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Travis Cantu,1 Kyle Walsh,2 Varun P Pattani,3 Austin J Moy,3 James W Tunnell,3 Jennifer A Irvin,1,2 Tania Betancourt1,2 1Materials Science, Engineering, and Commercialization Program, Texas State University, San Marcos, TX, USA; 2Department of Chemistry and Biochemistry, Texas State University, San Marcos, TX, USA; 3Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA Abstract: Laser-mediated photothermal ablation of cancer cells aided by photothermal agents is a promising strategy for localized, externally controlled cancer treatment. We report the synthesis, characterization, and in vitro evaluation of conductive polymeric nanoparticles (CPNPs) of poly(diethyl-4,4'-{[2,5-bis(2,3-dihydrothieno[3,4-b][1,4]dioxin-5-yl)-1,4-phenylene]bis(oxy)}dibutanoate) (P1) and poly(3,4-ethylenedioxythiophene) (PEDOT) stabilized with 4-dodecylbenzenesulfonic acid and poly(4-styrenesulfonic acid-co-maleic acid) as photothermal ablation agents. The nanoparticles were prepared by oxidative-emulsion polymerization, yielding stable aqueous suspensions of spherical particles of

Priyaveena Puvanakrishnan1, Jaesook Park1, Deyali Chatterjee2, Sunil Krishnan2, James W Tunnell11Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA; 2The UT MD Anderson Cancer Center, Houston, TX, USAAbstract: Gold nanoparticles (GNPs) have gained significant interest as nanovectors for combined imaging and photothermal therapy of tumors. Delivered systemically, GNPs preferentially accumulate at the tumor site via the enhanced permeability and retention effect, and when irradiated with near infrared light, produce sufficient heat to treat tumor tissue. The efficacy of this process strongly depends on the targeting ability of the GNPs, which is a function of the particle’s geometric properties (eg, size) and dosing strategy (eg, number and amount of injections). The purpose of this study was to investigate the effect of GNP type and dosing strategy on in vivo tumor targeting. Specifically, we investigated the in vivo tumor-targeting efficiency of pegylated gold nanoshells (GNSs) and gold nanorods (GNRs) for single and multiple dosing. We used Swiss nu/nu mice with a subcutaneous tumor xenograft model that received intravenous administration for a single and multiple doses of GNS and GNR. We performed neutron activation analysis to quantify the gold present in the tumor and liver. We performed histology to determine if there was acute toxicity as a result of multiple dosing. Neutron activation analysis results showed that the smaller GNRs accumulated in higher concentrations in the tumor compared to the larger GNSs. We observed a significant increase in GNS and GNR accumulation in the liver for higher doses. However, multiple doses increased targeting efficiency with minimal effect beyond three doses of GNPs. These results suggest a significant effect of particle type and multiple doses on increasing particle accumulation and on tumor targeting ability.Keywords: gold nanorods, gold nanoshells, tumor targeting, multiple dosing

Digital staining streamlines traditional staining procedures by digitally generating stained images from unstained or differently stained images. While conventional staining methods involve time-consuming chemical processes, digital staining offers an efficient and low-infrastructure alternative. Researchers can expedite tissue analysis without physical sectioning by leveraging microscopy-based techniques, such as confocal microscopy. However, interpreting grayscale or pseudo-color microscopic images remains challenging for pathologists and surgeons accustomed to traditional histologically stained images. To fill this gap, various studies explore digitally simulating staining to mimic targeted histological stains. This paper introduces a novel network, In-and-Out Net, designed explicitly for digital staining tasks. Based on Generative Adversarial Networks (GAN), our model efficiently transforms Reflectance Confocal Microscopy (RCM) images into Hematoxylin and Eosin (H&E) stained images. Using aluminum chloride preprocessing for skin tissue, we enhance nuclei contrast in RCM images. We trained the model with digital H&E labels featuring two fluorescence channels, eliminating the need for image registration and providing pixel-level ground truth. Our contributions include proposing an optimal training strategy, conducting a comparative analysis demonstrating state-of-the-art performance, validating the model through an ablation study, and collecting perfectly matched input and ground truth images without registration. In-and-Out Net showcases promising results, offering a valuable tool for digital staining tasks and advancing the field of histological image analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Significance: Traditional pathology workflow suffers from limitations including biopsy invasiveness, small fraction of large tissue samples being analyzed, and complex and time-consuming processing., Aim: We address limitations of conventional pathology workflow through development of a laser microbiopsy device for minimally invasive harvest of sub-microliter tissue volumes. Laser microbiopsy combined with rapid diagnostic methods, such as virtual hematoxylin and eosin (H&E) imaging has potential to provide rapid minimally invasive tissue diagnosis., Approach: Laser microbiopsies were harvested using an annular shaped Ho:YAG laser beam focused onto the tissue surface. As the annulus was ablated, the tissue section in the center of the annulus was ejected and collected directly onto a glass slide for analysis. Cryogen spray cooling was used before and after laser harvest to limit thermal damage. Microbiopsies were collected from porcine skin and kidney. Harvested microbiopsies were imaged with confocal microscopy and digitally false colored to provide virtual H&E images., Results: Microbiopsies were successfully harvested from porcine skin and kidney. Computational and experimental results show the benefit of cryogen pre- and post-cooling to limit thermal damage. Virtual H&E images of microbiopsies retained observable cellular features including cell nuclei., Conclusions: Laser microbiopsy with virtual H&E imaging shows promise as a potential rapid and minimally invasive tool for biopsy and diagnosis., (© 2022 The Authors.)

