Cardiolipin drives the catalytic activity of GPX4 on membranes: Insights from the R152H mutant.

The aim of this study was to examine, in biochemical detail, the functional role of the Arg152 residue in the selenoprotein Glutathione Peroxidase 4 (GPX4), whose mutation to His is involved in Sedaghatian-type Spondylometaphyseal Dysplasia (SSMD). Wild-type and mutated recombinant enzymes with selenopcysteine (Sec) at the active site, were purified and structurally characterized to investigate the impact of the R152H mutation on enzymatic function. The mutation did not affect the peroxidase reaction's catalytic mechanism, and the kinetic parameters were qualitatively similar between the wild-type enzyme and the mutant when mixed micelles and monolamellar liposomes containing phosphatidylcholine and its hydroperoxide derivatives were used as substrate. However, in monolamellar liposomes also containing cardiolipin, which binds to a cationic area near the active site of GPX4, including residue R152, the wild-type enzyme showed a non-canonical dependency of the reaction rate on the concentration of both enzyme and membrane cardiolipin. To explain this oddity, a minimal model was developed encompassing the kinetics of both the enzyme interaction with the membrane and the catalytic peroxidase reaction. Computational fitting of experimental activity recordings showed that the wild-type enzyme was surface-sensing and prone to "positive feedback" in the presence of cardiolipin, indicating a positive cooperativity. This feature was minimal, if any, in the mutant. These findings suggest that GPX4 physiology in cardiolipin containing mitochondria is unique, and emerges as a likely target of the pathological dysfunction in SSMD.

Antenna-enhanced mid-infrared detection of extracellular vesicles derived from human cancer cell cultures.

BACKGROUND: Extracellular Vesicles (EVs) are sub-micrometer lipid-bound particles released by most cell types. They are considered a promising source of cancer biomarkers for liquid biopsy and personalized medicine due to their specific molecular cargo, which provides biochemical information on the state of parent cells. Despite this potential, EVs translation process in the diagnostic practice is still at its birth, and the development of novel medical devices for their detection and characterization is highly required. RESULTS: In this study, we demonstrate mid-infrared plasmonic nanoantenna arrays designed to detect, in the liquid and dry phase, the specific vibrational absorption signal of EVs simultaneously with the unspecific refractive index sensing signal. For this purpose, EVs are immobilized on the gold nanoantenna surface by immunocapture, allowing us to select specific EV sub-populations and get rid of contaminants. A wet sample-handling technique relying on hydrophobicity contrast enables effortless reflectance measurements with a Fourier-transform infrared (FTIR) spectro-microscope in the wavelength range between 10 and 3 µm. In a proof-of-principle experiment carried out on EVs released from human colorectal adenocarcinoma (CRC) cells, the protein absorption bands (amide-I and amide-II between 5.9 and 6.4 µm) increase sharply within minutes when the EV solution is introduced in the fluidic chamber, indicating sensitivity to the EV proteins. A refractive index sensing curve is simultaneously provided by our sensor in the form of the redshift of a sharp spectral edge at wavelengths around 5 µm, where no vibrational absorption of organic molecules takes place: this permits to extract of the dynamics of EV capture by antibodies from the overall molecular layer deposition dynamics, which is typically measured by commercial surface plasmon resonance sensors. Additionally, the described metasurface is exploited to compare the spectral response of EVs derived from cancer cells with increasing invasiveness and metastatic potential, suggesting that the average secondary structure content in EVs can be correlated with cell malignancy. CONCLUSIONS: Thanks to the high protein sensitivity and the possibility to work with small sample volumes-two key features for ultrasensitive detection of extracellular vesicles- our lab-on-chip can positively impact the development of novel laboratory medicine methods for the molecular characterization of EVs.

Sensing red blood cell nano-mechanics: Toward a novel blood biomarker for Alzheimer's disease.

