total, 45, 28, and 28 ARG subtypes were identified in the HWW samples using ResFinder, CARD, and the NCBI AMRFinderPlus databases, respectively. The most abundant AMR mechanisms among the five hospitals were linked to the inhibition of protein synthesis. Using the ResFinder database, streptogramin resistance genes were most prevalent in Hospitals 1 and 5 (15% and 40%, respectively); using CARD, aminoglycoside, lincosamide, and macrolide resistance genes were most predominant (relative abundances 35โ60%). Using NCBI AMRFinderPlus, streptomycin, tetracycline, and macrolide resistance genes were most prevalent (relative abundances 30.1โ60%). Detection of plasmid replicons in HWW identified 39 different plasmid-associated replication genes via the PlasmidFinder database. The Col440l-1, colRNAI-1 and Col440ll-1 plasmid replicons were the most detected across the five hospitals with relative abundances of 16.6%, 10.9% and 9.6%, respectively. This study revealed different microbial communities among HWW and tap water in addition to the widespread occurrence of ARGs and AMR encoding plasmid replicons in the HWW in the five different hospitals in Cairo, Egypt indicating a significant risk associated with HWW, necessitating the implementation of preventative measures to avert their environmental diffusion. To our knowledge, this is one of the first Egyptian studies to apply Oxford Nanopore long-read metagenomic sequencing for simultaneous profiling of microbial communities and the resistome in HWW and tap water, using three ARG databases across five hospitals in two seasons.

Antimicrobial resistance (AMR) is a worldwide health concern that compromises the successful treatment of a growing array of infectious diseases, particularly in low- and middle-income countries. AMR is exaggerated by the spread of antimicrobial resistance genes (ARGs) across humans, animals, and environmental reservoirs like water and soil. Hospital wastewater (HWW) is the main source of antimicrobial resistance in the environment. The current study used high throughput metagenomic nanopore sequencing to investigate the microbial abundance and ARGs associated with both HWW and tap water in five different hospitals in Cairo, Egypt. The bacterial community composition of the HWW microbiome identified 25 taxonomic families. The most abundant genera in HWW were Acinetobacter (6%) and Propioniciclav (5%) out of 101 unique genera while, the most abundant in tap water were Enterococcus (53%), Escherichia (15%), and Francisella (14%) out of 89 unique genera. Alpha diversity analysis revealed significantly greater microbial diversity in the HWW samples than in the tap water samples (P valueโ>โ0.05), moreover beta diversity analysis revealed a significant difference in the microbial community composition between the tap water and HWW samples (P valueโ>โ0.05) using Chao metric for richness estimation and Shannon metric for richness and evenness estimation. Total ARG analysis revealed absence of ARGs in tap water using the three databases, while comparable levels of ARGs were detected in HWW across the five hospitals. In total, 45, 28, and 28 ARG subtypes were identified in the HWW samples using ResFinder, CARD, and the NCBI AMRFinderPlus databases, respectively. The most abundant AMR mechanisms among the five hospitals were linked to the inhibition of protein synthesis. Using the ResFinder database, streptogramin resistance genes were most prevalent in Hospitals 1 and 5 (15% and 40%, respectively); using CARD, aminoglycoside, lincosamide, and macrolide resistance genes were most predominant (relative abundances 35โ60%). Using NCBI AMRFinderPlus, streptomycin, tetracycline, and macrolide resistance genes were most prevalent (relative abundances 30.1โ60%). Detection of plasmid replicons in HWW identified 39 different plasmid-associated replication genes via the PlasmidFinder database. The Col440l-1, colRNAI-1 and Col440ll-1 plasmid replicons were the most detected across the five hospitals with relative abundances of 16.6%, 10.9% and 9.6%, respectively. This study revealed different microbial communities among HWW and tap water in addition to the widespread occurrence of ARGs and AMR encoding plasmid replicons in the HWW in the five different hospitals in Cairo, Egypt indicating a significant risk associated with HWW, necessitating the implementation of preventative measures to avert their environmental diffusion. To our knowledge, this is one of the first Egyptian studies to apply Oxford Nanopore long-read metagenomic sequencing for simultaneous profiling of microbial communities and the resistome in HWW and tap water, using three ARG databases across five hospitals in two seasons.