Nurdles, also known as plastic resin pellets, are now a major source of plastic pollution on beaches globally, thus it is important to elucidate their weathering patterns and environmental fates as well as the associated pollutants. In this study we collected nurdles from 24 sites in the coastal bend region of south Texas, covering areas from the near shore railway stations to the adjacent bays and barrier islands. The morphologies of nurdles and associated pollutants including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and mercury, were investigated. The results showed that the nurdles varied greatly in color, shape, polymer composition, and oxidation degree. More than 80 % of the nurdles were made with polyethylene, and the rest with polypropylene, polyester, polystyrene, polyethylene-vinyl acetate, and polyvinyl chloride based on Fourier Transform Infrared Spectroscopy (FTIR) analysis. PCBs were not detected on nurdles. PAHs and mercury on nurdles were detected at 12 % and 20 % of the sampling sites. The total concentrations of detectable PAHs ranged from 92.59 to 1787.23 ng/g-nurdle, and the detectable mercury concentrations ranged from 1.23 to 22.25 ng/g-nurdle. Although the concentrations of these pollutants were not at the acute toxic effect level, the presence of PAHs and mercury suggested the potential risk of pollutant exposure to marine organisms in ecosystems, given the fact that nurdles are persistent in the environment., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Nanomedicine is a novel field of study that involves the use of nanomaterials to address challenges and issues that are associated with conventional therapeutics for cancer treatment including, but not limited to, low bioavailability, low water-solubility, narrow therapeutic window, nonspecific distribution, and multiple side effects of the drugs. Multiple strategies have been exploited to reduce the nonspecific distribution, and thus the side effect of the active pharmaceutical ingredients (API), including active and passive targeting strategies and externally controllable release of the therapeutic cargo. Site-specific release of the drug prevents it from impacting healthy cells, thereby significantly reducing side effects. API release triggers can be either externally applied, as in ultrasound-mediated activation, or induced by the tumor. To rationally design such nanomedicines, a thorough understanding of the differences between the tumor microenvironment versus that of healthy tissues must be paired with extensive knowledge of stimuli-responsive biomaterials. Herein, we describe the characteristics that differentiate tumor tissues from normal tissues. Then, we introduce smart materials that are commonly used for the development of smart nanomedicines to be triggered by stimuli such as changes in pH, temperature, and enzymatic activity. The most recent advances and their impact on the field of cancer therapy are further discussed., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Significance: Raman spectroscopy (RS) provides an automated approach for assisting Mohs micrographic surgery for skin cancer diagnosis; however, the specificity of RS is limited by the high spectral similarity between tumors and normal tissues structures. Reflectance confocal microscopy (RCM) provides morphological and cytological details by which many features of epidermis and hair follicles can be readily identified. Combining RS with deep-learning-aided RCM has the potential to improve the diagnostic accuracy of RS in an automated fashion, without requiring additional input from the clinician., Aim: The aim of this study is to improve the specificity of RS for detecting basal cell carcinoma (BCC) using an artificial neural network trained on RCM images to identify false positive normal skin structures (hair follicles and epidermis)., Approach: Our approach was to build a two-step classification model. In the first step, a Raman biophysical model that was used in prior work classified BCC tumors from normal tissue structures with high sensitivity. In the second step, 191 RCM images were collected from the same site as the Raman data and served as inputs for two ResNet50 networks. The networks selected the hair structure and epidermis images, respectively, within all images corresponding to the positive predictions of the Raman biophysical model with high specificity. The specificity of the BCC biophysical model was improved by moving the Raman spectra corresponding to these selected images from false positive to true negative., Results: Deep-learning trained on RCM images removed 52% of false positive predictions from the Raman biophysical model result while maintaining a sensitivity of 100%. The specificity was improved from 84.2% using Raman spectra alone to 92.4% by integrating Raman spectra with RCM images., Conclusions: Combining RS with deep-learning-aided RCM imaging is a promising tool for guiding tumor resection surgery.

In the present study, we demonstrate that soft tissue fiber architectural maps captured using polarized spatial frequency domain imaging (pSFDI) can be utilized as an effective texture source for DIC-based planar surface strain analyses. Experimental planar biaxial mechanical studies were conducted using pericardium as the exemplar tissue, with simultaneous pSFDI measurements taken. From these measurements, the collagen fiber preferred direction [Formula: see text] was determined at the pixel level over the entire strain range using established methods ( https://doi.org/10.1007/s10439-019-02233-0 ). We then utilized these pixel-level [Formula: see text] maps as a texture source to quantify the deformation gradient tensor [Formula: see text] as a function of spatial position [Formula: see text] within the specimen at time t. Results indicted that that the pSFDI approach produced accurate deformation maps, as validated using both physical markers and conventional particle based method derived from the DIC analysis of the same specimens. We then extended the pSFDI technique to extract the fiber orientation distribution [Formula: see text] as a function of [Formula: see text] from the pSFDI intensity signal. This was accomplished by developing a calibration procedure to account for the optical behavior of the constituent fibers for the soft tissue being studied. We then demonstrated that the extracted [Formula: see text] was accurately computed in both the referential (i.e. unloaded) and deformed states. Moreover, we noted that the measured [Formula: see text] agreed well with affine kinematic deformation predictions. We also demonstrated this calibration approach could also be effectively used on electrospun biomaterials, underscoring the general utility of the approach. In a final step, using the ability to simultaneously quantify [Formula: see text] and [Formula: see text], we examined the effect of deformation and collagen structural measurements on the measurement region size. For pericardial tissues, we determined a critical length of [Formula: see text] 8 mm wherein the regional variations sufficiently dissipated. This result has immediate potential in the identification of optimal length scales for meso-scale strain measurement in soft tissues and fibrous biomaterials., (© 2022. The Author(s) under exclusive licence to Biomedical Engineering Society.)

