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Cellular senescence is a diverse phenotype characterised by permanent cell cycle arrest and an associated secretory phenotype (SASP) which includes inflammatory cytokines. Typically, senescent cells are removed by the immune system, but this process becomes dysregulated with age causing senescent cells to accumulate and induce chronic inflammatory signalling. Identifying senescent cells is challenging due to senescence phenotype heterogeneity, and senotherapy often requires a combinatorial approach. Here we systematically collected 119 transcriptomic datasets related to human fibroblasts, forming an online database describing the relevant variables for each study allowing users to filter for variables and genes of interest. Our own analysis of the database identified 28 genes significantly up-or downregulated across four senescence types (DNA damage induced senescence (DDIS), oncogene induced senescence (OIS), replicative senescence, and bystander induced senescence) compared to proliferating controls. We also found gene expression patterns of conventional senescence markers were highly specific and reliable for different senescence inducers, cell lines, and timepoints. Our comprehensive data supported several observations made in existing studies using single datasets, including stronger p53 signalling in DDIS compared to OIS. However, contrary to some early observations, both p16 and p21 mRNA levels rise quickly, depending on senescence type, and persist for at least 8-11 days. Additionally, little evidence was found to support an initial TGFβ-centric SASP. To support our transcriptomic analysis, we computationally modelled temporal protein changes of select core senescence proteins during DDIS and OIS, as well as perform knockdown interventions. We conclude that while universal biomarkers of senescence are difficult to identify, conventional senescence markers follow predictable profiles and construction of a framework for studying senescence could lead to more reproducible data and understanding of senescence heterogeneity. [ABSTRACT FROM AUTHOR]

Aims: Biomarker‐driven therapies have not been developed for infant medulloblastoma (iMB). We sought to robustly sub‐classify iMB, and proffer strategies for personalized, risk‐adapted therapies. Methods: We characterized the iMB molecular landscape, including second‐generation subtyping, and the associated retrospective clinical experience, using large independent discovery/validation cohorts (n = 387). Results: iMBGrp3 (42%) and iMBSHH (40%) subgroups predominated. iMBGrp3 harboured second‐generation subtypes II/III/IV. Subtype II strongly associated with large‐cell/anaplastic pathology (LCA; 23%) and MYC amplification (19%), defining a very‐high‐risk group (0% 10yr overall survival (OS)), which progressed rapidly on all therapies; novel approaches are urgently required. Subtype VII (predominant within iMBGrp4) and subtype IV tumours were standard risk (80% OS) using upfront CSI‐based therapies; randomized‐controlled trials of upfront radiation‐sparing and/or second‐line radiotherapy should be considered. Seventy‐five per cent of iMBSHH showed DN/MBEN histopathology in discovery and validation cohorts (P < 0.0001); central pathology review determined diagnosis of histological variants to WHO standards. In multivariable models, non‐DN/MBEN pathology was associated significantly with worse outcomes within iMBSHH. iMBSHH harboured two distinct subtypes (iMBSHH‐I/II). Within the discriminated favourable‐risk iMBSHH DN/MBEN patient group, iMBSHH‐II had significantly better progression‐free survival than iMBSHH‐I, offering opportunities for risk‐adapted stratification of upfront therapies. Both iMBSHH‐I and iMBSHH‐II showed notable rescue rates (56% combined post‐relapse survival), further supporting delay of irradiation. Survival models and risk factors described were reproducible in independent cohorts, strongly supporting their further investigation and development. Conclusions: Investigations of large, retrospective cohorts have enabled the comprehensive and robust characterization of molecular heterogeneity within iMB. Novel subtypes are clinically significant and subgroup‐dependent survival models highlight opportunities for biomarker‐directed therapies. [ABSTRACT FROM AUTHOR]

Subsurface drainage, while an important and necessary agricultural production practice in the Midwest, contributes nitrate (NO3-N) and soluble phosphorus (P) to surface waters. Eutrophication (i.e., excessive enrichment of surface water by NO3-N and soluble P) supports harmful algal blooms in receiving waters. The magnitude of NO3-N and soluble P loss in subsurface drainage varies greatly by landscape, weather, and field management factors. This study evaluated both the relative and combined impacts of these factors on observed NO3-N and soluble P concentrations in subsurface drainage water in the Western Lake Erie Basin watershed. Water quality data from multiple drainage outlet sites in northwest Ohio provided evidence that the primary management factors affecting NO3-N and soluble P loss were the amount and time of fertilizer application. Results strongly support following Tri-State fertilizer recommendations and 4R nutrient stewardship principles to reduce the risk of NO3-N and soluble P loss. Results also provided evidence of NO3-N and soluble P transport to subsurface drains via different pathways. Due to differences in NO3-N and soluble P transport through the soil profile (via baseflow and preferential flow, respectively), management approaches taken to reduce one nutrient may exacerbate losses of the other. Further research is needed to address potential changes in field hydrology (and consequently the infield transport of soluble nutrients) from different types of agricultural best management practices (BMPs) and to evaluate optimal stacking of BMPs to achieve reductions in both NO3-N and soluble P loss. Controlled drainage has a high potential for stacking with other BMPs because it is primarily a physical discharge and load reduction practice. [ABSTRACT FROM AUTHOR]

The US Midwest is expected to experience higher intensity rainfall events along with an increased chance of drought during the mid- and late 21st century under projected future climate scenarios. Development of strategies to mitigate the impact of these projected changes on agricultural production and environmental quality is important for ensuring agricultural resiliency to future climate. This study used the DRAINMOD hydrologic model to simulate subsurface drainage discharge at a field site in the headwaters of the Western Lake Erie Basin using future climate patterns projected by 20 general circulation models. Despite projected increases in rainfall, by the late twenty-first century, subsurface discharge was projected to decrease 7% and 11% under representative concentration pathway (RCP) 4.5 and RCP 8.5, respectively. Reductions in subsurface discharge were attributed to increased temperature and evapotranspiration. The performance of controlled drainage was not projected to change on an annual basis throughout the next century. The benefits of controlled drainage systems as an agricultural best management practice were still evident under the projected climate change of the next century. The role of controlled drainage as a means to potentially retain more crop available water in the soil profile could become critically important under future climate conditions. [ABSTRACT FROM AUTHOR]