Session Index

As the final layer of the central dogma, metabolomes directly reflect phenotypic changes in human bodies. However, the cumbersome sample preparation process for mass spectroscopic measurement and the lack of spatial information in tissues limit their wide application in clinical practice. Here, we propose the use of fluorescent metabolomics, which consists of metabolites that can emit fluorescence in blood, saliva, and urine. In comparison to conventional mass spectroscopic measurement, fluorescent metabolomics allows for direct measurement without the need for reagents. It can serve as a continuous monitoring device for detecting the emergence of acute illnesses. Furthermore, when combined with a multiphoton imaging system, spatial metabolomic information can be obtained with sub-cellular resolution. In this lecture, we will demonstrate the use of fluorescent metabolomics in evaluating organoid pharmacokinetics, detecting the presence of acute mesenteric ischemia, and aiding in the differential diagnosis of prediabetes. This provides a new avenue toward precision medicine.

  Preview abstract

With a miniaturized scan lens and a micro-electro-mechanical system (MEMS) mirror, we designed the 1st-gen miniaturized endoscopy system which is called “NTU miniScope”. Through different designs of scan lens and gradient refractive index (GRIN) lens pair, one can easily substitute the imaging head of the NTU miniScope by using a magnetic-base design. Moreover, with a sparse spiral scanning pattern, a 600Hz frame rate can be realized for voltage imaging.

  Preview abstract

This study investigates enhancing endoscopy image quality through deep learning. We explore supervised and unsupervised approaches using a dataset of 3500 images. Preprocessing techniques reduce noise, and experiments highlight deep learning’s potential. The study aims to improve image quality and elucidate effective methodologies.


  Preview abstract

Endo-microscopy with structured illumination HiLo imaging process can provide sectioning ability. However, moving optical elements in the axial direction for the 3D imaging restricts compact endoscopic system design. In addition, HiLo imaging requires multiple shots, which is time-consuming and make system configuration complicated. Here, we propose an in-vivo intelligent fluorescence sectioning using meta-varifocal endo-microscopy. With the telecentric design, the endo-microscopy can provide constant magnification during axial scanning for in-vivo 3D imaging of mouse brains. Furthermore, we introduce the deep learning (DL) network for HiLo sectioning technique, which can substantially reduce image acquisition time and system complexity.

  Preview abstract

Understanding human brain function is crucial yet challenging due to its complexity, especially in Attention-Deficit/Hyperactivity Disorder (ADHD). This study addresses the issue by utilizing cerebral organoids from human pluripotent stem cells (hiPSCs) and employing a custom two-photon microscopy and Fluo-4 indicator for calcium imaging and neural activity analysis. To handle the extensive and complex streaming data, we propose an analytics methodology. Results exhibit synchronization patterns and frequency-amplitude differences between different genotypes. Our analysis not only provides comprehensive insights into neuron dynamics but also holds promise for understanding the intricacies of brain function and dysfunction.

  Preview abstract

Mammograms are critical for early detection of breast cancer. However, the accuracy of mammogram readings varies and depends on radiologists' experience and skill. Artificial intelligence (AI), with its visualization capability, can assist physicians in detecting cancer. However, current AI models often detect lesions but lack information on types and the Breast Imaging Reporting & Data System (BI-RADS) scores. In this study, we propose an approach that leverages mammogram resources, biopsy results, and the BI-RADS scoring procedure of radiologists to predict breast malignancies on our private dataset of 155 patients using our custom model.

  Preview abstract

Swept source optical coherence tomography (SS-OCT) is a high-speed, and non-contact imaging modality that can provide three-dimensional tissue structure. With the advantage of long coherence length, MEMS tunable vertical cavity surface emitting laser (VCSEL) is a suitable light source for full-eye imaging. In this work, we have developed a full-eye imaging engine by using a novel wavelength-swept laser light source based on high-contrast grating (HCG) VCSEL. Full eye model imaging and the axial length measurement as well as the evaluation of the tuning noise of the HCG-VCSEL are performed at an A-scan rate of 30 kHz.

