Fluorescence Microscopy Images Research Articles

Chlorin Conjugates in Photodynamic Chemotherapy for Triple-Negative Breast Cancer.

Breast cancer (BC) is the most common type of cancer in women and the number of new cases in the US is still increasing each year. Triple-negative breast cancer (TNBC), which comprises 15-20% of all breast cancer, is a heterogeneous disease and is considered the most aggressive type of breast cancer due to the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expressions for treatments. Traditional chemotherapy is the standard protocol for the treatment of TNBC. Toxicity and multidrug resistance are major drawbacks to chemotherapy. The lack of molecular targets and poor prognosis for TNBC prompts an urgent need to discover novel therapeutic strategies to improve clinical outcomes and quality of life for patients. Photodynamic therapy (PDT) or light treatment is a binary anti-cancer procedure that uses a photosensitizer (PS) that, upon light activation, produces cytotoxic oxygen species, destroying tumor cells. PDT is minimally invasive and can be repeated a few times without accumulating significant toxicity in the surrounding tissues. The primary goal of this study was to investigate in vitro photodynamic chemotherapy as a ternary combination therapy using our synthesized photosensitizers (chlorin-vitamin conjugates and their corresponding indium complexes) co-treated with known chemotherapeutic agents (taxol, doxorubicin, cisplatin, fluorouracil, or methotrexate) in the presence of light and determine the optimum conditions as a pre-clinical study of an enhanced tumoricidal effect against TNBC. Our results indicated that the best combination for an effective chemophotodynamic effect involves a ternary treatment of the indium complex of the chlorin-lipoic acid conjugate (InCLA) co-treated with taxol, which exhibited strong synergism at the nanomolar concentration when combined in the presence of visible light irradiation. Other ternary combinations containing taxol with a synergistic anti-tumor effect against TNBC include chlorin-pantothenic acid (CPA) and chlorin-biotin (CBTN) conjugates. Several other ternary combinations containing InCLA, CBTN, and CPA with either cisplatin, fluorouracil, or methotrexate were identified to generate a synergistic or additive effect. The light dosage remained constant, but the dosages of photosensitizers and chemotherapy drugs were varied to obtain the lowest possible concentration for the desired effect. The synergistic, additive or antagonistic effects of the drug combinations were determined based on the Chou-Talalay method, with InCLA-taxol having the lowest combination index (CI) of 0.25. Fluorescence and transmission electron microscopy (TEM) images provided evidence of apoptosis as the preferred mode of cell death. Our study demonstrated the combination of PDT and chemotherapy as a potential treatment option for TNBC patients.

Detection of Active SARS-CoV-2 3CL Protease in Infected Cells Using Activity-Based Probes with a 2,6-Dichlorobenzoyloxymethyl Ketone Reactive Warhead.

The 3CL protease (3CLpro) is a viral cysteine protease of SARS-CoV-2 and is responsible for the main processing of the viral polyproteins involved in viral replication and proliferation. Despite the importance of 3CLpro as a drug target, the intracellular dynamics of active 3CLpro, including its expression and subcellular localization in SARS-CoV-2-infected cells, are poorly understood. Herein, we report an activity-based probe (ABP) with a clickable alkyne and an irreversible warhead for the SARS-CoV-2 3CL protease. We designed and synthesized two ABPs that contain a chloromethyl ketone (probe 2) or 2,6-dichlorobenzoyloxymethyl ketone (probe 3) reactive group at the P1' site. Labeling of recombinant 3CLpro by the ABPs in the purified and proteome systems revealed that probe 3 displayed ligand-directed and selective labeling against 3CLpro. Labeling of transiently expressed active 3CLpro in COS-7 cells also validated the good target selectivity of probe 3 for 3CLpro. We finally demonstrated that endogenously expressed 3CLpro in SARS-CoV-2-infected cells can be detected by fluorescence microscopy imaging using probe 3, suggesting that active 3CLpro at 5 h postinfection is localized in the juxtanuclear region. To the best of our knowledge, this is the first report investigating the subcellular localization of active 3CLpro by using ABPs. We believe that probe 3 will be a useful chemical tool for acquiring important biological knowledge of active 3CLpro in SARS-CoV-2-infected cells.

