Extraction and characterization of carotenoid pigments with antioxidant and antibacterial potential from marine yeast Rhodotorula sp. KSB1.

Pigments are coloring agents used widely in different industrial sectors. There is a demand for using natural pigments rather than synthetic dyes because of the health hazards caused by synthetic dyes. Many natural pigments have different medicinal activities which can contribute to the nutritional value of the product. This study was carried forward with marine yeasts which can produce pigments. A total of 4 marine yeast isolates were recovered from the mangrove area of Sundarbans, West Bengal, India. Among them, the isolate KSB1 produced 856 µg/g total concentration of carotenoid pigment and the dry mass weight was 3.56 g/L. The stability of the extracted pigments was checked using temperature, pH, UV light exposure time, and different saline conditions. The pigments were characterized using HPLC and FTIR analysis. All of the extracted pigments showed good antioxidant activity in DPPH, metal chelating, and reducing power assay. The pigments were also found to have good antibacterial activity against the bacterial pathogens Staphylococcus aureus, Listeria monocytogenes, and Escherichia coli. Carotenoid pigment from KSB1 was found to have maximum activity in all the pathogens. The cytogenotoxicity using onion roots and phytotoxicity analysis indicated that the pigments were non-toxic and safe for cells. Finally, the potential marine yeast was identified using 18 s rRNA sequencing and identified as Rhodotorula sp. KSB1 (Accession no. MH782232).

Oral Astringency in Plant Proteins: An Underestimated Issue in Formulating Next-Generation Plant-Based Foods.

Ensuring the supply of affordable, palatable, healthy, and sustainable nutrients to feed the growing population without transgressing the planetary boundaries remains a key challenge in the food science community. A dietary transition toward low-emission, plant-based foods, with less reliance on animal agriculture, is advocated for sustainability, health, and ethical reasons. A major hurdle for mainstream adoption of plant-based foods is their poor sensorial performance, such as nonjuicy and astringent textures as well as various off-flavors. This review presents the current understanding of astringency and oral friction of plant-based foods. It focuses on plant proteins and their application in plant-based meat and dairy analogs. In addition, the latest advances in the quantitative characterization of astringency using tribology, electrochemistry, and cellular tools are covered. Finally, we examine factors influencing astringency and propose easy-to-implement colloidal strategies that may mitigate astringency issues, thereby underpinning the design of the next generation of sustainable and pleasurable plant-based foods. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 15 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A comprehensive trajectory analyzing the impact of neighborhood on women's health.

Impacts of neighborhoods are more pronounced on women's health since gender roles are often influenced by neighborhoods. To comprehend specific influences of neighborhoods on women's health, a systematic review of literature has been conducted. Authors have found that positive physical and social attributes of the neighborhood tend to promote good health status among women. While degraded physical and social environments of the neighborhoods result in adverse health status for women. The researchers suggest that majority of researchers' focuses are restricted to the United States of America (USA) and their works have peaked since the year 2003. Nevertheless, there is a dearth of researchers examining neighborhoods' influence on women's health in developing countries like India. Also, the health status of reproductive age group of women has not been specifically studied in any of these publications.

Machine learning and topological data analysis identify unique features of human papillae in 3D scans.

The tongue surface houses a range of papillae that are integral to the mechanics and chemistry of taste and textural sensation. Although gustatory function of papillae is well investigated, the uniqueness of papillae within and across individuals remains elusive. Here, we present the first machine learning framework on 3D microscopic scans of human papillae ([Formula: see text]), uncovering the uniqueness of geometric and topological features of papillae. The finer differences in shapes of papillae are investigated computationally based on a number of features derived from discrete differential geometry and computational topology. Interpretable machine learning techniques show that persistent homology features of the papillae shape are the most effective in predicting the biological variables. Models trained on these features with small volumes of data samples predict the type of papillae with an accuracy of 85%. The papillae type classification models can map the spatial arrangement of filiform and fungiform papillae on a surface. Remarkably, the papillae are found to be distinctive across individuals and an individual can be identified with an accuracy of 48% among the 15 participants from a single papillae. Collectively, this is the first evidence demonstrating that tongue papillae can serve as a unique identifier, and inspires a new research direction for food preferences and oral diagnostics.

Benchmarking of a microgel-reinforced hydrogel-based aqueous lubricant against commercial saliva substitutes.