  Preview abstract

Diabetes is a chronic metabolic disease that can lead to hypertension, cardiovascular
complications, strokes, and mortality if blood glucose remains uncontrolled. Monitoring blood
glucose trends enables physicians to tailor treatment strategies. However, current invasive
testing methods, such as blood tests are inconvenient, which hinders regular screening. To tackle
this issue, we developed a non-invasive diffuse reflectance optical system incorporating a
machine learning algorithm. This system computes skin tissue's optical properties and
establishes a correlation between glucose variations during the oral glucose tolerance test and
changes in scattering coefficients. This non-invasive approach aims to enhance awareness and
management of diabetes-related risks.

  Preview abstract

We have developed a multifunctional catheter-based OCT system, which provides architecture and birefringence information of biological tissue and allows volumetric imaging of the luminal part of the cervix. Preliminary imaging results of the in vivo human buccal mucosa and tongue were shown to validate the capabilities of volumetric imaging in the developed multifunctional OCT system, and further obtained the birefringence information by analyzing the polarization information of the OCT signal to implement the multifunctional OCT imaging.

  Preview abstract

This study aims to develop a non-invasive and handheld optical system for accurate measurement of hemoglobin concentration, with potential applications in diagnosing and monitoring various diseases, such as anemia. We utilized DRS for non-invasive hemoglobin measurement with an optical system featuring six LED wavelengths and photodetector (PD) modules, achieving precise hemoglobin monitoring. In 10 participants, our optical system data correlated strongly (r=0.85187) with data from invasive devices. Our system shows promise for clinical diagnosis and health monitoring, with potential for measuring other physiological parameters in the future.

  Preview abstract

Mid-infrared (MIR) spectrometer is an extremely and fundamentally important scientific instrument that can provide critical information on material composition and properties by analyzing the energy absorption properties of molecules at specific wavelengths and has been widely used in many applications. In this study, we demonstrate a miniaturized, low-cost, and portable mid-infrared optical spectrometer for different carbon dioxide gases detection. Based on the results, this spectrometer will have many applications in the future.

  Preview abstract

By capitalizing on label-free imaging, high-resolution capabilities, and the simultaneous visualization of tissue structures and chemical properties offered by nonlinear optical (NLO) microscopy, we can potentially attain accuracy levels akin to those of traditional histopathology in the study of human esophageal cancer specimens. Moreover, the outcomes derived from this approach serve as invaluable training data for the machine learning (ML) algorithm. This combined study empowers us to achieve rapid and accurate cancer detection, which facilitates the translation of NLO microscopy into clinical contexts, thus broadening its utility spectrum from fundamental biomedical research to AI-assisted pathology.

  Preview abstract

In the current assessment of skin disorders, optical coherence tomography (OCT) is commonly employed as a frontline diagnostic tool. This study focuses on the analysis of skin images obtained from a lightweight handheld OCT device, aiming for automated analysis. Segmentation algorithms are applied to enhance accuracy and processing speed. Additionally, data augmentation and increased dataset size are explored to improve model training accuracy.

  Preview abstract

The COVD-19 epidemic has brought huge disasters to the world since 2020 including millions of deaths, and the economies of many countries have also been severely hit. Therefore, the development of drugs that can inhibit COVD-19 has become a topic of worldwide concern. In this experiment, we used the principle of SPR to determine the inhibitory effect of different potential drugs on the binding of SARS-Cov-19 omicron Spike S1 protein and human ACE2 receptors. This time we chose Antcin K. To observe whether it can inhibit the combination between the S-1 protein and ACE2 protein.

  Preview abstract

The study aims to create an optical reflective device to simultaneously measure arterial oxygen saturation and hemoglobin concentration. We validated its capability to detect real-time blood oxygen changes during breath-holding experiments. Using finger prick tests as a reference, we achieved correlation coefficients of 0.923 and 0.961 for hemoglobin concentration measured on the forehead and wrist, respectively. Our findings confirm the system's accurate in-vivo hemoglobin concentration calculation.

  Preview abstract

Optical coherence tomography (OCT) is a non-invasive optical imaging technology that can provide real-time and two- or three-dimensional information about the sample architecture based on intrinsic optical scattering contrast. The emergence of the second generation of OCT – Fourier-domain (OCT) with so-called Fourier-domain interferometry has revolutionized OCT in biomedical applications, leveraging the increased imaging speed, improved detection sensitivity, and extended imaging range, which also leads to adding the functional information of the imaging tissue, for example, OCT angiography (OCTA) and polarization-sensitive OCT (PS-OCT). In addition, the FD-OCT also further reduced the system complexity, beneficial to the broader commercialization of the OCT technology. In addition to exploring the feasibility of OCT in various biomedical applications, the interest in using OCT for industry non-destructive inspection has increased recently, for example, the volumetric inspection of defects present within semiconductor chips or wafers. In this talk, I will review our recent work on developing high-speed OCT technology for various biomedical applications and share preliminary results on using OCT for volumetric imaging of semiconductor wafers.

