Class I methanol masers in low-mass star formation regions

Four Class I maser sources were detected at 44, 84, and 95 GHz toward chemically rich outflows in the regions of low-mass star formation NGC 1333I4A, NGC 1333I2A, HH25, and L1157. One more maser was found at 36 GHz toward a similar outflow, NGC 2023. Flux densities of the newly detected masers are no more than 18 Jy, being much lower than those of strong masers in regions of high-mass star formation. The brightness temperatures of the strongest peaks in NGC 1333I4A, HH25, and L1157 at 44 GHz are higher than 2000 K, whereas that of the peak in NGC 1333I2A is only 176 K. However, rotational diagram analysis showed that the latter source is also a maser. The main properties of the newly detected masers are similar to those of Class I methanol masers in regions of massive star formation. The former masers are likely to be an extension of the latter maser population toward low luminosities of both the masers and the corresponding YSOs.Comment: 5 pages, 1 figure, Proc. IAU Symp. 287 "Cosmic Masers: from OH to H0". LSR velocities of the HH25 masers, which are presented in Table 1, are correcte

SENSIBILIDADE DE ESPECTROS DE ONDAS OCEÂNICAS RECUPERADOS POR RADAR DE ABERTURA SINTÉTICA

SAR (Synthetic Aperture Radar ou Radar de Abertura Sintética) é o único sensor transportado por satélites capaz de medir o espectro direcional de ondas. Sua elevada cobertura espacial e temporal permite caracterizar o estado de mar, especialmente a região de baixa frequência do espectro de energia, que vem sendo assimilada em modelos numéricos de previsão de ondas em diversos centros operacionais espalhados pelo globo. Contudo, a extração do espectro de ondas de uma imagem SAR é um procedimento complexo. Alguns modos de operação não permitem o emprego de imagens sequenciais para resolver a ambiguidade direcional de propagação das ondas, o que requer informações adicionais, geralmente obtidas de um modelo de ondas. A dependência destas informações adicionais é investigada aplicando-se a inversão clássica de Hasselmann a alguns estados de mar teóricos. Esta abordagem é baseada na transformação analítica do espectro direcional de ondas sobre o espectro de imagem SAR correspondente. A solução deste problema inverso é determinada por um algoritmo numérico que minimiza um funcional não linear. Apesar de amplamente utilizado por diversos centros operacionais de previsão, este método não foi extensivamente testado em cenários experimentais bem definidos. Os resultados mostram que a dependência investigada é bastante significativa, sobretudo no que diz respeito à direção de propagação das ondas, levantando questionamentos sobre a acurácia da técnica

Beliefs and preferences regarding biological treatments for severe asthma

Background: Severe asthma is a serious condition with a significant burden on patients' morbidity, mortality, and quality of life. Some biological therapies targeting the IgE and interleukin-5 (IL5) mediated pathways are now available. Due to the lack of direct comparison studies, the choice of which medication to use varies. We aimed to explore the beliefs and practices in the use of biological therapies in severe asthma, hypothesizing that differences will occur depending on the prescribers’ specialty and experience. Methods: We conducted an online survey composed of 35 questions in English. The survey was circulated via the INterasma Scientific Network (INESNET) platform as well as through social media. Responses from allergists and pulmonologists, both those with experience of prescribing omalizumab with (OMA/IL5) and without (OMA) experience with anti-IL5 drugs, were compared. Results: Two hundred eighty-five (285) valid questionnaires from 37 countries were analyzed. Seventy-on percent (71%) of respondents prescribed biologics instead of oral glucocorticoids and believed that their side effects are inferior to those of Prednisone 5 mg daily. Agreement with ATS/ERS guidelines for identifying severe asthma patients was less than 50%. Specifically, significant differences were found comparing responses between allergists and pulmonologists (Chi-square test, p < 0.05) and between OMA/IL5 and OMA groups (p < 0.05). Conclusions: Uncertainties and inconsistencies regarding the use of biological medications have been shown. The accuracy of prescribers to correctly identify asthma severity, according to guidelines criteria, is quite poor. Although a substantial majority of prescribers believe that biological drugs are safer than low dose long-term treatment with oral steroids, and that they must be used instead of oral steroids, every effort should be made to further increase awareness. Efficacy as disease modifiers, biomarkers for selecting responsive patients, timing for outcomes evaluation, and checks need to be addressed by further research. Practices and beliefs regarding the use of asthma biologics differ between the prescriber's specialty and experience; however, the latter seems more significant in determining beliefs and behavior. Tailored educational measures are needed to ensure research results are better integrated in daily practice

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse

Evolutionary characterization of lung adenocarcinoma morphology in TRACERx

Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and ‘tumor spread through air spaces’ were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk

The evolution of lung cancer and impact of subclonal selection in TRACERx

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy