Directing cell migration and organization via nanocrater-patterned cell-repellent interfaces.

Although adhesive interactions between cells and nanostructured interfaces have been studied extensively, there is a paucity of data on how nanostructured interfaces repel cells by directing cell migration and cell-colony organization. Here, by using multiphoton ablation lithography to pattern surfaces with nanoscale craters of various aspect ratios and pitches, we show that the surfaces altered the cells focal-adhesion size and distribution, thus affecting cell morphology, migration and ultimately localization. We also show that nanocrater pitch can disrupt the formation of mature focal adhesions to favour the migration of cells towards higher-pitched regions, which present increased planar area for the formation of stable focal adhesions. Moreover, by designing surfaces with variable pitch but constant nanocrater dimensions, we were able to create circular and striped cellular patterns. Our surface-patterning approach, which does not involve chemical treatments and can be applied to various materials, represents a simple method to control cell behaviour on surfaces

GraPE: fast and scalable Graph Processing and Embedding

Graph Representation Learning methods have enabled a wide range of learning problems to be addressed for data that can be represented in graph form. Nevertheless, several real world problems in economy, biology, medicine and other fields raised relevant scaling problems with existing methods and their software implementation, due to the size of real world graphs characterized by millions of nodes and billions of edges. We present GraPE, a software resource for graph processing and random walk based embedding, that can scale with large and high-degree graphs and significantly speed up-computation. GraPE comprises specialized data structures, algorithms, and a fast parallel implementation that displays everal orders of magnitude improvement in empirical space and time complexity compared to state of the art software resources, with a corresponding boost in the performance of machine learning methods for edge and node label prediction and for the unsupervised analysis of graphs.GraPE is designed to run on laptop and desktop computers, as well as on high performance computing cluster

Acute Kidney Injury, Renal Function, and the Elderly Obese Surgical Patient: A Matched Case-Control Study

OBJECTIVE: To investigate the association between obesity and perioperative acute kidney injury (AKI), controlling for preoperative kidney dysfunction. BACKGROUND: More than 30% of patients older than 60 years are obese and, therefore, at risk for kidney disease. Postoperative AKI is a significant problem. METHODS: We performed a matched case-control study of patients enrolled in the Obesity and Surgical Outcomes Study, using data of Medicare claims enriched with detailed chart review. Each AKI patient was matched with a non-AKI control similar in procedure type, age, sex, race, emergency status, transfer status, baseline estimated glomerular filtration rate, admission APACHE score, and the risk of death score with fine balance on hospitals. RESULTS: We identified 514 AKI cases and 694 control patients. Of the cases, 180 (35%) followed orthopedic procedures and 334 (65%) followed colon or thoracic surgery. After matching, obese patients undergoing a surgical procedure demonstrated a 65% increase in odds of AKI within 30 days from admission (odds ratio = 1.65, P \u3c 0.005) when compared with the nonobese patients. After adjustment for potential confounders, the odds of postoperative AKI remained elevated in the elderly obese (odds ratio = 1.68, P = 0.01.) CONCLUSIONS: : Obesity is an independent risk factor for postoperative AKI in patients older than 65 years. Efforts to optimize kidney function preoperatively should be employed in this at-risk population along with keen monitoring and maintenance of intraoperative hemodynamics. When subtle reductions in urine output or a rising creatinine are observed postoperatively, timely clinical investigation is warranted to maximize renal recovery

GRAPE for fast and scalable graph processing and random-walk-based embedding

Graph representation learning methods opened new avenues for addressing complex, real-world problems represented by graphs. However, many graphs used in these applications comprise millions of nodes and billions of edges and are beyond the capabilities of current methods and software implementations. We present GRAPE (Graph Representation Learning, Prediction and Evaluation), a software resource for graph processing and embedding that is able to scale with big graphs by using specialized and smart data structures, algorithms, and a fast parallel implementation of random-walk-based methods. Compared with state-of-the-art software resources, GRAPE shows an improvement of orders of magnitude in empirical space and time complexity, as well as competitive edge- and node-label prediction performance. GRAPE comprises approximately 1.7 million well-documented lines of Python and Rust code and provides 69 node-embedding methods, 25 inference models, a collection of efficient graph-processing utilities, and over 80,000 graphs from the literature and other sources. Standardized interfaces allow a seamless integration of third- party libraries, while ready-to-use and modular pipelines permit an easy-to- use evaluation of graph-representation-learning methods, therefore also positioning GRAPE as a software resource that performs a fair comparison between methods and libraries for graph processing and embedding