Xerostomia, the subjective sensation of 'dry mouth' affecting at least 1 in 10 adults, predominantly elders, increases life-threatening infections, adversely impacting nutritional status and quality of life. A patented, microgel-reinforced hydrogel-based aqueous lubricant, prepared using either dairy or plant-based proteins, has been demonstrated to offer substantially enhanced lubricity comparable to real human saliva in in vitro experiments. Herein, we present the benchmarking of in vitro lubrication performance of this aqueous lubricant, both in its dairy and vegan formulation against a range of widely available and employed commercial saliva substitutes, latter classified based on their shear rheology into "liquids", "viscous liquids" and "gels", and also had varying extensional properties. Strikingly, the fabricated dairy-based aqueous lubricant offers up to 41-99% more effective boundary lubrication against liquids and viscous liquids, irrespective of topography of the tested dry mouth-mimicking tribological surfaces. Such high lubricity of the fabricated lubricants might be attributed to their limited real-time desorption (7%) from a dry-mouth mimicking hydrophobic surface unlike the tested commercial products including gels (23-58% desorption). This comprehensive benchmarking study therefore paves the way for employing these microgel-based aqueous lubricant formulations as a novel topical platform for dry mouth therapy.

Synthetic and biopolymeric microgels: Review of similarities and difference in behaviour in bulk phases and at interfaces.

This review discusses the current knowledge of interfacial and bulk interactions of biopolymeric microgels in relation to the well-established properties of synthetic microgels for applications as viscosity modifiers and Pickering stabilisers. We present a timeline showing the key milestones in designing microgels and their bulk/ interfacial performance. Poly(N-isopropylacrylamide) (pNIPAM) microgels have remained as the protagonist in the synthetic microgel domain whilst proteins or polysaccharides have been primarily used to fabricate biopolymeric microgels. Bulk properties of microgel dispersions are dominated by the volume fraction (ϕ) of the microgel particles, but ϕ is difficult to pinpoint, as addressed by many theoretical models. By evaluating recent experimental studies over the last five years, we find an increasing focus on the analysis of microgel elasticity as a key parameter in modulating their packing at the interfaces, within the provinces of both synthetic and biopolymeric systems. Production methods and physiochemical factors shown to influence microgel swelling in the aqueous phase can have a significant impact on their bulk as well as interfacial performance. Compared to synthetic microgels, biopolymer microgels show a greater tendency for polydispersity and aggregation and do not appear to have a core-corona structure. Comprehensive studies of biopolymeric microgels are still lacking, for example, to accurately determine their inter- and intra- particle interactions, whilst a wider variety of techniques need to be applied in order to allow comparisons to real systems of practical usage.

Development of a Ratiometric Tension Sensor Exclusively Responding to Integrin Tension Magnitude in Live Cells.

Integrin tensions are critical for cell mechanotransduction. By converting force to fluorescence, molecular tension sensors image integrin tensions in live cells with a high resolution. However, the fluorescence signal intensity results collectively from integrin tension magnitude, tension dwell time, integrin density, sensor accessibility, and so forth, making it highly challenging to specifically monitor the molecular force level of integrin tensions. Here, a ratiometric tension sensor (RTS) was developed to exclusively monitor the integrin tension magnitude. The RTS consists of two tension-sensing units that are coupled in series and always subject to the same integrin tension. These two units are activated by tension to fluoresce in separate spectra and with different activation rates. The ratio of their activation probabilities, reported by fluorescence ratiometric measurement, is solely determined by the local integrin tension magnitude. RTS responded sensitively to the variation of integrin tension magnitude in platelets and focal adhesions due to different cell plating times, actomyosin inhibition, or vinculin knockout. At last, RTS confirmed that integrin tension magnitude in platelets and focal adhesions decreases monotonically with the substrate rigidity, verifying the rigidity dependence of integrin tensions in live cells and suggesting that integrin tension magnitude could be a key biomechanical factor in cell rigidity sensing.

Transforming sustainable plant proteins into high performance lubricating microgels.

