Label-Free Optical Technologies for Middle-Ear Diseases.

Medical applications of optical technology have increased tremendously in recent decades. Label-free techniques have the unique advantage of investigating biological samples in vivo without introducing exogenous agents. This is especially beneficial for a rapid clinical translation as it reduces the need for toxicity studies and regulatory approval for exogenous labels. Emerging applications have utilized label-free optical technology for screening, diagnosis, and surgical guidance. Advancements in detection technology and rapid improvements in artificial intelligence have expedited the clinical implementation of some optical technologies. Among numerous biomedical application areas, middle-ear disease is a unique space where label-free technology has great potential. The middle ear has a unique anatomical location that can be accessed through a dark channel, the external auditory canal; it can be sampled through a tympanic membrane of approximately 100 microns in thickness. The tympanic membrane is the only membrane in the body that is surrounded by air on both sides, under normal conditions. Despite these favorable characteristics, current examination modalities for middle-ear space utilize century-old technology such as white-light otoscopy. This paper reviews existing label-free imaging technologies and their current progress in visualizing middle-ear diseases. We discuss potential opportunities, barriers, and practical considerations when transitioning label-free technology to clinical applications.

Indigenous institutions as adaptive measures to environmental dynamics: an ethnographic study of Loba Community of Upper Mustang, Nepal.

This paper investigates how different institutions of Loba communities of the Upper Mustang work together and facilitate the community to cope with the environmental dynamics in the region. The indigenous institutions are place-based, and their evolution is concerned with reducing vulnerability and enhancing the resilience capacity of place-based communities to cope with and adapt to local natural and socio-cultural environmental dynamics. The paper is based on anthropological fieldwork. Qualitative data were collected by applying observation and interviews. The paper presents the role of the galbo, (Lo King), ghenba (Village Chief), Lama (Monk), and dhongba (Household) as local institutions that act in close relation and make community-level decisions. The findings reveal that the King is seen as the leader whose governance best suited to the local natural environment, cultural practices, and economy. The Lama plays a major role in reinforcing local rules, while the Ghenba is an agent who mediates the Lo King and people in materializing rules and operationalizing institutional mechanisms. The Dhongbas are units of production of the local social-ecosystem that are entitled to use local resources within the context of the institution's agreed rules, norms, and values. These local institutions are cooperating well, successfully regulating, managing, and protecting agricultural, forest, and pasture lands, and maintaining the monuments in Lo-manthang for centuries. However, recent social-environmental dynamics such as climate change, migration, and modernization are reducing the relevancies of traditional norms and practices. Nevertheless, the institutions are working hard to continue their existence by frequently modifying their rules and norms.

AI-Powered Biomolecular-Specific and Label-Free Multispectral Imaging Rapidly Detects Malignant Neoplasm in Surgically Excised Breast Tissue Specimens.

CONTEXT.­: Repeated surgery is necessary for 20% to 40% of breast conservation surgeries owing to the unavailability of any adjunctive, accurate, and objective tool in the surgeon's hand for real-time margin assessment to achieve the desired balance of oncologic and cosmetic outcomes. OBJECTIVE.­: To assess the feasibility of using a multispectral autofluorescence imaging device for discriminating malignant neoplasm from normal breast tissue in pathology as a critical step in the development of a device for intraoperative use, and to demonstrate the device's utility for use in processing and prioritizing specimens during frozen section and in the pathology grossing room. DESIGN.­: We performed a preliminary assessment of our device, called the TumorMAP system, on 172 fresh tissue blocks from 115 patients obtained from lumpectomy specimens at the time of initial gross examination and compared the device results with gold standard pathology evaluation. RESULTS.­: The preliminary results demonstrate the potential of our device in detecting breast cancer in fresh tissue samples with a sensitivity of 82%, a specificity of 91%, a positive predictive value of 84%, and a negative predictive value of 89%. CONCLUSIONS.­: Our results suggest that the TumorMAP system is suitable for the detection of malignant neoplasm in freshly excised breast specimens and has the potential to evaluate resection margins in real time.

