Diagnostic accuracy of hemodynamic assessment of intracranial atherosclerotic stenosis from a single angiographic view: a validation study.

BACKGROUND: The aim of this study is to assess the feasibility of identifying the hemodynamic status of intracranial atherosclerotic stenosis (ICAS) using angio-based fractional flow (FF) calculated from a single angiographic view, with wire-based FF as the reference standard. METHOD: The study retrospectively recruited 100 ICAS patients who underwent pressure wire measurement and digital subtraction angiography. The AccuICAD software was used to calculate angio-based FF, with the wire-measured value serving as the reference standard for evaluating the accuracy, consistency, and diagnostic performance of angio-based FF. RESULTS: The mean±SD value of wire-based FF was 0.77±0.18, while the mean value of angio-based FF was 0.77±0.19. A good correlation between angio-based FF and wire-based FF was evident (r=0.90, P<0.001), with good agreement (mean difference 0.00±0.08). The diagnostic accuracy of angio-based FF and percent diameter stenosis (DS%) were 93.23% versus 72.18%, 91.73% versus 72.93%, and 89.47% versus 78.95% for predicted wire-based FF thresholds of 0.70, 0.75, and 0.80, respectively. The area under the curve (AUC) values for angio-based FF and DS% were 0.975 versus 0.822, 0.970 versus 0.814, and 0.943 versus 0.826 at the respective thresholds, respectively. CONCLUSION: The FF calculated from a single angiographic view can be considered an effective tool for functional assessment of cerebral arterial stenosis.

A flexible capacitive pressure sensor with a hybrid porous PDMS/SA hydrogel structure for touch/pain detection.

Exploring highly sensitive flexible electronic skins (e-skins) that can mimic the tactile and pain perception of human skin is an important prerequisite for achieving biomimetic robots and intelligent prosthetics. However, it is still difficult to realize both touch and pain sensing using a single pressure sensor. Herein, a novel flexible capacitive pressure sensor that can distinguish noxious pressure stimuli is proposed for detecting touch and pain, which is composed of a porous polydimethylsiloxane (PDMS) skeleton and a sodium alginate (SA) hydrogel core. The sensor employs two different working mechanisms depending on the range of external pressure, determining the mechanism of operation for transducing the sense of touch or pain. Such a unique structural design plays a crucial role in enhancing pain perception, leading to maximum sensitivity (14.25 kPa-1) in a large pressure regime (up to 400 kPa) and an adjustable pressure threshold. Moreover, the sensor also exhibits a fast response (45 ms) and recovery speed (70 ms), ensuring a sufficiently fast response to noxious pressure stimuli. Finally, we demonstrate the capabilities of a robotic hand based on the pressure sensor for precisely detecting both touch and pain, which shows great promise in developing intelligent robots and prosthetic limbs to prevent possible damage under external noxious stimuli.

Prevalence and clinical implications of calcification in internal carotid artery stenosis: a retrospective study.

BACKGROUND: Calcification is common in advanced atheromatous plaque, but its clinical significance remains unclear. This study aimed to assess the prevalence of plaque calcification in the moderate-to-severe internal carotid artery stenosis and investigate its relationship with ipsilateral ischemia. METHODS: The retrospective study included 178 patients detected with proximal internal carotid artery (pICA) stenosis of ≥ 50% on multidetector computed tomography at Zhejiang Hospital from January 2019 to March 2023. Association between plaque calcification characteristics (calcification thickness, position, type, circumferential extent, calcium volume and calcium score) and ipsilateral cerebrovascular events was analyzed. RESULTS: The 178 patients (mean age 71.24 ± 10.02 years, 79.78% males) had 224 stenosed pICAs overall. Plaque calcification was noted in 200/224 (89.29%) arteries. Calcification rates were higher in older age-groups. Calcification volume (r = 0.219, p < 0.001) and calcification score (r = 0.230, p < 0.001) were correlated with age. Ipsilateral ischemic events were significantly more common in the noncalcification group than in the calcification group (χ2 = 4.160, p = 0.041). The most common calcification type was positive rim sign calcification (87/200, 43.50%), followed by bulky calcification (66/200, 33.00%); both were significantly associated with ischemic events (χ2 = 10.448, p = 0.001 and χ2 = 4.552, p = 0.033, respectively). Calcification position, thickness, and circumferential extent, and calcification volume and score, were not associated with ischemic events. In multivariate analysis, positive rim signs (OR = 2.795, 95%CI 1.182-6.608, p = 0.019) was an independent predictor of ischemic events. CONCLUSIONS: Plaque calcification in proximal internal carotid artery is common, and prevalence increases with age. Calcification characteristics could be predictive of ipsilateral ischemic events. The positive rim sign within plaque is a high-risk factor for a future ischemic event.

