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Otitis media (OM), a highly prevalent inflammatory middle-ear disease in children worldwide, is commonly caused by an infection, and can lead to antibiotic-resistant bacterial biofilms in recurrent/chronic OM cases. A biofilm related to OM typically contains one or multiple bacterial species. OCT has been used clinically to visualize the presence of bacterial biofilms in the middle ear. This study used OCT to compare microstructural image texture features from bacterial biofilms. The proposed method applied supervised machine-learning-based frameworks (SVM, random forest, and XGBoost) to classify multiple species bacterial biofilms from in vitro cultures and clinically-obtained in vivo images from human subjects. Our findings show that optimized SVM-RBF and XGBoost classifiers achieved more than 95% of AUC, detecting each biofilm class. These results demonstrate the potential for differentiating OM-causing bacterial biofilms through texture analysis of OCT images and a machine-learning framework, offering valuable insights for real-time in vivo characterization of ear infections.
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Room temperature phosphorescent (RTP) carbon dot (CD) materials have been widely used in various fields, but it is difficult to achieve a long lifetime, high stability and easy synthesis. In particular, realizing the phosphorescence emission of CDs using a metal oxide (MO) matrix is a challenge. Here, solid gels are synthesized via in situ hydrolysis, and then RTP CDs are synthesized based on a SiO2 matrix (CDs@SiO2) and hybridized with a MO matrix (CDs@SiO2-MO) by high-temperature calcination. Among the materials synthesized, Al2O3 matrix RTP CDs (CDs@SiO2-Al2O3) have a long phosphorescence lifetime of 689 ms and can exhibit yellow-green light visible to the naked eye for 9 s after the UV light (365 nm) is turned off. Compared with the green phosphorescence of CDs@SiO2, the yellow-green phosphorescence lifetime of CDs@SiO2-Al2O3 is enhanced by 420 ms. In addition, CDs@SiO2-Al2O3 maintains good stability of phosphorescence emission in water, strongly oxidizing solutions and organic solvents. As a result, CDs@SiO2-Al2O3 can be applied to the field of information encryption and security anti-counterfeiting, and this work provides a new, easy and efficient synthesis method for MO as an RTP CD matrix.
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The core-shell structure is an effective means to improve the stability and optoelectronic properties of cesium lead halide (CsPbX3 (X = Cl, Br, I)) perovskite quantum dots (QDs). However, confined by the ionic radius differences, developing a core-shell packaging strategy suitable for the entire CsPbX3 system remains a challenge. In this study, we introduce an optimized hot-injection method for the epitaxial growth of the CsPb2X5 substrate on CsPbX3 surfaces, achieved by precisely controlling the reaction time and the ratio of lead halide precursors. The synthesized CsPbX3/CsPb2X5 composite microplates exhibit an emission light spectrum that covers the entire visible range. Crystallographic analyses and density functional theory (DFT) calculations reveal a minimal lattice mismatch between the (002) plane of CsPb2X5 and the (11¯0) plane of CsPbX3, facilitating the formation of high-quality type-I heterojunctions. Furthermore, introducing Cl- and I- significantly alters the surface energy of CsPb2X5's (110) plane, leading to an evolutionary morphological shift of grains from circular to square microplates. Benefiting from the passivation of CsPb2X5, the composites exhibit enhanced optical properties and stability. Subsequently, the white light-emitting diode prepared using the CsPbX3/CsPb2X5 composite microplates has a high luminescence efficiency of 136.76 lm/W and the PL intensity decays by only 3.6% after 24 h of continuous operation.
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Optimal imaging strategies remain underdeveloped to maximize information for fluorescence microscopy while minimizing the harm to fragile living systems. Taking hint from the supercontinuum generation in ultrafast laser physics, we generated supercontinuum fluorescence from untreated unlabeled live samples before nonlinear photodamage onset. Our imaging achieved high-content cell phenotyping and tissue histology, identified bovine embryo polarization, quantified aging-related stress across cell types and species, demystified embryogenesis before and after implantation, sensed drug cytotoxicity in real-time, scanned brain area for targeted patching, optimized machine learning to track small moving organisms, induced two-photon phototropism of leaf chloroplasts under two-photon photosynthesis, unraveled microscopic origin of autumn colors, and interrogated intestinal microbiome. The results enable a facility-type microscope to freely explore vital molecular biology across life sciences.