  Preview abstract

Full-field optical coherence tomography (FF-OCT) achieve non-invasive and high spatial resolution in cell imaging. Presently, we have developed a method to capture dynamic signals in cells using the FF-OCT system. We analyze different dynamic characteristics of cells within the frequency domain, allowing for the generation of color-coded dynamic FF-OCT image through a customized analysis program. This approach enables the exploration of various dynamic characteristics manifested by cells, thereby enhancing comprehension of the samples.

  Preview abstract

Full-field optical coherence tomography (FF-OCT) can achieve cellular-resolution imaging non-invasively. Integrating a high-frame-rate CCD sensor and a high-brightness broadband source can pinpoint the dynamic physiological signals with micron resolution within the 3-D imaging volume at a millisecond time scale. As a demonstration, human corneal epithelial cells (HCECs) were cultivated and used as the test sample for the 3-D dynamic FF-OCT system. The dynamic behavior of the HCECs was analyzed in the frequency domain and coded by colors. The 3-D color-coded D-FF-OCT can well reveal spatial-temporal physiological cellular activities of the HCECs.

  Preview abstract

This study utilizes multiphoton excited fluorescence microscopy (MPEFM) to scan sections of fibrotic mouse lungs. By employing time-correlated single photon counting (TCSPC), fluorescence lifetime information can be directly obtained. This allows recording the fluorescence lifetime values for each pixel, which are then used to reconstruct a fluorescence lifetime image (FLIM) with spatial resolution of submicron. Finally, the phasor analysis method is applied to identify the presence of collagen type I and type III within the images.

  Preview abstract

During the treatment for periodontitis, dental calculus removal is necessary. We have proposed the DAM algorithm previously for lesion identification, which enables the non-contact evaluation during the operation. However, dental calculus delineation was still flawed. Therefore, we utilized the power of polarization-sensitive optical coherence tomography and evaluated the contrast called degree of polarization uniformity for dental calculus visualization.

  Preview abstract

With the rising annual prevalence of high myopia patients, the patients are often coupled with myopia choroidal neovascularization (mCNV) exhibiting the potential to induce visual impairment. This study endeavors to harness optical coherence tomography (OCT) and OCT angiography (OCTA) imaging data to build machine learning models capable of distinguishing between active and inactive mCNV cases. The ultimate objective is to curtail the necessity for frequent recourse to fluorescein angiography (FAG).

  Preview abstract

In order to address the limitations of circular phantoms and improve the versatility of the reconstruction approach via diffuse optical imaging (DOI), transfer learning is utilized in this work. Transfer learning is employed to adapt the previously developed architecture(s) to handle elliptical phantoms in DOI. By leveraging the knowledge and pre-trained weights obtained from the circular phantom dataset, the network is fine-tuned using the newly acquired elliptical phantom dataset. This approach can potentially enhance the realism and accuracy of DOT imaging, enabling more precise characterization of biological tissues and structures.

  Preview abstract

Biophotonics tools offer noninvasive and easily applicable tools for the detection of alternations in structural and biochemical compositions of tissues and cells, which may indicate the presence of disease. The present work discusses about developing reliable, sensitive and objective biophotonics tools for various biomedical applications. Our methods have the added advantage of being label-free, objective because of the fact that diagnostic evaluation is by statistical methods, eliminating errors from lack of experience, fatigue factor, and subjectivity in the decision making.

  Preview abstract

The current study aimed to establish a patient-derived xenografts (PDXs) model in athymic nude mice. The breast tumor progression was monitored at two progressive tumor volumes of 300 mm3 & 600 mm3, respectively. Ex vivo tumor specimens were also collected, reflecting the diversity of breast cancer types, tissue changes, and tumor behavior. These samples were subjected to photoacoustic spectral measurements compared to control samples. The photoacoustic spectral data analysis involving preprocessing, wavelet transform, feature selection, and classification using support vector machine learning demonstrated an overall accuracy of 98.3%, revealing the tool's potentiality in breast cancer detection.

