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Corneal epithelial healing after refractive surgery is a clinically significant issue, especially for surface ablation procedures, and this can be monitored using optical coherence tomography (OCT). The aim of this work is to investigate the corneal epithelial thickness and irregularity by OCT after transepithelial photorefractive keratectomy (t-PRK) and analyse its correlation with visual and refractive outcomes. Patients aged ≥18 years with myopia, with or without astigmatism, who underwent t-PRK between May 2020 and August 2021 were included. All participants were subjected to complete ophthalmic examinations and OCT pachymetry at every follow-up visit. Patients were followed up at 1 week and 1, 3, and 6 months postoperatively. A total of 67 patients (126 eyes) were enrolled in this study. One month postoperatively, spherical equivalent refraction and visual acuity achieved preliminary stability. However, central corneal epithelial thickness (CCET) and standard deviation of the corneal epithelial thickness (SDcet) took 3–6 months to progressive recovery. Patients with higher baseline spherical equivalent refraction were associated with slower epithelial recovery. At every follow-up time point, a significant superior-inferior difference in the minimum corneal epithelial thickness area was observed. Higher stromal haze was correlated with higher spherical equivalent refraction (both baseline and residual) but had no relation with visual outcomes. There was a significant correlation between higher CCET with a better uncorrected distance visual acuity and lower corneal epithelial thickness irregularity. CCET and SDcet measured by OCT seem to be a good auxiliary indicator for reflecting the status of corneal wound recovery after t-PRK surgery. However, a well-designed randomised control study is needed to confirm the study results.

Plant fiber/plastic composites (PPCs) have been widely used in food contact materials (FCMs) for many benefits, such as their claimed better environmental footprint compared to conventional plastics. However, their safety is still not fully understood and must be comprehensively evaluated. Non-volatiles extracted from six PPCs with different plant fibers and polymer matrices were characterized by employing ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry in combination with various spectral libraries and manual elucidation, taking into account spectral similarity and characteristic product ions. A total of 115 compounds were tentatively identified, 50 of which were oligomers or their derivatives from the sample with polylactic acid (PLA) and polybutylene adipate terephthalate (PBAT) as the polymer matrix, and some of them were Cramer rules class III substances based on the threshold of toxicological concern (TTC). Seven reaction products between PLA and PBAT monomers, as well as four derivatives of melamine, were elucidated and well detailed for the first time. In addition, bisphenol S was detected in all samples even though its origin remains to be further explored. Isoprothiolane, as an insecticide and fungicide used to control a range of rice pests, was identified in the sample with rice husk as fillers, experimentally confirming the presence of agrochemicals in samples containing plant fibers.

Providing early predictions of academic performance is necessary for identifying at-risk students and subsequently providing them with timely intervention for critical factors affecting their academic performance. Although e-book systems are often used to provide students with teaching/learning materials in university courses, seldom has research made the early prediction based on their online reading behaviours by implementing machine learning classifiers. This study explored to what extent university students’ academic achievement can be predicted, based on their reading behaviours in an e-book supported course, using the classifiers. It further investigated which of the features extracted from the reading logs influence the predictions. The participants were 100 first-year undergraduates enrolled in a compulsory course at a university in Taiwan. The results suggest that logistic regression supports vector classification, decision trees, and random forests, and neural networks achieved moderate prediction performance with accuracy, precision, and recall metrics. The Bayes classifier identified almost all at-risk students. Additionally, student online reading behaviours affecting the prediction models included: turning pages, going back to previous pages and jumping to other pages, adding/deleting markers, and editing/removing memos. These behaviours were significantly positively correlated to academic achievement and should be encouraged during courses supported by e-books. Implications for practice or policy: For identifying at-risk students, educators could prioritise using Gaussian naïve Bayes in an e-book supported course, as it shows almost perfect recall performance. Assessors could give priority to logistic regression and neural networks in this context because they have stable achievement prediction performance with different evaluation metrics. The prediction models are strongly affected by student online reading behaviours, in particular by locating/returning to relevant pages and modifying markers.

