Autofluorescence lifetime flow cytometry with time-correlated single photon counting.

Autofluorescence lifetime imaging microscopy (FLIM) is sensitive to metabolic changes in single cells based on changes in the protein-binding activities of the metabolic co-enzymes NAD(P)H. However, FLIM typically relies on time-correlated single-photon counting (TCSPC) detection electronics on laser-scanning microscopes, which are expensive, low-throughput, and require substantial post-processing time for cell segmentation and analysis. Here, we present a fluorescence lifetime-sensitive flow cytometer that offers the same TCSPC temporal resolution in a flow geometry, with low-cost single-photon excitation sources, a throughput of tens of cells per second, and real-time single-cell analysis. The system uses a 375 nm picosecond-pulsed diode laser operating at 50 MHz, alkali photomultiplier tubes, an FPGA-based time tagger, and can provide real-time phasor-based classification (i.e., gating) of flowing cells. A CMOS camera produces simultaneous brightfield images using far-red illumination. A second PMT provides two-color analysis. Cells are injected into the microfluidic channel using a syringe pump at 2-5 mm/s with nearly 5 ms integration time per cell, resulting in a light dose of 2.65 J/cm2 that is well below damage thresholds (25 J/cm2 at 375 nm). Our results show that cells remain viable after measurement, and the system is sensitive to autofluorescence lifetime changes in Jurkat T cells with metabolic perturbation (sodium cyanide), quiescent versus activated (CD3/CD28/CD2) primary human T cells, and quiescent versus activated primary adult mouse neural stem cells, consistent with prior studies using multiphoton FLIM. This TCSPC-based autofluorescence lifetime flow cytometer provides a valuable label-free method for real-time analysis of single-cell function and metabolism with higher throughput than laser-scanning microscopy systems.

Preclinical Models of Anal Cancer Combined-Modality Therapy.

INTRODUCTION: There have been no significant changes in anal cancer treatment options in 4 decades. In this study, we highlight two preclinical models designed to assess anal cancer treatments. MATERIALS AND METHODS: Transgenic K14E6/E7 mice were treated with 7, 12-dimethylbenz(a)anthracene until anal tumors developed. Mice were treated with localized radiation in addition to chemotherapy (combined-modality therapy [CMT]) and compared to no treatment control (NTC). K14E6/E7 mouse anal spheroids with and without Pik3ca mutations were isolated and treated with vehicle, LY3023414 (LY3) (a drug previously shown to be effective in cancer prevention), CMT, or CMT + LY3. RESULTS: In the in vivo model, there was a significant increase in survival in the CMT group compared to the NTC group (P = 0.0392). In the ex vivo model, there was a significant decrease in the mean diameter of CMT and CMT + LY3-treated spheroids compared to vehicle (P ≤ 0.0001). For LY3 alone compared to vehicle, there was a statistically significant decrease in spheroid size in the K14E6/E7 group without mutation (P = 0.0004). CONCLUSIONS: We have provided proof of concept for two preclinical anal cancer treatment models that allow for the future testing of novel therapies for anal cancer.

Carbomer-based adjuvant elicits CD8 T-cell immunity by inducing a distinct metabolic state in cross-presenting dendritic cells.

There is a critical need for adjuvants that can safely elicit potent and durable T cell-based immunity to intracellular pathogens. Here, we report that parenteral vaccination with a carbomer-based adjuvant, Adjuplex (ADJ), stimulated robust CD8 T-cell responses to subunit antigens and afforded effective immunity against respiratory challenge with a virus and a systemic intracellular bacterial infection. Studies to understand the metabolic and molecular basis for ADJ's effect on antigen cross-presentation by dendritic cells (DCs) revealed several unique and distinctive mechanisms. ADJ-stimulated DCs produced IL-1ß and IL-18, suggestive of inflammasome activation, but in vivo activation of CD8 T cells was unaffected in caspase 1-deficient mice. Cross-presentation induced by TLR agonists requires a critical switch to anabolic metabolism, but ADJ enhanced cross presentation without this metabolic switch in DCs. Instead, ADJ induced in DCs, an unique metabolic state, typified by dampened oxidative phosphorylation and basal levels of glycolysis. In the absence of increased glycolytic flux, ADJ modulated multiple steps in the cytosolic pathway of cross-presentation by enabling accumulation of degraded antigen, reducing endosomal acidity and promoting antigen localization to early endosomes. Further, by increasing ROS production and lipid peroxidation, ADJ promoted antigen escape from endosomes to the cytosol for degradation by proteasomes into peptides for MHC I loading by TAP-dependent pathways. Furthermore, we found that induction of lipid bodies (LBs) and alterations in LB composition mediated by ADJ were also critical for DC cross-presentation. Collectively, our model challenges the prevailing metabolic paradigm by suggesting that DCs can perform effective DC cross-presentation, independent of glycolysis to induce robust T cell-dependent protective immunity to intracellular pathogens. These findings have strong implications in the rational development of safe and effective immune adjuvants to potentiate robust T-cell based immunity.