  Preview abstract

We propose using a Transformer model to predict 17 joint locations from sparse point clouds, enabling more comprehensive body information extraction. Our current results achieve an mae of 1.678cm.

  Preview abstract

We demonstrated three-photon fluorescence microscopy for drosophila brain imaging based on a 24-MHz Cr:forsterite oscillator. We studied the soliton mode-locking dynamics to optimize the output pulse width and peak power by managing the intracavity dispersion. We have realized three-photon fluorescence imaging, and the imaging contrast and penetration depth are much better than the results obtained from the two-photon excitation. Moreover, we found that the signal-to-background ratio at depth is greatly improved when using shorter pulses from the laser oscillator. For functional imaging applications, we also demonstrated three-photon calcium imaging stimulated by an external electric shock.

  Preview abstract

This study combines functional near-infrared spectroscopy (fNIRS) with machine learning to find the difference between healthy individuals and migraine patients in young populations during a concentration task (CT). Statistical methods are applied to find the features which have significant differences. In this research, we employ the support vector machine (SVM) for young migraine detection, achieving accuracies of 96.4% and 83.3% on training and testing data, respectively.

  Preview abstract

This study explores the increasing prevalence of Tourette syndrome (TS) and its impact on patient’s quality of life. TS symptoms, known as tics, can be motor or vocal. While drugs are commonly used for treatment, they often entail significant side effects. Therefore, behavior therapy, particularly neurofeedback training using functional near-infrared spectroscopy, is considered a preferable approach. The research demonstrates the effectiveness of neurofeedback training for TS patients, with an 83.3% training and 75.0% testing accuracy in distinguishing high and low tic severity groups. The study confirms the model's generalization ability, offering the potential for advanced classification using machine learning.

  Preview abstract

Recently various swept sources have achieved commercial success for the biomedical applications such as optical coherence tomography and photo acoustic tomography, but there has been a limitation for increasing repetition speed and phase stability. Achieving both ultra-high-speed (multi-MHz repetition rates) and ultra-phase stability (sub-nm) simultaneously has been reported based on the stretched-pulse active mode locking (SPML) configuration The long and continuous chirped pulse with a broad spectral bandwidth is achieved through the repeated stretching, amplification, and compression of the optical pulse in the SPML laser cavity.

  Preview abstract

Fluorescence lifetime imaging microscopy of exogenous fluorophore of calcium (Ca2+) sensor Oregon Green 488 BAPTA-1 (OGB) and endogenous fluorescent coenzymes nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) has been used to differentiate the calcium signaling and metabolic changes in cancerous and normal cells, and the effects of the application of the nanosecond pulsed electric field (nsPEF) on intracellular functions and dynamics, including the cell death, have been examined. FLIM of OGB, NADH, and FAD has revealed that the concentration and distribution of Ca2+ and metabolic processes and their responses to nsPEF are different in cancerous and normal cells

  Preview abstract

We present the use of polarization-resolved second harmonic generation (P-SHG) microscopy as an effective tool for diagnosing osteoarthritis (OA) and rheumatoid arthritis (RA), which is crucial to enhance the contrast in distinguishing between normal tissue and OA and RA, as well as OA and RA. The derived parameters, such as the susceptibility tensor ratio, degree of linear polarization (DOLP), SHG anisotropy factor, and orientation distribution of collagen fibrils, can be used for diseased tissue classifications. Importantly, the results support a clear understanding of the degradation process of collagen fibrils in cartilage.

  Preview abstract

In this study, we simulate the behavior of photons in skin tissues using the Monte Carlo Method to obtain the Photoplethysmography (PPG) waveform. These simulations give us comprehensive insights into how tissue structure influences the PPG waveform and determine the optimal distance between the detector and light source, which is approximately 0.4 cm in our simulation results.

  Preview abstract

Starch is one of the most abundantly found carbohydrates in cereals, roots, legumes, and fruits and is located in the amyloplasts of plants. The amorphous amylose and crystalline amylopectin regions in starch granules are susceptible to certain physical modifications, such as gamma irradiation. P-SHG microscopy in conjunction with SHG-circular dichroism was used to assess the 3D molecular order and inherent chirality of starch granules and their reaction to different dosages of gamma irradiation. The results showed that changes in the structure and orientation of long-chain amylopectin were supported by the decrease in the SHG anisotropy factor and the χ22/χ16 ratio.

  Preview abstract

Third-harmonic-generation (THG) imaging, offering sub-cellular resolution and sub-millimeter penetration depth, holds great promise for skin virtual biopsy. However, its conventional implementation necessitates expensive components like femtosecond fiber lasers and high-numerical-aperture objective lenses. In this study, we harnessed deep learning to create THG-like images. We developed a three-dimensional conditional generative adversarial network model capable of generating THG-like images from reflectance scanning microscope data. Applying this model to human skin samples demonstrated its efficacy. This innovative approach offers a cost-effective means to leverage the benefits of THG imaging for non-invasive skin analysis, potentially revolutionizing virtual biopsies.

  Preview abstract

Utilizing an intermediate layer, the Attention-UW Net model improves segmentation efficiency between encoders and decoders. We demonstrate its effectiveness in segmenting time-lapse cell images from an electron microscopy dataset, achieving high evaluation scores (precision: 0.97, recall: 0.76, F1 Score: 0.82) even without data augmentation.

  Preview abstract

Glycated hemoglobin (HbA1c) is a pivotal metric for diabetes diagnosis. Conventional measurements tend to be invasive and time-consuming. Here, we report a method utilizing ultraviolet-visible spectrum measurement to determine HbA1c levels. Comprehensive spectral feature analyses, wavelength selection, validations based on idealized samples, and tests employing real blood samples were conducted. We also incorporated a novel correction technique, substantially bolstering the predictive accuracy of our real blood model, with the R-squared value rising from 0.55 to 0.86. This study enriches the theoretical exploration of optical detection for HbA1c, presenting a more exhaustive argument and promising extensive applications.

  Preview abstract

Optical coherence tomography (OCT) has been widely used in many clinical apartments. The trade-off between field-of-view (FOV) and transverse resolution has always become critical. High-resolution (HR) image reconstruction of OCT can increase the resolution without reducing the FOV. But, it is hard to find one-to-one paired HR for reference. The HR methods are used to improve the cross-sectional OCT image only. Therefore, we build a wide FOV, multi-scale OCT that can produce excellent high- and low-resolution one-to-one mapping volumetric data set. With the HR methods, we can reduce the acquisition of synthetic high-resolution volumetric images by up to four times.

  Preview abstract

Utilizing time-stretching of carrier pulses in nonlinear light microscopy, we've developed a new method to boost signal strength without degrading image quality and signal to noise ratio. In the reports, 80% signal enhancement in second-harmonic generation collagen fiber imaging was achieved with an improved signal to noise ratio. This also increased the image depth from 200 to 220 microns. Offering reduced photo-damage risk and faster imaging, our method is compatible with other enhancement approaches, making it promising for both research and industrial applications with nonlinear laser scanning microscopes.



  Preview abstract

Esophageal cancer is a leading cause of death, especially in East Asia. Taiwan's 2022 mortality statistics revealed it accounted for 25% of all deaths. This study collaborated with Chung-Ho Memorial Hospital, using 2067 early-stage esophageal cancer images. Hyperspectral technology and YOLOv8 models were employed, achieving improved detection. The RGB-WLI model scored 0.85 mAP, 0.86 Sensitivity, 0.88 F1-score, and 0.85 Overall Accuracy. The HSI-NBI model scored 0.87 mAP, 0.88 Sensitivity, 0.89 F1-score, and 0.88 Overall Accuracy. Hyperspectral imaging enhances esophageal cancer detection capabilities.

  Preview abstract

Fluorescence lifetime imaging microscopy (FLIM) technology is a non-destructive detection method known for its numerous advantages, such as providing quantitative measurements and high sensitivity. In recent years, scientists have developed various advanced algorithms for analyzing fluorescence lifetime data, driven by the need to handle larger datasets and reduce analysis times. These algorithms include phasor analysis (PA), maximum likelihood estimate (MLE), and others. This study's primary objective is to comprehensively explain the computational methods employed in phasor analysis and the traditional curve fitting method. Furthermore, it seeks to highlight the differences and distinctions between these two algorithms.

  Preview abstract

This study explores and implements the use of L-curve and U-curve method to determine the regularization parameter to reconstruct diffuse optical images and use some simulated measurement data to observe the image reconstruction. Some synthesized case examples and experimental ones as well are conducted to verify the performance. uses some simulated measurement data to observe the image reconstruction.

