Search Results (547)

Background/Objectives: Metabolic/bariatric surgery is currently the most successful treatment for patients with obesity; however, a fifth of patients undergoing surgery may not lose enough weight to be considered successful. Recent studies have shown that bariatric/metabolic surgery alters the epigenome and may explain postoperative improvements in metabolic health. The primary objective is to consolidate published differentially methylated CpG sites in pre- and post-metabolic/bariatric surgery female patients and associate them with the respective genes and pathways. Methods: This systematic review adhered to the PRISMA-P guidelines and was registered with the PROSPERO (CRD42023421852). Following an initial screening of 541 studies using COVIDENCE, six studies were selected, comprising three epigenome-wide association studies (EWAS) and three candidate gene methylation studies. The published studies collected DNA samples from female patients with obesity before and after surgery (3 months, 6 months, 9–31 months, and 2 years). KEGG pathway analysis was performed on genes where the extracted CpG sites were located. Results: The meta-analysis showed that 11,456 CpG sites are differentially methylated after a successful weight loss surgery, with 109 sites mapped to genes involved in key metabolic pathways, including FoxO, mTOR, insulin, cAMP, adipocytokine, Toll-like receptor, and PI3K-Akt. Conclusion: The highlighted differentially methylated CpG sites can be further used to predict the molecular signature associated with successful metabolic/bariatric surgery. Full article

Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most lethal cancers, accounting for a significant proportion of cancer-related deaths globally. Despite advancements in medical science, treatment options for PDAC remain limited, and the prognosis is often poor. Early detection is a critical factor in improving patient outcomes, but current diagnostic methods often fail to detect PDAC until it has advanced to a late stage. In this context, the development of more effective diagnostic tools is of paramount importance. In this study, we explored the potential of non-coding RNAs (ncRNAs) as diagnostic markers for PDAC using cell-free nucleotides and liquid biopsies. Leveraging the power of Next Generation Sequencing (NGS), bioinformatics analysis, and machine learning (ML), we were able to identify unique RNA signatures associated with PDAC. Our findings revealed twenty key genes, including microRNAs (miRNAs), long-non-coding RNAs (lncRNAs), and miscellaneous RNAs that demonstrated high classification accuracy. Specifically, our model achieved a classification accuracy of 87% and an area under the receiver operating characteristic curve (AUC) of 91%. These ncRNAs could potentially serve as robust biomarkers for PDAC, offering a promising avenue for the development of a non-invasive diagnostic test. This could revolutionize PDAC diagnosis, enabling earlier detection and intervention, which is crucial for improving patient outcomes. This work lays the groundwork for future research, with the potential to significantly enhance PDAC diagnosis and therapy. Full article

The detection of gamma-ray burst GRB 221009A has attracted significant attention due to its record brightness and first-ever detection of multi-TeV $\mathit{\gamma }$-rays from a GRB. Located at redshift $z=0.151$, this event is relatively nearby by GRB standards yet remains cosmologically distant, making the survival of multi-TeV photons surprising. The Large High Altitude Air Shower Observatory detected photons with energies up to ∼13 TeV during the early afterglow phase, challenging standard EBL models. We investigate whether several theoretical frameworks can explain this anomalous emission: reduced EBL opacity due to cosmic voids along the line of sight, novel emission mechanisms within the GRB environment, secondary $\mathit{\gamma }$-ray production through cosmic-ray cascades, and new physics scenarios involving Lorentz invariance violation or axion-like particles. Our analysis reveals areas of consensus regarding the exceptional nature of this event, while highlighting ongoing theoretical tensions about the dominant physical processes. We discuss the limitations of current models and identify specific observational signatures that future multi-wavelength and multi-messenger observations could provide to discriminate between competing explanations. The continued study of similar events with next-generation facilities will be crucial for resolving these theoretical challenges and advancing our understanding of extreme particle acceleration processes in astrophysical environments. Full article

