Biology subjects

Pham, D. L.

Publications and source records attributed to Pham, D. L..

7 recordsLinked to original sources

bioRxiv2025

Autofluorescence imaging reveals the impact of cryopreservation on T cell metabolism and activation response

Cryopreservation or the process of freezing cells is a cornerstone of most cell therapy protocols. Optimization of cryopreservation protocols and cryoprotectant agents to improve cell viability and functionality is under further investigation. However, the impact of cryopreservation on cellular metabolism and function immediately post-thaw is not fully understood. Here, we used label-free, non-invasive optical metabolic imaging (OMI) of NAD(P)H and FAD to characterize the activation response of frozen T cells from healthy donors and lymphoma patients post-thaw. Using OMI, we identified significant metabolic shift, along with delayed and diminished activation response in healthy donor T cells throughout the first 4.5 hours upon thawing. In cryopreserved peripheral T cells from lymphoma patients in our bispecific CD19/CD20 CAR T therapy clinical trial, OMI could identify early metabolic stress and allowed gating of metabolically-fit cells associated with post-thaw viability. Notably, in our pilot study, only metabolically-fit T cells from complete responders exhibited metabolic responses to activating stimuli within the first 4.5 hours post-thaw. Overall, our findings suggest that 4-5 hours post-thaw is a critical time window to assess the impact of cryopreservation and thawing, and support the potential of OMI to optimize cryopreservation protocols and evaluate patient T cell quality for cell therapy.

immunology↗

bioRxiv2025

Characterization of mechanical tissue properties in post-mortem human brain using magnetic resonance elastography

Traumatic brain injury (TBI) is a serious health condition that can cause neurological dysfunction to varying degrees depending on the nature of the mechanical insult. In biomechanical studies of TBI under high loading conditions, post-mortem human subjects (PMHS) are often used since ethical concerns prohibit such experiments in living human subjects. Because PMHS brains undergo significant changes following death, it is important to understand the relationship between the mechanical properties of PMHS brain tissue and living tissue. In this study, we performed magnetic resonance elastography (MRE) on three PMHS specimens to estimate the material properties of the cadaveric brain, namely the storage modulus and the loss modulus, as well as the resulting shear stiffness and damping ratio. We also performed longitudinal MRE scans on one of the PMHS over the span of two months to investigate the evolution of tissue properties with post-mortem degradation. In comparison to in vivo subjects of age range 70-75 years, a substantially higher stiffness (mean: 5.96kPa) and lower damping ratio (mean: 0.09) were found in PMHS models. This study also revealed an initial increase in shear stiffness up to the seventh day post-mortem, followed by a steady decrease by the fifty-eighth day. However, the damping ratio displayed an opposite trend to that of shear stiffness. These changes were heterogeneous across brain regions. The collected measurements and analysis elucidate the changes in mechanical properties in post-mortem subjects, and can be used to build and validate computational models of TBI.

neuroscience↗

bioRxiv2025

Segmentation-guided photon pooling enables robust single cell analysis and fast fluorescence lifetime imaging microscopy

Fluorescence lifetime imaging microscopy (FLIM) can probe the metabolic environment of living cells in a label-free and non-invasive manner. However, endogenous fluorophores have low absorption and quantum yields, which necessitates long integration times to acquire the high photon counts needed for accurate pixel-wise multi-exponential decay fitting. Here, we present a region-of-interest photon pooling technique to expedite label-free, single cell FLIM acquisition and analysis. As a result, we achieved single-cell metabolic information at intervals as low as one second and acquired large FLIM mosaics 15 times faster than would be possible with conventional pixel-level analysis. This technique is computationally light, does not require machine learning algorithms, and has been integrated with commonly used analysis software and file types.

cell biology↗

bioRxiv2024

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/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 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.

cell biology↗

bioRxiv2024

Label free metabolic imaging to enhance the efficacy of Chimeric Antigen Receptor T cell therapy

