Small cell lung cancer (SCLC) is an aggressive neuroendocrine tumor, and no effective treatment is available to date. Mouse models of SCLC based on the inactivation of Rb1 and Trp53 show frequent ...amplifications of the Nfib and Mycl genes. Here, we report that, although overexpression of either transcription factor accelerates tumor growth, NFIB specifically promotes metastatic spread. High NFIB levels are associated with expansive growth of a poorly differentiated and almost exclusively E-cadherin (CDH1)-negative invasive tumor cell population. Consistent with the mouse data, we find that NFIB is overexpressed in almost all tested human metastatic high-grade neuroendocrine lung tumors, warranting further assessment of NFIB as a tumor progression marker in a clinical setting.
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•NFIB drives tumor initiation and progression in mouse models of SCLC•NFIB enhances metastasis and changes the metastatic profile•NFIB promotes dedifferentiation and invasion in SCLC•NFIB marks stage III/IV high-grade neuroendocrine carcinomas in patients
SCLC is a highly malignant cancer with an unmet need for better intervention strategies. Semenova et al. report that the transcription factor NFIB drives SCLC growth and metastasis, defines an aggressive tumor compartment in mice, and marks a subgroup of high-grade pulmonary neuroendocrine tumors (pNETs) in patients.
Cyclic voltammetry and controlled-potential (bulk) electrolysis have been employed to investigate the direct electrochemical reductions of 2-bromo-N-phenylacetamide (1a) and 2-iodo-N-phenylacetamide ...(1b) at glassy carbon cathodes in dimethylformamide containing tetramethylammonium tetrafluoroborate (TMABF4) as supporting electrolyte. Cyclic voltammograms for reduction of 1a and 1b each exhibit a pair of irreversible cathodic peaks; the first peak arises from a combination of one-electron and two-electron reductive cleavage of the respective carbon–halogen bond and the second peak is due to overall two-electron reductive cleavage of the carbon–halogen bond to produce a free halide ion together with 2-oxo-2-(phenylamino)ethan-1-ide. Controlled-potential (bulk) electrolysis of a 5mM solution of 1a or 1b at a potential corresponding to either the first or second cathodic peak affords only phenylacetamide. However, bulk electrolysis of a 10mM solution of 1a or 1b at a potential corresponding to either cathodic peak leads to a mixture of phenylacetamide and 1,4-diphenylpiperazine-2,5-dione. In the presence of a large excess of 1,1,1,3,3,3-hexafluoro-2-propanol (a proton donor), bulk electrolyses of 1a or 1b at a potential on the first peak give phenylacetamide exclusively. When either 1a or 1b is electrolyzed in the presence of 1M D2O, the resulting phenylacetamide is deuterated to a very significant extent (evidence for a carbanion intermediate), and a small quantity of 2-(dimethylamino)-N-phenylacetamide is seen as a side-product. Mechanisms to account for the behavior of 1a and 1b are proposed.
•Electrolyses of 5mM 2-halo-N-phenylacetamides afford phenylacetamide only.•Reduction of 10mM 2-halo-N-phenylacetamides yields 1,4-diphenylpiperazine-2,4-dione.•Reduction of 2-halo-N-phenylacetamides at glassy carbon is a two-step process.•Electrolyses of 10mM 2-halo-N-phenylacetamides give a mixture of products.
Stratigraphic identification from wire-line logs and core samples is a common method for lithology classification. This traditional approach is considered superior, despite its significant financial ...cost. Artificial neural networks and machine learning offer alternative, cost-effective means for automated data interpretation, allowing geoscientists to extract insights from data. At the same time, supervised and semi-supervised learning techniques are commonly employed, requiring a sufficient amount of labeled data to be generated through manual interpretation. Typically, there are abundant unlabeled geophysical data while labeled data are scarcer. Supervised and semi-supervised techniques partially address the cost issue. An underutilized class of machine-learning-based methods, unsupervised data clustering, can perform consonant classification by grouping similar data without requiring known results, presenting an even more cost-effective solution. In this study, we examine a state-of-the-art unsupervised data clustering algorithm called piecemeal clustering to identify lithofacies from wire-line logs, effectively addressing these challenges. The piecemeal clustering algorithm groups similar wire-log signatures into clusters, determines the number of clusters present in the data, and assigns each signature to one of the clusters, each of which represents a lithofacies. To evaluate the performance, we tested the algorithm on publicly released data from ten wells drilled in the Hugoton and Panoma fields of southwest Kansas and northwest Oklahoma, respectively. The data consist of two major groups: marine and non-marine facies. The study herein is centered around addressing two fundamental research questions regarding the accuracy and practicality of the piecemeal clustering algorithm. The algorithm successfully identified nine distinct clusters in our dataset, aligning with the cluster count observed in previously published works employing the same data. Regarding mapping accuracy, the results were notable, with success rates of 81.90% and 45.20% with and without considering adjacent facies, respectively. Further detailed analysis of the results was conducted for individual types of facies and independently for each well. These findings suggest the algorithm’s precision in characterizing the geological formations. To assess its performance, a comprehensive comparative analysis was conducted, encompassing other data clustering algorithms, as well as supervised and semi-supervised machine learning techniques. Notably, the piecemeal clustering algorithm outperformed alternative data clustering methods. Furthermore, despite its unsupervised nature, the algorithm demonstrated competitiveness by yielding results comparable to, or even surpassing, those obtained through supervised and semi-supervised techniques.
To better understand the expression pattern of programmed death-ligand 1 (PD-L1) expression in different breast cancer types, we characterized PD-L1 expression in tumor and tumor-infiltrating immune ...cells, in relation to mutation rate, BRCA1-like status and survival. We analyzed 410 primary treatment-naive breast tumors comprising 162 estrogen receptor-positive (ER+) and HER2−, 101 HER2+ and 147 triple-negative (TN) cancers. Pathologists quantified tumor-infiltrating lymphocytes (TILs) and PD-L1 expression in tumor cells and TILs using whole slides and tissue microarray. Mutation rate was assessed by DNA sequencing, BRCA1-like status using multiplex ligation-dependent probe amplification, and immune landscape by multiplex image analyses of CD4, CD68, CD8, FOXP3, cytokeratin, and PD-L1. Half of PD-L1 scores evaluated by tissue microarray were false negatives compared to whole slide evaluations. We observed at least 1% of PD-L1-positive (PD-L1+) cells in 53.1% of ER+HER2−, 73.3% of HER2+, and 84.4% of TN tumors. PD-L1 expression was higher in ductal compared to lobular carcinomas, also within ER+HER2− tumors (p = 0.04). High PD-L1+ TILs score (> 50%) was independently associated with better outcome in TN tumors (HR = 0.27; 95%CI = 0.10-0.69). Within TN tumors, PD-L1 and TIL scores showed a modest but significant positive association with the number of silent mutations, but no association with BRCA1-like status. Multiplex image analyses indicated that PD-L1 is expressed on multiple immune cells (CD68+ macrophages, CD4+, FOXP3+, and CD8+ T cells) in the breast tumor microenvironment, independent of the PD-L1 status of the tumor cells. We found no evidence that levels of PD-L1+ TILs in TN breast cancer are driven by high mutation rate or BRCA1-like status.
Various approaches have been discussed in the literature for the clustering of data, such as partitioning, hierarchical, and machine learning methods. Most of the approaches require some prior ...knowledge about the clusters, such as their total number. Furthermore, some previous algorithms are not robust enough to process higher-dimensional data or require a large amount of memory for computations. We propose, herein, a data clustering algorithm, Piecemeal Clustering, that successfully clusters data without prior knowledge of the number of clusters. The proposed clustering algorithm uses the similarity and density of the data to identify the number of clusters in the data set and works with both low- and high-dimensional data. We demonstrate the power of the proposed Piecemeal Clustering algorithm with two real-world data sets. It is found that the proposed algorithm outperforms seven other state-of-the-art algorithms on both of these data sets.
A novel procedure has been devised for the synthesis of derivatives of 1H-indole that is based on the direct, room-temperature electrochemical reduction of substituted o-nitrostyrenes at carbon ...cathodes in N,N-dimethylformamide containing tetramethylammonium tetrafluoroborate as supporting electrolyte and in the presence of a 10-fold molar excess of a proton donor (phenol or methyl 3-oxobutanoate).
Immune checkpoint inhibitors (ICI) can achieve remarkable responses in urothelial cancer (UC), which may depend on tumor microenvironment (TME) characteristics. However, the relationship between the ...TME, usually characterized by immune cell density, and response to ICI is unclear. Here, we quantify the TME immune cell densities and spatial relationships (SRs) of 24 baseline UC samples, obtained before pre-operative combination ICI treatment, using multiplex immunofluorescence. We describe SRs by approximating the first nearest-neighbor distance distribution with a Weibull distribution and evaluate the association between TME metrics and ipilimumab+nivolumab response. Immune cell density does not discriminate between response groups. However, the Weibull SR metrics of CD8
T cells or macrophages to their closest cancer cell positively associate with response. CD8
T cells close to B cells are characteristic of non-response. We validate our SR response associations in a combination ICI cohort of head and neck tumors. Our data confirm that SRs, in contrast to density metrics, are strong biomarkers of response to pre-operative combination ICIs.
In this paper, curve-fitting and intensity-level-selection (ILS)-based algorithms for wind parameter extraction from shipborne X-band nautical radar images are investigated. First, to exclude the ...rain cases and low-backscatter images, a data quality control process is designed for both algorithms. An additional process is then introduced for the ILS-based method to improve the accuracy of wind measurements, including the recognition of blockages and islands in the temporally integrated radar images. For the low sea states, a dual-curve-fitting is proposed. These wind algorithms are tested using radar images and shipborne anemometer data collected on the east coast of Canada. It is shown that the dual-curve-fitting algorithm produces improvements in the mean differences between the radar and the anemometer results for wind direction and speed of about 5.7° and 0.3 m/s, respectively, under sea states with significant wave height lower than 2.30 m. Also, a harmonic function that is least-squares fitted to the selected range distances vector as a function of antenna look direction is applied. Compared with the original ILS-based algorithm, the modified procedure reduces the standard deviation for wind direction and speed by about 4° and 0.2 m/s, respectively. Finally, the performance of these two modified methods are compared.
In non-small cell lung cancer (NSCLC), PD-L1 expression on either tumor cells (TC) or both TC and tumor-infiltrating immune cells (IC) is currently the most used biomarker in cancer immunotherapy. ...However, the mechanisms involved in PD-L1 regulation are not fully understood. To provide better insight in these mechanisms, a multiangular analysis approach was used to combine protein and mRNA expression with several clinicopathological characteristics.
Archival tissues from 640 early stage, resected NSCLC patients were analyzed with immunohistochemistry for expression of PD-L1 and CD8 infiltration. In addition, mutational status and expression of a selection of immune genes involved in the PD-L1/PD-1 axis and T-cell response was determined.
Tumors with high PD-L1 expression on TC or on IC represent two subsets of NSCLC with minimal overlap. We observed that PD-L1 expression on IC irrespective of expression on TC is a good marker for inflammation within tumors. In the tumors with the highest IC expression and absent TC expression an association with reduced IFNγ downstream signaling in tumor cells was observed.
These results show that PD-L1 expression on TC and IC are both independent hallmarks of the inflamed phenotype in NSCLC, and TC-negative/IC-high tumors can also be categorized as inflamed. The lack of correlation between PD-L1 TC and IC expression in this subgroup may be caused by impaired IFNγ signaling in tumor cells. These findings may bring a better understanding of the tumor-immune system interaction and the clinical relevance of PD-L1 expression on IC irrespective of PD-L1 expression on TC.
Surface alkylation of glassy carbon (GC) and reticulated vitreous carbon (RVC) cathodes can occur when a primary alkyl monohalide is present in solution and when the electrode is polarized at ...potentials more negative than those required for reductive cleavage of the carbon–halogen bond, leading to the grafting of alkyl moieties onto the surface of the carbon cathode. Examination of electrode surfaces by means of X-ray photoelectron spectroscopy (XPS) has revealed that surface sp2:sp3 carbon ratios are approximately 4:1 for both pristine GC and RVC electrode materials that are commercially available. Further XPS analysis of these electrodes before and after reduction of perfluorobutyl iodide (C4F9I) provides substantial supporting evidence for a previously proposed mechanism for the grafting process that involves an SN2-like reaction between sp2-hybridized carbon (nucleophile) of the cathode and primary alkyl halides (electrophile) leading to conversion of sp2 sites to sp3 sites, with final surface sp2:sp3 carbon ratios that fall below 1:1. At the end of this paper, we discuss (mainly in qualitative terms) the ramifications of this surface modification of GC and RVC electrodes with respect to (a) bulk reduction of primary alkyl halides and (b) use and behavior of a well-known catalyst precursor (1,2,4,5-tetracyanobenzene).
•Electroreduction of alkyl monohalides grafts alkyl groups onto glassy carbon.•Conversion of sp2 to sp3 sites upon alkyl-group grafting is revealed by XPS.•Alkyl groups grafted onto glassy carbon affect the behavior of a redox catalyst.•Behavior of a RVC electrode is irreversibly altered via grafting of alkyl groups.
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