Enteroviruses initiate genomic replication via a highly conserved mechanism that is controlled by an RNA platform, also known as the 5’ cloverleaf (5’CL). Here, we present a biophysical analysis of the 5’CL conformation of three enterovirus serotypes under various ionic conditions, utilizing CD spectroscopy, size-exclusion chromatography, and small-angle X-ray scattering. In general, a tendency toward a smaller monomeric hydrodynamic radius in the presence of salts was observed, but the exact structural signature of each 5’CL varied depending upon the serotype. Rhinovirus B14 (RVB14) exhibited at least two monomeric conformations and a low propensity for dimerization, while poliovirus 1 (PV1) showed a high propensity for dimerization, which was enhanced by the presence of salts. Enterovirus D70 was observed to be somewhat intermediate, with primarily a monomeric structure, but possessing some potential for dimerization. The equilibrium between the two monomeric and the dimeric conformations is also discussed. These results indicate that the 5’CL conformation may be more complex than the current literature suggests, thus underscoring the need for a combined crystal and solution approach for the accurate representation of the 5’CL conformation, and the conformation of other RNA structural elements, under native conditions. Full article

Woodcreepers (Dendrocolaptinae) constitute a subfamily of Neotropical passerines currently recognized as a monophyletic group within Furnariidae. Although Furnariidae is one of the most diverse avian families in the Neotropics, cytogenetic data remain scarce. In this study, we present the first cytogenetic analysis of Lepidocolaptes falcinellus using conventional (Ag-NOR, C-banding) and molecular (hybridization in situ fluorescence—FISH with telomeric and 18S rDNA probes) approaches. The species exhibits a karyotype with 2n = 80 chromosomes, predominantly acrocentric macrochromosomes, and heterochromatin restricted to centromeric regions. Telomeric repeats were confined to terminal regions, and 18S rDNA sites (NORs) were detected on the short arm of chromosome pair 1. This pattern, also observed in other Dendrocolaptinae species, contrasts with the ancestral avian condition of NORs on microchromosomes, suggesting a derived, lineage-specific chromosomal signature. These results support the cytogenetic cohesion of Dendrocolaptinae and reinforce the potential of NOR localization as a phylogenetic marker within the group. Our findings contribute novel cytotaxonomic data that enhance the understanding of chromosomal evolution and systematics in Furnariidae. Full article

Background: The respiratory microbiota is pivotal in maintaining pulmonary health and modulating disease; however, the intricate interplay between smoking, lung cancer, and microbiome composition remains incompletely understood. Here, we characterized the lower respiratory tract microbiome in a Russian cohort of 297 individuals, comprising healthy subjects and lung cancer patients of different smoking statuses (current smokers, former smokers, and nonsmokers). Methods: Using next-generation sequencing of the 16S rRNA gene from unstimulated sputum samples, we identify distinct microbiota signatures linked to smoking and lung cancer. A PERMANOVA (Adonis) test and linear discriminant analysis effect size were used for statistical analysis of data. Results: In healthy individuals, smoking did not affect microbiome diversity but markedly altered its composition, characterized by an increase in Streptococcus and a reduction in Neisseria as well as other genera such as Fusobacterium, Alloprevotella, Capnocytophaga, and Zhouea. Healthy former smokers’ microbiota profiles closely resembled those of healthy nonsmokers. In lung cancer patients, microbiome diversity and composition were minimally impacted by smoking, possibly due to the dominant influence of tumor-microenvironment-related factors. Nevertheless, Neisseria abundance remained significantly lower in smokers across advanced-stage lung cancer. Lung cancer patients exhibited distinctive microbiota signatures, including enrichment of Flavobacteriia, Bacillales, and Pasteurellales and depletion of Alphaproteobacteria, Coriobacteriaceae, and Microbacteriaceae, irrespective of smoking status. Conclusions: Our findings emphasize the profound impact of smoking on healthy respiratory microbiota which may be masked by lung-cancer-related factors. These insights highlight the necessity of considering smoking status in microbiome studies to enhance the understanding of respiratory health and disease. Full article

High-resolution and three-dimensional measurements at large scales represent a crucial frontier in flow diagnostics. Color-encoded illumination particle imaging velocimetry has emerged as a promising non-contact volumetric measurement technique in recent years. By employing chromatic gradient illumination to excite tracer particles, this method encodes depth information into color signatures, which are then correlated with two-dimensional positional data in images to reconstruct three-dimensional flow fields using a single camera. This review first introduces the fundamental principles of particle image velocimetry/particle tracking velocimetry and chromatic-depth encoding. Subsequently, we categorize color-depth-encoded particle velocimetry methods based on different illumination strategies, including LED-based, projector-based, and laser-based systems, discussing their respective configurations and representative applications. Finally, we summarize the current research progress in color-encoded particle image velocimetry techniques, provide a comparative analysis of their advantages and limitations, and discuss existing challenges along with future development prospects. Full article

