A computational model for single cell Lamin-A structural organization after microfluidic compression.

In recent years, nuclear mechanobiology gained a lot of attention for the study of cell responses to external cues like adhesive forces, applied compression, and/or shear-stresses. In details, the Lamin-A protein-as major constituent of the cell nucleus structure-plays a crucial role in the overall nucleus mechanobiological response. However, modeling and analysis of Lamin-A protein organization upon rapid compression conditions in microfluidics are still difficult to be performed. Here, we introduce the possibility to control an applied microfluidic compression on single cells, deforming them up to the nucleus level. In a wide range of stresses (~1-102 kPa) applied on healthy and cancer cells, we report increasing Lamin-A intensities which scale as a power law with the applied compression. Then, an increase up to two times of the nuclear viscosity is measured in healthy cells, due to the modified Lamin-A organization. This is ascribable to the increasing assembly of Lamin-A filament-like branches which increment both in number and elongation (up to branches four-time longer). Moreover, the solution of a computational model of differential equations is presented as a powerful tool for a single cell prediction of the Lamin-A assembly as a function of the applied compression.

HiViPore: a highly viable in-flow compression for a one-step cell mechanoporation in microfluidics to induce a free delivery of nano- macro-cargoes.

BACKGROUND: Among mechanoporation techniques for intracellular delivery, microfluidic approaches succeed in high delivery efficiency and throughput. However, especially the entry of large cargoes (e.g. DNA origami, mRNAs, organic/inorganic nanoparticles) is currently impaired since it requires large cell membrane pores with the need to apply multi-step processes and high forces, dramatically reducing cell viability. RESULTS: Here, HiViPore presents as a microfluidic viscoelastic contactless compression for one-step cell mechanoporation to produce large pores while preserving high cell viability. Inducing an increase of curvature at the equatorial region of cells, formation of a pore with a size of ~ 1 µm is obtained. The poration is coupled to an increase of membrane tension, measured as a raised fluorescence lifetime of 12% of a planarizable push-pull fluorescent probe (Flipper-TR) labelling the cell plasma membrane. Importantly, the local disruptions of cell membrane are transient and non-invasive, with a complete recovery of cell integrity and functions in ~ 10 min. As result, HiViPore guarantees cell viability as high as ~ 90%. In such conditions, an endocytic-free diffusion of large nanoparticles is obtained with typical size up to 500 nm and with a delivery efficiency up to 12 times higher than not-treated cells. CONCLUSIONS: The proposed one-step contactless mechanoporation results in an efficient and safe approach for advancing intracellular delivery strategies. In detail, HiViPore solves the issues of low cell viability when multiple steps of poration are required to obtain large pores across the cell plasma membrane. Moreover, the compression uses a versatile, low-cost, biocompatible viscoelastic fluid, thus also optimizing the operational costs. With HiViPore, we aim to propose an easy-to-use microfluidic device to a wide range of users, involved in biomedical research, imaging techniques and nanotechnology for intracellular delivery applications in cell engineering.

Easy Surface Functionalization and Bioconjugation of Peptides as Capture Agents of a Microfluidic Biosensing Platform for Multiplex Assay in Serum.

The development of assays for protein biomarkers in complex matrices is a demanding task that still needs implementation of new approaches. Antibodies as capture agents have been largely used in bioassays but their low stability, low-efficiency production, and cross-reactivity in multiplex approaches impairs their larger applications. Instead, synthetic peptides, even with higher stability and easily adapted amino acid sequences, still remain largely unexplored in this field. Here, we provide a proof-of-concept of a microfluidic device for direct detection of biomarker overexpression. The multichannel microfluidic polydimethylsiloxane (PDMS) device was first derivatized with PAA (poly(acrylic acid)) solution. CRP-1, VEGF-114, and ΦG6 peptides were preliminarily tested to respectively bind the biomarkers, C-reactive protein (CRP), vascular endothelial growth factor (VEGF), and tumor necrosis factor-alpha (TNF-α). Each PDMS microchannel was then respectively bioconjugated with a specific peptide (CRP-1, VEGF-114, or ΦG6) to specifically capture CRP, VEGF, and TNF-α. With such microdevices, a fluorescence bioassay has been set up with sensitivity in the nanomolar range, both in buffered solution and in human serum. The proposed multiplex assay worked with a low amount of sample (25 µL) and detected biomarker overexpression (above nM concentration), representing a noninvasive and inexpensive screening platform.