Microglia in the hypothalamic paraventricular nucleus sense hemodynamic disturbance and promote sympathetic excitation in hypertension.

Hypertension is usually accompanied by elevated sympathetic tonicity, but how sympathetic hyperactivity is triggered is not clear. Recent advances revealed that microglia-centered neuroinflammation contributes to sympathetic excitation in hypertension. In this study, we performed a temporospatial analysis of microglia at both morphological and transcriptomic levels and found that microglia in the hypothalamic paraventricular nucleus (PVN), a sympathetic center, were early responders to hypertensive challenges. Vasculature analyses revealed that the PVN was characterized by high capillary density, thin vessel diameter, and complex vascular topology relative to other brain regions. As such, the PVN was susceptible to the penetration of ATP released from the vasculature in response to hemodynamic disturbance after blood pressure increase. Mechanistically, ATP ligation to microglial P2Y12 receptor was responsible for microglial inflammatory activation and the eventual sympathetic overflow. Together, these findings identified a distinct vasculature pattern rendering vulnerability of PVN pre-sympathetic neurons to hypertension-associated microglia-mediated inflammatory insults.

A Low-Power and Robust Micromachined Thermal Convective Accelerometer.

This paper presents a micromachined thermal convective accelerometer with low power and high reliability. This accelerometer comprises a heater and two thermistors. The central heater elevates the temperature of the chip above ambient levels while the symmetrically arranged thermistors monitor the temperature differentials induced by acceleration. The heater and thermistors are fabricated on a glass substrate using a standard micro-electromechanical systems (MEMS) process flow, and the fabricated sensor is installed on a rotation platform and a shaking table experimental setup to perform the experiment. The results indicate that the sensor has the capability to measure accelerations surpassing 80 m/s2, with an approximate linear sensitivity of 110.69 mV/g. This proposed thermal convective accelerometer offers promising potential for various applications requiring precise acceleration measurements in environments where low power consumption and high reliability are paramount.

Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit.

This study aimed to develop a machine learning (ML)-based tool for early and accurate prediction of in-hospital mortality risk in patients with spontaneous intracerebral hemorrhage (sICH) in the intensive care unit (ICU). We did a retrospective study in our study and identified cases of sICH from the MIMIC IV (n = 1486) and Zhejiang Hospital databases (n = 110). The model was constructed using features selected through LASSO regression. Among five well-known models, the selection of the best model was based on the area under the curve (AUC) in the validation cohort. We further analyzed calibration and decision curves to assess prediction results and visualized the impact of each variable on the model through SHapley Additive exPlanations. To facilitate accessibility, we also created a visual online calculation page for the model. The XGBoost exhibited high accuracy in both internal validation (AUC = 0.907) and external validation (AUC = 0.787) sets. Calibration curve and decision curve analyses showed that the model had no significant bias as well as being useful for supporting clinical decisions. XGBoost is an effective algorithm for predicting in-hospital mortality in patients with sICH, indicating its potential significance in the development of early warning systems.

Long-term causal effects estimation via latent surrogates representation learning.

Estimating long-term causal effects based on short-term surrogates is a significant but challenging problem in many real-world applications such as marketing and medicine. Most existing methods estimate causal effects in an idealistic and simplistic manner - disregarding unobserved surrogates and treating all short-term outcomes as surrogates. However, such methods are not well-suited to real-world scenarios where the partially observed surrogates are mixed with the proxies of unobserved surrogates among short-term outcomes. To address this issue, we develop our flexible method called LASER to estimate long-term causal effects in a more realistic situation where the surrogates are either observed or have observed proxies. In LASER, we employ an identifiable variational autoencoder to learn the latent surrogate representation by using all the surrogate candidates without the need to distinguish observed surrogates or proxies of unobserved surrogates. With the learned representation, we further devise a theoretically guaranteed and unbiased estimation of long-term causal effects. Extensive experimental results on the real-world and semi-synthetic datasets demonstrate the effectiveness of our proposed method.

