Rapid time-lapse 3D oxygen tension measurements within hydrogels using widefield frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) and image segmentation.

Understanding the influence of oxygen tension on cellular functions and behaviors is crucial for investigating various physiological and pathological conditions. In vitro cell culture models, particularly those based on hydrogel extracellular matrices, have been developed to study cellular responses in specific oxygen microenvironments. However, accurately characterizing oxygen tension variations with great spatiotemporal resolutions, especially in three dimensions, remains challenging. This paper presents an approach for rapid time-lapse 3D oxygen tension measurements in hydrogels using a widely available inverted fluorescence microscope. Oxygen-sensitive fluorescent microbeads and widefield frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) are utilized for oxygen tension estimation. To incorporate the third dimension, a motorized sample stage is implanted that enables automated image acquisition in the vertical direction. A machine learning algorithm based on K-means clustering is employed for microbead position identification. Using an upside-down microfluidic device, 3D oxygen gradients are generated within a hydrogel sample, and z-stack images are acquired using the FD-FLIM system. Analyses of the acquired images, involving microbead position identification, lifetime calculation, and oxygen tension conversion, are then performed offline. The results demonstrate the functionality of the developed approach for rapid time-lapse 3D oxygen tension measurements in hydrogels. Furthermore, the 3D oxygen tension adjacent to a tumor spheroid within a hydrogel during media exchange is characterized. The results further confirm that the 3D spatiotemporal oxygen tension profiles can be successfully measured quantitatively using the established setup and analysis process and that the approach may have great potential for investigating cellular activities within oxygen microenvironments.

The effects of nontoxic bio-based substances (egg white) on the performance and passivation of ZnO nanorods arrays-based light emitting devices.

An innovative approach is proposed to passivate the existing defects from metal oxide semiconductors by functionalizing nontoxic bio-based substances. As a demonstration, we synthesized zinc oxide nanorods (ZnO NRs) using a hydrothermal method and incorporated chicken egg white (albumen) as a passivator to the defects. X-ray diffraction analysis of ZnO NRs shows enhanced quality and crystallinity features after incorporating albumen. XPS measurements were performed not only to introduce the chemical bonding between the albumen and the bare ZnO NRs but also specifically provide evidence of successful capping and defect passivation to the surface layer of ZnO NRs. It was observed that when the albumen was annealed, it formed sulfhydryl groups and disulfide bonds (which created disulfide bridges) from the chemical reaction in irreversible thermal denaturation. Steady-state photoluminescence of ZnO NRs showed two emission bands, i.e. near band-edge emission (NBE) and deep-level emission (DL). The NBE is significantly improved as compared to DL emission after capping and annealing the albumen, while the quenching of DL emission confirmed the reduced defects arising from the surface of ZnO NRs. The advantages and enhanced characteristics of the albumen-capped ZnO NRs led to fabricating a stable and highly efficient light-emitting device. This work opens the great potential of utilizing nontoxic and low-cost biomaterials in passivating the defects of metal oxide nanomaterials for the development of bio-inspired and stable optoelectronic devices.

90% Accuracy for Photoplethysmography-Based Non-Invasive Blood Glucose Prediction by Deep Learning with Cohort Arrangement and Quarterly Measured HbA1c.

Previously published photoplethysmography-(PPG) based non-invasive blood glucose (NIBG) measurements have not yet been validated over 500 subjects. As illustrated in this work, we increased the number subjects recruited to 2538 and found that the prediction accuracy (the ratio in zone A of Clarke's error grid) reduced to undesirable 60.6%. We suspect the low prediction accuracy induced by larger sample size might arise from the physiological diversity of subjects, and one possibility is that the diversity might originate from medication. Therefore, we split the subjects into two cohorts for deep learning: with and without medication (1682 and 856 recruited subjects, respectively). In comparison, the cohort training for subjects without any medication had approximately 30% higher prediction accuracy over the cohort training for those with medication. Furthermore, by adding quarterly (every 3 months) measured glycohemoglobin (HbA1c), we were able to significantly boost the prediction accuracy by approximately 10%. For subjects without medication, the best performing model with quarterly measured HbA1c achieved 94.3% prediction accuracy, RMSE of 12.4 mg/dL, MAE of 8.9 mg/dL, and MAPE of 0.08, which demonstrates a very promising solution for NIBG prediction via deep learning. Regarding subjects with medication, a personalized model could be a viable means of further investigation.

