Optimized low-dose combinatorial drug treatment boosts selectivity and efficacy of colorectal carcinoma treatment.

The current standard of care for colorectal cancer (CRC) is a combination of chemotherapeutics, often supplemented with targeted biological drugs. An urgent need exists for improved drug efficacy and minimized side effects, especially at late-stage disease. We employed the phenotypically driven therapeutically guided multidrug optimization (TGMO) technology to identify optimized drug combinations (ODCs) in CRC. We identified low-dose synergistic and selective ODCs for a panel of six human CRC cell lines also active in heterotypic 3D co-culture models. Transcriptome sequencing and phosphoproteome analyses showed that the mechanisms of action of these ODCs converged toward MAP kinase signaling and cell cycle inhibition. Two cell-specific ODCs were translated to in vivo mouse models. The ODCs reduced tumor growth by ~80%, outperforming standard chemotherapy (FOLFOX). No toxicity was observed for the ODCs, while significant side effects were induced in the group treated with FOLFOX therapy. Identified ODCs demonstrated significantly enhanced bioavailability of the individual components. Finally, ODCs were also active in primary cells from CRC patient tumor tissues. Taken together, we show that the TGMO technology efficiently identifies selective and potent low-dose drug combinations, optimized regardless of tumor mutation status, outperforming conventional chemotherapy

Spatiotemporal Pattern of Urban Forest Leaf Area Index in Response to Rapid Urbanization and Urban Greening

Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index (LAI) under rapid urbanization and urban greening is important for urban forest planning and management. We evaluated the potential for estimating urban forest LAI spatiotemporally by using Landsat TM imagery. We collected three scenes of Landsat TM (thematic mapper) images acquired in 1997, 2004 and 2010 and conducted a field survey to collect urban forest LAI. Finally, spatiotemporal maps of the urban forest LAI were created using a NDVI-based urban forest LAI predictive model. Our results show that normalized differential vegetation index (NDVI) could be used as a predictor for urban forest LAI similar to natural forests. Both rapid urbanization and urban greening contribute to the changing process of urban forest LAI. The urban forest has changed considerably from 1997 to 2010. Urban vegetated pixels decreased gradually from 1997 to 2010 due to intensive urbanization. Leaf area for the study area was 216.4, 145.2 and 173.7 km2 in the years 1997, 2004 and 2010, respectively. Urban forest LAI decreased sharply from 1997 to 2004 and increased slightly from 2004 to 2010 because of numerous greening policies. The urban forest LAI class distributions were skewed toward low values in 1997 and 2004. Moreover, the LAI presented a decreasing trend from suburban to downtown areas. We demonstrate the usefulness of TM remote-sensing in understanding spatiotemporal changing patterns of urban forest LAI under rapid urbanization and urban greening

Global estimates on the number of people blind or visually impaired by age-related macular degeneration: a meta-analysis from 2000 to 2020

BACKGROUND: We aimed to update estimates of global vision loss due to age-related macular degeneration (AMD). METHODS: We did a systematic review and meta-analysis of population-based surveys of eye diseases from January, 1980, to October, 2018. We fitted hierarchical models to estimate the prevalence of moderate and severe vision impairment (MSVI; presenting visual acuity from <6/18 to 3/60) and blindness ( < 3/60) caused by AMD, stratified by age, region, and year. RESULTS: In 2020, 1.85 million (95%UI: 1.35 to 2.43 million) people were estimated to be blind due to AMD, and another 6.23 million (95%UI: 5.04 to 7.58) with MSVI globally. High-income countries had the highest number of individuals with AMD-related blindness (0.60 million people; 0.46 to 0.77). The crude prevalence of AMD-related blindness in 2020 (among those aged ≥ 50 years) was 0.10% (0.07 to 0.12) globally, and the region with the highest prevalence of AMD-related blindness was North Africa/Middle East (0.22%; 0.16 to 0.30). Age-standardized prevalence (using the GBD 2019 data) of AMD-related MSVI in people aged ≥ 50 years in 2020 was 0.34% (0.27 to 0.41) globally, and the region with the highest prevalence of AMD-related MSVI was also North Africa/Middle East (0.55%; 0.44 to 0.68). From 2000 to 2020, the estimated crude prevalence of AMD-related blindness decreased globally by 19.29%, while the prevalence of MSVI increased by 10.08%. CONCLUSIONS: The estimated increase in the number of individuals with AMD-related blindness and MSVI globally urges the creation of novel treatment modalities and the expansion of rehabilitation services