This comprehensive review explores the pivotal role of radiotherapy in cancer treatment, emphasizing the diverse applications of genetic profiling. The review highlights genetic markers for predicting radiation toxicity, enabling personalized treatment planning. It delves into the impact of genetic profiling on radiotherapy strategies across various cancer types, discussing research findings related to treatment response, prognosis, and therapeutic resistance. The integration of genetic profiling is shown to transform cancer treatment paradigms, offering insights into personalized radiotherapy regimens and guiding decisions in cases where standard protocols may fall short. Ultimately, the review underscores the potential of genetic profiling to enhance patient outcomes and advance precision medicine in oncology.

UNASSIGNED: Metabolic reprogramming is a hallmark feature of pancreatic ductal adenocarcinoma (PDAC). A pancreatic juice (PJ) metabolic signature has been reported to be prognostic of oncological outcome for PDAC. Integration of PJ profiling with transcriptomic and spatial characterization of the tumor microenvironment would help in identifying PDACs with peculiar vulnerabilities.
UNASSIGNED: We performed a transcriptomic analysis of 26 PDAC samples grouped into 3 metabolic clusters (M_CL) according to their PJ metabolic profile. We analyzed molecular subtypes and transcriptional differences. Validation was performed by multidimensional imaging on tumor slides.
UNASSIGNED: Pancreatic juice metabolic profiling was associated with PDAC transcriptomic molecular subtypes (p=0.004). Tumors identified as M_CL1 exhibited a non-squamous molecular phenotype and demonstrated longer survival. Enrichment analysis revealed the upregulation of immune genes and pathways in M_CL1 samples compared to M_CL2, the group with worse prognosis, a difference confirmed by immunofluorescence on tissue slides. Enrichment analysis of 39 immune signatures by xCell confirmed decreased immune signatures in M_CL2 compared to M_CL1 and allowed a stratification of patients associated with longer survival.
UNASSIGNED: PJ metabolic fingerprints reflect PDAC molecular subtypes and the immune microenvironment, confirming PJ as a promising source of biomarkers for personalized therapy.

Extracellular vesicles (EV) and the microRNAs that they contain are increasingly recognised as a rich source of informative biomarkers, reflecting pathological processes and fundamental biological pathways and responses. Their presence in biofluids makes them particularly attractive for biomarker identification. However, a frequent caveat in relation to clinical studies is low abundance of EV RNA content. In this study, we used NanoString nCounter technology to assess the microRNA profiles of n = 64 EV low concentration RNA samples (180-49125 pg), isolated from serum and cell culture media using precipitation reagent or sequential ultracentrifugation. Data was subjected to robust quality control parameters based on three levels of limit of detection stringency, and differential microRNA expression analysis was performed between biological subgroups. We report that RNA concentrations > 100 times lower than the current NanoString recommendations can be successfully profiled using nCounter microRNA assays, demonstrating acceptable output ranges for imaging parameters, binding density, positive/negative controls, ligation controls and normalisation quality control. Furthermore, despite low levels of input RNA, high-level differential expression analysis between biological subgroups identified microRNAs of biological relevance. Our results demonstrate that NanoString nCounter technology offers a sensitive approach for the detection and profiling of low abundance EV-derived microRNA, and may provide a solution for research studies that focus on limited sample material.

Thanks to the recent development of innovative instruments and software with high accuracy and resolution, 3D modelling provides useful insights in several sectors (from industrial metrology to cultural heritage). Moreover, the 3D reconstruction of objects of artistic interest is becoming mandatory, not only because of the risks to which works of art are increasingly exposed (e.g., wars and climatic disasters) but also because of the leading role that the virtual fruition of art is taking. In this work, we compared the performance of four 3D instruments based on different working principles and techniques (laser micro-profilometry, structured-light topography and the phase-shifting method) by measuring four samples of different sizes, dimensions and surface characteristics. We aimed to assess the capabilities and limitations of these instruments to verify their accuracy and the technical specifications given in the suppliers\' data sheets. To this end, we calculated the point densities and extracted several profiles from the models to evaluate both their lateral (XY) and axial (Z) resolution. A comparison between the nominal resolution values and those calculated on samples representative of cultural artefacts was used to predict the performance of the instruments in real case studies. Overall, the purpose of this comparison is to provide a quantitative assessment of the performance of the instruments that allows for their correct application to works of art according to their specific characteristics.

