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Lipid nanoparticles (LNPs) have emerged as potent carriers for mRNA delivery, but several challenges remain before this approach can offer broad clinical translation of mRNA therapeutics. To improve their efficacy, a better understanding is required regarding how LNPs are trapped and processed at the anionic endosomal membrane prior to mRNA release. We used surface-sensitive fluorescence microscopy with single LNP resolution to investigate the pH dependency of the binding kinetics of ionizable lipid-containing LNPs to a supported endosomal model membrane. A sharp increase of LNP binding was observed when the pH was lowered from 6 to 5, accompanied by stepwise large-scale LNP disintegration. For LNPs preincubated in serum, protein corona formation shifted the onset of LNP binding and subsequent disintegration to lower pH, an effect that was less pronounced for lipoprotein-depleted serum. The LNP binding to the endosomal membrane mimic was observed to eventually become severely limited by suppression of the driving force for the formation of multivalent bonds during LNP attachment or, more specifically, by charge neutralization of anionic lipids in the model membrane due to their association with cationic lipids from earlier attached LNPs upon their disintegration. Cell uptake experiments demonstrated marginal differences in LNP uptake in untreated and lipoprotein-depleted serum, whereas lipoprotein-depleted serum increased mRNA-controlled protein (eGFP) production substantially. This complies with model membrane data and suggests that protein corona formation on the surface of the LNPs influences the nature of the interaction between LNPs and endosomal membranes.

Purpose: The quantitative percussion diagnostics (QPD) response of a mandibular second molar and a maxillary central incisor including their supporting ligament/bone structure was simulated using dynamic 3D finite element analysis (FEA). The focus of the work was on the role of the periodontal ligament (PDL) which acts as a damper in the dental structure and dissipates occlusal forces transmitted from the tooth surface to the surrounding bone. Methods: Several FEA models were developed to examine the effects of mechanical characteristics that have been reported for the PDL. Specifically, the effects of changing the PDL’s quasi-static elastic modulus and Rayleigh damping properties were predicted. Results: The present FEA simulations indicate that the PDL can significantly reduce forces for both the incisor and the molar compared to when there is no PDL (i.e. ankylosed tooth) as long as the quasi-static elastic modulus of the PDL is among the lowest reported (~ 0.1 MPa). In addition, the FEA simulations for both the incisor and molar with this lower value of the PDL quasi-static elastic modulus are also in reasonably good agreement with experimental percussion data. A simple approximation for partitioning Rayleigh damping properties between the hard and soft tissues was also found to provide reasonable values of overall damping that are consistent with experimental data. Conclusion: The overall findings indicate that using a quasi-static elastic modulus of approximately 0.1 MPa for the PDL in combination with Rayleigh damping gives realistic predictions of the mechanical response of a tooth under QPD loading conditions.

Inadequate molecular and clinical stratification of the patients with high-risk diffuse large B-cell lymphoma (DLBCL) is a clinical challenge hampering the establishment of personalized therapeutic options. We studied the translational significance of liquid biopsy in a uniformly treated trial cohort. Pretreatment circulating tumor DNA (ctDNA) revealed hidden clinical and biological heterogeneity, and high ctDNA burden determined increased risk of relapse and death independently of conventional risk factors. Genomic dissection of pretreatment ctDNA revealed translationally relevant phenotypic, molecular, and prognostic information that extended beyond diagnostic tissue biopsies. During therapy, chemorefractory lymphomas exhibited diverging ctDNA kinetics, whereas end-of-therapy negativity for minimal residual disease (MRD) characterized cured patients and resolved clinical enigmas, including false residual PET positivity. Furthermore, we discovered fragmentation disparities in the cell-free DNA that characterize lymphoma-derived ctDNA and, as a proof-of-concept for their clinical application, used machine learning to show that end-of-therapy fragmentation patterns predict outcome. Altogether, we have discovered novel molecular determinants in the liquid biopsy that can noninvasively guide treatment decisions.

In-depth understanding of the intricate interactions between biomolecules and nanoparticles is hampered by a lack of analytical methods providing quantitative information about binding kinetics. Herein, we demonstrate how label-free evanescent light-scattering microscopy can be used to temporally resolve specific protein binding to individual surface-bound (∼100 nm) lipid vesicles. A theoretical model is proposed that translates protein-induced changes in light-scattering intensity into bound mass. Since the analysis is centered on individual lipid vesicles, the signal from nonspecific protein binding to the surrounding surface is completely avoided, offering a key advantage over conventional surface-based techniques. Further, by averaging the intensities from less than 2000 lipid vesicles, the sensitivity is shown to increase by orders of magnitude. Taken together, these features provide a new avenue in studies of protein-nanoparticle interaction, in general, and specifically in the context of nanoparticles in medical diagnostics and drug delivery.

