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  1. 56781
    “…CONCLUSIONS: While the binomial presence or absence of PD-L1 expression in the TME was not sufficient to predict response to anti-PD-1 in patients with MCC, we show that quantitative assessments of PD-1+ and PD-L1+ cell densities as well as the geographic interactions between these two cell populations correlate with clinical response. …”
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  2. 56782
  3. 56783
    “…Shigella was responsible for 63 713 deaths (41 191–93 611) among children younger than 5 years and was frequently associated with diarrhoea across all adult age groups, increasing in elderly people, with broad geographical distribution. ETEC was the eighth leading cause of diarrhoea mortality in 2016 among all age groups, accounting for 51 186 deaths (26 757–83 064) and about 3·2% (1·8–4·7) of diarrhoea deaths. …”
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  4. 56784
  5. 56785
  6. 56786
    “…METHODS: In the present study, we investigated the virome of leaf and sapwood samples from native H. brasiliensis trees collected in two geographic areas in the Brazilian Amazon. Small RNA (sRNA) deep sequencing and bioinformatic tools were used to assembly, identify and characterize viral contigs. …”
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  7. 56787
  8. 56788
    “…The microbiomes of control children contained more genes that were related to fermentation and the biosynthesis of short-chain fatty acids, but these were not consistently associated with particular taxa across geographically diverse clinical centres, suggesting that microbial factors associated with T1D are taxonomically diffuse but functionally more coherent. …”
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  9. 56789
    “…However, there is little very research quantifying wasteful test use, despite the £3 billion annual expenditure. Geographical variation has been suggested as one metric in which to quantify inappropriate use. …”
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  10. 56790
    “…Our analysis methods will combine machine learning methods for detecting transportation mode use and physical activity, use temporal Geographic Information Systems to quantify changes to urban intervention exposure, and apply analytic methods for natural experiment studies including interrupted time series analysis. …”
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  11. 56791
  12. 56792
    “…The influence of different contracts, team and network structures and regional and geographic settings on processes and results including patient-reported outcomes will be analyzed in five subprojects: [1] structural characteristics of SAPV and their impact on patient care, [2] quality of care from the perspective of patients, [3] quality of care from the perspective of SAPV teams, hospices, ambulatory nursing services, nursing homes and other care givers, content and extent of care from [4] the perspective of General Practitioners and [5] from the perspective of payers. …”
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  13. 56793
    “…The finding of no alternative causes for geographic differences in microcephaly rate leads us to hypothesize that the Northeast region was disproportionately affected by this Zika outbreak, with 94% of an estimated 8.5 million total cases occurring in this region, suggesting a need for seroprevalence surveys to determine the underlying reason.…”
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  14. 56794
    “…The demographic, socioeconomic, geographic, behavioural and cardiometabolic predictors of NWCO were explored with multivariable logistic regression. …”
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  15. 56795
    “…An occurrence of Ft over a wide geographical region indicates its expansion to enzootic range, and demonstrates the need for further investigation among potential disease reservoirs and at-risk populations, such as farmers and veterinarians.…”
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  16. 56796
    “…Most (92%, 185/201) sought treatment of which 80% (149/185) sought treatment at a health centre. Geographic proximity to a health centre (AOR = 6.5; CI = 1.74–24.25; for those < 3.5 km versus those > 3.6 km) and previous experience of attending a health centre (AOR = 4.7; CI = 1.2–19.1) were strong predictors of visiting a health centre for febrile symptoms. …”
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  17. 56797
  18. 56798
  19. 56799
  20. 56800
    “…In stage 2, the most accurate algorithms were validated with chart data within two other geographic areas in the province of Quebec. RESULTS: Accurate identification of diabetes in children (ages ≤15 years) required four physician claims or one hospitalization (with International Classification of Disease codes within 1 year (sensitivity 91.2%, 95% confidence interval [CI] 89.2–92.9]; positive predictive value [PPV] 93.5%, 95% CI 91.7–95.0) or using only four physician claims in 2 years (sensitivity 90.4%, 95% CI 88.3–92.2; PPV 93.2%, 95% CI 91.7–95.0). …”
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