Improved empirical mode decomposition method based on amplitude-frequency characteristic of vortex signals.

The vortex flowmeter occupies a vital position in flow measurement with its unique advantages. It is essentially a fluid vibration instrument, and its measurement process is susceptible to interference, which seriously affects measurement accuracy. In particular, at low flow rates, it is an urgent problem to extract vortex signals from the complex noise. Among many signal processing methods, Empirical Mode Decomposition (EMD) is a time-frequency analysis method suitable for nonlinear, non-stationary signals. EMD can adaptively decompose noisy signals into noise and useful signal components arranged from high frequency to low frequency. For the above problems, an innovative, improved EMD method is proposed in this paper. The digital filter is designed according to the amplitude-frequency characteristic of vortex signals. After filtering, the vortex signal is adjusted to a fixed value, and high-frequency noise is filtered. According to the consistency of the filtered signal's amplitude, we design a decomposition stop criterion for EMD to process the output signal of the vortex sensor. This method not only maintains the characteristic of adaptive decomposition in EMD but also completes the automatic extraction of the vortex signal under complex noise. It provides a new comprehensive method for realizing high-precision and anti-interference vortex flowmeters.

Cholinergic hyperintensity pathways are associated with cognitive performance in patients with asymptomatic carotid artery stenosis.

OBJECTIVES: We aimed to determine whether asymptomatic carotid artery stenosis (ACS) induced cognitive impairments were related to the cholinergic hyperintensity pathway. METHODS: This cross-sectional study included patients with moderate-to-severe ACS, who were categorized into mild cognitive impairment (MCI) and normal cognition groups on the basis of Montreal Cognitive Assessment (MoCA) scores. The cholinergic pathway hyperintensity scale (CHIPS), Fazekas, and medial temporal atrophy (MTA) scores were assessed. SPSS software was used for statistical analyses. RESULTS: A total of 117 ACS patients (70.89 ± 8.81 years) and 105 controls (67.87 ± 9.49 years) were evaluated (t = 2.46, p = 0.015). The ACS group showed a worse median Mini-Mental Status Examination (MMSE) score (z = -2.41, p = 0.016) and MoCA score (z = -3.51, p < 0.001), and a significantly higher median total CHIPS score (z = 4.88, p < 0.001) and mean Fazekas score (t = 2.39, p = 0.018). In the correlation analysis, the MoCA score showed a significant negative correlation with the CHIPS score (ρ = -0.41, p < 0.001) and Fazekas score (ρ = -0.31, p < 0.001) in ACS group. Logistic regression analyses suggested that CHIPS scores were risk factors for MCI in patients with ACS (odds ratio [OR] = 1.07, 95% Confidence Interval [CI]1.01-1.13 and controls (OR = 1.09, 95%CI 1.01-1.17), while the MTA and Fazekas scores showed no predictive power. The receiver operating characteristic curve showed that the area under the curve of the CHIPS score for predicting MCI was 0.71 in ACS group, but was only 0.57 in controls. CONCLUSIONS: Patients with ACS showed poorer cognitive performance and higher CHIPS and Fazekas scores. CHIPS, but not Fazekas, scores were risk factors for cognitive impairment and were a valuable factor to predict MCI in patients with ACS.

Metformin enhances METTL14-Mediated m6A methylation to alleviate NIT-1 cells apoptosis induced by hydrogen peroxide.

Injuries to pancreatic ß-cells are intricately linked to the onset of diabetes mellitus (DM). Metformin (Met), one of the most widely prescribed medications for diabetes and metabolic disorders, has been extensively studied for its antioxidant, anti-aging, anti-glycation, and hepatoprotective activities. N6-methyladenosine (m6A) plays a crucial role in the regulation of ß-cell growth and development, and its dysregulation is associated with metabolic disorders. This study aimed to elucidate the mechanistic basis of m6A involvement in the protective effects of Met against oxidative damage in pancreatic ß-cells. Hydrogen peroxide (H2O2) was employed to induce ß-cell damage. Remarkably, Met treatment effectively increased methylation levels and the expression of the methyltransferase METTL14, subsequently reducing H2O2-induced apoptosis. Knocking down METTL14 expression using siRNA significantly compromised cell viability. Conversely, targeted overexpression of METTL14 specifically in ß-cells substantially enhanced their capacity to withstand H2O2-induced stress. Molecular evidence suggests that the anti-apoptotic properties of Met may be mediated through Bcl-xL and Bim proteins. In conclusion, our findings indicate that Met induces METTL14-mediated alterations in m6A methylation levels, thereby shielding ß-cells from apoptosis and oxidative damage induced by oxidative stress.

