Using Voice Assistant Systems to Improve Dietary Recall among Older Adults: Perspectives of Registered Dietitians.

Dietary assessments are important clinical tools used by Registered Dietitians (RDs). Current methods pose barriers to accurately assess the nutritional intake of older adults due to age-related increases in risk for cognitive decline and more complex health histories. Our qualitative study explored whether implementing Voice assistant systems (VAS) could improve current dietary recall from the perspective of 20 RDs. RDs believed the implementing VAS in dietary assessments of older adults could potentially improve patient accuracy in reporting food intake, recalling portion sizes, and increasing patient-provider efficiency during clinic visits. RDs reported that low technology literacy in older adults could be a barrier to implementation. Our study provides a better understanding of how VAS can better meet the needs of both older adults and RDs in managing and assessing dietary intake.

Laplacian Projection Based Global Physical Prior Smoke Reconstruction.

We present a novel framework for reconstructing fluid dynamics in real-life scenarios. Our approach leverages sparse view images and incorporates physical priors across long series of frames, resulting in reconstructed fluids with enhanced physical consistency. Unlike previous methods, we utilize a differentiable fluid simulator (DFS) and a differentiable renderer (DR) to exploit global physical priors, reducing reconstruction errors without the need for manual regularization coefficients. We introduce divergence-free Laplacian eigenfunctions (div-free LE) as velocity bases, improving computational efficiency and memory usage. By employing gradient-related strategies, we achieve better convergence and superior results. Extensive experiments demonstrate the effectiveness of our method, showcasing improved reconstruction quality and computational efficiency compared to existing approaches. We validate our approach using both synthetic and real data, highlighting its practical potential.

Progress in RAS-targeted therapeutic strategies: From small molecule inhibitors to proteolysis targeting chimeras.

As a widely considerable target in chemical biology and pharmacological research, rat sarcoma (RAS) gene mutations play a critical driving factor in several fatal cancers. Despite the great progress of RAS subtype-specific inhibitors, rapid acquired drug resistance could limit their further clinical applications. Proteolysis targeting chimera (PROTAC) has emerged as a powerful tool to handle "undruggable" targets and exhibited significant therapeutic benefit for the combat of drug resistance. Owing to unique molecular mechanism and binding kinetics, PROTAC is expected to become a feasible strategy to break the bottleneck of classical RAS inhibitors. This review aims to discuss the current advances of RAS inhibitors and especially focus on PROTAC strategy targeting RAS mutations and their downstream effectors for relevant cancer treatment.

Enhancing Targeted Therapy in Hepatocellular Carcinoma through a pH-Responsive Delivery System: Folic Acid-Modified Polydopamine-Paclitaxel-Loaded Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Nanoparticles.

Currently, there is an inherent contradiction between the multifunctionality and excellent biocompatibility of anticancer drug nanocarriers, which limits their application. Therefore, to overcome this limitation, we aimed to develop a biocompatible drug delivery system for the treatment of hepatocellular carcinoma (HCC). In this study, we employed poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) as the fundamental framework of the nanocarrier and utilized the emulsion solvent evaporation method to fabricate nanoparticles loaded with paclitaxel (PTX), known as PTX-PHBV NPs. To enhance the tumor-targeting capability, a dopamine self-polymerization strategy was employed to form a pH-sensitive coating on the surface of the nanoparticles. Then, folic acid (FA)-targeting HCC was conjugated to the nanoparticles with a polydopamine (PDA) coating by using the Michael addition reaction, resulting in the formation of HCC-targeted nanoparticles (PTX-PHBV@PDA-FA NPs). The PTX-PHBV@PDA-FA NPs were characterized and analyzed by using dynamic light scattering, scanning electron microscopy, fourier-transform infrared spectroscopy, X-ray diffraction, differential scanning calorimetry, and thermogravimetric analysis. Encouragingly, PTX-PHBV@PDA-FA NPs exhibited remarkable anticancer efficacy in an HCC xenograft mouse model. Furthermore, compared to raw PTX, PTX-PHBV@PDA-FA NPs showed less toxicity in vivo. In conclusion, these results demonstrate the potential of PTX-PHBV@PDA-FA NPs for HCC treatment and biocompatibility.

Part-Aware Point Cloud Completion through Multi-Modal Part Segmentation.