Chimeric antigen receptor (CAR) T cell therapy for solid tumors remains challenging due to the complex manufacturing process and the immunosuppressive tumor microenvironment. The manufacturing condition directly impacts CAR T cell yield, phenotype, and metabolism, which correlate with in vivo potency and persistence. Optical metabolic imaging (OMI) is a non-invasive, label-free method to evaluate single cell metabolism based on autofluorescent metabolic coenzymes NAD(P)H and FAD. Using OMI, we identified the dominating impacts of media composition over the selection of antibody stimulation and/or cytokines on anti-GD2 CAR T cell metabolism, activation strength and kinetics, and phenotype. We demonstrated that OMI parameters were indicative of cell cycle stage and optimal gene transfer conditions for both viral transduction and electroporation-based CRISPR/Cas9. Notably, OMI accurately predicted oxidative metabolic phenotype of virus-free CRISPR-edited anti-GD2 CAR T cells that correlated to higher in vivo potency against neuroblastoma. Our data supports OMIs potential as a robust, sensitive analytical tool that enables dynamic and optimal manufacturing conditions for increased CAR T cell yield and metabolic fitness. One sentence summaryAutofluorescence imaging informs manufacturing conditions that enhance yield and metabolic fitness of CAR T cells for neuroblastoma.

immunology↗

bioRxiv2021

In Vivo MRI of Endogenous Remyelination in a Nonhuman Primate Model of Multiple Sclerosis

Remyelination is crucial for recovery from inflammatory demyelination in multiple sclerosis (MS). Investigating remyelination in vivo using magnetic resonance imaging (MRI) is difficult in MS, where collecting serial short-interval scans is challenging. Using experimental autoimmune encephalomyelitis (EAE) in common marmosets, a model of MS that recapitulates focal cerebral MS lesions, we investigated whether remyelination can be detected and characterized noninvasively. In 6 animals followed with multisequence 7-tesla MRI, 36 focal lesions, classified as demyelinated or remyelinated based on signal intensity on proton density-weighted images, were subsequently assessed with histopathology. Remyelination occurred in 5 of 6 marmosets and 51% of lesions. Radiological-pathological comparison showed high sensitivity (88%) and specificity (90%) for detecting remyelination by in vivo MRI. This study demonstrates the prevalence of spontaneous remyelination in marmoset EAE and the ability of in vivo MRI to detect it, with implications for preclinical testing of pro-remyelinating agents and translation to clinical practice.

neuroscience↗

bioRxiv2021

Validation of Data Acquisition and Phase Estimation for Quantitative Susceptibility Mapping with a Rotating-Tube Phantom

PurposeQuantitative Susceptibility Mapping (QSM) is an MRI tool with the potential to reveal pathological changes from magnetic susceptibility measurements. Before phase data can be used to recover susceptibility ({Delta}{chi}), the QSM process begins with two steps: data acquisition and phase estimation. We assess the performance of these steps, when applied without user intervention, on several variations of a phantom imaging task. ApproachWe used a rotating-tube phantom with five tubes ranging from {Delta}{chi}=0.05 ppm to {Delta}{chi}=0.336 ppm. MRI data was acquired at nine angles of rotation for four different pulse sequences. The images were processed by 10 phase estimation algorithms including Laplacian, region-growing, branch-cut, temporal unwrapping and maximum-likelihood methods. We analyzed errors between measured and expected phase using the probability mass function and Cumulative Distribution Function. ResultsRepeatable acquisition and estimation methods were identified based on the probability of relative phase errors. For single-echo GRE and segmented EPI sequences, a region-growing method was most reliable with Pr(relative error<0.1)=0.95 and 0.90 respectively. For multi-echo sequences, a Maximum-Likelihood method was most reliable with Pr(relative error<0.1)=0.97. The most repeatable multi-echo methods outperformed the most repeatable single-echo methods. ConclusionsWe found a wide range of repeatability and reproducibility for off-the-shelf MRI acquisition and phase estimation approaches. The error was dominated in many cases by spatially discontinuous phase unwrapping errors. Any post-processing applied on erroneous phase estimates, such as QSMs background field removal and dipole inversion, would suffer from error propagation. Our paradigm identifies methods that yield consistent and accurate phase estimates that would ultimately yield consistent and accurate {Delta}{chi} estimates.

bioengineering↗