The pressing need for multifunctional materials in medical settings encompasses a wide array of scenarios, necessitating specific tissue functionalities. A critical challenge is the occurrence of biofouling, particularly by contamination in surgical environments, a common cause of scaffolds impairment. Beyond the imperative to avoid infections, it is also essential to integrate scaffolds with living cells to allow for tissue regeneration, mediated by cell attachment. Here, we focus on the development of a versatile material for medical applications, driven by the diverse time-definite events after scaffold implantation. We investigate the potential of incorporating graphene oxide (GO) into polycaprolactone (PCL) and create a composite for 3D printing a scaffold with time-controlled antibacterial and anti-adhesive growth properties. Indeed, the as-produced PCL-GO scaffold displays a local hydrophobic effect, which is translated into a limitation of biological entities-attachment, including a diminished adhesion of bacteriophages and a reduction of E. coli and S. aureus adhesion of ∼81% and ∼69%, respectively. Moreover, the ability to 3D print PCL-GO scaffolds with different heights enables control over cell distribution and attachment, a feature that can be also exploited for cellular confinement, i.e., for microfluidics or wound healing applications. With time, the surface wettability increases, and the scaffold can be populated by cells. Finally, the presence of GO allows for the use of infrared light for the sterilization of scaffolds and the disruption of any bacteria cell that might adhere to the more hydrophilic surface. Overall, our results showcase the potential of PCL-GO as a versatile material for medical applications.

Rogue waves are intense and unexpected wavepackets ubiquitous in complex systems. In optics, they are promising as robust and noise-resistant beams for probing and manipulating the underlying material. Localizing large optical power is crucial especially in biomedical systems, where, however, extremely intense beams have not yet been observed. We here discover that tumor-cell spheroids manifest optical rogue waves when illuminated by randomly modulated laser beams. The intensity of light transmitted through bio-printed three-dimensional tumor models follows a signature Weibull statistical distribution, where extreme events correspond to spatially-localized optical modes propagating within the cell network. Experiments varying the input beam power and size indicate the rogue waves have a nonlinear origin. We show these optical filaments form high-transmission channels with enhanced transmission. They deliver large optical power through the tumor spheroid, which can be exploited to achieve a local temperature increase controlled by the input wave shape. Our findings shed new light on optical propagation in biological aggregates and demonstrate how extreme event formation allows light concentration in deep tissues, paving the way to using rogue waves in biomedical applications such as light-activated therapies.

In physiological conditions, red blood cells (RBCs) are capable of dramatic deformations when passing through the microvasculature. This extreme deformability is closely related to the RBC biconcave shape, to the fluidic nature of the haemoglobin and the cell membrane structure, primarily consisting of a phospholipid bilayer with an underlying two-dimensional spectrin network. In many pathological and inflammatory conditions, the shape and the extreme deformability of erythrocytes appear to be significantly altered. These findings have stimulated intense research towards the search and validation of novel erythrocyte-based mechanical biomarkers, useful for disease diagnosis and therapy monitoring. In this study, we investigated with Atomic Force Microscopy (AFM) the mechanical properties of erythrocytes obtained from a 68 years old cirrhotic man diagnosed with spur cell anaemia and cold agglutinated disease, before and after liver transplantation. Mechanical changes are compared with ultrastructural alterations as studied by scanning electron microscopy and discussed according to confocal fluorescence microscopy results, showing possible alterations induced by the cirrhotic environment at the level of the RBCs cytoskeletal organisation and lipidic composition. Taken together, the results here presented show that liver transplantation not only contributes to restoring the proper RBC morphology, but it also induces recovery of the physiological viscous behaviour of cells, further stressing the relevance of viscous and dissipative forces in determining the RBC biomechanical response.

Optical neural networks process information at the speed of light and are energetically efficient. Photonic artificial intelligence allows speech recognition, image classification, and Ising machines. Modern machine learning paradigms, as extreme learning machines, reveal that disordered and biological materials may realize optical neural networks with thousands of nodes trained only at the input and at the readout. May we use living matter for machine learning? Here, we employ living three-dimensional tumor brain models to demonstrate a random optical learning machine (ROM) for the investigation of glioblastoma. The tumor spheroid act as a computational reservoir. The ROM detects cancer morphodynamics by laser-induced hyperthermia, quantifies chemotherapy, and cell metabolism. The ROM is a sensitive noninvasive smart probe for cytotoxicity assay and enables real-time investigation of tumor dynamics. We hence design and demonstrate a novel bio-hardware for optical computing and the study of light/complex matter interaction. Can living systems function as artificial neural networks for biophysical applications? Here, the authors show that living tumor spheroids can be employed as random optical learning machines and used to investigate cancer morphodynamics and quantify the effect of chemotherapy.