With the resource-intensive meat industry accounting for over 50% of food-linked emissions, plant protein consumption is an inevitable need of the hour. Despite its significance, the key barrier to adoption of plant proteins is their astringent off-sensation, typically associated with high friction and consequently poor lubrication performance. Herein, we demonstrate that by transforming plant proteins into physically cross-linked microgels, it is possible to improve their lubricity remarkably, dependent on their volume fractions, as evidenced by combining tribology using biomimetic tongue-like surface with atomic force microscopy, dynamic light scattering, rheology and adsorption measurements. Experimental findings which are fully supported by numerical modelling reveal that these non-lipidic microgels not only decrease boundary friction by an order of magnitude as compared to native protein but also replicate the lubrication performance of a 20:80 oil/water emulsion. These plant protein microgels offer a much-needed platform to design the next-generation of healthy, palatable and sustainable foods.

Monitoring Metabolic Changes in Response to Chemotherapies in Cancer with Raman Spectroscopy and Metabolomics.

Resistance to clinical therapies remains a major barrier in cancer management. There is a critical need for rapid and highly sensitive diagnostic tools that enable early prediction of treatment response to allow accurate clinical decisions. Here, Raman spectroscopy was employed to monitor changes in key metabolites as early predictors of response in KRAS-mutant colorectal cancer (CRC) cells, HCT116, treated with chemotherapies. We show at the single cell level that HCT116 is resistant to cetuximab (CTX), the first-line treatment in CRC, but this resistance can be overcome with pre-sensitization of cells with oxaliplatin (OX). In combination treatment of CTX + OX, sequential delivery of OX followed by CTX rather than simultaneous administration of drugs was observed to be critical for effective therapy. Our results demonstrated that metabolic changes are well aligned to cellular mechanical changes where Young's modulus decreased after effective treatment, indicating that both changes in mechanical properties and metabolism in cells are likely responsible for cancer proliferation. Raman findings were verified with mass spectrometry (MS) metabolomics, and both platforms showed changes in lipids, nucleic acids, and amino acids as predictors of resistance/response. Finally, key metabolic pathways enriched were identified when cells are resistant to CTX but downregulated with effective treatment. This study highlights that drug-induced metabolic changes both at the single cell level (Raman) and ensemble level (MS) have the potential to identify mechanisms of response to clinical cancer therapies.

Unraveling anticancer potential of a novel serine protease inhibitor from marine yeast Candida parapsilosis ABS1 against colorectal and breast cancer cells.

The study was planned to isolate a serine protease inhibitor compound with anticancer potential against colorectal and breast cancer cells from marine yeast. Protease enzymes play a crucial role in the mechanism of life-threatening diseases like cancer, malaria and AIDS. Hence, blocking these enzymes with potential inhibitors can be an efficient approach in drug therapy for these diseases. A total of 12 marine yeast isolates, recovered from mangrove swamps of Sundarbans, India, showed inhibition activity against trypsin. The yeast isolate ABS1 showed highest inhibition activity (89%). The optimum conditions for protease inhibitor production were found to be glucose, ammonium phosphate, pH 7.0, 30 °C and 2 M NaCl. The PI protein from yeast isolate ABS1 was purified using ethyl acetate extraction and anion exchange chromatography. The purified protein was characterized using denaturing SDS-PAGE, Liquid Chromatography Electrospray Ionization Mass Spectrometry (LC-ESI-MS), Reverse Phase High Pressure Liquid Chromatography (RP-HPLC) and Fourier Transform Infra-red Spectroscopy (FTIR) analysis. The intact molecular weight of the PI protein was determined to be 25.584 kDa. The PI protein was further studied for in vitro anticancer activities. The IC50 value for MTT cell proliferation assay was found to be 43 µg/ml against colorectal cancer HCT15 cells and 48 µg/ml against breast cancer MCF7 cells. Hoechst staining, DAPI staining and DNA fragmentation assay were performed to check the apoptotic cells. The marine yeast was identified as Candida parapsilosis ABS1 (Accession No. MH782231) using 18s rRNA sequencing.

Ultra-stable liquid crystal droplets coated by sustainable plant-based materials for optical sensing of chemical and biological analytes.

Herein, we demonstrate for the first time the synthesis of ultra-stable, spherical, nematic liquid crystal (LC) droplets of narrow size polydispersity coated by sustainable, biodegradable, plant-based materials that trigger a typical bipolar-to-radial configurational transition in dynamic response to chemical and biological analytes. Specifically, a highly soluble polymer, potato protein (PoP) and a physically-crosslinked potato protein microgel (PoPM) of ∼100 nm in diameter, prepared from the PoP, a byproduct of the starch industry, were compared for their ability to coat LC droplets. Although both PoP and PoPM were capable of reducing the interfacial tension between water and n-tetradecane <30 mN m-1, PoPM-coated LC droplets showed better stability than the PoP-coated droplets via a Pickering-like mechanism. Strikingly, the Pickering LC droplets outperformed PoP-stabilized droplets in terms of dynamic response with 5× lower detection limit to model chemical analytes (sodium dodecyl sulphate, SDS) due to the difference in SDS-binding features between the protein and the microgel. To eliminate the effect of size polydispersity on the response, monodisperse Pickering LC droplets of diameter ∼16 µm were additionally obtained using microfluidics, which mirrored the response to chemical as well as biological analytes, i.e., primary bile acid, an important biomarker of liver diseases. We demonstrate that these eco-friendly microgels used for creating monodisperse, ultra-stable, LC complex colloids are powerful templates for fabricating next generation, sustainable optical sensors for early diagnosis in clinical settings and other sensing applications.

Frictional behaviour of plant proteins in soft contacts: unveiling nanoscale mechanisms.

Despite the significance of nanotribology in the design of functional biomaterials, little is known about nanoscale friction in the presence of protein-coated soft contact surfaces. Here, we report a detailed investigation of frictional behaviour of sustainable plant proteins at the nanoscale for the first time, using deformable bio-relevant surfaces that achieve biologically relevant contact pressures. A combination of atomic force microscopy, quartz crystal microbalance with dissipation monitoring, and friction force microscopy with soft polydimethylsiloxane (PDMS, 150 kPa) surfaces was employed to elucidate the frictional properties of model plant proteins, i.e. lupine, pea, and potato proteins at the nanoscale while systematically varying the pH and ionic strength. Interactions of these plant proteins with purified mucins were also probed. We provide the much-needed direct experimental evidence that the main factor dictating the frictional properties of plant proteins is their affinity towards the surface, followed by the degree of protein film hydration. Proteins with high surface affinity, such as pea and potato protein, have better lubricating performance than lupine at the nanoscale. Other minor factors that drive lubrication are surface interactions between sliding bodies, especially at low load, whilst jamming of the contact area caused by larger protein aggregates increases friction. Novel findings reveal that interactions between plant proteins and mucins lead to superior lubricating properties, by combining high surface affinity from the plant proteins and high hydration by mucins. We anticipate that fundamental understanding gained from this work will set the stage for the design of a plethora of sustainable biomaterials and food with optimum nanolubrication performance.

Insights into the Multiscale Lubrication Mechanism of Edible Phase Change Materials.

Investigation of a lubrication behavior of phase change materials (PCM) can be challenging in applications involving relative motion, e.g., sport (ice skating), food (chocolates), energy (thermal storage), apparel (textiles with PCM), etc. In oral tribology, a phase change often occurs in a sequence of dynamic interactions between the ingested PCM and oral surfaces from a licking stage to a saliva-mixed stage at contact scales spanning micro- (cellular), meso- (papillae), and macroscales. Often the lubrication performance and correlations across length scales and different stages remain poorly understood due to the lack of testing setups mimicking real human tissues. Herein, we bring new insights into lubrication mechanisms of PCM using dark chocolate as an exemplar at a single-papilla (meso)-scale and a full-tongue (macro) scale covering the solid, molten, and saliva-mixed states, uniting highly sophisticated biomimetic oral surfaces with in situ tribomicroscopy for the first time. Unprecedented results from this study supported by transcending lubrication theories reveal how the tribological mechanism in licking shifted from solid fat-dominated lubrication (saliva-poor regime) to aqueous lubrication (saliva-dominant regime), the latter resulted in increasing the coefficient of friction by at least threefold. At the mesoscale, the governing mechanisms were bridging of cocoa butter in between confined cocoa particles and fat coalescence of emulsion droplets for the molten and saliva-mixed states, respectively. At the macroscale, a distinctive hydrodynamic viscous film formed at the interface governing the speed-dependent lubrication behavior indicates the striking importance of multiscale analyses. New tribological insights across different stages and scales of phase transition from this study will inspire rational design of the next generation of PCM and solid particle-containing materials.

Few-shot deep learning for AFM force curve characterization of single-molecule interactions.

