Deep learning-based endoscopic anatomy classification: an accelerated approach for data preparation and model validation.

BACKGROUND: Photodocumentation during endoscopy procedures is one of the indicators for endoscopy performance quality; however, this indicator is difficult to measure and audit in the endoscopy unit. Emerging artificial intelligence technology may solve this problem, which requires a large amount of material for model development. We developed a deep learning-based endoscopic anatomy classification system through convolutional neural networks with an accelerated data preparation approach. PATIENTS AND METHODS: We retrospectively collected 8,041 images from esophagogastroduodenoscopy (EGD) procedures and labeled them using two experts for nine anatomical locations of the upper gastrointestinal tract. A base model for EGD image multiclass classification was first developed, and an additional 6,091 images were enrolled and classified by the base model. A total of 5,963 images were manually confirmed and added to develop the subsequent enhanced model. Additional internal and external endoscopy image datasets were used to test the model performance. RESULTS: The base model achieved total accuracy of 96.29%. For the enhanced model, the total accuracy was 96.64%. The overall accuracy improved with the enhanced model compared with the base model for the internal test dataset without narrowband images (93.05% vs. 91.25%, p < 0.01) or with narrowband images (92.74% vs. 90.46%, p < 0.01). The total accuracy was 92.56% of the enhanced model on the external test dataset. CONCLUSIONS: We constructed a deep learning-based model with an accelerated approach that can be used for quality control in endoscopy units. The model was also validated with both internal and external datasets with high accuracy.

Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant information in the endoscopy reporting system to facilitate data collection, which may be inaccurate. The current study aimed to develop a full deep learning-based algorithm to identify and analyze intra-procedural colonoscopy quality indicators based on endoscopy images obtained during the procedure. METHODS: A deep learning system for classifying colonoscopy images for quality assurance purposes was developed and its performance was assessed with an independent dataset. The system was utilized to analyze captured images and results were compared with those of real-world reports. RESULTS: In total, 10,417 images from the hospital endoscopy database and 3157 from Hyper-Kvasir open dataset were utilized to develop the quality assurance algorithm. The overall accuracy of the algorithm was 96.72% and that of the independent test dataset was 94.71%. Moreover, 761 real-world reports and colonoscopy images were analyzed. The accuracy of electronic reports about cecal intubation rate was 99.34% and that of the algorithm was 98.95%. The agreement rate for the assessment of polypectomy rates using the electronic reports and the algorithm was 0.87 (95% confidence interval 0.83-0.90). A good correlation was found between the withdrawal time calculated using the algorithm and that entered by the physician (correlation coefficient r = 0.959, p < 0.0001). CONCLUSION: We proposed a novel deep learning-based algorithm that used colonoscopy images for quality assurance purposes. This model can be used to automatically assess intra-procedural colonoscopy quality indicators in clinical practice.

Upper endoscopy photodocumentation quality evaluation with novel deep learning system.

OBJECTIVES: Visualization and photodocumentation during endoscopy procedures are suggested to be one indicator for endoscopy performance quality. However, this indicator is difficult to measure and audit manually in clinical practice. Artificial intelligence (AI) is an emerging technology that may solve this problem. METHODS: A deep learning model with an accuracy of 96.64% was developed from 15,305 images for upper endoscopy anatomy classification in the unit. Endoscopy images for asymptomatic patients receiving screening endoscopy were evaluated with this model to assess the completeness of photodocumentation rate. RESULTS: A total of 15,723 images from 472 upper endoscopies performed by 12 endoscopists were enrolled. The complete photodocumentation rate from the pharynx to the duodenum was 53.8% and from the esophagus to the duodenum was 78.0% in this study. Endoscopists with a higher adenoma detection rate had a higher complete examination rate from the pharynx to duodenum (60.0% vs. 38.7%, P < 0.0001) and from esophagus to duodenum (83.0% vs. 65.7%, P < 0.0001) compared with endoscopists with lower adenoma detection rate. The pharynx, gastric angle, gastric retroflex view, gastric antrum, and the first portion of duodenum are likely to be missed by endoscopists with lower adenoma detection rates. CONCLUSIONS: We report the use of a deep learning model to audit endoscopy photodocumentation quality in our unit. Endoscopists with better performance in colonoscopy had a better performance for this quality indicator. The use of such an AI system may help the endoscopy unit audit endoscopy performance.