AIE-labeled fluorescent polystyrene nanoplastics for quantitative analysis in macrophages uptake

Nanoplastics have attracted significant attention due to their harmful effects on the environment and organisms. However, accurately detecting and quantifying nanoplastics that are ingested by organisms poses a challenge. Conventional organic fluorescent-labeled nanoplastics have reduced labeling efficiency due to aggregation-caused quenching (ACQ), leading to artifacts caused by leakage of fluorescent molecules. To address these limitations, this study utilized AIE fluorescence for internally labeling polystyrene nanoparticles. AIE-active molecules do not emit fluorescence in dilute solutions, thus preventing accuracy issues associated with fluorescence leakage. Three model plastics (TPE@PS) of varying particle sizes were synthesized via the swelling method. The preparation parameters were optimized, followed by stability tests conducted on TPE@PS. Fluorescence microscopy imaging revealed significant uptake of TPE@PS by RAW246.7 cells. A successful standard curve of fluorescence intensity-concentration was established successfully and utilized to accurately quantify the amount of TPE@PS that was ingested by RAW246.7 cells. The results indicate a consistent increase with increasing concentration in TPE@PS uptake across all particle sizes during the fixed exposure duration of 48 h. Furthermore, RAW264.7 cells exhibited a higher propensity to uptake smaller TPE@PS particles. Flow cytometry was also employed to validated the suitability of TPE@PS as a model nanoplastic for tracing purposes.

How Does the Antibiotic Amphotericin B Enter Membranes and What Does It Do There?

Amphotericin B is a popular antifungal antibiotic, but the exact way it works is still a matter of debate. Here, we used monolayers composed of phosphatidylcholine with ergosterol as a model of fungal lipid membranes to study drug incorporation from the aqueous phase and analyze the molecular reorganization of membranes underlying the biological activity of the antibiotic. The results show that the internalization of antibiotic molecules into membranes occurs only in the presence of ergosterol in the lipid phase. Comparison of images of solid-supported monolayers obtained by atomic force microscopy and lifetime imaging fluorescence microscopy shows the formation of intramembrane clusters of various sizes in the lipid phase, consisting mainly of antibiotic dimers and relatively large membrane pores (∼15 nm in diameter). The results reveal multiple modes of action of amphotericin B, acting simultaneously, each of which adversely affects the structural properties of the lipid membranes and their physiological functionality.

Multi-scale perceptual YOLO for automatic detection of clue cells and trichomonas in fluorescence microscopic images

Vaginitis is a common disease among women and has a high recurrence rate. The primary diagnosis method is fluorescence microscopic inspection, but manual inspection is inefficient and can lead to false detection or missed detection. Automatic cell identification and localization in microscopic images are necessary. For vaginitis diagnosis, clue cells and trichomonas are two important indicators and are difficult to be detected because of the different scales and image characteristics. This study proposes a Multi-Scale Perceptual YOLO (MSP-YOLO) with super-resolution reconstruction branch to meet the detection requirements of clue cells and trichomonas. Based on the scales and image characteristics of clue cells and trichomonas, we employed a super-resolution reconstruction branch to the detection network. This branch guides the detection branch to focus on subtle feature differences. Simultaneously, we proposed an attention-based feature fusion module that is injected with dilated convolutional group. This module makes the network pay attention to the non-centered features of the large target clue cells, which contributes to the enhancement of detection sensitivity. Experimental results show that the proposed detection network MSP-YOLO can improve sensitivity without compromising specificity. For clue cell and trichomoniasis detection, the proposed network achieved sensitivities of 0.706 and 0.910, respectively, which were 0.218 and 0.051 higher than those of the baseline model. In this study, the characteristics of the super-resolution reconstruction task are used to guide the network to effectively extract and process image features. The novel proposed network has an increased sensitivity, which makes it possible to detect vaginitis automatically.

Dimensionally stable and durable wood by lignin impregnation

Cracking, warping, and decaying stemming from wood's poor dimensional stability and durability are the most annoying issues of natural wood. There is an urgent need to address these issues, of which, sustainable and green chemical treatments are favorably welcomed. Herein, we developed a facile method through the incorporation of environmentally friendly biopolymer lignin into wood cells for wood dimensional stability and durability enhancement. Enzymatic hydrolysis lignin (EHL) was dissolved into various solvents followed by impregnation and drying to incorporate lignin into wood cells. Impregnation treatment was developed to incorporate into wood to improve its dimensional stability, durability, and micromechanics. The anti-swelling efficiency reached up to 99.4 %, the moisture absorption decreased down to 0.55 %, the mass loss after brown rot decay decreased to 7.22 %, and the cell wall elasticity as well as hardness increased 8.7 % and 10.3 %, respectively. Analyses acquired from scanning electron microscopy, fluorescent microscopy, and Raman imaging revealed that the EHL was successfully colonized in cell lumen as well as in cell walls, thus improved wood dimensional stability and durability. Moreover, Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy confirmed EHL interaction with the cell wall components, thus the wood mechanical property was not impaired significantly, whereas nanoindentation data indicated even slight mechanical enhancement on the cell walls. This facile approach can improve the wood properties in multiple aspects and remarkably enhance the outdoor performance of modified wood products. In addition, using lignin as a natural modifying agent to improve wood performance will have a great positive impact on the environment.

Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging

Malaria, a significant global health challenge, is caused by Plasmodium parasites. The Plasmodium liver stage plays a pivotal role in the establishment of the infection. This study focuses on the liver stage development of the model organism Plasmodium berghei, employing fluorescent microscopy imaging and convolutional neural networks (CNNs) for analysis. Convolutional neural networks have been recently proposed as a viable option for tasks such as malaria detection, prediction of host-pathogen interactions, or drug discovery. Our research aimed to predict the transition of Plasmodium-infected liver cells to the merozoite stage, a key development phase, 15 hours in advance. We collected and analyzed hourly imaging data over a span of at least 38 hours from 400 sequences, encompassing 502 parasites. Our method was compared to human annotations to validate its efficacy. Performance metrics, including the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity, were evaluated on an independent test dataset. The outcomes revealed an AUC of 0.873, a sensitivity of 84.6%, and a specificity of 83.3%, underscoring the potential of our CNN-based framework to predict liver stage development of P. berghei. These findings not only demonstrate the feasibility of our methodology but also could potentially contribute to the broader understanding of parasite biology.

Ultrabright quantum dots assisted in vivo NIR-II fluorescence microscopic imaging for brain metastases in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive and often fatal disease, especially since the brain metastasis of TNBC has been a particularly severe manifestation. However, brain metastasis in TNBC at early stages often lacks noticeable symptoms, making it challenging to detect. Near-infrared II (NIR-II) fluorescence microscopic imaging obtains long wavelength, which enables reduced scattering, high spatial resolution and minimal autofluorescence, it is also a favorable imaging method for tumor diagnosis. PbS@CdS quantum dots (QDs) are one of the popular NIR-II fluorescence nanoprobes for well brightness. In this study, NIR-II emissive PbS@CdS QDs were utilized and further encapsulated with thiol-terminated poly(ethylene oxide) (SH-PEG, MW = 5000) to form PbS@CdS@PEG QDs nanoparticles (NPs). The obtained PbS@CdS@PEG QDs NPs were then characterized and further studied in detail. The PbS@CdS@PEG QDs NPs had large absorption spectra, exhibited strong NIR-II fluorescence emission at approximately 1300[Formula: see text]nm, and possessed good NIR-II fluorescence properties. Then, the mice model of early-stage brain metastases of TNBC was established, and the PbS@CdS@PEG QDs NPs were injected into the tumor-bearing mice for NIR-II fluorescence microscopic bioimaging. The brain vessels and tumors of the living mice were detected with high spatial resolution under the NIR-II fluorescence microscopic imaging system with irradiation of 808[Formula: see text]nm laser. The tumor tissues were further restricted and prepared as thin slices. The NIR-II fluorescence signals were collected from the tumor slices with high spatial resolution and signal-to-background ratio (SBR). Thus, the PbS@CdS@PEG QDs NPs-assisted NIR-II fluorescence microscopic system can effectively achieve targeting brain metastases of TNBC imaging, offering a novel and promising approach for TNBC-specific diagnosis.

