skip to main content

Search for: All records

Creators/Authors contains: "Benjamin, T."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract Background Lung cancer is the leading cause of cancer death in both men and women. The most common lung cancer subtype is non-small cell lung carcinoma (NSCLC) comprising about 85% of all cases. NSCLC can be further divided into three subtypes: adenocarcinoma (LUAD), squamous cell carcinoma (LUSC), and large cell lung carcinoma. Specific genetic mutations and epigenetic aberrations play an important role in the developmental transition to a specific tumor subtype. The elucidation of normal lung versus lung tumor gene expression patterns and regulatory targets yields biomarker systems that discriminate lung phenotypes (i.e., biomarkers) and provide a foundation formore »the discovery of normal and aberrant gene regulatory mechanisms. Results We built condition-specific gene co-expression networks (csGCNs) for normal lung, LUAD, and LUSC conditions. Then, we integrated normal lung tissue-specific gene regulatory networks (tsGRNs) to elucidate control-target biomarker systems for normal and cancerous lung tissue. We characterized co-expressed gene edges, possibly under common regulatory control, for relevance in lung cancer. Conclusions Our approach demonstrates the ability to elucidate csGCN:tsGRN merged biomarker systems based on gene expression correlation and regulation. The biomarker systems we describe can be used to classify and further describe lung specimens. Our approach is generalizable and can be used to discover and interpret complex gene expression patterns for any condition or species.« less
    Free, publicly-accessible full text available December 1, 2023
  2. Abstract Background Quantification of gene expression from RNA-seq data is a prerequisite for transcriptome analysis such as differential gene expression analysis and gene co-expression network construction. Individual RNA-seq experiments are larger and combining multiple experiments from sequence repositories can result in datasets with thousands of samples. Processing hundreds to thousands of RNA-seq data can result in challenges related to data management, access to sufficient computational resources, navigation of high-performance computing (HPC) systems, installation of required software dependencies, and reproducibility. Processing of larger and deeper RNA-seq experiments will become more common as sequencing technology matures. Results GEMmaker, is a nf-core compliant,more »Nextflow workflow, that quantifies gene expression from small to massive RNA-seq datasets. GEMmaker ensures results are highly reproducible through the use of versioned containerized software that can be executed on a single workstation, institutional compute cluster, Kubernetes platform or the cloud. GEMmaker supports popular alignment and quantification tools providing results in raw and normalized formats. GEMmaker is unique in that it can scale to process thousands of local or remote stored samples without exceeding available data storage. Conclusions Workflows that quantify gene expression are not new, and many already address issues of portability, reusability, and scale in terms of access to CPUs. GEMmaker provides these benefits and adds the ability to scale despite low data storage infrastructure. This allows users to process hundreds to thousands of RNA-seq samples even when data storage resources are limited. GEMmaker is freely available and fully documented with step-by-step setup and execution instructions.« less
    Free, publicly-accessible full text available December 1, 2023
  3. Free, publicly-accessible full text available June 1, 2023
  4. The design/synthesis and characterization of organic donor–acceptor (D–A) dyads can provide precious data allowing to improve the efficiency of classical photo-induced bimolecular interactions/processes. In this report, two novel triplet D–A dyads (4 and 5) were synthesized and fully characterized. While the optical absorption and emission profiles of these new systems exhibit similar spectral structures as that of the triplet donor/sensitizer quinoidal thioamide (QDN), the transient absorption (TA) spectra of these two dyads produced new features that can be associated with triplet transients and charge transfer species. However, the kinetics of the excited-state processes/dynamics is significantly influenced by the geometrical arrangement(s)more »of donor/acceptor chromophores. Further analysis of the TA data suggests that the dyad with slip-stack geometry (4) is less effective in undergoing both intra- and inter-dyad triplet energy transfer than the dyad with co-facial geometry (5). Subsequently, triplet sensitization of 9,10-diphenylanthracene (DPA) using both dyads led to upconverted photoluminescence via triplet–triplet annihilation of DPA triplet transients. But, it was found that a maximum upconversion quantum yield could be achieved at a low power density using the co-facial type dyad 5. Altogether, these results provide valuable guidance in the design of triplet donor–acceptor dyads, which could be used for light-harvesting/modulation applications.« less
    Free, publicly-accessible full text available May 12, 2023
  5. Free, publicly-accessible full text available March 1, 2023
  6. The disappearance of mass-independent sulfur isotope fractionation (S-MIF) within the c. 2.3-billion-year-old (Ga) Rooihoogte Formation has been heralded as a chemostratigraphic marker of permanent atmospheric oxygenation. Reports of younger S-MIF, however, question this narrative, leaving significant uncertainties surrounding the timing, tempo, and trajectory of Earth’s oxygenation. Leveraging a new bulk quadruple S-isotope record, we return to the South African Transvaal Basin in search of support for supposed oscillations in atmospheric oxygen beyond 2.3 Ga. Here, as expected, within the Rooihoogte Formation, our data capture a collapse in Δ 3× S values and a shift from Archean-like Δ 36 S/Δ 33more »S slopes to their mass-dependent counterparts. Importantly, the interrogation of a Δ 33 S-exotic grain reveals extreme spatial variability, whereby atypically large Δ 33 S values are separated from more typical Paleoproterozoic values by a subtle grain-housed siderophile-enriched band. This isotopic juxtaposition signals the coexistence of two sulfur pools that were able to escape diagenetic homogenization. These large Δ 33 S values require an active photochemical sulfur source, fingerprinting atmospheric S-MIF production after its documented cessation elsewhere at ∼2.4 Ga. By contrast, the Δ 33 S monotony observed in overlying Timeball Hill Formation, with muted Δ 33 S values (<0.3‰) and predominantly mass-dependent Δ 36 S/Δ 33 S systematics, remains in stark contrast to recent reports of pronounced S-MIF within proximal formational equivalents. If reflective of atmospheric processes, these observed kilometer-scale discrepancies disclose heterogenous S-MIF delivery to the Transvaal Basin and/or poorly resolved fleeting returns to S-MIF production. Rigorous bulk and grain-scale analytical campaigns remain paramount to refine our understanding of Earth’s oxygenation and substantiate claims of post-2.3 Ga oscillations in atmospheric oxygen.« less
    Free, publicly-accessible full text available March 29, 2023
  7. Free, publicly-accessible full text available April 1, 2023
  8. Free, publicly-accessible full text available December 15, 2022
  9. Free, publicly-accessible full text available November 1, 2022
  10. Free, publicly-accessible full text available November 1, 2022