Germination and seedling development in Pistia stratiotes L.

This study aimed to describe the post-seminal development, evaluate how the available water, light and temperature influence seed germination and to describe the vegetative propagation by selecting one of the collected plants of Pistia stratiotes. The plant material was collected in a tributary of the Rio Igaraçu, Parnaíba, Piauí State, Brazil. A botanical description of the species was made using individuals collected in the study area. For the germination tests, a total of 1400 seeds were harvested and three experiments were conducted, varying the amount of available water, light and temperature. The results showed that the highest percentage of germination is occurred with seeds pre-washed with distilled water, sown on filter paper with abundant water (enough to form a sheet of water) and exposed to alternating light at an average temperature of 37°C. Germination began on the fourth day after sowing, marked by the appearance of the cataphyll. After 22 days, the seedling stage was completed. Vegetative propagation of this species is efficient and fast. In 50 days, a total of 134 new vegetative shoots were recorded in just one individual. The results showed that the germination rate is related to the amount of light and temperature

Recognition of the genus Thaumatophyllum Schott − formerly Philodendron subg. Meconostigma (Araceae) − based on molecular and morphological evidence

Philodendron subgenus Meconostigma has been a well-circumscribed group since 1829. Members of this group are easily distinguished by diagnostic morphological characters as well as by a distinct ecology and geographical distribution. Based on molecular, morphological and cytological evidence, we propose the recognition of P. subg. Meconostigma as a distinct genus, Thaumatophyllum Schott. We also present the necessary new combinations, an emended key and some nomenclatural and taxonomic corrections regarding 21 names of Thaumatophyllum

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

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

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

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

The TESS-Keck Survey. III. A Stellar Obliquity Measurement of TOI-1726 c

We report the measurement of a spectroscopic transit of TOI-1726c, one of two planets transiting a G-type star with V = 6.9 in the Ursa Major Moving Group (~400 Myr). With a precise age constraint from cluster membership, TOI-1726 provides a great opportunity to test various obliquity excitation scenarios that operate on different timescales. By modeling the Rossiter–McLaughlin (RM) effect, we derived a sky-projected obliquity of −1^(+35)_(−32)∘. This result rules out a polar/retrograde orbit and is consistent with an aligned orbit for planet c. Considering the previously reported, similarly prograde RM measurement of planet b and the transiting nature of both planets, TOI-1726 tentatively conforms to the overall picture that compact multitransiting planetary systems tend to have coplanar, likely aligned orbits. TOI-1726 is also a great atmospheric target for understanding differential atmospheric loss of sub-Neptune planets (planet b 2.2 R⊕ and c 2.7 R⊕ both likely underwent photoevaporation). The coplanar geometry points to a dynamically cold history of the system that simplifies any future modeling of atmospheric escape

Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

Background 1Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

Assessing the potential of acoustic telemetry to underpin the regional management of basking sharks (Cetorhinus maximus)

Acoustic telemetry can provide valuable space-use data for a range of marine species. Yet the deployment of species-specific arrays over vast areas to gather data on highly migratory vertebrates poses formidable challenges, often rendering it impractical. To address this issue, we pioneered the use of acoustic telemetry on basking sharks (Cetorhinus maximus) to test the feasibility of using broadscale, multi-project acoustic receiver arrays to track the movements of this species of high conservation concern through the coastal waters of Ireland, Northern Ireland, and Scotland. Throughout 2021 and 2022, we tagged 35 basking sharks with acoustic transmitters off the west coast of Ireland; 27 of these were detected by 96 receiver stations throughout the study area (n = 9 arrays) with up to 216 detections of an individual shark (mean = 84, s.d. 65). On average, sharks spent ~ 1 day at each acoustic array, with discrete residency periods of up to nine days. Twenty-one sharks were detected at multiple arrays with evidence of inter-annual site fidelity, with the same individuals returning to the same locations in Ireland and Scotland over 2 years. Eight pairs of sharks were detected within 24 h of each other at consecutive arrays, suggesting some level of social coordination and synchronised movement. These findings demonstrate how multi-project acoustic telemetry can support international, cost-effective monitoring of basking sharks and other highly mobile species. Decision support tools such as these can consolidate cross-border management strategies, but to achieve this goal, collaborative efforts across jurisdictions are necessary to establish the required infrastructure and secure ongoing support

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks