Thin flexible photoacoustic endoscopic probe with a distal-driven micro-step motor for pump-probe-based high-specific molecular imaging.

Conventional photoacoustic endoscopy (PAE) is mostly for structural imaging, and its molecular imaging ability is quite limited. In this work, we address this issue and present the development of a flexible acoustic-resolution-based photoacoustic endoscopic (AR-PAE) probe with an outer diameter of 8 mm. This probe is driven by a micro-step motor at the distal end, enabling flexible and precise angular step control to synchronize with the optical parametric oscillator (OPO) lasers. This probe retains the high spatial resolution, high penetration depth, and spectroscopic imaging ability of conventional AR-PAE. Moreover, it is capable for background-free high-specific photoacoustic molecular imaging with a novel pump-probe detection technique, as demonstrated by the distribution visualizing of the FDA approved contrast agent methylene blue (MB) in an ex-vivo pig ileum. This proposed method represents an important technical advancement in multimodal PAE, and can potentially make considerable contributions across various biomedical fields.

Dynamic monitoring of oxygen partial pressure in photodynamic therapy using pump-probe-based photoacoustic tomography.

Pump-probe-based photoacoustic tomography (PP-PAT) is an innovative and promising molecular imaging technique. In this study, we utilized PP-PAT for the first time, to the best of our knowledge, to monitor the dynamics of oxygen partial pressure (pO2) within murine tumors during photodynamic therapy (PDT) with methylene blue (MB). We developed, to our knowledge, a novel two-step fitting method to simultaneously map both the pO2 and the MB concentrations and implemented it with mexCuda to accelerate the pixel-wise-based calculation. The results demonstrated a penetration depth of up to 5 mm and revealed a significant decrease in pO2 during the PDT process, consistent with existing research findings. This study suggests that PP-PAT has the potential to become a valuable tool for intraoperative monitoring of PDT, thereby enhancing therapeutic efficacy.

Development of a novel lncRNA-derived immune gene score using machine learning-based ensembles for predicting the survival of HCC.

BACKGROUND: Long noncoding RNAs (lncRNAs) are implicated in the tumor immunology of hepatocellular carcinoma (HCC). METHODS: HCC mRNA and lncRNA expression profiles were used to extract immune-related genes with the ImmPort database, and immune-related lncRNAs with the ImmLnc algorithm. The MOVICS package was used to cluster immune-related mRNA, immune-related lncRNA, gene mutation and methylation data on HCC from the TCGA. GEO and ICGC datasets were used to validate the model. Data from single-cell sequencing was used to determine the expression of genes from the model in various immune cell types. RESULTS: With this model, the area under the curve (AUC) for 1-, 3- and 5-year survival of HCC patients was 0.862, 0.869 and 0.912, respectively. Single-cell sequencing showed EREG was significantly expressed in a variety of immune cell types. Knockdown of the EREG target gene resulted in significant anti-apoptosis, pro-proliferation and pro-migration effects in HepG2 and HUH7 cells. Moreover, serum and liver tissue EREG levels in HCC patients were significantly higher than those of healthy control patients. CONCLUSION: We built a prognostic model with good accuracy for predicting HCC patient survival. EREG is a potential immunotherapeutic target and a promising prognostic biomarker.

Fenton-Like Reaction: Recent Advances and New Trends.

The Fenton reaction refers to the reaction in which ferrous ions (Fe2+ ) produce hydroxyl radicals and other reactive oxidizing substances by decomposing hydrogen peroxide (H2 O2 ). This paper reviews the mechanism, application system, and materials employed in the Fenton reaction including conventional homogeneous and non-homogeneous Fenton reactions as well as photo-, electrically-, ultrasonically-, and piezoelectrically-triggered Fenton reactions, and summarizes the applications in the degradation of soil oil pollutions, landfill leachate, textile wastewater, and antibiotics from a practical point of view. The mineralization paths of typical pollutant are elucidated with relevant case studies. The paper concludes with a summary and outlook of the further development of Fenton-like reactions.

The Landscape of m6A Regulators in Multiple Brain Regions of Alzheimer's Disease.

