Advancements in fluorescence lifetime imaging microscopy Instrumentation: Towards high speed and 3D.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging tool offering molecular specific insights into samples through the measurement of fluorescence decay time, with promising applications in diverse research fields. However, to acquire two-dimensional lifetime images, conventional FLIM relies on extensive scanning in both the spatial and temporal domain, resulting in much slower acquisition rates compared to intensity-based approaches. This problem is further magnified in three-dimensional imaging, as it necessitates additional scanning along the depth axis. Recent advancements have aimed to enhance the speed and three-dimensional imaging capabilities of FLIM. This review explores the progress made in addressing these challenges and discusses potential directions for future developments in FLIM instrumentation.

Improving Rebar Twist Prediction Exploiting Unified-Channel Attention-Based Image Restoration and Regression Techniques.

Recent research has made significant progress in automated unmanned systems utilizing Artificial Intelligence (AI)-based image processing to optimize the rebar manufacturing process and minimize defects such as twisting during production. Despite various studies, including those employing data augmentation through Generative Adversarial Networks (GANs), the performance of rebar twist prediction has been limited due to image quality degradation caused by environmental noise, such as insufficient image quality and inconsistent lighting conditions in rebar processing environments. To address these challenges, we propose a novel approach for real-time rebar twist prediction in manufacturing processes. Our method involves restoring low-quality grayscale images to high resolution and employing an object detection model to identify and track rebar endpoints. We then apply regression analysis to the coordinates obtained from the bounding boxes to estimate the error rate of the rebar endpoint positions, thereby determining the occurrence of twisting. To achieve this, we first developed a Unified-Channel Attention (UCA) module that is robust to changes in intensity and contrast for grayscale images. The UCA can be integrated into image restoration models to more accurately detect rebar endpoint characteristics in object detection models. Furthermore, we introduce a method for predicting the future positions of rebar endpoints using various linear and non-linear regression models. The predicted positions are used to calculate the error rate in rebar endpoint locations, determined by the distance between the actual and predicted positions, which is then used to classify the presence of rebar twisting. Our experimental results demonstrate that integrating the UCA module with our image restoration model significantly improved existing models in Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) metrics. Moreover, employing regression models to predict future rebar endpoint positions enhances the F1 score for twist prediction. As a result, our approach offers a practical solution for rapid defect detection in rebar manufacturing processes.

Microglia Gravitate toward Amyloid Plaques Surrounded by Externalized Phosphatidylserine via TREM2.

Microglia play a crucial role in synaptic elimination by engulfing dystrophic neurons via triggering receptors expressed on myeloid cells 2 (TREM2). They are also involved in the clearance of beta-amyloid (Aß) plaques in Alzheimer's disease (AD); nonetheless, the driving force behind TREM2-mediated phagocytosis of beta-amyloid (Aß) plaques remains unknown. Here, using advanced 2D/3D/4D co-culture systems with loss-of-function mutations in TREM2 (a frameshift mutation engineered in exon 2) brain organoids/microglia/assembloids, it is identified that the clearance of Aß via TREM2 is accelerated by externalized phosphatidylserine (ePtdSer) generated from dystrophic neurons surrounding the Aß plaques. Moreover, it is investigated whether microglia from both sporadic (CRISPR-Cas9-based APOE4 lines) and familial (APPNL-G-F/MAPT double knock-in mice) AD models show reduced levels of TREM2 and lack of phagocytic activity toward ePtdSer-positive Aß plaques. Herein new insight is provided into TREM2-dependent microglial phagocytosis of Aß plaques in the context of the presence of ePtdSer during AD progression.

Electrophysiological insights with brain organoid models: a brief review.

