Triptolide, a Cancer Cell Proliferation Inhibitor, Causes Zebrafish Muscle Defects by Regulating Notch and STAT3 Signaling Pathways.

Triptolide is a natural compound in herbal remedies with anti-inflammatory and anti-proliferative properties. We studied its effects on critical signaling processes within the cell, including Notch1 and STAT3 signaling. Our research showed that triptolide reduces cancer cell proliferation by decreasing the expression of downstream targets of these signals. The levels of each signal-related protein and mRNA were analyzed using Western blot and qPCR methods. Interestingly, inhibiting one signal with a single inhibitor alone did not significantly reduce cancer cell proliferation. Instead, MTT assays showed that the simultaneous inhibition of Notch1 and STAT3 signaling reduced cell proliferation. The effect of triptolide was similar to a combination treatment with inhibitors for both signals. When we conducted a study on the impact of triptolide on zebrafish larvae, we found that it inhibited muscle development and interfered with muscle cell proliferation, as evidenced by differences in the staining of myosin heavy chain and F-actin proteins in confocal fluorescence microscopy. Additionally, we noticed that inhibiting a single type of signaling did not lead to any significant muscle defects. This implies that triptolide obstructs multiple signals simultaneously, including Notch1 and STAT3, during muscle development. Chemotherapy is commonly used to treat cancer, but it may cause muscle loss due to drug-related adverse reactions or other complex mechanisms. Our study suggests that anticancer agents like triptolide, inhibiting essential signaling pathways including Notch1 and STAT3 signaling, may cause muscle atrophy through anti-proliferative activity.

Analyzing the response of rice to tefuryltrione herbicide: Haplotype variation and evolutionary dynamics of the HIS1 gene.

Weeds pose multifaceted challenges in rice cultivation, leading to substantial economic losses through reduced yield and poor grain quality. Harnessing the natural genetic diversity in germplasm collections becomes crucial for identifying novel herbicide resistance loci in crops. A comprehensive analysis was conducted on 475 rice accessions from the KRICE depository, assessing their response to TFT (tefuryltrione) and probing the underlying HIS1 (HPPD INHIBITOR SENSITIVE 1) genotypic variations. The HIS1 gene, responsible for detoxifying benzobicyclon (BBC) and imparting broad-spectrum herbicide resistance, holds significant promise in rice breeding. This study explores the genetic landscape of HIS1 within Korean rice collection (KRICE), aiming to unveil genetic variations, haplotype diversity, and evolutionary relationships across diverse rice ecotypes. The indica ecotype showed the highest nucleotide diversity, while the wild and temperate japonica groups exhibited low diversity, hinting at selective sweeps and possible population expansion. Negative Tajima's D values in temperate japonica and wild groups indicate an excess of low-frequency mutations, potentially resulting from selective sweeps. In contrast, with positive Tajima's D values, admixture, indica, and aus groups suggest balancing selection. Furthermore, haplotype analysis uncovered 42 distinct haplotypes within KRICE, with four shared haplotypes between cultivated and wild accessions, four specific to cultivated accessions, and 34 specific to wild types. Phenotypic assessments of these haplotypes revealed that three haplotypes, viz., Hap_1 (predominant in japonica), Hap_2 (predominant in indica), and Hap_3 (specific to indica), displayed significant differences from aus-specific Hap_4 and indica-specific Hap_5. This study offers insights into genetic diversity, selective pressures, and ecotype-specific responses, ultimately paving the way for developing HPPD-inhibiting herbicide-resistant rice cultivars.

Evolutionary and synteny analysis of HIS1, BADH2, GBSS1, and GBSS2 in rice: insights for effective introgression breeding strategies.