Deep learning (DL)-based analytics has the scope to transform the field of atomic force microscopy (AFM) with regard to fast and bias-free measurement characterization. For example, AFM force-distance curves can help estimate important parameters of binding kinetics, such as the most probable rupture force, binding probability, association, and dissociation constants, as well as receptor density on live cells. Other than the ideal single-rupture event in the force-distance curves, there can be no-rupture, double-rupture, or multiple-rupture events. The current practice is to go through such datasets manually, which can be extremely tedious work for the experimentalists. We address this issue by adopting a few-shot learning approach to build sample-efficient DL models that demonstrate better performance than shallow ML models while matching the performance of moderately trained humans. We also release our AFM force curve dataset and annotations publicly as a benchmark for the research community.

Deep Learning for Live Cell Shape Detection and Automated AFM Navigation.

Atomic force microscopy (AFM) provides a platform for high-resolution topographical imaging and the mechanical characterization of a wide range of samples, including live cells, proteins, and other biomolecules. AFM is also instrumental for measuring interaction forces and binding kinetics for protein-protein or receptor-ligand interactions on live cells at a single-molecule level. However, performing force measurements and high-resolution imaging with AFM and data analytics are time-consuming and require special skill sets and continuous human supervision. Recently, researchers have explored the applications of artificial intelligence (AI) and deep learning (DL) in the bioimaging field. However, the applications of AI to AFM operations for live-cell characterization are little-known. In this work, we implemented a DL framework to perform automatic sample selection based on the cell shape for AFM probe navigation during AFM biomechanical mapping. We also established a closed-loop scanner trajectory control for measuring multiple cell samples at high speed for automated navigation. With this, we achieved a 60× speed-up in AFM navigation and reduced the time involved in searching for the particular cell shape in a large sample. Our innovation directly applies to many bio-AFM applications with AI-guided intelligent automation through image data analysis together with smart navigation.

Arsenite toxicity is regulated by queuine availability and oxidation-induced reprogramming of the human tRNA epitranscriptome.

Cells respond to environmental stress by regulating gene expression at the level of both transcription and translation. The ∼50 modified ribonucleotides of the human epitranscriptome contribute to the latter, with mounting evidence that dynamic regulation of transfer RNA (tRNA) wobble modifications leads to selective translation of stress response proteins from codon-biased genes. Here we show that the response of human hepatocellular carcinoma cells to arsenite exposure is regulated by the availability of queuine, a micronutrient and essential precursor to the wobble modification queuosine (Q) on tRNAs reading GUN codons. Among oxidizing and alkylating agents at equitoxic concentrations, arsenite exposure caused an oxidant-specific increase in Q that correlated with up-regulation of proteins from codon-biased genes involved in energy metabolism. Limiting queuine increased arsenite-induced cell death, altered translation, increased reactive oxygen species levels, and caused mitochondrial dysfunction. In addition to demonstrating an epitranscriptomic facet of arsenite toxicity and response, our results highlight the links between environmental exposures, stress tolerance, RNA modifications, and micronutrients.

Microfluidic chip grafted with integrin tension sensors for evaluating the effects of flowing shear stress and ROCK inhibitor on platelets.

Integrins are key players in platelet adhesion and aggregation. Integrin molecular tensions, the forces transmitted by integrin molecules, are regulated by both mechanical and biochemical cues, and the outside-in and inside-out signaling has been extensively studied. While the mechanical properties of platelets at static status have been studied by atomic force microscopy, traction force microscopy and tension sensors, the biomechanical properties of flowing platelets remain elusive. Herein, we report microfluidic chips grafted with integrin tension sensors for microfluidic-force mapping in platelets. Specifically, the process of integrin αIIbß3 mediating tension transmission and platelet adhesion under low flow rates has been obtained, and the process of platelet clustering at post-stenotic regions has been demonstrated. We found that flowing shear force can postpone the integrin-mediated tension transmission and platelet adhesion. We further evaluated the effect of Y-27632, a ROCK inhibitor that has been proven to reduce integrin-mediated platelet adhesion, at a series of concentrations and demonstrated that microfluidic chips with integrin tension sensors are sensitive to the concentration-dependent effects of Y-27632. Given their low cost and scalable throughput, these chips are ideal technical platforms for biological studies of platelets at flowing status and for platelet inhibitor or potential antiplatelet drug screening.

