Objective:To support cancer screening and identify precancerous conditions, such as atypical hyperplasia, to improve cure rates and reduce mortality, by analyzing the performance of a previously confirmed procedure. Patients and Methods:We established 204 short-term blood-derived cell lines from patients with cancer between December 1, 2013 and December 31, 2022. A dataset of phenotypic patterns, cytopathological variables, and proliferation profiles was used to train a neural network model. Comparative analysis of standard optical, functional, and machine learning supported diagnosis was performed to verify reproducibility and clinical translatability. Results:Tumor heterogeneity was classified into 7 phenotypic patterns (Pn1-Pn7); the Pn6-7 group showed an overall survival of 8 months (95% CI, 6-9). Among variables Vc1-Vc8, Vc3 (area under the curve=1, P<.001) and Vc5-6 (area under the curve=0.838, P<.001) were identified as discriminant for cell atypia (rho=0.5 correlation with biopsy). Proliferative ranges were 0%-30% healthy, 30%-35% hyperplasia, and >35% cancer. Artificial intelligence-supported cytology showed positive and negative predictive values of 0.99±0.015 and 1±0 compared with histopathological specimens (0.94±0.1 and 0.85±0.04). The algorithm achieved a 1±0 sensitivity and a 0.98±0.04 specificity, with respect to traditional diagnosis (specificity [0.875-0.923] and sensitivity [0.926-0.984]). Conclusion:The model demonstrated fast adaptive performance in predicting cancer risk and primary source assessment. The results suggest that this screening model is sufficient to detect atypical hyperplasia compared with models based on oligoanalysis for single or double mutations.

Passive microvalves enable autonomous operation of microfluidic devices by allowing time-controlled fluid delivery without external actuation. Here, we report a simple, low-cost, single-use passive microvalve based on poly(vinyl alcohol) (PVA) for time-programmed fluid delivery. The valve operates through dissolution of a solidified PVA plug formed inside poly(methyl methacrylate) (PMMA) microchannels after evaporation of the solvent phase. The valve dissolves when exposed to an aqueous medium, enabling fluid flow. The valve opening time was experimentally characterized as a function of the injected liquid volume using three PVA formulations and three microchannel cross-sections fabricated in PMMA. Experimental results showed a non-linear dependence of the opening time on the injected volume, as well as the influence of PVA formulation, channel geometry, and temperature. In addition, a demonstrative multi-valve device showed sequential valve opening with delays up to 7 h. The proposed approach enables simple and autonomous timed fluid release using inexpensive materials and straightforward fabrication processes, representing a promising strategy for low-cost microfluidic applications.

LX-2 cells were treated with different lipidic formulations to induce the transition from active to quiescent-like state. Raman imaging highlighted different lipid profiles for the cells, although they share the same quiescent state.

We present a miniaturized, inexpensive, and user-friendly microfluidic platform to support biological applications. The system integrates a mini-incubator providing controlled environmental conditions and housing a microfluidic device for long-term cell culture experiments. The incubator is designed to be compatible with standard inverted optical microscopes and Raman spectrometers, allowing for the non-invasive imaging and spectroscopic analysis of cell cultures in vitro. The microfluidic device, which reproduces a dynamic environment, was optimized to sustain a passive, gravity-driven flow of medium, eliminating the need for an external pumping system and reducing mechanical stress on the cells. The platform was tested using Raman analysis and adherent tumoral cells to assess proliferation prior and subsequent to hydrogen peroxide treatment for oxidative stress induction. The results demonstrated a successful adhesion of cells onto the substrate and their proliferation. Furthermore, the platform is suitable for carrying out optical monitoring of cultures and Raman analysis. In fact, it was possible to discriminate spectra deriving from control and hydrogen peroxide-treated cells in terms of DNA backbone and cellular membrane modification effects provoked by reactive oxygen species (ROS) activity. The 800–1100 cm−1 band highlights the destructive effects of ROS on the DNA backbone’s structure, as its rupture modifies its vibration; moreover, unpaired nucleotides are increased in treated sample, as shown in the 1154–1185 cm−1 band. Protein synthesis deterioration, led by DNA structure damage, is highlighted in the 1257–1341 cm−1, 1440–1450 cm−1, and 1640–1670 cm−1 bands. Furthermore, membrane damage is emphasized in changes in the 1270, 1301, and 1738 cm−1 frequencies, as phospholipid synthesis is accelerated in an attempt to compensate for the membrane damage brought about by the ROS attack. This study highlights the potential use of this platform as an alternative to conventional culturing and analysis procedures, considering that cell culturing, optical imaging, and Raman spectroscopy can be performed simultaneously on living cells with minimal cellular stress and without the need for labeling or fixation.