Chaotic-flow-driven mixing in T- and V-shaped micromixers

T- and V-shaped (or arrow-shaped) micromixers enable the control of rapid chemical reactions by permitting accelerated mixing. Their mixing performance has been extensively investigated at moderate flow rates, which correspond to Reynolds numbers of the order of several hundreds. However, this operating range does not align with the recent applications of microreactors in organic synthesis. Therefore, this study examined mixing times in T- and V-shaped micromixers with 250-µm-wide channels at high flow rates (Reynolds numbers of up to 1500). The progress of mixing between an acidic solution and a basic solution containing a pH-sensitive fluorescent molecule was visualized by fluorescence microscopy imaging. An image analysis of 200 frames for each condition helped evaluate the degree of mixing and its stability over time under chaotic flow. The performance and stability of the V-shaped micromixer were significantly enhanced when the flow-rate ratio was changed from 1:1 to 1:2. The difference in momentum between the two inlet streams suppressed the undesirable alternation of the flow patterns at the junction. The effects of the choice of fluids (in the lower- and higher-flow-rate sides) on the reaction selectivity were explored through a numerical analysis. It was clarified that the substrate-side flow rate has to be set lower than that of the reactant side in the competing consecutive reaction system. Moreover, a short mixing time of 1 ms was achieved using the V-shaped micromixer at a flow-rate ratio of 1:2 and Re of 1500. These findings provide practical guidelines for the design and operation of microreactor systems.

Illuminating Polysulfide Distribution in Lithium Sulfur Batteries; Tracking Polysulfide Shuttle Using Operando Optical Fluorescence Microscopy.

High-energy-density lithium sulfur (Li-S) batteries suffer heavily from the polysulfide shuttle effect, a result of the dissolution and transport of intermediate polysulfides from the cathode, into the electrolyte, and onto the anode, leading to rapid cell degradation. If this primary mechanism of cell failure is to be overcome, the distribution, dynamics, and degree of polysulfide transport must first be understood in depth. In this work, operando optical fluorescence microscope imaging of optically accessible Li-S cells is shown to enable real-time qualitative visualization of the spatial distribution of lithium polysulfides, both within the electrolyte and porous cathode. Quantitative determinations of spatial concentration are also possible at a low enough concentration. The distribution throughout cycling is monitored, including direct observation of polysulfide shuttling to the anode and consequent dendrite formation. This was enabled through the optimization of a selective fluorescent dye, verified to fluoresce proportionally with concentration of polysulfides within Li-S cells. This ability to directly and conveniently track the spatial distribution of soluble polysulfide intermediates in Li-S battery electrolytes, while the cell operates, has the potential to have a widespread impact across the field, for example, by enabling the influence of a variety of polysulfide mitigation strategies to be assessed and optimized, including in this work the LiNO3 additive.

Large-field and fast super-resolution microscopic imaging method based on laser interferometry

In recent years, structured illumination microscopy (SIM) has been drawing great attention for both technique development and application. However, conventional SIM, which uses a spatial light modulator (SLM) for fringe projection, often has a limited field of view. To meet the demand for high-throughput microscopic imaging in biomedicine research, a large-field super-resolution (SR) fluorescence microscopic imaging method based on laser interferometry was proposed. The method that combines a two-dimensional (2D) grating for fringe pattern projection and an SLM for selecting fringe orientation can break the limitation of fringe number limited by the digital projection devices. A spatial-domain reconstruction algorithm was developed to improve the computational speed of super-resolution imaging. Finally, an experimental platform for SIM microscopy was established. A large-field view of 1380 μm × 1035 μm under a 20×/NA0.75 objective is experimentally demonstrated, and an enhancement of 1.8-fold resolution is realized. The spatial-domain reconstruction algorithm can significantly improve the computational speed by approximately 10 times faster compared to the traditional frequency-domain algorithm.

Tetracyclic homoisoflavanoid (+)-brazilin: a natural product inhibits c-di-AMP-producing enzyme and Streptococcus mutans biofilms.