Brain organoid is a three-dimensional (3D) tissue derived from stem cells such as induced pluripotent stem cells (iPSCs) embryonic stem cells (ESCs) that reflect real human brain structure. It replicates the complexity and development of the human brain, enabling studies of the human brain in vitro. With emerging technologies, its application is various, including disease modeling and drug screening. A variety of experimental methods have been used to study structural and molecular characteristics of brain organoids. However, electrophysiological analysis is necessary to understand their functional characteristics and complexity. Although electrophysiological approaches have rapidly advanced for monolayered cells, there are some limitations in studying electrophysiological and neural network characteristics due to the lack of 3D characteristics. Herein, electrophysiological measurement and analytical methods related to neural complexity and 3D characteristics of brain organoids are reviewed. Overall, electrophysiological understanding of brain organoids allows us to overcome limitations of monolayer in vitro cell culture models, providing deep insights into the neural network complex of the real human brain and new ways of disease modeling. [BMB Reports 2024; 57(7): 311-317].

Guidelines for Manufacturing and Application of Organoids: Brain.

This study offers a comprehensive overview of brain organoids for researchers. It combines expert opinions with technical summaries on organoid definitions, characteristics, culture methods, and quality control. This approach aims to enhance the utilization of brain organoids in research. Brain organoids, as three-dimensional human cell models mimicking the nervous system, hold immense promise for studying the human brain. They offer advantages over traditional methods, replicating anatomical structures, physiological features, and complex neuronal networks. Additionally, brain organoids can model nervous system development and interactions between cell types and the microenvironment. By providing a foundation for utilizing the most human-relevant tissue models, this work empowers researchers to overcome limitations of two-dimensional cultures and conduct advanced disease modeling research.

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. METHODS AND RESULTS: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated. CONCLUSION: This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

Direct interrogation of context-dependent GPCR activity with a universal biosensor platform.

G protein-coupled receptors (GPCRs) are the largest family of druggable proteins encoded in the human genome, but progress in understanding and targeting them is hindered by the lack of tools to reliably measure their nuanced behavior in physiologically relevant contexts. Here, we developed a collection of compact ONE vector G-protein Optical (ONE-GO) biosensor constructs as a scalable platform that can be conveniently deployed to measure G-protein activation by virtually any GPCR with high fidelity even when expressed endogenously in primary cells. By characterizing dozens of GPCRs across many cell types like primary cardiovascular cells or neurons, we revealed insights into the molecular basis for G-protein coupling selectivity of GPCRs, pharmacogenomic profiles of anti-psychotics on naturally occurring GPCR variants, and G-protein subtype signaling bias by endogenous GPCRs depending on cell type or upon inducing disease-like states. In summary, this open-source platform makes the direct interrogation of context-dependent GPCR activity broadly accessible.

Augmented interpretation of HER2, ER, and PR in breast cancer by artificial intelligence analyzer: enhancing interobserver agreement through a reader study of 201 cases.

BACKGROUND: Accurate classification of breast cancer molecular subtypes is crucial in determining treatment strategies and predicting clinical outcomes. This classification largely depends on the assessment of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) status. However, variability in interpretation among pathologists pose challenges to the accuracy of this classification. This study evaluates the role of artificial intelligence (AI) in enhancing the consistency of these evaluations. METHODS: AI-powered HER2 and ER/PR analyzers, consisting of cell and tissue models, were developed using 1,259 HER2, 744 ER, and 466 PR-stained immunohistochemistry (IHC) whole-slide images of breast cancer. External validation cohort comprising HER2, ER, and PR IHCs of 201 breast cancer cases were analyzed with these AI-powered analyzers. Three board-certified pathologists independently assessed these cases without AI annotation. Then, cases with differing interpretations between pathologists and the AI analyzer were revisited with AI assistance, focusing on evaluating the influence of AI assistance on the concordance among pathologists during the revised evaluation compared to the initial assessment. RESULTS: Reevaluation was required in 61 (30.3%), 42 (20.9%), and 80 (39.8%) of HER2, in 15 (7.5%), 17 (8.5%), and 11 (5.5%) of ER, and in 26 (12.9%), 24 (11.9%), and 28 (13.9%) of PR evaluations by the pathologists, respectively. Compared to initial interpretations, the assistance of AI led to a notable increase in the agreement among three pathologists on the status of HER2 (from 49.3 to 74.1%, p < 0.001), ER (from 93.0 to 96.5%, p = 0.096), and PR (from 84.6 to 91.5%, p = 0.006). This improvement was especially evident in cases of HER2 2+ and 1+, where the concordance significantly increased from 46.2 to 68.4% and from 26.5 to 70.7%, respectively. Consequently, a refinement in the classification of breast cancer molecular subtypes (from 58.2 to 78.6%, p < 0.001) was achieved with AI assistance. CONCLUSIONS: This study underscores the significant role of AI analyzers in improving pathologists' concordance in the classification of breast cancer molecular subtypes.