Advancements in nanoparticle characterization techniques are critical for improving the understanding of how biological nanoparticles (BNPs) contribute to different cellular processes, such as cellular communication, viral infection, as well as various drug-delivery applications. Since BNPs are intrinsically heterogeneous, there is a need for characterization methods that are capable of providing information about multiple parameters simultaneously, preferably at the single-nanoparticle level. In this work, fluorescence microscopy was combined with surface-based two-dimensional flow nanometry, allowing for simultaneous and independent determination of size and fluorescence emission of individual BNPs. In this way, the dependence of the fluorescence emission of the commonly used self-inserting lipophilic dye 3,3′-dioctadecyl-5,5′-di(4-sulfophenyl)oxacarbocyanine (SP-DiO) could successfully be correlated with nanoparticle size for different types of BNPs, including synthetic lipid vesicles, lipid vesicles derived from cellular membrane extracts, and extracellular vesicles derived from human SH-SY5Y cell cultures; all vesicles had a radius, r, of ∼50 nm and similar size distributions. The results demonstrate that the dependence of fluorescence emission of SP-DiO on nanoparticle size varies significantly between the different types of BNPs, with the expected dependence on membrane area, r2, being observed for synthetic lipid vesicles, while a significant weaker dependence on size was observed for BNPs with more complex composition. The latter observation is attributed to a size-dependent difference in membrane composition, which may influence either the optical properties of the dye and/or the insertion efficiency, indicating that the fluorescence emission of this type of self-inserting dye may not be reliable for determining size or size distribution of BNPs with complex lipid compositions.

We have designed and fabricated a microwell array chip (MWAC) to trap and detect the entire content of individual vesicles after disruption of the vesicular membrane by an applied electrical potential. To understand the mechanism of vesicle impact electrochemical cytometry (VIEC) in microwells, we simulated the rupture of the vesicles and subsequent diffusion of entrapped analytes. Two possibilities were tested: (i) the vesicle opens toward the electrode, and (ii) the vesicle opens away from the electrode. These two possibilities were simulated in the different microwells with varied depth and width. Experimental VIEC measurements of the number of molecules for each vesicle in the MWAC were compared to VIEC on a gold microdisk electrode as a control, and the quantified catecholamines between these two techniques was the same. We observed a prespike foot in a significant number of events (∼20%) and argue this supports the hypothesis that the vesicles rupture toward the electrode surface with a more complex mechanism including the formation of a stable pore intermediate. This study not only confirms that in standard VIEC experiments the whole content of the vesicle is oxidized and quantified at the surface of the microdisk electrode but actively verifies that the adsorbed vesicle on the surface of the electrode forms a pore in the vicinity of the electrode rather than away from it. The fabricated MWAC promotes our ability to quantify the content of vesicles accurately, which is fundamentally important in bioanalysis of the vesicles.

Extracellular vesicles (EVs) are generating a growing interest because of the key roles they play in various biological processes and because of their potential use as biomarkers in clinical diagnostics and as efficient carriers in drug-delivery and gene-therapy applications. Their full exploitation, however, depends critically on the possibility to classify them into different subpopulations, a task that in turn relies on efficient means to identify their unique biomolecular and physical signatures. Because of the large heterogeneity of EV samples, such information remains rather elusive, and there is accordingly a need for new and complementary characterization schemes that can help expand the library of distinct EV features. In this work, we used surface-sensitive waveguide scattering microscopy with single EV resolution to characterize two subsets of similarly sized EVs that were preseparated based on their difference in buoyant density. Unexpectedly, the scattering intensity distribution revealed that the scattering intensity of the high-density (HD) population was on an average a factor of three lower than that of the low-density (LD) population. By further labeling the EV samples with a self-inserting lipid-membrane dye, the scattering and fluorescence intensities from EVs could be simultaneously measured and correlated at the single-particle level. The labeled HD sample exhibited not only lower fluorescence and scattering intensities but also lower effective refractive index (n≈ 1.35) compared with the LD EVs (n≈ 1.38), indicating that both the lipid and protein contents were indeed lower in the HD EVs. Although separation in density gradients of similarly sized EVs is usually linked to differences in biomolecular content, we suggest based on these observations that the separation rather reflects the ability of the solute of the gradient to penetrate the lipid membrane enclosing the EVs, that is, the two gradient bands are more likely because of the differences in membrane permeability than to differences in biomolecular content of the EVs.