Extracellular vesicles (EVs) contain abundant extracellular RNA (exRNA), which can be a valuable source of liquid biopsy. However, as various RNA species exist in different types of EVs, lack of detailed characterization of these RNA species and efficient collection methods limits the clinical application of exRNA. In the present study, we measured two mRNAs, CK19 and PCTK1; one lncRNA, MALAT1; and two miRNAs, miR21 and miR155, in different EV fractions separated by differential centrifugation or captured by magnetic beads coated with annexin A5 (ANX beads). The results showed that in a cultured medium, the majority of mRNA and lncRNA exist in larger EVs, whereas miRNA exist in both large and small EVs from the differential centrifugation fractions. All these RNA species exist in ANX beads captured EVs. We then used ANX beads to capture EVs in plasma samples from non-small-cell lung cancer patients and age-matched healthy volunteers. We found that the ANX bead capturing could efficiently improve RNA detection from human plasma, compared with direct extraction of RNA from plasma. Using ANX-bead capturing and reverse transcription and quantitative PCR, we detected significantly higher levels of CK19 mRNA, MALAT1 lncRNA, and miR155 miRNA in the plasma of lung cancer patients. These facts suggested the collection methods strongly affect the results of exRNA measurement from EVs, and that ANX beads can be a useful tool for detecting exRNA from plasma samples in clinical application.

Organic dyes are typically applied as photosensitizers in photoelectrochemical (PEC) cells but have not been reported in polarity-reversal-mode PEC sensors with excellent sensitivity and accuracy. Herein, an elegant and robust PEC biosensor for carcinoembryonic antigen (CEA) has been designed by photocurrent polarity switching of CdTe quantum dots (QDs), which is obtained by embedding methylene blue (MB) into amplified double-stranded DNA (dsDNA) anchored to the superparamagnetic Fe3O4@SiO2. The target-triggered Exo III-assisted cyclic amplification strategy and in situ magnetic enrichment enable the remarkable sensitivity. The extraction of target-analogue single-stranded DNA (output DNA) contributes to high selectivity resulting from the elimination of possible interferences in real samples or matrixes. Particularly, this exclusive polarity-reversal-mode PEC aptasensing can efficiently eliminate the false-positive or false-negative signals, leading to accurate measurements. Moreover, different from the probes and layer-by-layer assembled photoelectric beacons on electrodes in advance, this rational split-type approach is doomed to help the PEC biosensor with additional merits of convenient fabrication, short time consumption, wider linearity, as well as outstanding reproducibility and stability in practical applications. In light of the ability of MB acting as a kind of signal probe in typical electrochemical sensors, certainly, this ingenious design can not only be extended to a wide variety of target monitoring but also provide new ideas for the construction of high-performance electrochemical and PEC biosensors.

Analysis of cortisol levels in human sweat is increasingly important as it can be a "stress biomarker" in stress-related disorders, giving real-time information about human health status. In this study, a portable 3D microfluidic origami biosensor based on a smartphone was developed for cortisol-level detection in human sweat. Molybdenum disulfide (MoS

MicroRNA (miRNA) has become a key indicator of cancer diagnosis based on its abnormal expression levels. However, high-performance monitoring of miRNA is still a difficult task because of its low concentration, small size, and similarity of sequences. Herein, an elegant and robust photoelectrochemical (PEC) biosensor for miRNA-122 has been flexibly designed based on the split mode between entropy-driven DNA signal amplification and photocurrent expression. The entropy-driven DNA circuit uses a multichain composite structure instead of a DNA hairpin structure, leading to decrease the reversibility of each step of the signal amplification system. Also, the unique increasing entropy mechanism, rather than the free energy release from the new base pairs forming, improves the reaction efficiency and enhances more thermal stability and strong specific identification ability. Particularly, the biologically functionalized superparamagnetic Fe3O4@SiO2 complex endows this split mode PEC biosensor with excellent specificity and enhanced efficiency of electrode fabrication. Additionally, this strategy of only the CdTe-signal DNA modified on the ITO electrode for photocurrent readout overcomes the shortcomings of tediously long layer-by-layer assembly process and multiple rinsing steps, leading to efficient improvement of the stability and reproducibility for the as-designed PEC biosensor. This elegant strategy opens a new path for miRNA measurements with superior performance.

Probes are usually required for specific detection using photoelectrochemical (PEC) sensors. However, tedious probe modification and cleaning procedures reduce the efficiency of PEC sensors. To ove...