Red blood cells (RBCs) are characterized by a remarkable elasticity, which allows them to undergo very large deformation when passing through small vessels and capillaries. This extreme deformability is altered in various clinical conditions, suggesting that the analysis of red blood cell (RBC) mechanics has potential applications in the search for non-invasive and cost-effective blood biomarkers. Here, we provide a comparative study of the mechanical response of RBCs in patients with Alzheimer's disease (AD) and healthy subjects. For this purpose, RBC viscoelastic response was investigated using atomic force microscopy (AFM) in the force spectroscopy mode. Two types of analyses were performed: (i) a conventional analysis of AFM force-distance (FD) curves, which allowed us to retrieve the apparent Young's modulus, E; and (ii) a more in-depth analysis of time-dependent relaxation curves in the framework of the standard linear solid (SLS) model, which allowed us to estimate cell viscosity and elasticity, independently. Our data demonstrate that, while conventional analysis of AFM FD curves fails in distinguishing the two groups, the mechanical parameters obtained with the SLS model show a very good classification ability. The diagnostic performance of mechanical parameters was assessed using receiving operator characteristic (ROC) curves, showing very large areas under the curves (AUC) for selected biomarkers (AUC > 0.9). Taken all together, the data presented here demonstrate that RBC mechanics are significantly altered in AD, also highlighting the key role played by viscous forces. These RBC abnormalities in AD, which include both a modified elasticity and viscosity, could be considered a potential source of plasmatic biomarkers in the field of liquid biopsy to be used in combination with more established indicators of the pathology.

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy.

Extracellular vesicles (EVs) are abundantly released into the systemic circulation, where they show remarkable stability and harbor molecular constituents that provide biochemical information about their cells of origin. Due to this characteristic, EVs are attracting increasing attention as a source of circulating biomarkers for cancer liquid biopsy and personalized medicine. Despite this potential, none of the discovered biomarkers has entered the clinical practice so far, and novel approaches for the label-free characterization of EVs are highly demanded. In this regard, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides a quick, reproducible, and informative biomolecular fingerprint of EVs. In this pilot study, we investigated, for the first time in the literature, the capability of FTIR spectroscopy to distinguish between EVs extracted from sera of cancer patients and controls based on their mid-IR spectral response. For this purpose, EV-enriched suspensions were obtained from the serum of patients diagnosed with Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our data point out the presence of statistically significant differences in the integrated intensities of major mid-IR absorption bands, including the carbohydrate and nucleic acids band, the protein amide I and II bands, and the lipid CH stretching band. Additionally, we used Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) for the automated classification of spectral data according to the shape of specific mid-IR spectral signatures. The diagnostic performances of the proposed spectral biomarkers, alone and combined, were evaluated using multivariate logistic regression followed by a Receiving Operator Curve analysis, obtaining large Areas Under the Curve (AUC = 0.91, 95% CI 0.81-1.0). Very interestingly, our analyses suggest that the discussed spectral biomarkers can outperform the classification ability of two widely used circulating HCC markers measured on the same groups of subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of vitamin K or antagonist-II (PIVKA-II).

Label-free spectroscopic characterization of exosomes reveals cancer cell differentiation.

Exosomes (EXOs) are considered an exceptionally promising source of cancer biomarkers for personalized medicine and liquid biopsy. Despite this potential, the EXOs translation process in diagnostics is still at its birth, and the development of reliable and reproducible methods for their characterization is highly demanded. Fourier Transform Infrared (FTIR) Spectroscopy is perfectly suited for this purpose, as it can provide a label-free biochemical profile of EXOs in terms of lipid, protein, and nucleic acid content. Here we evaluated the applicability of FTIR spectroscopy to the study of cancer-derived EXOs as a function of cell differentiation. For this purpose, we used N-acetyl-l-Cysteine (NAC) to induce a controlled differentiation in human colon carcinoma cells from a proliferative mesenchymal morphology to a less invasive epithelial phenotype, as measured with fluorescence and electron microscopy. EXOs derived from cells with different phenotypes showed significant variation in the relative intensity of the amide I-II and CH-stretching bands in the mid-IR range, indicating the spectroscopic lipid/protein ratio as an effective classification parameter. Additionally, we showed that different cell phenotypes are associated with a shape modification in these spectral bands that can be automatically detected by combining Principal Component Analysis (PCA) with Linear Discriminant Analysis (LDA). On the one hand, our study confirms that an FTIR analysis of EXOs allows scientists to precisely detect modifications occurring at the parental cell level; on the other hand, it unveils a set of effective spectral biomarkers able to monitoring cell changes from a mesenchymal to an epithelial phenotype, a clinically valuable piece of information considering that the epithelial-to-mesenchymal transition is a key step in the metastatic process.

Mapping the NFT revolution: market trends, trade networks, and visual features.