Hydrogel Microparticles for Fluorescence Detection of miRNA in Mix-Read Bioassay.

Herein we describe the development of a mix-read bioassay based on a three-dimensional (3D) poly ethylene glycol-(PEG)-hydrogel microparticles for the detection of oligonucleotides in complex media. The key steps of hydrogels synthesis and molecular recognition in a 3D polymer network are elucidated. The design of the DNA probes and their density in polymer network were opportunely optimized. Furthermore, the diffusion into the polymer was tuned adjusting the polymer concentration and consequently the characteristic mesh size. Upon parameters optimization, 3D-PEG-hydrogels were synthetized in a microfluidic system and provided with fluorescent probe. Target detection occurred by double strand displacement assay associated to fluorescence depletion within the hydrogel microparticle. Proposed 3D-PEG-hydrogel microparticles were designed for miR-143-3p detection. Results showed 3D-hydrogel microparticles with working range comprise between 10-6-10-12 M, had limit of detection of 30 pM and good specificity. Moreover, due to the anti-fouling properties of PEG-hydrogel, the target detection occurred in human serum with performance comparable to that in buffer. Due to the approach versatility, such design could be easily adapted to other short oligonucleotides detection.

One-step scalable fluorescent microgel bioassay for the ultrasensitive detection of endogenous viral miR-US4-5p.

Human cytomegalovirus (hCMV) infection is the leading cause of birth defects in newborns and death in immunosuppressed people. Traditional techniques require time-consuming and costly analyses, and sometimes result in false positive results; thus, a rapid and accurate detection for hCMV infection is necessary. Recently, hcmv-miR-US4-5p was selected as the biomarker for cytomegalovirus diagnosis and follow-up. Herein, we propose a bioassay based on microgels endowed with optical fluorescent oligonucleotide probes for the detection of circulating endogenous hcmv-microRNAs. In particular, a double strand probe, based on the fluorescence recovery after target capture, was conjugated on microgels and the probe density was opportunely optimised. Then, the microgels were directly mixed with the sample. The fluorescence read-out was measured as a function of target concentration at a fixed number of microgels per tube. As a bead-based assay, the performances of optical detection in terms of dynamic working range and limit of detection could be finely tuned by tuning the number of microgels per tube. The limit of detection of the assay could be tuned in the range from 39.1 fM to 156 aM by changing the microgel concentration from 50 µg mL-1 to 0.5 µg mL-1, respectively. The assay results specific for the selected target were stable over a one-year time span and they were not affected by the presence of human serum. Therefore, this bioassay based on microgels might represent a flexible platform that should be able to predict, identify and follow-up several diseases by monitoring freely circulating oligonucleotides in body fluids.

Supramolecular spectrally encoded microgels with double strand probes for absolute and direct miRNA fluorescence detection at high sensitivity.

We present novel microgels as a particle-based suspension array for direct and absolute microRNA (miRNA) detection. The microgels feature a flexible molecular architecture, antifouling properties, and enhanced sensitivity with a large dynamic range of detection. Specifically, they possess a core-shell molecular architecture with two different fluorescent dyes for multiplex spectral analyses and are endowed with a fluorescent probe for miRNA detection. Encoding and detection fluorescence signals are distinguishable by nonoverlapping emission spectra. Tunable fluorescence probe conjugation and emission confinement on single microgels allow for ultrasensitive miRNA detection. Indeed, the suspension array has high selectivity and sensitivity with absolute quantification, a detection limit of 10(-15) M, a dynamic range from 10(-9) to 10(-15) M, and higher accuracy than qRT-PCR. The antifouling properties of the microgels also permit the direct measurement of miRNAs in serum, without sample pretreatment or target amplification. A multiplexed assay has been tested for a set of miRNAs chosen as cancer biomarkers.

MicroLOCK: Highly stable microgel biosensor using locked nucleic acids as bioreceptors for sensitive and selective detection of let-7a.