Point cloud completion aims to generate high-resolution point clouds using incomplete point clouds as input and is the foundational task for many 3D visual applications. However, most existing methods suffer from issues related to rough localized structures. In this paper, we attribute these problems to the lack of attention to local details in the global optimization methods used for the task. Thus, we propose a new model, called PA-NET, to guide the network to pay more attention to local structures. Specifically, we first use textual embedding to assist in training a robust point assignment network, enabling the transformation of global optimization into the co-optimization of local and global aspects. Then, we design a novel plug-in module using the assignment network and introduce a new loss function to guide the network's attention towards local structures. Numerous experiments were conducted, and the quantitative results demonstrate that our method achieves novel performance on different datasets. Additionally, the visualization results show that our method efficiently resolves the issue of poor local structures in the generated point cloud.

Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising.

In many human-computer interaction applications, fast and accurate hand tracking is necessary for an immersive experience. However, raw hand motion data can be flawed due to issues such as joint occlusions and high-frequency noise, hindering the interaction. Using only current motion for interaction can lead to lag, so predicting future movement is crucial for a faster response. Our solution is the Multi-task Spatial-Temporal Graph Auto-Encoder (Multi-STGAE), a model that accurately denoises and predicts hand motion by exploiting the inter-dependency of both tasks. The model ensures a stable and accurate prediction through denoising while maintaining motion dynamics to avoid over-smoothed motion and alleviate time delays through prediction. A gate mechanism is integrated to prevent negative transfer between tasks and further boost multi-task performance. Multi-STGAE also includes a spatial-temporal graph autoencoder block, which models hand structures and motion coherence through graph convolutional networks, reducing noise while preserving hand physiology. Additionally, we design a novel hand partition strategy and hand bone loss to improve natural hand motion generation. We validate the effectiveness of our proposed method by contributing two large-scale datasets with a data corruption algorithm based on two benchmark datasets. To evaluate the natural characteristics of the denoised and predicted hand motion, we propose two structural metrics. Experimental results show that our method outperforms the state-of-the-art, showcasing how the multi-task framework enables mutual benefits between denoising and prediction.

Feasibility of using the Automated Self-Administered 24-hour (ASA-24) dietary assessment tool in older adults.

Background: Dietary patterns can impact the trajectories of healthy aging. However, dietary assessment tools can be challenging to use. With the increased use of technology in older adults, we aimed to evaluate the feasibility of older adults completing the online, Automated Self-Administered 24-h (ASA-24) dietary assessment tool. Methods: We conducted a randomized, two-period, two-sequence, crossover design of twenty community-dwelling older adults (≥65 years) comparing their preference for completing the ASA-24 alone versus with a research assistant (RA). Participants were recruited via ResearchMatch.com and randomly allocated 1:1 to a sequence of completing both an ASA-24 alone or with an RA, separated by one week. After each session, participants completed an online 11-item feasibility survey (Likert-scale range of 1-5, strongly disagree to strongly agree). Mean and standard deviations were reported for each question. Results: Mean age was 69 ± 3.5 years (90% females), with no differences were observed for sex, age, race, ethnicity, education, or income. Neither group felt a need for RA assistance (p = 0.34). However, both groups felt the system was easier to follow with the help of an RA (RA: 4.4 ± 1.3, vs. SA 4.6 ± 0.5, p = 0.65), particularly when they completed the ASA-24 alone, first (p = 0.04). When conducting the ASA-24 alone, there was less confidence the system could be learned quickly (SA 4.5 ± 0.5→3.4 ± 1.0 vs RA 3.4 ± 1.0→3.4 ± 0.7, p = 0.001). The ASA-24 was thought to be less cumbersome after repeated exposure in those concluding with the RA. Conclusion: While older adults were able to complete the ASA-24 independently, the use of an RA led to improved confidence. Enhancing the sample diversity in a larger number of participants could provide helpful data to improve the science of dietary assessment.

Physics-Based Differentiable Rendering for Efficient and Plausible Fluid Modeling from Monocular Video.