  Preview abstract

Revealing the 3D structure neural network play an important role in the studies of neuroscience. However, image contrast and image quality in deep brain degrade due to the scattering of both excitation beam and the emission light. Here, we report the development of a high-resolution 3D imaging platform for intact whole mouse brain. An ultrahigh 0.475μm lateral resolution even at the bottom of a whole intact mouse brain was achieved, corresponding to a 7.3 mm penetration depth in brain tissues.

  Preview abstract

Analysis of wood is generally based on observing its external characteristics to determine the type and quality of the wood. However, it cannot accurately identify the chemical composition and structural characteristics, thus failing to meet the requirements of modern industry for wood quality control. This study utilizes two-photon hyperspectral microscopy as a tool to analyze the two-photon fluorescence spectra of three types of softwoods and nine types of hardwoods. It combines techniques such as linear unmixing, principal component analysis (PCA), and KNN to establish models and explore the possibility of differentiating between softwood and hardwood using two-photon fluorescence spectra.

  Preview abstract

Temporal focusing multiphoton excitation microscopy (TFMPEM) offers faster image acquisition compared to the traditional point-scanning multiphoton excitation microscopy (PSMPEM). Nevertheless, TFMPEM encounters challenges due to scattering in deeper biotissue layers. In this study, we introduce a multi-stage 3D U-Net approach to enhance TFMPEM image quality specifically for shallow layers without extending acquisition time. Furthermore, we propose a network based on ConvLSTM and PhyCell to predict images of deeper layers. This network learns from TFMPEM-restored images and enables precise analysis of deeper biological specimen layers within PSMPEM images.

  Preview abstract

In an aging society, early detection of osteoporosis is imperative due to the increased risk of bone injury associated with low bone mineral density (BMD). Our study introduces an intelligent optical bone densitometer (iOBD) combined with deep learning for estimating BMD in specific body regions. To accurately capture the wrist position, the target region for iOBD measurement, we utilize U-net for automated biomedical image segmentation to generate a mask for the wrist image. We can obtain noise-free images by multiplying the mask with original wrist images, facilitating subsequent deep learning analysis to estimate BMD in multiple body regions accurately.

  Preview abstract

Circulating tumor cells (CTCs) are the key prognostic biomarker for evaluating the treatment response of cancer patients but their rarity in the bloodstream is the major challenge. We demonstrated a label-free liquid crystal (LC) cytosensor, by adopting an aptamer against epithelial cell adhesion molecule (EpCAM) to capture the EpCAM positive cancer cells. The optical biosensing approach resulted in a limit of detection (LOD) of 5 CTCs. Through the dielectric approach, we further improved the LOD to a single CTC. This study manifested the detection of single-cell CTCs in cancer cell-spiked human serum and whole blood using the LC-based dielectric cytosensor.

  Preview abstract

This research proposes a novel human-machine interface (HMI) that automatically identifies types of lung lesions during surgery via combining mobile optical coherence tomography (OCT) and deep learning algorithms. With over 80 % sensitivity and specificity, this technique facilitates rapid histologically graded diagnosis, providing fast information to clinicians and offering a cost-effective approach for early detection and treatment guidance.

  Preview abstract

TBA

  Preview abstract

This study developed a biosensing platform, based on lyotropic chromonic liquid crystal (LCLC), for rapid detections and real-time monitoring of bovine serum albumin, cancer biomarker CA125, and SARS-CoV-2 nucleocapsid protein. At a concentration of 28 wt.% in water, sunset yellow exhibits a distinctive liquid crystal phase. The optical and electrical responses to these protein analytes were measured. The LCLC platform achieves highly sensitive protein detection. Additionally, this platform stands out for its simplicity and cost-efficiency. As such, the LCLC-based system has the potential for clinical sensing and real-time monitoring of viruses, playing a vital role in controlling and preventing outbreaks.

  Preview abstract

This study used non-invasive near-infrared spectroscopy (NIRS) to evaluate the microcirculation of the lower limbs in patients undergoing extracorporeal membrane oxygenation (ECMO). The clinical sequential organ failure assessment (SOFA) score was employed as an illness severity indicator. By integrating real-time blood oxygen data with support vector machine (SVM), we can effectively differentiate disease severity between Veno-Venous (VV) and Veno-Arterial (VA) ECMO patient groups. In addition, combing near-infrared spectroscopy (NIRS) with machine learning allows clinicians to make better ECMO settings and drug dosage adjustments, potentially improving patients' prognosis and outcomes.

  Preview abstract

This study explores biodegradable and biocompatible protein materials (bovine serum albumin and lysozyme) as dielectric layers in n-type organic field-effect transistors (OFETs). The OFETs operate at low-voltage, with threshold voltages around -0.2 V, subthreshold swings of ~0.15 V/decade, and on/off current ratios > 105. Investigating sensitivity to bacteria, Escherichia coli (E. coli) of varying concentrations were introduced into OFET channels. High bacterial concentration (108 CFU/ml) significantly impacted transistor electrical properties. These findings open possibilities for protein-based OFETs in high-concentration bacteria detection and future applications.

  Preview abstract

Inadequate lighting, in particular output with respect to output at ~480nm, has been
correlated with sleep disturbance. Dynamic white lighting in which the output of different colors
of LEDs are modulated during daylight hours to mimic the sun is a promising solution. We have
modeled and implemented a system using only 4 different LEDs to produce white light varying
in correlated color temperature (CCT), intensity, and output at 480nm.

  Preview abstract

Image segmentation in Magnetic Resonance Imaging (MRI) plays a crucial diagnostic role. We applied Attention-UW Net networks for brain lesion segmentation in MRI images. Results shows Attention-UW Net outperforms U-Net (IoU: 0.80 vs. 0.75, precision: 0.86 vs. 0.85, recall: 0.83 vs. 0.70, F1 score: 0.80 vs. 0.81).

  Preview abstract

We evaluated the effect of the He-Ne laser on seeds of ashwagandha and brinjal for improved agronomic traits. Healthy seeds of ashwagandha and brinjal were selected, irradiated with different laser doses, and germinated under in vitro conditions. Lasers stimulated substantial seed germination and morphological traits. The maximum germination rate, seedling length, and carotenoid content were recorded at 25 J groups. Withanolide A and chlorogenic acid content were maximum at 20 J groups compared to the control. The investigation revealed improved plant growth and bioactive metabolite production with laser bio-stimulation for cellular agriculture and industrial production.

  Preview abstract

A novel optical resonant-state with high-quality factor and ultra-sensitivity is presented, which is mainly resonant coupling of the topological interface-states and the optical cavity-modes in one-dimensional photonic systems, namely topological cavity-states (TCS). A key feature of TCS is topological protection and therefore robustness in the presence of structural imperfection. The potential applications of TCS in bio-photonic sensors have also been discussed, including ultra-sensitivity of 2000 nm/RIU and high-Q of 10^9 for detecting analyte solution. TCS in one-dimensional photonic systems not only opens new possibilities for advanced optical resonators, but also provides practical applications in ultra-sensitivity and high-Q, especially bio-photonic sensors.

  Preview abstract

Heren, we synthesized polyaniline-containing galactosylated Ag aggregation-structure nanoparticles (Ag@PGlyco-PSMA ANPs) via an in-situ polymerization of ortho-nitrophenyl-β-galactopyranoside and reduction of Ag ions. The addition of poly(styrene-alt-maleic acid) sodium salt solution (PSMA) hindered the precipitation of Ag@PGlyco-PSMA ANPs and provided exceptional bio-compatibility due to the lowering Ag ion release. Because the Ag@PGlyco-PSMA ANPs have intrinsic polyaniline-based SERS signal, we demonstrated the H2O2 sensing ability in terms of SERS signal decrease. As performing SERS mapping imaging technology, the new SERS probe allowed to screen the cancer cells with high intracellular H2O2 concentration compared with the normal cells.

  Preview abstract

We developed a sugar carbonization reaction of o-nitrophenyl-β-D-galactopyranoside (ONPG) to fabricate glycosyl-/graphene-based nanoparticles (ONPG NPs). As hybridized with iron chlorophyll (Chl/Fe) photosensitizers, the ONPG-Chl/Fe NPs could perform PDT and CDT to kill cancer cells. Because ONPG-Chl/Fe exposed saccharide molecules on the particle surface, enabling to recognize the lectin receptors at the macrophage, the following downstream biologic effects induced M0 macrophage polarization to M1 phenotype. Combined with PDT and CDT to cancer cells, we demonstrated that reprogramming in the generation of M1-type macrophage was improved for the benefit integration of the immunotherapy after sugar-mediated phototherapy.