Technologies to Assess Drug Response and Heterogeneity in Patient-Derived Cancer Organoids.

Patient-derived cancer organoids (PDCOs) are organotypic 3D cultures grown from patient tumor samples. PDCOs provide an exciting opportunity to study drug response and heterogeneity within and between patients. This research can guide new drug development and inform clinical treatment planning. We review technologies to assess PDCO drug response and heterogeneity, discuss best practices for clinically relevant drug screens, and assert the importance of quantifying single-cell and organoid heterogeneity to characterize response. Autofluorescence imaging of PDCO growth and metabolic activity is highlighted as a compelling method to monitor single-cell and single-organoid response robustly and reproducibly. We also speculate on the future of PDCOs in clinical practice and drug discovery.Future development will require standardization of assessment methods for both morphology and function in PDCOs, increased throughput for new drug development, prospective validation with patient outcomes, and robust classification algorithms.

Prostate cancer cells demonstrate unique metabolism and substrate adaptability acutely after androgen deprivation therapy.

BACKGROUND: Androgen deprivation therapy (ADT) has been the standard of care for advanced hormone-sensitive prostate cancer (PC), yet tumors invariably develop resistance resulting in castrate-resistant PC. The acute response of cancer cells to ADT includes apoptosis and cell death, but a large fraction remains arrested but viable. In this study, we focused on intensively characterizing the early metabolic changes that result after ADT to define potential metabolic targets for treatment. METHODS: A combination of mass spectrometry, optical metabolic imaging which noninvasively measures drug responses in cells, oxygen consumption rate, and protein expression analysis was used to characterize and block metabolic pathways over several days in multiple PC cell lines with variable hormone response status including ADT sensitive lines LNCaP and VCaP, and resistant C4-2 and DU145. RESULTS: Mass spectrometry analysis of LNCaP pre- and postexposure to ADT revealed an abundance of glycolytic intermediates after ADT. In LNCaP and VCaP, a reduction in the optical redox ratio [NAD(P)H/FAD], extracellular acidification rate, and a downregulation of key regulatory enzymes for fatty acid and glutamine utilization was acutely observed after ADT. Screening several metabolic inhibitors revealed that blocking fatty acid oxidation and synthesis reversed this stress response in the optical redox ratio seen with ADT alone in LNCaP and VCaP. In contrast, both cell lines demonstrated increased sensitivity to the glycolytic inhibitor 2-Deoxy- d-glucose(2-DG) and maintained sensitivity to electron transport chain inhibitor Malonate after ADT exposure. ADT followed by 2-DG results in synergistic cell death, a result not seen with simultaneous administration. CONCLUSIONS: Hormone-sensitive PC cells displayed altered metabolic profiles early after ADT including an overall depression in energy metabolism, induction of a quiescent/senescent phenotype, and sensitivity to selected metabolic inhibitors. Glycolytic blocking agents (e.g., 2-DG) as a sequential treatment after ADT may be promising.

Reproducibility and staging of 3D human retinal organoids across multiple pluripotent stem cell lines.

