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The transition state is the most critical and dangerous state of the VTOL fixed wing aircraft in the whole flight process. In this paper, a transition corridor for a distributed propulsion VTOL fixed-wing aircraft is studied based on the lift characteristics of the wing and the power constraints of the power unit. Firstly, according to the sliding flow theory, the dynamic characteristics models of the lift fan system in the front part of the fuselage and the distributed duct system in the rear part of the fuselage were established by introducing the influence factor of the duct, and verified with the test data. Secondly, according to the lift characteristics of the wing, the transition curves of the aircraft at different angles of attack are calculated, in which the transition curves corresponding to the zero-lift attack angle and stall attack angle constitute the lift characteristics transition corridor of the distributed propulsion VTOL fixed-wing aircraft. Finally based on the dynamic performance of the power unit model, calculate the lift characteristic transition each state point in corridor corresponding power demand, according to the power limit of the lift fan system, distributed duct system and power unit total power limitation, get distributed to promote vertical take-off and landing a fixed wing aircraft power limitation in lifting features and power unit under the condition of complete transition corridor. The final results show that the minimum forward velocity is inversely proportional to the attack angle. The power required by the tail distributed duct system will exceed the limit when the aircraft is in low speed and small dip angle transition. For the power limit boundary required, the power limit condition of individual component is stricter than the total power limit condition. The research results of this paper can provide some reference for the transition corridor research of such VTOL fixed-wing aircraft, and on this basis, the subsequent work such as parameter sensitivity analysis and control system design of transition corridor can be carried out.

To determine whether the outer retinal layer (ORL) thickness around geographic atrophy (GA) could serve as a clinical biomarker to predict the annual enlargement rate (ER) of GA.Retrospective analysis of a prospective, observational case series.Eyes with GA were imaged with a swept-source OCT 6 × 6 mm scan pattern. GA lesions were measured from customized en face OCT images and the annual ERs were calculated. The ORL was defined and segmented from the inner boundary of outer plexiform layer (OPL) to the inner boundary of retinal pigment epithelium (RPE) layer. The ORL thickness was measured at different subregions around GA.A total of 38 eyes from 27 participants were included. The same eyes were used for the choriocapillaris (CC) flow deficit (FD) analysis and the RPE to the Bruch membrane (RPE-BM) distance measurements. A negative correlation was observed between the ORL thickness and the GA growth. The ORL thickness in a 300-μm rim around GA showed the strongest correlation with the GA growth (r = -0.457, P = .004). No correlations were found between the ORL thickness and the CC FDs; however, a significant correlation was found between the ORL thickness and the RPE-BM distances around GA (r = -0.398, P = .013).ORL thickness showed a significant negative correlation with annual GA growth, but also showed a significant correlation with the RPE-BM distances, suggesting that they were dependently correlated with GA growth. This finding suggests that the loss of photoreceptors was associated with the formation of basal laminar deposits around GA.

Cerebral creatine deficiency syndromes (CCDSs) are a group of rare mendelian disorders mainly characterized by intellectual disability, movement anomaly, behavior disorder and seizures. SLC6A8, GAMT, and GATM are known genes responsible for CCDS. In this study, seven pediatric patients with developmental delay were recruited and submitted to a series of clinical evaluation, laboratory testing, and genetic analysis. The clinical manifestations and core biochemical indications of each child were basically consistent with the diagnosis of CCDS. Genetic diagnosis determined that all patients were positive for SLC6A8 or GAMT variation. A total of 12 variants were identified in this cohort, including six novel ones. The frequency of these variants, the Revel scores and the conservatism of the affected amino acids support their pathogenicity. Our findings expanded the mutation spectrum of CCDS disorders, and provided solid evidence for the counseling to affected families.