Widefield frequency domain fluorescence lifetime imaging microscopy (FD-FLIM) for accurate measurement of oxygen gradients within microfluidic devices.

An oxygen gradient is a key variable influencing various biological activities in vivo, such as tissue repair and tumor growth. To study the phenomenon, in vitro cell studies using microfluidic devices capable of generating oxygen gradients have been developed recently. However, it is challenging to accurately measure the gradient profiles in devices. The traditional fluorescence intensity-based method suffers from the difficulty of accurate measurement due to background fluorescence artefacts. In addition, it is hard to obtain accurate calibration conditions because of the difficulties to achieve a fully depleted and saturated oxygen concentrations in the devices. To overcome these difficulties, a widefield frequency domain fluorescence imaging microscopy (FD-FLIM) system was constructed and utilized to accurately measure oxygen gradient profiles in a microfluidic device in this paper. Since lifetime-based measurements do not solely depend on intensity variations, oxygen calibration processes are amiable and the measured oxygen concentrations can be more accurate. The performance of the FD-FLIM system was validated by comparing the experimental and simulation results in microfluidic devices with different geometries. The experimental results show that the oxygen gradients generated from the chemical reaction method can provide more hypoxic oxygen conditions compared to the gradients created by the gas flowing method. Owing to the advantages provided by the widefield microscopy technique, the image acquisition time can be significantly reduced resulting in less photobleaching for time-lapsed imaging applications. Consequently, the measurement technique developed in this paper is an efficient tool, which can greatly help scientists to better study biological activities under various oxygen conditions.

Multiplex detection of urinary miRNA biomarkers by transmission surface plasmon resonance.

The clinical assessment of short-stranded nucleic acid biomarkers such as miRNAs could potentially provide useful information for monitoring disease progression, prompting definitive treatment decisions. In the past decade, advancements in biosensing technology have led to a shift towards rapid, real-time and label-free detection systems; as such, surface plasmon resonance (SPR) biosensor-based technology has become of high interest. Here, we developed an automated multiplex transmissive surface plasmon resonance (t-SPR) platform with the use of a capped gold nanoslit integrated microfluidic surface plasmon resonance (SPR) biosensor. The automated platform was custom designed to allow the analysis of spectral measurements using wavelength shift (dλ), intensity (dI) and novel area change (dA) for surface binding reactions. A simple and compact nanostructure based biosensor was fabricated with multiplex real-time detection capabilities. The sensitivity and specificity of the microfluidic device was demonstrated through the use of functionalised AuNPs for target molecule isolation and signal enhancement in combination with probes on the CG nanoslit surface. Our work allows for the multiplex detection of miRNA at femtomolar concentrations in complex media such as urine.

Deduction learning for precise noninvasive measurements of blood glucose with a dozen rounds of data for model training.

Personalized modeling has long been anticipated to approach precise noninvasive blood glucose measurements, but challenged by limited data for training personal model and its unavoidable outlier predictions. To overcome these long-standing problems, we largely enhanced the training efficiency with the limited personal data by an innovative Deduction Learning (DL), instead of the conventional Induction Learning (IL). The domain theory of our deductive method, DL, made use of accumulated comparison of paired inputs leading to corrections to preceded measured blood glucose to construct our deep neural network architecture. DL method involves the use of paired adjacent rounds of finger pulsation Photoplethysmography signal recordings as the input to a convolutional-neural-network (CNN) based deep learning model. Our study reveals that CNN filters of DL model generated extra and non-uniform feature patterns than that of IL models, which suggests DL is superior to IL in terms of learning efficiency under limited training data. Among 30 diabetic patients as our recruited volunteers, DL model achieved 80% of test prediction in zone A of Clarke Error Grid (CEG) for model training with 12 rounds of data, which was 20% improvement over IL method. Furthermore, we developed an automatic screening algorithm to delete low confidence outlier predictions. With only a dozen rounds of training data, DL with automatic screening achieved a correlation coefficient ([Formula: see text]) of 0.81, an accuracy score ([Formula: see text]) of 93.5, a root mean squared error of 13.93 mg/dl, a mean absolute error of 12.07 mg/dl, and 100% predictions in zone A of CEG. The nonparametric Wilcoxon paired test on [Formula: see text] for DL versus IL revealed near significant difference with p-value 0.06. These significant improvements indicate that a very simple and precise noninvasive measurement of blood glucose concentration is achievable.