Numerous protocols have been described for producing neural retina from human pluripotent stem cells (hPSCs), many of which are based on the culture of 3D organoids. Although nearly all such methods yield at least partial segments of retinal structure with a mature appearance, variabilities exist within and between organoids that can change over a protracted time course of differentiation. Adding to this complexity are potential differences in the composition and configuration of retinal organoids when viewed across multiple differentiations and hPSC lines. In an effort to understand better the current capabilities and limitations of these cultures, we generated retinal organoids from 16 hPSC lines and monitored their appearance and structural organization over time by light microscopy, immunocytochemistry, metabolic imaging and electron microscopy. We also employed optical coherence tomography and 3D imaging techniques to assess and compare whole or broad regions of organoids to avoid selection bias. Results from this study led to the development of a practical staging system to reduce inconsistencies in retinal organoid cultures and increase rigor when utilizing them in developmental studies, disease modeling and transplantation.

Time-domain single photon-excited autofluorescence lifetime for label-free detection of T cell activation.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique, capable of label-free assessment of the metabolic state and function within single cells. The FLIM measurements of autofluorescence were recently shown to be sensitive to the functional state and subtype of T cells. Therefore, autofluorescence FLIM could improve cell manufacturing technologies for adoptive immunotherapy, which currently require a time-intensive process of cell labeling with fluorescent antibodies. However, current autofluorescence FLIM implementations are typically too slow, bulky, and prohibitively expensive for use in cell manufacturing pipelines. Here we report a single photon-excited confocal whole-cell autofluorescence system that uses fast field-programmable gate array-based time tagging electronics to achieve time-correlated single photon counting (TCSPC) of single-cell autofluorescence. The system includes simultaneous near-infrared bright-field imaging and is sensitive to variations in the fluorescence decay profile of the metabolic coenzyme NAD(P)H in human T cells due to the activation state. The classification of activated and quiescent T cells achieved high accuracy and precision (area under the receiver operating characteristic curve, AUC = 0.92). The lower-cost, higher acquisition speed, and resistance to pile-up effects at high photon flux compared to traditional multiphoton-excited FLIM and TCSPC implementations with similar SNR make this system attractive for integration into flow cytometry, sorting, and quality control in cell manufacturing.

Microfluidic Tumor-on-a-Chip Model to Study Tumor Metabolic Vulnerability.

Tumor-specific metabolic adaptations offer an interesting therapeutic opportunity to selectively destroy cancer cells. However, solid tumors also present gradients of nutrients and waste products across the tumor mass, forcing tumor cells to adapt their metabolism depending on nutrient availability in the surrounding microenvironment. Thus, solid tumors display a heterogenous metabolic phenotype across the tumor mass, which complicates the design of effective therapies that target all the tumor populations present. In this work, we used a microfluidic device to study tumor metabolic vulnerability to several metabolic inhibitors. The microdevice included a central chamber to culture tumor cells in a three-dimensional (3D) matrix, and a lumen in one of the chamber flanks. This design created an asymmetric nutrient distribution across the central chamber, generating gradients of cell viability. The results revealed that tumor cells located in a nutrient-enriched environment showed low to no sensitivity to metabolic inhibitors targeting glycolysis, fatty acid oxidation, or oxidative phosphorylation. Conversely, when cell density inside of the model was increased, compromising nutrient supply, the addition of these metabolic inhibitors disrupted cellular redox balance and led to tumor cell death.

BET inhibitors reduce cell size and induce reversible cell cycle arrest in AML.

Inhibitors of the bromodomain and extraterminal domain family (BETi) offer a new approach to treat hematological malignancies, with leukemias containing mixed lineage leukemia rearrangements being especially sensitive due to a reliance on the regulation of transcription elongation. We explored the mechanism of action of BETi in cells expressing the t(8;21), and show that these compounds reduced the size of acute myeloid leukemia cells, triggered a rapid but reversible G0 /G1 arrest, and with time, cause cell death. Meta-analysis of PRO-seq data identified ribosomal genes, which are regulated by MYC, were downregulated within 3 hours of addition of the BETi. This reduction of MYC regulated metabolic genes coincided with the loss of mitochondrial respiration and large reductions in the glycolytic rate. In addition, gene expression analysis showed that transcription of BCL2 was rapidly affected by BETi but this did not cause dramatic increases in cell death. Cell cycle arrest, lowered metabolic activity, and reduced BCL2 levels suggested that a second compound was needed to push these cells over the apoptotic threshold. Indeed, low doses of the BCL2 inhibitor, venetoclax, in combination with the BETi was a potent combination in t(8;21) containing cells. Thus, BET inhibitors that affect MYC and BCL2 expression should be considered for combination therapy with venetoclax.