Realistic fluid models play an important role in computer graphics applications. However, efficiently reconstructing volumetric fluid flows from monocular videos remains challenging. In this work, we present a novel approach for reconstructing 3D flows from monocular inputs through a physics-based differentiable renderer coupled with joint density and velocity estimation. Our primary contributions include the proposed efficient differentiable rendering framework and improved coupled density and velocity estimation strategy. Rather than relying on automatic differentiation, we derive the differential form of the radiance transfer equation under single scattering. This allows the direct computation of the radiance gradient with respect to density, yielding higher efficiency compared to prior works. To improve temporal coherence in the reconstructed flows, subsequent fluid densities are estimated via a coupled strategy that enables smooth and realistic fluid motions suitable for applications that require high efficiency. Experiments on synthetic and real-world data demonstrated our method's capacity to reconstruct plausible volumetric flows with smooth dynamics efficiently. Comparisons to prior work on fluid motion reconstruction from monocular video revealed over 50-170x speedups across multiple resolutions.

An ultrasensitive method for detecting mutations from short and rare cell-free DNA.

Circulating tumor DNA (ctDNA) was short and rare, making the detection performance of the current targeted sequencing methods unsatisfying. We developed the One-PrimER Amplification (OPERA) system and examined its performance in detecting mutations of low variant allelic frequency (VAF) in various samples with short-sized DNA fragments. In cell line-derived samples containing sonication-sheared DNA fragments with 50-150 bp, OPERA was capable of detecting mutations as low as 0.0025% VAF, while CAPP-Seq only detected mutations of >0.03% VAF. Both single nucleotide variant and insertion/deletion can be detected by OPERA. In synthetic fragments as short as 80 bp with low VAF (0.03%-0.1%), the detection sensitivity of OPERA was significantly higher compared to that of droplet digital polymerase chain reaction. The error rate was 5.9×10-5 errors per base after de-duplication in plasma samples collected from healthy volunteers. By suppressing "single-strand errors", the error rate can be further lowered by >5 folds in EGFR T790M hotspot. In plasma samples collected from lung cancer patients, OPERA detected mutations in 57.1% stage I patients with 100% specificity and achieved a sensitivity of 30.0% in patients with tumor volume of less than 1 cm3. OPERA can effectively detect mutations in rare and highly-fragmented DNA.

Lightweight Co3O4/CC Composites with High Microwave Absorption Performance.

With the rapid development of electronic and communication technology for military radars, the demand for microwave-absorbing materials in the low-frequency range with thin layers is growing. In this study, flexible Co3O4/CC (carbon cloth) composites derived from Co-MOFs (metal-organic frameworks) and CC are prepared using hydrothermal and thermal treatment processes. The flexible precursors of the Co-MOFs/CC samples are calcined with different calcination temperatures, for which the material structure, dielectric properties, and microwave absorption performance are changed. With the increases in calcination temperature, the minimum reflection loss of the corresponding Co3O4/CC composites gradually moves to the lower frequency with a thinner thickness. In addition, the Co3O4/CC composites with the 25 wt% filler loading ratio exhibit the minimum reflection loss (RL) of -46.59 dB at 6.24 GHz with a 4.2 mm thickness. When the thickness is 3.70 mm, the effective absorption bandwidth is 3.04 GHz from 5.84 to 8.88 GHz. This study not only proves that the Co3O4/CC composite is an outstanding microwave-absorbing material with better flexibility but also provides useful inspiration for research on wideband microwave absorption materials below 10 GHz.

Rapid Identification of Pathogens in Severe Pneumonia by Species-specific Bacterial Detector (SSBD).

Fast and accurate detection of pathogenic bacterial infection in patients with severe pneumonia is significant to its treatment. The traditional culture method currently used by most medical institutions relies on a time-consuming culture process (over two days) that is unable to meet clinical needs. Rapid, accurate, and convenient species-specific bacterial detector (SSBD) has been developed to provide timely information on pathogenic bacteria. The SSBD was designed based on the fact that Cas12a indiscriminately cleaves any DNA following the binding of the crRNA-Cas12a complex to the target DNA molecule. SSBD involves two processes, starting with PCR of the target DNA using primers specific for the pathogen, followed by detection of the existence of pathogen target DNA in the PCR product using the corresponding crRNA and Cas12a protein. Compared to the culture test, the SSBD can obtain accurate pathogenic information in only a few hours, dramatically shortening the detection time and allowing more patients to benefit from timely clinical treatment.

A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis.

