No Man's Sky gets weird sometimes.
#NoMansSky #NMS #NoMansSkyWorlds #video #gamevideo #SciFi #procgen #gametography #virtualphotography #PCgaming #PS4 #Steam #HelloGames #gamers #games #gaming #odd #spacegame #fps #mammary #survivalgame #game #weird
The #mammary #glands of #cows abundantly display #receptors for circulating #avian #H5 viruses
Source: Journal of Virology, ABSTRACTInfluenza A viruses (IAVs) from the H5N1 2.3.4.4b clade are circulating in dairy farms in the USA.; ruminants were presumed not to be hosts for IAVs. Previously, IAV-positive mammalian species were hunters and scavengers, possibly getting infected while feeding on infected birds. It is now recognized that H5N1 viruses that circulate in US…
#Avian and #Human #Influenza A Virus #Receptors in #Bovine #Mammary #Gland, Emerg Infect Dis.: https://wwwnc.cdc.gov/eid/article/30/9/24-0696_article
An outbreak of influenza A (#H5N1) virus was detected in dairy cows in the #USA. We detected influenza A virus #sialic acid -α2,3/α2,6-galactose host receptors in bovine mammary glands by lectin histochemistry. Our results provide a rationale for the high levels of H5N1 virus in #milk from infected cows.
Fucosylated and non-fucosylated alpha2,3 #sialosides were detected on the #bovine #mammary #gland tissues, BioRxIV: https://www.biorxiv.org/content/10.1101/2024.07.29.605565v1
Receptors for high pathogenicity avian #influenza viruses (#HPAIVs) in mammary glands of dairy #cattle were detected using various recombinant #hemagglutinins (rHAs). Results demonstrated presence of fucosylated and non-fucosylated alpha2,3 sialosides, which were typically targeted by the HA of clade 2.3.4.4b HPAIVs.
#Sialic #Acid #Receptor Specificity in #Mammary #Gland of Dairy #Cattle Infected with Highly Pathogenic Avian #Influenza A(#H5N1) Virus, Emerg Infect Dis.: https://wwwnc.cdc.gov/eid/article/30/7/24-0689_article
Mammary gland tissues co-stained with sialic acids and influenza A virus #nucleoprotein showed predominant co-localization with the virus and SA α2,3-gal. HPAI H5N1 exhibited epitheliotropism within the mammary gland, and we observed rare immunolabeling within macrophages.
The #avian and #human #influenza A virus #receptors #sialic acid (SA)-α2,3 and SA-α2,6 are widely expressed in the #bovine #mammary #gland, BioRxIV, https://www.biorxiv.org/content/10.1101/2024.05.03.592326v1?rss=1
IAVs isolated from chickens generally bind more tightly to SA-α2,3-Gal-β1,4 (chicken receptor), whereas IAVs isolated from duck to SA-α2,3-Gal-β1,3 (duck receptor). We found all receptors were expressed, to a different degree, in the mammary gland, respiratory tract, and cerebrum of beef and/or dairy cattle.
New #radiomics model could provide results as good as BI-RADS in classifying #mammary masses. (Kawtar Debbi et al.)
#InsightsIntoImaging #BIRADS #BreastCancer
Click here to read more ➡️ https://insightsimaging.springeropen.com/articles/10.1186/s13244-023-01404-x
Background Recent advanced in radiomics analysis could help to identify breast cancer among benign mammary masses. The aim was to create a radiomics signature using breast DCE-MRI extracted features to classify tumors and to compare the performances with the BI-RADS classification. Material and methods From September 2017 to December 2019 images, exams and records from consecutive patients with mammary masses on breast DCE-MRI and available histology from one center were retrospectively reviewed (79 patients, 97 masses). Exclusion criterion was malignant uncertainty. The tumors were split in a train-set (70%) and a test-set (30%). From 14 kinetics maps, 89 radiomics features were extracted, for a total of 1246 features per tumor. Feature selection was made using Boruta algorithm, to train a random forest algorithm on the train-set. BI-RADS classification was recorded from two radiologists. Results Seventy-seven patients were analyzed with 94 tumors, (71 malignant, 23 benign). Over 1246 features, 17 were selected from eight kinetic maps. On the test-set, the model reaches an AUC = 0.94 95 CI [0.85–1.00] and a specificity of 33% 95 CI [10–70]. There were 43/94 (46%) lesions BI-RADS4 (4a = 12/94 (13%); 4b = 9/94 (10%); and 4c = 22/94 (23%)). The BI-RADS score reached an AUC = 0.84 95 CI [0.73–0.95] and a specificity of 17% 95 CI [3–56]. There was no significant difference between the ROC curves for the model or the BI-RADS score (p = 0.19). Conclusion A radiomics signature from features extracted using breast DCE-MRI can reach an AUC of 0.94 on a test-set and could provide as good results as BI-RADS to classify mammary masses.
Scientific Frontline
Blake Patterson
Giuseppe Michieli
Your Autistic Life FR/EN/ES
Insights Into Imaging