The key genes BADH2, GBSS1, GBSS2, and HIS1 regulate the fragrance, starch synthesis, and herbicide resistance in rice. Although the molecular functions of four genes have been investigated in the Oryza sativa species, little is known regarding their evolutionary history in the Oryza genus. Here, we studied the evolution of four focal genes in 10 Oryza species using phylogenetic and syntenic approaches. The HIS1 family underwent several times of tandem duplication events in the Oryza species, resulting in copy number variation ranging from 2 to 7. At most one copy of BADH2, GBSS1, and GBSS2 orthologs were identified in each Oryza species, and gene loss events of BADH2 and GBSS2 were identified in three Oryza species. Gene transfer analysis proposed that the functional roles of GBSS1 and GBSS2 were developed in the Asian and African regions, respectively, and most allelic variations of BADH2 in japonica rice emerged after the divergence between the Asian and African rice groups. These results provide clues to determine the origin and evolution of the key genes in rice breeding as well as valuable information for molecular breeders and scientists to develop efficient strategies to simultaneously improve grain quality and yield potential in rice.

Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions.

Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.

Harnessing γ-TMT Genetic Variations and Haplotypes for Vitamin E Diversity in the Korean Rice Collection.

Gamma-tocopherol methyltransferase (γ-TMT), a key gene in the vitamin E biosynthesis pathway, significantly influences the accumulation of tocochromanols, thereby determining rice nutritional quality. In our study, we analyzed the γ-TMT gene in 475 Korean rice accessions, uncovering 177 genetic variants, including 138 SNPs and 39 InDels. Notably, two functional SNPs, tmt-E2-28,895,665-G/A and tmt-E4-28,896,689-A/G, were identified, causing substitutions from valine to isoleucine and arginine to glycine, respectively, across 93 accessions. A positive Tajima's D value in the indica group suggests a signature of balancing selection. Haplotype analysis revealed 27 haplotypes, with two shared between cultivated and wild accessions, seven specific to cultivated accessions, and 18 unique to wild types. Further, profiling of vitamin E isomers in 240 accessions and their association with haplotypes revealed that Hap_2, distinguished by an SNP in the 3' UTR (tmt-3UTR-28,897,360-T/A) exhibited significantly lower α-tocopherol (AT), α-tocotrienol (AT3), total tocopherol, and total tocotrienol, but higher γ-tocopherol (GT) in the japonica group. Additionally, in the indica group, Hap_2 showed significantly higher AT, AT3, and total tocopherol, along with lower GT and γ-tocotrienol, compared to Hap_19, Hap_20, and Hap_21. Overall, this study highlights the genetic landscape of γ-TMT and provides a valuable genetic resource for haplotype-based breeding programs aimed at enhancing nutritional profiles.

Multifunctional HfAlO thin film: Ferroelectric tunnel junction and resistive random access memory.

This study presents findings indicating that the ferroelectric tunnel junction (FTJ) or resistive random-access memory (RRAM) in one cell can be intentionally selected depending on the application. The HfAlO film annealed at 700 °C shows stable FTJ characteristics and can be converted into RRAM by forming a conductive filament inside the same cell, that is, the process of intentionally forming a conductive filament is the result of defect generation and redistribution, and applying compliance current prior to a hard breakdown event of the dielectric film enables subsequent RRAM operation. The converted RRAM demonstrated good memory performance. Through current-voltage fitting, it was confirmed that the two resistance states of the FTJ and RRAM had different transport mechanisms. In the RRAM, the 1/f noise power of the high-resistance state (HRS) was about ten times higher than that of the low-resistance state (LRS). This is because the noise components increase due to the additional current paths in the HRS. The 1/f noise power according to resistance states in the FTJ was exactly the opposite result from the case of the RRAM. This is because the noise component due to the Poole-Frenkel emission is added to the noise component due to the tunneling current in the LRS. In addition, we confirmed the potentiation and depression characteristics of the two devices and further evaluated the accuracy of pattern recognition through a simulation by considering a dataset from the Modified National Institute of Standards and Technology.

Clinical Feasibility of Deep Learning-Based Attenuation Correction Models for Tl-201 Myocardial Perfusion SPECT.

