Celiac Disease Detection From Videocapsule Endoscopy Images Using Strip Principal Component Analysis.

The purpose of this study was to implement principal component analysis (PCA) on videocapsule endoscopy (VE) images to develop a new computerized tool for celiac disease recognition. Three PCA algorithms were implemented for feature extraction and sparse representation. A novel strip PCA (SPCA) with nongreedy L1-norm maximization is proposed for VE image analysis. The extracted principal components were interpreted by a non-parametric k-nearest neighbor (k-NN) method for automated celiac disease classification. A benchmark dataset of 460 images (240 from celiac disease patients with small intestinal villous atrophy versus 220 control patients lacking villous atrophy) was constructed from the clinical VE series. It was found that the newly developed SPCA with nongreedy L1-norm maximization was most efficient for computerized celiac disease recognition, having a robust performance with an average recognition accuracy of 93.9 percent. Furthermore, SPCA also has a reduced computation time as compared with other methods. Therefore, it is likely that SPCA will be a helpful adjunct for the diagnosis of celiac disease.

A bioactive implant in situ and long-term releases combined drugs for treatment of osteoarticular tuberculosis.

Anti-tuberculosis chemotherapy with a long duration and adequate dosing is the mainstay for treatment of osteoarticular tuberculosis (TB). However, it is difficult for systemic administration to reach adequate local drug concentrations and achieve effective treatment. Herein, a hydroxyapatite (HA) scaffold implant combined with a drug-releasing system was designed to achieve in situ and long-term anti-TB drug release and highly efficient therapeutic activity in vitro and in vivo. The clinical anti-TB drugs hydrophilic isoniazid (INH) and hydrophobic rifampicin (RFP) were molecularly dispersed into polyvinyl alcohol (PVA) through immersion-curing techniques and were steadily adhered onto the surfaces of HA scaffolds (HA-drug@PVA). The HA-drug@PVA scaffolds showed a long-term, sustained drug release profile and killed proliferating Mycobacterium in vitro. In vivo experimental results revealed that the HA-drug@PVA scaffolds provided over 10- and 100-fold higher concentrations in muscles and bones, respectively, as well as a much lower concentration (<0.025) in blood. Furthermore, the HA-drug@PVA scaffold implanted in an osteoarticular TB rabbit model showed obvious bone regeneration and fusion due to the inhibition of TB-associated inflammatory changes. The excellent therapeutic effects indicate that in situ implant materials combined with a long-term drug release system are promising for the treatment of osteoarticular TB and other osteoarticular infections.

A self-destructive nanosweeper that captures and clears amyloid ß-peptides.

Cerebral amyloid ß-peptide (Aß) accumulation resulting from an imbalance between Aß production and clearance is one of the most important causes in the formation of Alzheimer's disease (AD). In order to preserve the maintenance of Aß homeostasis and have a notable AD therapy, achieving a method to clear up Aß plaques becomes an emerging task. Herein, we describe a self-destructive nanosweeper based on multifunctional peptide-polymers that is capable of capturing and clearing Aß for the effective treatment of AD. The nanosweeper recognize and bind Aß via co-assembly through hydrogen bonding interactions. The Aß-loaded nanosweeper enters cells and upregulates autophagy thus promoting the degradation of Aß. As a result, the nanosweeper decreases the cytotoxicity of Aß and rescues memory deficits of AD transgenic mice. We believe that this resourceful and synergistic approach has valuable potential as an AD treatment strategy.

In situ construction of nanonetworks from transformable nanoparticles for anti-angiogenic therapy.