Chemically modified oligonucleotides can solve biosensing issues for the development of capture probes, antisense, CRISPR/Cas, and siRNA, by enhancing their duplex-forming ability, their stability against enzymatic degradation, and their specificity for targets with high sequence similarity as microRNA families. However, the use of modified oligonucleotides such as locked nucleic acids (LNA) for biosensors is still limited by hurdles in design and from performances on the material interface. Here we developed a fluorogenic biosensor for non-coding RNAs, represented by polymeric PEG microgels conjugated with molecular beacons (MB) modified with locked nucleic acids (MicroLOCK). By 3D modeling and computational analysis, we designed molecular beacons (MB) inserting spot-on LNAs for high specificity among targets with high sequence similarity (95%). MicroLOCK can reversibly detect microRNA targets in a tiny amount of biological sample (2 µL) at 25 °C with a higher sensitivity (LOD 1.3 fM) without any reverse transcription or amplification. MicroLOCK can hybridize the target with fast kinetic (about 30 min), high duplex stability without interferences from the polymer interface, showing high signal-to-noise ratio (up to S/N = 7.3). MicroLOCK also demonstrated excellent resistance to highly nuclease-rich environments, in real samples. These findings represent a great breakthrough for using the LNA in developing low-cost biosensing approaches and can be applied not only for nucleic acids and protein detection but also for real-time imaging and quantitative assessment of gene targeting both in vitro and in vivo.

Exploring altered bovine sperm trajectories by sperm tracking in unconfined conditions.

Mammalian sperm motility is getting more relevant due to rising infertility rates worldwide, generating the need to improve conventional analysis and diagnostic approaches. Nowadays, computer assisted sperm analysis (CASA) technologies represent a popular alternative to manual examination which is generally performed by observing sperm motility in very confined geometries. However, under physiological conditions, sperm describe three-dimensional motility patterns which are not well reconstructed by the limited depth of standard acquisition chambers. Therefore, affordable and more versatile alternatives are needed. Here, a motility analysis in unconfined conditions is proposed. In details, the analysis is characterized by a significant longer duration -with respect to conventional systems- with the aim to observe eventually altered motility patterns. Brightfield acquisition in rectangular glass capillaries captured frozen-thawed bovine spermatozoa which were analyzed by means of a self-written tracking routine and classified in sub-populations, based on their curvilinear velocity. To test the versatility of our approach, cypermethrin -a commonly used pesticides- known to be responsible for changes in sperm motility was employed, assessing its effect at three different time-steps. Experimental results showed that such drug induces an increase in sperm velocity and progressiveness as well as circular pattern formation, likely independent of wall interactions. Moreover, this resulted in a redistribution of sperm with the rapid class declining in number with time, but still showing an overall velocity increase. The flexibility of the approach permits parameter modifications with the experimental needs, allowing us to conduct a comprehensive examination of sperm motility. This adaptability facilitated data acquisition which can be computed at different frame rates, extended time periods, and within deeper observation chambers. The suggested approach for sperm analysis exhibits potential as a valuable augmentation to current diagnostic instruments.

Accounting for misalignments and thermal fluctuations in fluorescence correlation spectroscopy experiments on membranes.

Several authors have exploited the ability of the fluorescence correlation spectroscopy to probe motion at the molecular level. In a couple of decades, all their efforts have allowed the application of this technique even to the diffusion measurement of cellular components. Nowadays, the fluorescence correlation spectroscopy is considered a standard tool to measure diffusion in cells both in vivo and in vitro. Unfortunately, while the interpretation and the set-up have been consolidated for 3D diffusion measurements (i.e. diffusion in an aqueous solution), the experiments carried out on flat elements, such as membranes, show unusually high relative errors. Furthermore, long tail correlations are generally detected and ascribed to diffusion anomalies. The 2D fluorescence correlation measurements have been interpreted under certain hypotheses, whereby the membrane is assumed to be perfectly flat, motionless and aligned with the optical axes. Here, we investigated the robustness of these hypotheses, trying to understand, in an elementary but not trivial way, how misalignments and thermal fluctuations affect the temporal correlation of the intensity fluctuation collected during measurements on membranes.

Silver-containing mesoporous bioactive glass with improved antibacterial properties.

The aim of the present work is the study of the bacteriostatic/bactericidal effect of a silver-containing mesoporous bioactive glass obtained by evaporation-induced self-assembly and successive thermal stabilization. Samples of the manufactured mesophase were characterized by means of transmission electron microscopy and N2 adsorption/desorption at 77 K, revealing structural and textural properties similar to SBA-15 mesoporous silica. Glass samples used for bioactivity experiments were put in contact with a standardized, commercially available cell culture medium instead of lab-produced simulated body fluid, and were then characterized by means of X-ray diffraction, field emission scanning electron microscopy and Fourier transform infrared spectroscopy. All these analyses confirmed the development of a hydroxyl carbonate apatite layer on glass particles. Moreover, the investigated mesostructure showed a very good antibacterial effect against S. aureus strain, with a strong evidence of bactericidal activity already registered at 0.5 mg/mL of glass concentration. A hypothesis about the mechanism by which Ag affects the bacterial viability, based on the intermediate formation of crystalline AgCl, was also taken into account. With respect to what already reported in the literature, these findings claim a deeper insight into the possible use of silver-containing bioactive glasses as multifunctional ceramic coatings for orthopedic devices.