Recent focus on cancer immunotherapies has led to significant interest in the development of therapeutic strategies that can lead to immunogenic cell death (ICD), which can cause activation of an immune response against tumor cells and improve immunotherapy outcomes by enhancing the immunogenicity of the tumor microenvironment. In this work, a nanomedicine-mediated combination therapy is used to deliver the ICD inducers doxorubicin (Dox), a chemotherapeutic agent, and indocyanine green (ICG), a photothermal agent. These agents are loaded into nanoparticles (NPs) of bovine serum albumin (BSA) that are prepared through a desolvation process. The formulation of BSA NPs is optimized to achieve NPs of 102.6  nm in size and loadings of 8.55 % and 5.69 % (w/w) for ICG and Dox, respectively. The controlled release of these agents from the BSA NPs is confirmed. Upon laser irradiation for 2.5 min, NPs at a dose of 62.5 μg mL -1 are able to increase the temperature of the cells by 7 °C and thereby inhibit the growth of B16F10 melanoma cells in vitro. Surface presentation of heat shock proteins and calreticulin from the cells after treatment confirmed the ability of the Dox/ICG loaded BSA NPs to induce ICD in the melanoma cells., (© 2021 Wiley-VCH GmbH.)

Introduction: This study aimed at answering three research questions: (1) Under the experimental conditions studied, what is the dominant mechanism of Holmium:YAG lithotripsy with or without pulse modulation? (2) Under what circumstances can laser pulse modulation increase crater volume of stone ablation per joule of emitted radiant energy? (3) Are BegoStone phantoms a suitable model for laser lithotripsy studies? Materials and Methods: The research questions were addressed by ablation experiments with BegoStone phantoms and native stones. Experiments were performed under three stone conditions: dry stones in air, hydrated stones in air, and hydrated stones in water. Single pulses with and without pulse modulation were applied. For each pulse mode, temporal profile, transmission through 1 mm water, and cavitation bubble collapse pressures were measured and compared. For each stone condition and pulse mode, stones were ablated with a fiber separation distance of 1 mm and crater volumes were measured using optical coherence tomography. Results: Pulses with and without pulse modulation had high (>80%) transmission through 1 mm of water. Pulses without pulse modulation generated much higher peak pressures than those with pulse modulation (62.3 vs 11.4 bar). Pulse modulation resulted in similar or larger craters than without pulse modulation. Trends in BegoStone crater volumes differed from trends in native stones. Conclusions: This results of this study suggest that the dominant mechanism is photothermal with possible photoacoustic contributions for some stone compositions. Pulse modulation can increase ablation volume per joule of emitted radiant energy, but the effect may be composition specific. BegoStones showed unique infrared ablation characteristics compared with native stones and are not a suitable model for laser lithotripsy studies.

Significance: Sub-diffuse optical properties may serve as useful cancer biomarkers, and wide-field heatmaps of these properties could aid physicians in identifying cancerous tissue. Sub-diffuse spatial frequency domain imaging (sd-SFDI) can reveal such wide-field maps, but the current time cost of experimentally validated methods for rendering these heatmaps precludes this technology from potential real-time applications., Aim: Our study renders heatmaps of sub-diffuse optical properties from experimental sd-SFDI images in real time and reports these properties for cancerous and normal skin tissue subtypes., Approach: A phase function sampling method was used to simulate sd-SFDI spectra over a wide range of optical properties. A machine learning model trained on these simulations and tested on tissue phantoms was used to render sub-diffuse optical property heatmaps from sd-SFDI images of cancerous and normal skin tissue., Results: The model accurately rendered heatmaps from experimental sd-SFDI images in real time. In addition, heatmaps of a small number of tissue samples are presented to inform hypotheses on sub-diffuse optical property differences across skin tissue subtypes., Conclusion: These results bring the overall process of sd-SFDI a fundamental step closer to real-time speeds and set a foundation for future real-time medical applications of sd-SFDI such as image guided surgery.

Nurdles, the pre-production plastic pellets, are a major source of plastic pollution in marine environments due to unregulated spills during production and transportation. We analyzed the types of plastics and associated organic pollutants on nurdles collected along the shoreline of Gulf of Mexico in Texas. Our results showed that the nurdles were made from polyethylene (81.9%) and polypropylene (18.1%). Polycyclic aromatic hydrocarbons (PAHs, 16 US EPA priority) and polychlorinated biphenyls (PCBs, 7 commercial congeners) sorbed to the nurdles were in concentration ranges of 1.6-14,700 ng/ g and 0-642 ng/ g, respectively. Heavily weathered nurdles tended to have higher concentrations of PAHs and PCBs than lightly weathered ones. The bioaccessibility of sorbed contaminants was evaluated using a simulated intestinal fluid. The results showed that the associated PAHs were more bioaccessible in lightly weathered nurdles (13.1 ± 2.3%) than heavily weathered one (5.3 ± 0.1%), and that no PCBs were bioaccessible. These findings are informative for toxicity evaluation and resource management of plastic debris in coastal environments., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Recent advances in immunotherapy have highlighted a need for therapeutics that initiate immunogenic cell death in tumors to stimulate the body's immune response to cancer. This study examines whether laser-generated bubbles surrounding nanoparticles ("nanobubbles") induce an immunogenic response for cancer treatment. A single nanosecond laser pulse at 1064 nm generates micron-sized bubbles surrounding gold nanorods in the cytoplasm of breast cancer cells. Cell death occurred in cells treated with nanorods and irradiated, but not in cells with irradiation treatment alone. Cells treated with nanorods and irradiation had increased damage-associated molecular patterns (DAMPs), including increased expression of chaperone proteins human high mobility group box 1 (HMGB1), adenosine triphosphate (ATP), and heat shock protein 70 (HSP70). This enhanced expression of DAMPs led to the activation of dendritic cells. Overall, this treatment approach is a rapid and highly specific method to eradicate tumor cells with simultaneous immunogenic cell death signaling, showing potential as a combination strategy for immunotherapy.