Alzheimer's disease research has been conducted for many years, yet no effective cure methods have been found. N6-methyladenosine (m6A) RNA methylation, an essential post-transcriptional regulation mechanism, has been discovered to affect essential neurobiological processes, such as brain cell development and aging, which are closely related to neurodegenerative diseases such as Alzheimer's disease. The relationship between Alzheimer's disease and the m6A mechanism still needs further investigation. Our work evaluated the alteration profile of m6A regulators and their influences on Alzheimer's disease in 4 brain regions: the postcentral gyrus, superior frontal gyrus, hippocampus, and entorhinal cortex. We found that the expression levels of the m6A regulators FTO, ELAVL1, and YTHDF2 were altered in Alzheimer's disease and were related to pathological development and cognitive levels. We also assessed AD-related biological processes influenced by m6A regulators via GSEA and GSVA method. Biological Processes Gene Ontology terms including memory, cognition, and synapse-signaling were found to potentially be affected by m6A regulators in AD. We also found different m6A modification patterns in AD samples among different brain regions, mainly due to differences in m6A readers. Finally, we further evaluated the importance of AD-related regulators based on the WGCNA method, assessed their potential targets based on correlation relationships, and constructed diagnostic models in 3 of all 4 regions using hub regulators, including FTO, YTHDC1, YTHDC2, etc., and their potential targets. This work aims to provide a reference for the follow-up study of m6A and Alzheimer's disease.

In vivo photothermal therapy monitored by multi-position calibrated photoacoustic thermometer.

With the ability of monitoring both temperature and photothermal agents, the photoacoustic (PA) imaging is a promising guiding tool for the photothermal therapy (PTT). The calibration line which depicts the relative variation of PA amplitude with the temperature should be obtained before using PA thermometer. In existing study, a calibration line was generated based on the data from one spatial position, and used in the whole region of interesting (ROI). However, the generalization of this calibration line in ROI was not verified, especially for ROI with heterogeneous tissues. Moreover, the relationship between the distributions of photothermal agents and effective treatment area is not clear, hindering using photothermal agents' distribution to optimize the administration-therapy interval. In this study, the distribution of effective photothermal agents and temperature in subcutaneously transplanted tumor mouse models were continuously monitored by 3D photoacoustic/ ultrasonic dual-modality imaging in 8 h after administration. With multiple micro-temperature probes in tumor and surrounding normal tissue, the PA thermometer was calibrated and evaluated at multiple spatial positions for the first time. The generalization in homologous tissue and tissue specificity in heterogeneous tissues of the PA thermometer calibration line were verified. Our study not only validated the effectivity of PA thermometer by proving the generalization of calibration line, but also removes a major obstacle that prevents applying the PA thermometer to a heterogeneous tissues ROI. The positive correlation between the proportion of effective treatment area and the proportion of effective photothermal agent area in the tumor was observed. Since the latter can be monitored with fast PA imaging, PA imaging can be employed as a convenient tool for seeking optimal administration-treatment interval.

A Testlet Diagnostic Classification Model with Attribute Hierarchies.

In this article, a testlet hierarchical diagnostic classification model (TH-DCM) was introduced to take both attribute hierarchies and item bundles into account. The expectation-maximization algorithm with an analytic dimension reduction technique was used for parameter estimation. A simulation study was conducted to assess the parameter recovery of the proposed model under varied conditions, and to compare TH-DCM with testlet higher-order CDM (THO-DCM; Hansen, M. (2013). Hierarchical item response models for cognitive diagnosis (Unpublished doctoral dissertation). UCLA; Zhan, P., Li, X., Wang, W.-C., Bian, Y., & Wang, L. (2015). The multidimensional testlet-effect cognitive diagnostic models. Acta Psychologica Sinica, 47(5), 689. https://doi.org/10.3724/SP.J.1041.2015.00689). Results showed that (1) ignoring large testlet effects worsened parameter recovery, (2) DCMs assuming equal testlet effects within each testlet performed as well as the testlet model assuming unequal testlet effects under most conditions, (3) misspecifications in joint attribute distribution had an differential impact on parameter recovery, and (4) THO-DCM seems to be a robust alternative to TH-DCM under some hierarchical structures. A set of real data was also analyzed for illustration.