Microalbuminuria (MAU) reflects the generalized vascular endothelial dysfunction. Whether MAU has correlation with atherosclerotic intracranial and extracranial arterial stenosis in cerebral infarction patients is not known and is explored in the present investigation.We enrolled 255 cerebral infarction patients hospitalized at the department of neurology. All patients underwent digital subtraction angiography (DSA) to evaluate the severity and distribution of intracranial and extracranial arterial stenosis. MAU was expressed as the urine albumin-to-creatinine ratio (UACR). We collected basic information, medical history reviews and laboratory results of each participant. The multivariate logistic regression analysis was utilized to analyze the risk factors for severity and distribution of cerebral arterial stenosis.The prevalence of MAU in patients with cerebral infarction was 39.2%, patients with MAU had older age, lower blood uric acid, higher systolic blood pressure (SBP), higher prevalence of hypertension and diabetes (p 0.05) and higher incidence of atherosclerotic intracranial and extracranial arterial stenosis (χ2 = 5.900, p = 0.015). In multiple logistic regression analysis for intracranial and extracranial arterial stenosis more than 50% or occlusion groups, UACR (OR 1.088 95%CI 1.012-1.170p = 0.022), male (OR 2.196 95%CI 1.085-4.442p = 0.029) as well as SBP (OR 5.870 95%CI 1.026-1.048p = 0.015) showed statistical significance. But UACR had no correlation with the distribution of intracranial and extracranial artery stenosis after adjusting for all potential confounders.Microalbuminuria was an independent risk factor for intracranial and extracranial arterial stenosis more than 50% or occlusion.

Clinically and biologically, it is essential to detect rare DNA-sequence variants for early cancer diagnosis or drug-resistance mutation identification. Some of the common quantitative polymerase chain reaction (qPCR)-based variant detection methods are restricted in the limit of detection (LoD) because the DNA polymerases used for these methods have a high polymerase misincorporation rate; thus, the detection sensitivity is sometimes unsatisfactory. With the proofreading activity, high-fidelity (HiFi) DNA polymerases have a 50- to 250-fold higher fidelity. However, there are currently no proper probe-based designs functioning as the fluorescence indicator allowing multiplexed HiFi qPCR reactions, thus restricting the application of HiFi DNA polymerases like the variant detection. We presented the occlusion system, composed of a 5'-overhanged primer with a fluorophore modification and a probe with a short-stem hairpin and a 3' quencher modification. We demonstrated that the occlusion system allowed multiplexing HiFi qPCR reaction, and it was compatible with the current variant-enrichment method to improve the LoD up to 10-fold. Thus, the occlusion system satisfactorily functioned as an efficient fluorescence indicator in HiFi qPCR reactions and allowed the application of HiFi DNA polymerases in variant detection methods to improve detection sensitivity.

Background. Oxidative stress (OS) and immune inflammation play complex intersections in the pathophysiology of ischemic stroke (IS). However, a competing endogenous RNA- (ceRNA-) based mechanism linked to the intersections in IS has not been explored. We aimed to identify potential OS-related signatures and analyze immune infiltration characteristics in IS. Methods. Three datasets (GSE22255, GSE110993, and GSE140275) from the GEO database were extracted. Differentially expressed long noncoding RNAs, microRNAs, and messenger RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) between IS patients and controls were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were explored. Moreover, a triple ceRNA network was constructed to reveal transcriptional regulation mechanisms. A comprehensive strategy among least absolute shrinkage and selection operator (LASSO) regression, DEmRNAs, uprelated DEmRNAs, and OS-related genes was adopted to select the best signature. Then, we evaluated and verified the discriminant ability of the signature via receiver operating characteristic (ROC) analysis. Immune infiltration characteristics were explored via the CIBERSORT algorithm. Moreover, the best signature was verified via qPCR and western blot methods in rat brain tissues and PC12 cells. Results. 11 DEmRNAs were identified totally. Enrichment analysis showed that the DEmRNAs were primarily concentrated in MAPK-associated biological processes and immune or inflammation-involved pathways. DUSP1 was identified as the best signature with an area under the ROC curve of 73.5% ( 95 % CI = 57.02 -89.98, sensitivity = 95 % , and specificity = 60 % ) in GSE22255 and 100.0% ( 95 % CI = 100.00 -100.00, sensitivity = 100 % , and specificity = 100 % ) in GSE140275. Importantly, we also identified the AC079305/DUSP1 axis in the ceRNA network. Immune infiltration showed that resting mast cells infiltrate less in IS patients compared with controls. And DUSP1 was negatively correlated with resting mast cells ( r = − 0.703 , P < 0.01 ), whereas it was positively correlated with neutrophils ( r = 0.339 , P < 0.05 ). Both in vivo and in vitro models confirmed the upregulated expression of DUSP1 and the downregulated expression of miR-429. Conclusion. This study identified the ceRNA-based AC079305/DUSP1 axis as a promising OS-related signature for IS. Immune infiltrating cells, especially mast cells, may exert a pivotal role in IS progression. Pharmacological agents targeting signatures, their receptors, or mast cells may shed a novel light on therapeutic targets for IS.

