Profiling Tools Research Articles

Bringing Hope to Improve Treatment in Pancreatic Ductal Adenocarcinoma—A New Tool for Molecular Profiling of KRAS Mutations in Tumor and Plasma Samples

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) incidence is rising, and prognosis remains poor due to late diagnosis and limited effective therapies. Currently, patients are treated based on TNM staging, without molecular tumor characterization. This study aimed to validate a technique that combines the amplification refractory mutation system (ARMS) with high-resolution melting analysis (HRMA) for detecting mutations in codon 12 of KRAS in tumor and plasma, and to assess its prognostic value. Methods: Prospective study including patients with newly diagnosed PDAC with tumor and plasma samples collected before treatment. Mutations in codon 12 of KRAS (G12D, G12V, G12C, and G12R) were detected using ARMS–HRMA and compared to Sanger sequencing (SS). Univariate and multivariate analyses were used to evaluate the prognostic significance of these mutations. Results: A total of 88 patients, 93% with ECOG-PS 0–1, 57% with resectable disease. ARMS–HRMA technique showed a higher sensitivity than SS, both in tumor and plasma (77% vs. 51%; 25 vs. 0%, respectively). The most frequent mutation was G12D (n = 32, 36%), followed by G12V (n = 22, 25%). On multivariate analysis, patients with G12D and/or G12C mutations, either in tumor or plasma, had lower PFS (HR 1.792, 95% CI 1.061–3.028, p = 0.029; HR 2.081, 95% CI 1.014–4.272, p = 0.046, respectively) and lower OS (HR 1.757, 95% CI 1.013–3.049, p = 0.045; HR 2.229, 95% CI 1.082–4.594, p = 0.030, respectively). Conclusions: ARMS–HRMA is a rapid and cost-effective method for detecting KRAS mutations in PDAC patients, offering the potential for stratifying prognosis and guiding treatment decisions. The presence of G12D and G12C mutations in both tumor and plasma is associated with a poorer prognosis.

Viral epitope profiling of hematopoietic cell transplant recipients with respiratory syncytial virus upper respiratory tract and lower respiratory tract infections

Abstract Background The pre-fusion conformation of the F glycoprotein of respiratory syncytial virus (RSVpreF) has been the target of recent respiratory syncytial virus (RSV) therapies, including monoclonal antibodies for immunocompetent children and vaccines for the elderly. However, the utility of targeted therapies against RSVpreF is unknown in pediatric or adult hematopoietic cell transplant (HCT) recipients, and there are limited natural history studies characterizing humoral immune responses after RSV infection in HCT recipients. We utilized VirScan, a novel high-throughput profiling of antiviral antibody epitopes, to identify differences in global RSV-related epitope hits after an RSV infection. Methods We evaluated adult and pediatric allogeneic HCT recipients who acquired RSV from 12/2011 to 12/2019. Patients were categorized into 3 groups: upper respiratory tract infections (URTI) only, those who progressed from URTI to lower respiratory tract infections (progressors) and lower respiratory tract infections (LRTI) at diagnosis, and tested at baseline prior to infection (pre-RSV), at RSV URTI or LRTI diagnosis (RSV diagnosis), at LRTI progression (LRTI), 4-6 weeks after infection (Response 1) and >8 weeks after infection (Response 2), depending on sample availability. We interrogated the viral antibody repertoire using a serosurvey (VirScan) that detects immunoglobulin G responses to 206 viruses. VirScan metrics evaluated included: (1) number of RSV epitope hits, (2) log10 of the maximum RSV epitope binding signal (EBS), analogous to an antibody titer for each epitope, and (3) geometric mean of all RSV EBS. Kruskal-Wallis tests were used to compare groups for each VirScan metric at the different time points. Results A total of 129 samples from 39 patients were analyzed; 24 with URTI only, 8 progressors, and 7 with LRTI at diagnosis. At each time point, VirScan metrics were similar among the 3 patient groups (Table 1). Though patterns of VirScan metrics following RSV diagnosis varied by patient, most showed a modest increase in values (Figure 1). Conclusion In this preliminary study, we utilized the power of VirScan, a comprehensive serologic profiling tool of the entire human virome, to characterize RSV specific antibody changes after RSV infection in allogeneic HCT recipients. There were no differences in global RSV VirScan metrics between the 3 groups, suggesting that antibodies may not be the primary driver of viral infection attenuation in this population. Future analyses will focus on differences in individual epitope acquisition, including RSVpreF, between the 3 groups, and investigate possible interactions with humoral responses to other viruses. Figure 1. Longitudinal RSV VirScan metrics for each patient separated by 3 groups (top row: RSV URTI only; middle row: progressors from URTI to LRTI; bottom row: LRTI at diagnosis). Each line is an individual patient. The different panels show the changes in RSV related epitope hits (A), the log10 maximum epitope binding signal (EBS) among RSV epitopes (B), and the geometric mean of all the RSV related EBS (C). Open circles represent time points prior to RSV diagnosis, filled circles represent time points just prior to, on or after URTI, and asterisks represent time points just prior to, on, or after LRTI.

Enantiospecific profiling of D-amino acid for gastric cancer diagnosis by using a biocatalytic MHOF nanoreactor

The dynamic variation of D-amino acids (D-AAs) in human saliva has great potential as the indicator for individual physiological states and disease progression; however, enantiospecific profiling of D-AAs is a great challenge. In this work, a nanoreactor based on mesoporous hydrogen-bonded organic framework (MHOF) has been fabricated for the enantiospecific profiling of D-AAs. The nanoreactor is prepared by using MHOFs as the scaffold to organize the biocatalytic cascade of D-AA oxidase (DAAO) and horseradish peroxidase (HRP). In the meanwhile, the large, stable, and robust transport channels of MHOFs allow the unimpeded transport of the involved biocatalytic substrates. Once D-AA substrates efficiently transport into MHOFs, the chromogenic reactions of 3,3′,5,5′-tetramethylbenzidine (TMB) and H2O2 can be activated. So, using this MHOF nanoreactor, enantiospecific and visual detection of D-AAs can be achieved. Moreover, the stable nanoreactor can be operated in complex solution and utilized for the profiling of D-AA levels in saliva samples collected from gastric cancer patients, suggesting that D-AAs may be a powerful fingerprint for the diagnosis of gastric cancer. Therefore, the fabricated MHOF-based nanoreactor may provide an emerging tool for the enantiospecific profiling of D-AAs and supports the D-AA fingerprint as the indicator of gastric cancer diagnosis.

Distinguishing Artifactual Fatty Acid Dimers from Fatty Acid Esters of Hydroxy Fatty Acids in Untargeted LC-MS Pipelines.

Untargeted metabolomics is a powerful profiling tool for the discovery of possible biomarkers of disease onset and progression. Analytical pipelines applying liquid chromatography (LC) and mass spectrometry (MS)-based methods are widely used to survey a broad range of metabolites within various metabolic pathways, including organic acids, amino acids, nucleosides, and lipids. Accurate and complete identification of putative metabolites is an ongoing challenge in untargeted metabolomics studies. Highly sensitive instrumentation can result in the detection of adduct and fragment ions that form reproducibly and contain identifiable ions that are difficult to distinguish from metabolic pathway intermediates, which may result in false-positive identification. At concentrations as low as 10μM, free fatty acids have been found to form homo- and heterodimers in untargeted metabolomics pipelines that resemble the lipid class fatty acid esters of hydroxy fatty acids (FAHFAs), resulting in misidentification. This chapter details a protocol for LC-MS-based untargeted metabolomics using hydrophilic interaction chromatography (HILIC) that specifically aids in distinguishing artifactual fatty acid dimers from endogenous FAHFAs.

Immunoproteomics reveal different characteristics for the prognostic markers of intratumoral-infiltrating CD3+ T lymphocytes and immunoscore in colorectal cancer

Tumor-infiltrating lymphocytes (TILs) and immunoscoring based on densities of CD3+ and CD8+ TILs are both favorable prognostic markers in colorectal cancer (CRC). However, determination of the molecular features of TILs, particularly their immunoproteomic signatures would require the development of large-scale in situ spatiotemporal technologies. Recently, a multiplex in situ digital spatial proteomic profiling (DSP) tool GeoMx DSP has been applied to identify biomarkers predictive of therapeutic responses and to understand disease mechanisms and progression. Taking advantage of this tool, we simultaneously characterized the spatial distribution and interactions of 42 immune proteins in tumor cells (TC), CD3+ T stromal TILs (sTILs), and CD20+ B sTILs using tissue microarrays, and further studied their associations with CD3+ T TILs and immunoscores in CRC. First, our data showed that well-known immune checkpoints, such as PD-L1, PD-L2, and LAG3, were expressed at low levels, whereas some other immune proteins, such as CD11c, CD68, STING, and CD44, were highly expressed. Second, eight spatial interactions were identified, including five interactions between TC and CD20+ B sTILs, two interactions between CD3+ T sTILs and CD20+ B sTILs, and one interaction among TC, CD3+ T sTILs, and CD20+ B sTILs. Third, the differential immune microlandscape in the spatial compartments was identified in tissues with positive CD3+ T intratumoral TILs and high immunoscores. Collectively, our study is the first to provide in situ spatial immune characteristics at the proteomic level. Moreover, our findings provide direct evidence supporting the infiltration of CD3+ T sTILs from stoma to TC and shed important insights into better understanding and treating CRC patients related to different immune prognostic markers.

Role of Exosomes in Salivary Gland Tumors and Technological Advances in Their Assessment.

Backgroud: Salivary gland tumors (SGTs) are rare and diverse neoplasms, presenting significant challenges in diagnosis and management due to their rarity and complexity. Exosomes, lipid bilayer vesicles secreted by almost all cell types and present in all body fluids, have emerged as crucial intercellular communication agents. They play multifaceted roles in tumor biology, including modulating the tumor microenvironment, promoting metastasis, and influencing immune responses. Results: This review focuses on the role of exosomes in SGT, hypothesizing that novel diagnostic and therapeutic approaches can be developed by exploring the mechanisms through which exosomes influence tumor occurrence and progression. By understanding these mechanisms, we can leverage exosomes as diagnostic and prognostic biomarkers, and target them for therapeutic interventions. The exploration of exosome-mediated pathways contributing to tumor progression and metastasis could lead to more effective treatments, transforming the management of SGT and improving patient outcomes. Ongoing research aims to elucidate the specific cargo and signaling pathways involved in exosome-mediated tumorigenesis and to develop standardized techniques for exosome-based liquid biopsies in clinical settings. Conclusions: Exosome-based liquid biopsies have shown promise as non-invasive, real-time systemic profiling tools for tumor diagnostics and prognosis, offering significant potential for enhancing patient care through precision and personalized medicine. Methods like fluorescence, electrochemical, colorimetric, and surface plasmon resonance (SPR) biosensors, combined with artificial intelligence, improve exosome analysis, providing rapid, precise, and clinically valid cancer diagnostics for difficult-to-diagnose cancers.

Abstract C053: Pancreatic cancer patient-derived organoids, preclinical tools for therapeutic profiling, patient response prediction, and tumor evolution