Direct interrogation of context-dependent GPCR activity with a universal biosensor platform.

G protein-coupled receptors (GPCRs) are the largest family of druggable proteins in the human genome, but progress in understanding and targeting them is hindered by the lack of tools to reliably measure their nuanced behavior in physiologically-relevant contexts. Here, we developed a collection of compact ONE vector G-protein Optical (ONE-GO) biosensor constructs as a scalable platform that can be conveniently deployed to measure G-protein activation by virtually any GPCR with high fidelity even when expressed endogenously in primary cells. By characterizing dozens of GPCRs across many cell types like primary cardiovascular cells or neurons, we revealed new insights into the molecular basis for G-protein coupling selectivity of GPCRs, pharmacogenomic profiles of anti-psychotics on naturally-occurring GPCR variants, and G-protein subtype signaling bias by endogenous GPCRs depending on cell type or upon inducing disease-like states. In summary, this open-source platform makes the direct interrogation of context-dependent GPCR activity broadly accessible.

Caffeine Produced in Rice Plants Provides Tolerance to Water-Deficit Stress.

Exogenous or endogenous caffeine application confers resistance to diverse biotic stresses in plants. In this study, we demonstrate that endogenous caffeine in caffeine-producing rice (CPR) increases tolerance even to abiotic stresses such as water deficit. Caffeine produced by CPR plants influences the cytosolic Ca2+ ion concentration gradient. We focused on examining the expression of Ca2+-dependent protein kinase genes, a subset of the numerous proteins engaged in abiotic stress signaling. Under normal conditions, CPR plants exhibited increased expressions of seven OsCPKs (OsCPK10, OsCPK12, OsCPK21, OsCPK25, OsCPK26, OsCPK30, and OsCPK31) and biochemical modifications, including antioxidant enzyme (superoxide dismutase, catalase, peroxidase, and ascorbate peroxidase) activity and non-enzymatic antioxidant (ascorbic acid) content. CPR plants exhibited more pronounced gene expression changes and biochemical alterations in response to water-deficit stress. CPR plants revealed increased expressions of 16 OsCPKs (OsCPK1, OsCPK2, OsCPK3, OsCPK4, OsCPK5, OsCPK6, OsCPK9, OsCPK10, OsCPK11, OsCPK12, OsCPK14, OsCPK16, OsCPK18, OsCPK22, OsCPK24, and OsCPK25) and 8 genes (OsbZIP72, OsLEA25, OsNHX1, OsRab16d, OsDREB2B, OsNAC45, OsP5CS, and OsRSUS1) encoding factors related to abiotic stress tolerance. The activity of antioxidant enzymes increased, and non-enzymatic antioxidants accumulated. In addition, a decrease in reactive oxygen species, an accumulation of malondialdehyde, and physiological alterations such as the inhibition of chlorophyll degradation and the protection of photosynthetic machinery were observed. Our results suggest that caffeine is a natural chemical that increases the potential ability of rice to cope with water-deficit stress and provides robust resistance by activating a rapid and comprehensive resistance mechanism in the case of water-deficit stress. The discovery, furthermore, presents a new approach for enhancing crop tolerance to abiotic stress, including water deficit, via the utilization of a specific natural agent.

The QPLEX™ Plus Assay Kit for the Early Clinical Diagnosis of Alzheimer's Disease.

We recently developed a multiplex diagnostic kit, QPLEX™ Alz plus assay kit, which captures amyloid-ß1-40, galectin-3 binding protein, angiotensin-converting enzyme, and periostin simultaneously using microliters of peripheral blood and utilizes an optimized algorithm for screening Alzheimer's disease (AD) by correlating with cerebral amyloid deposition. Owing to the demand for early AD detection, we investigate the potential of our kit for the early clinical diagnosis of AD. A total of 1395 participants were recruited, and their blood samples were analyzed with the QPLEX™ kit. The average of QPLEX™ algorithm values in each group increased gradually in the order of the clinical progression continuum of AD: cognitively normal (0.382 ± 0.150), subjective cognitive decline (0.452 ± 0.130), mild cognitive impairment (0.484 ± 0.129), and AD (0.513 ± 0.136). The algorithm values between each group showed statistically significant differences among groups divided by Mini-Mental State Examination and Clinical Dementia Rating. The QPLEX™ algorithm values could be used to distinguish the clinical continuum of AD or cognitive function. Because blood-based diagnosis is more accessible, convenient, and cost- and time-effective than cerebral spinal fluid or positron emission tomography imaging-based diagnosis, the QPLEX™ kit can potentially be used for health checkups and the early clinical diagnosis of AD.

Fine-tuning GPCR-mediated neuromodulation by biasing signaling through different G protein subunits.

G-protein-coupled receptors (GPCRs) mediate neuromodulation through the activation of heterotrimeric G proteins (Gαßγ). Classical models depict that G protein activation leads to a one-to-one formation of Gα-GTP and Gßγ species. Each of these species propagates signaling by independently acting on effectors, but the mechanisms by which response fidelity is ensured by coordinating Gα and Gßγ responses remain unknown. Here, we reveal a paradigm of G protein regulation whereby the neuronal protein GINIP (Gα inhibitory interacting protein) biases inhibitory GPCR responses to favor Gßγ over Gα signaling. Tight binding of GINIP to Gαi-GTP precludes its association with effectors (adenylyl cyclase) and, simultaneously, with regulator-of-G-protein-signaling (RGS) proteins that accelerate deactivation. As a consequence, Gαi-GTP signaling is dampened, whereas Gßγ signaling is enhanced. We show that this mechanism is essential to prevent the imbalances of neurotransmission that underlie increased seizure susceptibility in mice. Our findings reveal an additional layer of regulation within a quintessential mechanism of signal transduction that sets the tone of neurotransmission.

Detecting GPCR Signals With Optical Biosensors of Gα-GTP in Cell Lines and Primary Cell Cultures.

G protein-coupled receptors (GPCRs) are the largest class of transmembrane receptors and mediate a wide variety of physiological processes. GPCRs respond to a plethora of extracellular ligands and initiate signaling pathways inside cells via heterotrimeric G proteins (Gαßγ). Because of the critical role GPCRs play in regulating biological processes and as pharmacological targets, the availability of tools to measure their signaling activity are of high interest. Live-cell biosensors that detect the activity of G proteins in response to GPCR stimulation have emerged as a powerful approach to investigate GPCR/G protein signaling. Here, we detail methods to monitor G protein activity through direct measurement of GTP-bound Gα subunits using optical biosensors based on bioluminescence resonance energy transfer (BRET). More specifically, this article describes the use of two types of complementary biosensors. The first protocol explains how to use a multicomponent BRET biosensor that relies on expression of exogenous G proteins in cell lines. This protocol yields robust responses that are compatible with endpoint measurements of dose-dependent ligand effects or with kinetic measurements of subsecond resolution. The second protocol describes the implementation of unimolecular biosensors that detect the activation of endogenous G proteins in cell lines expressing exogenous GPCRs or in primary cells upon stimulation of endogenous GPCRs. Overall, using the biosensors as described in this article will help users characterize the mechanisms of action of many pharmacological agents and natural ligands that modulate GPCR and G protein signaling with high precision. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Using bimolecular BRET biosensors to monitor Gα-GTP formation of tagged Gα in live cells Alternate Protocol 1: Measuring GPCR dose-dependent Gα-GTP responses in endpoint format Basic Protocol 2: Using unimolecular BRET biosensors to study endogenous G protein activity Alternate Protocol 2: Using unimolecular BRET biosensors to study endogenous G protein activity in mouse cortical neurons.