The tenacious biofilms formed by Streptococcus mutans are resistant to conventional antibiotics and current treatments. There is a growing need for novel therapeutics that selectively inhibit S. mutans biofilms while preserving the normal oral microenvironment. Previous studies have shown that increased levels of cyclic di-AMP, an important secondary messenger synthesized by diadenylate cyclase (DAC), favored biofilm formation in S. mutans. Thus, targeting S. mutans DAC is a novel strategy to inhibit S. mutans biofilms. We screened a small NCI library of natural products using a fluorescence detection assay. (+)-Brazilin, a tetracyclic homoisoflavanoid found in the heartwood of Caesalpinia sappan, was identified as one of the 11 "hits," with the greatest reduction (>99%) in fluorescence at 100 µM. The smDAC inhibitory profiles of the 11 "hits" established by a quantitative high-performance liquid chromatography assay revealed that (+)-brazilin had the most enzymatic inhibitory activity (87% at 100 µM) and was further studied to determine its half maximal inhibitory concentration (IC50 = 25.1 ± 0.98 µM). (+)-Brazilin non-competitively inhibits smDAC's enzymatic activity (Ki = 140.0 ± 27.13 µM), as determined by a steady-state Michaelis-Menten kinetics assay. In addition, (+)-brazilin's binding profile with smDAC (Kd = 11.87 µM) was illustrated by a tyrosine intrinsic fluorescence quenching assay. Furthermore, at low micromolar concentrations, (+)-brazilin selectively inhibited the biofilm of S. mutans (IC50 = 21.0 ± 0.60 µM) and other oral bacteria. S. mutans biofilms were inhibited by a factor of 105 in colony-forming units when treated with 50 µM (+)-brazilin. In addition, a significant dose-dependent reduction in extracellular DNA and glucan levels was evident by fluorescence microscopy imaging of S. mutans biofilms exposed to different concentrations of (+)-brazilin. Furthermore, colonization of S. mutans on a representative model of enamel using suspended hydroxyapatite discs showed a >90% reduction with 50 µM (+)-brazilin. In summary, we have identified a drug-like natural product inhibitor of S. mutans biofilm that not only binds to smDAC but can also inhibit the function of smDAC. (+)-Brazilin could be a good candidate for further development as a potent therapeutic for the prevention and treatment of dental caries.IMPORTANCEThis study represents a significant advancement in our understanding of potential therapeutic options for combating cariogenic biofilms produced by Streptococcus mutans. The research delves into the use of (+)-brazilin, a natural product, as a potent inhibitor of Streptococcus mutans' diadenylate cyclase (smDAC), an enzyme crucial in the formation of biofilms. The study establishes (+)-brazilin as a non-competitive inhibitor of smDAC while providing initial insights into its binding mechanism. What makes this finding even more promising is that (+)-brazilin does not limit its inhibitory effects to S. mutans alone. Instead, it demonstrates efficacy in hindering biofilms in other oral bacteria as well. The broader spectrum of anti-biofilm activity suggests that (+)-brazilin could potentially serve as a versatile tool in a natural product-based treatment for combating a range of conditions caused by resilient biofilms.

SUPPOSe 3Dge: A Method for Super-Resolved Detection of Surfaces in Volumetric Fluorescence Microscopy

We present SUPPOSe 3Dge, a method for the detection of surfaces in volumetric fluorescence microscopy images with resolution better than the diffraction limit. The method works by approximating an arbitrary object surface as a polyhedron formed by small triangular faces, which are thought as virtual point like sources of signal gradient. Then, the super resolution arises from solving a least square problem only on the positions of the sources, by comparing the measured image gradient with a synthetic one built from the approximated surface and the known point spread function of the instrument. We present the formulation of the method and its characterization using simulated measurements of two different types. We show that the method is able to identify with high precision and accuracy the sizes and shapes of objects smaller than the instrumental resolution. Using different quantifiers that measure the distance between the solution and the target object, we report reconstructions with an accuracy 100 times better than the axial resolution and 40 times the lateral resolution of the instrument.

SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging

Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional single-cell resolution platform for targeted spatial proteomics. However, the precision of subsequent clinical analysis is constrained by imaging noise and resolution. Here, we propose SpiDe-Sr, a super-resolution network embedded with a denoising module for IMC spatial resolution enhancement. SpiDe-Sr effectively resists noise and improves resolution by 4 times. We demonstrate SpiDe-Sr respectively with cells, mouse and human tissues, resulting 18.95%/27.27%/21.16% increase in peak signal-to-noise ratio and 15.95%/31.63%/15.52% increase in cell extraction accuracy. We further apply SpiDe-Sr to study the tumor microenvironment of a 20-patient clinical breast cancer cohort with 269,556 single cells, and discover the invasion of Gram-negative bacteria is positively correlated with carcinogenesis markers and negatively correlated with immunological markers. Additionally, SpiDe-Sr is also compatible with fluorescence microscopy imaging, suggesting SpiDe-Sr an alternative tool for microscopy image super-resolution.

Human Airway Organoids and Multimodal Imaging-Based Toxicity Evaluation of 1-Nitropyrene.

