Achieving Brazil's deforestation target will reduce fire and deliver air quality and public health benefits

Climate, deforestation, and forest fires are closely coupled in the Amazon, but models of fire that include these interactions are lacking. We trained machine learning models on temperature, rainfall, deforestation, land-use, and fire data to show that spatial and temporal patterns of fire in the Amazon are strongly modified by deforestation. We find that fire count across the Brazilian Amazon increases by 0.44 percentage points for each percentage point increase in deforestation rate. We used the model to predict that the increased deforestation rate in the Brazilian Amazon from 2013 to 2020 caused a 42% increase in fire counts in 2020. We predict that if Brazil had achieved the deforestation target under the National Policy on Climate Change, there would have been 32% fewer fire counts across the Brazilian Amazon in 2020. Using a regional chemistry-climate model and exposure-response associations, we estimate that the improved air quality due to reduced smoke emission under this scenario would have resulted in 2300 fewer deaths due to reduced exposure to fine particulate matter. Our analysis demonstrates the air quality and public health benefits that would accrue from reducing deforestation in the Brazilian Amazon

Impact of weather types on UK ambient particulate matter concentrations

Each year more than 29,000 premature deaths in the UK are linked to long term-exposure to ambient particulate matter (PM) with a diameter less than 2.5 μm (PM2.5). Many studies have focused on the long-term impacts of exposure to PM, but short-term increases in pollution can also exacerbate health effects, leading to deaths brought forward within exposed populations. This study investigates the impact of different atmospheric circulation patterns on UK PM2.5 concentrations and the relative contribution of local and transboundary pollutants to variations in PM2.5 concentrations. Daily mean PM2.5 observations from 42 UK background sites indicate that easterly, south-easterly and southerly wind directions and anticyclonic circulation patterns enhance background concentrations of PM2.5 at all UK sites by up to 12 μg m-3. Results from back trajectory analysis and the European Monitoring and Evaluation Programme for UK model (EMEP4UK) show this is due to the transboundary transport of pollutants from continental Europe. While back trajectories indicate under easterly, south-easterly and southerly flow 25–50% of the total accumulated primary PM2.5 emissions originate outside of the UK, with a very polluted footprint (0.25–0.35 μg m-2). Anticyclonic conditions, which occur frequently (21%), also lead to increases in PM2.5 concentrations (UK multi-annual mean 14.7 μg m-3). EMEP4UK results indicate this is likely due the build-up of local emissions due to slack winds. Under westerly and north-westerly flow 15–30% of the total accumulated primary PM2.5 emissions originate outside of the UK, and are much less polluted (0.1 μg m-2) with model results indicating transport of clean maritime air masses from the Atlantic. Results indicate that both wind-direction and stability under anticyclonic conditions are important in controlling ambient PM2.5 concentrations across the UK. There is also a strong dependence of high PM2.5 Daily Air Quality Index (DAQI) values on easterly, south-easterly and southerly wind-directions, with >70% of occurrences of observed 48–71+ μg m-3 concentrations occurring under these wind directions. While north-westerly and cyclonic conditions reduce PM2.5 concentrations at all sites by up to 8 μg m-3. PM2.5 DAQI values are also lowest under these conditions, with >80% of 0–11 μg m-3 concentrations and >50% of 12–23 μg m-3 concentrations observed during westerly, north-westerly and northerly wind directions. Indicating that these conditions are likely to be associated with a reduction in the potential health effects from exposure to ambient levels of PM2.5

Multimodality local consolidative treatment versus conventional care of advanced lung cancer after first-line systemic anti-cancer treatment: study protocol for the RAMON multicentre randomised controlled trial with an internal pilot