PURPOSE: We aimed to develop deep learning (DL)-based attenuation correction models for Tl-201 myocardial perfusion SPECT (MPS) images and evaluate their clinical feasibility. PATIENTS AND METHODS: We conducted a retrospective study of patients with suspected or known coronary artery disease. We proposed a DL-based image-to-image translation technique to transform non-attenuation-corrected images into CT-based attenuation-corrected (CT AC ) images. The model was trained using a modified U-Net with structural similarity index (SSIM) loss and mean squared error (MSE) loss and compared with other models. Segment-wise analysis using a polar map and visual assessment for the generated attenuation-corrected (GEN AC ) images were also performed to evaluate clinical feasibility. RESULTS: This study comprised 657 men and 328 women (age, 65 ± 11 years). Among the various models, the modified U-Net achieved the highest performance with an average mean absolute error of 0.003, an SSIM of 0.990, and a peak signal-to-noise ratio of 33.658. The performance of the model was not different between the stress and rest datasets. In the segment-wise analysis, the myocardial perfusion of the inferior wall was significantly higher in GEN AC images than in the non-attenuation-corrected images in both the rest and stress test sets ( P < 0.05). In the visual assessment of patients with diaphragmatic attenuation, scores of 4 (similar to CT AC images) or 5 (indistinguishable from CT AC images) were assigned to most GEN AC images (65/68). CONCLUSIONS: Our clinically feasible DL-based attenuation correction models can replace the CT-based method in Tl-201 MPS, and it would be useful in case SPECT/CT is unavailable for MPS.

Sinonasal microbiome and inflammatory profiles in fungal ball and chronic rhinosinusitis.

OBJECTIVE: Fungal balls (FB) are the main form of non-invasive fungal rhinosinusitis found in immunocompetent hosts. Bacterial coinfection affects clinical symptoms. We investigated the sinonasal microbiome and inflammatory profiles in FB and chronic rhinosinusitis (CRS) patients. METHODS: Thirty-three participants were prospectively recruited. Nasal swab samples and sinonasal tissues were collected from controls, and FB and CRS patients. DNA extraction and microbiome analysis using V3-V4 region 16S rRNA sequencing were performed. Inflammatory cytokine levels in the sinonasal tissues, blood eosinophil counts, and serum total IgE were measured. RESULTS: No significant differences were observed in species richness or evenness measures. The phylogenetic tree demonstrated that the FB samples were different from the controls. The sinus bacteria composition differed among the groups. At the phylum level, Firmicutes in FB were significantly depleted compared with those in CRS, while Proteobacteria were more enriched in FB than that in controls and CRS. At the genus level, in FB, Staphylococcus and Corynebacterium were significantly decreased compared to those in the controls. The prevalence of Haemophilus was the highest in FB. Blood eosinophil counts and IL-5 and periostin levels in the sinonasal tissue of the FB group were significantly lower than those in the CRS group. CONCLUSIONS: FB patients had different microbiome compositions and fewer type 2 inflammatory profiles than CRS patients did. However, whether these findings cause FB or result from bacterial and/or fungal infection remains unclear. Further studies are needed to reveal how these differences occur and affect the development of FB and clinical symptoms.

Wearable and Wavelength-Tunable Near-Infrared Organic Light-Emitting Diodes for Biomedical Applications.

Near-infrared organic light-emitting diodes (NIR OLEDs) have significant potential for wearable phototherapeutic applications because of the unique properties of the OLEDs, including their free-form electronics and the excellent biomedical effects of NIR emission. In spite of their tremendous promise, given that the majority of NIR OLEDs in previous research have relied on the utilization of an intrinsically brittle indium tin oxide (ITO) electrode, their practicality in the field of wearable electronics is inherently constrained. Here, we report wearable and wavelength-tunable NIR OLEDs that employ a high-performance NIR emitter and an innovative architecture by replacing the ITO with a silver (Ag) electrode. The NIR OLEDs permit wavelength tuning of emissions from 700 to 800 nm and afford stable operation even under repeated bending conditions. The NIR OLEDs provide a lowered device temperature of 37.5 °C even during continuous operation under several emission intensities. In vitro experiments were performed with freshly fabricated NIR OLEDs. The outcomes were evaluated against experimental results performed using the same procedure utilizing blue, green, and red OLEDs. When exposed to NIR light irradiation, the promoting effect of cell proliferation surpassed the proliferative responses observed under the influence of visible light irradiation. The proliferation effect of human hair follicle dermal papilla cells is clearly related to the irradiation wavelength and time, thus underscoring the potential of wavelength-tunable NIR OLEDs for efficacious phototherapy. This work will open novel avenues for wearable NIR OLEDs in the field of biomedical application.