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Addressing the challenge of lighting stability in perovskite white light emitting diodes (WLEDs) is crucial for their commercial viability. CsPbX3 (X = Cl, Br, I, or mixed) nanocrystals (NCs) are promising for next-generation lighting due to their superior optical and electronic properties. However, the inherent soft material structure of CsPbX3 NCs is particularly susceptible to the elevated temperatures associated with prolonged WLED operation. Additionally, these NCs face stability challenges in high humidity environments, leading to reduced lighting performance. This study introduces a two-step dual encapsulation method, resulting in CsPbBr3@SiO2/Al2SiO5 composite fibers (CFs) with enhanced optical stability under extreme conditions. In testing, WLEDs incorporating these CFs, even under prolonged operation at high power (100 mA for 9 h), maintain consistent electroluminescence (EL) intensity and optoelectronic parameters, with surface temperatures reaching 84.2 °C. Crucially, when subjected to 85 °C and 85% relative humidity for 200 h, the WLEDs preserve 97% of their initial fluorescence efficiency. These findings underscore the efficacy of the dual encapsulation strategy in significantly improving perovskite material stability, marking a significant step toward their commercial application in optoelectronic lighting.
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Otitis media (OM) is primarily a bacterial middle-ear infection prevalent among children worldwide. In recurrent and/or chronic OM cases, antibiotic-resistant bacterial biofilms can develop in the middle ear. A biofilm related to OM typically contains one or multiple bacterial strains, the most common include Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, Pseudomonas aeruginosa, and Staphylococcus aureus. Optical coherence tomography (OCT) has been used clinically to visualize the presence of bacterial biofilms in the middle ear. This study used OCT to compare microstructural image texture features from primary bacterial biofilms in vitro and in vivo. The proposed method applied supervised machine-learning-based frameworks (SVM, random forest (RF), and XGBoost) to classify and speciate multiclass bacterial biofilms from the texture features extracted from OCT B-Scan images obtained from in vitro cultures and from clinically-obtained in vivo images from human subjects. Our findings show that optimized SVM-RBF and XGBoost classifiers can help distinguish bacterial biofilms by incorporating clinical knowledge into classification decisions. Furthermore, both classifiers achieved more than 95% of AUC (area under receiver operating curve), detecting each biofilm class. These results demonstrate the potential for differentiating OM-causing bacterial biofilms through texture analysis of OCT images and a machine-learning framework, which could provide additional clinically relevant data during real-time in vivo characterization of ear infections.
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Current methods for detecting unlabeled antisense oligonucleotide (ASO) drugs rely on immunohistochemistry (IHC) and/or conjugated molecules, which lack sufficient sensitivity, specificity, and resolution to fully investigate their biodistribution. Our aim was to demonstrate the qualitative and quantitative distribution of unlabeled bepirovirsen, a clinical stage ASO, in livers and kidneys of dosed mice using novel staining and imaging technologies at subcellular resolution. ASOs were detected in formalin-fixed paraffin-embedded (FFPE) and frozen tissues using an automated chromogenic in situ hybridization (ISH) assay: miRNAscope. This was then combined with immunohistochemical detection of cell lineage markers. ASO distribution in hepatocytes versus nonparenchymal cell lineages was quantified using HALO AI image analysis. To complement this, hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) imaging microscopy was used to specifically detect the unique cellular Raman spectral signatures following ASO treatment. Bepirovirsen was localized primarily in nonparenchymal liver cells and proximal renal tubules. Codetection of ASO with distinct cell lineage markers of liver and kidney populations aided target cell identity facilitating quantification. Positive liver signal was quantified using HALO AI, with 12.9% of the ASO localized to the hepatocytes and 87.1% in nonparenchymal cells. HS-CARS imaging specifically detected ASO fingerprints based on the unique vibrational signatures following unlabeled ASO treatment in a totally nonperturbative manner at subcellular resolution. Together, these novel detection and imaging modalities represent a significant increase in our ability to detect unlabeled ASOs in tissues, demonstrating improved levels of specificity and resolution. These methods help us understand their underlying mechanisms of action and ultimately improve the therapeutic potential of these important drugs for treating globally significant human diseases.
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Fígado , Oligonucleotídeos Antissenso , Camundongos , Humanos , Animais , Oligonucleotídeos Antissenso/genética , Oligonucleotídeos Antissenso/metabolismo , Distribuição Tecidual , Fígado/diagnóstico por imagem , Fígado/metabolismo , Hibridização In Situ , Coloração e RotulagemRESUMO
Although cesium halide lead (CsPbX3, X = Cl, Br, I) perovskite quantum dots (QDs) have excellent photovoltaic properties, their unstable characteristics are major limitations to application. Previous research has demonstrated that the core-shell structure can significantly improve the stability of CsPbX3 QDs and form heterojunctions at interfaces, enabling multifunctionalization of perovskite materials. In this article, we propose a convenient method to construct core-shell-structured perovskite materials, in which CsPbBr3@CsPb2Br5 core-shell micrometer crystals can be prepared by controlling the ratio of Cs+/Pb2+ in the precursor and the reaction time. The materials exhibited enhanced optical properties and stability that provided for further postprocessing. Subsequently, CsPbBr3@CsPb2Br5@TiO2 composites were obtained by coating a layer of dense TiO2 nanoparticles on the surfaces of micrometer crystals through hydrolysis of titanium precursors. According to density functional theory (DFT) calculations and experimental results, the presence of surface TiO2 promoted delocalization of photogenerated electrons and holes, enabling the CsPbBr3@CsPb2Br5@TiO2 composites to exhibit excellent performance in the field of photocatalysis. In addition, due to passivation of surface defects by CsPb2Br5 and TiO2 shells, the luminous intensity of white light-emitting diodes prepared with the materials only decayed by 2%-3% at high temperatures (>100 °C) when working for 24 h.
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Understanding drug fingerprints in complex biological samples is essential for the development of a drug. Hyperspectral coherent anti-Stokes Raman scattering (HS-CARS) microscopy, a label-free nondestructive chemical imaging technique, can profile biological samples based on their endogenous vibrational contrast. Here, we propose a deep learning-assisted HS-CARS imaging approach for the investigation of drug fingerprints and their localization at single-cell resolution. To identify and localize drug fingerprints in complex biological systems, an attention-based deep neural network, hyperspectral attention net (HAN), was developed. By formulating the task to a multiple instance learning problem, HAN highlights informative regions through the attention mechanism when being trained on whole-image labels. Using the proposed technique, we investigated the drug fingerprints of a hepatitis B virus therapy in murine liver tissues. With the increase in drug dosage, higher classification accuracy was observed, with an average area under the curve (AUC) of 0.942 for the high-dose group. Besides, highly informative tissue structures predicted by HAN demonstrated a high degree of similarity with the drug localization shown by the in situ hybridization staining results. These results demonstrate the potential of the proposed deep learning-assisted optical imaging technique for the label-free profiling, identification, and localization of drug fingerprints in biological samples, which can be extended to nonperturbative investigations of complex biological systems under various biological conditions.
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Microscopia , Análise Espectral Raman , Animais , Camundongos , Microscopia/métodos , Análise Espectral Raman/métodos , Fígado , Redes Neurais de ComputaçãoRESUMO
The thermal stability of phosphor materials had long been a bottleneck in their commercialization. Nowadays, cesium lead halide perovskite CsPbBr3 has been considered a potential replacement for the next generation of optoelectronic devices due to its excellent optical and electronic properties, however, the devices inevitably generate high temperatures on the surface under prolonged energization conditions in practical applications, which can be fatal to CsPbBr3. Despite the various strategies that have been employed to improve the thermal stability of CsPbBr3, systematic studies of the thermal stability of the basis CsPbBr3 are lacking. In this study, CsPbBr3 with different dimensions (0D quantum dots (QDs), 1D nanowires (NWs), 2D nanoplate (NPs), 3D micron crystals (MCs)) was prepared by traditional high-temperature thermal injection, and a systematic study was carried out on their optical properties and thermal stability. The results revealed that the dimensional change will directly influence the optical properties as well as the thermal stability of CsPbBr3. In particular, 3D CsPbBr3 MCs maintained relatively high thermal stability under high-temperature environments, which will bring interest for the commercialization of next-generation perovskite optoelectronic devices.
