Bachelor of Science, Zhejiang University (2011)
Doctor of Philosophy, Zhejiang University (2016)
A label-free optical sensor was constructed by integrating electrochemically etched porous silicon (pSi) and supported phospholipid bilayers in a microfluidic chip. The translocation of peptides through the phospholipid bilayers could induce a red shift in effective optical thickness of the pSi layer, which could be monitored by reflective interferometric Fourier transform spectroscopy. By measuring the kinetic data of membrane translocating on the phospholipid bilayers/pSi chip, the relationship between the behavior of membrane-translocating peptides (MTPs) and translocating mechanism was established. With these optical data, MTPs with different action modes on the cell membrane can be correctly discriminated. The bio-functionalized microfluidic sensor will provide a reliable and cost-effective platform to study the transmembrane behavior of peptides, which is of great importance in the MTP screening and peptide function study.
View details for DOI 10.1063/1.4971440
View details for Web of Science ID 000390113600014
View details for PubMedID 27990215
View details for PubMedCentralID PMC5135711
Bacteria detection plays an important role in the guarantee of food and water safety. This work proposed a new sensing strategy for the rapid detection of bacteria based on its blockage effect on nanopore array, which was prepared from electrochemically etched silicon. With the assistance of microfluidic technology, the nanopore array attached with Escherichia coli antibody can selectively and rapidly capture E. coli bacteria, resulting in the decrease of pore accessibility. The signal of pore blockage can be measured by in-direct Fourier Transformed Reflectometric Interference Spectroscopy (FT-RIS). The pore blockage signal has a linear relationship with the logarithm of bacterial density in aqueous sample within the range from 10(3) to 10(7)cfuml(-1). Due to the specific interaction between the antibody and target bacteria, only the E. coli sample displayed significant pore blockage effect, whereas the non-target bacteria, Nox and P17, almost did not show any pore blockage effect. The strategy established in this work might be pervasively applied in the rapid detection of target bacteria and cell in a label-free manner.
View details for DOI 10.1016/j.bios.2015.12.109
View details for Web of Science ID 000370309200098
View details for PubMedID 26774087
Kawasaki disease (KD) is an acute pediatric vasculitis of infants and young children with unknown etiology and no specific laboratory-based test to identify. A specific molecular diagnostic test is urgently needed to support the clinical decision of proper medical intervention, preventing subsequent complications of coronary artery aneurysms. We used a simple and low-cost colorimetric sensor array to address the lack of a specific diagnostic test to differentiate KD from febrile control (FC) patients with similar rash/fever illnesses.Demographic and clinical data were prospectively collected for subjects with KD and FCs under standard protocol. After screening using a genetic algorithm, eleven compounds including metalloporphyrins, pH indicators, redox indicators and solvatochromic dye categories, were selected from our chromatic compound library (n = 190) to construct a colorimetric sensor array for diagnosing KD. Quantitative color difference analysis led to a decision-tree-based KD diagnostic algorithm.This KD sensing array allowed the identification of 94% of KD subjects (receiver operating characteristic [ROC] area under the curve [AUC] 0.981) in the training set (33 KD, 33 FC) and 94% of KD subjects (ROC AUC: 0.873) in the testing set (16 KD, 17 FC). Color difference maps reconstructed from the digital images of the sensing compounds demonstrated distinctive patterns differentiating KD from FC patients.The colorimetric sensor array, composed of common used chemical compounds, is an easily accessible, low-cost method to realize the discrimination of subjects with KD from other febrile illness.
View details for DOI 10.1371/journal.pone.0146733
View details for Web of Science ID 000370038400003
View details for PubMedID 26859297
View details for PubMedCentralID PMC4747548
A label-free optical sensor was constructed by integrating pH sensing material and supported phospholipid bilayers (SPBs) in a microfluidic chip. The pH sensing material was composed of a double layer structure consisting of chitosan hydrogel and electrochemically etched porous silicon. The pH change in the microchip could induce a reversible swelling of the chitosan hydrogel layer and consequently caused a shift in effective optical thickness (EOT) of the double layer, which could be observed by Fourier transformed reflectometric interference spectroscopy (FT-RIS). After phospholipid bilayers (PLBs) were self-assembled on the sensing layer, the EOT almost remained constant during the cycling of pH from 7.4 to 6.2, indicating the blockage of H(+) translocation by the PLBs. For studying the behavior of ion channel protein, gramicidin A, a typical ion channel protein, was inserted in the SPBs for mimicking the ion transportation function of cell membrane. Due to the H(+) transportation capability of gramicidin A, the optical response to pH change could partially recover. In the presence of Ca(2+), the pore of the ion channel protein was blocked, causing a significant decrease in the EOT response upon pH change. The bio-functionalized microfluidic sensor fabricated in this work will provide a reliable platform for studying the function of ion channel protein, which is an important class of drug targets.
View details for DOI 10.1039/c3lc50937k
View details for Web of Science ID 000328910700009
View details for PubMedID 24232219
To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably developed after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In our controlled rat model study, matched ENU- and saline-exposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. Future characterization of the critical transition state (P60) during the brain tumor progression may reveal the underlying pathophysiology to device novel therapeutics preventing tumor formation. More detailed method and information are accessible through our website at http://translationalmedicine.stanford.edu.