Unknown cell class distinction via neural network based scattering snapshot recognition.

Neural network-based image classification is widely used in life science applications. However, it is essential to extrapolate a correct classification method for unknown images, where no prior knowledge can be utilised. Under a closed set assumption, unknown images will be inevitably misclassified, but this can be genuinely overcome choosing an open-set classification approach, which first generates an in-distribution of identified images to successively discriminate out-of-distribution images. The testing of such image classification for single cell applications in life science scenarios has yet to be done but could broaden our expertise in quantifying the influence of prediction uncertainty in deep learning. In this framework, we implemented the open-set concept on scattering snapshots of living cells to distinguish between unknown and known cell classes, targeting four different known monoblast cell classes and a single tumoral unknown monoblast cell line. We also investigated the influence on experimental sample errors and optimised neural network hyperparameters to obtain a high unknown cell class detection accuracy. We discovered that our open-set approach exhibits robustness against sample noise, a crucial aspect for its application in life science. Moreover, the presented open-set based neural network reveals measurement uncertainty out of the cell prediction, which can be applied to a wide range of single cell classifications.

Direct, precise, enzyme-free detection of miR-103-3p in real samples by microgels with highly specific molecular beacons.

Low abundance, small size, and sequence similarities render microRNA (miRNAs) detection challenging, particularly in real samples, where quantifying weakly expressed miRNAs can be arduous due to interference of more abundant molecules. The standard quantitative reverse transcription polymerase chain reaction (qRT-PCR) requires multiple steps, thermal cycles, and costly enzymatic reactions that can negatively affect results. Here we present a direct, precise, enzyme-free assay based on microgels particles conjugating molecular beacons (MB) capable of optically detecting low abundant miRNAs in real samples. We validate the applicability of microgels assay using qRT-PCR as a reference technology. As a relevant case, we chose miR-103-3p, a valuable diagnostic biomarker for breast cancer, both in serum samples and MCF7 cells. As a result, microgels assay quantifies miRNA molecules at room temperature in a single step, 1 h (vs. 4 hrs for qRT-PCR) without complementary DNA synthesis, amplification, or expensive reagents. Microgels assay exhibits femtomolar sensitivity, single nucleotide specificity, and a wide linear range (102-107 fM) (wider than qRT-PCR), with low sample consumption (2 µL) and excellent linearity (R2= 0.98). To test the selectivity of the microgel assay in real samples, MCF7 cells were considered where the pool of 8 other miRNAs were further upregulated with respect to miRNA 103-3p. In such complex environments, microgels assay selectively detects the miRNA target, mainly due to MB advanced stability and specificity as well as high microgel antifouling properties. These results show the reliability of microgels assay to detect miRNAs in real samples.

Hydrogel particles-on-chip (HyPoC): a fluorescence micro-sensor array for IgG immunoassay.

Novel microparticles have generated growing interest in diagnostics for potential sensitivity and specificity in biomolecule detection and for the possibility to be integrated in a micro-system array as a lab-on-chip. Indeed, bead-based technologies integrated in microfluidics could speed up incubation steps, reduce reagent consumption and improve accessibility of diagnostic devices to non-expert users. To limit non-specific interactions with interfering molecules and to exploit the whole particle volume for bioconjugation, hydrogel microparticles, particularly polyethylene glycol-based, have emerged as promising materials to develop high-performing biosensors since their network can be functionalized to concentrate the target and improve detection. However, the limitations in positioning, trapping and mainly fine manipulation of a precise number of particles in microfluidics have largely impaired point-of-care applications. Herein, we developed an on-chip sandwich immunoassay for the detection of human immunoglobulin G in biological fluids. The detection system is based on finely engineered cleavable PEG-based microparticles, functionalized with specific monoclonal antibodies. By changing the particle number, we demonstrated tuneable specificity and sensitivity (down to 3 pM) in serum and urine. Therefore, a controlled number of hydrogel particles have been integrated in a microfluidic device for on-chip detection (HyPoC) allowing for their precise positioning and fluid exchange for incubation, washing and target detection. HyPoC dramatically decreases incubation time from 180 minutes to one minute and reduces washing volumes from 3.5 ml to 90 µL, achieving a limit of detection of 0.07 nM (with a dynamic range of 0.07-1 nM). Thus, the developed approach represents a versatile, fast and easy point-of-care testing platform for immunoassays.