GPIHBP1, an endothelial cell protein, binds LPL in the interstitial spaces and shuttles it to its site of action inside blood vessels. For years, studies of human GPIHBP1 have been hampered by an absence of useful antibodies. We reasoned that monoclonal antibodies (mAbs) against human GPIHBP1 would be useful for 1) defining the functional relevance of GPIHBP1's Ly6 and acidic domains to the binding of LPL; 2) ascertaining whether human GPIHBP1 is expressed exclusively in capillary endothelial cells; and 3) testing whether GPIHBP1 is detectable in human plasma. Here, we report the development of a panel of human GPIHBP1-specific mAbs. Two mAbs against GPIHBP1's Ly6 domain, RE3 and RG3, abolished LPL binding, whereas an antibody against the acidic domain, RF4, did not. Also, mAbs RE3 and RG3 bound with reduced affinity to a mutant GPIHBP1 containing an Ly6 domain mutation (W109S) that abolishes LPL binding. Immunohistochemistry studies with the GPIHBP1 mAbs revealed that human GPIHBP1 is expressed only in capillary endothelial cells. Finally, we created an ELISA that detects GPIHBP1 in human plasma. That ELISA should make it possible for clinical lipidologists to determine whether plasma GPIHBP1 levels are a useful biomarker of metabolic or vascular disease

Multiple sclerosis (MS) is a disease in which we can recognize destruction of the myelin that is around nerve cells of brain and spinal cord called as oligodendrocytes. Both genetic and environmental factors play roles in MS. One of these genes is the killer-cell immunoglobulin-like receptor(KIR) which expressed on surface of natural killer cells (NKs). These genes have loci (not locus) in human genome, so they inherit as haplotypes. The results of previous studies show that different genes of KIRmay affect both susceptibility and resistance to such autoimmune disorders that their pathogenesis in MS is still unclear. Since NKs play key roles in immune tolerance, we intend to perform a meta-analysis for the correlation of KIRgenes and MS. We used the software comprehensive meta-analysis for data of totally 568 MS patients and 280 controls. Among the 14 genes of KIRin the human genome, lack of KIR2DS1is accompanied by MS. No KIRgene found to be a risk factor for MS. Further studies on other molecules of NKs like CD94 and NKG2a is suggested.

LPL contains two principal domains: an amino-terminal catalytic domain (residues 1–297) and a carboxyl-terminal domain (residues 298–448) that is important for binding lipids and binding glycosylphosphatidylinositol-anchored high density lipoprotein binding protein 1 (GPIHBP1) (an endothelial cell protein that shuttles LPL to the capillary lumen). The LPL sequences required for GPIHBP1 binding have not been examined in detail, but one study suggested that sequences near LPL's carboxyl terminus (residues ∼403–438) were crucial. Here, we tested the ability of LPL-specific monoclonal antibodies (mAbs) to block the binding of LPL to GPIHBP1. One antibody, 88B8, abolished LPL binding to GPIHBP1. Consistent with those results, antibody 88B8 could not bind to GPIHBP1-bound LPL on cultured cells. Antibody 88B8 bound poorly to LPL proteins with amino acid substitutions that interfered with GPIHBP1 binding (e.g., C418Y, E421K). However, the sequences near LPL's carboxyl terminus (residues ∼403–438) were not sufficient for 88B8 binding; upstream sequences (residues 298–400) were also required. Additional studies showed that these same sequences are required for LPL binding to GPIHBP1. In conclusion, we identified an LPL mAb that binds to LPL's GPIHBP1-binding domain. The binding of both antibody 88B8 and GPIHBP1 to LPL depends on large segments of LPL's carboxyl-terminal domain.