The role of the auxiliary atomic ion beam in C60(+)-Ar+ co-sputtering.

Cluster ion sputtering has been proven to be an effective technique for depth profiling of organic materials. In particular, C(60)(+) ion beams are widely used to profile soft matter. The limitation of carbon deposition associated with C(60)(+) sputtering can be alleviated by concurrently using a low-energy Ar(+) beam. In this work, the role of this auxiliary atomic ion beam was examined by using an apparatus that could analyze the sputtered materials and the remaining target simultaneously using secondary ion mass spectrometry (SIMS) and X-ray photoelectron spectrometry (XPS), respectively. It was found that the auxiliary 0.2 kV Ar(+) stream was capable of slowly removing the carbon deposition and suppresses the carbon from implantation. As a result, a more steady sputtering condition was achieved more quickly with co-sputtering than by using C(60)(+) alone. Additionally, the Ar(+) beam was found to interfere with the C(60)(+) beam and may lower the overall sputtering rate and secondary ion intensity in some cases. Therefore, the current of this auxiliary ion beam needs to be carefully optimized for successful depth profiling.

Cost-effectiveness of percutaneous coronary intervention versus medical therapy in patients with acute myocardial infarction: real-world and lifetime-horizon data from Taiwan.

Although some studies have assessed the cost-effectiveness of percutaneous coronary intervention (PCI) in acute myocardial infarction (AMI), there has been a lack of nationwide real-world studies estimating life expectancy (LE), loss-of-LE, life-years saved, and lifetime medical costs. We evaluated the cost-effectiveness of PCI versus non-PCI therapy by integrating a survival function and mean-cost function over a lifelong horizon to obtain the estimations for AMI patients without major comorbidities. We constructed a longitudinal AMI cohort based on the claim database of Taiwan's National Health Insurance during 1999-2015. Taiwan's National Mortality Registry Database was linked to derive a survival function to estimate LE, loss-of-LE, life-years saved, and lifetime medical costs in both therapies. This study enrolled a total of 38,441 AMI patients; AMI patients receiving PCI showed a fewer loss-of-LE (3.6 versus 5.2 years), and more lifetime medical costs (US$ 49,112 versus US$ 43,532). The incremental cost-effectiveness ratio (ICER) was US$ 3488 per life-year saved. After stratification by age, the AMI patients aged 50-59 years receiving PCI was shown to be cost-saving. From the perspective of Taiwan's National Health Insurance, PCI is cost-effective in AMI patients without major comorbidities. Notably, for patients aged 50-59 years, PCI is cost-saving.

Generation of Augmented Capillary Network Optical Coherence Tomography Image Data of Human Skin for Deep Learning and Capillary Segmentation.

The segmentation of capillaries in human skin in full-field optical coherence tomography (FF-OCT) images plays a vital role in clinical applications. Recent advances in deep learning techniques have demonstrated a state-of-the-art level of accuracy for the task of automatic medical image segmentation. However, a gigantic amount of annotated data is required for the successful training of deep learning models, which demands a great deal of effort and is costly. To overcome this fundamental problem, an automatic simulation algorithm to generate OCT-like skin image data with augmented capillary networks (ACNs) in a three-dimensional volume (which we called the ACN data) is presented. This algorithm simultaneously acquires augmented FF-OCT and corresponding ground truth images of capillary structures, in which potential functions are introduced to conduct the capillary pathways, and the two-dimensional Gaussian function is utilized to mimic the brightness reflected by capillary blood flow seen in real OCT data. To assess the quality of the ACN data, a U-Net deep learning model was trained by the ACN data and then tested on real in vivo FF-OCT human skin images for capillary segmentation. With properly designed data binarization for predicted image frames, the testing result of real FF-OCT data with respect to the ground truth achieved high scores in performance metrics. This demonstrates that the proposed algorithm is capable of generating ACN data that can imitate real FF-OCT skin images of capillary networks for use in research and deep learning, and that the model for capillary segmentation could be of wide benefit in clinical and biomedical applications.

