Passive CO₂ removal in urban soils:evidence from brownfield sites

Management of urban brownfield land can contribute to significant removal of atmospheric CO2 through the development of soil carbonate minerals. However, the potential magnitude and stability of this carbon sink is poorly quantified as previous studies address a limited range of conditions and short durations. Furthermore, the suitability of carbonate-sequestering soils for construction has not been investigated. To address these issues we measured total inorganic carbon, permeability and ground strength in the top 20 cm of soil at 20 brownfield sites in northern England, between 2015 and 2017. Across all sites accumulation occurred at a rate of 1–16 t C ha−1 yr−1, as calcite (CaCO3), corresponding to removal of approximately 4–59 t CO2 ha−1 yr−1, with the highest rate in the first 15 years after demolition. C and O stable isotope analysis of calcite confirms the atmospheric origin of the measured inorganic carbon. Statistical modelling found that pH and the content of fine materials (combined silt and clay content) were the best predictors of the total inorganic carbon content of the samples. Measurement of permeability shows that sites with carbonated soils possess a similar risk of run-off or flooding to sandy soils. Soil strength, measured as in-situ bearing capacity, increased with carbonation. These results demonstrate that the management of urban brownfield land to retain fine material derived from concrete crushing on site following demolition will promote calcite precipitation in soils, and so offers an additional CO2 removal mechanism, with no detrimental effect on drainage and possible improvements in strength. Given the large area of brownfield land that is available for development, the contribution of this process to CO2 removal by urban soils needs to be recognised in CO2 mitigation policies

A system�based intervention to reduce Black�White disparities in the treatment of early stage lung cancer: A pragmatic trial at five cancer centers

Background: Advances in early diagnosis and curative treatment have reduced high mortality rates associated with non�small cell lung cancer. However, racial disparity in survival persists partly because Black patients receive less curative treatment than White patients. Methods: We performed a 5�year pragmatic, trial at five cancer centers using a system�based intervention. Patients diagnosed with early stage lung cancer, aged 18�85 were eligible. Intervention components included: (1) a real�time warning system derived from electronic health records, (2) race�specific feedback to clinical teams on treatment completion rates, and (3) a nurse navigator. Consented patients were compared to retrospective and concurrent controls. The primary outcome was receipt of curative treatment. Results: There were 2841 early stage lung cancer patients (16% Black) in the retrospective group and 360 (32% Black) in the intervention group. For the retrospective baseline, crude treatment rates were 78% for White patients vs 69% for Black patients (P < 0.001); difference by race was confirmed by a model adjusted for age, treatment site, cancer stage, gender, comorbid illness, and income�odds ratio (OR) 0.66 for Black patients (95% CI 0.51�0.85, P = 0.001). Within the intervention cohort, the crude rate was 96.5% for Black vs 95% for White patients (P = 0.56). Odds ratio for the adjusted analysis was 2.1 (95% CI 0.41�10.4, P = 0.39) for Black vs White patients. Between group analyses confirmed treatment parity for the intervention. Conclusion: A system�based intervention tested in five cancer centers reduced racial gaps and improved care for all

Charge Fluctuations and Counterion Condensation

We predict a condensation phenomenon in an overall neutral system, consisting of a single charged plate and its oppositely charged counterions. Based on the ``two-fluid'' model, in which the counterions are divided into a ``free'' and a ``condensed'' fraction, we argue that for high surface charge, fluctuations can lead to a phase transition in which a large fraction of counterions is condensed. Furthermore, we show that depending on the valence, the condensation is either a first-order or a smooth transition.Comment: 16 pages, 1 figure, accepted to be published in PR

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

A grammar-based distance metric enables fast and accurate clustering of large sets of 16S sequences