High-throughput digital pathology via a handheld, multiplexed, and AI-powered ptychographic whole slide scanner.

The recent advent of whole slide imaging (WSI) systems has moved digital pathology closer to diagnostic applications and clinical practices. Integrating WSI with machine learning promises the growth of this field in upcoming years. Here we report the design and implementation of a handheld, colour-multiplexed, and AI-powered ptychographic whole slide scanner for digital pathology applications. This handheld scanner is built using low-cost and off-the-shelf components, including red, green, and blue laser diodes for sample illumination, a modified stage for programmable sample positioning, and a synchronized image sensor pair for data acquisition. We smear a monolayer of goat blood cells on the main sensor for high-resolution lensless coded ptychographic imaging. The synchronized secondary sensor acts as a non-contact encoder for precisely tracking the absolute object position for ptychographic reconstruction. For WSI, we introduce a new phase-contrast-based focus metric for post-acquisition autofocusing of both stained and unstained specimens. We show that the scanner can resolve the 388-nm linewidth on the resolution target and acquire gigapixel images with a 14 mm × 11 mm area in ∼70 seconds. The imaging performance is validated with regular stained pathology slides, unstained thyroid smears, and malaria-infected blood smears. The deep neural network developed in this study further enables high-throughput cytometric analysis using the recovered complex amplitude. The reported do-it-yourself scanner offers a portable solution to transform the high-end WSI system into one that can be made widely available at a low cost. The capability of high-throughput quantitative phase imaging may also find applications in rapid on-site evaluations.

TCA cycle off, ATF4 on for metabolic homeostasis.

Tricarboxylic acid (TCA) cycle is a major hub for catabolic and anabolic reactions, yet cellular metabolic adaptations following its inhibition are largely unknown. Using multi-tiered omics approaches, Ryan et al. have shown convergent activation of the integrated stress response (ISR) through ATF4-mediated rewiring of cellular amino acid and redox metabolic pathways.

Injectable amnion hydrogel-mediated delivery of adipose-derived stem cells for osteoarthritis treatment.

Current treatment strategies for osteoarthritis (OA) predominantly address symptoms with limited disease-modifying potential. There is a growing interest in the use of adipose-derived stem cells (ADSCs) for OA treatment and developing biomimetic injectable hydrogels as cell delivery systems. Biomimetic injectable hydrogels can simulate the native tissue microenvironment by providing appropriate biological and chemical cues for tissue regeneration. A biomimetic injectable hydrogel using amnion membrane (AM) was developed which can self-assemble in situ and retain the stem cells at the target site. In the present study, we evaluated the efficacy of intraarticular injections of AM hydrogels with and without ADSCs in reducing inflammation and cartilage degeneration in a collagenase-induced OA rat model. A week after the induction of OA, rats were treated with control (phosphate-buffered saline), ADSCs, AM gel, and AM-ADSCs. Inflammation and cartilage regeneration was evaluated by joint swelling, analysis of serum by cytokine profiling and Raman spectroscopy, gross appearance, and histology. Both AM and ADSC possess antiinflammatory and chondroprotective properties to target the sites of inflammation in an osteoarthritic joint, thereby reducing the inflammation-mediated damage to the articular cartilage. The present study demonstrated the potential of AM hydrogel to foster cartilage tissue regeneration, a comparable regenerative effect of AM hydrogel and ADSCs, and the synergistic antiinflammatory and chondroprotective effects of AM and ADSC to regenerate cartilage tissue in a rat OA model.

Vibrational spectroscopy for decoding cancer microbiota interactions: Current evidence and future perspective.