The pneumonia outbreak of coronavirus disease 2019 (COVID-19) represents a global issue. The bidimensional material graphene has captured much attention due to promising antimicrobial applications and has also demonstrated antiviral efficacy. In response to this global outbreak, we summarized the current state of knowledge of graphene and virus interaction as well as possible successful applications to fight COVID-19. Antibody-conjugated graphene sheets can rapidly detect targeted virus proteins and can be useful for large population screening, but also for the development of environmental sensors and filters, given the low cost of graphene materials. Functionalized graphene has demonstrated a good viral capture capacity that, combined with heat or light-mediated inactivation, could be used as a disinfectant. Graphene sensors arrays can be implemented on standard utility textiles and drug efficacy screening. Thanks to its high versatility, we foresee that graphene may have a leading role in the fight against COVID-19.

The umbilical cord is a complex structure containing three vessels, one straight vein and two coiled arteries, encased by the Wharton Jelly (WJ) a spongy structure made of collagen and hydrated macromolecules. Fetal blood reaches the placenta through the arteries and flows back to the fetus through the vein. The role of the WJ in maintaining cord circulation proficiency and the ultimate reason for arterial coiling still lack of reasonable mechanistic interpretations. We performed biaxial tension tests and evidenced significant differences in the mechanical properties of the core and peripheral WJ. The core region, located between the arteries and the vein, resulted rather stiffer close to the fetus. Finite element modelling and optimization based inverse method were used to create 2D and 3D models of the cord and to simulate stress distribution in different hemodynamic conditions, compressive loads and arterial coiling. We recorded a facilitated stress transmission from the arteries to the vein through the soft core of periplacental WJ. This condition generates a pressure gradient that boosts the venous backflow circulation towards the fetus. Peripheral WJ allows arteries to act as pressure buffering chambers during the cardiac diastole and helps to dissipate compressive forces away from vessels. Altered WJ biomechanics may represent the structural basis of cord vulnerability in many high-risk clinical conditions.

In their physiological function, red blood cells (RBCs) need to undergo large deformations in order to pass through capillaries and small vessels. In several pathological conditions, including diabetes mellitus and Alzheimer’s disease, this extreme deformability appears to be deeply impaired and an increase in the RBCs stiffness is usually detected. Given the key role played by the mechanical properties of RBCs, we investigated their viscous-elastic response by AFM nano-mapping. High-resolution maps demonstrate that healthy erythrocytes are stiffer in their canter and softer at the periphery. The RBC stiffness profile shows a cylindrical symmetry that appears to be strongly correlated with their typical biconcave shape. Our measurements show that the Young’s modulus is strongly depending on the indentation rate, demonstrating that viscous forces have a key role in determining their mechanical response. The importance of viscous forces is further stressed by the comparison between healthy and pathological erythrocyte. Our data show that pathological RBCs are not simply stiffer than healthy ones. Conversely they display a different dependence on the indentation rate that leads to an apparent increase in stiffness. Taken together our results show that both the local stiffness distribution and the viscoelastic response provide important information on RBC biomechanics.

Optical neuromorphic computing processes information at the speed of light, but requires a careful design and fabrication of the deep layers, which strongly hampers the development of large-scale photonic learning machines [1,2]. New paradigms, as reservoir computing [3], suggest that brain-inspired complex systems such as disordered and biological materials may realize artificial neural networks with thousands of computational nodes trained only at the input and at the readout.

Graphene oxide is the hot topic in biomedical and pharmaceutical research of the current decade. However, its complex interactions with human blood components complicate the transition from the promising in vitro results to clinical settings. Even though graphene oxide is made with the same atoms as our organs, tissues and cells, its bi-dimensional nature causes unique interactions with blood proteins and biological membranes and can lead to severe effects like thrombogenicity and immune cell activation. In this review, we will describe the journey of graphene oxide after injection into the bloodstream, from the initial interactions with plasma proteins to the formation of the "biomolecular corona", and biodistribution. We will consider the link between the chemical properties of graphene oxide (and its functionalized/reduced derivatives), protein binding and in vivo response. We will also summarize data on biodistribution and toxicity in view of the current knowledge of the influence of the biomolecular corona on these processes. Our aim is to shed light on the unsolved problems regarding the graphene oxide corona to build the groundwork for the future development of drug delivery technology.