Purpose: Current skin cancer detection relies on dermatologists' visual assessments of moles directly or dermoscopically. Our goal is to show that our similarity assessment algorithm on dermoscopic images can perform as well as a dermatologist's assessment. Approach: Given one target mole and two other moles from the same patient, our model determines which mole is more similar to the target mole. Similarity was quantified as the Euclidean distance in a feature space designed to capture mole properties such as size, shape, and color. We tested our model on 18 patients, each of whom had at least five moles, and compared the model assessments of mole similarity with that of three dermatologists. Fleiss' Kappa agreement coefficients and iteration tests were used to evaluate the agreement in similarity assessment among dermatologists and our model. Results: With the selected features of size, entropy (color variation), and cluster prominence (asymmetry), our algorithm's similarity assessments agreed moderately with the similarity assessments of dermatologists. The mean Kappa of 1000 iteration tests was 0.49 ( confidence interval   ( CI ) = [ 0.23 , 0.74 ] ) when comparing three dermatologists and our model, which is comparable to the agreement in similarity assessment among the dermatologists themselves (the mean Kappa of 1000 iteration tests for three dermatologists was 0.48, CI = [ 0.19 , 0.77 ] .) By contrast, the mean Kappa was 0.22 ( CI = [ - 0.00 , 0.43 ] ) when comparing the similarity assessments of three dermatologists and random guesses. Conclusions: Our study showed that our image feature-engineering-based algorithm can effectively assess the similarity of moles as dermatologists do. Such a similarity assessment could serve as the foundation for computer-assisted intra-patient evaluation of moles., (© 2021 Society of Photo-Optical Instrumentation Engineers (SPIE).)

The use of nanomedicines to induce immunogenic cell death is a new strategy that aims to increase tumor immunogenicity and thereby prime tumors for further immunotherapies. In this study, we developed a nanoparticle formulation for combinatory chemotherapy and photothermal therapy based only on materials previously used in FDA-approved products and investigated the effect of the combinatory therapy on the growth inhibition and induction of immunogenic cell death in human MDA-MB-231 breast cancer cells. The formulation consists of ~108-nm nanoparticles made of poly(lactic acid)-b-methoxy poly(ethylene glycol) which carry doxorubicin for chemotherapy and indocyanine green for photothermal therapy. A 0.3 mg/mL suspension of NPs increased the medium temperature up to 10 °C upon irradiation with an 808-nm diode laser. In vitro studies showed that combination of laser assisted indocyanine green-mediated photothermal therapy and doxorubicin-mediated chemotherapy effectively eradicated cancer cells and resulted in the highest level of damage-associated molecular pattern presentation (calreticulin, high mobility group box 1, and adenosine triphosphate) compared to the individual treatments alone. These results demonstrate that our nanoparticle-mediated combinatory approach led to the most intense immunogenic cell death when compared to individual chemotherapy or photothermal therapy, making it a potent option for future in vivo studies in combination with cancer immunotherapies., (Copyright © 2020 Elsevier B.V. All rights reserved.)

A key challenge in melanoma diagnosis is the large number of unnecessary biopsies on benign nevi, which requires significant amounts of time and money. To reduce unnecessary biopsies while still accurately detecting melanoma lesions, we propose using Raman spectroscopy as a non-invasive, fast, and inexpensive method for generating a "second opinion" for lesions being considered for biopsy. We collected in vivo Raman spectral data in the clinical skin screening setting from 52 patients, including 53 pigmented lesions and 7 melanomas. All lesions underwent biopsies based on clinical evaluation. Principal component analysis and logistic regression models with leave one lesion out cross validation were applied to classify melanoma and pigmented lesions for biopsy recommendations. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.903 and a specificity of 58.5% at perfect sensitivity. The number needed to treat for melanoma could have been decreased from 8.6 (60/7) to 4.1 (29/7). This study in a clinical skin screening setting shows the potential of Raman spectroscopy for reducing unnecessary skin biopsies with in vivo Raman data and is a significant step toward the application of Raman spectroscopy for melanoma screening in the clinic.

There is an increasing awareness of microplastics within the global problem of marine plastic pollution. In 2018, small plastic pellets or "nurdles" were observed on the beaches of Corpus Christi, Texas. A citizen science project, "Nurdle Patrol," was established by the Mission-Aransas National Estuarine Research Reserve to monitor the presence of nurdles, with volunteer interest enabling this project to expand across the Gulf of Mexico region. This case study describes the sampling methodology, the policy framework, and initial quantitative data from the citizen science project on nurdle distribution along the Gulf coast. A total of 2042 Nurdle Patrol surveys have been conducted by 744 citizen scientists covering shorelines from Mahahual, Mexico to Fort Jefferson, Florida. All 20 of the highest standardized nurdle counts were recorded at sites in Texas. Results can inform decision-maker response across regulatory scales and further research on nurdle pollution., Competing Interests: Declaration of competing interest None., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Spontaneous Raman micro-spectroscopy has been demonstrated great potential in delineating tumor margins; however, it is limited by slow acquisition speed. We describe a superpixel acquisition approach that can expedite acquisition between ~×100 and ×10 000, as compared to point-by-point scanning by trading off spatial resolution. We present the first demonstration of superpixel acquisition on rapid discrimination of basal cell carcinoma tumor from eight patients undergoing Mohs micrographic surgery. Results have been demonstrated high discriminant power for tumor vs normal skin based on the biochemical differences between nucleus, collagen, keratin and ceramide. We further perform raster-scanned superpixel Raman imaging on positive and negative margin samples. Our results indicate superpixel acquisition can facilitate the use of Raman microspectroscopy as a rapid and specific tool for tumor margin assessment., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low-cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Over the past century, the environment of the Gulf of Mexico has been significantly altered and impaired by extensive human activities. A national commitment to restore the Gulf was finally initiated in response to the unprecedented Deepwater Horizon oil spill in 2010. Consequently, there is a critical need for an assessment framework and associated set of indicators that can characterize the health and sustainability of an ecosystem having the scale and complexity of the Gulf. The assessment framework presented here was developed as an integration of previous ecological risk- and environmental management-based frameworks for assessing ecosystem health. It was designed to identify the natural and anthropogenic drivers, pressures, and stressors impinging on ecosystems and ecosystem services, and the ecological conditions that result, manifested as effects on valued ecosystem components. Four types of societal and ecological responses are identified: reduction of pressures and stressors, remediation of existing stressors, active ecosystem restoration, and natural ecological recovery. From this conceptual framework are derived the specific indicators to characterize ecological condition and progress toward achieving defined ecological health and sustainability goals. Additionally, the framework incorporates a hierarchical structure to communicate results to a diversity of audiences, from research scientists to environmental managers and decision makers, with the level of detail or aggregation appropriate for each targeted audience. Two proof-of-concept studies were conducted to test this integrated assessment and decision framework, a prototype Texas Coastal Ecosystems Report Card, and a pilot study on enhancing rookery islands in the Mission-Aransas Reserve, Texas, USA. This Drivers-Pressures-Stressors-Condition-Responses (DPSCR 4 ) conceptual framework is a comprehensive conceptual model of the coupled human-ecological system. Much like its predecessor, the ecological risk assessment framework, the DPSCR 4 conceptual framework can be tailored to different scales of complexity, different ecosystem types with different stress regimes, and different environmental settings. Integr Environ Assess Manag 2019;15:544-564. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