  Preview abstract

This study simulates the pinhole tunneling effect of the single-photon emission microscope (SPEM) and establishes the imaging models from the simulated point response functions. The models include the flux model, width model and principal angle model. The imaging system matrix is then generated by using the established models. Subsequently, we use the ordered-subset expectation maximization algorithm (OSEM) to reconstruct 3D object images with the corresponding projected images and system matrix. The image reconstruction results validate the established pinhole tunneling model and imaging system matrix.

  Preview abstract

In this study, we analyzed the natural photonic crystal structures comprised in Turquoise-fronted Amazon Parrot feathers. Using UV-Vis spectrophotometry, we validated that, upon pigment removal, the photonic crystal exhibited a significant enhancement in reflectance across the range of 400-900 nm wavelength, surpassing 65%. Notably, it achieved a peak reflectance of 79% at 530 nm. We replicated the photonic crystal found in Turquoise-fronted Amazon Parrot feathers to construct a model through the simulation by Finite-Difference Time-Domain (FDTD) method. Our verification process confirmed that this structure possesses a remarkably high reflectance of 95% within the wavelength of 510 nm to 570 nm.

  Preview abstract

This study created Au@2ATP@ONPG nanoparticles using ONPG and 2ATP, capable of SERS tracking, targeting cancer cells, and stimulating macrophage polarization for immune activation. Sugar-based ONPG polymerization on the gold surface forms a conductive PANI backbone and enhances Raman scattering (SERS) on the gold core, allowing particle concentration detection within cancer cells through SERS intensity. Thus, Au@2ATP@ONPG carried the photosensitizer Ce6, resulting in Au@2ATP@ONPG@Ce6. This biophotonic nanoparticle design could induce PDT effects and transform M2-to-M1 macrophages, prompted by PDT-triggered ROS production upon macrophage binding. This enhanced immune response against cancer cells led to observed PDT-elicited immunotherapy effects.

  Preview abstract

Spontaneously hypertensive rat (SHR) is a well-known animal model of human essential hypertension and the most used model of hypertension and cardiovascular disease so far [1]. We investigated that treatment of hypertensive rats with intravascular laser irradiation of blood (ILIB) [2] improves blood pressure through molecular mechanisms of central cardiovascular regulation. We observed that the administration of 10mW ILIB to SHR rats can reduce the blood pressure of SHR rats, but increase the blood pressure of WKY rats. Next-generation sequencing to analyze the nucleus tractus solitarii found that differentially expressed genes were significantly different between SHR and WKY rats.

  Preview abstract

Extracellular viscosity plays a significant role as a biophysical stimulus, varying within the microenvironment of different tumor types. In this study, we increased the viscosity of the cell culture medium by supplementing it with 0.8% Methylcellulose (MC), raising its viscosity from 0.98 cp to 68.14 cp. We demonstrated how extracellular viscosity regulates cell biomechanical and biochemical properties, including cell spreading, actin and focal adhesion formation, and cell junctions. This, in turn, enhances tumor spheroid formation and promotes the invasion capability of cancer cells from tumor spheroids into surrounding 3D collagen matrices.

  Preview abstract

Intravascular laser irradiation of blood (ILIB) is a therapeutic technique that was initially developed for cardiovascular diseases and represents a novel application of lasers in medicine [1]. We aim to investigate these changes and determine the molecular mechanisms involved in post-stroke rehabilitation patients. Our demonstrated differential gene expression before and after ILIB treatment in ischemic stroke patients. These genes were significantly enriched in pathways related to TNF signaling, IL-17 signaling, cancer misregulation, and osteoclast differentiation. Furthermore, gene ontology analyses revealed significant enrichment in biological processes, cellular components, and molecular functions related to immune response, hemopoiesis, and oxidoreductase activity, among others.

  Preview abstract

Cancer cells often re-program the metabolism to promote their growth and strengthen resistance to chemotherapies. The formation of lipid droplets in cancer cells is one of the indications of this alternation. Therefore, to identify the quantity and type of lipid in the lipid droplets of cancer cells is critical. In this work, the dark-field microscopy is combined with Raman spectroscopy to identify the lipid droplets in liver cancer cells. The primitive results show that the Raman identification may be used to clarify the relationship between external stimulus and lipid droplets.

  Preview abstract