Automatic Classification of Histopathology Images across Multiple Cancers Based on Heterogeneous Transfer Learning.

BACKGROUND: Current artificial intelligence (AI) in histopathology typically specializes on a single task, resulting in a heavy workload of collecting and labeling a sufficient number of images for each type of cancer. Heterogeneous transfer learning (HTL) is expected to alleviate the data bottlenecks and establish models with performance comparable to supervised learning (SL). METHODS: An accurate source domain model was trained using 28,634 colorectal patches. Additionally, 1000 sentinel lymph node patches and 1008 breast patches were used to train two target domain models. The feature distribution difference between sentinel lymph node metastasis or breast cancer and CRC was reduced by heterogeneous domain adaptation, and the maximum mean difference between subdomains was used for knowledge transfer to achieve accurate classification across multiple cancers. RESULT: HTL on 1000 sentinel lymph node patches (L-HTL-1000) outperforms SL on 1000 sentinel lymph node patches (L-SL-1-1000) (average area under the curve (AUC) and standard deviation of L-HTL-1000 vs. L-SL-1-1000: 0.949 ± 0.004 vs. 0.931 ± 0.008, p value = 0.008). There is no significant difference between L-HTL-1000 and SL on 7104 patches (L-SL-2-7104) (0.949 ± 0.004 vs. 0.948 ± 0.008, p value = 0.742). Similar results are observed for breast cancer. B-HTL-1008 vs. B-SL-1-1008: 0.962 ± 0.017 vs. 0.943 ± 0.018, p value = 0.008; B-HTL-1008 vs. B-SL-2-5232: 0.962 ± 0.017 vs. 0.951 ± 0.023, p value = 0.148. CONCLUSIONS: HTL is capable of building accurate AI models for similar cancers using a small amount of data based on a large dataset for a certain type of cancer. HTL holds great promise for accelerating the development of AI in histopathology.

Spectroscopic photoacoustic/ultrasound/optical-microscopic multimodal intrarectal endoscopy for detection of centimeter-scale deep lesions.

The inadequacy of existing colorectal imaging tools has significantly obstructed the efficient detection of colorectal cancer. To address this issue, this work presents the cross-scale endoscopic imaging of rectal tumors with a combined photoacoustic/ultrasound tomography system and wide-field optical microscopy. This multimodal system combines the merits of centimeter-scale deep penetration, multi-spectral imaging, cross-scale imaging ability, low system cost, and 360° view in a single modality. Results indicated that the proposed system could reliably depict the location of the cancer invasion depth spectroscopically with indocyanine green The tumor angiogenesis can be well identified in the wide-field optical imaging mode, which helps to localize the tumors and guide the following photoacoustic/ultrasound scan. This work may facilitate the accurate characterization of colorectal cancer and promote the clinical translation of photoacoustic-based colorectal endoscopy.

Microglia-Mediated Neurovascular Unit Dysfunction in Alzheimer's Disease.

The neurovascular unit (NVU) is involved in the pathological changes in Alzheimer's disease (AD). The NVU is a structural and functional complex that maintains microenvironmental homeostasis and metabolic balance in the central nervous system. As one of the most important components of the NVU, microglia not only induce blood-brain barrier breakdown by promoting neuroinflammation, the infiltration of peripheral white blood cells and oxidative stress but also mediate neurovascular uncoupling by inducing mitochondrial dysfunction in neurons, abnormal contraction of cerebral vessels, and pericyte loss in AD. In addition, microglia-mediated dysfunction of cellular components in the NVU, such as astrocytes and pericytes, can destroy the integrity of the NVU and lead to NVU impairment. Therefore, we review the mechanisms of microglia-mediated NVU dysfunction in AD. Furthermore, existing therapeutic advancements aimed at restoring the function of microglia and the NVU in AD are discussed. Finally, we predict the role of pericytes in microglia-mediated NVU dysfunction in AD is the hotspot in the future.

On-the-fly parameter estimation based on item response theory in item-based adaptive learning systems.