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The inherent single narrow emission peak and fast anion exchange process of cesium lead halide perovskite CsPbX3 (X = Cl, Br, I) nanocrystals severely limited its application in white light-emitting diodes. Previous studies have shown that composite structures can passivate surface defects of NCs and improve the stability of perovskite materials, but complex post-treatment processes commonly lead to dissolution of NCs. In this study, CsPb(Cl/Br)3 NCs was in-situ grown in TiO2 hollow shells doped with Eu3+ ions by a modified thermal injection method to prepare CsPb(Cl/Br)3/TiO2:Eu3+ composites with direct excitation of white light without additional treatment. Among them, the well-crystalline TiO2 shells acted as both a substrate for the dopant, avoiding the direct doping of Eu3+ into the interior of NCs to affect the crystal structure of the perovskite materials, and also as a protection layer to isolate the contact between PL quenching molecules and NCs, which significantly improves the stability. Further, the WLED prepared using the composites had bright white light emission, luminous efficiency of 87.39 lm/W, and long-time operating stability, which provided new options for the development of perovskite devices.
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With the latest advancements in optical bioimaging, rich structural and functional information has been generated from biological samples, which calls for capable computational tools to identify patterns and uncover relationships between optical characteristics and various biomedical conditions. Constrained by the existing knowledge of the novel signals obtained by those bioimaging techniques, precise and accurate ground truth annotations can be difficult to obtain. Here we present a weakly supervised deep learning framework for optical signature discovery based on inexact and incomplete supervision. The framework consists of a multiple instance learning-based classifier for the identification of regions of interest in coarsely labeled images and model interpretation techniques for optical signature discovery. We applied this framework to investigate human breast cancer-related optical signatures based on virtual histopathology enabled by simultaneous label-free autofluorescence multiharmonic microscopy (SLAM), with the goal of exploring unconventional cancer-related optical signatures from normal-appearing breast tissues. The framework has achieved an average area under the curve (AUC) of 0.975 on the cancer diagnosis task. In addition to well-known cancer biomarkers, non-obvious cancer-related patterns were revealed by the framework, including NAD(P)H-rich extracellular vesicles observed in normal-appearing breast cancer tissue, which facilitate new insights into the tumor microenvironment and field cancerization. This framework can be further extended to diverse imaging modalities and optical signature discovery tasks.
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Lead-free double perovskites (DP) have the potential to become a rising star in the next generation of lighting markets by addressing the toxicity and instability issues associated with traditional lead-based perovskites. However, high concentrations of hydrochloric acid (HCl) were often employed as a solvent in the preparation of most DPs, accompanied by slow crystallization at high temperatures, which not only raised the risk and cost in the preparation process, but also had a potential threat to the environment. Here, an in situ fabrication strategy was proposed to realize the crystallization of DP in the polymer at low temperature with a mild dimethyl sulfoxide (DMSO) solvent, and subsequently obtained optically well-behaved Cs2Na0.8Ag0.2BiCl6/PMMA composite films (CFs) by doping with Ag+, generating bright orange luminescence with a photoluminescence quantum yield (PLQY) of up to 21.52%. Moreover, the growth dynamics of Cs2Na0.8Ag0.2BiCl6/PMMA CFs was further investigated by in situ optical transformation, which was extended to other DP-based polymer CFs. Finally, these CFs exhibited excellent performance in optoelectronic devices and anticounterfeit printing, the results of which provide a new pathway to advance the development of lead-free DP materials in the optical field.