Despite significant advances in understanding the general health impacts of air pollution, the toxic effects of air pollution on cells in the human respiratory tract are still elusive. A robust, biologically relevant in vitro model for recapitulating the physiological response of the human airway is needed to obtain a thorough understanding of the molecular mechanisms of air pollutants. In this study, by using 1-nitropyrene (1-NP) as a proof-of-concept, we demonstrate the effectiveness and reliability of evaluating environmental pollutants in physiologically active human airway organoids. Multimodal imaging tools, including live cell imaging, fluorescence microscopy, and MALDI-mass spectrometry imaging (MSI), were implemented to evaluate the cytotoxicity of 1-NP for airway organoids. In addition, lipidomic alterations upon 1-NP treatment were quantitatively analyzed by nontargeted lipidomics. 1-NP exposure was found to be associated with the overproduction of reactive oxygen species (ROS), and dysregulation of lipid pathways, including the SM-Cer conversion, as well as cardiolipin in our organoids. Compared with that of cell lines, a higher tolerance of 1-NP toxicity was observed in the human airway organoids, which might reflect a more physiologically relevant response in the native airway epithelium. Collectively, we have established a novel system for evaluating and investigating molecular mechanisms of environmental pollutants in the human airways via the combinatory use of human airway organoids, multimodal imaging analysis, and MS-based analyses.

A Review for Artificial Intelligence Based Protein Subcellular Localization.

Proteins need to be located in appropriate spatiotemporal contexts to carry out their diverse biological functions. Mislocalized proteins may lead to a broad range of diseases, such as cancer and Alzheimer's disease. Knowing where a target protein resides within a cell will give insights into tailored drug design for a disease. As the gold validation standard, the conventional wet lab uses fluorescent microscopy imaging, immunoelectron microscopy, and fluorescent biomarker tags for protein subcellular location identification. However, the booming era of proteomics and high-throughput sequencing generates tons of newly discovered proteins, making protein subcellular localization by wet-lab experiments a mission impossible. To tackle this concern, in the past decades, artificial intelligence (AI) and machine learning (ML), especially deep learning methods, have made significant progress in this research area. In this article, we review the latest advances in AI-based method development in three typical types of approaches, including sequence-based, knowledge-based, and image-based methods. We also elaborately discuss existing challenges and future directions in AI-based method development in this research field.

SC-Track: a robust cell-tracking algorithm for generating accurate single-cell lineages from diverse cell segmentations.

Computational analysis of fluorescent timelapse microscopy images at the single-cell level is a powerful approach to study cellular changes that dictate important cell fate decisions. Core to this approach is the need to generate reliable cell segmentations and classifications necessary for accurate quantitative analysis. Deep learning-based convolutional neural networks (CNNs) have emerged as a promising solution to these challenges. However, current CNNs are prone to produce noisy cell segmentations and classifications, which is a significant barrier to constructing accurate single-cell lineages. To address this, we developed a novel algorithm called Single Cell Track (SC-Track), which employs a hierarchical probabilistic cache cascade model based on biological observations of cell division and movement dynamics. Our results show that SC-Track performs better than a panel of publicly available cell trackers on a diverse set of cell segmentation types. This cell-tracking performance was achieved without any parameter adjustments, making SC-Track an excellent generalized algorithm that can maintain robust cell-tracking performance in varying cell segmentation qualities, cell morphological appearances and imaging conditions. Furthermore, SC-Track is equipped with a cell class correction function to improve the accuracy of cell classifications in multiclass cell segmentation time series. These features together make SC-Track a robust cell-tracking algorithm that works well with noisy cell instance segmentation and classification predictions from CNNs to generate accurate single-cell lineages and classifications.

Hexagonal single crystals of perylene with patterned heterogeneous domains

Hexagonal single crystals of perylene were grown on a substrate by solution evaporation. Fluorescence microscopy images showed patterned heterogeneous domains with different fluorescence colors. Polarized ultra-low-frequency Raman microscopy revealed that the crystal structure is homogeneous throughout the entire crystal despite the domains observed in the fluorescence images. We concluded that hexagonal crystals were formed by the further growth of the rhombic β-crystal, which is one of the two polymorphs of the perylene crystal. This mechanism explains the formation of domains with different crystal qualities, resulting in different fluorescence colors.