Development of a Microfluidic Array to Study Drug Response in Breast Cancer.

Luminal geometries are common structures in biology, which are challenging to mimic using conventional in vitro techniques based on the use of Petri dishes. In this context, microfluidic systems can mimic the lumen geometry, enabling a large variety of studies. However, most microfluidic models still rely on polydimethylsiloxane (PDMS), a material that is not amenable for high-throughput fabrication and presents some limitations compared with other materials such as polystyrene. Thus, we have developed a microfluidic device array to generate multiple bio-relevant luminal structures utilizing polystyrene and micro-milling. This platform offers a scalable alternative to conventional microfluidic devices designed in PDMS. Additionally, the use of polystyrene has well described advantages, such as lower permeability to hydrophobic molecules compared with PDMS, while maintaining excellent viability and optical properties. Breast cancer cells cultured in the devices exhibited high cell viability similar to PDMS-based microdevices. Further, co-culture experiments with different breast cell types showed the potential of the model to study breast cancer invasion. Finally, we demonstrated the potential of the microfluidic array for drug screening, testing chemotherapy drugs and photodynamic therapy agents for breast cancer.

Photothermal optical coherence tomography of indocyanine green in ex vivo eyes.

Indocyanine green (ICG) is routinely used during surgery to stain the inner limiting membrane (ILM) and provide contrast on white light surgical microscopy. While translation of optical coherence tomography (OCT) for intraoperative imaging during ophthalmic surgery has enhanced visualization, the ILM remains difficult to distinguish from underlying retinal structures and ICG does not provide additional OCT contrast. We present photothermal OCT (PT-OCT) for high-specificity detection of ICG on retinal OCT images. We demonstrate our technique by performing an ILM peel in ex vivo eyes using low ICG concentrations and laser powers. These results establish the feasibility of PT-OCT for intraoperative guidance during retinal surgery.

Signal Transducer and Activator of Transcription 3, Mediated Remodeling of the Tumor Microenvironment Results in Enhanced Tumor Drug Delivery in a Mouse Model of Pancreatic Cancer.

BACKGROUND & AIMS: A hallmark of pancreatic ductal adenocarcinoma (PDAC) is the presence of a dense desmoplastic reaction (stroma) that impedes drug delivery to the tumor. Attempts to deplete the tumor stroma have resulted in formation of more aggressive tumors. We have identified signal transducer and activator of transcription (STAT) 3 as a biomarker of resistance to cytotoxic and molecularly targeted therapy in PDAC. The purpose of this study is to investigate the effects of targeting STAT3 on the PDAC stroma and on therapeutic resistance. METHODS: Activated STAT3 protein expression was determined in human pancreatic tissues and tumor cell lines. In vivo effects of AZD1480, a JAK/STAT3 inhibitor, gemcitabine or the combination were determined in Ptf1a(cre/+);LSL-Kras(G12D/+);Tgfbr2(flox/flox) (PKT) mice and in orthotopic tumor xenografts. Drug delivery was analyzed by matrix-assisted laser desorption/ionization imaging mass spectrometry. Collagen second harmonic generation imaging quantified tumor collagen alignment and density. RESULTS: STAT3 activation correlates with decreased survival and advanced tumor stage in patients with PDAC. STAT3 inhibition combined with gemcitabine significantly inhibits tumor growth in both an orthotopic and the PKT mouse model of PDAC. This combined therapy attenuates in vivo expression of SPARC, increases microvessel density, and enhances drug delivery to the tumor without depletion of stromal collagen or hyaluronan. Instead, the PDAC tumors demonstrate vascular normalization, remodeling of the tumor stroma, and down-regulation of cytidine deaminase. CONCLUSIONS: Targeted inhibition of STAT3 combined with gemcitabine enhances in vivo drug delivery and therapeutic response in PDAC. These effects occur through tumor stromal remodeling and down-regulation of cytidine deaminase without depletion of tumor stromal content.

Deconvolution of fluorescence lifetime imaging microscopy by a library of exponentials.