Simultaneous assessment of cell morphology and adhesion using aluminum nanoslit-based plasmonic biosensing chips.

A variety of physiological and pathological processes rely on cell adhesion, which is most often tracked by changes in cellular morphology. We previously reported a novel gold nanoslit-based biosensor that is capable of real-time and label-free monitoring of cell morphological changes and cell viability. However, the preparation of gold biosensors is inefficient, complicated and costly. Recently, nanostructure-based aluminum (Al) sensors have been introduced for biosensing applications. The Al-based sensor has a longer decay length and is capable of analyzing large-sized mass such as cells. Here, we developed two types of double-layer Al nanoslit-based plasmonic biosensors, which were nanofabricated and used to evaluate the correlation between metastatic potency and adhesion of lung cancer and melanoma cell lines. Cell adhesion was determined by Fano resonance signals that were induced by binding of the cells to the nanoslit. The peak and dip of the Fano resonance spectrum respectively reflected long- and short-range cellular changes, allowing us to simultaneously detect and distinguish between focal adhesion and cell spreading. Also, the Al nanoslit-based biosensor chips were used to evaluate the inhibitory effects of drugs on cancer cell spreading. We are the first to report the use of double layer Al nanoslit-based biosensors for detection of cell behavior, and such devices may become powerful tools for anti-metastasis drug screening in the future.

Compressed sensing based CT reconstruction algorithm combined with modified Canny edge detection.

Given that the computed tomography (CT) reconstruction algorithm based on compressed sensing (CS) results in blurred edges, we propose a modified Canny operator that assists the CS algorithm to accurately capture an object's edge, to preserve and further enhance the contrasts in the reconstructed image, thereby improving image quality. We modified two procedures of the traditional Canny operator, namely non-maximum suppression and edge tracking by hysteresis according to the characteristics of low-dose CT reconstruction, and proposed two major modifications: double-response edge detection and directional edge tracking. The newly modified Canny operator was combined with the CS reconstruction algorithm to become an edge-enhanced CS (EECS). Both a 2D Shepp-Logan phantom and a 3D dental phantom were used to conduct reconstruction testing. Root-mean-square error, peak signal-to-noise ratio, and universal quality index were employed to verify the reconstruction results. Qualitative and quantitative results of EECS reconstruction showed its superiority over conventional CS or CS combined with different edge detection techniques, such as Laplacian, Prewitt, Sobel operators, etc. The experiments verified that the proposed modified Canny operator is able to effectively detect the edge location of an object during low-dose reconstruction, enabling EECS to reconstruct images with better quality than those produced by other algorithms.

Neuberger's double-pass algorithm.

We analyze Neuberger's double-pass algorithm for the matrix-vector multiplication R(H) x Y [where R(H) is (n-1,n)th degree rational polynomial of positive definite operator H], and show that the number of floating-point operations is independent of the degree n, provided that the number of sites is much larger than the number of iterations in the conjugate gradient. This implies that the matrix-vector product (H)(-1/2)Y approximately R((n-1,n))(H).Y can be approximated to very high precision with sufficiently large n, without noticeably extra costs. Further, we show that there exists a threshold n(T) such that the double-pass is faster than the single pass for n>n(T), where n(T) approximately 12-25 for most platforms.

Acute aortic dissection associated with left ventricular dysfunction in a postpartum and normotensive young woman.

Aortic dissection is uncommon in young women and is associated with clinical conditions such as pregnancy and Marfan's syndrome. Owing to the low incidence, diagnosis of acute aortic dissection in young women might be missed or delayed in patients who have neither risk factors nor typical clinical manifestations. We report the case of a 28-year-old postpartum woman with aortic dissection. The patient complained of abdominal discomfort, transient back pain, and general malaise at our emergency department 1 week after delivery of a healthy baby. She had no history of hypertension, connective tissue disease or congenital heart disease. Cardiovascular insult was not considered until the patient developed shock. Myocarditis or peripartum cardiomyopathy with left ventricular dysfunction was diagnosed based on imaging studies and cardiac enzyme levels. Finally, computed tomography revealed acute aortic dissection after hemodynamic collapse occurred. This case suggests that acute aortic dissection can be associated with left ventricular dysfunction, and non-specific clinical symptoms in young, normotensive, and postpartum women. A high index of clinical suspicion and alertness are needed to identify this condition.

