Born to run? Vegetative spread of the invasive plant Phragmites australis via stolons (runners)

Phragmites australis is a highly invasive wetland grass species that dominates nearly any ecosystem that it invades, this is due to its incredibly dense foliage which makes it hard for plants and animals to live in the vicinity of phragmites. Phragmites can grow in versatile environments and are extremely durable. Therefore, once phragmites establish itself, it is very difficult to remove it. On top of that, Phragmites spreads very quickly by utilizing both sexual and asexual reproduction

Life on the rocks: Small-scale primary succession in an abandoned limestone quarry

Abandoned quarries, from which all soil and plant life have been removed, represent an opportunity to study primary succession at a small scale. Using a framework suggested by Gilardelli et al. (2016), we assessed the stage of primary succession in an abandoned limestone quarry in Greencastle, Indiana, where gravel extraction ceased in 1977. From 2018-2021 we surveyed the quarry floor to describe the species composition and distribution of flowering plant species that have established at the site, then described each species in terms of its plant form, life history, native and wetland status, and invasive rank using the USDA website. In 2021, we made a grid across the quarry bottom and randomly selected 50 two-meter plots of which we characterized the substrate and identified flowering plant species found within each plot. We identified 106 species in the quarry, 72% are native to Indiana. From the quarry survey, we found that most of the species currently growing in the Nature Park quarry are native, herbaceous perennials. From the sample plots, we found that the quarry bottom does not follow the pattern of late-phase succession as laid out by Gilardelli et al. (2016) with only 28% of species identified being woody perennials that are sparsely distributed. Shrubland communities are not replacing herbaceous pioneer species as quickly as expected

Sugar-Sweetened Beverage Intake and Cancer Recurrence and Survival in CALGB 89803 (Alliance)

Background: In colon cancer patients, obesity, sedentary lifestyle, and high dietary glycemic load have been associated with increased risk of cancer recurrence. High sugar-sweetened beverage intake has been associated with obesity, diabetes, and cardio-metabolic diseases, but the influence on colon cancer survival is unknown. Methods: We assessed the association between sugar-sweetened beverage consumption on cancer recurrence and mortality in 1,011 stage III colon cancer patients who completed food frequency questionnaires as part of a U.S. National Cancer Institute-sponsored adjuvant chemotherapy trial. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated with Cox proportional hazard models. Results: Patients consuming ≥2 servings of sugar-sweetened beverages per day experienced an adjusted HR for disease recurrence or mortality of 1.67 (95% CI, 1.04–2.68), compared with those consuming <2 servings per month (Ptrend = 0.02). The association of sugar-sweetened beverages on cancer recurrence or mortality appeared greater among patients who were both overweight (body mass index ≥25 kg/m2) and less physically active (metabolic equivalent task-hours per week <18) (HR = 2.22; 95% CI, 1.29–3.81, Ptrend = 0.0025). Conclusion: Higher sugar-sweetened beverage intake was associated with a significantly increased risk of cancer recurrence and mortality in stage III colon cancer patients

Phase I/II study of first-line irinotecan combined with 5-fluorouracil and folinic acid Mayo Clinic schedule in patients with advanced colorectal cancer

BACKGROUND: This multicentre phase I/II study was designed to determine the maximum tolerated dose of irinotecan when combined with 5-fluorouracil and folinic acid according to the Mayo Clinic schedule and to evaluate the activity of this combination as first-line therapy in patients with advanced colorectal cancer. METHODS: Sixty-three patients received irinotecan (250 or 300 mg/m(2), 30- to 90-minute intravenous infusion on day 1), immediately followed by folinic acid (20 mg/m(2)/day) and 5-fluorouracil (425 mg/m(2), 15-minute bolus infusion) days 1 to 5, every four weeks. RESULTS: Diarrhoea was dose limiting at 300 mg/m(2 )irinotecan in combination with 5-fluorouracil and folinic acid, and this was determined to be the maximum tolerated dose. Grade 3–4 neutropenia was the most frequently reported toxicity. The recommended dose of irinotecan for the phase II part of the study was 250 mg/m(2). The response rate for the evaluable patient population was 36% (13/36), and 44% (16 patients) had stable disease (including 19% of minor response). For the intention-to-treat population, the response rate was 29% (14/49) and 35% (17 patients) stable disease (including 14% of minor response). The median time to progression was 7.0 months and the median survival was 12.0 months. Grade 3–4 non-haematological drug-related toxicities included delayed diarrhoea, stomatitis, fatigue, and nausea/vomiting. There were three deaths due to septic shock that were possibly or probably treatment-related. CONCLUSIONS: This regimen of irinotecan in combination with the Mayo Clinic schedule of bolus 5-fluorouracil/folinic acid every four weeks showed activity as first-line therapy in patients with advanced colorectal cancer. In keeping with other published results of studies using bolus 5-fluorouracil combined with irinotecan, the use of this regimen is limited by a relatively high rate of grade 3–4 neutropenia, and the combination of irinotecan and infusional 5-fluorouracil / folinic acid should remain the regimen of first choice

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Natural Variation in Decision-Making Behavior in Drosophila melanogaster

There has been considerable recent interest in using Drosophila melanogaster to investigate the molecular basis of decision-making behavior. Deciding where to place eggs is likely one of the most important decisions for a female fly, as eggs are vulnerable and larvae have limited motility. Here, we show that many natural genotypes of D. melanogaster prefer to lay eggs near nutritious substrate, rather than in nutritious substrate. These preferences are highly polymorphic in both degree and direction, with considerable heritability (0.488) and evolvability

Tumor-Infiltrating Lymphocytes in Glioblastoma Are Associated with Specific Genomic Alterations and Related to Transcriptional Class

Tumor-infiltrating lymphocytes (TILs) have prognostic significance in many cancers, yet their roles in glioblastoma (GBM) have not been fully defined. We hypothesized TILs in GBM are associated with molecular alterations, histologies and survival

Clinical practice guidelines for the prevention and treatment of EGFR inhibitor-associated dermatologic toxicities

Background Epidermal growth factor receptor inhibitors (EGFRI) produce various dermatologic side effects in the majority of patients, and guidelines are crucial for the prevention and treatment of these untoward events. The purpose of this panel was to develop evidence-based recommendations for EGFRI-associated dermatologic toxicities. Methods A multinational, interdisciplinary panel of experts in supportive care in cancer reviewed pertinent studies using established criteria in order to develop first-generation recommendations for EGFRI-associated dermatologic toxicities. Results Prophylactic and reactive recommendations for papulopustular (acneiform) rash, hair changes, radiation dermatitis, pruritus, mucositis, xerosis/fissures, and paronychia are presented, as well as general dermatologic recommendations when possible. Conclusion Prevention and management of EGFRI-related dermatologic toxicities is critical to maintain patients’ health-related quality of life and dose intensity of antineoplastic regimens. More rigorous investigation of these toxicities is warranted to improve preventive and treatment strategies

Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing