Expression of microRNA-223 and microRNA-214 in gingival crevicular fluid of smoker and nonsmoker periodontitis patients, an observational diagnostic accuracy study.

OBJECTIVE: Periodontitis is a multifactorial disease that affects a wide range of populations. However, its pathogenesis remains unclear. miRNAs are now considered potential diagnostic markers for many inflammatory diseases. Thus, the aim of this study was to assess the expression of microRNA-223(miRNA-223) and microRNA-214 (miRNA-214) in gingival crevicular fluid (GCF) of smoker and nonsmoker with periodontitis. MATERIALS AND METHODS: We conducted a prospective study among 42 participants: 14 healthy controls, 14 nonsmoker periodontitis participants, and 14 smokers with periodontitis. Eligibility criteria for inclusion were consecutive adults, aged 20-60 years, with stage III periodontitis grade B/C and no systemic diseases. All consenting participants had gingival crevicular fluid samples collected after diagnosis to assess miRNA-214 and -223 by quantitative real-time polymerase chain reaction assay. RESULTS: ROC curve analyses for the non-smoker periodontitis group showed that miR-214 as a predictor in comparison to miR-223 had higher sensitivity [92.86%-64.29%], same specificity [100%], and a significantly higher area under the curve [0.974-0.796] respectively (p = 0.036). As for the smoker periodontitis group, a ROC curve with miR-214 as predictor in comparison to miR-223 had higher sensitivity [100%-71.43%], same specificity [100%], and a non-significantly higher area under the curve [1-0.872], respectively (p = 0.059). CONCLUSION: Both miRNA-214 and 223 are reliable potential diagnostic markers for periodontitis, with miRNA-214 being more accurate for smokers with periodontitis. CLINICAL RELEVANCE: Both miRNA-214 and 223 could be considered for potential chair-side diagnostics, by simply collecting GCF detecting the disease in its first steps and aid in preventing unrepairable damage.

Extracellular vesicles carry transcriptional 'dark matter' revealing tissue-specific information.

From eukaryotes to prokaryotes, all cells secrete extracellular vesicles (EVs) as part of their regular homeostasis, intercellular communication, and cargo disposal. Accumulating evidence suggests that small EVs carry functional small RNAs, potentially serving as extracellular messengers and liquid-biopsy markers. Yet, the complete transcriptomic landscape of EV-associated small RNAs during disease progression is poorly delineated due to critical limitations including the protocols used for sequencing, suboptimal alignment of short reads (20-50 nt), and uncharacterized genome annotations-often denoted as the 'dark matter' of the genome. In this study, we investigate the EV-associated small unannotated RNAs that arise from endogenous genes and are part of the genomic 'dark matter', which may play a key emerging role in regulating gene expression and translational mechanisms. To address this, we created a distinct small RNAseq dataset from human prostate cancer & benign tissues, and EVs derived from blood (pre- & post-prostatectomy), urine, and human prostate carcinoma epithelial cell line. We then developed an unsupervised data-based bioinformatic pipeline that recognizes biologically relevant transcriptional signals irrespective of their genomic annotation. Using this approach, we discovered distinct EV-RNA expression patterns emerging from the un-annotated genomic regions (UGRs) of the transcriptomes associated with tissue-specific phenotypes. We have named these novel EV-associated small RNAs as 'EV-UGRs' or "EV-dark matter". Here, we demonstrate that EV-UGR gene expressions are downregulated by ∼100 fold (FDR < 0.05) in the circulating serum EVs from aggressive prostate cancer subjects. Remarkably, these EV-UGRs expression signatures were regained (upregulated) after radical prostatectomy in the same follow-up patients. Finally, we developed a stem-loop RT-qPCR assay that validated prostate cancer-specific EV-UGRs for selective fluid-based diagnostics. Overall, using an unsupervised data driven approach, we investigate the 'dark matter' of EV-transcriptome and demonstrate that EV-UGRs carry tissue-specific Information that significantly alters pre- and post-prostatectomy in the prostate cancer patients. Although further validation in randomized clinical trials is required, this new class of EV-RNAs hold promise in liquid-biopsy by avoiding highly invasive biopsy procedures in prostate cancer.

Biosynthesis of copper nanoclusters for fluorescence detection of bilirubin in biofluids.

Copper nanoclusters (Cu NCs) have shown significant attention in sensing of molecular and ionic species. In this work, a single-step biosynthetic approach was introduced for the preparation of fluorescent Cu NCs using Holarrhena pubescens (H. pubescens) leaves extract as a template. The synthesized H. pubescens-Cu NCs act as a nanomolecular probe for the detection of bilirubin in biofluids. The synthesized H. pubescens-Cu NCs displayed highest fluorescence intensity at 454 nm, when excited at 330 nm. Importantly, selective detection of bilirubin was obtained by introducing H. pubescens-Cu NCs as a simple molecular probe. The interaction of bilirubin and H. pubescens-Cu NCs resulted in a remarkable decrease in the emission peak intensity. The developed H. pubescens-Cu NCs-based bilirubin molecular probe has a wide linear range of 0.5-20.00 µM with the limit of detection of 30.54 nM for bilirubin. The promising application of H. pubescens-Cu NCs-based molecular probe was assessed by assaying bilirubin in spiked biofluids.

Rapid nanomolar detection of cocaine in biofluids by electrochemical aptamer-based sensor with low-temperature effect for drugged driving screening.

Cocaine is one of the most abused illicit drugs, and its abuse damages the central nervous system and can even lead directly to death. Therefore, the development of simple, rapid and highly sensitive detection methods is crucial for the prevention and control of drug abuse, traffic accidents and crime. In this work, an electrochemical aptamer-based (EAB) sensor based on the low-temperature enhancement effect was developed for the direct determination of cocaine in bio-samples. The signal gain of the sensor at 10 °C was greatly improved compared to room temperature, owing to the improved affinity between the aptamer and the target. Additionally, the electroactive area of the gold electrode used to fabricate the EAB sensor was increased 20 times by a simple electrochemical roughening method. The porous electrode possesses more efficient electron transfer and better antifouling properties after roughening. These improvements enabled the sensor to achieve rapid detection of cocaine in complex bio-samples. The low detection limits (LOD) of cocaine in undiluted urine, 50% serum and 50% saliva were 70 nM, 30 nM and 10 nM, respectively, which are below the concentration threshold in drugged driving screening. The aptasensor was simple to construct and reusable, which offers potential for drugged driving screening in the real world.

Biofluid specific protein coronas affect lipid nanoparticle behavior in vitro.

Lipid nanoparticles (LNPs) have successfully entered the clinic for the delivery of mRNA- and siRNA-based therapeutics, most recently as vaccines for COVID-19. Nevertheless, there is a lack of understanding regarding their in vivo behavior, in particular cell targeting. Part of this LNP tropism is based on the adherence of endogenous protein to the particle surface. This protein forms a so-called corona that can change, amongst other things, the circulation time, biodistribution and cellular uptake of these particles. The formation of this protein corona, in turn, is dependent on the nanoparticle properties (e.g., size, charge, surface chemistry and hydrophobicity) as well as the biological environment from which it is derived. With the potential of gene therapy to target virtually any disease, administration sites other than intravenous route are considered, resulting in tissue specific protein coronas. For neurological diseases, intracranial administration of LNPs results in a cerebral spinal fluid derived protein corona, possibly changing the properties of the lipid nanoparticle compared to intravenous administration. Here, the differences between plasma and CSF derived protein coronas on a clinically relevant LNP formulation were studied in vitro. Protein analysis showed that LNPs incubated in human CSF (C-LNPs) developed a protein corona composition that differed from that of LNPs incubated in plasma (P-LNPs). Lipoproteins as a whole, but in particular apolipoprotein E, represented a higher percentage of the total protein corona on C-LNPs than on P-LNPs. This resulted in improved cellular uptake of C-LNPs compared to P-LNPs, regardless of cell origin. Importantly, the higher LNP uptake did not directly translate into more efficient cargo delivery, underlining that further assessment of such mechanisms is necessary. These findings show that biofluid specific protein coronas alter LNP functionality, suggesting that the site of administration could affect LNP efficacy in vivo and needs to be considered during the development of the formulation.

Developing a label-free full-range highly selective pH nanobiosensor using a novel high quantum yield pH-responsive activated-protein-protected gold nanocluster prepared by a novel ultrasonication-protein-assisted procedure.

A novel, label-free, ultra-selective, reproducible, and reversible pH nanobiosensor was developed for analyzing biofluids, food samples, and real water media utilizing a novel activated-protein-protected gold nanocluster with an ultra-narrow emission band, termed as ABSA-AuNCs. The ABSA-AuNCs were synthesized via a novel ultrasonication-protein-assisted procedure, for the first time, using activated bovine serum albumin as both capping and reducing agents. The ABSA-AuNCs revealed a highly narrow symmetric emission spectrum (λmax = 330.0 nm upon excitation at 312-317 nm), and a highly narrow size distribution of 2.9-3.7 nm along with an enhanced quantum yield of 28.3 %. At present, with a full width at half maximum (FWHM) of 14.0 nm, ABSA-AuNCs have the narrowest bandwidth of fluorescent nanomaterials reported to date. The ABSA-AuNCs were characterized for their stability, size, morphology, crystallinity, structural, and optical properties. The ABSA-AuNCs were found to be appropriate for constructing a label-free ultraselective pH nanobiosensor. A linear range over 2.0-11.0, fast response time of less than 5 s, and long-term stability of 99.7 % after 500 min were achieved. The %RSD for repeatability, intra-day reproducibility, and inter-day reproducibility was found to be 1.4 %, 1.7 %, and 2.3 %, in order, to reveal high repeatable and reproducible results. The selectivity of the pH biosensor was evaluated upon the addition of different interferents, indicating an excellent pH selectivity for the ABSA-AuNCs. Real sample analysis proved the feasibility of the ABSA-AuNCs for accurate, precise, and reliable pH sensing in biofluids (undiluted blood and urine), a variety of food samples, and several real water samples.

On the efficacy of facial masks to suppress the spreading of pathogen-carrying saliva particles during human respiratory events: Insights gained via high-fidelity numerical modeling.

Respiratory fluid dynamics is integral to comprehending the transmission of infectious diseases and the effectiveness of interventions such as face masks and social distancing. In this research, we present our recent studies that investigate respiratory particle transport via high-fidelity large eddy simulation coupled with the Lagrangian particle tracking method. Based on our numerical simulation results for human respiratory events with and without face masks, we demonstrate that facial masks could significantly suppress particle spreading. The studied respiratory events include coughing and normal breathing through mouth and nose. Using the Lagrangian particle tracking simulation results, we elucidated the transport pathways of saliva particles during inhalation and exhalation of breathing cycles, contributing to our understanding of respiratory physiology and potential disease transmission routes. Our findings underscore the importance of respiratory fluid dynamics research in informing public health strategies to reduce the spread of respiratory infections. Combining advanced mathematical modeling techniques with experimental data will help future research on airborne disease transmission dynamics and the effectiveness of preventive measures such as face masks.

When surface-enhanced Raman spectroscopy meets complex biofluids: A new representation strategy for reliable and comprehensive characterization.

BACKGROUND: Surface-enhanced Raman spectroscopy (SERS) has gained increasing importance in molecular detection due to its high specificity and sensitivity. Complex biofluids (e.g., cell lysates and serums) typically contain large numbers of different bio-molecules with various concentrations, making it extremely challenging to be reliably and comprehensively characterized via conventional single SERS spectra due to uncontrollable electromagnetic hot spots and irregular molecular motions. The traditional approach of directly reading out the single SERS spectra or calculating the average of multiple spectra is less likely to take advantage of the full information of complex biofluid systems. RESULTS: Herein, we propose to construct a spectral set with unordered multiple SERS spectra as a novel representation strategy to characterize full molecular information of complex biofluids. This new SERS representation not only contains details from each single spectra but captures the temporal/spatial distribution characteristics. To address the ordering-independent property of traditional chemometric methods (e.g., the Euclidean distance and the Pearson correlation coefficient), we introduce Wasserstein distance (WD) to quantitatively and comprehensively assess the quality of spectral sets on biofluids. WD performs its superiority for the quantitative assessment of the spectral sets. Additionally, WD benefits from its independence of the ordering of spectra in a spectral set, which is undesirable for traditional chemometric methods. With experiments on cell lysates and human serums, we successfully achieve the verification for the reproducibility between parallel samples, the uniformity at different positions in the same sample, the repeatability from multiple tests at one location of the same sample, and the cardinality effect of the spectral set. SERS spectral sets also manage to distinguish different classes of human serums and achieve higher accuracy than the traditional prostate-specific antigen in prostate cancer classification. SIGNIFICANCE: The proposed SERS spectral set is a robust representation approach in accessing full information of biological samples compared to relying on a single or averaged spectra in terms of reproducibility, uniformity, repeatability, and cardinality effect. The application of WD further demonstrates the effectiveness and robustness of spectral sets in characterizing complex biofluid samples, which extends and consolidates the role of SERS.

Frontiers in plasma proteome profiling platforms: innovations and applications.

Biomarkers play a crucial role in advancing precision medicine by enabling more targeted and individualized approaches to diagnosis and treatment. Various biofluids, including serum, plasma, cerebrospinal fluid (CSF), saliva, tears, pancreatic cyst fluids, and urine, have been identified as rich sources of potential for the early detection of disease biomarkers in conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders. The analysis of plasma and serum in proteomics research encounters challenges due to their high complexity and the wide dynamic range of protein abundance. These factors impede the sensitivity, coverage, and precision of protein detection when employing mass spectrometry, a widely utilized technology in discovery proteomics. Conventional approaches such as Neat Plasma workflow are inefficient in accurately quantifying low-abundant proteins, including those associated with tissue leakage, immune response molecules, interleukins, cytokines, and interferons. Moreover, the manual nature of the workflow poses a significant hurdle in conducting large cohort studies. In this study, our focus is on comparing workflows for plasma proteomic profiling to establish a methodology that is not only sensitive and reproducible but also applicable for large cohort studies in biomarker discovery. Our investigation revealed that the Proteograph XT workflow outperforms other workflows in terms of plasma proteome depth, quantitative accuracy, and reproducibility while offering complete automation of sample preparation. Notably, Proteograph XT demonstrates versatility by applying it to various types of biofluids. Additionally, the proteins quantified widely cover secretory proteins in peripheral blood, and the pathway analysis enriched with relevant components such as interleukins, tissue necrosis factors, chemokines, and B and T cell receptors provides valuable insights. These proteins, often challenging to quantify in complex biological samples, hold potential as early detection markers for various diseases, thereby contributing to the improvement of patient care quality.

Applications of Raman spectroscopy in ocular biofluid detection.

Ophthalmic and many systemic diseases may damage the eyes, resulting in changes in the composition and content of biomolecules in ocular biofluids such as aqueous humor and tear. Therefore, the biomolecules in biofluids are potential biomarkers to reveal pathological processes and diagnose diseases. Raman spectroscopy is a non-invasive, label-free, and cost-effective technique to provide chemical bond information of biomolecules and shows great potential in the detection of ocular biofluids. This review demonstrates the applications of Raman spectroscopy technology in detecting biochemical components in aqueous humor and tear, then summarizes the current problems encountered for clinical applications of Raman spectroscopy and looks forward to possible approaches to overcome technical bottlenecks. This work may provide a reference for wider applications of Raman spectroscopy in biofluid detection and inspire new ideas for the diagnosis of diseases using ocular biofluids.

Higher Concentrations of Essential Trace Elements in Women Undergoing IVF May Be Associated with Poor Reproductive Outcomes Following Single Euploid Embryo Transfer.

Essential trace elements are micronutrients whose deficiency has been associated with altered fertility and/or adverse pregnancy outcomes, while surplus may be toxic. The concentrations of eight essential trace elements were measured using inductively coupled mass spectrometry (ICP-MS) and assessed with respect to clinical in vitro fertilization (IVF) outcomes in a population of 51 women undergoing IVF with intracytoplasmic sperm injection (ICSI), pre-implantation genetic screening for aneuploidy (PGT-A), and single frozen euploid embryo transfer (SET/FET). Specifically, copper (Cu), zinc (Zn), molybdenum, selenium, lithium, iron, chromium, and manganese were quantified in follicular fluid and whole blood collected the day of vaginal oocyte retrieval (VOR) and in urine collected the day of VOR and embryo transfer. We found that the whole blood Cu/Zn ratio was significantly associated with superior responses to ovarian stimulation. Conversely, the whole blood zinc and selenium concentrations were significantly associated with poor ovarian response outcomes. Higher levels of whole blood zinc and selenium, urinary selenium, lithium, and iron had significant negative associations with embryologic outcomes following IVF. Regarding clinical IVF outcomes, higher urinary molybdenum concentrations the day of VOR were associated with significantly lower odds of implantation and live birth, while higher urinary Cu/Mo ratios on the day of VOR were associated with significantly higher odds of implantation, clinical pregnancy, and live birth. Our results suggest that essential trace element levels may directly influence the IVF outcomes of Spanish patients, with selenium and molybdenum exerting negative effects and copper-related ratios exerting positive effects. Additional studies are warranted to confirm these relationships in other human populations.

Direct comparison of different protocols to obtain surface enhanced Raman spectra of human serum.

Label-free Surface Enhanced Raman Spectroscopy (SERS) is a rapid technique that has been extensively applied in clinical diagnosis and biomedicine for the analysis of biofluids. The purpose of this approach relies on the ability to detect specific "metabolic fingerprints" of complex biological samples, but the full potential of this technique in diagnostics is yet to be exploited, mainly because of the lack of common analytical protocols for sample preparation and analysis. Variation of experimental parameters, such as substrate type, laser wavelength and sample processing can greatly influence spectral patterns, making results from different research groups difficult to compare. This study aims at making a step toward a standardization of the protocols in the analysis of human serum samples with Ag nanoparticles, by directly comparing the SERS spectra obtained from five different methods in which parameters like laser power, nanoparticle concentration, incubation/deproteinization steps and type of substrate used vary. Two protocols are the most used in the literature, and the other three are "in-house" protocols proposed by our group; all of them are employed to analyze the same human serum sample. The experimental results show that all protocols yield spectra that share the same overall spectral pattern, conveying the same biochemical information, but they significantly differ in terms of overall spectral intensity, repeatability, and preparation steps of the sample. A Principal Component Analysis (PCA) was performed revealing that protocol 3 and protocol 1 have the least variability in the dataset, while protocol 2 and 4 are the least repeatable.

Optimization and validation of metabolomics methods for feline urine and serum towards application in veterinary medicine.

BACKGROUND: Metabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed. RESULTS: Systematic optimization was performed using fractional factorial experiments for both serum (n = 57) and urine (n = 24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n = 76) and untargeted (n = 1949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV ≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2 ≥ 0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n = 69) and untargeted (n = 2348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV ≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n = 41 significant metabolites for serum, and n = 55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y) > 0.95, Q2(Y) > 0.65, p-value<0.001 for both matrices). SIGNIFICANCE: This study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.