Preliminary investigation on the implementation of an artificial synapse using TaOx-based memristor with thermally oxidized active layer.

This study presents a preliminary exploration of thermally oxidized TaOx-based memristors and their potential as artificial synapses. Unlike the 10-min annealed devices, which display instability due to current overshoots, the 5-min annealed device exhibits stable resistive switching, retention, and endurance characteristics. Moreover, our memristor showcases synaptic behaviors encompassing potentiation, depression, spike-timing-dependent plasticity, and excitatory postsynaptic currents. This synaptic emulation holds tremendous promise for applications in neuromorphic computing, offering the opportunity to replicate the adaptive learning principles observed in biological synapses. In addition, we evaluate the device's suitability for pattern recognition within a neural network using the modified National Institute of Standards and Technology dataset. Our assessment reveals that the Pt/TaOx/Ta memristor with an oxidized insulator achieves outstanding potential manifested by an accuracy of 93.25% for the identical pulse scheme and an impressive accuracy of 95.42% for the incremental pulse scheme.

IGZO/SnOx-based dynamic memristor with fading memory effect for reservoir computing.

We investigate a synaptic device with short-term memory characteristics using IGZO/SnOx as the switching layer. The thickness and components of each layer are analyzed by using x-ray photoelectron spectroscopy and transmission electron microscopy. The memristor exhibits analog resistive switching and a volatile feature with current decay over time. Moreover, through ten cycles of potentiation and depression, we demonstrate stable conductance modulation, leading to high-accuracy Modified National Institute of Standards and Technology pattern recognition. We effectively emulate the learning system of a biological synapse, including paired-pulse facilitation, spiking-amplitude-dependent plasticity, and spiking-rate-dependent plasticity (SRDP) by pulse trains. Ultimately, 4-bit reservoir computing divided into 16 states is incarnated using a pulse stream considering short-term memory plasticity and decay properties.

Multi-Layered Triboelectric Nanogenerators with Controllable Multiple Spikes for Low-Power Artificial Synaptic Devices.

In the domains of wearable electronics, robotics, and the Internet of Things, there is a demand for devices with low power consumption and the capability of multiplex sensing, memory, and learning. Triboelectric nanogenerators (TENGs) offer remarkable versatility in this regard, particularly when integrated with synaptic transistors that mimic biological synapses. However, conventional TENGs, generating only two spikes per cycle, have limitations when used in synaptic devices requiring repetitive high-frequency gating signals to perform various synaptic plasticity functions. Herein, a multi-layered micropatterned TENG (M-TENG) consisting of a polydimethylsiloxane (PDMS) film and a composite film that includes 1H,1H,2H,2H-perfluorooctyltrichlorosilane/BaTiO3 /PDMS are proposed. The M-TENG generates multiple spikes from a single touch by utilizing separate triboelectric charges at the multiple friction layers, along with a contact/separation delay achieved by distinct spacers between layers. This configuration allows the maximum triboelectric output charge of M-TENG to reach up to 7.52 nC, compared to 3.69 nC for a single-layered TENG. Furthermore, by integrating M-TENGs with an organic electrochemical transistor, the spike number multiplication property of M-TENGs is leveraged to demonstrate an artificial synaptic device with low energy consumption. As a proof-of-concept application, a robotic hand is operated through continuous memory training under repeated stimulations, successfully emulating long-term plasticity.

Human microglial state dynamics in Alzheimer's disease progression.