Systemic lupus erythematosus with initial presentation of empyematous pleural effusion in an elderly male patient: a diagnostic challenge.

Systemic lupus erythematosus (SLE) poses great difficulty in making an early diagnosis in elderly males, often presenting with atypical manifestations. Acute onset of empyematous pleural effusion has rarely been seen. Herein, we report a 66-year-old man with SLE presenting with rapid progression of bilateral pleural effusion. Diagnostic thoracocentesis disclosed neutrophil-predominant exudates and chest computed tomography revealed multiple loculated pleural effusions. Nevertheless, optimal antibiotic therapy plus surgical decortication of the pleura did not improve his condition. The diagnosis of SLE was readily established after LE cells were accidentally found in the pleural effusion. Large amounts of pleural effusion subsided soon after high dose corticosteroid therapy.

Low Papanicolaou smear screening rate of women with HIV infection: a nationwide population-based study in Taiwan, 2000-2010.

BACKGROUND: Women infected by human immunodeficiency virus (HIV) have a higher risk of contracting cervical cancer. Recent guidelines recommend that all HIV-positive women should receive two Pap smears in the first year after their HIV diagnosis. METHODS: This was a population-based cohort study, and the National Health Insurance Research Database (NHIRD) in Taiwan was used to estimate the Pap smear screening rate for 1449 HIV-infected women aged 18 years and over from 2000 to 2010. A multiple logistic regression analysis was used to identify factors associated with HIV-infected women who had received Pap smears. RESULTS: Of 1449 women, 618 (43%) women received at least one Pap smear. Only 14.7% of the HIV-infected women received Pap smears within one year after being diagnosed with HIV. A logistic regression analysis showed that the factors associated with receiving at least one Pap smear after HIV diagnosis were increasing age (AOR 1.04, 95% CI 1.03-1.05), high monthly income (AOR 1.83, 95% CI 1.51-2.23), any history of antiretroviral therapy (AOR 1.78, 95% CI 1.38-2.29), retention in HIV care (AOR 1.36, 95% CI 1.04-1.77), a history of sexually transmitted diseases (AOR 1.96, 95% CI 1.50-2.56), and any history of treatment for opportunistic infections (AOR 2.46, 95% CI 1.91-3.16). CONCLUSIONS: A great need exists to develop strategies for promoting receipt of Pap smear screening services that specifically target severely disadvantaged women with HIV, particularly younger, lower income women and those in an asymptomatic phase.

Improving in-hospital mortality in elderly patients after acute coronary syndrome--a nationwide analysis of 97,220 patients in Taiwan during 2004-2008.

BACKGROUND: Elderly patients seem to have especially poor outcomes after acquiring acute coronary syndrome (ACS). We conducted this study to examine the in-hospital mortality by utilization of invasive coronary therapies and age in a nationwide population in Taiwan. METHODS: This observational study was conducted on a retrospective cohort from January 2004 to December 2008. Epidemiological features, including incidence rate and clinical characteristics of ACS in a Chinese population were investigated. Risk factors of in-hospital mortality, including myocardial infarction, shock, previous history of stroke, chronic kidney disease, diabetes mellitus, congestive heart failure, pneumonia, chronic obstructive pulmonary disease, dementia, peripheral arterial occlusive disease, septicemia and the use of invasive coronary procedures, were explored using a logistic regression model. RESULTS: A total of 97,220 patients were enrolled, and 53.6% of them were elderly. A significant decrease in the utilization rate of invasive coronary therapies (diagnostic coronary angiography and PCI) and increased in-hospital mortality (p<0.001) were observed as patient age increased. Adjusted multivariate logistic regression analysis revealed that the impact of PCI in reducing in-hospital mortality is consistent across age groups, including those older than 75 years old. CONCLUSIONS: Our nationwide study provides evidence that PCI is associated with significant improvement of in-hospital mortality in patients with ACS. Even the very elderly patients could benefit from PCI. However, currently the utilization rate of PCI in the aging population still does not present enough. A prospective study is indicated to corroborate the findings of this study.