The role of human microbiota in cancer initiation and progression is recognized in recent years. In order to investigate the interactions between cancer cells and microbes, a systematic analysis using various emerging techniques is required. Owing to the label-free, non-invasive and molecular fingerprinting characteristics, vibrational spectroscopy is uniquely suited to decode and understand the relationship and interactions between cancer and the microbiota at the molecular level. In this review, we first provide a quick overview of the fundamentals of vibrational spectroscopic techniques, namely Raman and infrared spectroscopy. Next, we discuss the emerging evidence underscoring utilities of these spectroscopic techniques to study cancer or microbes separately, and share our perspective on how vibrational spectroscopy can be employed at the intersection of the two fields. Finally, we envision the potential opportunities in exploiting vibrational spectroscopy not only in basic cancer-microbiome research but also in its clinical translation, and discuss the challenges in the bench to bedside translation.

Advancing Raman spectroscopy from research to clinic: Translational potential and challenges.

Raman spectroscopy has emerged as a non-invasive and versatile diagnostic technique due to its ability to provide molecule-specific information with ultrahigh sensitivity at near-physiological conditions. Despite exhibiting substantial potential, its translation from optical bench to clinical settings has been impacted by associated limitations. This perspective discusses recent clinical and biomedical applications of Raman spectroscopy and technological advancements that provide valuable insights and encouragement for resolving some of the most challenging hurdles.

Raman and quantitative phase imaging allow morpho-molecular recognition of malignancy and stages of B-cell acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is one of the most common malignancies that account for nearly one-third of all pediatric cancers. The current diagnostic assays are time-consuming, labor-intensive, and require expensive reagents. Here, we report a label-free approach featuring diffraction phase imaging and Raman microscopy that can retrieve both morphological and molecular attributes for label-free optical phenotyping of individual B cells. By investigating leukemia cell lines of early and late stages along with the healthy B cells, we show that phase images can capture subtle morphological differences among the healthy, early, and late stages of leukemic cells. By exploiting its biomolecular specificity, we demonstrate that Raman microscopy is capable of accurately identifying not only different stages of leukemia cells but also individual cell lines at each stage. Overall, our study provides a rationale for employing this hybrid modality to screen leukemia cells using the widefield QPI and using Raman microscopy for accurate differentiation of early and late-stage phenotypes. This contrast-free and rapid diagnostic tool exhibits great promise for clinical diagnosis and staging of leukemia in the near future.

Coarse Raman and optical diffraction tomographic imaging enable label-free phenotyping of isogenic breast cancer cells of varying metastatic potential.

Identification of the metastatic potential represents one of the most important tasks for molecular imaging of cancer. While molecular imaging of metastases has witnessed substantial progress as an area of clinical inquiry, determining precisely what differentiates the metastatic phenotype has proven to be more elusive. In this study, we utilize both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to propose a label-free route for optical phenotyping of cancer cells at single-cell resolution. By using an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential, we show that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging its molecular specificity, we demonstrate that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single-cell level. We also perform multivariate curve resolution alternating least squares decomposition of the spectral dataset to demarcate spectra from cytoplasm and nucleus, and test the feasibility of identifying metastatic phenotypes using the spectra only from the cytoplasmic and nuclear regions. Overall, our study provides a rationale for employing coarse Raman mapping to substantially reduce measurement time thereby enabling the acquisition of reasonably large training datasets that hold the key for label-free single-cell analysis and, consequently, for differentiation of indolent from aggressive phenotypes.

Identification and Staging of B-Cell Acute Lymphoblastic Leukemia Using Quantitative Phase Imaging and Machine Learning.

Identification and classification of leukemia cells in a rapid and label-free fashion is clinically challenging and thus presents a prime arena for implementing new diagnostic tools. Quantitative phase imaging, which maps optical path length delays introduced by the specimen, has been demonstrated to discern cellular phenotypes based on differential morphological attributes. Rapid acquisition capability and the availability of label-free images with high information content have enabled researchers to use machine learning (ML) to reveal latent features. We developed a set of ML classifiers, including convolutional neural networks, to discern healthy B cells from lymphoblasts and classify stages of B cell acute lymphoblastic leukemia. Here, we show that the average dry mass and volume of normal B cells are lower than those of cancerous cells and that these morphologic parameters increase further alongside disease progression. We find that the relaxed training requirements of a ML approach are conducive to the classification of cell type, with minimal space, training time, and memory requirements. Our findings pave the way for a larger study on clinical samples of acute lymphoblastic leukemia, with the overarching goal of its broader use in hematopathology, where the prospect of objective diagnoses with minimal sample preparation remains highly desirable.