Altered microglial states affect neuroinflammation, neurodegeneration, and disease but remain poorly understood. Here, we report 194,000 single-nucleus microglial transcriptomes and epigenomes across 443 human subjects and diverse Alzheimer's disease (AD) pathological phenotypes. We annotate 12 microglial transcriptional states, including AD-dysregulated homeostatic, inflammatory, and lipid-processing states. We identify 1,542 AD-differentially-expressed genes, including both microglia-state-specific and disease-stage-specific alterations. By integrating epigenomic, transcriptomic, and motif information, we infer upstream regulators of microglial cell states, gene-regulatory networks, enhancer-gene links, and transcription-factor-driven microglial state transitions. We demonstrate that ectopic expression of our predicted homeostatic-state activators induces homeostatic features in human iPSC-derived microglia-like cells, while inhibiting activators of inflammation can block inflammatory progression. Lastly, we pinpoint the expression of AD-risk genes in microglial states and differential expression of AD-risk genes and their regulators during AD progression. Overall, we provide insights underlying microglial states, including state-specific and AD-stage-specific microglial alterations at unprecedented resolution.

Epigenomic dissection of Alzheimer's disease pinpoints causal variants and reveals epigenome erosion.

Recent work has identified dozens of non-coding loci for Alzheimer's disease (AD) risk, but their mechanisms and AD transcriptional regulatory circuitry are poorly understood. Here, we profile epigenomic and transcriptomic landscapes of 850,000 nuclei from prefrontal cortexes of 92 individuals with and without AD to build a map of the brain regulome, including epigenomic profiles, transcriptional regulators, co-accessibility modules, and peak-to-gene links in a cell-type-specific manner. We develop methods for multimodal integration and detecting regulatory modules using peak-to-gene linking. We show AD risk loci are enriched in microglial enhancers and for specific TFs including SPI1, ELF2, and RUNX1. We detect 9,628 cell-type-specific ATAC-QTL loci, which we integrate alongside peak-to-gene links to prioritize AD variant regulatory circuits. We report differential accessibility of regulatory modules in late AD in glia and in early AD in neurons. Strikingly, late-stage AD brains show global epigenome dysregulation indicative of epigenome erosion and cell identity loss.

Unraveling dynamically encoded latent transcriptomic patterns in pancreatic cancer cells by topic modeling.

Building a comprehensive topic model has become an important research tool in single-cell genomics. With a topic model, we can decompose and ascertain distinctive cell topics shared across multiple cells, and the gene programs implicated by each topic can later serve as a predictive model in translational studies. Here, we present a Bayesian topic model that can uncover short-term RNA velocity patterns from a plethora of spliced and unspliced single-cell RNA-sequencing (RNA-seq) counts. We showed that modeling both types of RNA counts can improve robustness in statistical estimation and can reveal new aspects of dynamic changes that can be missed in static analysis. We showcase that our modeling framework can be used to identify statistically significant dynamic gene programs in pancreatic cancer data. Our results discovered that seven dynamic gene programs (topics) are highly correlated with cancer prognosis and generally enrich immune cell types and pathways.

Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease.

Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE-gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP-ARE-gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia.

Genomic landscape of the OsTPP7 gene in its haplotype diversity and association with anaerobic germination tolerance in rice.

Early season flooding is a major constraint in direct-seeded rice, as rice genotypes vary in their coleoptile length during anoxia. Trehalose-6-phosphate phosphatase 7 (OsTPP7, Os09g0369400) has been identified as the genetic determinant for anaerobic germination (AG) and coleoptile elongation during flooding. We evaluated the coleoptile length of a diverse rice panel under normal and flooded conditions and investigated the Korean rice collection of 475 accessions to understand its genetic variation, population genetics, evolutionary relationships, and haplotypes in the OsTPP7 gene. Most accessions displayed enhanced flooded coleoptile lengths, with the temperate japonica ecotype exhibiting the highest average values for normal and flooded conditions. Positive Tajima's D values in indica, admixture, and tropical japonica ecotypes suggested balancing selection or population expansion. Haplotype analysis revealed 18 haplotypes, with three in cultivated accessions, 13 in the wild type, and two in both. Hap_1 was found mostly in japonica, while Hap-2 and Hap_3 were more prevalent in indica accessions. Further phenotypic performance of major haplotypes showed significant differences in flooded coleoptile length, flooding tolerance index, and shoot length between Hap_1 and Hap_2/3. These findings could be valuable for future selective rice breeding and the development of efficient haplotype-based breeding strategies for improving flood tolerance.