Fluorescence lifetime microscopy imaging (FLIM) is an optic technique that allows a quantitative characterization of the fluorescent components of a sample. However, for an accurate interpretation of FLIM, an initial processing step is required to deconvolve the instrument response of the system from the measured fluorescence decays. In this paper, we present a novel strategy for the deconvolution of FLIM data based on a library of exponentials. Our approach searches for the scaling coefficients of the library by non-negative least squares approximations plus Thikonov/l(2) or l(1) regularization terms. The parameters of the library are given by the lower and upper bounds in the characteristic lifetimes of the exponential functions and the size of the library, where we observe that this last variable is not a limiting factor in the resulting fitting accuracy. We compare our proposal to nonlinear least squares and global non-linear least squares estimations with a multi-exponential model, and also to constrained Laguerre-base expansions, where we visualize an advantage of our proposal based on Thikonov/l(2) regularization in terms of estimation accuracy, computational time, and tuning strategy. Our validation strategy considers synthetic datasets subject to both shot and Gaussian noise and samples with different lifetime maps, and experimental FLIM data of ex-vivo atherosclerotic plaques and human breast cancer cells.

Classification of Neural Stem Cell Activation State In Vitro using Autofluorescence.

Neural stem cells (NSCs) divide and produce newborn neurons in the adult brain through a process called adult neurogenesis. Adult NSCs are primarily quiescent, a reversible cell state where they have exited the cell cycle (G0) yet remain responsive to the environment. In the first step of adult neurogenesis, quiescent NSCs (qNSCs) receive a signal and activate, exiting quiescence and re-entering the cell cycle. Thus, understanding the regulators of NSC quiescence and quiescence exit is critical for future strategies targeting adult neurogenesis. However, our understanding of NSC quiescence is limited by technical constraints in identifying quiescent NSCs (qNSCs) and activated NSCs (aNSCs). This protocol describes a new approach to identify and enrich qNSCs and aNSCs generated in in vitro cultures by imaging NSC autofluorescence. First, this protocol describes how to use a confocal microscope to identify autofluorescent markers of qNSCs and aNSCs to classify NSC activation state using autofluorescence intensity. Second, this protocol describes how to use a fluorescent activated cell sorter (FACS) to classify NSC activation state and enrich samples for qNSCs or aNSCs using autofluorescence intensity. Third, this protocol describes how to use a multiphoton microscope to perform fluorescence lifetime imaging (FLIM) at single-cell resolution, classify NSC activation state, and track the dynamics of quiescent exit using both autofluorescence intensities and fluorescence lifetimes. Thus, this protocol provides a live-cell, label-free, single-cell resolution toolkit for studying NSC quiescence and quiescence exit.

Metabolic changes in Toxoplasma gondii-infected host cells measured by autofluorescence imaging.

Toxoplasma gondii, the causative agent of toxoplasmosis, is an obligate intracellular parasite that infects warm-blooded vertebrates across the world. In humans, seropositivity rates of T. gondii range from 10% to 90% across communities. Despite its prevalence, few studies address how T. gondii infection changes the metabolism of host cells. In this study, we investigate how T. gondii manipulates the host cell metabolic environment by monitoring the metabolic response over time using noninvasive autofluorescence lifetime imaging of single cells, metabolite analysis, extracellular flux analysis, and reactive oxygen species (ROS) production. Autofluorescence lifetime imaging indicates that infected host cells become more oxidized and have an increased proportion of bound NAD(P)H compared to uninfected controls. Over time, infected cells also show decreases in levels of intracellular glucose and lactate, increases in oxygen consumption, and variability in ROS production. We further examined changes associated with the pre-invasion "kiss and spit" process using autofluorescence lifetime imaging, which also showed a more oxidized host cell with an increased proportion of bound NAD(P)H over 48 hours compared to uninfected controls, suggesting that metabolic changes in host cells are induced by T. gondii kiss and spit even without invasion.IMPORTANCEThis study sheds light on previously unexplored changes in host cell metabolism induced by T. gondii infection using noninvasive, label-free autofluorescence imaging. In this study, we use optical metabolic imaging (OMI) to measure the optical redox ratio (ORR) in conjunction with fluorescence lifetime imaging microscopy (FLIM) to noninvasively monitor single host cell response to T. gondii infection over 48 hours. Collectively, our results affirm the value of using autofluorescence lifetime imaging to noninvasively monitor metabolic changes in host cells over the time course of a microbial infection. Understanding this metabolic relationship between the host cell and the parasite could uncover new treatment and prevention options for T. gondii infections worldwide.