Non Fungible Tokens (NFTs) are digital assets that represent objects like art, collectible, and in-game items. They are traded online, often with cryptocurrency, and are generally encoded within smart contracts on a blockchain. Public attention towards NFTs has exploded in 2021, when their market has experienced record sales, but little is known about the overall structure and evolution of its market. Here, we analyse data concerning 6.1 million trades of 4.7 million NFTs between June 23, 2017 and April 27, 2021, obtained primarily from Ethereum and WAX blockchains. First, we characterize statistical properties of the market. Second, we build the network of interactions, show that traders typically specialize on NFTs associated with similar objects and form tight clusters with other traders that exchange the same kind of objects. Third, we cluster objects associated to NFTs according to their visual features and show that collections contain visually homogeneous objects. Finally, we investigate the predictability of NFT sales using simple machine learning algorithms and find that sale history and, secondarily, visual features are good predictors for price. We anticipate that these findings will stimulate further research on NFT production, adoption, and trading in different contexts.

Recent Advances in the Label-Free Characterization of Exosomes for Cancer Liquid Biopsy: From Scattering and Spectroscopy to Nanoindentation and Nanodevices.

Exosomes (EXOs) are nano-sized vesicles secreted by most cell types. They are abundant in bio-fluids and harbor specific molecular constituents from their parental cells. Due to these characteristics, EXOs have a great potential in cancer diagnostics for liquid biopsy and personalized medicine. Despite this unique potential, EXOs are not yet widely applied in clinical settings, with two main factors hindering their translational process in diagnostics. Firstly, conventional extraction methods are time-consuming, require large sample volumes and expensive equipment, and often do not provide high-purity samples. Secondly, characterization methods have some limitations, because they are often qualitative, need extensive labeling or complex sampling procedures that can induce artifacts. In this context, novel label-free approaches are rapidly emerging, and are holding potential to revolutionize EXO diagnostics. These methods include the use of nanodevices for EXO purification, and vibrational spectroscopies, scattering, and nanoindentation for characterization. In this progress report, we summarize recent key advances in label-free techniques for EXO purification and characterization. We point out that these methods contribute to reducing costs and processing times, provide complementary information compared to the conventional characterization techniques, and enhance flexibility, thus favoring the discovery of novel and unexplored EXO-based biomarkers. In this process, the impact of nanotechnology is systematically highlighted, showing how the effectiveness of these techniques can be enhanced using nanomaterials, such as plasmonic nanoparticles and nanostructured surfaces, which enable the exploitation of advanced physical phenomena occurring at the nanoscale level.

Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) detection as a rapid and convenient screening test for cystinuria.

BACKGROUND: Cystinuria is an inborn congenital disorder characterised by a defective cystine metabolism resulting in the formation of cystine stones. The Brand's test, used for diagnosis, requires dangerous substances, so has been replaced with high-performance liquid chromatography with fluorimetric detection (HPLC-FL). However, this technique requires the use of complex equipment. Infrared spectroscopy, universally used for stone analysis, recently was employed to detect insoluble cystine in urine. The aim of this study is to evaluate Infrared Spectroscopy combined with chemometric analysis as screening method to identify those patients requiring confirmation by HPLC-FL analysis. METHODS: We examined 24 h urine specimens from 57 patients. The quantitative analysis was performed by HPLC-FL. The infrared spectroscopic urine sediment analysis was performed with an ATR accessory (ATR-FTIR). Urine is centrifuged, the supernatant is discarded, and the sediment is dried on to the ATR prism surface. Statistical analysis was performed using a custom-made software developed in MATLAB environment. RESULTS: The HPLC-FL determination showed a normal excretion of cystine in 49 samples and an abnormal excretion in the remaining 8 samples. The ATR-FTIR analysis combined with a statistical approach gives a sensitivity of 1.0 and a specificity of 0.82 were obtained. CONCLUSIONS: The introduction of the ATR-FTIR technique in our clinical laboratory setting may reduce time and cost analysis for diagnosis of cystinuria.

Fourier Transform Infrared Spectroscopy as a useful tool for the automated classification of cancer cell-derived exosomes obtained under different culture conditions.