Introduction Lung cancer is the most common cause of cancer death worldwide and most patients present with extensive disease. One-year survival is improving but remains low (37%) despite novel systemic anti-cancer treatments forming the current standard of care. Although new therapies improve survival, most patients have residual disease after treatment, and little is known on how best to manage it. Therefore, residual disease management varies across the UK, with some patients receiving only maintenance systemic anti-cancer treatment while others receive local consolidative treatment (LCT), alongside maintenance systemic anti-cancer treatment. LCT can be a combination of surgery, radiotherapy and/or ablation to remove all remaining cancer within the lung and throughout the body. This is intensive, expensive and impacts quality of life, but we do not know if it results in better survival, nor the extent of impact on quality of life and what the cost might be for healthcare providers. The RAMON study (RAdical Management Of Advanced Non-small cell lung cancer) will evaluate the acceptability, effectiveness and cost-effectiveness of LCT versus no LCT after first-line systemic treatment for advanced lung cancer. Methods and analysis RAMON is a pragmatic open multicentre, parallel group, superiority randomised controlled trial. We aim to recruit 244 patients aged 18 years and over with advanced non-small-cell lung cancer from 40 UK NHS hospitals. Participants will be randomised in a 1:1 ratio to receive LCT alongside maintenance treatment, or maintenance treatment alone. LCT will be tailored to each patient’s specific disease sites. Participants will be followed up for a minimum of 2 years. The primary outcome is overall survival from randomisation. Ethics and dissemination The West of Scotland Research Ethics Committee (22/WS/0121) gave ethical approval in August 2022 and the Health Research Authority in September 2022. Participants will provide written informed consent before participating in the study. Findings will be presented at international meetings, in peer-reviewed publications, through patient organisations and notifications to patients. Trial registration number ISRCTN11613852

Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution

Immune evasion is a hallmark of cancer. Losing the ability to present neoantigens through human leukocyte antigen (HLA) loss may facilitate immune evasion. However, the polymorphic nature of the locus has precluded accurate HLA copy-number analysis. Here, we present loss of heterozygosity in human leukocyte antigen (LOHHLA), a computational tool to determine HLA allele-specific copy number from sequencing data. Using LOHHLA, we find that HLA LOH occurs in 40% of non-small-cell lung cancers (NSCLCs) and is associated with a high subclonal neoantigen burden, APOBEC-mediated mutagenesis, upregulation of cytolytic activity, and PD-L1 positivity. The focal nature of HLA LOH alterations, their subclonal frequencies, enrichment in metastatic sites, and occurrence as parallel events suggests that HLA LOH is an immune escape mechanism that is subject to strong microenvironmental selection pressures later in tumor evolution. Characterizing HLA LOH with LOHHLA refines neoantigen prediction and may have implications for our understanding of resistance mechanisms and immunotherapeutic approaches targeting neoantigens. Video Abstract [Figure presented] Development of the bioinformatics tool LOHHLA allows precise measurement of allele-specific HLA copy number, improves the accuracy in neoantigen prediction, and uncovers insights into how immune escape contributes to tumor evolution in non-small-cell lung cancer

Phase 1, pharmacogenomic, dose-expansion study of pegargiminase plus pemetrexed and cisplatin in patients with ASS1-deficient non-squamous non-small cell lung cancer

Introduction We evaluated the arginine-depleting enzyme pegargiminase (ADI-PEG20; ADI) with pemetrexed (Pem) and cisplatin (Cis) (ADIPemCis) in ASS1-deficient non-squamous non-small cell lung cancer (NSCLC) via a phase 1 dose-expansion trial with exploratory biomarker analysis. Methods Sixty-seven chemonaïve patients with advanced non-squamous NSCLC were screened, enrolling 21 ASS1-deficient subjects from March 2015 to July 2017 onto weekly pegargiminase (36 mg/m2) with Pem (500 mg/m2) and Cis (75 mg/m2), every 3 weeks (four cycles maximum), with maintenance Pem or pegargiminase. Safety, pharmacodynamics, immunogenicity, and efficacy were determined; molecular biomarkers were annotated by next-generation sequencing and PD-L1 immunohistochemistry. Results ADIPemCis was well-tolerated. Plasma arginine and citrulline were differentially modulated; pegargiminase antibodies plateaued by week 10. The disease control rate was 85.7% (n = 18/21; 95% CI 63.7%–97%), with a partial response rate of 47.6% (n = 10/21; 95% CI 25.7%–70.2%). The median progression-free and overall survivals were 4.2 (95% CI 2.9–4.8) and 7.2 (95% CI 5.1–18.4) months, respectively. Two PD-L1-expressing (≥1%) patients are alive following subsequent pembrolizumab immunotherapy (9.5%). Tumoral ASS1 deficiency enriched for p53 (64.7%) mutations, and numerically worse median overall survival as compared to ASS1-proficient disease (10.2 months; n = 29). There was no apparent increase in KRAS mutations (35.3%) and PD-L1 (<1%) expression (55.6%). Re-expression of tumoral ASS1 was detected in one patient at progression (n = 1/3). Conclusions ADIPemCis was safe and highly active in patients with ASS1-deficient non-squamous NSCLC, however, survival was poor overall. ASS1 loss was co-associated with p53 mutations. Therapies incorporating pegargiminase merit further evaluation in ASS1-deficient and treatment-refractory NSCLC

Sublobar resection or lobectomy for stage Ia non-small cell lung cancer: a systematic review and meta-analysis.