Abstract Pancreatic cancer (PC) is characterized by an aggressive biology and an exceptionally high tumor heterogeneity that causes considerable variations in response to chemotherapies, targeted agents, and immunotherapies. Patient-derived organoids (PDOs) accurately reflect parental tumor biological and molecular features and may represent powerful preclinical avatars to predict drug response and support clinical decision-making. We generated a living organoid biobank of >100 PC PDO lines from treatment-naïve and pretreated primary tumor and metastases with a reliable efficacy (60.8%), and previously developed a pharmacotyping-guided prediction model to prognosticate patient therapy response in an initial feasibility trial (Beutel AK et al, 2021). Real-life chemotherapy responses in 46 patients (for a total of 93 therapy lines) matched to pharmacotyping-informed predictions with overall 73.1% accuracy, 85.4% sensitivity (responsiveness), and 63.5% specificity (non-responsiveness). Overall, our model allowed a successful drug-response prediction in naïve patients with an accuracy of 73.0% and 70.0% for first and second-line regimens. Prediction power was nevertheless lower in pretreated and heavily pretreated patients with a precision of 68.2% and 50.0% for subsequent chemotherapy lines, respectively. Interestingly, PDO-based pharmacotyping also precisely predicted patient clinical outcome in the neoadjuvant and adjuvant settings, with respective accuracies of 83.3% and 71.4%. Retrospective analysis of patient clinical data in palliative setting finally showed that the administration of a regimen predicted to be efficient ultimately translated into a significantly longer progression-free survival. Implementing automation and drug screening miniaturization to our workflow also significantly enhanced our process capacity, reduced time before pharmacotyping, and improved compliance to internal quality controls. Tracking clonal evolution in longitudinal biopsies (a set of seven PDO pairs derived from the same patients at two distinct timepoints) revealed lower mutational burden and therapy-driven genetic alterations upon progression. Notably, this approach revealed a CHEK2-mutated patient responded over time to PARP inhibitor maintenance therapy, aligning with our predictions and underscoring the robustness of our method. Single nucleus-resolved RNA and ATAC-seq analysis of a unique longitudinally-collected case uncovered transcriptomic and epigenetic dynamics associated with an oncogenic FGFR2 fusion and with a subsequent resistance-mediating mutation upon targeted treatment with FGFR2 inhibitors. Particularly, FGFR2 constitutive activation correlated with aberrant epigenetic trace and transcription programs of downstream targets as PI3K-AKT and RAS family members and of RNA polymerase II transcription machinery. Here, we report a robust and clinically-relevant preclinical tool for drug-response prediction, one more step towards a PDO therapeutic profiling-guided personalized medicine in clinical routine. Citation Format: Johann Gout, Yazid J Resheq, Jessica Lindenmayer, Julian D Schwab, Elodie Roger, Johann M Kraus, Thomas Ettrich, Alica K Beutel, Lukas Perkhofer, Hans A Kestler, Thomas Seufferlein, Alexander Kleger. Pancreatic cancer patient-derived organoids, preclinical tools for therapeutic profiling, patient response prediction, and tumor evolution [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C053.

Mapping Full Conformational Transition Dynamics of Intrinsically Disordered Proteins Using a Single-Molecule Nanocircuit.

Intrinsically disordered proteins (IDPs) are emerging therapeutic targets for human diseases. However, probing their transient conformations remains challenging because of conformational heterogeneity. To address this problem, we developed a biosensor using a point-functionalized silicon nanowire (SiNW) that allows for real-time sampling of single-molecule dynamics. A single IDP, N-terminal transactivation domain of tumor suppressor protein p53 (p53TAD1), was covalently conjugated to the SiNW through chemical engineering, and its conformational transition dynamics was characterized as current fluctuations. Furthermore, when a globular protein ligand in solution bound to the targeted p53TAD1, protein-protein interactions could be unambiguously distinguished from large-amplitude current signals. These proof-of-concept experiments enable semiquantitative, realistic characterization of the structural properties of IDPs and constitute the basis for developing a valuable tool for protein profiling and drug discovery in the future.

Phytochemical profiling and characterization of flavonoid derivatives from propolis sample and investigation of cytotoxic and antiprotozoal activities

Recently, the growth of consumer demand for functional foods with potential nutritional and health benefits led to rapid growth of analytical tools for profiling of bioactive metabolites and assure quality. Bee propolis is one of the most important bee products owing to its myriad health value. As a gummy exudate produced in beehives after harvesting from different plant species, bee propolis contains bioactive secondary metabolites. The current study aims to profiling the chemical composition of propolis samples from Nigeria using HPLC–UV-ELSD and with the aid of NMR-based analysis for assignment of metabolites classes abundant in Nigerian propolis. Red Nigerian propolis samples were subjected to phytochemical analysis using HPLC–UV-ELSD and NMR. Further chromatographic separation of promising fractions was performed by column chromatography and size exclusion chromatography. Screening of the antitrypanosomal and cytotoxic activities against Trypanosoma brucei and human leukemia cell lines (U937), respectively, was performed. The performance of LC–MS permitted identification of the different components from which 13 compound were identified and allowed combination of fractions to afford 9 fractions from which two isoflavonoids were isolated and identified using 1D and 2D NMR analysis with MS as isosativan and Medicarpin. Red Nigerian propolis crude extract showed the highest inhibitory activity at 6.5 µg/ml compared to moderate activity for the isolated compounds with MIC of 7.6 µg/ml and 12.1 µg/ml for medicarpin and isosativan, respectively. Moreover, the fraction RN-6 from the total extract showed the potent cytotoxic effect with IC50 = 26.5 µg/ml compared to standard diminazen which showed IC50 = 29.5 µg/ml.