View details for DOI 10.1016/j.ymeth.2015.05.004
View details for Web of Science ID 000358755100005
An easily accessible real-time Web-based utility to assess patient risks of future emergency department (ED) visits can help the health care provider guide the allocation of resources to better manage higher-risk patient populations and thereby reduce unnecessary use of EDs.Our main objective was to develop a Health Information Exchange-based, next 6-month ED risk surveillance system in the state of Maine.Data on electronic medical record (EMR) encounters integrated by HealthInfoNet (HIN), Maine's Health Information Exchange, were used to develop the Web-based surveillance system for a population ED future 6-month risk prediction. To model, a retrospective cohort of 829,641 patients with comprehensive clinical histories from January 1 to December 31, 2012 was used for training and then tested with a prospective cohort of 875,979 patients from July 1, 2012, to June 30, 2013.The multivariate statistical analysis identified 101 variables predictive of future defined 6-month risk of ED visit: 4 age groups, history of 8 different encounter types, history of 17 primary and 8 secondary diagnoses, 8 specific chronic diseases, 28 laboratory test results, history of 3 radiographic tests, and history of 25 outpatient prescription medications. The c-statistics for the retrospective and prospective cohorts were 0.739 and 0.732 respectively. Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. Cluster analysis in both the retrospective and prospective analyses revealed discrete subpopulations of high-risk patients, grouped around multiple "anchoring" demographics and chronic conditions. With the Web-based population risk-monitoring enterprise dashboards, the effectiveness of the active case finding algorithm has been validated by clinicians and caregivers in Maine.The active case finding model and associated real-time Web-based app were designed to track the evolving nature of total population risk, in a longitudinal manner, for ED visits across all payers, all diseases, and all age groups. Therefore, providers can implement targeted care management strategies to the patient subgroups with similar patterns of clinical histories, driving the delivery of more efficient and effective health care interventions. To the best of our knowledge, this prospectively validated EMR-based, Web-based tool is the first one to allow real-time total population risk assessment for statewide ED visits.
View details for DOI 10.2196/ijmr.4022
View details for PubMedID 25586600
View details for PubMedCentralID PMC4319080
Among patients who are discharged from the Emergency Department (ED), about 3% return within 30 days. Revisits can be related to the nature of the disease, medical errors, and/or inadequate diagnoses and treatment during their initial ED visit. Identification of high-risk patient population can help device new strategies for improved ED care with reduced ED utilization.A decision tree based model with discriminant Electronic Medical Record (EMR) features was developed and validated, estimating patient ED 30 day revisit risk. A retrospective cohort of 293,461 ED encounters from HealthInfoNet (HIN), Maine's Health Information Exchange (HIE), between January 1, 2012 and December 31, 2012, was assembled with the associated patients' demographic information and one-year clinical histories before the discharge date as the inputs. To validate, a prospective cohort of 193,886 encounters between January 1, 2013 and June 30, 2013 was constructed. The c-statistics for the retrospective and prospective predictions were 0.710 and 0.704 respectively. Clinical resource utilization, including ED use, was analyzed as a function of the ED risk score. Cluster analysis of high-risk patients identified discrete sub-populations with distinctive demographic, clinical and resource utilization patterns.Our ED 30-day revisit model was prospectively validated on the Maine State HIN secure statewide data system. Future integration of our ED predictive analytics into the ED care work flow may lead to increased opportunities for targeted care intervention to reduce ED resource burden and overall healthcare expense, and improve outcomes.
View details for DOI 10.1371/journal.pone.0112944
View details for PubMedID 25393305
View details for PubMedCentralID PMC4231082
For appropriate selection of antibiotics in the treatment of pathogen infection, rapid antibiotic susceptibility testing (AST) is urgently needed in clinical practice. This study reports the utilization of a microfluidic pH sensor for monitoring bacterial growth rate in culture media spiked with different kinds of antibiotics. The microfluidic pH sensor was fabricated by integration of pH-sensitive chitosan hydrogel with poly(dimethylsiloxane) (PDMS) microfluidic channels. For facilitating the reflectometric interference spectroscopic measurements, the chitosan hydrogel was coated on an electrochemically etched porous silicon chip, which was used as the substrate of the microfluidic channel. Real-time observation of the pH change in the microchannel can be realized by Fourier transform reflectometric interference spectroscopy (FT-RIFS), in which the effective optical thickness (EOT) was selected as the optical signal for indicating the reversible swelling process of chitosan hydrogel stimulated by pH change. With this microfluidic pH sensor, we demonstrate that confinement of bacterial cells in a nanoliter size channel allows rapid accumulation of metabolic products and eliminates the need for long-time preincubation, thus reducing the whole detection time. On the basis of this technology, the whole bacterial growth curve can be obtained in less than 2 h, and consequently rapid AST can be realized. Compared with conventional methods, the AST data acquired from the bacterial growth curve can provide more detailed information for studying the antimicrobial behavior of antibiotics during different stages. Furthermore, the new technology also provides a convenient method for rapid minimal inhibition concentration (MIC) determination of individual antibiotics or the combinations of antibiotics against human pathogens that will find application in clinical and point-of-care medicine.
View details for DOI 10.1021/ac303282j
View details for Web of Science ID 000317031600035
View details for PubMedID 23360389