Profiling social media users is an analytical approach to generate an extensive blueprint of user\'s personal characteristics, which can be useful for a diverse range of applications, such as targeted marketing and personalized recommendations. Although social user profiling has gained substantial attention in recent years, effectively constructing a collaborative model that could describe long and short-term profiles is still challenging. In this paper, we will discuss the profiling problem from two perspectives; how to mathematically model and track user\'s behavior over short and long periods and how to enhance the classification of user\'s activities. Using mathematical equations, our model can define periods in which the user\'s interests abruptly changed. A dataset consisting of 30,000 tweets was built and manually annotated into 10 topic categories. Bi-LSTM and GRU models are applied to classify the user\'s activities representing his interests, which then are utilized to create and model the dynamic profile. In addition, the effect of word embedding techniques and pre-trained classification models on the accuracy of the classification process is explored in this research.

Amplicon sequencing stands as a cornerstone in microbiome profiling, yet concerns persist regarding its resolution and accuracy. The enhancement of reference databases and annotations marks a new era for 16S rRNA-based profiling. Capitalizing on this potential, we introduce PM-profiler, a novel tool for profiling amplicon short reads. PM-profiler is implemented by C++-based advanced algorithms, such as pre-allocated hash for reference construction, hybrid and dynamic short-read matching, big-data-guided dual-mode hierarchical taxonomy annotation strategy, and full-procedure parallel computing. This tool delivers species-level resolution and ultrafast speed for large-scale microbiomes, surpassing alignment-based approaches and the Naïve-Bayesian model. Furthermore, recognizing the global uneven distribution of microbes, we delineate optimal annotation strategies for each sampling habitat based on microbial patterns over 270,000 microbiomes. Integrated with the established workflow of Parallel-Meta Suite and the latest curated reference databases, this endeavor offers a swift and dependable solution for high-precision microbiome surveys.IMPORTANCEOur study introduces PM-profiler, a new tool that deciphers the complexity of microbial communities. With advanced algorithms, flexible annotation strategies, and well-organized big-data, PM-profiler provides a faster and more accurate way to study on microbiomes, paving the way for discoveries that could improve our understanding of microbiomes and their impact on the world.

Comensal Bacteroidota (Bacteroidota) and Enterobacteriacea are often linked to gut inflammation. However, the causes for variability of pro-inflammatory surface antigens that affect gut commensal/opportunistic dualism in Bacteroidota remain unclear. By using the classical lipopolysaccharide/O-antigen \'rfb operon\' in Enterobacteriaceae as a surface antigen model (5-rfb-gene-cluster rfbABCDX), and a recent rfbA-typing strategy for strain classification, we characterized the integrity and conservancy of the entire rfb operon in Bacteroidota. Through exploratory analysis of complete genomes and metagenomes, we discovered that most Bacteroidota have the rfb operon fragmented into nonrandom patterns of gene-singlets and doublets/triplets, termed \'rfb-gene-clusters\', or rfb-\'minioperons\' if predicted as transcriptional. To reflect global operon integrity, contiguity, duplication, and fragmentation principles, we propose a six-category (infra/supra-numerary) cataloging system and a Global Operon Profiling System for bacteria. Mechanistically, genomic sequence analyses revealed that operon fragmentation is driven by intra-operon insertions of predominantly Bacteroides-DNA (thetaiotaomicron/fragilis) and likely natural selection in gut-wall specific micro-niches or micropathologies. Bacteroides-insertions, also detected in other antigenic operons (fimbriae), but not in operons deemed essential (ribosomal), could explain why Bacteroidota have fewer KEGG-pathways despite large genomes. DNA insertions, overrepresenting DNA-exchange-avid (Bacteroides) species, impact our interpretation of functional metagenomics data by inflating by inflating gene-based pathway inference and by overestimating \'extra-species\' abundance. Of disease relevance, Bacteroidota species isolated from cavitating/cavernous fistulous tract (CavFT) microlesions in Crohn\'s Disease have supra-numerary fragmented operons, stimulate TNF-alpha from macrophages with low potency, and do not induce hyperacute peritonitis in mice compared to CavFT Enterobacteriaceae. The impact of \'foreign-DNA\' insertions on pro-inflammatory operons, metagenomics, and commensalism/opportunism requires further studies to elucidate their potential for novel diagnostics and therapeutics, and to elucidate the role of co-existing pathobionts in Crohn\'s disease microlesions.