Contaminant mass discharge estimation of a sulfonamide plume by use of hydraulic profiling tool (HPT) and fluorescence techniques

The contaminant mass discharge is a relevant metric to evaluate the risk that a groundwater plume poses to water resources. However, this assessment is often vitiated by a high uncertainty inherent to the assessment method and often limited number of measurement points to carry out the assessment. Direct-Push techniques in combination with profiling tools and dedicated sampling can be an interesting alternative to increase the measurement point density and hence reduce the mass discharge uncertainty. The main objective of our study was to assess if DP logging and sampling could be employed to get a reasonable estimate of contaminant mass discharge in a large sulfonamide contaminant plume (> 1500 m wide), compared to a more traditional approach based on monitoring wells. To do so, an Hydraulic Profiling Tool (HPT) logging with a dedicated site calibration was used to estimate the hydraulic conductivity field. The sulfonamide concentrations were inferred from the compound fluorescence properties measured by laboratory spectrofluorometry (λEx / λEm = 255/340 nm) and a dedicated log-log linear regression model. Our results show that HPT-derived hydraulic conductivity values are in good agreement with the monitoring well results, and within the order of magnitude reported in similar studies or indirect geophysical techniques. Fluorescence appears as a powerful proxy for the sulfonamide concentration levels. Ultimately, the contaminant mass discharge estimate from HPT and fluorescence techniques lies within a factor 2 from the estimate by monitoring wells, with 549 [274–668] and 776 [695–879] kg/yr respectively. Overall, this study highlights that DP logging tools combined with indirect methods (correlation with fluorescence) could provide a relevant contaminant mass discharge estimate for some optically active substances, given that a proper calibration phase is carried out.

Direct Observation of Procedural Skills (DOPS) in Enhancing Clinical Competencies of Postgraduate Medical and Dental Education: A Scoping Review

Background: As postgraduate medical or dental education students, most of us will have come across Direct Observation of Procedural Skills or DOPS. DOPS promoted clinical effectiveness by evaluating practice-based skills in the authentic organizational context, and subsequently proactively feeding back the learning to learners. This scoping review sought to synthesize the work done in determining DOPS's effectiveness in enhancing clinical competencies in some fields of medicine and dentistry. Methods: The study was carried out by using the following search engines: PubMed, Medline, Google Scholar, Science Direct, SID, Medlib and Google searched unpublished sources (Gray literature) and selected references (reference of reference) by typing the following keywords: (DOPS), clinical competencies, postgraduate medical and dental education. Results: From 215 papers 40 were analyzed and together demonstrated the efficiency of the Direct Observation of Procedural Skills (DOPS) as an assessment tool for numerous medical and dental profiles. It was revealed that DOPS improved procedural confidence, procedural performance competence and general clinical skills, all over the world. In their views, learners and educators overestimated the usefulness of DOPS and acknowledged its function of enhancing clinical competencies and offering feedback. The participants encountered some difficulties such as time limitations, coordination problems, and curriculum mismatch Nevertheless, DOPS was much more effective than traditional approaches in increasing satisfaction and reliability of the assessments in various medical training settings. Conclusion: In the context of postgraduate medical and dental education and training, the DOPS assessment tool was found to be very effective in enhancing clinical competencies and procedural skills. However, the successful implementation has the points that need to be attended like the training of the assessors and standardization although there are benefits of the same. Further studies were encouraged to investigate ways of enhancing the use of DOPS and how best it could be incorporated into post-graduate training

Numerical modelling and experimental investigation of incremental sheet metal forming of Aluminum Alloy Al 3003-O

Abstract Incremental sheet forming (ISF) is an unconventional sheet metal forming technique that can be widely used in the automotive, medical, and aerospace industries. The final product is achieved by moving a rotating tool along a defined spiral or profile tool path controlled by a CNC milling machine. A truncated cone shape was modeled in single point incremental forming (SPIF) to investigate the influence of step size, and sheet initial thickness parameters on the forming force components Fx , Fy , Fz during the forming process.

Spatial landscapes of cancers: insights and opportunities.

Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.