Advancement in the understanding of biomolecular interactions has benefited greatly from the development of surface-sensitive bioanalytical sensors. To further increase their broad impact, significant efforts are presently being made to enable label-free and specific biomolecule detection with high sensitivity, allowing for quantitative interpretation and general applicability at low cost. In this work, we have addressed this challenge by developing a waveguide chip consisting of a flat silica core embedded in a symmetric organic cladding with a refractive index matching that of water. This is shown to reduce stray light (background) scattering and thereby allow for label-free detection of faint objects, such as individual sub-20 nm gold nanoparticles as well as sub-100 nm lipid vesicles. Measurements and theoretical analysis revealed that light-scattering signals originating from single surface-bound lipid vesicles enable characterization of their sizes without employing fluorescent lipids as labels. The concept is also demonstrated for label-free measurements of protein binding to and enzymatic (phospholipase A2) digestion of individual lipid vesicles, enabling an analysis of the influence on the measured kinetics of the dye-labeling of lipids required in previous assays. Further, diffraction-limited imaging of cells (platelets) binding to a silica surface showed that distinct subcellular features could be visualized and temporally resolved during attachment, activation, and spreading. Taken together, these results underscore the versatility and general applicability of the method, which due to its simplicity and compatibility with conventional microscopy setups may reach a widespread in life science and beyond.

Prevalence of Superficial Fungal Infection in Primary School Children in Ahvaz, IranBackground:Superficial fungal infections are common in schoolchildren. Superficial fungal diseases such as dermatophytosis and pityriasis versicolor, although not life-threatening, may be particularly distressing for this age group.Objective:The objectives of this study were to determine the prevalence, clinical types, and causative agents of superficial fungal infections among primary school children in Ahvaz, Iran.Methods:A total of 2827 randomly selected primary school pupils (aged 6-12) from 14 schools were examined for superficial fungal infections by direct microscopy and culture based laboratory diagnosed methods.Results:Generally, 13 (0.4%) persons had infections. Out of these, 8 (61.5 %) were male while 5 (38.5%) were female. Seborrheic dermatitis (0.21%) was the most common infection, followed by pityriais veriscolor (0.18%) and tinea capitis (0.07%). The etiological agents of tinea capitis were identified Microsporum canis.Pityriasis versicolor was occurred only on the neck (100%). Seborrheic dermatitis was occurred among 9-to10-years-old pupils.Conclusion:Our data provide a valuable baseline on which to assess future efforts directed toward the prevention of dermatophytes infections in our epidemiological.

Metabolomics is a mainstream approach for investigating the metabolic underpinnings of complex biological phenomena and is increasingly being applied to large-scale studies involving hundreds or thousands of samples. Although metabolomics methods are robust in smaller-scale studies, they can be challenging to apply to larger cohorts due to the inherent variability of liquid chromatography mass spectrometry (LC-MS). Much of this difficulty results from the time-dependent changes in the LC-MS system, which affects both the qualitative and quantitative performances of the instrument. Herein, we introduce an analytical strategy for addressing this problem in large-scale microbial studies. Our approach quantifies microbial boundary fluxes using two zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) columns that are plumbed to enable offline column equilibration. Using this strategy, we show that over 397 common metabolites can be resolved in 4.5 min per sample and that metabolites can be quantified with a median coefficient of variation of 0.127 across 1100 technical replicates. We illustrate the utility of this strategy via an analysis of 960 strains of Staphylococcus aureusisolated from bloodstream infections. These data capture the diversity of metabolic phenotypes observed in clinical isolates and provide an example of how large-scale investigations can leverage our novel analytical strategy.

Inadequate molecular and clinical stratification of the patientswith high-risk diffuse large B-cell lymphoma (DLBCL) is a clinical challenge hampering the establishment of personalizedtherapeutic options. We studiedthe translational significance of liquid biopsy in a uniformly treated trial cohort.Pretreatment circulating tumor DNA (ctDNA)revealed hiddenclinical and biological heterogeneity, and high ctDNA burdendeterminedincreasedrisk of relapse and deathindependentlyof conventional risk factors. Genomic dissection of pretreatment ctDNA revealed translationally relevantphenotypic, molecular,and prognostic information that extended beyond diagnostic tissue biopsies.During therapy, chemorefractory lymphomas exhibited diverging ctDNA kinetics, whereas end-of-therapy negativity for minimal residual diseasecharacterized cured patientsand resolvedclinical enigmas, including false residual PET positivity.Furthermore, we discovered fragmentation disparities in the cell-free DNA that characterize lymphoma-derived ctDNA and,as a proof-of-conceptfor their clinical application,utilized machinelearningto show that end-of-therapy fragmentation patterns predict outcome. Altogether, wehave discovered novel molecular determinantsin the liquid biopsythatcan non-invasively guide treatment decisions.