Small-molecule targeting of GPCR-independent noncanonical G-protein signaling in cancer.

Activation of heterotrimeric G-proteins (Gαßγ) by G-protein-coupled receptors (GPCRs) is a quintessential mechanism of cell signaling widely targeted by clinically approved drugs. However, it has become evident that heterotrimeric G-proteins can also be activated via GPCR-independent mechanisms that remain untapped as pharmacological targets. GIV/Girdin has emerged as a prototypical non-GPCR activator of G proteins that promotes cancer metastasis. Here, we introduce IGGi-11, a first-in-class small-molecule inhibitor of noncanonical activation of heterotrimeric G-protein signaling. IGGi-11 binding to G-protein α-subunits (Gαi) specifically disrupted their engagement with GIV/Girdin, thereby blocking noncanonical G-protein signaling in tumor cells and inhibiting proinvasive traits of metastatic cancer cells. In contrast, IGGi-11 did not interfere with canonical G-protein signaling mechanisms triggered by GPCRs. By revealing that small molecules can selectively disable noncanonical mechanisms of G-protein activation dysregulated in disease, these findings warrant the exploration of therapeutic modalities in G-protein signaling that go beyond targeting GPCRs.

Sex differences in the progression of glucose metabolism dysfunction in Alzheimer's disease.

Alzheimer's disease (AD) is a common neurodegenerative disease characterized by amyloid plaques and impaired brain metabolism. Because women have a higher prevalence of AD than men, sex differences are of great interest. Using cross-sectional and longitudinal data, we showed sex-dependent metabolic dysregulations in the brains of AD patients. Cohort 1 (South Korean, n = 181) underwent Pittsburgh compound B-PET, fluorodeoxyglucose-PET, magnetic resonance imaging, and blood biomarker (plasma tau and beta-amyloid 42 and 40) measurements at baseline and two-year follow-ups. Transcriptome analysis of data from Cohorts 2 and 3 (European, n = 78; Singaporean, n = 18) revealed sex differences in AD-related alterations in brain metabolism. In women (but not in men), all imaging indicators displayed consistent correlation curves with AD progression. At the two-year follow-up, clear brain metabolic impairment was revealed only in women, and the plasma beta-amyloid 42/40 ratio was a possible biomarker for brain metabolism in women. Furthermore, our transcriptome analysis revealed sex differences in transcriptomes and metabolism in the brains of AD patients as well as a molecular network of 25 female-specific glucose metabolic genes (FGGs). We discovered four key-attractor FGG genes (ALDOA, ENO2, PRKACB, and PPP2R5D) that were associated with amyloid/tau-related genes (APP, MAPT, BACE1, and BACE2). Furthermore, these genes successfully distinguished amyloid positivity in women. Understanding sex differences in the pathogenesis of AD and considering these differences will improve development of effective diagnostics and therapeutic treatments for AD.

Tunable image-mapping optical coherence tomography.

We present tunable image-mapping optical coherence tomography (TIM-OCT), which can provide optimized imaging performance for a given application by using a programmable phase-only spatial light modulator in a low-coherence full-field spectral-domain interferometer. The resultant system can provide either a high lateral resolution or a high axial resolution in a snapshot without moving parts. Alternatively, the system can achieve a high resolution along all dimensions through a multiple-shot acquisition. We evaluated TIM-OCT in imaging both standard targets and biological samples. Additionally, we demonstrated the integration of TIM-OCT with computational adaptive optics in correcting sample-induced optical aberrations.