BACKGROUND: This systematic review and meta-analysis synthesises evidence from both randomised trials and observational studies to determine whether lobectomy or sublobar resection offers improved outcomes for patients with stage Ia non-small cell lung cancer (NSCLC). METHODS: Studies (up to June 2025) comparing lobectomy and sublobar resection (segmentectomy or wedge) for clinical stage Ia NSCLC (<2 cm) were included in the random-effects meta-analyses. Risk of bias was assessed using Risk of Bias 2 for randomised trials or Risk of Bias in Non-randomised Studies of Interventions-I for observational studies. RESULTS: 19 studies, including four randomised trials, were included. Overall survival at 5 years was comparable between lobectomy and sublobar resection (HR=1.00; 95% CI 0.84 to 1.19; I²=26%), as was disease-free survival (HR=1.05; 95% CI 0.90 to 1.23; I²=0%). Sublobar resection was associated with significantly higher local recurrence (OR=1.86; 95% CI 1.07 to 3.25; I²=73%). No differences were observed in 10-year survival (OR=0.99; 95% CI 0.27 to 3.59; I²=86%) or postoperative change in forced expiratory volume in 1 s (mean difference=-4.70; 95% CI -11.15 to 1.76; I²=99%). In 10 studies that mandated systematic hilar and mediastinal lymph node sampling, sublobar resection was associated with improved overall survival compared with lobectomy (HR=0.81; 95% CI 0.69 to 0.965; I²=0%). CONCLUSION: Lobectomy and sublobar resection offer comparable long-term survival for patients with stage Ia NSCLC. While sublobar resection is associated with higher local recurrence rates, subgroup analysis suggests that when intraoperative systematic hilar and mediastinal lymph node sampling is performed, sublobar resection may offer a survival advantage

Exploring DOXP-reductoisomerase binding limits using phosphonated N-aryl and N-heteroarylcarboxamides as DXR inhibitors

DOXP-reductoisomerase (DXR) is a validated target for the development of antimalarial drugs to address the increase in resistant strains of Plasmodium falciparum. Series of aryl- and heteroarylcarbamoylphosphonic acids, their diethyl esters and disodium salts have been prepared as analogues of the potent DXR inhibitor fosmidomycin. The effects of the carboxamide N-substituents and the length of the methylene linker have been explored using in silico docking studies, saturation transfer difference NMR spectroscopy and enzyme inhibition assays using both EcDXR and PfDXR. These studies indicate an optimal linker length of two methylene units and have confirmed the importance of an additional binding pocket in the PfDXR active site. Insights into the constraints of the PfDXR binding site provide additional scope for the rational design of DXR inhibitors with increased ligand–receptor interactions

Discovery and Expansion of Gene Modules by Seeking Isolated Groups in a Random Graph Process

BACKGROUND: A central problem in systems biology research is the identification and extension of biological modules-groups of genes or proteins participating in a common cellular process or physical complex. As a result, there is a persistent need for practical, principled methods to infer the modular organization of genes from genome-scale data. RESULTS: We introduce a novel approach for the identification of modules based on the persistence of isolated gene groups within an evolving graph process. First, the underlying genomic data is summarized in the form of ranked gene-gene relationships, thereby accommodating studies that quantify the relevant biological relationship directly or indirectly. Then, the observed gene-gene relationship ranks are viewed as the outcome of a random graph process and candidate modules are given by the identifiable subgraphs that arise during this process. An isolation index is computed for each module, which quantifies the statistical significance of its survival time. CONCLUSIONS: The Miso (module isolation) method predicts gene modules from genomic data and the associated isolation index provides a module-specific measure of confidence. Improving on existing alternative, such as graph clustering and the global pruning of dendrograms, this index offers two intuitively appealing features: (1) the score is module-specific; and (2) different choices of threshold correlate logically with the resulting performance, i.e. a stringent cutoff yields high quality predictions, but low sensitivity. Through the analysis of yeast phenotype data, the Miso method is shown to outperform existing alternatives, in terms of the specificity and sensitivity of its predictions