Online learning systems are able to offer customized content catered to individual learner's needs, and have seen growing interest from industry and academia alike in recent years. In contrast to the traditional computerized adaptive testing setting, which has a well-calibrated item bank with new items added periodically, the online learning system has two unique features: (1) the number of items is large, and they have likely not gone through costly field testing for item calibration; and (2) the individual's ability may change as a result of learning. The Elo rating system has been recognized as an effective method for fast updating of item and person parameters in online learning systems to enable personalized learning. However, the updating parameter in Elo has to be tuned post hoc, and Elo is only suitable for the Rasch model. In this paper, we propose the use of a moment-matching Bayesian update algorithm to estimate item and person parameters on the fly. With sequentially updated item and person parameters, a modified maximum posterior weighted information criterion (MPWI) is proposed to adaptively assign items to individuals. The Bayesian updated algorithm along with MPWI is validated in a simulated multiple-session online learning setting, and the results show that the new combo can achieve fast and reasonably accurate parameter estimations that are comparable to random selection, match-difficulty selection, and traditional online calibration. Moreover, the combo can still function reasonably well with as low as 20% of items being pre-calibrated in the item bank.

New insights into mechanisms of berberine in alleviating reproductive disorders of polycystic ovary syndrome: Anti-inflammatory properties.

Polycystic ovary syndrome (PCOS) is a complex reproductive disorder that seriously harms female reproductive health and decreases quality of life. Although spontaneous or assisted ovulation occurs, women with PCOS suffer from poor-quality oocytes and embryos and lower fertilization and final pregnancy rates. Therefore, it is urgent to identify new pathological mechanisms and discover the underlying therapeutic targets for reproductive disorders associated with PCOS. Berberine, one of the famous traditional Chinese medicines, has been shown to improve ovulation and live birth rates in women with PCOS. The effects of berberine on insulin resistance and abnormal glucose and lipid metabolism for restoring the reproductive health of women with PCOS are well recognized and have been widely studied, but much less attention has been given to its anti-inflammatory properties. Chronic low-grade inflammation is the unifying feature of PCOS and may contribute to reproductive disorders in PCOS. Berberine can modulate the inflammatory state of the ovaries and uterus in PCOS. The anti-inflammatory properties of berberine may provide new insight into the mechanisms by which berberine alleviates reproductive disorders associated with PCOS. Here, we summarized the most recent insights into the anti-inflammatory properties of berberine in PCOS reproductive disorders to inspire researchers to pursue new study directions involving berberine.

In vitro transdifferentiated signatures of goat preadipocytes into mammary epithelial cells revealed by DNA methylation and transcriptome profiling.

During mammary development, the transdifferentiation of mammary preadipocytes is one of the important sources for lactating mammary epithelial cells (MECs). However, there is limited knowledge about the mechanisms of dynamic regulation of transcriptome and genome-wide DNA methylation in the preadipocyte transdifferentiation process. Here, to gain more insight into these mechanisms, preadipocytes were isolated from adipose tissues from around the goat mammary gland (GM-preadipocytes). The GM-preadipocytes were cultured on Matrigel in conditioned media made from goat MECs to induce GM-preadipocyte-to-MEC transdifferentiation. The transdifferentiated GM-preadipocytes showed high abundance of keratin 18, which is a marker protein of MECs, and formed mammary acinar-like structures after 8 days of induction. Then, we performed transcriptome and DNA methylome profiling of the GM-preadipocytes and transdifferentiated GM-preadipocytes, respectively, and the differentially expressed genes and differentially methylated genes that play underlying roles in the process of transdifferentiation were obtained. Subsequently, we identified the candidate transcription factors in regulating the GM-preadipocyte-to-MEC transdifferentiation by transcription factor-binding motif enrichment analysis of differentially expressed genes and differentially methylated genes. Meanwhile, the secretory proteome of GM-preadipocytes cultured in conditioned media was also detected. By integrating the transcriptome, DNA methylome, and proteome, three candidate genes, four proteins, and several epigenetic regulatory axes were further identified, which are involved in regulation of the cell cycle, cell polarity establishment, cell adhesion, cell reprogramming, and adipocyte plasticity. These findings provide novel insights into the molecular mechanism of preadipocyte transdifferentiation and mammary development.