Effectiveness and Safety of Chinese Herbal Injections Combined with SOX Chemotherapy Regimens for Advanced Gastric Cancer: a Bayesian Network Meta-Analysis.

Background: Randomized controlled trials (RCTs) have demonstrated that combining Chinese herbal injections (CHIs) with oxaliplatin plus tegafur (SOX) chemotherapy regimens improves clinical effectiveness and reduces adverse reactions in patients with advanced gastric cancer (AGC). These RCTs highlight the potential applications of CHIs and their impact on AGC patient prognosis. However, there is insufficient comparative evidence on the clinical effectiveness and safety of different CHIs when combined with SOX. Therefore, we performed a network meta-analysis to rank the clinical effectiveness and safety of different CHIs when combined with SOX chemotherapy regimens. This study aimed to provide evidence for selecting appropriate CHIs in the treatment of patients with AGC. Methods: We searched eight databases from their inception until March 2023. Surface Under the Cumulative Ranking Curve (SUCRA) probability values were used to rank the treatment measures, and the Confidence in Network Meta-Analysis (CINeMA) software assessed the grading of evidence. Results: A total of 51 RCTs involving 3,703 AGC patients were identified. Huachansu injections + SOX demonstrated the highest clinical effectiveness (SUCRA: 78.17%), significantly reducing the incidence of leukopenia (93.35%), thrombocytopenia (80.19%), and nausea and vomiting (95.15%). Shenfu injections + SOX improved Karnofsky's Performance Status (75.59%) and showed a significant reduction in peripheral neurotoxicity incidence (88.26%). Aidi injections + SOX were most effective in reducing the incidence of liver function damage (75.16%). According to CINeMA, most confidence rating results were classified as "low". Conclusion: The combination of CHIs and SOX shows promising effects in the treatment of AGC compared to SOX alone. Huachansu and Shenfu injections offer the greatest overall advantage among the CHIs, while Aidi injections are optimal for reducing the incidence of liver damage. However, further rigorous RCTs with larger sample sizes and additional pharmacological studies are necessary to reinforce these findings.

Increased serum extrachromosomal circular DNA SORBS1circle level is associated with insulin resistance in patients with newly diagnosed type 2 diabetes mellitus.

BACKGROUND: Extrachromosomal circular DNAs (eccDNAs) exist in human blood and somatic cells, and are essential for oncogene plasticity and drug resistance. However, the presence and impact of eccDNAs in type 2 diabetes mellitus (T2DM) remains inadequately understood. METHODS: We purified and sequenced the serum eccDNAs obtained from newly diagnosed T2DM patients and normal control (NC) subjects using Circle-sequencing. We validated the level of a novel circulating eccDNA named sorbin and SH3-domain- containing-1circle97206791-97208025 (SORBS1circle) in 106 newly diagnosed T2DM patients. The relationship between eccDNA SORBS1circle and clinical data was analyzed. Furthermore, we explored the source and expression level of eccDNA SORBS1circle in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. RESULTS: A total of 22,543 and 19,195 eccDNAs were found in serum samples obtained from newly diagnosed T2DM patients and NC subjects, respectively. The T2DM patients had a greater distribution of eccDNA on chromosomes 1, 14, 16, 17, 18, 19, 20 and X. Additionally, 598 serum eccDNAs were found to be upregulated, while 856 eccDNAs were downregulated in T2DM patients compared with NC subjects. KEGG analysis demonstrated that the genes carried by eccDNAs were mainly associated with insulin resistance. Moreover, it was validated that the eccDNA SORBS1circle was significantly increased in serum of newly diagnosed T2DM patients (106 T2DM patients vs. 40 NC subjects). The serum eccDNA SORBS1circle content was positively correlated with the levels of glycosylated hemoglobin A1C (HbA1C) and homeostasis model assessment of insulin resistance (HOMA-IR) in T2DM patients. Intracellular eccDNA SORBS1circle expression was significantly enhanced in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. Moreover, the upregulation of eccDNA SORBS1circle in the HG/PA-treated HepG2 cells was dependent on generation of apoptotic DNA fragmentation. CONCLUSIONS: These results provide a preliminary understanding of the circulating eccDNA patterns at the early stage of T2DM and suggest that eccDNA SORBS1circle may be involved in the development of insulin resistance.

Automated ASPECTS calculation may equal the performance of experienced clinicians: a machine learning study based on a large cohort.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS) is a semi-quantitative method to evaluate the severity of early ischemic change on non-contrast computed tomography (NCCT) in patients with acute ischemic stroke (AIS). In this work, we propose an automated ASPECTS method based on large cohort of data and machine learning. METHODS: For this study, we collected 3626 NCCT cases from multiple centers and annotated directly on this dataset by neurologists. Based on image analysis and machine learning methods, we constructed a two-stage machine learning model. The validity and reliability of this automated ASPECTS method were tested on an independent external validation set of 300 cases. Statistical analyses on the total ASPECTS, dichotomized ASPECTS, and region-level ASPECTS were presented. RESULTS: On an independent external validation set of 300 cases, for the total ASPECTS results, the intraclass correlation coefficient between automated ASPECTS and expert-rated was 0.842. The agreement between ASPECTS threshold of ≥ 6 versus < 6 using a dichotomized method was moderate (κ = 0.438, 0.391-0.477), and the detection rate (sensitivity) was 86.5% for patients with ASPECTS threshold of ≥ 6. Compared with the results of previous studies, our method achieved a slight lead in sensitivity (67.8%) and AUC (0.845), with comparable accuracy (78.9%) and specificity (81.2%). CONCLUSION: The proposed automated ASPECTS method driven by a large cohort of NCCT images performed equally well compared with expert-rated ASPECTS. This work further demonstrates the validity and reliability of automated ASPECTS evaluation method. CLINICAL RELEVANCE STATEMENT: The automated ASPECTS method proposed by this study may help AIS patients to receive rapid intervention, but should not be used as a stand-alone diagnostic basis. KEY POINTS: NCCT-based manual ASPECTS scores were poorly consistent. Machine learning can automate the ASPECTS scoring process. Machine learning model design based on large cohort data can effectively improve the consistency of ASPECTS scores.

Hemodynamic assessment for intracranial atherosclerosis from angiographic images: a clinical validation study.

BACKGROUND: Intracranial atherosclerotic stenosis (ICAS) is one of the leading causes of ischemic stroke. Conventional anatomical analysis by CT angiography, MRI, or digital subtraction angiography can provide valuable information on the anatomical changes of stenosis; however, they are not sufficient to accurately evaluate the hemodynamic severity of ICAS. The goal of this study was to assess the diagnostic performance of the pressure ratio across intracranial stenoses (termed as fractional flow (FF)) derived from cerebral angiography for the diagnosis of hemodynamically significant ICAS defined by pressure wire-derived FF. METHODS: This retrospective study represents a feasible and reliable method for calculating the FF from cerebral angiography (AccuFFicas). Patients (n=121) who had undergone wire-based measurement of FF and cerebral angiography were recruited. The accuracy of the computed pressure ratio was evaluated using wire-based FF as the reference standard. RESULTS: The mean value of wire-based FF was 0.78±0.19, while the computed AccuFFicas had an average value of 0.79±0.18. Good correlation (Pearson's correlation coefficient r=0.92, P<0.001) between AccuFFicas and FF was observed. Bland-Altman analysis showed that the mean difference between AccuFFicas and FF was -0.01±0.07, indicating good agreement. The area under the curve (AUC) of AccuFFicas in predicting FF≤0.70, FF≤0.75, and FF≤0.80 was 0.984, 0.986, and 0.962, respectively. CONCLUSION: Angiography-based FF computed from cerebral angiographic images could be an effective computational tool for evaluating the hemodynamic significance of ICAS.

An integral blood-brain barrier in adulthood relies on microglia-derived PDGFB.