Photoacoustic imaging of cells in a three-dimensional microenvironment.

Imaging live cells in a three-dimensional (3D) culture system yields more accurate information and spatial visualization of the interplay of cells and the surrounding matrix components compared to using a two-dimensional (2D) cell culture system. However, the thickness of 3D cultures results in a high degree of scattering that makes it difficult for the light to penetrate deeply to allow clear optical imaging. Photoacoustic (PA) imaging is a powerful imaging modality that relies on a PA effect generated when light is absorbed by exogenous contrast agents or endogenous molecules in a medium. It combines a high optical contrast with a high acoustic spatiotemporal resolution, allowing the noninvasive visualization of 3D cellular scaffolds at considerable depths with a high resolution and no image distortion. Moreover, advances in targeted contrast agents have also made PA imaging capable of molecular and cellular characterization for use in preclinical personalized diagnostics or PA imaging-guided therapeutics. Here we review the applications and challenges of PA imaging in a 3D cellular microenvironment. Potential future developments of PA imaging in preclinical applications are also discussed.

Enhanced Radiosensitization for Cancer Treatment with Gold Nanoparticles through Sonoporation.

We demonstrate the megavoltage (MV) radiosensitization of a human liver cancer line by combining gold-nanoparticle-encapsulated microbubbles (AuMBs) with ultrasound. Microbubbles-mediated sonoporation was administered for 5 min, at 2 h prior to applying radiotherapy. The intracellular concentration of gold nanoparticles (AuNPs) increased with the inertial cavitation of AuMBs in a dose-dependent manner. A higher inertial cavitation dose was also associated with more DNA damage, higher levels of apoptosis markers, and inferior cell surviving fractions after MV X-ray irradiation. The dose-modifying ratio in a clonogenic assay was 1.56 ± 0.45 for a 10% surviving fraction. In a xenograft mouse model, combining vascular endothelial growth factor receptor 2 (VEGFR2)-targeted AuMBs with sonoporation significantly delayed tumor regrowth. A strategy involving the spatially and temporally controlled release of AuNPs followed by clinically utilized MV irradiation shows promising results that make it worthy of further translational investigations.

Shear-wave elasticity measurements of three-dimensional cell cultures for mechanobiology.

Studying mechanobiology in three-dimensional (3D) cell cultures better recapitulates cell behaviors in response to various types of mechanical stimuli in vivo Stiffening of the extracellular matrix resulting from cell remodeling potentiates many pathological conditions, including advanced cancers. However, an effective tool for measuring the spatiotemporal changes in elastic properties of such 3D cell cultures without directly contacting the samples has not been reported previously. We describe an ultrasonic shear-wave-based platform for quantitatively evaluating the spatiotemporal dynamics of the elasticity of a matrix remodeled by cells cultured in 3D environments. We used this approach to measure the elasticity changes of 3D matrices grown with highly invasive lung cancer cells and cardiac myoblasts, and to delineate the principal mechanism underlying the stiffening of matrices remodeled by these cells. The described approach can be a useful tool in fields investigating and manipulating the mechanotransduction of cells in 3D contexts, and also has potential as a drug-screening platform.

Laser-speckle-contrast projection tomography for three-dimensional shear wave imaging.