Tumor metastasis as the most common reason of death from cancer has always been a great challenge in both clinical and scientific research, where angiogenesis plays a necessary role. Herein, we report an extracellularly transformable nanomaterial for in situ construction of defensive networks on interaction with vascular endothelial growth factor (VEGF) for anti-angiogenic therapy of tumor. The fibrous networks exhibit transformation-enhanced accumulation and retention (TEAR) effects (over 72 h), and bind and intercept cell-secreted VEGF over particulate and molecular anti-angiogenic agents with high efficiency, leading to anti-angiogenesis. This study demonstrates that angiogenesis is positively related to tumor growth as well as tumor metastasis; the anti-angiogenic therapy inhibits tumor metastasis with an inhibition rate of 65.9%. In addition, this extracellular strategy of transformation may be utilized to bind huge amounts of cell-secreted biomolecules/factors or receptors on cell surfaces and inhibit their functionalities for cancer therapy.

Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method.

BACKGROUND: Celiac disease is one of the most common diseases in the world. Capsule endoscopy is an alternative way to visualize the entire small intestine without invasiveness to the patient. It is useful to characterize celiac disease, but hours are need to manually analyze the retrospective data of a single patient. Computer-aided quantitative analysis by a deep learning method helps in alleviating the workload during analysis of the retrospective videos. METHOD: Capsule endoscopy clips from 6 celiac disease patients and 5 controls were preprocessed for training. The frames with a large field of opaque extraluminal fluid or air bubbles were removed automatically by using a pre-selection algorithm. Then the frames were cropped and the intensity was corrected prior to frame rotation in the proposed new method. The GoogLeNet is trained with these frames. Then, the clips of capsule endoscopy from 5 additional celiac disease patients and 5 additional control patients are used for testing. The trained GoogLeNet was able to distinguish the frames from capsule endoscopy clips of celiac disease patients vs controls. Quantitative measurement with evaluation of the confidence was developed to assess the severity level of pathology in the subjects. RESULTS: Relying on the evaluation confidence, the GoogLeNet achieved 100% sensitivity and specificity for the testing set. The t-test confirmed the evaluation confidence is significant to distinguish celiac disease patients from controls. Furthermore, it is found that the evaluation confidence may also relate to the severity level of small bowel mucosal lesions. CONCLUSIONS: A deep convolutional neural network was established for quantitative measurement of the existence and degree of pathology throughout the small intestine, which may improve computer-aided clinical techniques to assess mucosal atrophy and other etiologies in real-time with videocapsule endoscopy.

An integrative framework for 3D cobb angle measurement on CT images.

OBJECTIVE: Measuring the Cobb angle on computed tomography (CT) images remains a challenging but requisite task for clinical diagnoses of scoliosis. Traditionally, clinical practitioners resort to manual demarcation, but this approach is inefficient and subjective. Most of the existing computerized algorithms are two-dimensional (2D) and incapable of multi-angle calibration. METHODS: A novel integrative framework based on curvature features and geometric constraints is proposed to measure three-dimensional (3D)Cobb angles on CT images. This framework enables Cobb angle estimation in stereo and accomplishes the synchronous computation of the Cobb angle in three imaging planes. The whole system was quantitatively evaluated on 22 spine models obtained from the clinic. RESULTS: The results demonstrate that the integrative framework performs well in clinical Lenke classification and outperforms both the traditional manual method and the 2D digital method as evidenced by high intra-observer and inter-observer reliability (ICC>0.94, SEM 0.9°-1.2° for intra-observer, ICC>0.94, SEM 0.8°-1.2° for inter-observer). This 3D framework is also robust across different models (SE<3°). CONCLUSIONS: The new integrative framework is able to measure the Cobb angles in three imaging planes simultaneously and is therefore clinically advantageous.

Host Materials Transformable in Tumor Microenvironment for Homing Theranostics.

A pathology-adaptive nanosystem, in which nest-like hosts are built based on nanofibers that are transformed from i.v. injected nanoparticles under the acidic tumor microenvironment. The solid tumor is artificially modified by nest-like hosts readily and firmly, resulting in highly efficient accumulation and stabilization of guest theranostics. This strategy shows great potential for the theranostics delivery to tumors.

Block Principal Component Analysis With Nongreedy $\ell _{1}$ -Norm Maximization.