Small-molecule targeting of GPCR-independent non-canonical G protein signaling inhibits cancer progression.

Activation of heterotrimeric G-proteins (Gαßγ) by G-protein-coupled receptors (GPCRs) is a quintessential mechanism of cell signaling widely targeted by clinically-approved drugs. However, it has become evident that heterotrimeric G-proteins can also be activated via GPCR-independent mechanisms that remain untapped as pharmacological targets. GIV/Girdin has emerged as a prototypical non-GPCR activator of G proteins that promotes cancer metastasis. Here, we introduce IGGi-11, a first-in-class smallmolecule inhibitor of non-canonical activation of heterotrimeric G-protein signaling. IGGi-11 binding to G-protein α-subunits (Gαi) specifically disrupted their engagement with GIV/Girdin, thereby blocking non-canonical G-protein signaling in tumor cells, and inhibiting pro-invasive traits of metastatic cancer cells in vitro and in mice. In contrast, IGGi-11 did not interfere with canonical G-protein signaling mechanisms triggered by GPCRs. By revealing that small molecules can selectively disable non-canonical mechanisms of G-protein activation dysregulated in disease, these findings warrant the exploration of therapeutic modalities in G-protein signaling that go beyond targeting GPCRs.

Cascaded compressed-sensing single-pixel camera for high-dimensional optical imaging.

Single-pixel detectors are popular devices in optical sciences because of their fast temporal response, high sensitivity, and low cost. However, when being used for imaging, they face a fundamental challenge in acquiring high-dimensional information of an optical field because they are essentially zero-dimensional sensors and measure only the light intensity. To address this problem, we developed a cascaded compressed-sensing single-pixel camera, which decomposes the measurement into multiple stages, sequentially reducing the dimensionality of the data from a high-dimensional space to zero dimension. This measurement scheme allows us to exploit the compressibility of a natural scene in multiple domains, leading to highly efficient data acquisition. We demonstrated our method in several demanding applications, including enabling tunable single-pixel full-waveform hyperspectral light detection and ranging (LIDAR) for the first time.

Retrofitting of an implant-supported surveyed crown under an existing removable partial denture by using an acrylic resin template.

Retrofitting a crown to an existing removable partial denture (RPD) is a complex process and requires additional clinical and laboratory procedures. Various methods have been described for retrofitting a new tooth-supported crown. However, if an abutment tooth has to be extracted, descriptions of techniques for restoring a new edentulous site with an implant-supported crown retrofitted to an existing RPD are lacking. Therefore, this technical report describes a straightforward approach to fabricating an implant-supported surveyed crown fitted to an existing RPD by using an acrylic resin template.

Association of B cell profile and receptor repertoire with the progression of Alzheimer's disease.

Alzheimer's disease (AD) is the most prevalent type of dementia. Reports have revealed that the peripheral immune system is linked to neuropathology; however, little is known about the contribution of B lymphocytes in AD. For this longitudinal study, 133 participants are included at baseline and second-year follow-up. Also, we analyze B cell receptor (BCR) repertoire data generated from a public dataset of three normal and 10 AD samples and perform BCR repertoire profiling and pairwise sharing analysis. As a result, longitudinal increase in B lymphocytes is associated with increased cerebral amyloid deposition and hyperactivates induced pluripotent stem cell-derived microglia with loss-of-function for beta-amyloid clearance. Patients with AD share similar class-switched BCR sequences with identical isotypes, despite the high somatic hypermutation rate. Thus, BCR repertoire profiling can lead to the development of individualized immune-based therapeutics and treatment. We provide evidence of both quantitative and qualitative changes in B lymphocytes during AD pathogenesis.