Water-Conserving Landscapes: An Evaluation of Homeowner Preference

Landscape preferences were assessed for three identically designed Xeriscapes™, differing only in the plant material, under both well-watered and drought conditions. The classes of plant material included traditional (high water use), intermediate (moderate water use), and native/adapted plant species of the Intermountain West (low water use). Landscapes were subjected to a 5-week dry-down period. Under drought conditions, respondents preferred drought/adapted and intermediate landscapes to traditional landscapes. A focus on Xeriscape™ education, practices, and visual exposure may result in greater adoption of Xeriscape™ practices by homeowners and may also result in significant residential water savings

Water-conserving landscapes: an evaluation of homeowner preference

Landscape preferences were assessed for three identically designed Xeriscapes™, differing only in the plant material, under both well-watered and drought conditions. The classes of plant material included traditional (high water use), intermediate (moderate water use), and native/adapted plant species of the Intermountain West (low water use). Landscapes were subjected to a 5-week dry-down period. Under drought conditions, respondents preferred drought/adapted and intermediate landscapes to traditional landscapes. A focus on Xeriscape™ education, practices, and visual exposure may result in greater adoption of Xeriscape™ practices by homeowners and may also result in significant residential water savings

Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma

Purpose: [18F]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients. Materials and methods: Whole-body [18F]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [18F]FDG-avid lesions as well as the degree of diffuse [18F]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1–6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian 7 1.1 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 2: liver SUVmedian 7 1.5 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 3: liver SUVmedian 7 2 (axial skeleton), gluteal muscles SUVmedian 7 4 (extremities). Approach 4: ≥ 2.5. Approach 5: ≥ 2.5 (axial skeleton), ≥ 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients. Results: BM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [18F]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of β2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5. Conclusions: The automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts

Occurrence of seizures in hospitalized patients with a pre-existing seizure disorder

Objective. To assess the frequency of seizures in hospitalized patients with a pre-existing seizure disorder. Patients and Methods. A retrospective review was conducted on all patients with a documented seizure disorder who were hospitalized between January 1, 2002 and December 31, 2007. Children aged < 2 years and hospital admission for seizure control or surgical or obstetric indications were excluded. The first hospital admission of at least 24 hours was identified for each patient. Patient demographics, details of the seizure disorder, details of the hospital admission, and clinically-apparent seizure activity documented during the inpatient stay were recorded from the medical record. Results. During the 6-year study period, 720 patients with a documented seizure disorder were admitted for at least 24 hours. Thirty-nine patients experienced seizure activity for an overall frequency of 5.4% (95% CI: 3.8-7.1%). Younger age (p = 0.001), greater frequency of baseline seizure activity (p < 0.001), recent seizure activity (p < 0.001), greater number of chronic antiepileptic medications (p = 0.01), and admission for neurological (p = 0.03) conditions were associated with increased frequency of seizure activity during hospitalization. Conclusions. The majority of seizures occurring in hospitalized patients with a pre-existing seizure disorder appear related to the patient’s underlying seizure disorder. Because patients with frequent seizures on numerous anti-epileptic medications are likely to experience a seizure while hospitalized, it is essential to be prepared to treat seizure activity regardless of the reason for admission

Temporal dynamics of selective attention and conflict resolution during cross-dimensional go-nogo decisions

<p>Abstract</p> <p>Background</p> <p>Decision-making is a fundamental capacity which is crucial to many higher-order psychological functions. We recorded event-related potentials (ERPs) during a visual target-identification task that required go-nogo choices. Targets were identified on the basis of cross-dimensional conjunctions of particular colors and forms. Color discriminability was manipulated in three conditions to determine the effects of color distinctiveness on component processes of decision-making.</p> <p>Results</p> <p>Target identification was accompanied by the emergence of prefrontal P2a and P3b. Selection negativity (SN) revealed that target-compatible features captured attention more than target-incompatible features, suggesting that intra-dimensional attentional capture was goal-contingent. No changes of cross-dimensional selection priorities were measurable when color discriminability was altered. Peak latencies of the color-related SN provided a chronometric measure of the duration of attention-related neural processing. ERPs recorded over the frontocentral scalp (N2c, P3a) revealed that color-overlap distractors, more than form-overlap distractors, required additional late selection. The need for additional response selection induced by color-overlap distractors was severely reduced when color discriminability decreased.</p> <p>Conclusion</p> <p>We propose a simple model of cross-dimensional perceptual decision-making. The temporal synchrony of separate color-related and form-related choices determines whether or not distractor processing includes post-perceptual stages. ERP measures contribute to a comprehensive explanation of the temporal dynamics of component processes of perceptual decision-making.</p

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

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

Search for a vector-like quark T′ → tH via the diphoton decay mode of the Higgs boson in proton-proton collisions at s \sqrt{s} = 13 TeV

A search for the electroweak production of a vector-like quark T′, decaying to a top quark and a Higgs boson is presented. The search is based on a sample of proton-proton collision events recorded at the LHC at = 13 TeV, corresponding to an integrated luminosity of 138 fb−1. This is the first T′ search that exploits the Higgs boson decay to a pair of photons. For narrow isospin singlet T′ states with masses up to 1.1 TeV, the excellent diphoton invariant mass resolution of 1–2% results in an increased sensitivity compared to previous searches based on the same production mechanism. The electroweak production of a T′ quark with mass up to 960 GeV is excluded at 95% confidence level, assuming a coupling strength κT = 0.25 and a relative decay width Γ/MT′ < 5%