In rotating machines, any faults in anti-friction bearings occurring during operation can lead to failures that are unacceptable due to considerable downtime losses and maintenance costs. Hence, early fault detection is essential, and different vibration-based methods (VBMs) are explored to recognise incipient fault signatures. Based on rotordynamics, if a bearing defect causes metal-to-metal (MtM) impacts during shaft rotation, the impacts excite high-frequency resonance responses of the bearing assembly. The defect-related frequencies are modulated with the resonance responses and rely on signal demodulation for fault detection. However, the current study highlights that the bearing fault/faults may not be detected if the defect in a bearing is not causing MtM impacts nor exciting the high-frequency resonance of the bearing assembly. In a roller bearing, a localised defect may maintain persistent contact between rolling elements and raceways, thereby preventing the occurrence of impulse vibration responses. Due to contact persistence, such defects may not generate impact and may not be detected by existing VBMs, and the bearing could behave as healthy. This paper investigates such specific cases by exploring the relationship between roller-bearing defect characteristics and their potential to generate impact loads during operation. Using an experimental bearing rig, different roller and inner-race defects are presented while their fault characteristic frequencies remain undetected by the envelope analysis, fast Kurtogram, cyclic spectral coherence, and tensor decomposition methods. This study highlights the significance of both the dimension and location of defects within bearings on their detectability based on the rotordynamics concept. Further, simple roller-beam experiments are carried out to visualise and validate the reliability of the experimental observations made on the roller bearing dynamics. Full article

This review synthesizes advances in livestock genomics by examining the interplay between candidate genes, molecular markers (MMs), signatures of selection (SSs), and quantitative trait loci (QTLs) in shaping economically vital traits across livestock species. By integrating advances in genomics, bioinformatics, and precision breeding, the study elucidates genetic mechanisms underlying productivity, reproduction, meat quality, milk yield, fibre characteristics, disease resistance, and climate resilience traits pivotal to meeting the projected 70% surge in global animal product demand by 2050. A critical synthesis of 1455 peer-reviewed studies reveals that targeted genetic markers (e.g., SNPs, Indels) and QTL regions (e.g., IGF2 for muscle development, DGAT1 for milk composition) enable precise selection for superior phenotypes. SSs, identified through genome-wide scans and haplotype-based analyses, provide insights into domestication history, adaptive evolution, and breed-specific traits, such as heat tolerance in tropical cattle or parasite resistance in sheep. Functional candidate genes, including leptin (LEP) for feed efficiency and myostatin (MSTN) for double-muscling, are highlighted as drivers of genetic gain in breeding programs. The review underscores the transformative role of high-throughput sequencing, genome-wide association studies (GWASs), and CRISPR-based editing in accelerating trait discovery and validation. However, challenges persist, such as gene interactions, genotype–environment interactions, and ethical concerns over genetic diversity loss. By advocating for a multidisciplinary framework that merges genomic data with phenomics, metabolomics, and advanced biostatistics, this work serves as a guide for researchers, breeders, and policymakers. For example, incorporating DGAT1 markers into dairy cattle programs could elevate milk fat content by 15-20%, directly improving farm profitability. The current analysis underscores the need to harmonize high-yield breeding with ethical practices, such as conserving heat-tolerant cattle breeds, like Sahiwal. Full article