Mortality and Cardiovascular Disease among Older Live Kidney Donors

Over the past two decades, live kidney donation by older individuals (≥55 years) has become more common. Given the strong associations of older age with cardiovascular disease (CVD), nephrectomy could make older donors vulnerable to death and cardiovascular events. We performed a cohort study among older live kidney donors who were matched to healthy older individuals in the Health and Retirement Study. The primary outcome was mortality ascertained through national death registries. Secondary outcomes ascertained among pairs with Medicare coverage included death or CVD ascertained through Medicare claims data. During the period from 1996 to 2006, there were 5717 older donors in the United States. We matched 3368 donors 1:1 to older healthy nondonors. Among donors and matched pairs, the mean age was 59 years; 41% were male and 7% were black race. In median follow-up of 7.8 years, mortality was not different between donors and matched pairs (p = 0.21). Among donors with Medicare, the combined outcome of death/CVD (p = 0.70) was also not different between donors and nondonors. In summary, carefully selected older kidney donors do not face a higher risk of death or CVD. These findings should be provided to older individuals considering live kidney donation

KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response.

Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time-consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community vary drastically for different tasks; the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates heterogeneous biomedical data to produce knowledge graphs (KGs), and applied it to create a KG for COVID-19 response. This KG framework also can be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics

Quality of life impact and recovery after ureteroscopy and stent insertion: Insights from daily surveys in STENTS

BACKGROUND: Our objective was to describe day-to-day evolution and variations in patient-reported stent-associated symptoms (SAS) in the STudy to Enhance uNderstanding of sTent-associated Symptoms (STENTS), a prospective multicenter observational cohort study, using multiple instruments with conceptual overlap in various domains. METHODS: In a nested cohort of the STENTS study, the initial 40 participants having unilateral ureteroscopy (URS) and stent placement underwent daily assessment of self-reported measures using the Brief Pain Inventory short form, Patient-Reported Outcome Measurement Information System measures for pain severity and pain interference, the Urinary Score of the Ureteral Stent Symptom Questionnaire, and Symptoms of Lower Urinary Tract Dysfunction Research Network Symptom Index. Pain intensity, pain interference, urinary symptoms, and bother were obtained preoperatively, daily until stent removal, and at postoperative day (POD) 30. RESULTS: The median age was 44 years (IQR 29,58), and 53% were female. The size of the dominant stone was 7.5 mm (IQR 5,11), and 50% were located in the kidney. There was consistency among instruments assessing similar concepts. Pain intensity and urinary symptoms increased from baseline to POD 1 with apparent peaks in the first 2 days, remained elevated with stent in situ, and varied widely among individuals. Interference due to pain, and bother due to urinary symptoms, likewise demonstrated high individual variability. CONCLUSIONS: This first study investigating daily SAS allows for a more in-depth look at the lived experience after URS and the impact on quality of life. Different instruments measuring pain intensity, pain interference, and urinary symptoms produced consistent assessments of patients\u27 experiences. The overall daily stability of pain and urinary symptoms after URS was also marked by high patient-level variation, suggesting an opportunity to identify characteristics associated with severe SAS after URS

The Atacama Cosmology Telescope: Sunyaev Zel'dovich Selected Galaxy Clusters at 148 GHz in the 2008 Survey

We report on twenty-three clusters detected blindly as Sunyaev-Zel'dovich (SZ) decrements in a 148 GHz, 455 square-degree map of the southern sky made with data from the Atacama Cosmology Telescope 2008 observing season. All SZ detections announced in this work have confirmed optical counterparts. Ten of the clusters are new discoveries. One newly discovered cluster, ACT-CL J0102-4915, with a redshift of 0.75 (photometric), has an SZ decrement comparable to the most massive systems at lower redshifts. Simulations of the cluster recovery method reproduce the sample purity measured by optical follow-up. In particular, for clusters detected with a signal-to-noise ratio greater than six, simulations are consistent with optical follow-up that demonstrated this subsample is 100% pure. The simulations further imply that the total sample is 80% complete for clusters with mass in excess of 6x10^14 solar masses referenced to the cluster volume characterized by five hundred times the critical density. The Compton y -- X-ray luminosity mass comparison for the eleven best detected clusters visually agrees with both self-similar and non-adiabatic, simulation-derived scaling laws.Comment: 13 pages, 7 figures, Accepted for publication in Ap

Community Service: Editor pride and user preference on local newspaper websites

Armed with readily accessible online traffic logs that provide detailed information about the items users are selecting to view, editors are voicing concern about the potential effect on their own content decisions. Through a survey of local British newspaper editors, this article examines the overlap between user preferences, as suggested by assessments of website traffic, and content that editors identify as their best. Results are considered in the context of two related subsets of agenda-setting theory, as well as the sociological process of “making news.” The study finds overlap between broad categories of stories preferred by editors and users, but a considerable disconnect over the nature of the items within those categories