We employ living three-dimensional tumour brain models to demonstrate a bio-inspired optical neural network trained via image transmission to detect cancer mor-phodynamics inaccessible by optical imaging.

Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for serious hospital infections worldwide and represents a global public health problem. Curcumin, the major constituent of turmeric, is effective against MRSA but only at cytotoxic concentrations or in combination with antibiotics. The major issue in curcumin-based therapies is the poor solubility of this hydrophobic compound and the cytotoxicity at high doses. In this paper, we describe the efficacy of a composite nanoparticle made of curcumin (CU) and graphene oxide (GO), hereafter GOCU, in MRSA infection treatment. GO is a nanomaterial with a large surface area and high drug-loading capacity. GO has also antibacterial properties due mainly to a mechanical cutting of the bacterial membranes. For this physical mechanism of action, microorganisms are unlikely to develop resistance against this nanomaterial. In this work, we report the capacity of GO to support and stabilize curcumin molecules in a water environment and we demonstrate the efficacy of GOCU against MRSA at a concentration below 2 µg ml −1 . Further, GOCU displays low toxicity on fibroblasts cells and avoids haemolysis of red blood cells. Our results indicate that GOCU is a promising nanomaterial against antibiotic-resistant MRSA.

The new era of artificial intelligence demands large-scale ultrafast hardware for machine learning. Optical artificial neural networks process classical and quantum information at the speed of light, and are compatible with silicon technology, but lack scalability and need expensive manufacturing of many computational layers. New paradigms, as reservoir computing and the extreme learning machine, suggest that disordered and biological materials may realize artificial neural networks with thousands of computational nodes trained only at the input and at the readout. Here we employ biological complex systems, i.e., living three-dimensional tumour brain models, and demonstrate a random neural network (RNN) trained to detect tumour morphodynamics via image transmission. The RNN, with the tumour spheroid as a three-dimensional deep computational reservoir, performs programmed optical functions and detects cancer morphodynamics from laser-induced hyperthermia inaccessible by optical imaging. Moreover, the RNN quantifies the effect of chemotherapy inhibiting tumour growth. We realize a non-invasive smart probe for cytotoxicity assay, which is at least one order of magnitude more sensitive with respect to conventional imaging. Our random and hybrid photonic/living system is a novel artificial machine for computing and for the real-time investigation of tumour dynamics.

Today, liposomes are an advanced technology of drug carriers with a dozen drugs in clinical practice and many more in clinical trials. A bottleneck associated with the clinical translation of liposomes has long been 'opsonization', i.e. the adsorption of plasma proteins at the liposome surface resulting in their rapid clearance from circulation. For decades, the most popular way to avoid opsonization has been grafting polyethylene glycol (PEG) onto the liposome surface. Recent studies have clarified that grafting PEG onto the liposome surface reduces, but does not completely prevent protein binding. In this work, we employed dynamic light scattering, zeta-potential analysis, one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE), semi-quantitative densitometry and cell imaging to explore the bio-nano-interactions between human plasma (HP) and Onivyde, a PEGylated liposomal drug that has recently been approved by the Food and Drug Administration (FDA) for the treatment of metastatic pancreatic ductal adenocarcinoma (PDAC). To properly evaluate the role of PEGylation, an unPEGylated variant of Onivyde was used as a reference. Collectively, our findings suggest that: (i) although PEGylated, Onivyde is not "stealth" in HP; (ii) surface chemistry is more important than PEGylation in controlling the bio-nano-interactions between Onivyde and plasma components. Of note is that the PC was found to boost the cellular uptake of Onivyde in the pancreas ductal adenocarcinoma cell line (PANC-1) thus suggesting its prominent role in its indication for PDAC treatment. Relevant implications for drug delivery and drug design are discussed.