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The working stability of perovskite light-emitting diodes (LEDs) has become an urgent bottleneck to be solved in the process of commercialization. Although lead halide perovskite CsPbX3 (X = Br, I, Cl) quantum dots (QDs) are considered rising stars in the lighting market owing to their excellent optoelectronic properties, they suffer from fluorescence quenching under thermal conditions. Unfortunately, the surfaces of electronic devices inevitably warm up under long-term energization, which is extremely detrimental to the appropriate functioning of CsPbX3 QDs. Based on the above discussion, the relationship function between the energization time and surface temperature of electronic devices was analyzed, after which a strategy for the preparation of dual-encapsulating perovskites using organic (polystyrene (PS)) and inorganic (ZrO2) materials was proposed, and the change in optical stability before and after encapsulation was investigated. The results show that the thermal stability of CsPbBr3@ZrO2/PS composite films (CFs) after the dual encapsulation was remarkably enhanced, and the assembled white LEDs still retain the initial emission intensity under prolonged high-power operation. In addition, the double encapsulation layer completely suppresses the ion leakage in CsPbBr3 and avoids damage to the ecosystem. It can be seen that this encapsulation strategy was capable of imparting excellent working stability to the perovskite material, which would clear the obstacles to commercial conversion.
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AIM: To identify potential mutations and elucidate the clinical findings of male patients and female carriers of X-linked retinitis pigmentosa (XLRP) in a Chinese family. METHODS: A four generation pedigree was collected that consisted of 20 individuals. Genomic DNA was extracted from peripheral blood, and then the target fragments were amplified by PCR and sequenced directly. In addition, all affected patients and female carriers underwent comprehensively ophthalmic evaluation. RESULTS: A novel mutation c.2865G>A p.W955X in RPGR gene was identified of this family, including four affected individuals and eight carriers. All male patients, aging from 7 to 31y, tended to have more various, even potentially deleterious clinical features of RP. At the same time, individuals with heterozygous mutations (carriers) manifested a wide spectrum of clinical features. Herein, only two male patients and three female carriers manifested pathological myopia (PM). Among the female carriers, half of subjects who harbor poor visual acuity suffered esotropia or exotropia. Additionally, 16.7% and 66.7% of carriers had abnormal electroretinogram (ERG) and fundus, respectively. CONCLUSION: In this study, a novel mutation of the RPGR gene is identified, which broadens the spectrum of RPGR mutations, and elaborates the relationship between genotype and phenotype.
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Otitis media (OM) is an extremely common disease that affects children worldwide. Optical coherence tomography (OCT) has emerged as a noninvasive diagnostic tool for OM, which can detect the presence and quantify the properties of middle ear fluid and biofilms. Here, the use of OCT data from the chinchilla, the gold-standard OM model for the human disease, is used to supplement a human image database to produce diagnostically relevant conclusions in a machine learning model. Statistical analysis shows the datatypes are compatible, with a blended-species model reaching â¼95% accuracy and F1 score, maintaining performance while additional human data is collected.
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Antisense oligonucleotides (ASOs), a novel paradigm in modern therapeutics, modulate cellular gene expression by binding to complementary messenger RNA (mRNA) sequences. While advances in ASO medicinal chemistry have greatly improved the efficiency of cellular uptake, selective uptake by specific cell types has been difficult to achieve. For more efficient and selective uptake, ASOs are often conjugated with molecules with high binding affinity for transmembrane receptors. Triantennary N-acetyl-galactosamine conjugated phosphorothioate ASOs (GalNAc-PS-ASOs) were developed to enhance targeted ASO delivery into liver through the hepatocyte-specific asialoglycoprotein receptor (ASGR). We assessed the kinetics of uptake and subsequent intracellular distribution of AlexaFluor 488 (AF488)-labeled PS-ASOs and GalNAc-PS-ASOs in J774A.1 mouse macrophages and primary mouse or rat hepatocytes using simultaneous coherent anti-Stokes Raman scattering (CARS) and two-photon fluorescence (2PF) imaging. The CARS modality captured the dynamic lipid distributions and overall morphology of the cells; two-photon fluorescence (2PF) measured the time- and dose-dependent localization of ASOs delivered by a modified treatment of suspension cells. Our results show that in macrophages, the uptake rate of PS-ASOs did not significantly differ from that of GalNAc-PS-ASOs. However, in hepatocytes, GalNAc-PS-ASOs exhibited a peripheral uptake distribution compared to a polar uptake distribution observed in macrophages. The peripheral distribution correlated with a significantly larger amount of internalized GalNAc-PS-ASOs compared to the PS-ASOs. This work demonstrates the relevance of multimodal imaging for elucidating the uptake mechanism, accumulation, and fate of different ASOs in liver cells that can be used further in complex in vitro models and liver tissues to evaluate ASO distribution and activity.