Exploring doxorubicin localization in eluting TiO2 nanotube arrays through fluorescence correlation spectroscopy analysis.

Drug elution properties of TiO(2) nanotube arrays have been largely investigated by means of solely macroscopic observations. Controversial elution performances have been reported so far and a clear comprehension of these phenomena is still missing as a consequence of a lack of molecular investigation methods. Here we propose a way to discern drug elution properties of nanotubes through the evaluation of drug localization by Fluorescence Correlation Spectroscopy (FCS) analysis. We verified this method upon doxorubicin elution from differently loaded TiO(2) nanotubes. Diverse elution profiles were obtained from nanotubes filled by soaking and wet vacuum impregnation methods. Impregnated nanotubes controlled drug diffusion up to thirty days, while soaked samples completed elution in seven days. FCS analysis of doxorubicin motion in loaded nanotubes clarified that more than 90% of drugs dwell preferentially in inter-nanotube spaces in soaked samples due to decorrelation in a 2D fashion, while a 97% fraction of molecules showed 1D mobility ascribable to displacements along the nanotube vertical axis of wet vacuum impregnated nanotubes. The diverse drug localizations inferred from FCS measurements, together with distinct drug-surface interaction strengths resulting from diverse drug filling techniques, could explain the variability in elution kinetics.

Fluorescence lifetimes and quantum yields of rhodamine derivatives: new insights from theory and experiment.

Although lifetimes and quantum yields of widely used fluorophores are often largely characterized, a systematic approach providing a rationale of their photophysical behavior on a quantitative basis is still a challenging goal. Here we combine methods rooted in the time-dependent density functional theory and fluorescence lifetime imaging microscopy to accurately determine and analyze fluorescence signatures (lifetime, quantum yield, and band peaks) of several commonly used rhodamine and pyronin dyes. We show that the radiative lifetime of rhodamines can be correlated to the charge transfer from the phenyl toward the xanthene moiety occurring upon the S(0) ← S(1) de-excitation, and to the xanthene/phenyl relative orientation assumed in the S(1) minimum structure, which in turn is variable upon the amino and the phenyl substituents. These findings encourage the synergy of experiment and theory as unique tool to design finely tuned fluorescent probes, such those conceived for modern optical sensors.

Wide-range viscoelastic compression forces in microfluidics to probe cell-dependent nuclear structural and mechanobiological responses.

The cell nucleus plays a critical role in mechanosensing and mechanotransduction processes, by adaptive changes of its envelope composition to external biophysical stimuli such as substrate rigidity and tensile forces. Current measurement approaches lack precise control in stress application on nuclei, thus significantly impairing a complete mechanobiological study of cells. Here, we present a contactless microfluidic approach capable to exert a wide range of viscoelastic compression forces (10-103 µN)-as an alternative to adhesion-related techniques-to induce cell-specific mechano-structural and biomolecular changes. We succeed in monitoring substantial nuclear modifications in Lamin A/C expression and coverage, diffusion processes of probing molecules, YAP shuttling, chromatin re-organization and cGAS pathway activation. As a result, high compression forces lead to a nuclear reinforcement (e.g. up to +20% in Lamin A/C coverage) or deconstruction (e.g. down to -45% in Lamin A/C coverage with a 30% reduction of chromatin condensation state parameter) up to cell death. We demonstrate how wide-range compression on suspended cells can be used as a tool to investigate nuclear mechanobiology and to define specific nuclear signatures for cell mechanical phenotyping.

Single cell classification of macrophage subtypes by label-free cell signatures and machine learning.

Pro-inflammatory (M1) and anti-inflammatory (M2) macrophage phenotypes play a fundamental role in the immune response. The interplay and consequently the classification between these two functional subtypes is significant for many therapeutic applications. Albeit, a fast classification of macrophage phenotypes is challenging. For instance, image-based classification systems need cell staining and coloration, which is usually time- and cost-consuming, such as multiple cell surface markers, transcription factors and cytokine profiles are needed. A simple alternative would be to identify such cell types by using single-cell, label-free and high throughput light scattering pattern analyses combined with a straightforward machine learning-based classification. Here, we compared different machine learning algorithms to classify distinct macrophage phenotypes based on their optical signature obtained from an ad hoc developed wide-angle static light scattering apparatus. As the main result, we were able to identify unpolarized macrophages from M1- and M2-polarized phenotypes and distinguished them from naive monocytes with an average accuracy above 85%. Therefore, we suggest that optical single-cell signatures within a lab-on-a-chip approach along with machine learning could be used as a fast, affordable, non-invasive macrophage phenotyping tool to supersede resource-intensive cell labelling.