Block principal component analysis with l1 -norm (BPCA-L1) has demonstrated its effectiveness in a lot of visual classification and data mining tasks. However, the greedy strategy for solving the l1 -norm maximization problem is prone to being struck in local solutions. In this paper, we propose a BPCA with nongreedy l1 -norm maximization, which obtains better solutions than BPCA-L1 with all the projection directions optimized simultaneously. Other than BPCA-L1, the new algorithm has been evaluated against some popular principal component analysis (PCA) algorithms including PCA-L1 and 2-D PCA-L1 on a variety of benchmark data sets. The results demonstrate the effectiveness of the proposed method.

Zinc-Dithizone Complex Engineered Upconverting Nanosensors for the Detection of Hypochlorite in Living Cells.

Current chemo/biosensors for hypochlorous acid or hypochlorite detections are usually limited to the submicromolar level because of their insufficient sensitivity, which is a problem because the concentrations in biological matrices is generally on the nanomolar scale or even lower. Developing a probe with a high enough sensitivity remains a challenge. Using the minimal background fluorescence of upconversion nanocrystals to our advantage, we herein report on an energy-transfer mechanism-based upconversion luminescent nanosensor for the sensitive and selective detection of hypochlorite in aqueous solution. In this nanosensor water-dispersible upconversion nanoparticles act as the energy donor and a novel hypochlorite-responsive coordination complex Zn(DZ)3 is employed as the energy acceptor. The quenched upconversion luminescence, induced by the Zn(DZ)3 complex, can be efficiently recovered after addition of hypochlorite through the selective oxidative breakage of the Zn-S-C bonds in the Zn(DZ)3 complex, which was verified by mass spectrometry. The detection limit for hypochlorite of this sensing system is as low as 3 nM. Furthermore, this newly coordination-complex engineered upconversion nanosensor is successfully applied to image different amounts of exogenous hypochlorite in living HeLa cells.

Mesoporous silica-coated upconversion nanocrystals for near infrared light-triggered control of gene expression in zebrafish.

AIM: To develop a platform technology for photoactivation of gene expression in deep tissues. MATERIALS & METHODS: Upconversion nanoparticles (UCNs) were synthesized from rare earth elements like Ytterbium, Yttrium and Thulium. The nanoparticles were then further coated with a layer of mesoporous silica and loaded with photomorpholinos or photocaged plasmids and tested in zebrafish. The UCNs were activated using safe near-infrared (NIR) light which in turn produced UV light locally to enable photoactivation in deep tissues. RESULTS: Light-controlled gene knockdown was demonstrated in an in vivo model, namely zebrafish. UCNs loaded with photomorpholinos were used to knockdown a gene - ntl, which is essential for notochord formation and mesoderm patterning in zebrafish using NIR light. UCN-mediated light-controlled gene expression was also achieved by expressing GFP in tumor cells transplanted into adult zebrafish by irradiating the fish with NIR light. Apart from the delivery and control of genes, the UCNs were also used as imaging agents to image both zebrafish embryos and adult zebrafish. enabled excellent background-free, fluorescent imaging of both embryos and adult zebrafish. CONCLUSION: This technique of controlling gene expression/knockdown through NIR using UCNs is a game changer in the field of genetic manipulation and has the potential of being an excellent, safe and easy to implement tool for developmental biologists to investigate the role of specific genes in development. However, this technique is not restricted to be used only in zebrafish and can be extended for use in other animal models and even for clinical use, in various gene therapy applications.

Numerical Study of Pillar Shapes in Deterministic Lateral Displacement Microfluidic Arrays for Spherical Particle Separation.

Deterministic lateral displacement (DLD) arrays containing shaped pillars have been found to be more effective in biomedical sample separation. This study aims to numerically investigate the interplay between particles and microfluidic arrays, and to find out the key factors in determining the critical size of a DLD device with shaped pillars. A new formula is thus proposed to estimate the critical size for spherical particle separation in this kind of new DLD microfluidic arrays. The simulation results show that both rectangular and I-shaped arrays have considerably smaller critical sizes. The ratio of sub-channel widths is also found to play an important role in reducing the critical sizes. This paves a valuable way toward designing high-performance DLD microfluidic arrays.