Laser-speckle-contrast shear wave (LSC-SW) imaging is an optical method for tracking the propagation of a transient shear wave. With high spatial resolution and sensitivity in detecting displacements, this method is suitable for performing mechanical measurements in vitro. Here, we present a LSC-SW tomographic imaging system for visualizing the propagating shear wave wavefront in four dimensions [i.e., three-dimensional (3D) space plus time]. The volumetric elasticity distribution of a sample is constructed by estimating the speeds of the shear waves propagating along multiple paths at different angles. The proposed method enables multidirectional estimations of the shear wave speed. The capabilities of the imaging system are demonstrated by evaluating isotropy (both homogeneous and heterogeneous) and anisotropy in semiturbid phantoms. The proposed system is suitable for the mechanical characterization of a 3D cell culture system, such as monitoring changes in fiber orientation during the remodeling of the extracellular matrix that is known to be strongly associated with the progression and characterization of tumors.

Study of diffusive- and convective-transport mediated microtumor growth in a controlled microchamber.

In this paper, we report on using mass transport to control nutrition supply of colorectal cancer cells for developing a microtumor in a confined microchamber. To mimic the spatial heterogeneity of a tumor, two microfluidic configurations based on resistive circuits are designed. One has a convection-dominated microchamber to simulate the tumor region proximal to leaky blood vessels. The other has a diffusion-dominated microchamber to mimic the tumor core that lacks blood vessels and nutrient supply. Thus, the time for nutrition to fill the microchamber can vary from tens of minutes to several hours. Results show that cells cultured under a diffusive supply of nutrition have a high glycolytic rate and a nearly constant oxygen consumption rate. In contrast, cells cultured under convective supply of nutrition have a gradual increase of oxygen consumption rate with a low glycolytic rate. This suggests that cancer cells have distinct reactions under different mass transport and nutrition supply. Using these two microfluidic platforms to create different rate of nutrition supply, it is found that a continuous microtumor that almost fills the mm-size microchamber can be developed under a low-nutrient supply environment, but not for the convective condition. It also is demonstrated that microchannels can simulate the delivery of anti-cancer drugs to the microtumor under controlled mass-transport. This method provides a means to develop a larger scale microtumor in a lab-on-a-Chip system for post development and stimulations, and microchannels can be applied to control the physical and chemical environment for anti-cancer drug screening.

Ultrasound Strain Imaging to Assess the Biceps Brachii Muscle in Chronic Poststroke Spasticity.

OBJECTIVES: The aim of the study was to assess the feasibility of ultrasound strain imaging in characterizing the biceps brachii muscle in chronic poststroke spasticity. METHODS: We prospectively analyzed strain imaging data from bilateral biceps brachii muscles in 8 healthy volunteers and 7 patients with poststroke chronic spasticity. Axial deformations of the biceps brachii muscle and overlying subcutaneous tissue were produced by external compression using a sandbag (1.0 kg) attached to a transducer. The lengthening and shortening of the biceps brachii muscle and subcutaneous tissue were produced by manual passive elbow extension (from 90° to 0°) and flexion (from 0° to 90°), respectively. We used offline 2-dimensional speckle tracking to estimate axial and longitudinal strain ratios (biceps brachii strain/subcutaneous tissue strain), and the longitudinal tissue velocity of the biceps brachii muscle. Statistical analyses included analysis of variance for testing differences in strain imaging parameters among healthy, nonspastic, and spastic biceps brachii muscles, the Bonferroni correction for further testing differences in US strain imaging among paired groups (healthy versus spastic, nonspastic versus spastic, and healthy versus nonspastic), and the Pearson correlation coefficient for assessing the intraobserver reliability of performing strain imaging in stroke survivors. RESULTS: The differences in strain imaging parameters between healthy and spastic and between nonspastic and spastic biceps brachii muscles were significant at both 90° elbow flexion and maximal elbow extension (P < .01). There was no significant difference in axial strain ratios at 90° of elbow flexion or longitudinal tissue velocities between healthy and nonspastic muscles (P > .05). The intraobserver reliability of performing strain imaging in stroke survivors was good (r = 0.85; P < .01). CONCLUSIONS: Ultrasound strain imaging seems to be feasible for characterizing the biceps brachii muscle in chronic poststroke spasticity.