Pancreatic cancer is a very aggressive malignancy that is often diagnosed in the advanced stages, with the implication that long-term survivors are extremely rare. Thus, developing new methods for the early detection of pancreatic cancer is an urgent task for current research. To date, nanotechnology offers unprecedented opportunities for cancer therapeutics and diagnosis. The aim of this study is the development of a new pancreatic cancer diagnostic technology based on the exploitation of the nano-biointeractions between nanoparticles and blood samples. In this study, blood samples from 20 pancreatic cancer patients and 5 patients without malignancy were allowed to interact with designed lipid nanoparticles, leading to the formation of a hard "protein corona" at the nanoparticle surface. After isolation, the protein patterns were characterized by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS PAGE). We found that the protein corona of pancreatic cancer patients was much more enriched than that of healthy individuals. Statistical analysis of SDS-PAGE results allowed us to discriminate between healthy and pancreatic cancer patients with a total discriminate correctness rate of 88%.

Dystroglycan (DG) serves as an adhesion complex linking the actin cytoskeleton to the extracellular matrix. DG is encoded by a single gene as a precursor, which is constitutively cleaved to form the α- and β-DG subunits. α-DG is a peripheral protein characterized by an extensive glycosylation that is essential to bind laminin and other extracellular matrix proteins, while β-DG binds the cytoskeleton proteins. The functional properties of DG depend on the correct glycosylation of α-DG and on the cross-talk between the two subunits. A reduction of α-DG glycosylation has been observed in muscular dystrophy and cancer while the inhibition of the interaction between α- and β-DG is associated to aberrant post-translational processing of the complex. Here we used confocal microscopy based techniques to get insights into the influence of α-DG glycosylation on the functional properties of the β-DG, and its effects on cell migration. We used epithelial cells transfected with wild-type and with a mutated DG harboring the mutation T190M that has been recently associated to dystroglycanopathy. We found that α-DG hypoglycosylation, together with an increased protein instability, reduces the membrane dynamics of the β-subunit and its clustering within the actin-rich domains, influencing cell migration and spontaneous cell movement. These results contribute to give novel insights into the involvement of aberrant glycosylation of DG in the developing of muscular dystrophy and tumor metastasis.

Tumour microenvironment contributes importantly to the phenotype development of cancer cells, which receive and adapt to chemical and physical signals. It is hypothesized that remodelling of the actin cytoskeleton may enable tumor cells to evade normal apoptotic signalling and permit the acquisition of metastatic properties such as anchorage-independent growth and enhanced cell migration. Among different cancer cell lines, the SW480 and SW620 colon cells, derived from the same patient at different stages of tumour progression, represent a unique model to study the changes in mechanical properties during metastases. The SW480 derive from a primary colon tumour, while the SW620 originate from a population of malignant cells appeared in a lymph node metastases months after the initial surgery. In this work we measured by AFM, combined with Electron and Confocal Microscopy, the mechanic adaptability of cancer cell which reached in vivo the lymph node environment. We demonstrate how to resist to apoptotic stimuli in the lymphatic circulation, where the flow shear stress reduce cell survival, the metastatic cell increase their non-specific adhesion while retaining a flexible and soft cytoskeleton, related to uncontrolled growth properties. These features allow accomplishing the spreading in the circulation aim of metastatic cells.

The usual assumption made in mechanical characterization of soft tissues with Atomic Force Microscopy (AFM) is that the specimen behaves as a purely elastic material. Recent investigations have shown that in the case of immature porcine zona pellucida (ZP) samples viscous effects become more significant for sharp tips. Interestingly, a linear relationship between the limit indentation rate and the geometry of the AFM probe was derived, which is similar to the relationship existing between hardness and radius of curvature of the indenter typically observed for elasto-plastic materials. This study will analyze soft biotissues with different elasticity and viscous properties showing different response to nanoindentation. The relationship between limit indentation rate and tip geometry will be derived for each material to confirm previous experimental observations.

It is now established that the gastric pathogen Helicobacter pylori has the ability to form biofilms in vitro as well as on the human gastric mucosa. The aim of this study is to evaluate the antimicrobial effects of Clarithromycin on H. pylori biofilm and to enhance the effects of this antibiotic by combining it with Alginate Lyase, an enzyme degrading the polysaccharides present in the extracellular polymeric matrix forming the biofilm. We evaluated the Clarithromycin minimum inhibition concentration (MIC) on in vitro preformed biofilm of a H. pylori. Then the synergic effect of Clarithromycin and Alginate Lyase treatment has been quantified by using the Fractional Inhibitory Concentration index, measured by checkerboard microdilution assay. To clarify the mechanisms behind the effectiveness of this antibiofilm therapeutic combination, we used Atomic Force Microscopy to analyze modifications of bacterial morphology, percentage of bacillary or coccoid shaped bacteria cells and to quantify biofilm properties. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1584–1591, 2016