Blockchain technology and smart contracts: A potential tool for improving operational profit margin

This study presents a practical framework for implementing blockchain technology, specifically smart contracts, to optimise operations and enhance financial performance in the Consumer Packaged Goods (CPG) sector. It identifies best practices for operational efficiency and outlines the structural flow and challenges of implementing smart contracts in a small-scale CPG company. While blockchain is often associated with cryptocurrency, its value lies in enhancing core business processes such as vendor selection, procurement and legal compliance monitoring. The framework integrates blockchain-enabled smart contracts with project management lifecycle updates to streamline operations, enhance cash flow and reduce the Cost of Goods Sold (COGS). It highlights how procurement processes, legal requirements and vendor management can be streamlined through smart contracts, providing transparency, reducing delays and ensuring regulatory compliance. Blockchain is a decentralised database, and its applications span procurement, production processes and inventory management. However, leveraging blockchain effectively requires smart contracts. Integrating these contracts with project management tools ensures efficient operations and measurable financial metrics. This interdisciplinary approach combines technology, business law and project management to deliver actionable insights. The study highlights how modest operational efficiencies can drive profitability in low-margin industries, such as CPG, and establishes a foundation for future implementation studies across other sectors

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Comprehensive Molecular Cytogenetic Characterization of Cervical Cancer Cell Lines

We applied a combination of molecular cytogenetic methods, including comparative genomic hybridization (CGH), spectral karyotyping (SKY), and fluorescence in situ hybridization (FISH), to characterize the genetic aberrations in eight widely used cervical cancer (CC) cell lines. CGH identified the most frequent chromosomal losses including 2q, 3p, 4q, 6q, 8p, 9p, 10p, 13q, and 18q; gains including 3q, 5p, 5q, 8q, 9q, 11q, 14q, 16q, 17q, and 20q; and high-level chromosomal amplification at 3q21, 7p11, 8q23– q24, 10q21, 11q13, 16q23– q24, 20q11.2, and 20q13. Several recurrent structural chromosomal rearrangements, including der(5)t(5;8)(p13;q23) and i(5)(p10); deletions affecting chromosome bands 5p11, 5q11, and 11q23; and breakpoint clusters at 2q31, 3p10, 3q25, 5p13, 5q11, 7q11.2, 7q22, 8p11.2, 8q11.2, 10p11.2, 11p11.2, 14q10, 15q10, 18q21, and 22q11.2 were identified by SKY. We detected integration of HPV16 sequences by FISH on the derivative chromosomes involving bands 18p10 and 18p11 in cell line C-4I, 2p16, 5q21, 5q23, 6q, 8q24, 10, 11p11, 15q, and 18p11 in Ca Ski, and normal chromosome 17 at 17p13 in ME-180. FISH analysis was also used further to determine the copy number changes of PIKA3CA and MYC. This comprehensive cytogenetic characterization of eight CC cell lines enhances their utility in experimental studies aimed at gene discovery and functional analysis

A survey of detection and mitigation for fake images on social media platforms

Recently, the spread of fake images on social media platforms has become a significant concern for individuals, organizations, and governments. These images are often created using sophisticated techniques to spread misinformation, influence public opinion, and threaten national security. This paper begins by defining fake images and their potential impact on society, including the spread of misinformation and the erosion of trust in digital media. This paper also examines the different types of fake images and their challenges for detection. We then review the recent approaches proposed for detecting fake images, including digital forensics, machine learning, and deep learning. These approaches are evaluated in terms of their strengths and limitations, highlighting the need for further research. This paper also highlights the need for multimodal approaches that combine multiple sources of information, such as text, images, and videos. Furthermore, we present an overview of existing datasets, evaluation metrics, and benchmarking tools for fake image detection. This paper concludes by discussing future directions for fake image detection research, such as developing more robust and explainable methods, cross-modal fake detection, and the integration of social context. It also emphasizes the need for interdisciplinary research that combines computer science, digital forensics, and cognitive psychology experts to tackle the complex problem of fake images. This survey paper will be a valuable resource for researchers and practitioners working on fake image detection on social media platforms.peer-reviewe

Comparison of oral microbiota in tumor and non-tumor tissues of patients with oral squamous cell carcinoma

Abstract Background Bacterial infections have been linked to malignancies due to their ability to induce chronic inflammation. We investigated the association of oral bacteria in oral squamous cell carcinoma (OSCC/tumor) tissues and compared with adjacent non-tumor mucosa sampled 5 cm distant from the same patient (n = 10). By using culture-independent 16S rRNA approaches, denaturing gradient gel electrophoresis (DGGE) and cloning and sequencing, we assessed the total bacterial diversity in these clinical samples. Results DGGE fingerprints showed variations in the band intensity profiles within non-tumor and tumor tissues of the same patient and among the two groups. The clonal analysis indicated that from a total of 1200 sequences characterized, 80 bacterial species/phylotypes were detected representing six phyla, Firmicutes, Bacteroidetes, Proteobacteria, Fusobacteria, Actinobacteria and uncultivated TM7 in non-tumor and tumor libraries. In combined library, 12 classes, 16 order, 26 families and 40 genera were observed. Bacterial species, Streptococcus sp. oral taxon 058, Peptostreptococcus stomatis, Streptococcus salivarius, Streptococcus gordonii, Gemella haemolysans, Gemella morbillorum, Johnsonella ignava and Streptococcus parasanguinis I were highly associated with tumor site where as Granulicatella adiacens was prevalent at non-tumor site. Streptococcus intermedius was present in 70% of both non-tumor and tumor sites. Conclusions The underlying changes in the bacterial diversity in the oral mucosal tissues from non-tumor and tumor sites of OSCC subjects indicated a shift in bacterial colonization. These most prevalent or unique bacterial species/phylotypes present in tumor tissues may be associated with OSCC and needs to be further investigated with a larger sample size. </jats:sec

DSG3 As a Biomarker for the Ultrasensitive Detection of Cccult Lymph Node Metastasis in Oral Cancer Using Nanostructured Immunoarrays

OBJECTIVES: The diagnosis of cervical lymph node metastasis in head and neck squamous cell carcinoma (HNSCC) patients constitutes an essential requirement for clinical staging and treatment selection. However, clinical assessment by physical examination and different imaging modalities, as well as by histological examination of routine lymph node cryosections can miss micrometastases, while false positives may lead to unnecessary elective lymph node neck resections. Here, we explored the feasibility of developing a sensitive assay system for desmoglein 3 (DSG3) as a predictive biomarker for lymph node metastasis in HNSCC. MATERIALS AND METHODS: DSG3 expression was determined in multiple general cancer- and HNSCC-tissue microarrays (TMAs), in negative and positive HNSCC metastatic cervical lymph nodes, and in a variety of HNSCC and control cell lines. A nanostructured immunoarray system was developed for the ultrasensitive detection of DSG3 in lymph node tissue lysates. RESULTS: We demonstrate that DSG3 is highly expressed in all HNSCC lesions and their metastatic cervical lymph nodes, but absent in non-invaded lymph nodes. We show that DSG3 can be rapidly detected with high sensitivity using a simple microfluidic immunoarray platform, even in human tissue sections including very few HNSCC invading cells, hence distinguishing between positive and negative lymph nodes. CONCLUSION: We provide a proof of principle supporting that ultrasensitive nanostructured assay systems for DSG3 can be exploited to detect micrometastatic HNSCC lesions in lymph nodes, which can improve the diagnosis and guide in the selection of appropriate therapeutic intervention modalities for HNSCC patients