Transient triplet differential-based photoacoustic lifetime imaging with an automatic interleaved data acquisition method for improved scanning speed and stability.

Transient triplet differential (TTD) based photoacoustic lifetime (PALT) imaging provides valuable means for background-free molecular imaging and mapping of the oxygen partial pressure (pO2) in deep tissues. However, the broad application of this method is hindered by its long scanning time, poor accuracy, and low stability. This is mainly because most PALT systems execute the three data acquisition sequences separately without automatic control and neglect the long-time fluctuation of the laser output. In this work, we have proposed a novel automatic interleaved data acquisition method for PALT. This new method not only improved the scanning efficiency but also eliminated the long-time fluctuations of laser pulse energy. Results show that this new method can significantly improve the system's stability and help reduce the scanning time. With this new method, we obtained the 3D background-free TTD images for the first time. We also observed distinct hypoxia inside the tumor due to the high metabolic rate of cancer cells, demonstrating the high reliability of our proposed method. The proposed method in this work can significantly promote the application of PALT imaging in biomedical studies.

Item Selection With Collaborative Filtering in On-The-Fly Multistage Adaptive Testing.

An important design feature in the implementation of both computerized adaptive testing and multistage adaptive testing is the use of an appropriate method for item selection. The item selection method is expected to select the most optimal items depending on the examinees' ability level while considering other design features (e.g., item exposure and item bank utilization). This study introduced collaborative filtering (CF) as a new method for item selection in the on-the-fly assembled multistage adaptive testing framework. The user-based CF (UBCF) and item-based CF (IBCF) methods were compared to the maximum Fisher information method based on the accuracy of ability estimation, item exposure rates, and item bank utilization under different test conditions (e.g., item bank size, test length, and the sparseness of training data). The simulation results indicated that the UBCF method outperformed the traditional item selection methods regarding measurement accuracy. Also, the IBCF method showed the most superior performance in terms of item bank utilization. Limitations of the current study and the directions for future research are discussed.

Acoustic-resolution-based spectroscopic photoacoustic endoscopy towards molecular imaging in deep tissues.

Due to many technical difficulties, the study of molecular photoacoustic endoscopic (PAE) imaging in deep tissues is limited. In this work, we have set up a multimodal acoustic-resolution-based PAE (AR-PAE) system to image the rabbit rectum and preliminarily explored the potential of molecular PAE for deep-seated targets in proof-of-concept. We developed an improved back-projection (IBP) algorithm for focused detection over the centimeter-scale imaging depth. We also developed a deep-learning-based algorithm to remove the electrical noise from the step motor to prevent data averaging for reduced scanning time. We injected a dose of indocyanine green (ICG) near the rabbit rectum and compared 2D and 3D photoacoustic/ultrasound (PA/US) images at different wavelengths. We proposed incorporating a small camera to guide the slow PA/US endoscopic scan. Results show that this system has achieved a lateral resolution of about 0.77/0.65 mm for PA/US images with a signal-to-noise ratio (SNR) of 25/38 dB at an imaging depth of 1.4 cm. We found that the rectum wall and the ICG can be well distinguished spectroscopically. Results also show that the PA images at 532 nm have higher signal intensity and reflection artifacts from pelvic tendons and bones than those at longer wavelengths such as 800 nm. The proposed methods and the intuitive findings in this work may guide and promote the development of high-penetration molecular PAE.

Role of adiponectin in osteoarthritis.