Raman microspectroscopy is a powerful, label-free technique for the biochemical characterization of cells, but its complex spectral data require advanced computational methods for meaningful interpretation. Clustering analysis is widely used in spectroscopic imaging to extract meaningful biochemical information. Traditional methods, such as K-means clustering with Euclidean distance, often struggle to capture subtle spectral variations, leading to suboptimal segmentation. Alternative distance metrics, including cosine and Mahalanobis distances, have been explored to enhance cluster separability, yet challenges remain in distinguishing chemically relevant features while minimizing redundancy and noise. In this study, we introduce an asymmetric metric distance matrix with a tunable eccentricity parameter to improve clustering performance in Raman hyperspectral imaging. Our results demonstrate that suitable eccentricity values enhance the identification of subcellular structures while requiring fewer clusters than Euclidean-based approaches. Compared to polar metrics, the proposed asymmetric metric achieves better stability and reduced noise, leading to more accurate segmentation. Future research could explore its application in other clustering techniques and machine learning frameworks, as well as its application in broader spectral imaging techniques where the distance metric plays a fundamental role.

Background the problem in early diagnosis of sporadic cancer is understanding the individual’s risk to develop disease. In response to this need, global scientific research is focusing on developing predictive models based on non-invasive screening tests. A tentative solution to the problem may be a cancer screening blood-based test able to discover those cell requirements triggering subclinical and clinical onset latency, at the stage when the cell disorder, i.e. atypical epithelial hyperplasia, is still in a subclinical stage of proliferative dysregulation. Methods a well-established procedure to identify proliferating circulating tumor cells was deployed to measure the cell proliferation of circulating non-haematological cells which may suggest tumor pathology. Moreover, the data collected were processed by a supervised machine learning model to make the prediction. Results the developed test combining circulating non-haematological cell proliferation data and artificial intelligence shows 98.8% of accuracy, 100% sensitivity, and 95% specificity. Conclusion this proof of concept study demonstrates that integration of innovative non invasive methods and predictive-models can be decisive in assessing the health status of an individual, and achieve cutting-edge results in cancer prevention and management.

Sarcopenia is a degenerative condition characterized by the atrophy and functional decline of myofibers, resulting in disability. While the clinical risk factors are known, there is no validated in vitro model to understand the molecular mechanisms and identify therapeutics. To tackle this challenge, we generated an in vitro post-mitotic muscular system by differentiating mouse myoblast cells, namely C2C12. After 12 days of differentiation, cells were expressing physiological markers of myotubes and became self-contracting. Importantly, transcriptomic analyses demonstrated high similarity (r=0.70) when compared to primary human myotubes (HSkMC) providing evidence of resemblance to human cells. Next, we starved and incubated cells with dexamethasone and observed myotube shrinkage, oxidative stress, modification of anabolic, inflammatory, and catabolic markers recapitulating sarcopenia. Conversely, cell refeeding resulted in a recovery in the model with nutrient deprivation but not when incubated also with dexamethasone. In conclusion, we present a model of sarcopenia due to nutrient deprivation and corticosteroids. This model may allow more efficient and effective future research to identify therapeutics against sarcopenia in humans.