Due to the space limitation of the launching platform, the wings of the space-based gravity delivery UAV need to be folded before launching. In the process of wing folding and launching, the dynamics model of UAV will show the characteristics of multiple rigid bodies and multiple degrees of freedom, and the aerodynamic characteristics of UAV are also quite different from that of cruise stage, so the traditional aircraft dynamics modeling method is no longer applicable. In this paper, the multibody dynamics model of gravitational airdrop UAV is first built based on the Lagrange equation, and then according to the aerodynamic change on unmanned aerial vehicle in deploying process, the angle between the wing and the fuselage is introduced as a new variable, the UAV launch phase nonlinear aerodynamic model is established, and through comparison with software calculation results the reliability of the aerodynamic model is verified. Based on the aerodynamic model and dynamics model, the dynamic response of UAV deployment process is simulated, and the influence of UAV deployment process on UAV subsequent pulling stage under the same control instructions is compared, and the dynamics and kinematics characteristics of gravity launch are studied and explored. Finally, the simulation results are compared with the experimental data, indicating that the multi-body dynamic model established in this paper can accurately describe the dynamic response of UAV in the launching stage and the subsequent modification stage, which can provide reference for the technical personnel engaged in the design, test and use of related models.

Qualitative and quantitative assessments of calcified drusen are clinically important for determining the risk of disease progression in age-related macular degeneration (AMD). This paper reports the development of an automated algorithm to segment and quantify calcified drusen on swept-source optical coherence tomography (SS-OCT) images. The algorithm leverages the higher scattering property of calcified drusen compared with soft drusen. Calcified drusen have a higher optical attenuation coefficient (OAC), which results in a choroidal hypotransmission defect (hypoTD) below the calcified drusen. We show that it is possible to automatically segment calcified drusen from 3D SS-OCT scans by combining the OAC within drusen and the hypoTDs under drusen. We also propose a correction method for the segmentation of the retina pigment epithelium (RPE) overlying calcified drusen by automatically correcting the RPE by an amount of the OAC peak width along each A-line, leading to more accurate segmentation and quantification of drusen in general, and the calcified drusen in particular. A total of 29 eyes with nonexudative AMD and calcified drusen imaged with SS-OCT using the 6 × 6 mm2 scanning pattern were used in this study to test the performance of the proposed automated method. We demonstrated that the method achieved good agreement with the human expert graders in identifying the area of calcified drusen (Dice similarity coefficient: 68.27 ± 11.09%, correlation coefficient of the area measurements: r = 0.9422, the mean bias of the area measurements = 0.04781 mm2).

Graph neural networks (GNNs) have shown excellent performance in a wide range of applications such as recommendation, risk control, and drug discovery. With the increase in the volume of graph data, distributed GNN systems become essential to support efficient GNN training. However, existing distributed GNN training systems suffer from various performance issues including high network communication cost, low CPU utilization, and poor end-to-end performance. In this paper, we propose ByteGNN, which addresses the limitations in existing distributed GNN systems with three key designs: (1) an abstraction of mini-batch graph sampling to support high parallelism, (2) a two-level scheduling strategy to improve resource utilization and to reduce the end-to-end GNN training time, and (3) a graph partitioning algorithm tailored for GNN workloads. Our experiments show that ByteGNN outperforms the state-of-the-art distributed GNN systems with up to 3.5--23.8 times faster end-to-end execution, 2--6 times higher CPU utilization, and around half of the network communication cost.