Preparation and characterization of amnion hydrogel and its synergistic effect with adipose derived stem cells towards IL1ß activated chondrocytes.

Inflammation leads to chondrocyte senescence and cartilage degeneration, resulting in osteoarthritis (OA). Adipose-derived stem cells (ADSCs) exert paracrine effects protecting chondrocytes from degenerative changes. However, the lack of optimum delivery systems for ADSCs limits its use in the clinic. The use of extracellular matrix based injectable hydrogels has gained increased attention due to their unique properties. In the present study, we developed hydrogels from amnion tissue as a delivery system for ADSCs. We investigated the potential of amnion hydrogel to maintain ADSC functions, the synergistic effect of AM with ADSC in preventing the catabolic responses of inflammation in stimulated chondrocytes. We also investigated the role of Wnt/ß-catenin signaling pathway in IL-1ß induced inflammation in chondrocytes and the ability of AM-ADSC to inhibit Wnt/ß-catenin signaling. Our results showed that AM hydrogels supported cell viability, proliferation, and stemness. ADSCs, AM hydrogels and AM-ADSCs inhibited the catabolic responses of IL-1ß and inhibited the Wnt/ß-catenin signaling pathway, indicating possible involvement of Wnt/ß-catenin signaling pathways in IL-1ß induced inflammation. The results also showed that the synergistic effect of AM-ADSCs was more pronounced in preventing catabolic responses in activated chondrocytes. In conclusion, we showed that AM hydrogels can be used as a potential carrier for ADSCs, and can be developed as a potential therapeutic agent for treating OA.

Reagent-Free and Rapid Assessment of T Cell Activation State Using Diffraction Phase Microscopy and Deep Learning.

CD8+ T cells constitute an essential compartment of the adaptive immune system. During immune responses, naïve T cells become functional, as they are primed with their cognate determinants by the antigen presenting cells. Current methods of identifying activated CD8+ T cells are laborious, time-consuming and expensive due to the extensive list of required reagents. Here, we demonstrate an optical imaging approach featuring quantitative phase imaging to distinguish activated CD8+ T cells from naïve CD8+ T cells in a rapid and reagent-free manner. We measured the dry mass of live cells and employed transport-based morphometry to better understand their differential morphological attributes. Our results reveal that, upon activation, the dry cell mass of T cells increases significantly in comparison to that of unstimulated cells. By employing deep learning formalism, we are able to accurately predict the population ratios of unknown mixed population based on the acquired quantitative phase images. We envision that, with further refinement, this label-free method of T cell phenotyping will lead to a rapid and cost-effective platform for assaying T cell responses to candidate antigens in the near future.

High Power Density Low-Lead-Piezoceramic-Polymer Composite Energy Harvester.

Polymer-piezoceramic composites show mutual properties of piezoceramics and polymers that can be efficiently utilized in energy harvesting applications. Here we fabricated 0-3 composite films using high-performance low-lead piezoceramic (x)Bi(Ni1/2Zr1/2)O3-(1-x)PbTiO3 (BNZ-PT) as ceramic filler and polyvinylidene fluoride (PVDF) as polymer matrix. Unlike the conventional morphotropic phase boundary piezoelectrics such as the (1-x)PbTiO3-(x)PbZrO3, the large piezoelectric response of the BNZ-PT can be obtained by poling-induced cubic-like-to-tetragonal phase transformation. This leads to high piezoelectric coefficient of the PVDF-BNZ-PT composite films as well as high-energy harvesting performance. Composite films with different volume fractions of ceramic showed surface power density of 1.3- [Formula: see text]/cm2, and volume power density of 72.2- [Formula: see text]/cm3 using simple bending and unbending movements. Energy harvester in the form of cantilever fixed at both ends showed surface power density of 56.97- [Formula: see text]/cm2 and volume power density of 3165- [Formula: see text]/cm3 in response to impact pressure pulses. The generated power from the composite films is comparable to composite energy generators reported to date. The volume power density, however, is highest to the best of our knowledge among the reported 0-3 polymer-piezoceramic composite energy harvesters.