Abstract 2018: Tumor treating fields (TTFields) disrupt cancer cell invasion by impacting cell-ECM traction forces

Abstract Introduction: Tumor Treating Fields (TTFields) are an anti-cancer treatment that use low intensity, alternating electric fields. Anti-mitotic treatment effects of TTFields have been, to date, considered the primary anti-cancer effect. Recent studies have shown additional impacts on cancer cell invasion and migration, among other effects, resulting in a complex anti-tumor response derived from a combination of factors. By deploying computational imaging tools to assess experimental conditions that apply TTFields treatment to 3D cancer multicellular spheroid cultures, the goal of our study is to elucidate important mechanisms and effect sizes on anti-tumor effects relating to the modulation of cancer cell-extracellular matrix (ECM) biophysical interactions. Methods: 3D multicellular tumor spheroids (MTS) are cultured using GFP-tagged U-87 MG glioma cells. A single 3D MTS is placed in a cell culture insert and embedded in collagen I ECM at 2.25 mg/mL. Fluorescent polystyrene microspheres are dispersed in the ECM to facilitate subsequent tracking of displacement fields induced by the MTS-ECM construct. Fluorescence microscopy imaging is acquired for all spheroids prior to treatment initiation. Then, with 3 replicates in each treatment condition, TTFields are applied for a duration of 48 hours at 200 kHz frequency with a no treatment condition as a control. At 48 hours, we acquire fluorescence microscopy images to track spheroid growth and bead-field displacement. To determine deformation fields induced by the cancer spheroid, we compare each image at 48 hours to their respective baseline image. Deformation fields are analyzed using a custom-developed analysis code that performs an initial alignment of the baseline and specific time point images using a global rigid registration. Next, we perform a B-spline based nonrigid image registration to generate an estimate of the deformation field vector at each pixel location within the image. Deformation intensity is measured within a circular region of interest (r = 900 µm) centered at the spheroid core. Results: The average magnitude of displacement for treatment and control groups is 0.52±0.2 µm and 1.07±0.1 µm, respectively. Analysis of deformation fields reveals a significant difference (p < 0.1) in the magnitude of deformation present between treatment and control groups. Conclusions: Implementation of our computational imaging analysis methods using rigid and nonrigid registration, we observe a 69.6% decrease in the magnitude of deformation in TTFields treated spheroids compared to control spheroids. Due to the decrease in deformation induced by cancer spheroids treated with TTFields, we conclude that TTFields impact cancer cell traction forces applied to the ECM to disrupt cancer cell invasion. Citation Format: Samantha M. Short, Haley J. Bowers, Jared A. Weis. Tumor treating fields (TTFields) disrupt cancer cell invasion by impacting cell-ECM traction forces [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2018.

Targeted inhibition of colorectal cancer proliferation: Thedual-modulatory role of 2,4-DTBP on anti-apoptotic Bcl-2 and Survivin proteins.

The anti-apoptotic proteins, Bcl-2 and Survivin, are consistently overexpressed in numerous human malignancies, notably in colorectal cancer. 2,4-Di-tert-butylphenol (2,4-DTBP) is a naturally occurring phenolic compound known for its diverse biological activities, including anti-cancer properties. The mechanism behind 2,4-DTBP-induced inhibition of cell proliferation and apoptosis in human colorectal cancer cells, specifically regarding Bcl-2 and Survivin, remains to be elucidated. In this study, we employed both in silico and invitro methodologies to underpin this interaction at the molecular level. Molecular docking demonstrated a substantial binding affinity of 2,4-DTBP towards Bcl-2 (ΔG = -9.8 kcal/mol) and Survivin (ΔG = -5.6 kcal/mol), suggesting a potential inhibitory effect. Further, molecular dynamic simulations complemented by MM-GBSA calculations confirmed the significant binding of 2,4-DTBP with Bcl-2 (dGbind = -54.85 ± 6.79 kcal/mol) and Survivin (dGbind = -32.36 ± 1.29 kcal/mol). Invitro assays using HCT116 colorectal cancer cells revealed that 2,4-DTBP inhibited proliferation and promoted apoptosis in both a dose- and time-dependent manner. Fluorescence imaging and scanning electron microscopy illustrated the classical features associated with apoptosis upon 2,4-DTBP exposure. Cell cycle analysis through flow cytometry highlighted a G1 phase arrest and apoptosis assay demonstrated increased apoptotic cell population. Notably, western blotting results indicated a decreased expression of Bcl-2 and Survivin post-treatment. Considering the cytoprotective roles of Bcl-2 and Survivin through the inhibition of mitochondrial dysfunction, our findings of disrupted mitochondrial bioenergetics, characterized by reduced ATP production and oxygen consumption, further accentuate the functional impairment of these proteins. Overall, the integration of in silico and invitro data suggests that 2,4-DTBP holds promise as a therapeutic agent targeting Bcl-2 and Survivin in colorectal cancer.