Pericyte is an indispensable cellular constituent of blood-brain barrier (BBB) and its homeostasis heavily rely on PDGFB-PDGFRß signaling. However, the primary cellular sources of PDGFB in the central nervous system (CNS) are unclear. Microglia is not considered a component of BBB and its role in maintaining BBB integrity in steady state is controversial. In this study, by analyzing transcriptomic data and performing in situ hybridization, we revealed a transition of the primary central PDGFB producers from endothelial cells in newborns to microglia in adults. Acute loss of microglial PDGFB profoundly impaired BBB integrity in adult but not newborn mice, and thus, adult mice deficient of microglial PDGFB could not survive from a sublethal endotoxin challenge due to rampant microhemorrhages in the CNS. In contrast, acute abrogation of endothelial PDGFB had minimal effects on the BBB of adult mice but led to a severe impairment of CNS vasculature in the neonates. Moreover, we found that microglia would respond to a variety of BBB insults by upregulating PDGFB expression. These findings underscore the physiological importance of the microglia-derived PDGFB to the BBB integrity of adult mice both in steady state and under injury.

Lambda-free light chain: A serum marker of dengue disease via NS3 protease-mediated antibody cleavage.

Dengue poses a significant global public health threat, with diverse clinical manifestations due to complex interactions between the host and the pathogen. Recent reports have highlighted elevated serum-free light chain (FLC) levels in viral infectious diseases. Hence, our study aimed to investigate serum FLC levels in dengue patients. The findings revealed elevated serum λ FLCs, which were associated with the severity of dengue. Receiver operating characteristic curve (ROC) analysis demonstrated that λ FLCs may serve as a serum marker for identifying dengue disease (AUC: 0.7825, sensitivity: 80, specificity: 71.43) and classifying severe dengue (AUC: 0.8102, sensitivity: 75, specificity: 79.52). The viral protease, Dengue virus (DENV) nonstructural protein 3 (NS3), acts as a protease that cleaves viral polyproteins as well as host substrates. Therefore, we proposed that antibodies might be potential targets of NS3 protease, leading to an increase in FLCs. LC/MS-MS analysis confirmed that λ FLCs were the predominant products after antibody degradation by NS3 protease. Additionally, purified NS3 protease cleaved both human IgG and DENV2-neutralizing antibodies, resulting in the presence of λ FLCs. Moreover, NS3 protease administration in vitro led to a reduction in the neutralizing efficacy of DENV2-neutralizing antibodies. In summary, the elevated serum λ FLC levels effectively differentiate dengue patients from healthy individuals and identify severe dengue. Furthermore, the elevation of serum λ FLCs is, at least in part, mediated through NS3 protease-mediated antibody cleavage. These findings provide new insights for developing diagnostic tools and understanding the pathogenesis of DENV infection.

Antibody Profiling of Dengue Severities Using Flavivirus Protein Microarrays.

Dengue is a viral disease transmitted by Aedes aegypti mosquitoes. According to the World Health Organization, about half of the world's population is at risk of dengue. There are four serotypes of the dengue virus. After infection with one serotype, it will be immune to such a serotype. However, subsequent infection with other serotypes will increase the risk of severe outcomes, e.g., dengue hemorrhagic fever, dengue shock syndrome, and even death. Since severe dengue is challenging to predict and lacks molecular markers, we aim to build a multiplexed Flavivirus protein microarray (Flaviarray) that includes all of the common Flaviviruses to profile the humoral immunity and cross-reactivity in the dengue patients with different outcomes. The Flaviarrays we fabricated contained 17 Flavivirus antigens with high reproducibility (R-square = 0.96) and low detection limits (172-214 pg). We collected serums from healthy subjects (n = 36) and dengue patients within 7 days after symptom onset (mild dengue (n = 21), hospitalized nonsevere dengue (n = 29), and severe dengue (n = 36)). After profiling the serum antibodies using Flaviarrays, we found that patients with severe dengue showed higher IgG levels against multiple Flavivirus antigens. With logistic regression, we found groups of markers with high performance in distinguishing dengue patients from healthy controls as well as hospitalized from mild cases (AUC > 0.9). We further reported some single markers that were suitable to separate dengue patients from healthy controls (AUC > 0.9) and hospitalized from mild outcomes (AUC > 0.8). Together, Flaviarray is a valuable tool to profile antibody specificities, uncover novel markers for decision-making, and shed some light on early preventions and treatments.