Osteoarthritis (OA) is a widespread and most common joint disease which leads to social cost increasing accompany with aging population. Surgery is often the final treatment option. The major progression of OA includes cartilage degradation caused by chondrocytes metabolism imbalance. So, the molecular mechanisms of action in chondrocytes may provide insights into treatment methods for OA. Adiponectin is an adipokine with many biological functions in the cell metabolism. Numerous studies have illustrated that adiponectin has diverse biological effects, such as inhibition of cell apoptosis. It regulates various functions in different organs, including muscle, adipose tissue, brain, and bone, and regulates skeletal homeostasis. However, the relationship between adiponectin and cell death in the progression of OA needs further investigation. We elaborate the structure and function and the effect of adiponectin and state the correlation and intersection between adiponectin, autophagy, inflammation, and OA. From the perspective of oxidative stress, apoptosis, pyroptosis, and autophagy, we discuss the possible association between adiponectin, chondrocyte metabolism, and inflammatory factor efforts in OA. What's more, we summarize the possible treatment methods, including the use of adiponectin as a drug target, and highlight the potential future mechanistic research. In this review, we summarize the molecular pathways and mechanisms of action of adiponectin in chondrocyte inflammation and death and the pathogenesis of OA. We also review the research on adiponectin as a target for treating OA. These studies provide a novel perspective to explore more effective treatment options considering the complex interrelationship between inflammation and metabolism in OA.

Regularized Variational Estimation for Exploratory Item Factor Analysis.

Item factor analysis (IFA), also known as Multidimensional Item Response Theory (MIRT), is a general framework for specifying the functional relationship between respondents' multiple latent traits and their responses to assessment items. The key element in MIRT is the relationship between the items and the latent traits, so-called item factor loading structure. The correct specification of this loading structure is crucial for accurate calibration of item parameters and recovery of individual latent traits. This paper proposes a regularized Gaussian Variational Expectation Maximization (GVEM) algorithm to efficiently infer item factor loading structure directly from data. The main idea is to impose an adaptive [Formula: see text]-type penalty to the variational lower bound of the likelihood to shrink certain loadings to 0. This new algorithm takes advantage of the computational efficiency of GVEM algorithm and is suitable for high-dimensional MIRT applications. Simulation studies show that the proposed method accurately recovers the loading structure and is computationally efficient. The new method is also illustrated using the National Education Longitudinal Study of 1988 (NELS:88) mathematics and science assessment data.

In-vivo imaging of melanoma with simultaneous dual-wavelength acoustic-resolution-based photoacoustic/ultrasound microscopy.

Melanoma is a common, highly fatal skin cancer. Photoacoustic imaging can achieve highly sensitive and high-contrast detection of melanin molecules in tissues, also inheriting the high penetration depth and high spatial resolution characteristics of ultrasound imaging, thus it is a very promising non-invasive diagnostic tool for early melanoma. In this work, we built an acoustic-resolution-based photoacoustic microscopy system, using 1064 nm/532 nm pulsed light to observe melanoma in the back of a mouse with simultaneous photoacoustic/ultrasound imaging. Through the fusion of multi-modal images, accurate positioning of melanoma and its surrounding normal tissues were realized. This work will further promote the application of photoacoustic imaging in the clinical diagnosis of early melanoma.

Approximate back-projection method for improving lateral resolution in circular-scanning-based photoacoustic tomography.

PURPOSE: In circular-scanning-based photoacoustic tomography (PAT), the effect of finite transducer aperture has not been effectively resolved. The goal of this paper is to propose a practical reconstruction method that accounts for the finite transducer aperture to improve the lateral resolution. METHODS: We for the first time propose to calculate the spatial-temporal response (STR) of the employed finite-sized transducer in a forward model, and then compensate the time delay and the directional sensitivity of the transducer in the framework of the back-projection method. Both simulation and phantom experiments were carried out to evaluate the lateral resolution improvement with the proposed method. The performance of this new method for imaging complicated targets was also assessed by calculating the mean image gradient. RESULTS: Simulation results showed that with this new method the lateral resolution for off-center targets can be as good as that for the center targets. Phantom experimental results showed that this new method can improve the lateral resolution more than two times for a point target about 5 mm far from the rotation center. Phantom experimental results also showed that many blurred fine structures of a piece of leaf veins at the off-center regions were well restored with the new method, and the mean image gradient improved about 1.3 times. CONCLUSION: The proposed new method can effectively account for the effect of finite transducer aperture for circular-scanning-based PAT in homogenous acoustic media. This new method also features its robustness and computational efficiency, so that it is a worthy replacement to the conventional back-projection algorithm in circular-scanning-based PAT. This new method can be of great importance to the design of circular-scanning or spherical-scanning-based PAT systems.