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Hepatócitos , Macrófagos , Oligonucleotídeos Antissenso , Animais , Receptor de Asialoglicoproteína/genética , Receptor de Asialoglicoproteína/metabolismo , Linhagem Celular , Fluorescência , Hepatócitos/metabolismo , Macrófagos/metabolismo , Camundongos , Oligonucleotídeos Antissenso/metabolismo , Oligonucleotídeos Fosforotioatos/metabolismo , RatosRESUMO
A high-performance biochar derived from the residue of Chaga mushroom (Inonotus obliquus) was reported in this study. Inonotus obliquus residues were used to prepare biochar, and the optimal synthesis conditions were obtained by response surface methodology. The specific surface area, pore volume, and average pore size of the optimal biochar (Zn-IORBC) was 1676.78 m2/g, 1.87 cm3/g, and 3.88 nm, respectively. Methylene blue (MB) and tetracycline (TC) were selected to estimate the adsorption performance of Zn-IORBC. The adsorption process was suitable for the pseudo-second-order model and Langmuir model. Zn-IORBC could maintained a large amount of TC adsorption (the lowest value was 686.20 mg/g in mountain spring water) in different natural water. The maximum adsorption capacity of TC and MB was 947.42 and 1033.66 mg/g. The adsorption mechanism was contributed to the electrostatic attraction, hydrogen bonding, π-π interactions, and pore-filling. Zn-IORBC is an effective adsorbent for high-performance pollutants removal.
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Poluentes Ambientais , Poluentes Químicos da Água , Adsorção , Carvão Vegetal , Inonotus , Cinética , Poluentes Químicos da Água/análiseRESUMO
Polarization-sensitive optical coherence tomography (PS-OCT) is a high-resolution label-free optical biomedical imaging modality that is sensitive to the microstructural architecture in tissue that gives rise to form birefringence, such as collagen or muscle fibers. To enable polarization sensitivity in an OCT system, however, requires additional hardware and complexity. We developed a deep-learning method to synthesize PS-OCT images by training a generative adversarial network (GAN) on OCT intensity and PS-OCT images. The synthesis accuracy was first evaluated by the structural similarity index (SSIM) between the synthetic and real PS-OCT images. Furthermore, the effectiveness of the computational PS-OCT images was validated by separately training two image classifiers using the real and synthetic PS-OCT images for cancer/normal classification. The similar classification results of the two trained classifiers demonstrate that the predicted PS-OCT images can be potentially used interchangeably in cancer diagnosis applications. In addition, we applied the trained GAN models on OCT images collected from a separate OCT imaging system, and the synthetic PS-OCT images correlate well with the real PS-OCT image collected from the same sample sites using the PS-OCT imaging system. This computational PS-OCT imaging method has the potential to reduce the cost, complexity, and need for hardware-based PS-OCT imaging systems.
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A middle ear infection is a prevalent inflammatory disease most common in the pediatric population, and its financial burden remains substantial. Current diagnostic methods are highly subjective, relying on visual cues gathered by an otoscope. To address this shortcoming, optical coherence tomography (OCT) has been integrated into a handheld imaging probe. This system can non-invasively and quantitatively assess middle ear effusions and identify the presence of bacterial biofilms in the middle ear cavity during ear infections. Furthermore, the complete OCT system is housed in a standard briefcase to maximize its portability as a diagnostic device. Nonetheless, interpreting OCT images of the middle ear more often requires expertise in OCT as well as middle ear infections, making it difficult for an untrained user to operate the system as an accurate stand-alone diagnostic tool in clinical settings. Here, we present a briefcase OCT system implemented with a real-time machine learning platform for middle ear infections. A random forest-based classifier can categorize images based on the presence of middle ear effusions and biofilms. This study demonstrates that our briefcase OCT system coupled with machine learning can provide user-invariant classification results of middle ear conditions, which may greatly improve the utility of this technology for the diagnosis and management of middle ear infections.