Defining and modeling dynamic spatial heterogeneity within tumor microenvironments

Many solid tumors exhibit significant genetic, cellular, and biophysical heterogeneity which dynamically evolves during disease progression and after treatment. This constant flux in cell composition, phenotype, spatial relationships, and tissue properties poses significant challenges in accurately diagnosing and treating patients. Much of the complexity lies in unraveling the molecular changes in different tumor compartments, how they influence one another in space and time and where vulnerabilities exist that might be appropriate to target therapeutically. Recent advances in spatial profiling tools and technologies are enabling new insight into the underlying biology of complex tumors, creating a greater understanding of the intricate relationship between cell types, states, and the microenvironment. Here we reflect on some recent discoveries in this area, where the key knowledge and technology gaps lie, and the advancements in spatial measurements and in vitro models for the study of spatial intratumoral heterogeneity.

Assessment of the Hydraulic Profiling Tool for Lower Permeability Characterization

AbstractThe Hydraulic Profiling Tool (HPT) has become one of the most widely accepted approaches for obtaining vertical profiles of hydraulic conductivity (K) in environmental site investigations. The current tool, however, is limited to use in moderately permeable settings with a measurable K range of 0.03 to 25 m/d. In this work, we added a low‐flow injection system to standard HPT and modified the field profiling procedure so that it could be used more effectively in lower‐K settings. The modified lower‐K HPT was tested and evaluated against direct‐push slug tests at a field site in the Kansas River floodplain. Results indicated that when the injection rate was reduced, injection pressure decreased, which reduced the potential of injection‐induced formation alteration. A particular challenge of applying HPT in lower‐K zones is the large pressure generated by probe advancement; this can significantly affect the pressure signal measured at the injection screen. Our results showed that the impacts of advancement‐generated pressure could be mitigated by reducing the speed of probe advancement. Compared to K estimates by slug tests, the vertical variability in HPT K was much lower. The reduced variability in HPT K was likely due to formation alteration during probe advancement, as well as pressure interference from injections at previous depths and probe advancement at the bottom. Additional work, such as the use of a smaller‐diameter probe, is needed to further improve the performance of HPT in lower permeability zones.

Electrical conductivity profiling for rapid contamination assessment in unsaturated zones: A case study of an MSW landfill

This study investigates the potential of using bulk soil electrical conductivity (ECbulk) to predict pore water conductivity (ECpw) for assessing the contamination in the unsaturated zone of an old municipal solid waste (MSW) landfill. ECbulk, ECpw, and water content were evaluated with depth at an old MSW landfill in Bhalswa, Delhi, using the Hydraulic Profiling Tool (HPT) and a dual tube soil sampling system. This data was also supplemented by a cone penetration test (CPTu) for high-resolution soil type identification. The correlation of ECbulk with ECpw was primarily influenced by volumetric water content and mineral conductivity with the latter being negligible at this site due to the high conductivity of the leachate. A reasonable linear correlation between normalized EC (ECbulk/ECpw) was observed with volumetric water content, except at low water contents. ECbulk and ECpw profiles with depth indicated attenuation of contaminants in clay layers, while sand layers exhibited constant profile with depth. ECpw was contributed by macro ions generally found in the leachate, including Na+, Mg2+, K+, Ca2+, NH4+, Cl−, SO42−, and HCO3−, as demonstrated by a strong correlation with their cumulative ionic strength. The results indicate that ECbulk profile can be used as a rapid semi-quantitative method for assessing contaminant migration in the unsaturated soil zone, supporting the remediation or control strategies at old landfills.

Advancing structural elucidation of conjugation drug metabolites in metabolite profiling with novel electron-activated dissociation.