As the most common idiopathic inflammatory myopathy in children, juvenile dermatomyositis (JDM) is characterized by skin rashes and muscle weakness. The childhood myositis assessment scale (CMAS) is commonly used to measure the degree of muscle involvement for diagnosis or rehabilitation monitoring. On the one hand, human diagnosis is not scalable and may be subject to personal bias. On the other hand, automatic action quality assessment (AQA) algorithms cannot guarantee 100% accuracy, making them not suitable for biomedical applications. As a solution, we propose a video-based augmented reality system for human-in-the-loop muscle strength assessment of children with JDM. We first propose an AQA algorithm for muscle strength assessment of JDM using contrastive regression trained by a JDM dataset. Our core insight is to visualize the AQA results as a virtual character facilitated by a 3D animation dataset, so that users can compare the real-world patient and the virtual character to understand and verify the AQA results. To allow effective comparisons, we propose a video-based augmented reality system. Given a feed, we adapt computer vision algorithms for scene understanding, evaluate the optimal way of augmenting the virtual character into the scene, and highlight important parts for effective human verification. The experimental results confirm the effectiveness of our AQA algorithm, and the results of the user study demonstrate that humans can more accurately and quickly assess the muscle strength of children using our system.

High expression of RNF31 is associated with tumor immune cell infiltration and leads to poor prognosis in liver hepatocellular carcinoma.

Ring finger protein 31 (RNF31) has been found to play an important role in tumor immunity. However, the role of RNF31 in liver hepatocellular carcinoma (LIHC) has not been reported. Therefore, we investigated the expression and prognostic value of RNF31 in patients with LIHC and explored its relationship with immune cell infiltration. The Cancer Genome Atlas liver hepatocellular carcinoma (TCGA-LIHC) dataset was downloaded to analyse the impact of RNF31 on the prognosis and immune cell infiltration of LIHC. The Tumor Immune Estimation Resource (TIMER) database was used to analyse the correlation between RNF31 and tumor immune cell infiltration in LIHC. Additionally, we analysed the relationship between RNF31 and tumor necrosis factor (TNF) as well as the interferon-gamma (IFN-γ) signaling pathway. The expression of RNF31 in LIHC was significantly higher than that in normal tissues. Increased RNF31 expression was associated with decreased overall survival (OS) and relapse-free survival (RFS). An increase in RNF31 expression was closely related to the infiltration levels of immune cells (e.g., natural killer (NK) cells, CD8 + T cells, and B cells). RNF31 was also positively correlated with the expression of immune checkpoint genes in LIHC. Moreover, RNF31 may participate in TNF and IFN-γ signaling pathways. In conclusion, RNF31 is a potentially valuable prognostic biomarker in LIHC. RNF31 is also associated with immune cell infiltration in LIHC. RNF31 may be a potential target for immunotherapy of LIHC.

Comparative-genomic analysis reveals dynamic NLR gene loss and gain across Apiaceae species.

Introduction: Nucleotide-binding leucine-rich repeat (NLR) genes play a crucial role in green plants' responding to various pathogens. Genome-scale evolutionary studies of NLR genes are important for discovering and applying functional NLR genes. However, little is known about the evolution of NLR genes in the Apiaceae family including agricultural and medical plants. Methods: In this study, comparative genomic analysis was performed in four Apiaceae species to trace the dynamic evolutionary patterns of NLR genes during speciation in this family. Results: The results revealed different number of NLR genes in these four Apiaceae species, namely, Angelica sinensis (95), Coriandrum sativum (183), Apium graveolens (153) and Daucus carota (149). Phylogenetic analysis demonstrated that NLR genes in these four species were derived from 183 ancestral NLR lineages and experienced different levels of gene-loss and gain events. The contraction pattern of the ancestral NLR lineages was discovered during the evolution of D. carota, whereas a different pattern of contraction after first expansion of NLR genes was observed for A. sinensis, C. sativum and A. graveolens. Discussion: Taken together, rapid and dynamic gene content variation has shaped evolutionary history of NLR genes in Apiaceae species.

Tunable Electromagnetic and Microwave Absorption Properties of Magnetic FeNi3 Alloys.