Sample concentration is extremely important in microfluidic detection systems, especially for the detection of trace substance. Among various sample concentration techniques used in microfluidic devices, direct electrokinetic trapping is more convenient and easier to realize. In this paper, a T-shaped microchannel configuration was developed to achieve electrokinetic concentration. Numerical simulation analysis on two-dimensional (2D) configuration model were performed. The microfluidic configuration for DNA enrichment was firstly optimized by analyzing various field distributions. Then, the influence of selected dimension and electrical parameters on enrichment rate was analyzed, including size of the transition chamber and enrichment chamber, distance between the inlet branches, length of the inlet vertical branches, size of the electrode and the electric field intensity. With optimized parameters, our model is able to achieve an optimal enrichment rate of 234.2 at an applied voltage of 20 V within a period of 1200s. Our method provides a valuable guidance for the design of an easy-controlled microfluidic system of precise enrichment capability.

Enzymes that can decompose synthetic plastics such as polyethylene terephthalate (PET) are urgently needed. Still, a bottleneck remains due to a lack of techniques for detecting and sorting environmental microorganisms with vast diversity and abundance. Here, we developed a fluorescence-activated droplet sorting (FADS) pipeline for high-throughput screening of PET-degrading microorganisms or enzymes (PETases). The pipeline comprises three steps: generation and incubation of droplets encapsulating single cells, picoinjection of fluorescein dibenzoate (FDBz) as the fluorogenic probe, and screening of droplets to obtain PET-degrading cells. We characterized critical factors associated with this method, including specificity and sensitivity for discriminating PETase from other enzymes. We then optimized its performance and compatibility with environmental samples. The system was used to screen a wastewater sample from a PET textile mill. We successfully obtained PET-degrading species from nine different genera. Moreover, two putative PETases from isolates Kineococcus endophyticus Un-5 and Staphylococcus epidermidis Un-C2-8 were genetically derived, heterologously expressed, and preliminarily validated for PET-degrading activities. We speculate that the FADS pipeline can be widely adopted to discover new plastic-degrading microorganisms and enzymes in various environments and may be utilized in the directed evolution of degrading enzymes using synthetic biology.

In virtue of the inherent molecular recognition and programmability, DNA has recently become the most promising for high-performance biosensors. The rationally engineered nucleic acid architecture will be very advantageous to hybridization efficiency, specificity, and sensitivity. Herein, a robust and split-mode photoelectrochemical (PEC) biosensor for miRNA-196a was developed based on an entropy-driven tetrahedral DNA (EDTD) amplifier coupled with superparamagnetic nanostructures. The DNA tetrahedron structure features in rigidity and structural stability that contribute to obtain precise identification units and specific orientations, improving the hybridization efficiency, sensitivity, and selectivity of the as-designed PEC biosensor. Further, superparamagnetic Fe3O4@SiO2@CdS particles integrated with DNA nanostructures are beneficial for the construction of a split-mode, highly selective, and reliable PEC biosensor. Particularly, the enzyme- and hairpin-free EDTD amplifier eliminates unnecessary interference from the complex secondary structure of pseudoknots or kissing loops in typical hairpin DNAs, significantly lowers the background noise, and improves the detection sensitivity. This PEC biosensor is capable of monitoring miRNA-196a in practical settings with additional advantages of efficient electrode fabrication, stability, and reproducibility. This strategy can be extended to various miRNA assays in complex biological systems with excellent performance.

In this study, an origami microfluidic electrochemical nano-aptasensor was developed for the rapid detection of the peanut allergen Ara h1. Specifically, the microfluidic aptasensor was fabricated through sequential folding of a piece of chromatography paper substrate patterned with microchannel and screen-printed electrodes. Aptamer-decorated black phosphorus nanosheets (BPNSs) were electrodeposited onto the paper-based electrode surface as sensing probes for enhanced electrochemical detection and high specificity and selectivity. Critical design parameters (the concentration of probe, time for self-assembly of aptamer and reaction time) were investigated to optimize the aptasensor performance. The prepared aptasensor was able to complete detection within 20 min and demonstrated a linear range from 50 ~ 1000 ng/mL with a detection limit of 21.6 ng/mL. The aptasensor was successfully used to detect the Ara h1 spiked cookie dough sample. The proposed method reduces the gap between complex lab testing and food allergen analysis at the point of need.