Integration of diffraction phase microscopy and Raman imaging for label-free morpho-molecular assessment of live cells.

Label-free quantitative imaging is highly desirable for studying live cells by extracting pathophysiological information without perturbing cell functions. Here, we demonstrate a novel label-free multimodal optical imaging system with the capability of providing comprehensive morphological and molecular attributes of live cells. Our morpho-molecular microscopy (3M) system draws on the combined strength of quantitative phase microscopy (QPM) and Raman microscopy to probe the morphological features and molecular fingerprinting characteristics of each cell under observation. While the commonr-path geometry of our QPM system allows for highly sensitive phase measurement, the Raman microscopy is equipped with dual excitation wavelengths and utilizes the same detection and dispersion system, making it a distinctive multi-wavelength system with a small footprint. We demonstrate the applicability of the 3M system by investigating nucleated and nonnucleated cells. This integrated label-free platform has a promising potential in preclinical research, as well as in clinical diagnosis in the near future.

Label-free spectrochemical probe for determination of hemoglobin glycation in clinical blood samples.

Glycated hemoglobin, HbA1c, is an important biomarker that reveals the average value of blood glucose over the preceding 3 months. While significant recent attention has been focused on the use of optical and direct molecular spectroscopic methods for determination of HbA1c, a facile test that minimizes sample preparation needs and turnaround time still remains elusive. Here, we report a label-free approach for identifying low, mid and high-HbA1c groups in hemolysate and in whole blood samples featuring resonance Raman (RR) spectroscopy and support vector machine (SVM)-based classification of spectral patterns. The diagnostic power of RR measurements stems from its selective enhancement of hemoglobin-specific features, which simultaneously minimizes the blood matrix spectral interference and permits detection in the native solution. In this pilot study, our spectroscopic observations reveal that glycation of hemoglobin results in subtle but reproducible changes even when detected in the whole blood matrix. Leveraging SVM analysis of the principal component scores determined from the RR spectra, we show high degree of accuracy in classifying clinical specimen. We envisage that the promising findings will pave the way for more extensive clinical specimen investigations with the ultimate goal of translating molecular spectroscopy for routine point-of-care testing.

Electrostrain in excess of 1% in polycrystalline piezoelectrics.

Piezoelectric actuators transform electrical energy into mechanical energy, and because of their compactness, quick response time and accurate displacement, they are sought after in many applications. Polycrystalline piezoelectric ceramics are technologically more appealing than single crystals due to their simpler and less expensive processing, but have yet to display electrostrain values that exceed 1%. Here we report a material design strategy wherein the efficient switching of ferroelectric-ferroelastic domains by an electric field is exploited to achieve a high electrostrain value of 1.3% in a pseudo-ternary ferroelectric alloy system, BiFeO3-PbTiO3-LaFeO3. Detailed structural investigations reveal that this electrostrain is associated with a combination of several factors: a large spontaneous lattice strain of the piezoelectric phase, domain miniaturization, a low-symmetry ferroelectric phase and a very large reverse switching of the non-180° domains. This insight for the design of a new class of polycrystalline piezoceramics with high electrostrains may be useful to develop alternatives to costly single-crystal actuators.

Differential diagnosis of otitis media with effusion using label-free Raman spectroscopy: A pilot study.