Numerous experimental and computational studies show that continuous hopper flows of granular materials obey the Beverloo equation that relates the volume flow rate $Q$ and the orifice width $w$: $Q \sim (w/\sigma_{\rm avg}-k)^{\beta}$, where $\sigma_{\rm avg}$ is the average particle diameter, $k\sigma_{\rm avg}$ is an offset where $Q\sim 0$, the power-law scaling exponent $\beta=d-1/2$, and $d$ is the spatial dimension. Recent studies of hopper flows of deformable particles in different background fluids suggest that the particle stiffness and dissipation mechanism can also strongly affect the power-law scaling exponent $\beta$. We carry out computational studies of hopper flows of deformable particles with both kinetic friction and background fluid dissipation in two and three dimensions. We show that the exponent $\beta$ varies continuously with the ratio of the viscous drag to the kinetic friction coefficient, $\lambda=\zeta/\mu$. $\beta = d-1/2$ in the $\lambda \rightarrow 0$ limit and $d-3/2$ in the $\lambda \rightarrow \infty$ limit, with a midpoint $\lambda_c$ that depends on the hopper opening angle $\theta_w$. We also characterize the spatial structure of the flows and associate changes in spatial structure of the hopper flows to changes in the exponent $\beta$. The offset $k$ increases with particle stiffness until $k \sim k_{\rm max}$ in the hard-particle limit, where $k_{\rm max} \sim 3.5$ is larger for $\lambda \rightarrow \infty$ compared to that for $\lambda \rightarrow 0$. Finally, we show that the simulations of hopper flows of deformable particles in the $\lambda \rightarrow \infty$ limit recapitulate the experimental results for quasi-2D hopper flows of oil droplets in water., Comment: 15 pages, 12 figures

The flow-induced vibration (FIV) of multi cylinders is a problem involving the safety of fluid engineering and energy harvesting. Due to the effect of wake galloping and vortex induced vibration (VIV), the mechanism of two tandem cylinders is more complex than that of a single cylinder. In this study, the vibration modes of two tandem cylinders with different spans (L/D = 1.5–4.0) are investigated at subcritical Reynolds number and high mass damping ratio through wind tunnel tests. In the experiment, the cylinders are free to vibrate in the transverse and in-flow direction. The characteristics of the vibration amplitude and vibration frequency response are discussed with the vibration mode. The results show that the vibration mode is related to the reduced pitches between the cylinders. The vibration of the two tandem cylinder system is combines results of vortex induced vibration and wake induced galloping (WIG). When the span is lower than 2.0, the galloping effect is more obvious than that of larger spans cylinders at the experiment mass damping parameters. The two cylinders turn to vibrate separately as the span grows larger.

BACKGROUND AND OBJECTIVES There remains a need to objectively monitor burn wound healing within a clinical setting, and optical coherence tomography (OCT) is proving itself one of the ideal modalities for just such a use. The aim of this study is to utilize the noninvasive and multipurpose capabilities of OCT, along with its cellular-level resolution, to demonstrate the application of optical attenuation coefficient (OAC), as derived from OCT data, to facilitate the automatic digital segmentation of the epidermis from scan images and to work as an objective indicator for burn wound healing assessment. STUDY DESIGN/MATERIALS AND METHODS A simple, yet efficient, method was used to estimate OAC from OCT images taken over multiple time points following acute burn injury. This method enhanced dermal-epidermal junction (DEJ) contrast, which facilitated the automatic segmentation of the epidermis for subsequent thickness measurements. In addition, we also measured and compared the average OAC of the dermis within said burns for correlative purposes. RESULTS Compared with unaltered OCT maps, enhanced DEJ contrast was shown in OAC maps, both from single A-lines and completed B-frames. En face epidermal thickness and dermal OAC maps both demonstrated significant changes between imaging sessions following burn injury, such as a loss of epidermal texture and decreased OAC. Quantitative analysis also showed that OAC of acute burned skin decreased below that of healthy skin following injury. CONCLUSIONS Our study has demonstrated that the OAC estimated from OCT data can be used to enhance imaging contrast to facilitate the automatic segmentation of the epidermal layer, as well as help elucidate our understanding of the pathological changes that occur in human skin when exposed to acute burn injury, which could serve as an objective indicator of skin injury and healing.

Molecular detection of disease-associated mutations, especially those with low abundance, is essential for academic research and clinical diagnosis. Certain variant detection methods reach satisfactory sensitivity and specificity in detecting rare mutations based on the introduction of blocking oligos to prevent the amplification of wild-type or unwanted templates, thus selectively amplifying and enriching the mutations. These blocking oligos usually suppress PCR amplification through the 3' chemical modifications, with high price, slow synthesis, and reduced purity. Herein, we introduce chemistry-free designs to block enzymatic extension during PCR by the steric hindrance from the secondary structures attached to the 3' end of the oligos (nonextensible oligonucleotide, NEO). We demonstrated that NEO efficiently prohibited the extension of both Taq and high-fidelity DNA polymerases. By further applying NEO as blockers in blocker displacement amplification (BDA) qPCR, multiplex BDA (mBDA) NGS, and quantitative BDA (QBDA) NGS methods, we showed that NEO blockers had performance comparable with previously validated chemical modifications. Comparison experiments using QBDA with NEO blockers and droplet digital PCR (ddPCR) on clinical formalin-fixed paraffin-embedded (FFPE) samples exhibited 100% concordance. Lastly, the ability of NEO to adjust plex uniformity through changes of PCR amplification efficiency was demonstrated in an 80-plex NGS panel.