Oxidative cleavage-based upconversional nanosensor for visual evaluation of antioxidant activity of drugs.

In this work, we reported a simple and effective upconversional nanoprobe for selective detection of hydroxyl radical (OH) and visual evaluation of OH-scavenging activities of drugs for the first time. The upconversion luminescence from NaYF4:Yb,Er nanoparticles was first quenched by carminic acid (CA) through luminescence resonance energy transfer (LRET) mechanism, and then hydroxyl radical-initiated oxidative cleavage of CA can recover the luminescence by inhibition of LRET. The nanosensors exhibited high selectivity towards other reactive oxygen species and many common metal ions with the detection limit down to 0.21 µM, and displayed a relative standard deviation ranging from 1.17% to 3.13%. More attractively, the nanosensors have efficiently avoided the interference of autofluorescence upon near-infrared excitation, and provided a robust platform to study hydroxyl radical scavenging abilities of several common antioxidants such as tannic acid, ascorbic acid and ferulic acid, and visually evaluate antioxidant activities of five traditional Chinese medicines by luminescent images. This newly developed nanosensor could be further exploited for many applications in pharmaceutical, biomedical and environmental engineering areas.

Evaluation of robust wave image processing methods for magnetic resonance elastography.

Magnetic resonance elastography (MRE) is a promising modality for in vivo quantification and visualization of soft tissue elasticity. It involves three stages of processes for (1) external excitation, (2) wave imaging and (3) elasticity reconstruction. One of the important issues to be addressed in MRE is wave image processing and enhancement. In this study we approach it from three different ways including phase unwrapping, directional filtering and noise suppression. The relevant solutions were addressed briefly. Some of them were implemented and evaluated on both simulated and experimental MRE datasets. The results confirm that wave image enhancement is indispensable before carrying out MRE elasticity reconstruction.

Near-infrared-light-based nano-platform boosts endosomal escape and controls gene knockdown in vivo.

Current nanoparticle-based gene delivery techniques face two major limitations, namely, endosomal degradation and poor cytosolic release of the nanoparticles and nonspecificity of treatment. These limitations can be overcome with certain light-based techniques, such as photochemical internalization to enable endosomal escape of the delivered nanoparticles and light-controlled gene expression to overcome the nonspecific effects. However, these techniques require UV/visible light, which is either phototoxic and/or has low tissue penetration capabilities, thus preventing their use in deep tissues in a clinical setting. In an effort to overcome these barriers, we have successfully demonstrated a light-based gene delivery system that significantly boosts cytosolic gene delivery, with precise control over gene expression and the potential for use in nonsuperficial tissues. Core-shell fluorescent upconversion nanoparticles excited by highly penetrating near-infrared radiation and emitting simultaneously in the ultraviolet and visible ranges were synthesized and used as remote nanotransducers to simultaneously activate endosomal escape and gene knockdown. Gene knockdown using photomorpholinos was enhanced as much as 30% in vitro compared to the control without endosomal escape facilitation. A similar trend was seen in vivo in a murine melanoma model, demonstrating the enormous clinical potential of this system.

MREJ: MRE elasticity reconstruction on ImageJ.

Magnetic resonance elastography (MRE) is a promising method for health evaluation and disease diagnosis. It makes use of elastic waves as a virtual probe to quantify soft tissue elasticity. The wave actuator, imaging modality and elasticity interpreter are all essential components for an MRE system. Efforts have been made to develop more effective actuating mechanisms, imaging protocols and reconstructing algorithms. However, translating MRE wave images into soft tissue elasticity is a nontrivial issue for health professionals. This study contributes an open-source platform - MREJ - for MRE image processing and elasticity reconstruction. It is established on the widespread image-processing program ImageJ. Two algorithms for elasticity reconstruction were implemented with spatiotemporal directional filtering. The usability of the method is shown through virtual palpation on different phantoms and patients. Based on the results, we conclude that MREJ offers the MRE community a convenient and well-functioning program for image processing and elasticity interpretation.