This study focuses on the advantage of using the novel electron-activated dissociation (EAD) technology on the QTOF system for structural elucidation of conjugation metabolites. In drug metabolite identification, conceptual "boxes" are generally used to represent potential sites of modifications, which are proposed based on MS/MS data. Electron-activated dissociation (EAD) provides unique fragmentation patterns, potentially allowing for more precise localization of the metabolic modification sites compared to CID, particularly for conjugations. Known compounds were incubated with rat liver microsomes in the presence of nicotinamide adenine dinucleotide phosphate (NADPH), uridine dihosphate-glucuronic acid (UDPGA), and glutathione. Conjugation metabolites were analyzed using the QTOF system. High-resolution MS/MS spectra were collected using EAD and CID fragmentations along with TOF MS full scan for tested drugs and metabolites. Fragmentation patterns were compared to evaluate their efficiency in structural elucidation. Metabolite profiling identified conjugation metabolites (glucuronides and GSH adducts), using characteristic mass shifts. A comparison of EAD and CID fragmentation revealed EAD-specific fragments for most conjugates. EAD was able to break the relatively stable bonds on parent drug motifs while keeping relatively weak conjugation bonds intact, despite the generally low intensity of EAD. EAD effectively narrowed the conceptual "box" representing modification sites, providing more definitive information on conjugation sites and facilitating the structural elucidation of conjugated metabolites. EAD is a powerful tool for metabolite profiling in drug development, particularly for identifying conjugation sites. EAD-enabled MS/MS spectra offer a greater variety of signature fragments compared to CID, resulting in more comprehensive and unique structural information for metabolic modification analysis. Overall, EAD, complementary to CID, has the potential to narrow down potential modification sites, significantly enhancing the precision of conjugation metabolite structure elucidation.

Melon: metagenomic long-read-based taxonomic identification and quantification using marker genes

Long-read sequencing holds great potential for characterizing complex microbial communities, yet taxonomic profiling tools designed specifically for long reads remain lacking. We introduce Melon, a novel marker-based taxonomic profiler that capitalizes on the unique attributes of long reads. Melon employs a two-stage classification scheme to reduce computational time and is equipped with an expectation-maximization-based post-correction module to handle ambiguous reads. Melon achieves superior performance compared to existing tools in both mock and simulated samples. Using wastewater metagenomic samples, we demonstrate the applicability of Melon by showing it provides reliable estimates of overall genome copies, and species-level taxonomic profiles.

AI hybrid survival assessment for advanced heart failure patients with renal dysfunction

Renal dysfunction (RD) often characterizes the worse course of patients with advanced heart failure (AHF). Many prognosis assessments are hindered by researcher biases, redundant predictors, and lack of clinical applicability. In this study, we enroll 1736 AHF/RD patients, including data from Henan Province Clinical Research Center for Cardiovascular Diseases (which encompasses 11 hospital subcenters), and Beth Israel Deaconess Medical Center. We developed an AI hybrid modeling framework, assembling 12 learners with different feature selection paradigms to expand modeling schemes. The optimized strategy is identified from 132 potential schemes to establish an explainable survival assessment system: AIHFLevel. The conditional inference survival tree determines a probability threshold for prognostic stratification. The evaluation confirmed the system’s robustness in discrimination, calibration, generalization, and clinical implications. AIHFLevel outperforms existing models, clinical features, and biomarkers. We also launch an open and user-friendly website www.hf-ai-survival.com, empowering healthcare professionals with enhanced tools for continuous risk monitoring and precise risk profiling.

6-Gingerol modulates miRNAs and PODXL gene expression via methyltransferase enzymes in NB4 cells: an in silico and in vitro study

This investigation delves into the influence of predicted microRNAs on DNA methyltransferases (DNMTs) and the PODXL gene within the NB4 cell line, aiming to elucidate their roles in the pathogenesis of acute myeloid leukemia (AML). A comprehensive methodological framework was adopted to explore the therapeutic implications of 6-gingerol on DNMTs. This encompassed a suite of bioinformatics tools for protein structure prediction, docking, molecular dynamics, and ADMET profiling, alongside empirical assessments of miRNA and PODXL expression levels. Such a multifaceted strategy facilitated an in-depth understanding of 6-gingerol’s potential efficacy in DNMT modulation. The findings indicate a nuanced interplay where 6-gingerol administration modulated miRNA expression levels, decreasing in DNMT1 and DNMT3A expression in NB4 cells. This alteration indirectly influenced PODXL expression, contributing to the manifestation of oncogenic phenotypes. The overexpression of DNMT1 and DNMT3A in NB4 cells may contribute to AML, which appears modulable via microRNAs such as miR-193a and miR-200c. Post-treatment with 6-gingerol, DNMT1 and DNMT3A expression alterations were observed, culminating in the upregulation of miR-193a and miR-200c. This cascade effect led to the dysregulation of tumor suppressor genes in cancer cells, including downregulation of PODXL, and the emergence of cancerous traits. These insights underscore the therapeutic promise of 6-gingerol in targeting DNMTs and microRNAs within the AML context.