Seaweed extracts have enormous potential as bio-stimulants and demonstrated increased growth and yield in different crops. The presence of physiologically active component stimulate plant stress signaling pathways, enhances growth and productivity, as well as serve as plant defense agents. The seaweed extracts can reduce the use of chemicals that harm the environment for disease management. In the present study, the Sargassum tenerrimum extract treatment was applied, alone and in combination with Sclerotium rolfsii, to Arachis hypogea, to study the differential metabolite expression. The majority of metabolites showed maximum accumulation with Sargassum extract-treated plants compared to fungus-treated plants. The different classes of metabolite compounds like sugars, carboxylic acids, polyols, showed integrated peaks in different treatments of plants. The sugars were higher in Sargassum extract and Sargassum extract + fungus treatments compared to control and fungus treatment, respectively. Interestingly, Sargassum extract + fungus treatment showed maximum accumulation of carboxylic acids. Pathway enrichment analysis showed regulation of different metabolites, highest impact with galactose metabolism pathway, identifying sucrose, myo-inositol, glycerol and fructose. The differential metabolite profiling and pathway analysis of groundnut in response to Sargassum extract and S. rolfsii help in understanding the groundnut- S. rolfsii interactions and the potential role of the Sargassum extract towards these interactions.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s12298-024-01418-9.

Functional traits influence the assembly of microbial communities, but identifying these traits in the environment has remained challenging. We studied ectomycorrhizal fungal (EMF) communities inhabiting Populus trichocarpa roots distributed across a precipitation gradient in the Pacific Northwest, USA. We profiled these communities using taxonomic (meta-barcoding) and functional (metagenomic) approaches. We hypothesized that genes involved in fungal drought-stress tolerance and fungal mediated plant water uptake would be most abundant in drier soils. We were unable to detect support for this hypothesis; instead, the abundance of genes involved in melanin synthesis, hydrophobins, aquaporins, trehalose-synthases, and other gene families exhibited no significant shifts across the gradient. Finally, we studied variation in sequence homology for certain genes, finding that fungal communities in dry soils are composed of distinct aquaporin and hydrophobin gene sequences. Altogether, our results suggest that while EMF communities exhibit significant compositional shifts across this gradient, coupled functional turnover, at least as inferred using community metagenomics is limited. Accordingly, the consequences of these distinct EMF communities on plant water uptake remain critically unknown, and future studies targeting the expression of genes involved in drought stress tolerance are required.

Disruption of the glycosylation machinery is a common feature in many types of cancer, and colorectal cancer (CRC) is no exception. Core fucosylation is mediated by the enzyme fucosyltransferase 8 (FucT-8), which catalyzes the addition of α1,6-l-fucose to the innermost GlcNAc residue of N-glycans. We and others have documented the involvement of FucT-8 and core-fucosylated proteins in CRC progression, in which we addressed core fucosylation in the syngeneic CRC model formed by SW480 and SW620 tumor cell lines from the perspective of alterations in their N-glycosylation profile and protein expression as an effect of the knockdown of the FUT8 gene that encodes FucT-8. Using label-free, semiquantitative mass spectrometry (MS) analysis, we found noticeable differences in N-glycosylation patterns in FUT8-knockdown cells, affecting core fucosylation and sialylation, the Hex/HexNAc ratio, and antennarity. Furthermore, stable isotopic labeling of amino acids in cell culture (SILAC)-based proteomic screening detected the alteration of species involved in protein folding, endoplasmic reticulum (ER) and Golgi post-translational stabilization, epithelial polarity, and cellular response to damage and therapy. This data is available via ProteomeXchange with identifier PXD050012. Overall, the results obtained merit further investigation to validate their feasibility as biomarkers of progression and malignization in CRC, as well as their potential usefulness in clinical practice.