Modeling shear modulus distribution in magnetic resonance elastography with piecewise constant level sets.

Magnetic resonance elastography (MRE) is designed for imaging the mechanical properties of soft tissues. However, the interpretation of shear modulus distribution is often confusing and cumbersome. For reliable evaluation, a common practice is to specify the regions of interest and consider regional elasticity. Such an experience-dependent protocol is susceptible to intrapersonal and interpersonal variability. In this study we propose to remodel shear modulus distribution with piecewise constant level sets by referring to the corresponding magnitude image. Optimal segmentation and registration are achieved by a new hybrid level set model comprised of alternating global and local region competitions. Experimental results on the simulated MRE data sets show that the mean error of elasticity reconstruction is 11.33% for local frequency estimation and 18.87% for algebraic inversion of differential equation. Piecewise constant level set modeling is effective to improve the quality of shear modulus distribution, and facilitates MRE analysis and interpretation.

Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation.

The performance of the level set segmentation is subject to appropriate initialization and optimal configuration of controlling parameters, which require substantial manual intervention. A new fuzzy level set algorithm is proposed in this paper to facilitate medical image segmentation. It is able to directly evolve from the initial segmentation by spatial fuzzy clustering. The controlling parameters of level set evolution are also estimated from the results of fuzzy clustering. Moreover the fuzzy level set algorithm is enhanced with locally regularized evolution. Such improvements facilitate level set manipulation and lead to more robust segmentation. Performance evaluation of the proposed algorithm was carried on medical images from different modalities. The results confirm its effectiveness for medical image segmentation.

Development of a mobile pulse waveform analyzer for cardiovascular health monitoring.

Noninvasive pulse waveforms contain rich pathophysiological information of cardiovascular system. It is hereby a tradition of interest to implement risk stratification by pulse waveform monitoring and analysis. In contrast to conventional computer- or network-based solutions, we attempt to accomplish pulse waveform monitoring and analysis within a self-contained mobile platform. It adopts a compact biosensor for pulse waveform acquisition. The collected signals are then submitted to a core board for pulse waveform processing and analysis. In addition, the core board coordinates user interaction and network communication too. Such compact pulse waveform analyzer is of great help for cardiovascular health monitoring at home. A carefully designed evaluation has been undertaken within our research group. The results confirmed its prospect in home healthcare.

SIBAS: a blood bank information system and its 5-year implementation at Macau.

Automation systems and information technology can greatly help medical facilities to improve their working efficiency and optimize the whole workflow. This article surveys electronic information management in blood donation and transfusion service, and explores the rationale and archetype of blood bank information systems, then exemplifies a successful in-running system-Sistema Integrado de Bancos de Sangue (SIBAS), which is developed by the Institute of Systems and Computer Engineering of Macau (INESC-Macau) in cooperation with the Macau Blood Transfusion Center (CTS-Macau). Its implementation and the related lessons are briefly introduced too. In essence, this article is oriented to serve as a reference of contemporary blood bank information systems.

Barcode technology in blood bank information systems: upgrade and its impact.

This paper desires to explore the role of barcode technology in blood bank information systems via addressing its upgrade and the consequent impact. Firstly, it briefs the application and effect of barcode technology in blood donation and transfusion service. In the second, the barcode paradigms of Macau Codabar and ISBT 128 are carefully examined and compared in accordance with the procedure and specifications of barcode upgrade. Then, the impact due to upgrade is assessed from the perspectives of blood bank information system, blood banks, and even blood donation and transfusion service. It finally discusses the considerations on implementing the upgrade of barcode technology in blood bank information systems.