Collagen fibers are the primary structural elements that define many soft-tissue structure and mechanical function relationships, so that quantification of collagen organization is essential to many disciplines. Current tissue-level collagen fiber imaging techniques remain limited in their ability to quantify fiber organization at macroscopic spatial scales and multiple time points, especially in a non-contacting manner, requiring no modifications to the tissue, and in near real-time. Our group has previously developed polarized spatial frequency domain imaging (pSFDI), a reflectance imaging technique that rapidly and non-destructively quantifies planar collagen fiber orientation in superficial layers of soft tissues over large fields-of-view. In this current work, we extend the light scattering models and image processing techniques to extract a critical measure of the degree of collagen fiber alignment, the normalized orientation index (NOI), directly from pSFDI data. Electrospun fiber samples with architectures similar to many collagenous soft tissues and known NOI were used for validation. An inverse model was then used to extract NOI from pSFDI measurements of aortic heart valve leaflets and clearly demonstrated changes in degree of fiber alignment between opposing sides of the sample. These results show that our model was capable of extracting absolute measures of degree of fiber alignment in superficial layers of heart valve leaflets with only general a priori knowledge of fiber properties, providing a novel approach to rapid, non-destructive study of microstructure in heart valve leaflets using a reflectance geometry.

Achieving adequate margins during tumor margin resection is critical to minimize the recurrence rate and maximize positive patient outcomes during skin cancer surgery. Although Mohs micrographic surgery is by far the most effective method to treat nonmelanoma skin cancer, it can be limited by its inherent required infrastructure, including time-consuming and expensive on-site histopathology. Previous studies have demonstrated that Raman spectroscopy can accurately detect basal cell carcinoma (BCC) from surrounding normal tissue; however, the biophysical basis of the detection remained unclear. Therefore, we aim to explore the relevant Raman biomarkers to guide BCC margin resection. Raman imaging was performed on skin tissue samples from 30 patients undergoing Mohs surgery. High correlations were found between the histopathology and Raman images for BCC and primary normal structures (including epidermis, dermis, inflamed dermis, hair follicle, hair shaft, sebaceous gland and fat). A previously developed model was used to extract the biochemical changes associated with malignancy. Our results showed that BCC had a significantly different concentration of nucleus, keratin, collagen, triolein and ceramide compared to normal structures. The nucleus accounted for most of the discriminant power (90% sensitivity, 92% specificity - balanced approach). Our findings suggest that Raman spectroscopy is a promising surgical guidance tool for identifying tumors in the resection margins., Competing Interests: The authors declare that there are no conflicts of interest related to this article.

Raman spectroscopy (RS) has demonstrated great potential for in vivo cancer screening; however, the biophysical changes that occur for specific diagnoses remain unclear. We recently developed an inverse biophysical skin cancer model to address this issue. Here, we presented the first demonstration of in vivo melanoma and nonmelanoma skin cancer (NMSC) detection based on this model. We fit the model to our previous clinical dataset and extracted the concentration of eight Raman active components in 100 lesions in 65 patients diagnosed with malignant melanoma (MM), dysplastic nevi (DN), basal cell carcinoma, squamous cell carcinoma, and actinic keratosis. We then used logistic regression and leave-one-lesion-out cross validation to determine the diagnostically relevant model components. Our results showed that the biophysical model captures the diagnostic power of the previously used statistical classification model while also providing the skin's biophysical composition. In addition, collagen and triolein were the most relevant biomarkers to represent the spectral variances between MM and DN, and between NMSC and normal tissue. Our work demonstrates the ability of RS to reveal the biophysical basis for accurate diagnosis of different skin cancers, which may eventually lead to a reduction in the number of unnecessary excisional skin biopsies performed., ((2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).)

Coralgal reefs preserve the signatures of sea-level fluctuations over Earth's history, in particular since the Last Glacial Maximum 20,000 years ago, and are used in this study to indicate that punctuated sea-level rise events are more common than previously observed during the last deglaciation. Recognizing the nature of past sea-level rises (i.e., gradual or stepwise) during deglaciation is critical for informing models that predict future vertical behavior of global oceans. Here we present high-resolution bathymetric and seismic sonar data sets of 10 morphologically similar drowned reefs that grew during the last deglaciation and spread 120 km apart along the south Texas shelf edge. Herein, six commonly observed terrace levels are interpreted to be generated by several punctuated sea-level rise events forcing the reefs to shrink and backstep through time. These systematic and common terraces are interpreted to record punctuated sea-level rise events over timescales of decades to centuries during the last deglaciation, previously recognized only during the late Holocene.