Naive primary neutrophils play a dual role in the tumor microenvironment.

The tumor microenvironment (TME) is characterized by a network of cancer cells, recruited immune cells and extracellular matrix (ECM) in a hypoxic microenvironment. However, the specific role of neutrophils during tumor development, and their interactions with other immune cells is still not well understood. Thus, there is a need to investigate the interaction between primary neutrophils and natural killer cells and the resulting effects on tumor development. Here we use both standard well plate culture and an under oil microfluidic (UOM) assay with an integrated extracellular cell matrix (ECM) bridge to elucidate how naive primary neutrophils respond to both patient derived tumor cells and tumor cell lines. Our data demonstrated that both patient derived head and neck squamous cell carcinoma (HNSCC) tumor cells and MDA-MB-231 breast cancer cells trigger cluster formation in neutrophils, and the swarm of neutrophils restricts tumor invasion through the generation of reactive oxygen species (ROS) and neutrophil extracellular trap (NETs) release within the neutrophil cluster. However, we also observed that the presence of neutrophils downregulates granzyme B in NK-92 cells and the resulting NETs can obstruct NK cells from penetrating the tumor mass in vitro suggesting a dual role for neutrophils in the TME. Further, using label-free optical metabolic imaging (OMI) we observed changes in the metabolic activities of primary neutrophils during the different swarming phases when challenged with tumor cells. Finally, our data demonstrates that neutrophils in direct contact, or in close proximity, with tumor cells exhibit greater metabolic activities (lower nicotinamide adenine dinucleotide phosphate (NAD(P)H) mean lifetime) compared to non-contact neutrophils.

Autofluorescence lifetime flow cytometry with time-correlated single photon counting.

Autofluorescence lifetime imaging microscopy (FLIM) is sensitive to metabolic changes in single cells based on changes in the protein-binding activities of the metabolic co-enzymes NAD(P)H. However, FLIM typically relies on time-correlated single-photon counting (TCSPC) detection electronics on laser-scanning microscopes, which are expensive, low-throughput, and require substantial post-processing time for cell segmentation and analysis. Here, we present a fluorescence lifetime-sensitive flow cytometer that offers the same TCSPC temporal resolution in a flow geometry, with low-cost single-photon excitation sources, a throughput of tens of cells per second, and real-time single-cell analysis. The system uses a 375nm picosecond-pulsed diode laser operating at 50MHz, alkali photomultiplier tubes, an FPGA-based time tagger, and can provide real-time phasor-based classification ( i.e ., gating) of flowing cells. A CMOS camera produces simultaneous brightfield images using far-red illumination. A second PMT provides two-color analysis. Cells are injected into the microfluidic channel using a syringe pump at 2-5 mm/s with nearly 5ms integration time per cell, resulting in a light dose of 2.65 J/cm 2 that is well below damage thresholds (25 J/cm 2 at 375 nm). Our results show that cells remain viable after measurement, and the system is sensitive to autofluorescence lifetime changes in Jurkat T cells with metabolic perturbation (sodium cyanide), quiescent vs. activated (CD3/CD28/CD2) primary human T cells, and quiescent vs. activated primary adult mouse neural stem cells, consistent with prior studies using multiphoton FLIM. This TCSPC-based autofluorescence lifetime flow cytometer provides a valuable label-free method for real-time analysis of single-cell function and metabolism with higher throughput than laser-scanning microscopy systems.

Same People, Different Results: Categorizing Cancer Registry Cases Across the Rural-Urban Continuum.