Otitis media with effusion (OME) is an important and common condition affecting hearing in pediatric patients characterized by the presence of fluid in the middle ear space. The fluid is normally described as serous or mucoid based on differences in the fluid viscosity. The differential diagnosis of two OMEs, namely serous and mucoid is of significant clinical value because while the former is self-limiting, surgical procedure is commonly required for the latter. However, accurate identification of fluid types remains a challenging target unattainable with current clinical modalities due to unavailability of nonperturbative molecular tools. Here, we report an emerging spectroscopy approach featuring Raman scattering and multivariate analysis of spectral patterns to discern serous and mucoid fluids, obtained from pediatric patients undergoing myringotomy and tube placement, by providing information of differentially expressed molecules with high specificity. We demonstrate the feasibility of Raman spectroscopy-based approach to categorize middle ear effusion based on the characteristic spectral markers, notably of mucin, with classification accuracy of 91% and 93% for serous and mucoid, respectively. Our findings pave the way for further development of such a tool for fully noninvasive application that will lead to objective and accurate diagnosis thereby reducing unnecessary visits and surgical procedures.

Noninvasive Monitoring of Blood Glucose with Raman Spectroscopy.

The successful development of a noninvasive blood glucose sensor that can operate reliably over sustained periods of time has been a much sought after but elusive goal in diabetes management. Since diabetes has no well-established cure, control of elevated glucose levels is critical for avoiding severe secondary health complications in multiple organs including the retina, kidney and vasculature. While fingerstick testing continues to be the mainstay of blood glucose detection, advances in electrochemical sensing-based minimally invasive approaches have opened the door for alternate methods that would considerably improve the quality of life for people with diabetes. In the quest for better sensing approaches, optical technologies have surfaced as attractive candidates as researchers have sought to exploit the endogenous contrast of glucose, notably its absorption, scattering, and polarization properties. Vibrational spectroscopy, especially spontaneous Raman scattering, has exhibited substantial promise due to its exquisite molecular specificity and minimal interference of water in the spectral profiles acquired from the blood-tissue matrix. Yet, it has hitherto been challenging to leverage the Raman scattering signatures of glucose for prediction in all but the most basic studies and under the least demanding conditions. In this Account, we discuss the newly developed array of methodologies that address the key challenges in measuring blood glucose accurately using Raman spectroscopy and unlock new prospects for translation to sustained noninvasive measurements in people with diabetes. Owing to the weak intensity of spontaneous Raman scattering, recent research has focused on enhancement of signals from the blood constituents by designing novel excitation-collection geometries and tissue modulation methods while our attempts have led to the incorporation of nonimaging optical elements. Additionally, invoking mass transfer modeling into chemometric algorithms has not only addressed the physiological lag between the actual blood glucose and the measured interstitial fluid glucose values but also offered a powerful tool for predictive measurements of hypoglycemia. This framework has recently been extended to provide longitudinal tracking of glucose concentration without necessitating extensive a priori concentration information. These findings are advanced by the results of recent glucose tolerance studies in human subjects, which also hint at the need for designing nonlinear calibration models that can account for subject-to-subject variations in skin heterogeneity and hematocrit levels. Together, the emerging evidence underscores the promise of a blood withdrawal-free optical platform-featuring a combination of high-throughput Raman spectroscopic instrumentation and data analysis of subtle variations in spectral expression-for diabetes screening in the clinic and, ultimately, for personalized monitoring.

Ticagrelor Removal From Human Blood.

The authors devised an efficient method for ticagrelor removal from blood using sorbent hemadsorption. Ticagrelor removal was measured in 2 sets of in vitro experiments. The first set was a first-pass experiment using bovine serum albumin (BSA) solution pre-incubated with ticagrelor, whereas the second set, performed in a recirculating manner, used human blood mixed with ticagrelor. Removal of ticagrelor from BSA solution reached values >99%. The peak removal rate was 99% and 94% from whole blood and 99.99% and 90% from plasma during 10 h and 3 to 4 h of recirculating experiments, respectively. In conclusion, hemadsorption robustly removes ticagrelor from BSA solution and human blood samples.