Currently, due to the complexity of obtaining samples, specific features of laboratory processing and analysis of the results, there is a lack of data on the microbial signature of the small intestine in healthy and diseased states of the upper gastrointestinal tract. Objective: To investigate the characteristics of the small intestinal microbiome in acute pancreatitis of varying severity and to identify correlations with clinical factors. Methods: This study included 30 patients with acute pancreatitis of varying severity treated between 1 January 2019 and 31 December 2021. The composition of the microbiota was analyzed by metagenomic sequencing of the 16S rRNA gene from jejunal samples. Results: The mortality rate in the study group was 23.3%. The small intestinal microbiome was dominated by Streptococcus (median relative abundance 19.2%, interquartile range 6.4–35.1%), Veillonella (3.4%; 0.6–7%), Granulicatella (2.7%; 0.6–5%), Fusobacterium (2.2%; 0.3–5.9%), Prevotella (1.5%; 0.3–8%), Haemophilus (0.9%; 0.2–10%), Gemella (0.8%; 0.2–4.3%), and Lactobacillus (0.2%; 0.1–0.9%). More severe disease was associated with decreased abundance of Neisseria mucosa, Parvimonas micra, and Megasphaera micronuciformis. In contrast, the relative abundance of the genera Streptococcus (species S. rubneri/parasanguinis/australis), Actinomyces, and several genera within the family Enterobacteriaceae was higher in these patients. Conclusions: The state of the microbiota has important prognostic value and correlates with the duration from the onset of the pain syndrome to the time of receiving qualified care in the hospital. Full article

Inter-turn short-circuit (ITSC) faults in permanent magnet synchronous machines (PMSMs) present a significant reliability challenge in electric vehicle (EV) drivetrains, particularly under non-stationary operating conditions characterized by inverter-driven transients, variable loads, and magnetic saturation. Existing diagnostic approaches, including motor current signature analysis (MCSA) and wavelet-based methods, are primarily designed for steady-state conditions and rely on manual feature selection, limiting their applicability in real-time embedded systems. Furthermore, the lack of publicly available, high-fidelity datasets capturing the transient dynamics and nonlinear flux-linkage behaviors of PMSMs under fault conditions poses an additional barrier to developing data-driven diagnostic solutions. To address these challenges, this study introduces a simulation framework that generates a comprehensive dataset using finite element method (FEM) models, incorporating magnetic saturation effects and inverter-driven transients across diverse EV operating scenarios. Time-frequency features extracted via Discrete Wavelet Transform (DWT) from stator current signals are used to train a Transformer model for automated ITSC fault detection. The Transformer model, leveraging self-attention mechanisms, captures both local transient patterns and long-range dependencies within the time-frequency feature space. This architecture operates without sequential processing, in contrast to recurrent models such as LSTM or RNN models, enabling efficient inference with a relatively low parameter count, which is advantageous for embedded applications. The proposed model achieves 97% validation accuracy on simulated data, demonstrating its potential for real-time PMSM fault detection. Additionally, the provided dataset and methodology contribute to the facilitation of reproducible research in ITSC diagnostics under realistic EV operating conditions. Full article

Inelastic electron tunneling spectroscopy (IETS) has emerged as a powerful vibrational spectroscopy technique for molecular electronic junctions, providing unique insights into molecular vibrations and electron–phonon coupling at the nanoscale. In this review, we present a comprehensive overview of IETS in molecular junctions, tracing its development from foundational principles to the latest advances. We begin with the theoretical background, detailing the mechanisms by which inelastic tunneling processes generate vibrational fingerprints of molecules, and highlighting how IETS complements optical spectroscopies by accessing electrically driven vibrational excitations. We then discuss recent progress in experimental techniques and device architectures that have broadened the applicability of IETS. Central focus is given to emerging applications of IETS over the last decade: molecular sensing (identification of chemical bonds and conformational changes in junctions), thermoelectric energy conversion (probing vibrational contributions to molecular thermopower), molecular switches and functional devices (monitoring bias-driven molecular state changes via vibrational signatures), spintronic molecular junctions (detecting spin excitations and spin–vibration interplay), and advanced data analysis approaches such as machine learning for interpreting complex tunneling spectra. Finally, we discuss current challenges, including sensitivity at room temperature, spectral interpretation, and integration into practical devices. This review aims to serve as a thorough reference for researchers in physics, chemistry, and materials science, consolidating state-of-the-art understanding of IETS in molecular junctions and its growing role in molecular-scale device characterization. Full article