Recent advancements in non-invasive wearable electrochemical biosensors for biomarker analysis - A review.

A biomarker is a molecular indicator that can be used to identify the presence or severity of a disease. It may be produced due to biochemical or molecular changes in normal biological processes. In some cases, the presence of a biomarker itself is an indication of the disease, while in other cases, the elevated or depleted level of a particular protein or chemical substance aids in identifying a disease. Biomarkers indicate the progression of the disease in response to therapeutic interventions. Identifying these biomarkers can assist in diagnosing the disease early and providing proper therapeutic treatment. In recent years, wearable electrochemical (EC) biosensors have emerged as an important tool for early detection due to their excellent selectivity, low cost, ease of fabrication, and improved sensitivity. There are several challenges in developing a fully integrated wearable sensor, such as device miniaturization, high power consumption, incorporation of a power source, and maintaining the integrity and durability of the biomarker for long-term continuous monitoring. This review covers the recent advancements in the fabrication techniques involved in device development, the types of sensing platforms utilized, different materials used, challenges, and future developments in the field of wearable biosensors.

Sensing patches for biomarker identification in skin-derived biofluids.

In conventional clinical disease diagnosis and screening based on biomarker detection, most analysis samples are collected from serum, blood. However, these invasive collection methods require specific instruments, professionals, and may lead to infection risks. Additionally, the diagnosis process suffers from untimely results. The identification of skin-related biomarkers plays an unprecedented role in early disease diagnosis. More importantly, these skin-mediated approaches for collecting biomarker-containing biofluid samples are noninvasive or minimally invasive, which is more preferable for point-of-care testing (POCT). Therefore, skin-based biomarker detection patches have been promoted, owing to their unique advantages, such as simple fabrication, desirable transdermal properties and no requirements for professional medical staff. Currently, the skin biomarkers extracted from sweat, interstitial fluid (ISF) and wound exudate, are achieved with wearable sweat patches, transdermal MN patches, and wound patches, respectively. In this review, we detail these three types of skin patches in biofluids collection and diseases-related biomarkers identification. Patch classification and the corresponding manufacturing as well as detection strategies are also summarized. The remaining challenges in clinical applications and current issues in accurate detection are discussed for further advancement of this technology (Scheme 1).

Frontiers in Plasma Proteome Profiling Platforms: Innovations and Applications.

Biomarkers play a crucial role in advancing precision medicine by enabling more targeted and individualized approaches to diagnosis and treatment. Various biofluids, including serum, plasma, cerebrospinal fluid (CSF), saliva, tears, pancreatic cyst fluids, and urine, have been identified as rich sources of potential for the early detection of disease biomarkers in conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders. The analysis of plasma and serum in proteomics research encounters challenges due to their high complexity and the wide dynamic range of protein abundance. These factors impede the sensitivity, coverage, and precision of protein detection when employing mass spectrometry, a widely utilized technology in discovery proteomics. Conventional approaches such as neat plasma workflow are inefficient in accurately quantifying low-abundant proteins, including those associated with tissue leakage, immune response molecules, interleukins, cytokines, and interferons. Moreover, the manual nature of the workflow poses a significant hurdle in conducting large cohort studies. In this study, our focus is on comparing workflows for plasma proteomic profiling to establish a methodology that is not only sensitive and reproducible but also applicable for large cohort studies in biomarker discovery. Our investigation revealed that the SeerProteographXT workflow outperforms other workflows in terms of plasma proteome depth, quantitative accuracy, and reproducibility while offering complete automation of sample preparation. Notably, SeerProteographXT demonstrates versatility by applying it to various types of biofluids. Additionally, the proteins quantified widely cover secretory proteins in peripheral blood, and the pathway analysis enriched with relevant components such as interleukins, tissue necrosis factors, chemokines, and B and T cell receptors provides valuable insights. These proteins, often challenging to quantify in complex biological samples, hold potential as early detection markers for various diseases, thereby contributing to the improvement of patient care quality.