BACKGROUND/AIMS:Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global epidemic. The disease has a strong genetic component, and a common missense variant (rs2642438) in the mitochondrial amidoxime-reducing component 1 (MARC1) gene confers protection against its onset and severity. However, there are contrasting results regarding the mechanisms that promote this protection. METHODS:We downregulated MARC1 in primary human hepatocytes (PHHs) using short interfering RNA (siRNA). We measured neutral lipid content by Oil-Red O staining and fatty acid oxidation by radiolabeled tracers. We also performed RNA-sequencing and proteomic analysis using LC-MS. Additionally, we analyzed data from 239,075 participants from the UK Biobank. RESULTS:Downregulation of MARC1 reduced neutral lipid content in PHHs homozygous for the wild type (p.A165, risk), but not for the mutant (p.T165, protective), allele. We found that this reduction was mediated by increased fatty acid utilization via β-oxidation. Consistent with these results, we found that the levels of 3-hydroxybutyrate, a by-product of β-oxidation, were higher in carriers of the rs2642438 minor allele among samples from the UK biobank, indicating higher β-oxidation in these individuals. Moreover, downregulation of the MARC1 p.A165 variant resulted in a more favorable phenotype by reducing ferroptosis and reactive oxygen species levels. CONCLUSION:MARC1 downregulation in carriers of the risk allele results in lower hepatocyte neutral lipids content due to higher β-oxidation, while upregulating beneficial pathways involved in cell survival.

Among all neoplasms, melanoma is characterized by a very high percentage of cancer stem cells (CSCs). Several markers have been proposed for their identification, and lipid droplets (LDs) are among them. Different techniques are used for their characterization such as mass spectrometry, imaging techniques, and vibrational spectroscopies. Some emerging experimental approaches for the study of LDs are represented by correlative light–electron microscopy and by correlative Raman imaging–scanning electron microscopy (SEM). Based on these scientific approaches, we developed a novel methodology (CREL) by combining Raman micro-spectroscopy, confocal fluorescence microscopy, and SEM coupled with an energy-dispersive X-ray spectroscopy module. This procedure correlated cellular morphology, chemical properties, and spatial distribution from the same region of interest, and in this work, we presented the application of CREL for the analysis of LDs within patient-derived melanoma CSCs (MCSCs).

The necessity to improve in vitro cell screening assays is becoming ever more important. Pharmaceutical companies, research laboratories and hospitals require technologies that help to speed up conventional screening and therapeutic procedures to produce more data in a short time in a realistic and reliable manner. The design of new solutions for test biomaterials and active molecules is one of the urgent problems of preclinical screening and the limited correlation between in vitro and in vivo data remains one of the major issues. The establishment of the most suitable in vitro model provides reduction in times, costs and, last but not least, in the number of animal experiments as recommended by the 3Rs (replace, reduce, refine) ethical guiding principles for testing involving animals. Although two-dimensional (2D) traditional cell screening assays are generally cheap and practical to manage, they have strong limitations, as cells, within the transition from the three-dimensional (3D) in vivo to the 2D in vitro growth conditions, do not properly mimic the real morphologies and physiology of their native tissues. In the study of human pathologies, especially, animal experiments provide data closer to what happens in the target organ or apparatus, but they imply slow and costly procedures and they generally do not fully accomplish the 3Rs recommendations, i.e., the amount of laboratory animals and the stress that they undergo must be minimized. Microfluidic devices seem to offer different advantages in relation to the mentioned issues. This review aims to describe the critical issues connected with the conventional cells culture and screening procedures, showing what happens in the in vivo physiological micro and nano environment also from a physical point of view. During the discussion, some microfluidic tools and their components are described to explain how these devices can circumvent the actual limitations described in the introduction.

In this study, transmission electron microscopy atomic force microscopy, and surface enhanced Raman spectroscopy are combined through a direct imaging approach, to gather structural and chemical information of complex molecular systems such as ion channels in their original plasma membrane. Customized microfabricated sample holder allows to characterize Nav channels embedded in the original plasma membrane extracted from neuronal cells that are derived from healthy human induced pluripotent stem cells. The identification of the channels is accomplished by using two different approaches, one of them widely used in cryo-EM (the particle analysis method) and the other based on a novel Zernike Polynomial expansion of the images bitmap. This approach allows to carry out a whole series of investigations, one complementary to the other, on the same sample, preserving its state as close as possible to the original membrane configuration.