Magnetic materials have a very broad application prospect in the field of microwave absorption, among which soft magnetic materials become the focus of magnetic materials research because of their high saturation magnetization and low coercivity. FeNi3 alloy has been widely used in soft magnetic materials because of its excellent ferromagnetism and electrical conductivity. In this work, FeNi3 alloy was prepared by the liquid reduction method. The effect of the filling ratio of FeNi3 alloy on the electromagnetic properties of absorbing materials was studied. It is found that the impedance matching ability of FeNi3 alloy is better when the filling ratio is 70 wt% than that of other samples with different filling ratios (30-60 wt%), showing better microwave absorption characteristics. When the matching thickness is 2.35 mm, the minimum reflection loss (RL) of FeNi3 alloy with a 70 wt% filling ratio reaches -40.33 dB, and the effective absorption bandwidth is 5.5 GHz. When the matching thickness is between 2 and 3 mm, the effective absorption bandwidth ranges from 7.21 GHz to 17.81 GHz, almost covering the whole X and Ku bands (8-18 GHz). The results show that FeNi3 alloy has adjustable electromagnetic properties and microwave absorption properties with different filling ratios, which is conducive to selecting excellent microwave absorption materials.

Liquid-solid ratio during hydrothermal carbonization affects hydrochar application potential in soil: Based on characteristics comparison and economic benefit analysis.

Returning straw-like agricultural waste to the field by converting it into hydrochar through hydrothermal carbonization (HTC) is an important way to realize resource utilization of waste, soil improvement, and carbon sequestration. However, the large-scale HTC is highly limited by the large water consumption and waste liquid pollution. Here, we propose strategies to optimize the liquid-solid ratio (LSR) of HTC, and comprehensively evaluate the stability, soil application potential, and economic benefits of corn stover-based hydrochar under different LSRs. The results showed that the total amount of dissolved organic carbon of hydrochars increased by 55.0% as LSR reducing from 10:1 to 2:1, while the element content, thermal stability, carbon fixation potential, specific surface area, pore volume, and functional group type were not obviously affected. The specific surface area and pore volume of hydrochar decreased by 61.8% and 70.9% as LSR reduced to 1:1, due to incomplete carbonization. According to the gray relation, hydrochar derived at LSR of 10:1 and followed by 2:1 showed greatest relation degree of 0.80 and 0.70, respectively, indicating better soil application potential. However, reducing LSR from 10:1 to 2:1 made the income of single process production increased from -388 to 968 ¥, and the wastewater generation decreased by 80%. Considering the large-scale application of HTC in fields for farmland improvement and environmental remediation, the comprehensive advantages of optimized LSR will be further highlighted.

Cancer-associated fibroblasts in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) has a relatively good prognosis, yet there are some invasive PTC cases with worse clinicopathological features and poor outcome. Cancer-associated fibroblasts (CAFs) play an important role in cancer invasion and metastasis. This study aimed to investigate the expression of marker proteins of CAFs in PTC and their correlations with clinicopathological features through immunohistochemistry. The medical records of 125 PTC patients were reviewed in this study, whose specimens were retrieved for immunohistochemistry. Four CAFs marker proteins, FAP fibroblast activated protein (FAP), α-smooth muscle actin (α-SMA), Vimentin and platelet-derived growth factor receptor-α(PDGFR-α), were stained and scored. Then, statistical analyses were performed. The immunoreactivity scores of FAP and α-SMA correlated with tumor size, BRAF mutation, extrathyroidal, invasion, pathological subtype, lymph node metastasis and ATA risk stratification. Moreover, binary logistic regression analysis and receiver operating characteristic curves showed that high FAP and α-SMA immunoreactivity scores were risk factors for extrathyroidal invasion, BRAF mutation, multi-focality and lymph node metastasis (especially N1b) with good sensitivity and accuracy in prediction. A better performance was found in FAP than α-SMA. Strong expressions of CAFs were risk factors for worse thyroid cancer clinicopathological features. FAP was the better CAFs marker for PTC.

Optimized electromagnetic wave absorption ofα-Fe2O3@MoS2nanocomposites with core-shell structure.