Immune checkpoint therapy has become the first widely adopted immunotherapy for patients with late stage malignant melanoma, with potential for a wide range of cancers. While some patients can experience long term disease remission, this is limited only to a subset of patients and tumor types. The path forward to expand this therapy to more patients and tumor types is currently thought to be combinatorial treatments, the combination of immunotherapy with other treatments. In this review, the combinatorial approach of immune checkpoint therapy combined with nanoparticle-assisted localized hyperthermia is discussed, starting with an overview of the different nanoparticle hyperthermia approaches in development, an overview of the state of immune checkpoint therapy, recent reports of immune checkpoint therapy and nanoparticle-assisted hyperthermia in a combinatorial approach, and finally a discussion of future research topics and areas to be explored in this new combinatorial approach to cancer treatment., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Raman spectroscopy (RS) has shown great potential in noninvasive cancer screening. Statistically based algorithms, such as principal component analysis, are commonly employed to provide tissue classification; however, they are difficult to relate to the chemical and morphological basis of the spectroscopic features and underlying disease. As a result, we propose the first Raman biophysical model applied to in vivo skin cancer screening data. We expand upon previous models by utilizing in situ skin constituents as the building blocks, and validate the model using previous clinical screening data collected from a Raman optical fiber probe. We built an 830nm confocal Raman microscope integrated with a confocal laser-scanning microscope. Raman imaging was performed on skin sections spanning various disease states, and multivariate curve resolution (MCR) analysis was used to resolve the Raman spectra of individual in situ skin constituents. The basis spectra of the most relevant skin constituents were combined linearly to fit in vivo human skin spectra. Our results suggest collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin and water are the most important model components. We make available for download (see supplemental information) a database of Raman spectra for these eight components for others to use as a reference. Our model reveals the biochemical and structural makeup of normal, nonmelanoma and melanoma skin cancers, and precancers and paves the way for future development of this approach to noninvasive skin cancer diagnosis.

Fibrous structures are an integral and dynamic feature of soft biological tissues that are directly related to the tissues' condition and function. A greater understanding of mechanical tissue behavior can be gained through quantitative analyses of structure alone, as well as its integration into computational models of soft tissue function. Histology and other nonoptical techniques have traditionally dominated the field of tissue imaging, but they are limited by their invasiveness, inability to provide resolution on the micrometer scale, and dynamic information. Recent advances in optical modalities can provide higher resolution, less invasive imaging capabilities, and more quantitative measurements. Here we describe contemporary optical imaging techniques with respect to their suitability in the imaging of tissue structure, with a focus on characterization and implementation into subsequent modeling efforts. We outline the applications and limitations of each modality and discuss the overall shortcomings and future directions for optical imaging of soft tissue structure.

We illustrate wide-field imaging of skin using a structured light (SL) approach that highlights the contrast from superficial tissue scattering. Setting the spatial frequency of the SL in a regime that limits the penetration depth effectively gates the image for photons that originate from the skin surface. Further, rendering the SL images in a color format provides an intuitive format for viewing skin pathologies. We demonstrate this approach in skin pathologies using a custom-built handheld SL imaging system.

Our group previously introduced Polarized Spatial Frequency Domain Imaging (PSFDI), a wide-field, reflectance imaging technique which we used to empirically map fiber direction in porcine pulmonary heart valve leaflets (PHVL) without optical clearing or physical sectioning of the sample. Presented is an extended analysis of our PSFDI results using an inverse Mueller matrix model of polarized light scattering that allows additional maps of fiber orientation distribution, along with instrumentation permitting increased imaging speed for dynamic PHVL fiber measurements. We imaged electrospun fiber phantoms with PSFDI, and then compared these measurements to SEM data collected for the same phantoms. PHVL was then imaged and compared to results of the same leaflets optically cleared and imaged with small angle light scattering (SALS). The static PHVL images showed distinct regional variance of fiber orientation distribution, matching our SALS results. We used our improved imaging speed to observe bovine tendon subjected to dynamic loading using a biaxial stretching device. Our dynamic imaging experiment showed trackable changes in the fiber microstructure of biological tissue under loading. Our new PSFDI analysis model and instrumentation allows characterization of fiber structure within heart valve tissues (as validated with SALS measurements), along with imaging of dynamic fiber remodeling. The experimental data will be used as inputs to our constitutive models of PHVL tissue to fully characterize these tissues' elastic behavior, and has immediate application in determining the mechanisms of structural and functional failure in PHVLs used as bio-prosthetic implants.

The Ixtoc-I oil spill occurred in 1979 in shallow waters (50 m) of the Bay of Campeche, Mexico. Although it is known that a large portion of the released oil from this second largest accidental marine oil spill in history reached the surface, to date there has been no attempt to document the surface footprint and trajectory of the released oil. Our study attempts to fill this knowledge gap using remote sensing data collected by Landsat/MSS and CZCS. Both showed the same general patterns of oil trajectory to the northwest and north, nearly parallel to the coastline of the western Gulf of Mexico (GoM) with possible oil landing on Mexican and Texas beaches. Field observations at selected beaches and islands along the coast of the western and southern GoM during and after the spill confirmed these satellite-based findings, which were also used to help in planning a recent field campaign to collect sediment samples in the southern GoM., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The measurement of soft tissue fiber orientation is fundamental to pathophysiology and biomechanical function in a multitude of biomedical applications. However, many existing techniques for quantifying fiber structure rely on transmitted light, limiting general applicability and often requiring tissue processing. Herein, we present a novel wide-field reflectance-based imaging modality, which combines polarized light imaging (PLI) and spatial frequency domain imaging (SFDI) to rapidly quantify preferred fiber orientation on soft collagenous tissues. PLI utilizes the polarization dependent scattering property of fibers to determine preferred fiber orientation; SFDI imaging at high spatial frequency is introduced to reject the highly diffuse photons and to control imaging depth. As a result, photons scattered from the superficial layer of a multi-layered sample are highlighted. Thus, fiber orientation quantification can be achieved for the superficial layer with optical sectioning. We demonstrated on aortic heart valve leaflet that, at spatial frequency of f = 1mm(-1) , the diffuse background can be effectively rejected and the imaging depth can be limited, thus improving quantification accuracy.