Single allele Lmbrd1 knockout results in cardiac hypertrophy.

BACKGROUND/PURPOSE: LMBD1 protein, a type IV-B plasma membrane protein possessing nine putative trans-membrane domains, was previously demonstrated at cellular level to play a critical part in the signaling cascade of insulin receptor through its involvement in regulating clathrin-mediated endocytosis. However, at physiological level, the significance of LMBD1 protein in cardiac development remains unclear. METHODS: To understand the role of Lmbrd1 gene involved in the cardiac function, heterozygous knockout mice were used as an animal model system. The pathological outcomes were analyzed by micro-positron emission tomography, ECG acquisition, cardiac ultrasound, and immunohistochemistry. RESULTS: By studying the heterozygous knockout of Lmbrd1 (Lmbrd1+/-), we discovered that lack of Lmbrd1 not only resulted in the increase of cardiac-glucose uptake, pathological consequences were also observed. Here, we have distinguished that Lmbrd1+/- is sufficient in causing cardiac diseases through a pathway independent of the recessive vitamin B12 cblF cobalamin transport defect. Lmbrd1+/- mice exhibited an increase in myocardial glucose uptake and insulin receptor signaling that is insensitive to the administration of additional insulin. Pathological symptoms such as cardiac hypertrophy, ventricular tissue fibrosis, along with the increase of heart rate and cardiac muscle contractility were observed. As Lmbrd1+/- mice aged, the decrease in ejection fraction and fraction shortening showed signs of ventricular function deterioration. CONCLUSION: The results suggested that Lmbrd1 gene not only plays a significant role in mediating the energy homeostasis in cardiac tissue, it may also be a key factor in the regulation of cardiac function in mice.

Detection of Sphingomyelin Clusters by Raman Spectroscopy.

Sphingomyelin (SM) is a major sphingolipid in mammalian cells that forms specific lipid domains in combination with cholesterol (Chol). Using molecular-dynamics simulation and density functional theory calculation, we identified a characteristic Raman band of SM at ∼1643 cm(-1) as amide I of the SM cluster. Experimental results indicate that this band is sensitive to the hydration of SM and the presence of Chol. We showed that this amide I Raman band can be utilized to examine the membrane distribution of SM. Similarly to SM, ceramide phosphoethanolamine (CerPE) exhibited an amide I Raman band in almost the same region, although CerPE lacks three methyl groups in the phosphocholine moiety of SM. In contrast to SM, the amide I band of CerPE was not affected by Chol, suggesting the importance of the methyl groups of SM in the SM-Chol interaction.

Three-dimensional shear wave imaging based on full-field laser speckle contrast imaging with one-dimensional mechanical scanning.

The high imaging resolution and motion sensitivity of optical-based shear wave detection has made it an attractive technique in biomechanics studies with potential for improving the capabilities of shear wave elasticity imaging. In this study we implemented laser speckle contrast imaging for two-dimensional (X-Z) tracking of transient shear wave propagation in agarose phantoms. The mechanical disturbances induced by the propagation of the shear wave caused temporal and spatial fluctuations in the local speckle pattern, which manifested as local blurring. By mechanically moving the sample in the third dimension (Y), and performing two-dimensional shear wave imaging at every scan position, the three-dimensional shear wave velocity distribution of the phantom could be reconstructed. Based on comparisons with the reference shear wave velocity measurements obtained using a commercial ultrasound shear wave imaging system, the developed system can estimate the shear wave velocity with an error of less than 6% for homogeneous phantoms with shear moduli ranging from 1.52 kPa to 7.99 kPa. The imaging sensitivity of our system makes it capable of measuring small variations in shear modulus; the estimated standard deviation of the shear modulus was found to be less than 0.07 kPa. A submillimeter spatial resolution for three-dimensional shear wave imaging has been achieved, as demonstrated by the ability to detect a 1-mm-thick stiff plate embedded inside heterogeneous agarose phantoms.