A Machine Learning Approach Using [18F]FDG PET-Based Radiomics for Prediction of Tumor Grade and Prognosis in Pancreatic Neuroendocrine Tumor.

PURPOSE: We sought to develop and validate machine learning (ML) models for predicting tumor grade and prognosis using 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomography (PET)-based radiomics and clinical features in patients with pancreatic neuroendocrine tumors (PNETs). PROCEDURES: A total of 58 patients with PNETs who underwent pretherapeutic [18F]FDG PET/computed tomography (CT) were retrospectively enrolled. PET-based radiomics extracted from segmented tumor and clinical features were selected to develop prediction models by the least absolute shrinkage and selection operator feature selection method. The predictive performances of ML models using neural network (NN) and random forest algorithms were compared by the areas under the receiver operating characteristic curves (AUROCs) and validated by stratified five-fold cross validation. RESULTS: We developed two separate ML models for predicting high-grade tumors (Grade 3) and tumors with poor prognosis (disease progression within two years). The integrated models consisting of clinical and radiomic features with NN algorithm showed the best performances than the other models (stand-alone clinical or radiomics models). The performance metrics of the integrated model by NN algorithm were AUROC of 0.864 in the tumor grade prediction model and AUROC of 0.830 in the prognosis prediction model. In addition, AUROC of the integrated clinico-radiomics model with NN was significantly higher than that of tumor maximum standardized uptake model in predicting prognosis (P < 0.001). CONCLUSIONS: Integration of clinical features and [18F]FDG PET-based radiomics using ML algorithms improved the prediction of high-grade PNET and poor prognosis in a non-invasive manner.

Direct comparison of diagnostic and clinical values between Tc-99 m DPD and Tc-99 m PYP scintigraphy in patients with cardiac amyloidosis.

BACKGROUND: Technetium-99 m 3,3-diphosphono-1,2-propanodicarboxylic acid (DPD) and technetium-99 m sodium pyrophosphate (PYP) are the two most commonly used radiotracers for cardiac amyloidosis (CA), but no studies have directly compared them. Therefore, in this study, we directly compared the diagnostic and clinical utility of DPD and PYP scintigraphy in patients with CA. METHODS: Ten patients with CA were enrolled. Eight clinical variables and 12 scintigraphic parameters were used. Clinical variables were age, sex, estimated glomerular filtration rate (eGFR), N-terminal pro brain natriuretic peptide (NT-proBNP), and the results of electromyography (EMG), a sensory test, electrocardiogram, and echocardiography (EchoCG). Four heart retention ratios (heart/whole-body profile, heart/pelvis, heart/skull, and heart/contralateral lung) were calculated from the DPD and PYP scans and two visual scoring systems (Perugini and Dorbala systems) were used. Comparative analyses were performed between radiotracers and between visual scoring systems using clinical variables and scintigraphic parameters. RESULTS: Twenty DPD parameters and nine PYP parameters had significant associations with age, eGFR, NT-proBNP, EchoCG, and EMG. DPD parameters had more frequent significant associations with clinical variables than PYP parameters. Compared to visual scores in the DPD scan, the proportion of patients with higher visual scores in the PYP scan was relatively greater than those with lower visual scores, and there were more patients with a visual score of 2 or higher in PYP scans than DPD scans. CONCLUSIONS: DPD scintigraphy may reflect the disease severity of CA better than PYP scintigraphy, whereas PYP scintigraphy may be a more sensitive imaging modality for identifying CA involvement.