Diffuse reflectance spectroscopy (DRS) can be used to noninvasively measure skin properties. To extract skin properties from DRS spectra, you need a model that relates the reflectance to the tissue properties. Most models are based on the assumption that skin is homogenous. In reality, skin is composed of multiple layers, and the homogeneity assumption can lead to errors. In this study, we analyze the errors caused by the homogeneity assumption. This is accomplished by creating realistic skin spectra using a computational model, then extracting properties from those spectra using a one-layer model. The extracted parameters are then compared to the parameters used to create the modeled spectra. We used a wavelength range of 400 to 750 nm and a source detector separation of 250 μm. Our results show that use of a one-layer skin model causes underestimation of hemoglobin concentration [Hb] and melanin concentration [mel]. Additionally, the magnitude of the error is dependent on epidermal thickness. The one-layer assumption also causes [Hb] and [mel] to be correlated. Oxygen saturation is overestimated when it is below 50% and underestimated when it is above 50%. We also found that the vessel radius factor used to account for pigment packaging is correlated with epidermal thickness., (© The Authors.)

The design and characterization of an instrument combining Raman, fluorescence, and reflectance spectroscopic modalities is presented. Instrument development has targeted skin cancer applications as a novel fiber-optic probe has been specially designed to interrogate cutaneous lesions. The instrument is modular and both its software and hardware components are described in depth. Characterization of the fiber-optic probe is also presented, which details the probe's ability to measure diagnostically important parameters such as intrinsic fluorescence and absorption and reduced scattering coefficients along with critical performance metrics such as high Raman signal-to-noise ratios at clinically practical exposure times. Validation results using liquid phantoms show that the probe and system can extract absorption and scattering coefficients with less than 10% error. As the goal is to use the instrument for the clinical early detection of skin cancer, preliminary clinical data are also presented, which indicates our system's ability to measure physiological quantities such as relative collagen and nicotinamide adenine dinucleotide concentration, oxygen saturation, blood volume fraction, and mean vessel diameter.

Diffuse reflectance spectroscopy provides a noninvasive means to measure optical and physiological properties of tissues. To expand on these measurements, we have developed a handheld diffuse reflectance spectral imaging (DRSi) system capable of acquiring wide field hyperspectral images of tissue. The image acquisition time was approximately 50 seconds for a 50x50 pixel image. A transport model was used to fit each spectra for reduced scattering coefficient, hemoglobin concentration and melanin concentration resulting in optical property maps. The system was validated across biologically relevant levels of reduced scattering (5.14% error) and absorption (8.34% error) using tissue simulating phantoms. DRSi optical property maps of a pigmented skin lesion were acquired in vivo. These trends in optical properties were consistent with previous observations using point probe devices.

The guest editors introduce a Biomedical Optics Express feature issue that includes contributions from participants at the 2013 conference on Advances in Optics for Biotechnology, Medicine and Surgery XIII.

The goal of this study was to determine the diagnostic capability of a multimodal spectral diagnosis (SD) for in vivo noninvasive disease diagnosis of melanoma and nonmelanoma skin cancers. We acquired reflectance, fluorescence, and Raman spectra from 137 lesions in 76 patients using custom-built optical fiber-based clinical systems. Biopsies of lesions were classified using standard histopathology as malignant melanoma (MM), nonmelanoma pigmented lesion (PL), basal cell carcinoma (BCC), actinic keratosis (AK), and squamous cell carcinoma (SCC). Spectral data were analyzed using principal component analysis. Using multiple diagnostically relevant principal components, we built leave-one-out logistic regression classifiers. Classification results were compared with histopathology of the lesion. Sensitivity/specificity for classifying MM versus PL (12 versus 17 lesions) was 100%/100%, for SCC and BCC versus AK (57 versus 14 lesions) was 95%/71%, and for AK and SCC and BCC versus normal skin (71 versus 71 lesions) was 90%/85%. The best classification for nonmelanoma skin cancers required multiple modalities; however, the best melanoma classification occurred with Raman spectroscopy alone. The high diagnostic accuracy for classifying both melanoma and nonmelanoma skin cancer lesions demonstrates the potential for SD as a clinical diagnostic device.

The sampling depth of light for diffuse reflectance spectroscopy is analyzed both experimentally and computationally. A Monte Carlo (MC) model was used to investigate the effect of optical properties and probe geometry on sampling depth. MC model estimates of sampling depth show an excellent agreement with experimental measurements over a wide range of optical properties and probe geometries. The MC data are used to define a mathematical expression for sampling depth that is expressed in terms of optical properties and probe geometry parameters.