A weight averaged approach for predicting amide vibrational bands of a sphingomyelin bilayer.

Infrared (IR) and Raman spectra of a sphingomyelin (SM) bilayer have been calculated for the amide I, II and A modes and the double-bonded CC stretching mode by a weight averaged approach, based on an all-atom molecular dynamics (MD) simulation and a vibrational structure calculation. Representative structures and statistical weights of SM clusters connected by hydrogen bonds (HBs) are observed in MD trajectories. After constructing smaller fragments from the SM clusters, the vibrational spectra of the target modes were calculated by normal mode analysis with a correction for anharmonicity, using density functional theory. The final IR and Raman spectra of a SM bilayer were obtained as the weight averages over all SM clusters. The calculated Raman spectrum is in excellent agreement with a recent measurement, providing a clear assignment of the peak in question observed at 1643 cm(-1) to the amide I modes of a SM bilayer. The analysis of the IR spectrum has also revealed that the amide bands are sensitive to the water content inside the membrane, since their band positions are strongly modulated by the HB between SM and water molecules. The present study suggests that the amide I band serves as a marker to identify the formation of SM clusters, and opens a new way to detect lipid rafts in the biological membrane.

Lossless data compression for improving the performance of a GPU-based beamformer.

The powerful parallel computation ability of a graphics processing unit (GPU) makes it feasible to perform dynamic receive beamforming However, a real time GPU-based beamformer requires high data rate to transfer radio-frequency (RF) data from hardware to software memory, as well as from central processing unit (CPU) to GPU memory. There are data compression methods (e.g. Joint Photographic Experts Group (JPEG)) available for the hardware front end to reduce data size, alleviating the data transfer requirement of the hardware interface. Nevertheless, the required decoding time may even be larger than the transmission time of its original data, in turn degrading the overall performance of the GPU-based beamformer. This article proposes and implements a lossless compression-decompression algorithm, which enables in parallel compression and decompression of data. By this means, the data transfer requirement of hardware interface and the transmission time of CPU to GPU data transfers are reduced, without sacrificing image quality. In simulation results, the compression ratio reached around 1.7. The encoder design of our lossless compression approach requires low hardware resources and reasonable latency in a field programmable gate array. In addition, the transmission time of transferring data from CPU to GPU with the parallel decoding process improved by threefold, as compared with transferring original uncompressed data. These results show that our proposed lossless compression plus parallel decoder approach not only mitigate the transmission bandwidth requirement to transfer data from hardware front end to software system but also reduce the transmission time for CPU to GPU data transfer.

Multidimensional umbrella sampling and replica-exchange molecular dynamics simulations for structure prediction of transmembrane helix dimers.

Structural information of a transmembrane (TM) helix dimer is useful in understanding molecular mechanisms of important biological phenomena such as signal transduction across the cell membrane. Here, we describe an umbrella sampling (US) scheme for predicting the structure of a TM helix dimer in implicit membrane using the interhelical crossing angle and the TM-TM relative rotation angles as the reaction coordinates. This scheme conducts an efficient conformational search on TM-TM contact interfaces, and its robustness is tested by predicting the structures of glycophorin A (GpA) and receptor tyrosine kinase EphA1 (EphA1) TM dimers. The nuclear magnetic resonance (NMR) structures of both proteins correspond to the global free-energy minimum states in their free-energy landscapes. In addition, using the landscape of GpA as a reference, we also examine the protocols of temperature replica-exchange molecular dynamics (REMD) simulations for structure prediction of TM helix dimers in implicit membrane. A wide temperature range in REMD simulations, for example, 250-1000 K, is required to efficiently obtain a free-energy landscape consistent with the US simulations. The interhelical crossing angle and the TM-TM relative rotation angles can be used as reaction coordinates in multidimensional US and be good measures for conformational sampling of REMD simulations.