Exosomes possess great potential as cancer biomarkers in personalized medicine due to their easy accessibility and capability of representing their parental cells. To boost the translational process of exosomes in diagnostics, the development of novel and effective strategies for their label-free and automated characterization is highly desirable. In this context, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides direct access to specific biomolecular bands that give compositional information on exosomes in terms of their protein, lipid and genetic content. Here, we used FTIR spectroscopy in the mid-Infrared (mid-IR) range to study exosomes released from human colorectal adenocarcinoma HT-29 cancer cells cultured in different media. To this purpose, cells were studied in well-fed condition of growth, with 10% of exosome-depleted FBS (EVd-FBS), and under serum starvation with 0.5% EVd-FBS. Our data show the presence of statistically significant differences in the shape of the Amide I and II bands in the two conditions. Based on these differences, we showed the possibility to automatically classify cancer cell-derived exosomes using Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA); we tested the effectiveness of the classifier with a cross-validation approach, obtaining very high accuracy, precision, and recall. Aside from classification purposes, our FTIR data provide hints on the underlying cellular mechanisms responsible for the compositional differences in exosomes, suggesting a possible role of starvation-induced autophagy.

Searching for the Mechanical Fingerprint of Pre-diabetes in T1DM: A Case Report Study.

We report the case of a 38 year-old Caucasian man enrolled in a study aimed at investigating the physical properties of red blood cells (RBCs) using advanced microscopy techniques, including Atomic Force Microscopy (AFM). At the time of his first enrolment in the study, he had normal Fasting Plasma Glucose (FPG) values, a BMI of 24.1, and no other symptoms of diabetes, including fatigue, high triglycerides, low HDL cholesterol, and altered inflammatory and corpuscular RBC indices. The subject reported no family history of diabetes, obesity, and cardiovascular diseases. Despite his apparently healthy conditions, the biomechanics of his RBCs was altered, showing increased values of stiffness and viscosity. More than 1 year after the mechanical measurements, the subject was admitted to the Operational Unit of Diabetology of the Policlinico Gemelli Hospital with high blood glucose and glycosylated hemoglobin (HbA1c) levels and diagnosed with type 1 diabetes (T1DM). Here, we show these data, and we discuss the hypothesis that RBC mechanical properties could be sensitive to changes occurring during the pre-diabetic phase of T1DM.

Machine-learning assisted confocal imaging of intracellular sites of triglycerides and cholesteryl esters formation and storage.

All living systems are maintained by a constant flux of metabolic energy and, among the different reactions, the process of lipids storage and lipolysis is of fundamental importance. Current research has focused on the investigation of lipid droplets (LD) as a powerful biomarker for the early detection of metabolic and neurological disorders. Efforts in this field aim at increasing selectivity for LD detection by exploiting existing or newly synthesized probes. However, LD constitute only the final product of a complex series of reactions during which fatty acids are transformed into triglycerides and cholesterol is transformed in cholesteryl esters. These final products can be accumulated in intracellular organelles or deposits other than LD. A complete spatial mapping of the intracellular sites of triglycerides and cholesteryl esters formation and storage is, therefore, crucial to highlight any potential metabolic imbalance, thus predicting and counteracting its progression. Here, we present a machine learning assisted, polarity-driven segmentation which enables to localize and quantify triglycerides and cholesteryl esters biosynthesis sites in all intracellular organelles, thus allowing to monitor in real-time the overall process of the turnover of these non-polar lipids in living cells. This technique is applied to normal and differentiated PC12 cells to test how the level of activation of biosynthetic pathways changes in response to the differentiation process.

DHA Affects Microtubule Dynamics Through Reduction of Phospho-TCTP Levels and Enhances the Antiproliferative Effect of T-DM1 in Trastuzumab-Resistant HER2-Positive Breast Cancer Cell Lines.