Digital dynamic discrimination of primary colorectal cancer using systemic indocyanine green with near-infrared endoscopy.

As indocyanine green (ICG) with near-infrared (NIR) endoscopy enhances real-time intraoperative tissue microperfusion appreciation, it may also dynamically reveal neoplasia distinctively from normal tissue especially with video software fluorescence analysis. Colorectal tumours of patients were imaged mucosally following ICG administration (0.25 mg/kg i.v.) using an endo-laparoscopic NIR system (PINPOINT Endoscopic Fluorescence System, Stryker) including immediate, continuous in situ visualization of rectal lesions transanally for up to 20 min. Spot and dynamic temporal fluorescence intensities (FI) were quantified using ImageJ (including videos at one frame/second, fps) and by a bespoke MATLAB® application that provided digitalized video tracking and signal logging at 30fps (Fluorescence Tracker App downloadable via MATLAB® file exchange). Statistical analysis of FI-time plots compared tumours (benign and malignant) against control during FI curve rise, peak and decline from apex. Early kinetic FI signal measurement delineated discriminative temporal signatures from tumours (n = 20, 9 cancers) offering rich data for analysis versus delayed spot measurement (n = 10 cancers). Malignant lesion dynamic curves peaked significantly later with a shallower gradient than normal tissue while benign lesions showed significantly greater and faster intensity drop from apex versus cancer. Automated tracker quantification efficiently expanded manual results and provided algorithmic KNN clustering. Photobleaching appeared clinically irrelevant. Analysis of a continuous stream of intraoperatively acquired early ICG fluorescence data can act as an in situ tumour-identifier with greater detail than later snapshot observation alone. Software quantification of such kinetic signatures may distinguish invasive from non-invasive neoplasia with potential for real-time in silico diagnosis.

Effects of oral lubrication on satiety, satiation and salivary biomarkers in model foods: A pilot study.

With a dramatic increase in overweight and population with obesity over the last decades, there is an imminent need to tackle this issue using novel strategies. Addressing obesity issues by generating satiety in food to reduce energy intake has been one of those prominent strategies and often textural interventions have been used to generate satiety, specifically in short-term trials. This study aimed to investigate the role of preloads varying in their oral lubricating properties on appetite sensations, food intake, salivary friction and concentration of salivary biomarkers (proteins, α-amylase and mucins) in collected human saliva (n = 17 healthy participants). The preloads were model foods (flavoured hydrogels) either high or low in their lubricating properties, assessed both by instrumental and sensorial measurements. The results showed that hunger and desire to eat decreased immediately after preload and remained decreased for 10 and 20 min, respectively, after preload in the high lubricating condition compared to control (all p < 0.05). Fullness increased immediately after preload and remained increased for 10 and 20 min, respectively, after preload in high lubricating condition compared to control (p < 0.05). However, after controlling the values for baseline, such significant effect of the intervention did not exist anymore. Only the effect of time is observed. Consuming high lubricating hydrogels showed no effect on food intake and salivary biomarkers in this pilot study. Salivary lubrication correlated with feeling of fullness. Considering the issue of large time-interval (30 min) between preload and next meal in this study, it is worthwhile investigating the immediate effects of oral lubrication on appetite control, food intake and salivary biomarkers.

Detecting the epitranscriptome.

RNA modifications and their corresponding epitranscriptomic writer and eraser enzymes regulate gene expression. Altered RNA modification levels, dysregulated writers, and sequence changes that disrupt epitranscriptomic marks have been linked to mitochondrial and neurological diseases, cancer, and multifactorial disorders. The detection of epitranscriptomics marks is challenging, but different next generation sequencing (NGS)-based and mass spectrometry-based approaches have been used to identify and quantitate the levels of individual and groups of RNA modifications. NGS and mass spectrometry-based approaches have been coupled with chemical, antibody or enzymatic methodologies to identify modifications in most RNA species, mapped sequence contexts and demonstrated the dynamics of specific RNA modifications, as well as the collective epitranscriptome. While epitranscriptomic analysis is currently limited to basic research applications, specific approaches for the detection of individual RNA modifications and the epitranscriptome have potential biomarker applications in detecting human conditions and diseases. This article is categorized under: RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems RNA Processing > tRNA Processing RNA in Disease and Development > RNA in Disease.