Fourier-Based Fast 3-D Ultrasound Imaging Using Row-Column-Addressed 2-D Arrays.

A Fourier-based fast 3-D ultrasound imaging method using row-column-addressed (RCA) 2-D arrays is presented. The row elements in an RCA array are activated sequentially, and all the column elements are used to receive. The obtained dataset is adapted to approximate to that obtained using a fully sampled array after a plane wave at a given incident angle is transmitted. In this way, the fast algorithm in plane-wave Fourier imaging (PWFI) can be applied to the adapted dataset. In addition, synthesizing multiple datasets based on multiple incident angles enables angular compounding, which improves the image quality. The proposed method was validated using computer simulations and physical-phantom experiments. The results show that the spatial resolution and contrast of the proposed method are comparable with those of its PWFI counterpart without requiring a fully sampled (FS) array. Compared with the delay-and-sum (DAS) method using the RCA array, the proposed method provides comparable spatial resolution but lower contrast; however, the computational complexity is significantly reduced from O(N4Nz) to O(WN2Nz log2(N2Nz)) , where N is the number of elements on each side of the RCA array, Nz is the number of voxels in the axial direction in the output image, and W is the number of compounding angles. For example, in the simulated results when the maximum compounding angle M is 5°, at a given point the lateral - 6-dB width provided by the proposed method is 0.241 mm (0.267 mm for DAS), the contrast ratio of a hyperechoic cyst is 8.87 dB (9.10 dB for DAS), the number of real number operations is reduced by a factor of 20.62, and the number of memory accesses is reduced by a factor of 47.21, both compared with DAS. This novel fast algorithm could facilitate the development of compact real-time 3-D imaging systems, especially when the channel count is high and a large field of view (FOV) is required.

Ultrafast Doppler Imaging for Early Detection of Synovitis in Rheumatoid Arthritis.

OBJECTIVE: Current medical ultrasound systems possess limited sensitivity in detecting slow and weak blood flow during the early stages of rheumatoid arthritis (RA), leading to potential misdiagnosis. Ultrafast Doppler is capable of detecting slow and weak flow. This study was aimed at evaluating the diagnostic value of ultrafast Doppler for RA. METHODS: Thirty-three RA patients (19 established, 14 early stage) and 15 healthy participants were enrolled. A programmable imaging platform with ultrafast Doppler capability was used. The benchmark was a clinical system with conventional Doppler imaging. Standardized dorsal long-axis scanning of both wrists was performed. Both ultrafast and conventional power Doppler (PD) images were quantitatively analyzed with computer assistance and semiquantitatively scored with the Outcome Measures in Rheumatology (OMERACT) scoring system. RESULTS: Ultrafast PD revealed more blood area than conventional PD in both RA wrists and healthy wrists. Ultrafast PD OMERACT was positive in 65 of 66 RA wrists and 26 of 30 healthy wrists (sensitivity [SEN] = 0.985, accuracy [ACC] = 0.719), while conventional PD OMERACT was positive in 28 of 66 RA wrists and 0 of 30 healthy wrists (SEN = 0.424, ACC = 0.604). Ultrafast PD revealed a higher synovial PD area, dilated vessels and PD brightness in RA wrists. Peak synovial PD brightness had the best diagnostic value for RA (area under the receiver operating characteristic curve = 0.802, SEN = 0.909, ACC = 0.813). For early-stage RA patients, ultrafast peak synovial PD brightness had higher sensitivity and accuracy than conventional PD indexes. CONCLUSION: Ultrafast PD had an increase of 0.561 in sensitivity and 0.209 in accuracy when compared with conventional PD. With its high sensitivity, ultrafast PD can detect early synovitis and identify RA patients during the early phase.

Spatially controlled diffusion range of tumor-associated angiogenic factors to develop a tumor model using a microfluidic resistive circuit.