Heat Transfer by Sweat Droplet Evaporation.

Sweating regulates the body temperature in extreme environments or during exercise. Here, we investigate the evaporative heat transfer of a sweat droplet at the microscale to unveil how the evaporation complexity of a sweat droplet would affect the body's ability to cool under specific environmental conditions. Our findings reveal that, depending on the relative humidity and temperature levels, sweat droplets experience imperfect evaporation dynamics, whereas water droplets evaporate perfectly at equivalent ambient conditions. At low humidity, the sweat droplet fully evaporates and leaves a solid deposit, while at high humidity, the droplet never reaches a solid deposit and maintains a liquid phase residue for both low and high temperatures. This unprecedented evaporation mechanism of a sweat droplet is attributed to the intricate physicochemical properties of sweat as a biofluid. We suppose that the sweat residue deposited on the surface by evaporation is continuously absorbing the surrounding moisture. This route leads to reduced evaporative heat transfer, increased heat index, and potential impairment of the body's thermoregulation capacity. The insights into the evaporative heat transfer dynamics at the microscale would help us to improve the knowledge of the body's natural cooling mechanism with practical applications in healthcare, materials science, and sports science.

A Viscous-Biofluid Self-Pumping Organohydrogel Dressing to Accelerate Diabetic Wound Healing.

Viscous biofluids on wounds challenge conventional "water-absorbing" wound dressings in efficient drainage due to their poor fluidity, generally causing prolonged inflammation, anti-angiogenesis, and delayed wound closure. Herein, it is reported that a self-pumping organohydrogel dressing (SPD) with aligned hydrated hydrogel channels, prepared by a three-dimensional-templated wetting-enabled-transfer (3D-WET) polymerization process, can efficiently drain viscous fluids and accelerate diabetic wound healing. The asymmetric wettability of the hydrophobic-hydrophilic layers and aligned hydrated hydrogel channels enable unidirectional and efficient drainage of viscous fluids away from the wounds, preventing their overhydration and inflammatory stimulation. The organogel layer can adhere onto the skin around the wounds but can be easily detached from the wet wound area, avoiding secondary trauma to the newly formed tissues. Taking a diabetic rat model as an example, the SPD can significantly downregulate the inflammation response by ≈70.8%, enhance the dermal remodeling by ≈14.3%, and shorten wound closure time by about 1/3 compared with the commercial dressing (3M, Tegaderm hydrocolloid thin dressing). This study sheds light on the development of the next generation of functional dressings for chronic wounds involving viscous biofluids.

Proteomics of prostate cancer serum and plasma using low and high throughput approaches.

Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.

Oxysterol sulfates in fluids, cells and tissues: how much do we know about their clinical significance, biological relevance and biophysical implications?

Oxysterol sulfates are emerging as key players in lipid homeostasis, inflammation and immunity. Despite this, knowledge on their basal levels in fluids, cells and tissues and any changes associated with age, gender and diet in health and disease; as well as their spatio-temporal distribution in cell membranes and organelles have been greatly hampered by the lack of commercially available pure synthetic standards. Expansion of the panel of pure oxysterol sulfates standards is pivotal to improve our understanding on the impact of oxysterol sulfates at the membrane level and their role in cellular events. While the clinical significance, biophysical implications and biological relevance of oxysterol sulfates in fluids, cells and tissues remains largely unknown, knowledge already gathered on the precursors of oxysterol sulfates (e.g. oxysterols and cholesterol sulfate) can be used to guide researchers on the most relevant aspects to search for when screening for oxysterol sulfates bioavailability in (patho)physiological conditions which are crucial in the design of biophysical and of cell-based assays. Herein, we provide a review on the brief knowledge involving oxysterol sulfate and an overview on the biophysical implications and biological relevance of oxysterols and cholesterol sulfate useful to redirect further investigations on the role of oxysterol sulfates in health and disease.