Background: We propose a sequence clustering algorithm and compare the partition quality and execution time of the proposed algorithm with those of a popular existing algorithm. The proposed clustering algorithm uses a grammar-based distance metric to determine partitioning for a set of biological sequences. The algorithm performs clustering in which new sequences are compared with cluster-representative sequences to determine membership. If comparison fails to identify a suitable cluster, a new cluster is created. Results: The performance of the proposed algorithm is validated via comparison to the popular DNA/RNA sequence clustering approach, CD-HIT-EST, and to the recently developed algorithm, UCLUST, using two different sets of 16S rDNA sequences from 2,255 genera. The proposed algorithm maintains a comparable CPU execution time with that of CD-HIT-EST which is much slower than UCLUST, and has successfully generated clusters with higher statistical accuracy than both CD-HIT-EST and UCLUST. The validation results are especially striking for large datasets. Conclusions: We introduce a fast and accurate clustering algorithm that relies on a grammar-based sequence distance. Its statistical clustering quality is validated by clustering large datasets containing 16S rDNA sequences

Effect of an Antiracism Intervention on Racial Disparities in Time to Lung Cancer Surgery

PURPOSE Timely lung cancer surgery is a metric of high-quality cancer care and improves survival for early-stage non-small-cell lung cancer. Historically, Black patients experience longer delays to surgery than White patients and have lower survival rates. Antiracism interventions have shown benefits in reducing racial disparities in lung cancer treatment.METHODSWe conducted a secondary analysis of Accountability for Cancer Care through Undoing Racism and Equity, an antiracism prospective pragmatic trial, at five cancer centers to assess the impact on overall timeliness of lung cancer surgery and racial disparities in timely surgery. The intervention consisted of (1) a real-time warning system to identify unmet care milestones, (2) race-specific feedback on lung cancer treatment rates, and (3) patient navigation. The primary outcome was surgery within 8 weeks of diagnosis. Risk ratios (RRs) and 95% CIs were estimated using log-binomial regression and adjusted for clinical and demographic factors.RESULTSA total of 2,363 patients with stage I and II non-small-cell lung cancer were included in the analyses: intervention (n = 263), retrospective control (n = 1,798), and concurrent control (n = 302). 87.1% of Black patients and 85.4% of White patients in the intervention group (P =.13) received surgery within 8 weeks of diagnosis compared with 58.7% of Black patients and 75.0% of White patients in the retrospective group (P <.01) and 64.9% of Black patients and 73.2% of White patients (P =.29) in the concurrent group. Black patients in the intervention group were more likely to receive timely surgery than Black patients in the retrospective group (RR 1.43; 95% CI, 1.26 to 1.64). White patients in the intervention group also had timelier surgery than White patients in the retrospective group (RR 1.10; 95% CI, 1.02 to 1.18). CONCLUSION Accountability for Cancer Care through Undoing Racism and Equity is associated with timelier lung cancer surgery and reduction of the racial gap in timely surgery

A robust methodology to subclassify pseudokinases based on their nucleotide-binding properties

Protein kinase-like domains that lack conserved residues known to catalyse phosphoryl transfer, termed pseudokinases, have emerged as important signalling domains across all kingdoms of life. Although predicted to function principally as catalysis-independent protein-interaction modules, several pseudokinase domains have been attributed unexpected catalytic functions, often amid controversy. We established a thermal-shift assay as a benchmark technique to define the nucleotide-binding properties of kinase-like domains. Unlike in vitro kinase assays, this assay is insensitive to the presence of minor quantities of contaminating kinases that may otherwise lead to incorrect attribution of catalytic functions to pseudokinases. We demonstrated the utility of this method by classifying 31 diverse pseudokinase domains into four groups: devoid of detectable nucleotide or cation binding; cation-independent nucleotide binding; cation binding; and nucleotide binding enhanced by cations. Whereas nine pseudokinases bound ATP in a divalent cation-dependent manner, over half of those examined did not detectably bind nucleotides, illustrating that pseudokinase domains predominantly function as non-catalytic protein-interaction modules within signalling networks and that only a small subset is potentially catalytically active. We propose that henceforth the thermal-shift assay be adopted as the standard technique for establishing the nucleotide-binding and catalytic potential of kinase-like domains

Data science

Even though it has only entered public perception relatively recently, the term "data science" already means many things to many people. This chapter explores both top-down and bottom-up views on the field, on the basis of which we define data science as "a unique blend of principles and methods from analytics, engineering, entrepreneurship and communication that aim at generating value from the data itself". The chapter then discusses the disciplines that contribute to this "blend", briefly outlining their contributions and giving pointers for readers interested in exploring their backgrounds further