A two-layer Monte Carlo lookup table-based inverse model is validated with two-layered phantoms across physiologically relevant optical property ranges. Reflectance data for source-detector separations of 370 μm and 740 μm were collected from these two-layered phantoms and top layer thickness, reduced scattering coefficient and the top and bottom layer absorption coefficients were extracted using the inverse model and compared to the known values. The results of the phantom verification show that this method is able to accurately extract top layer thickness and scattering when the top layer thickness ranges from 0 to 550 μm. In this range, top layer thicknesses were measured with an average error of 10% and the reduced scattering coefficient was measured with an average error of 15%. The accuracy of top and bottom layer absorption coefficient measurements was found to be highly dependent on top layer thickness, which agrees with physical expectation; however, within appropriate thickness ranges, the error for absorption properties varies from 12-25%.

We present a Monte Carlo lookup table (MCLUT)-based inverse model for extracting optical properties from tissue-simulating phantoms. This model is valid for close source-detector separation and highly absorbing tissues. The MCLUT is based entirely on Monte Carlo simulation, which was implemented using a graphics processing unit. We used tissue-simulating phantoms to determine the accuracy of the MCLUT inverse model. Our results show strong agreement between extracted and expected optical properties, with errors rate of 1.74% for extracted reduced scattering values, 0.74% for extracted absorption values, and 2.42% for extracted hemoglobin concentration values.

Introduction: Near-infrared (NIR) absorbing plasmonic nanoparticles enhance photothermal therapy of tumors. In this procedure, systemically delivered gold nanoparticles preferentially accumulate at the tumor site and when irradiated using laser light, produce localized heat sufficient to damage tumor cells. Gold nanoshells and nanorods have been widely studied for this purpose, and while both exhibit strong NIR absorption, their overall absorption and scattering properties differ widely due to their geometry. In this paper, we compared the photothermal response of both nanoparticle types including the heat generation and photothermal efficiency., Methods: Tissue simulating phantoms, with varying concentrations of gold nanoparticles, were irradiated with a near-infrared diode laser while concurrently monitoring the surface temperature with an infrared camera. We calculated nanoshell and nanorod optical properties using the Mie solution and the discrete dipole approximation, respectively. In addition, we measured the heat generation of nanoshells and nanorods at the same optical density to determine the photothermal transduction efficiency for both nanoparticle types., Results: We found that the gold nanoshells produced more heat than gold nanorods at equivalent number densities (# of nanoparticles/ml), whereas the nanorods generated more heat than nanoshells at equivalent extinction values at the irradiance wavelength. To reach an equivalent heat generation, we found that it was necessary to have ∼36× more nanorods than nanoshells. However, the gold nanorods were found to have two times the photothermal transduction efficiency than the gold nanoshells., Conclusion: For the nanoparticles tested, the nanoshells generated more heat, per nanoparticle, than nanorods, primarily due to their overall larger geometric cross-section. Conversely, we found that the gold nanorods had a higher photothermal efficiency than the gold nanoshells. In conclusion, the ideal choice of plasmonic nanoparticle requires not only per particle efficiency, but also the in vivo particle targeting ability under study., (Copyright © 2012 Wiley Periodicals, Inc.)

Diffuse optical spectroscopy (DOS) provides a powerful tool for fast and noninvasive disease diagnosis. The ability to leverage DOS to accurately quantify tissue optical parameters hinges on the model used to estimate light-tissue interaction. We describe the accuracy of a lookup table (LUT)-based inverse model for measuring optical properties under different conditions relevant to biological tissue. The LUT is a matrix of reflectance values acquired experimentally from calibration standards of varying scattering and absorption properties. Because it is based on experimental values, the LUT inherently accounts for system response and probe geometry. We tested our approach in tissue phantoms containing multiple absorbers, different sizes of scatterers, and varying oxygen saturation of hemoglobin. The LUT-based model was able to extract scattering and absorption properties under most conditions with errors of less than 5 percent. We demonstrate the validity of the lookup table over a range of source-detector separations from 0.25 to 1.48 mm. Finally, we describe the rapid fabrication of a lookup table using only six calibration standards. This optimized LUT was able to extract scattering and absorption properties with average RMS errors of 2.5 and 4 percent, respectively.

Background: Nanoparticles have recently gained interest as exogenous contrast agents in a variety of biomedical applications related to cancer detection and treatment. The objective of this study was to determine the potential of topically administered antibody conjugated gold nanorods (GNRs) for imaging squamous cell carcinomas (SCCs) of the skin using near-infrared narrowband imaging (NBI). Near-infrared (NIR) NBI images narrow wavelength bands to enhance contrast from plasmonic particles in a wide field portable and noncontact device that is clinically compatible for real-time tumor imaging and tumor margin demarcation., Study Design: We conjugated GNRs to Cetuximab, a clinically approved humanized antibody that targets the epidermal growth factor receptor (EGFR), which is overexpressed on the surface of many tumor cells, especially SCCs. We excised subcutaneous xenografts of SCCs (A431) from Swiss nu/nu mice and divided the tumors into two groups: (1) the targeted group (Cetuximab conjugated GNRs) and (2) the control group (polyethylene glycol-conjugated GNRs). After topical application of particles and incubation for 30 minutes, the tumors were washed and imaged using NBI. In addition, we performed two-photon imaging to quantify the binding of EGFR targeted GNRs in tumors and their depth profile., Results: The NBI images showed a visual increase in contrast from tumors after topical administration of targeted GNR. Targeted GNR tumors showed increased contrast compared to tumors administered with the control GNR. There was a statistically significant increase in mean pixel intensity (∼2.5×) from targeted GNR tumors (n = 6). Two-photon microscopy images of targeted GNRs confirmed their binding affinity to the EGF receptors over expressed in the A431 tumors., Conclusion: We have demonstrated that a topical application of gold nanorods targeted specifically to tumor growth factor receptors results in a significantly higher image contrast compared to nontargeted gold nanorods. These results demonstrate the feasibility of near-infrared NBI to image and demarcate tumor margins during surgical resection using topical administration of targeted GNR., (Copyright © 2012 Wiley Periodicals, Inc.)