The altered glucose metabolism characterising cancer cells determines an increased amount of methylglyoxal in their secretome. Previous studies have demonstrated that the methylglyoxal, in turn, modifies the protonation state (PS) of soluble proteins contained in the secretomes of cultivated circulating tumour cells (CTCs). In this study, we describe a method to assess the content of methylglyoxal adducts (MAs) in the secretome by near-infrared (NIR) portable handheld spectroscopy and the extreme learning machine (ELM) algorithm. By measuring the vibration absorption functional groups containing hydrogen, such as C-H, O-H and N-H, NIR generates specific spectra. These spectra reflect alterations of the energy frequency of a sample bringing information about its MAs concentration levels. The algorithm deciphers the information encoded in the spectra and yields a quantitative estimate of the concentration of MAs in the sample. This procedure was used for the comparative analysis of different biological fluids extracted from patients suspected of having cancer (secretome, plasma, serum, interstitial fluid and whole blood) measured directly on the solute left on a surface upon a sample-drop cast and evaporation, without any sample pretreatment. Qualitative and quantitative regression models were built and tested to characterise the different levels of MAs by ELM. The final model we selected was able to automatically segregate tumour from non-tumour patients. The method is simple, rapid and repeatable; moreover, it can be integrated in portable electronic devices for point-of-care and remote testing of patients.

Protein A has long been used in different research fields due to its ability to specifically recognize immunoglobulins (Ig). The protein derived from Staphylococcus aureus binds Ig through the Fc region of the antibody, showing its strongest binding in immunoglobulin G (IgG), making it the most used protein in its purification and detection. The research presented here integrates, for the first time, protein A to a silicon surface patterned with gold nanoparticles for the oriented binding of IgG. The signal detection is conveyed through a metal enhanced fluorescence (MEF) system. Orienting immunoglobulins allows the exposition of the fragment antigen-binding (Fab) region for the binding to its antigen, substantially increasing the binding capacity per antibody immobilized. Antibodies orientation is of crucial importance in many diagnostics devices, particularly when either component is in limited quantities.

Superhydrophobic surfaces display an extraordinary repulsion to water and water-based solutions. This effect emerges from the interplay of intrinsic hydrophobicity of the surface and its morphology. These surfaces have been established for a long time and have been studied for decades. The increasing interest in recent years has been focused towards applications in many different fields and, in particular, biomedical applications. In this paper, we review the progress achieved in the last years in the fabrication of regularly patterned superhydrophobic surfaces in many different materials and their exploitation for the manipulation and characterization of biomaterial, with particular emphasis on the issues affecting the yields of the fabrication processes and the quality of the manufactured devices.

Scanning electron microscopy is a technique that provides high-resolution images at the micro- and nano-scale. The combination of scanning electron microscopy and energy dispersive X-ray spectroscopy analysis is developing fast for application in forensic science. In this work, we report a case of work-related traumatic death of a 50-year-old man. The autopsy showed cranial fractures with cerebral haemorrhage. It was more difficult to understand the accident dynamics because the body had been shifted from the accident site to mask what had really taken place. Scanning electron microscopy/energy dispersive X-ray spectroscopy was used to identify the material of the impacting tool and to establish the possible legal responsibility of the employer. In this study, we demonstrate that scanning electron microscopy/energy dispersive X-ray spectroscopy is a useful forensic tool for the analysis of biological samples. Further, for studying the lacerations on the corpse from doubtful blunt tools, scanning electron microscopy/energy dispersive X-ray spectroscopy can assist in demonstrating that the scene has been falsified, as it was in this case.

Lipid Droplets (LDs) are emerging as crucial players in colon cancer development and maintenance. Their expression has been associated with high tumorigenicity in Cancer Stem Cells (CSCs), so that they have been proposed as a new functional marker in Colorectal Cancer Stem Cells (CR-CSCs). They are also indirectly involved in the modulation of the tumor microenvironment through the production of pro-inflammatory molecules. There is growing evidence that a possible connection between metabolic alterations and malignant transformation exists, although the effects of nutrients, primarily glucose, on the CSC behavior are still mostly unexplored. Glucose is an essential fuel for cancer cells, and the connections with LDs in the healthy and CSC populations merit to be more deeply investigated. Here, we showed that a high glucose concentration activated the PI3K/AKT pathway and increased the expression of CD133 and CD44v6 CSC markers. Additionally, glucose was responsible for the increased amount of Reactive Oxygen Species (ROS) and LDs in both healthy and CR-CSC samples. We also investigated the gene modulations following the HG treatment and found out that the healthy cell gene profile was the most affected. Lastly, Atorvastatin, a lipid-lowering drug, induced the highest mortality on CR-CSCs without affecting the healthy counterpart.