Core-shell structures and interfacial polarization are of great significance to meet the diversified requirements of microwave attenuation. Herein,α-Fe2O3@MoS2nanocomposites are fabricated via a simple two-step hydrothermal process, in which MoS2nanosheets as the shell are self-assembled andα-Fe2O3microdrums are used as the core to constitute a special flower-like morphology with core-shell structure. This structure can provide more interface contact to achieve strong interfacial polarization and possibly offer more multiple reflection and scattering of electromagnetic waves. Furthermore, the microwave dissipation performances ofα-Fe2O3@MoS2nanocomposites can be significantly improved through construction of core-shell structure and flower-like morphology, controlling the content ofα-Fe2O3microdrums and adjusting the filler loading ratios. This work proves that the as-synthesized nanocomposites achieve excellent effective absorption bandwidth and outstanding electromagnetic wave absorption capabilities due to their special interfaces, core-shell structures and good impedance matching conditions. Therefore,α-Fe2O3@MoS2nanocomposites are expected to be a novel and desirable candidate for high-performance electromagnetic wave absorbers.

LOXL2 serves as a prognostic biomarker for hepatocellular carcinoma by mediating immune infiltration and vasculogenic mimicry.

BACKGROUND: The development of human hepatocellular carcinoma (HCC) is a multistep process that is accompanied by progressive changes in the liver microenvironment, including immune evasion and angiogenesis. Lysyl oxidase-like 2 (LOXL2) has been suggested to contribute to tumour progression and metastasis; however, the underlying mechanism remains unclear. The purpose of the present study was to explore the relationship between LOXL2 and immune infiltration and vasculogenic mimicry (VM) and to identify the role of LOXL2 in HCC diagnosis prognosis evaluation. METHODS: The Cancer Genome Atlas (TCGA), UALCAN, GEPIA and Kaplan-Meier plotter databases were used to analyse LOXL2 expression and perform survival analysis. The Tumour Immune Estimation Resource (TIMER) was used to analyse immune cell infiltration, immune cell biomarkers and immune checkpoints. Immunohistochemistry (IHC) of 201 HCC samples was used to confirm the expression of LOXL2 and its relationship with VM. Coimmunoprecipitation (co-IP) and gain- and loss-of-function studies were performed to confirm the molecular mechanism of LOXL2 in VM. RESULTS: The expression of LOXL2 in HCC was higher than that in normal tissues at both the mRNA and protein levels. High expression of LOXL2 was associated with a poorer prognosis of HCC. The genetic alteration rate of LOXL2 was 5%. LOXL2 was positively related to immune cell infiltration and immune checkpoints (PD-1 and CTLA-4) in HCC. Co-IP showed that LOXL2 can interact directly with IQGAP1. Both gain- and loss-of-function studies showed that LOXL2 significantly induced cell migration, invasion and VM formation when IQGAP1 was upregulated. CONCLUSIONS: LOXL2 is involved in immune cell infiltration and promotes VM by upregulating IQGAP1. LOXL2 can be used as a novel biomarker for HCC diagnosis and prognosis prediction.

Comparative analysis of QS3D versus droplet digital PCR for quantitative measures of EGFR T790M mutation from identical plasma.

Objectives: The capacity of QuantStudio™ 3D (QS3D) and droplet digital PCR (dPCR) for the detection of plasma Epidermal Growth Factor Receptor (EGFR) mutations have been widely reported. Few comparative studies on the quantitative test of the identical DNA material, however, are carried out. Here we compared the performance of the two methods in detecting EGFR T790M mutation in cell-free DNA (cfDNA) from the same lung cancer patients. Methods: We recruited 72 non-small cell lung cancer (NSCLC) patients who initially respond to tyrosine kinase inhibitor treatment but subsequently developed resistance. Two tubes of 10mL anticoagulant blood were collected and cfDNA was isolated from plasma. Identical cfDNA samples were analyzed for T790M mutation using QS3D and droplet dPCR in parallel. Results: T790M mutation was detected in 15 and 21 cfDNA samples by QS3D and droplet digital PCR, respectively. The 6 discordant samples showed low mutation abundance (∼0.1%) and the discrepancy is caused by the stricter threshold settings for QS3D dPCR. The overall agreement between the two methods was 91.7% (66/72). The median allele frequencies for QS3D dPCR and droplet dPCR to detect T790M mutation was 2.01% and 2.62%, respectively. There was no significance in mutation abundance detected by both methods. Both methods are highly correlated with allele frequencies and copy numbers in T790M wild type and mutant, with R2 of 0.98, 0.92 and 0.95, respectively. Conclusion: Our study demonstrated that QS3D dPCR are highly consistent with droplet PCR for quantitative determination of EGFR T790M mutation in plasma cfDNA.