Due to their clinical heterogeneity, nonspecific symptoms, and the limitations of existing biomarkers and imaging modalities, metabolic brain diseases (MBDs), such as mitochondrial encephalopathies, lysosomal storage disorders, and glucose metabolism syndromes, pose significant diagnostic challenges. This review examines the growing potential of cell-free DNA (cfDNA) derived from cerebrospinal fluid (CSF) epigenetic profiling as a dynamic, cell-type-specific, minimally invasive biomarker approach for MBD diagnosis and monitoring. We review important technological platforms and their use in identifying CNS-specific DNA methylation patterns indicative of neuronal injury, neuroinflammation, and metabolic reprogramming, including cfMeDIP-seq, enzymatic methyl sequencing (EM-seq), and targeted bisulfite sequencing. By synthesizing current findings across disorders such as MELAS, Niemann–Pick disease, Gaucher disease, GLUT1 deficiency syndrome, and diabetes-associated cognitive decline, we highlight the superior diagnostic and prognostic resolution offered by CSF cfDNA methylation signatures relative to conventional CSF markers or neuroimaging. We also address technical limitations, interpretive challenges, and translational barriers to clinical implementation. Ultimately, this review explores CSF cfDNA epigenetic analysis as a liquid biopsy modality. The central objective is to assess whether epigenetic profiling of CSF-derived cfDNA can serve as a reliable and clinically actionable biomarker for improving the diagnosis and longitudinal monitoring of metabolic brain diseases. Full article

Oral squamous cell carcinoma (OSCC) remains one of the most common malignancies in the head and neck region, often preceded by a spectrum of oral potentially malignant disorders (OPMDs). Despite advances in diagnostic methods, reliable and non-invasive biomarkers for early detection and prognostic stratification are still lacking. In recent years, circulating cell-free DNA (cfDNA) has emerged as a promising liquid biopsy tool in several solid tumors, offering insights into tumor burden, heterogeneity, and molecular dynamics. However, its application in oral oncology remains underexplored. This study aims to review and discuss the current evidence on cfDNA quantification and mutation analysis (including TP53, NOTCH1, and EGFR) in patients with OPMDs and OSCC. Particular attention is given to cfDNA fragmentation patterns, methylation signatures, and tumor-specific mutations as prognostic and predictive biomarkers. Moreover, we highlight the challenges in standardizing pre-analytical and analytical workflows in oral cancer patients and explore the potential role of cfDNA in monitoring oral carcinogenesis. Understanding cfDNA dynamics in the oral cavity might offer a novel, minimally invasive strategy to improve early diagnosis, risk assessment, and treatment decision-making in oral oncology. Full article

Adrenocortical carcinoma (ACC) is an aggressive cancer with a poor prognosis. Mitotane, the only FDA-approved treatment for ACC, targets adrenocortical cells and reduces cortisol levels. Although it remains the cornerstone of systemic therapy, its overall impact on long-term outcomes is still a matter of ongoing clinical debate. Drug repurposing is a cost-effective way to identify new therapies, and defactinib, currently in clinical trials as part of combination therapies for various solid tumours, may enhance ACC treatment. We aimed to assess its efficacy in combination with mitotane. We tested the combination of mitotane and defactinib in H295R, SW13, and mitotane-sensitive and -resistant HAC15 cells, using functional assays, transcriptomic profiling, 2D and 3D cultures, bioprinted tissues, and xenografts. We assessed drug interactions with NMR and toxicity in vivo, as mitotane and defactinib have never been previously administered together. Genomic data from 228 human ACC and 158 normal adrenal samples were also analysed. Transcriptomic analysis revealed dysregulation of focal adhesion along with mitotane-related pathways. Focal adhesion kinase (FAK) signalling was enhanced in ACC compared to normal adrenal glands, with PTK2 (encoding FAK) upregulated in 44% of tumour samples due to copy number alterations. High FAK signature scores correlated with worse survival outcomes. FAK inhibition by defactinib, both alone and in combination with mitotane, showed effective anti-tumour activity in vitro. No toxicity or drug—drug interactions were observed in vivo. Combination treatment significantly reduced tumour volume and the number of macrometastases compared to those in the mitotane and control groups, with defactinib-treated tumours showing increased necrosis in xenografts. Defactinib combined with conventionally used mitotane shows promise as a novel combination therapy for ACC and warrants further investigation. Full article