The adhesion, proliferation, and migration of cells over nanomaterials is regulated by a cascade of biochemical signals that originate at the interface of a cell with a substrate and propagate through the cytoplasm to the nucleus. The topography of the substrate plays a major role in this process. Cell adhesion molecules (CAMs) have a characteristic size of some nanometers and a range of action of some tens of nanometers. Controlling details of a surface at the nanoscale-the same dimensional over which CAMs operate-offers ways to govern the behavior of cells and create organoids or tissues with heretofore unattainable precision. Here, using electrochemical procedures, we generated mesoporous silicon surfaces with different values of pore size (PS≈11 nm and PS≈21 nm), roughness (Ra≈7 nm and Ra≈13 nm), and fractal dimension (Df≈2.48 and Df≈2.15). Using electroless deposition, we deposited over these substrates thin layers of gold nanoparticles. Resulting devices feature (i) nanoscale details for the stimulation and control of cell assembly, (ii) arrays of pores for drug loading/release, (iii) layers of nanostructured gold for the enhancement of the electromagnetic signal in Raman spectroscopy (SERS). We then used these devices as cell culturing substrates. Upon loading with the anti-tumor drug PtCl (O,O'-acac)(DMSO) we examined the rate of adhesion and growth of breast cancer MCF-7 cells under the coincidental effects of surface geometry and drug release. Using confocal imaging and SERS spectroscopy we determined the relative importance of nano-topography and delivery of therapeutics on cell growth-and how an unbalance between these competing agents can accelerate the development of tumor cells.

In this work, a disposable passive microfluidic device for cell culturing that does not require any additional/external pressure sources is introduced. By regulating the height of fluidic columns and the aperture and closure of the source wells, the device can provide different media and/or drug flows, thereby allowing different flow patterns with respect to time. The device is made of two Polymethylmethacrylate (PMMA) layers fabricated by micro-milling and solvent assisted bonding and allows us to ensure a flow rate of 18.6 μl/ℎ - 7%/day, due to a decrease of the fluid height while the liquid is driven from the reservoirs into the channels. Simulations and experiments were conducted to characterize flows and diffusion in the culture chamber. Melanoma tumor cells were used to test the device and carry out cell culturing experiments for 48 hours. Moreover, HeLa, Jurkat, A549 and HEK293T cell lines were cultivated successfully inside the microfluidic device for 72 hours.

Since its appearance, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has immediately alarmed the World Health Organization for its very high contagiousness and the complexity of patient clinical profiles. The worldwide scientific community is today gathered in a massive effort in order to develop safe vaccines and effective therapies in the shortest possible time. Every day, new pieces of SARS-CoV-2 infective puzzle are disclosed. Based on knowledge gained with other related coronaviruses and, more in general, on single-strand RNA viruses, we highlight underexplored molecular routes in which lipids and lipid droplets (LDs) might serve essential functions in viral infections. In fact, both lipid homeostasis and the pathways connected to lipids seem to be fundamental in all phases of the coronavirus infection. This review aims at describing potential roles for lipid and LDs in host-virus interactions and suggesting LDs as new and central cellular organelles to be investigated as potential targets against SARS-CoV-2 infection.

Multiple myeloma (MM) is a hematological malignancy characterized by abnormal plasma cell proliferation within the bone marrow which leads to progressive bone marrow failure, skeletal osteolytic lesions, and renal insufficiency, thus severely affecting the quality of life. MM is always preceded by monoclonal gammopathy of uncertain significance (MGUS), which progresses to asymptomatic-MM (aMM) or symptomatic-MM (sMM) at a rate of 1% per year. Despite impressive progress in the therapy of the disease, MM remains incurable. Based on these premises, the identification of biomarkers of MGUS progression to MM is a crucial issue in disease management. In this regard, exosomes (EXs) and their precious biomolecular cargo could play a pivotal role in MM detection, stratification, and follow-up. Raman spectroscopy, a label- and manipulation-free technique, and its enhanced version, surface-enhanced Raman spectroscopy (SERS), have been used for characterizing MGUS, aMM, and sMM patient-derived EXs. Here, we have demonstrated the capability of Raman spectroscopy for discriminating EXs along the progression from MGUS to aMM and sMM, thus providing useful clinical indications for patient care. The used SERS devices, based on random nanostructures, have shown good potential in terms of sensitivity, but further developments are needed for achieving reproducible and quantitative SERS results.