Predicting severe pain after major surgery: a secondary analysis of the Peri-operative Quality Improvement Programme (PQIP) dataset

Acute postoperative pain is common, distressing and associated with increased morbidity. Targeted interventions can prevent its development. We aimed to develop and internally validate a predictive tool to pre-emptively identify patients at risk of severe pain following major surgery. We analysed data from the UK Peri-operative Quality Improvement Programme to develop and validate a logistic regression model to predict severe pain on the first postoperative day using pre-operative variables. Secondary analyses included the use of peri-operative variables. Data from 17,079 patients undergoing major surgery were included. Severe pain was reported by 3140 (18.4%) patients; this was more prevalent in females, patients with cancer or insulin-dependent diabetes, current smokers and in those taking baseline opioids. Our final model included 25 pre-operative predictors with an optimism-corrected c-statistic of 0.66 and good calibration (mean absolute error 0.005, p = 0.35). Decision-curve analysis suggested an optimal cut-off value of 20–30% predicted risk to identify high-risk individuals. Potentially modifiable risk factors included smoking status and patient-reported measures of psychological well-being. Non-modifiable factors included demographic and surgical factors. Discrimination was improved by the addition of intra-operative variables (likelihood ratio χ2 496.5, p < 0.001) but not by the addition of baseline opioid data. On internal validation, our pre-operative prediction model was well calibrated but discrimination was moderate. Performance was improved with the inclusion of peri-operative covariates suggesting pre-operative variables alone are not sufficient to adequately predict postoperative pain

STAT1-dependent expression of energy metabolic pathways links tumour growth and radioresistance to the Warburg effect

<p>Abstract</p> <p>Background</p> <p>The Signal Transducer and Activator of Transcription 1 (STAT1) has traditionally been regarded as a transmitter of interferon signaling and a pro-apoptotic tumour suppressor. Recent data have identified new functions of STAT1 associated with tumourigenesis and resistance to genotoxic stress, including ionizing radiation (IR) and chemotherapy. To investigate the mechanisms contributing to the tumourigenic functions of STAT1, we performed a combined transcriptomic-proteomic expressional analysis and found that STAT1 is associated with regulation of energy metabolism with potential implication in the Warburg effect.</p> <p>Methods</p> <p>We generated a stable knockdown of STAT1 in the SCC61 human squamous cell carcinoma cell line, established tumour xenografts in athymic mice, and compared transcriptomic and proteomic profiles of STAT1 wild-type (WT) and knockdown (KD) untreated or irradiated (IR) tumours. Transcriptional profiling was based on Affymetrix Human GeneChip^®Gene 1.0 ST microarrays. Proteomes were determined from the tandem mass spectrometry (MS/MS) data by searching against the human subset of the UniProt database. Data were analysed using Significance Analysis of Microarrays for ribonucleic acid and Visualize software for proteins. Functional analysis was performed with Ingenuity Pathway Analysis with statistical significance measured by Fisher's exact test.</p> <p>Results</p> <p>Knockdown of STAT1 led to significant growth suppression in untreated tumours and radio sensitization of irradiated tumours. These changes were accompanied by alterations in the expression of genes and proteins of glycolysis/gluconeogenesis (GG), the citrate cycle (CC) and oxidative phosphorylation (OP). Of these pathways, GG had the most concordant changes in gene and protein expression and demonstrated a STAT1-dependent expression of genes and proteins consistent with tumour-specific glycolysis. In addition, IR drastically suppressed the GG pathway in STAT1 KD tumours without significant change in STAT1 WT tumours.</p> <p>Conclusion</p> <p>Our results identify a previously uncharacterized function of STAT1 in tumours: expressional regulation of genes encoding proteins involved in glycolysis, the citrate cycle and mitochondrial oxidative phosphorylation, with predominant regulation of glycolytic genes. STAT1-dependent expressional regulation of glycolysis suggests a potential role for STAT1 as a transcriptional modulator of genes responsible for the Warburg effect.</p