Cell deformability heterogeneity recognition by unsupervised machine learning from in-flow motion parameters.

Cell deformability is a well-established marker of cell states for diagnostic purposes. However, the measurement of a wide range of different deformability levels is still challenging, especially in cancer, where a large heterogeneity of rheological/mechanical properties is present. Therefore, a simple, versatile and cost-effective recognition method for variable rheological/mechanical properties of cells is needed. Here, we introduce a new set of in-flow motion parameters capable of identifying heterogeneity among cell deformability, properly modified by the administration of drugs for cytoskeleton destabilization. Firstly, we measured cell deformability by identification of in-flow motions, rolling (R), tumbling (T), swinging (S) and tank-treading (TT), distinctively associated with cell rheological/mechanical properties. Secondly, from a pool of motion and structural cell parameters, an unsupervised machine learning approach based on principal component analysis (PCA) revealed dominant features: the local cell velocity (VCell/VAvg), the equilibrium position (YEq) and the orientation angle variation (Δφ). These motion parameters clearly defined cell clusters in terms of motion regimes corresponding to specific deformability. Such correlation is verified in a wide range of rheological/mechanical properties from the elastic cells moving like R until the almost viscous cells moving as TT. Thus, our approach shows how simple motion parameters allow cell deformability heterogeneity recognition, directly measuring rheological/mechanical properties.

PEG-based cleavable hydrogel microparticles with controlled porosity for permiselective trafficking of biomolecular complexes in biosensing applications.

In the last decade, PEG-based hydrogels have been extensively used for the production of microparticles for biosensing applications. The biomolecule accessibility and mass transport rate represent key parameters for the realization of sensitive microparticles, therefore porous materials have been developed, mainly resorting to the use of inert porogens and copolymers with different chain lengths. However, very limited information is reported regarding the addition of cleavable crosslinkers to modulate the network porosity. In this scenario, the aim of this work is to design, synthesize and characterize hydrogel microparticles, based on the copolymerization between PEG-diacrylate and N,N'-(1,2-dihydroxyethylene)-bisacrylamide, a cleavable crosslinker that simultaneously produces pores and reactive groups for bioprobe 3D bioconjugation. The results show great accessibility of these microparticles to antibodies and their complexes, without affecting their diffusion rate. Furthermore, the presence of a well-defined number of reactive aldehydes, produced by the cleavage reaction, allows modulating biosensor sensitivity through a fine control of the conjugation degree. The antibody-conjugated microparticles can efficiently capture the analyte down to a few picograms. These novel microparticles could be used as a highly sensitive platform for biomacromolecule detection in complex fluids, exploiting the combined effects of PEG's anti-fouling properties, large network porosity and interconnections, and three-dimensional bioconjugation.

Fluorescence correlation spectroscopy in semiadhesive wall proximity.

With examination of diffusion in heterogeneous media through fluorescence correlation spectroscopy, the temporal correlation of the intensity signal shows a long correlation tail and the characteristic diffusion time results are no longer easy to determine. Excluded volume and sticking effects have been proposed to justify such deviations from the standard behavior since all contribute and lead to anomalous diffusion mechanisms . Usually, the anomalous coefficient embodies all the effects of environmental heterogeneity providing too general explanations for the exotic diffusion recorded. Here, we investigated whether the reason of anomalies could be related to a lack of an adequate interpretative model for heterogeneous systems and how the presence of obstacles on the detection volume length scale could affect fluorescence correlation spectroscopy experiments. We report an original modeling of the autocorrelation function where fluorophores experience reflection or adsorption at a wall placed at distances comparable with the detection volume size. We successfully discriminate between steric and adhesion effects through the analysis of long time correlations and evaluate the adhesion strength through the evaluation of probability of being adsorbed and persistence time at the wall on reference data. The proposed model can be readily adopted to gain a better understanding of intracellular and nanoconfined diffusion opening the way for a more rational analysis of the diffusion mechanism in heterogeneous systems and further developing biological and biomedical applications.