Developing a tumor model with vessels has been a challenge in microfluidics. This difficulty is because cancer cells can overgrow in a co-culture system. The up-regulation of anti-angiogenic factors during the initial tumor development can hinder neovascularization. The standard method is to develop a quiescent vessel network before loading a tumor construct in an adjacent chamber, which simulates the interaction between a tumor and its surrounding vessels. Here, we present a new method that allows a vessel network and a tumor to develop simultaneously in two linked chambers. The physiological environment of these two chambers is controlled by a microfluidic resistive circuit using two symmetric long microchannels. Applying the resistive circuit, a diffusion-dominated environment with a small 2-D pressure gradient is created across the two chambers with velocity <10.9 nm s-1 and Péclet number <6.3 × 10-5. This 2-D pressure gradient creates a V-shaped velocity clamp to confine the tumor-associated angiogenic factors at pores between the two chambers, and it has two functions. At the early stage, vasculogenesis is stimulated to grow a vessel network in the vessel chamber with minimal influence from the tumor that is still developed in the adjacent chamber. At the post-tumor-development stage, the induced steep concentration gradient at pores mimics vessel-tumor interactions to stimulate angiogenesis to grow vessels toward the tumor. Applying this method, we demonstrate that vasculogenic vessels can grow first, followed by stimulating angiogenesis. Angiogenic vessels can grow into stroma tissue up to 1.3 mm long, and vessels can also grow into or wrap around a 625 µm tumor spheroid or a tumor tissue developed from a cell suspension. In summary, our study suggests that the interactions between a developing vasculature and a growing tumor must be controlled differently throughout the tissue development process, including at the early stage when vessels are still forming and at the later stage when the tumor needs to interact with the vessels.

The intertransmembrane region of Kaposi's sarcoma-associated herpesvirus modulator of immune recognition 2 contributes to B7-2 downregulation.

Kaposi's sarcoma-associated herpesvirus (KSHV), a human tumor virus, encodes two homologous membrane-associated E3 ubiquitin ligases, modulator of immune recognition 1 (MIR1) and MIR2, to evade host immunity. Both MIR1 and MIR2 downregulate the surface expression of major histocompatibility complex class I (MHC I) molecules through ubiquitin-mediated endocytosis followed by lysosomal degradation. Since MIR2 additionally downregulates a costimulatory molecule (B7-2) and an integrin ligand (intercellular adhesion molecule 1 [ICAM-1]), MIR2 is thought to be a more important molecule for immune evasion than MIR1; however, the molecular basis of the MIR2 substrate specificity remains unclear. To address this issue, we determined which regions of B7-2 and MIR2 are required for MIR2-mediated B7-2 downregulation. Experiments with chimeras made by swapping domains between human B7-2 and CD8α, a non-MIR2 substrate, and between MIR1 and MIR2 demonstrated a significant contribution of the juxtamembrane (JM) region of B7-2 and the intertransmembrane (ITM) region of MIR2 to MIR2-mediated downregulation. Structure prediction and mutagenesis analyses indicate that Phe119 and Ser120 in the MIR2 ITM region and Asp244 in the B7-2 JM region contribute to the recognition of B7-2 by MIR2. This finding provides new insight into the molecular basis of substrate recognition by MIR family members.

All-optical scanhead for ultrasound and photoacoustic dual-modality imaging.

We propose a new scanhead design for combined ultrasound (US)/photoacoustic (PA) imaging that can be applied to dual-modality microscopy and biomedical imaging. Both imaging modalities employ the optical generation and detection of acoustic waves. The scanhead consists of an optical fiber with an axicon tip for excitation, and a microring for acoustic detection. No conventional piezoelectric device is needed, and the cost of the design makes it suitable for one-time, disposable use. Furthermore, a single laser pulse is employed to generate both US and PA signals. A subband imaging method can be applied to the receiver to enhance the contrast between the US and PA signals. Phantom data demonstrate the feasibility of this approach.