BACKGROUND: Many rural-urban indexes are utilized in cancer research. This variation introduces inconsistencies between studies. Recommendations on index use have prioritized geographical unit over feasibility of inclusion in analysis. We evaluated rural-urban indexes and recommend one for use to increase comparability across studies. METHODS: We assessed 9 US rural-urban indexes regarding their respective rural and urban code ranges; geographical unit, land area, and population distributions; percent agreement; suitability for analysis; and integration feasibility for national, state, and local cancer research. We referenced 1569 Wisconsin Pancreatic Cancer Registry patients to demonstrate how index choice affects patient categorization. RESULTS: Six indexes categorized rural and urban areas. Indexes agreed on binary rural-urban designation for 88.8% of the US population. As ternary variables, they agreed for 83.4%. For cancer registry patients, this decreased to 73.4% and 60.4% agreement, respectively. Rural-Urban Continuum Codes (RUCC) performed the best in differentiating metropolitan, micropolitan, and rural counties; availability for retrospective and prospective studies; and continuous coding for analysis. CONCLUSIONS: Urban/rural patient categorization changed with index selection. We conclude that RUCC is an appropriate and feasible rural-urban index to include in cancer research, as it is standardly available in national cancer registries, can be matched to patient's county of residence for local research, and it had the least amount of fluctuation of the indices analyzed. Utilizing RUCC as a continuous variable across studies with a rural-urban component will increase reproducibility and comparability of results and eliminate rural-urban index choice as a potential source of discrepancy between studies.

Development of a multilayer fetal membrane material model calibrated using bulge inflation mechanical tests.

The fetal membranes are an essential mechanical structure for pregnancy, protecting the developing fetus in an amniotic fluid environment and rupturing before birth. In cooperation with the cervix and the uterus, the fetal membranes support the mechanical loads of pregnancy. Structurally, the fetal membranes comprise two main layers: the amnion and the chorion. The mechanical characterization of each layer is crucial to understanding how each layer contributes to the structural performance of the whole membrane. The in-vivo mechanical loading of the fetal membranes and the amount of tissue stress generated in each layer throughout gestation remains poorly understood, as it is difficult to perform direct measurements on pregnant patients. Finite element analysis of pregnancy offers a computational method to explore how anatomical and tissue remodeling factors influence the load-sharing of the uterus, cervix, and fetal membranes. To aid in the formulation of such computational models of pregnancy, this work develops a fiber-based multilayer fetal membrane model that captures its response to previously published bulge inflation loading data. First, material models for the amnion, chorion, and maternal decidua are formulated, informed, and validated by published data. Then, the behavior of the fetal membrane as a layered structure was analyzed, focusing on the respective stress distribution and thickness variation in each layer. The layered computational model captures the overall behavior of the fetal membranes, with the amnion being the mechanically dominant layer. The inclusion of fibers in the amnion material model is an important factor in obtaining reliable fetal membrane behavior according to the experimental dataset. These results highlight the potential of this layered model to be integrated into larger biomechanical models of the gravid uterus and cervix to study the mechanical mechanisms of preterm birth.

Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images.

Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level information without extrinsic labels. However, traditional cell segmentation tools are often optimized for high signal-to-noise ratio (SNR) images, such as fluorescently labeled cells, and unsurprisingly perform poorly on low SNR autofluorescence images. Therefore, new cell segmentation tools are needed for autofluorescence microscopy. Cellpose is a deep learning network that is generalizable across diverse cell microscopy images and automatically segments single cells to improve throughput and reduce inter-human biases. This study aims to validate Cellpose for autofluorescence imaging, specifically from multiphoton intensity images of NAD(P)H. Manually segmented nuclear masks of NAD(P)H images were used to train new Cellpose models. These models were applied to PANC-1 cells treated with metabolic inhibitors and patient-derived cancer organoids (across 9 patients) treated with chemotherapies. These datasets include co-registered fluorescence lifetime imaging microscopy (FLIM) of NAD(P)H and FAD, so fluorescence decay parameters and the optical redox ratio (ORR) were compared between masks generated by the new Cellpose model and manual segmentation. The Dice score between repeated manually segmented masks was significantly lower than that of repeated Cellpose masks (p<0.0001) indicating greater reproducibility between Cellpose masks. There was also a high correlation (R2>0.9) between Cellpose and manually segmented masks for the ORR, mean NAD(P)H lifetime, and mean FAD lifetime across 2D and 3D cell culture treatment conditions. Masks generated from Cellpose and manual segmentation also maintain similar means, variances, and effect sizes between treatments for the ORR and FLIM parameters. Overall, Cellpose provides a fast, reliable, reproducible, and accurate method to segment single cells in autofluorescence microscopy images such that functional changes in cells are accurately captured in both 2D and 3D culture.