Trastuzumab emtansine (T-DM1) is an anti-human epidermal growth factor receptor 2 (HER2) antibody-drug conjugated to the microtubule-targeting agent emtansine (DM1). T-DM1 is an effective agent in the treatment of patients with HER2-positive breast cancer whose disease has progressed on the first-line trastuzumab containing chemotherapy. However, both primary and acquired tumour resistance limit its efficacy. Increased levels of the phosphorylated form of Translationally Controlled Tumour Protein (phospho-TCTP) have been shown to be associated with a poor clinical response to trastuzumab therapy in HER2-positive breast cancer. Here we show that phospho-TCTP is essential for correct mitosis in human mammary epithelial cells. Reduction of phospho-TCTP levels by dihydroartemisinin (DHA) causes mitotic aberration and increases microtubule density in the trastuzumab-resistant breast cancer cells HCC1954 and HCC1569. Combinatorial studies show that T-DM1 when combined with DHA is more effective in killing breast cells compared to the effect induced by any single agent. In an orthotopic breast cancer xenograft model (HCC1954), the growth of the tumour cells resumes after having achieved a complete response to T-DM1 treatment. Conversely, DHA and T-DM1 treatment induces a severe and irreversible cytotoxic effect, even after treatment interruption, thus, improving the long-term efficacy of T-DM1. These results suggest that DHA increases the effect of T-DM1 as poison for microtubules and supports the clinical development of the combination of DHA and T-DM1 for the treatment of aggressive HER2-overexpressing breast cancer.

Aconitase 2 inhibits the proliferation of MCF-7 cells promoting mitochondrial oxidative metabolism and ROS/FoxO1-mediated autophagic response.

BACKGROUND: Deregulation of the tricarboxylic acid cycle (TCA) due to mutations in specific enzymes or defective aerobic metabolism is associated with tumour growth. Aconitase 2 (ACO2) participates in the TCA cycle by converting citrate to isocitrate, but no evident demonstrations of its involvement in cancer metabolism have been provided so far. METHODS: Biochemical assays coupled with molecular biology, in silico, and cellular tools were applied to circumstantiate the impact of ACO2 in the breast cancer cell line MCF-7 metabolism. Fluorescence lifetime imaging microscopy (FLIM) of NADH was used to corroborate the changes in bioenergetics. RESULTS: We showed that ACO2 levels are decreased in breast cancer cell lines and human tumour biopsies. We generated ACO2- overexpressing MCF-7 cells and employed comparative analyses to identify metabolic adaptations. We found that increased ACO2 expression impairs cell proliferation and commits cells to redirect pyruvate to mitochondria, which weakens Warburg-like bioenergetic features. We also demonstrated that the enhancement of oxidative metabolism was supported by mitochondrial biogenesis and FoxO1-mediated autophagy/mitophagy that sustains the increased ROS burst. CONCLUSIONS: This work identifies ACO2 as a relevant gene in cancer metabolic rewiring of MCF-7 cells, promoting a different utilisation of pyruvate and revealing the potential metabolic vulnerability of ACO2-associated malignancies.

Low-Intensity Ultrasound Induces Thermodynamic Phase Separation of Cell Membranes through a Nucleation-Condensation Process.

Membrane fluidity, a broad term adopted to describe the thermodynamic phase state of biological membranes, can be altered by local pressure variations caused by ultrasound exposure. The alterations in lipid spatial configuration and dynamics can modify their interactions with membrane proteins and activate signal transduction pathways, thus regulating several cellular functions. Here fluidity maps of murine fibroblast cells are generated at a sub-micrometric scale during ultrasound stimulation with an intensity and frequency typical of medical applications. Ultrasound induces a phase separation characterized by two-step kinetics leading to a time-dependent decrease in fluidity. First, nucleation of liquid crystallin domains with an average dimension of ∼1 µm occurs. Then, these domains condense into larger clusters with an average dimension of ∼1.5 µm. The induced phase separation could be an important driving force critical for the cellular response connecting the ultrasound-induced mechanical stress and signal transduction.

Red blood cells membrane micropolarity as a novel diagnostic indicator of type 1 and type 2 diabetes.

Classification of the category of diabetes is extremely important for clinicians to diagnose and select the correct treatment plan. Glycosylation, oxidation and other post-translational modifications of membrane and transmembrane proteins, as well as impairment in cholesterol homeostasis, can alter lipid density, packing, and interactions of Red blood cells (RBC) plasma membranes in type 1 and type 2 diabetes, thus varying their membrane micropolarity. This can be estimated, at a submicrometric scale, by determining the membrane relative permittivity, which is the factor by which the electric field between the charges is decreased relative to vacuum. Here, we employed a membrane micropolarity sensitive probe to monitor variations in red blood cells of healthy subjects (n=16) and patients affected by type 1 (T1DM, n=10) and type 2 diabetes mellitus (T2DM, n=24) to provide a cost-effective and supplementary indicator for diabetes classification. We find a less polar membrane microenvironment in T2DM patients, and a more polar membrane microenvironment in T1DM patients compared to control healthy patients. The differences in micropolarity are statistically significant among the three groups (p<0.01). The role of serum cholesterol pool in determining these differences was investigated, and other factors potentially altering the response of the probe were considered in view of developing a clinical assay based on RBC membrane micropolarity. These preliminary data pave the way for the development of an innovative assay which could become a tool for diagnosis and progression monitoring of type 1 and type 2 diabetes.