Oxidative stress (OS) and immune inflammation play complex intersections in the pathophysiology of ischemic stroke (IS). However, a competing endogenous RNA- (ceRNA-) based mechanism linked to the intersections in IS has not been explored. We aimed to identify potential OS-related signatures and analyze immune infiltration characteristics in IS.Three datasets (GSE22255, GSE110993, and GSE140275) from the GEO database were extracted. Differentially expressed long noncoding RNAs, microRNAs, and messenger RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) between IS patients and controls were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were explored. Moreover, a triple ceRNA network was constructed to reveal transcriptional regulation mechanisms. A comprehensive strategy among least absolute shrinkage and selection operator (LASSO) regression, DEmRNAs, uprelated DEmRNAs, and OS-related genes was adopted to select the best signature. Then, we evaluated and verified the discriminant ability of the signature via receiver operating characteristic (ROC) analysis. Immune infiltration characteristics were explored via the CIBERSORT algorithm. Moreover, the best signature was verified via qPCR and western blot methods in rat brain tissues and PC12 cells.11 DEmRNAs were identified totally. Enrichment analysis showed that the DEmRNAs were primarily concentrated in MAPK-associated biological processes and immune or inflammation-involved pathways.This study identified the ceRNA-based

Clinically and biologically, rare DNA sequence variants are significant and informative. However, existing common detection technologies are either complex and time-consuming in workflow, or restricted in the limit of detection (LoD), or do not allow for multiplexing. Blocker displacement amplification (BDA) method can stably and effectively detect and enrich multiple rare variants with LoD around 0.1% variant allele fraction (VAF). Nonetheless, the detailed mutation information has to be identified by additional sequencing technologies. Here, we present allele-specific BDA (As-BDA), a method combining BDA with allele-specific TaqMan (As-TaqMan) probes for effective variant enrichment and simultaneous single nucleotide variant or small insertions and deletions (INDELs) profiling. We demonstrated that As-BDA could detect mutations down to 0.01% VAF. Further, As-BDA could detect up to four mutations with low to 0.1% VAF per reaction using only 15 ng DNA input. The median error of As-BDA in VAF determination is approximately 9.1%. Comparison experiments using As-BDA and droplet digital PCR on peripheral blood mononuclear cell clinical samples showed 100% concordance for samples with mutations at ≥ 0.1% VAF. Hence, we have shown that As-BDA can achieve simultaneous enrichment and identification of multiple targeted mutations within the same reaction with high clinical sensitivity and specificity, thus helpful for clinical diagnosis.

A deep learning algorithm was developed to automatically identify, segment, and quantify geographic atrophy (GA) based on optical attenuation coefficients (OACs) calculated from optical coherence tomography (OCT) datasets. Normal eyes and eyes with GA secondary to age-related macular degeneration were imaged with swept-source OCT using 6 × 6 mm scanning patterns. OACs calculated from OCT scans were used to generate customized composite en face OAC images. GA lesions were identified and measured using customized en face sub-retinal pigment epithelium (subRPE) OCT images. Two deep learning models with the same U-Net architecture were trained using OAC images and subRPE OCT images. Model performance was evaluated using DICE similarity coefficients (DSCs). The GA areas were calculated and compared with manual segmentations using Pearson’s correlation and Bland-Altman plots. In total, 80 GA eyes and 60 normal eyes were included in this study, out of which, 16 GA eyes and 12 normal eyes were used to test the models. Both models identified GA with 100% sensitivity and specificity on the subject level. With the GA eyes, the model trained with OAC images achieved significantly higher DSCs, stronger correlation to manual results and smaller mean bias than the model trained with subRPE OCT images (0.940 ± 0.032 vs 0.889 ± 0.056, p = 0.03, paired t-test, r = 0.995 vs r = 0.959, mean bias = 0.011 mm vs mean bias = 0.117 mm). In summary, the proposed deep learning model using composite OAC images effectively and accurately identified, segmented, and quantified GA using OCT scans.