Quantitative imaging of membrane micropolarity in living cells and tissues by spectral phasors analysis.

Intracellular micropolarity is essential in several metabolic processes, as it controls membrane permeability, regulating the fluxes of molecules and energy. Here we describe a method for the determination of the micropolarity in living cells using spectral confocal microscopy. The method is based on a phasor analysis of spectrally resolved images of live cells, labelled with the solvatochromic probe Nile Red. An application is provided to extract a polarity profile from the acquired Spectral datasets, which represent the contribution of hyperpolar, polar and non-polar lipids, and to generate a micropolarity map at submicrometric spatial resolution. A metabolic parameter, representing a quantitative index of the fatty acid-triacylglycerol turnover, is also furnished. This method allows a functional profiling of cells and tissues and the detection of metabolic imbalances between lipid storage and usage. •Use of spectral resolved confocal microscopy of Nile Red labelled cells for pixel resolved determination of the membranes micropolarity.•Spectral acquisition increases the specificity and sensitivity of the detection to provide a polarity profile and a metabolic index for fatty acid-TG turnover.•Use of spectral resolved confocal microscopy of Nile Red labelled cells for pixel resolved determination of the membranes micropolarity.

Real time quantitative analysis of lipid storage and lipolysis pathways by confocal spectral imaging of intracellular micropolarity.

Organisms store fatty acids in triacylglycerols in the form of lipid droplets, or hydrolyze triacylglycerols in response to energetic demands via activation of lipolytic or storage pathways. These pathways are complex sets of sequential reactions that are finely regulated in different cell types. Here we present a high spatial and temporal resolution-based method for the quantification of the turnover of fatty acids into triglycerides in live cells without introducing sample preparation artifacts. We performed confocal spectral imaging of intracellular micropolarity in cultured insulin secreting beta cells to detect micropolarity variations as they occur in time and at different pixels of microscope images. Acquired data are then analyzed in the framework of the spectral phasors technique. The method furnishes a metabolic parameter, which quantitatively assesses fatty acids - triacylglycerols turnover and the activation of lipolysis and storage pathways. Moreover, it provides a polarity profile, which represents the contribution of hyperpolar, polar and non-polar classes of lipids. These three different classes can be visualized on the image at a submicrometer resolution, revealing the spatial localization of lipids in cells under physiological and pathological settings. This new method allows for a fine-tuned, real-time visualization of the turnover of fatty acids into triglycerides in live cells with submicrometric resolution. It also detects imbalances between lipid storage and usage, which may lead to metabolic disorders within living cells and organisms.

Systemic profiling of ectopic fat deposits in the reproductive tract of dairy cows.

During the transition period, high-yielding dairy cows suffer from negative energy balance, intense lipomobilization and impaired lipid metabolism; this metabolic condition can lead to overburdened triglycerides accumulation in the liver, known as liver lipidosis, which has been associated to impaired fertility in dairy cows. The mechanisms of this impairment can be in principle correlated with the presence and the extent of ectopic fat depots. However, current methods for evaluating fat accumulation in liver and in the reproductive tract suffer from low resolution, sensitivity, and specificity. Confocal microscopes are equipped with Gallium arsenide phosphide detectors, thus enabling the acquisition of intense signals from tissue biopsies. This method could differentiate whether fat deposition occurred without requiring sample sectioning. Here, we examined with this technique liver, uterine and ovarian samples of heifers and regularly slaughtered repeat breeder and overconditioned dairy cows, to quantify lipid droplets and depots at a submicrometer scale with high specificity. With the aid of this technique, we found lipid depots in uterine and ovarian specimens. Moreover, we found that the size and number of depots increased with the degree of liver lipidosis. Further studies are needed to elucidate the relationship between the severity and extent of these deposits and the fertility of lactating dairy cows. Since tissues other than liver display different characteristic lipid droplet distributions, this technique can be potentially employed to shed new light on the pathogenesis of lipidosis and to assess new risk factors for infertility.