Effective polymerase chain reactions (PCR) are important in bio-laboratories. It is essential to detect rare DNA-sequence variants for early cancer diagnosis or for drug-resistance mutations identification. Some of the common detection quantitative PCR (qPCR) methods are restricted in the limit of detection (LoD) because of the high polymerase misincorporation rate in Taq DNA polymerases. High-fidelity (HiFi) DNA polymerases have a 50- to 250-fold higher fidelity. Yet, there are currently no proper designs for multiplexed HiFi qPCR reactions. Moreover, the popularity of targeting highly multiplex DNA sequences requires minimizing PCR side products, as the potential of dimerization grows quadratically as the plexes of primers increases. Efforts tried before were either an add-on step, or technology-specific, or requiring high-level computing skills. There lacks an easy-to-apply and cost-effective method for dimerization reduction. Here, we presented the Occlusion System, composed of a 59-overhanged primer and a probe with a short-stem hairpin. We demonstrated that it allowed multiplexing high-fidelity qPCR reaction, it was also compatible with the current variant-enrichment method to improve the LoD by 10-fold. Further, we found that the Occlusion System reduced the dimerization up to 10-fold in highly multiplexed PCR. Thus, the Occlusion System satisfactorily improved both qPCR sensitivity and PCR efficiency.

Quantitation of rare somatic mutations is essential for basic research and translational clinical applications including minimal residual disease (MRD) detection. Though unique molecular identifier (UMI) has suppressed errors for rare mutation detection, the sequencing depth requirement is high. Here, we present Quantitative Blocker Displacement Amplification (QBDA) which integrates sequence-selective variant enrichment into UMI quantitation for accurate quantitation of mutations below 0.01% VAF at only 23,000X depth. Using a panel of 20 genes recurrently altered in acute myeloid leukemia, we demonstrate quantitation of various mutations including single base substitutions and indels down to 0.001% VAF at a single locus with less than 4 million sequencing reads, allowing sensitive MRD detection in patients during complete remission. In a pan-cancer panel and a melanoma hotspot panel, we detect mutations down to 0.1% VAF using only 1 million reads. QBDA provides a convenient and versatile method for sensitive mutation quantitation using low-depth sequencing., Quantification of rare somatic mutations is essential for basic research and translational applications. Here the authors present Quantitative Blocker Displacement Amplification allowing for accurate detection of mutations below 0.01% VAF.

Direct capture and sequencing revealed a new DNA population in biofluids, named ultra-short single-stranded DNA (ussDNA), which was neglected by conventional DNA extraction and sequencing approaches. Evaluation of the size distribution and abundance of ussDNA in biofluids manifested generality of its presence in human, animal, and plants. Red blood cells were found to contain abundant ussDNA with enriched functional elements, and thus possesses great potential as a novel DNA biomarker.

Clinically and biologically, rare DNA sequence variants are significant and informative. However, existing detection technologies are either complex in workflow, or restricted in the limit of detection (LoD), or do not allow for multiplexing. Blocker displacement amplification (BDA) method can stably and effectively detect and enrich multiple rare variants with LoD around 0.1% variant allele fraction (VAF). Nonetheless, the detailed mutation information has to be identified by additional sequencing technologies. Here, we present allele-specific BDA (As-BDA), a method combining BDA with allele-specific TaqMan (As-TaqMan) probes for effective variant enrichment and simultaneous SNV profiling. We demonstrated that As-BDA could detect mutations down to 0.01% VAF. Further, As-BDA could detect up to four mutations with low to 0.1% VAF per reaction using only 15 ng DNA input. The median error of As-BDA in VAF determination is approximately 9.1%. Comparison experiments using As-BDA and droplet digital PCR (ddPCR) on peripheral blood mononuclear cell (PBMC) clinical samples showed 100% concordance for samples with mutations at ≥ 0.1% VAF. Hence, we have shown that As-BDA can achieve simultaneous enrichment and identification of multiple targeted mutations within the same reaction with high clinical sensitivity and specificity, thus helpful for clinical diagnosis.