This study is based on a novel conceptual framework, precision education, and takes a blended Python programming course as an example to explore how to implement precision education that includes diagnosis, prediction, prevention and treatment. Precision education follows the principles of personalized services for precision medicine. Its purpose is to strengthen the learning risk prediction and early intervention mentioned in emerging learning analytics through big data, artificial intelligence and other emerging technologies, thereby improving teacher teaching quality and student learning efficiency. This study is based on the design of the e-book learning dashboard, so that teachers can quickly understand students’ learning status, and improve the e-book through students’ feedback on the dashboard to achieve precision diagnosis. Next, this study uses machine learning algorithms to predict students' learning performance, and thus determine whether students are at-risk to achieve precision prediction. Finally, through the correspondence between reading strategy and reading sequence, and then clearly distinguish the types of students by grouping, and use it as a treatment target for precision treatment and prevention. It is hoped that this empirical study can be used as a case study for implementing precision education.

Foodborne pathogens pose significant concerns in both public health and food safety sector through the world. Rapid and accurate detection of foodborne pathogens at early stage is imperative for the prevention of foodborne disease outbreaks. Conventional methods for foodborne pathogen detection are usually laborious, time-consuming with poor diagnosis competences, and require costly or bulky equipment. Thus, various techniques have been exploited aiming for rapid detection of foodborne pathogens with high sensitivity. Microfluidic biosensor is a promising area in the detection of very low concentration of substance with accuracy in a cost-effective and time-saving manner. By microfluidic nanobiosensors, extremely high sensitivity can be achieved through the enhanced recognition or sensing events across the nanoscale surfaces. When used in foodborne pathogen detection, microfluidic nanobiosensors are capable of decreasing the assay time, reducing the impact of complex food matrix and enhancing the sensitivity and accuracy. Microfluidic nanobiosensors have the potential for low-cost, low-volume and easy-to-use point-of-care (POC) testing hence offering great commercial benefits to public health and food safety sector. A comprehensive literature survey is performed to give an overview on current state-of-the-art of microfluidic nanobiosensors that incorporate different detection methods for various foodborne pathogens with respect to effort and performance to date, along with their advantages and limitations. A few perspective directions of microfluidic nanobiosensor in its development are also discussed.

Background Infectious diseases are a leading cause of death in humans, animals, and plants globally. Pathogen infections can reduce food production and endanger biodiversity. Viruses, bacteria, and fungi are therefore scientifically and economically important in food production. Even outbreaks of a pathogen infection in plants or animals have direct consequences for the food chain and human health. Scope and approach Microorganisms such as bacteria, fungi and virus invade plant cells and utilize the host resources for their survival disturbing the plant or animal metabolism leading to diseases. Advance diagnosis and effective detection of pathogens, infectious diseases, and other parameters affecting the health of animals and plants in agro-defense will assist in reducing financial costs, increasing food production, and improving the global economy. In this article, common pathogens and infectious diseases in animals and plants, along with the point-of-care technologies that address them, are reviewed. Key findings and conclusions The synthesis and discovery of novel nanomaterials and the fabrication of highly specific and sensitive biosensors have expanded the scope for effective agro-defense biosensors. Progress in biosensor development and the existing challenges are reviewed to provide future directions in this field.

Vibrio parahaemolyticus is one of the foodborne bacteria that widely present in seafood as well as the leading cause of seafood-associated bacterial gastroenteritis. Traditional identification of such pathogens mainly relies on culturing methods, ELISA or PCR. These methods are usually laborious, time-consuming with poor diagnosis competences, or require costly and bulky equipment though of high sensitivity. In this study, a thread-based microfluidic electrochemical aptasensor was designed, fabricated and tested by using label-free aptamer immunosensing technology for rapid and highly sensitive detection of Vibrio parahaemolyticus in seafood. Both the microfluidic channels and electrodes were simply fabricated on threads. Molybdenum disulfide (MoS2) nanosheets were used to obtain enhanced sensitivity of the electrochemical measurement. When used in detecting Vibrio parahaemolyticus, the proposed aptasensor has a dynamic detection range of 10–106 CFU mL−1 with a detection limit of 5.74 CFU mL−1. Compared with traditional plate counting method, the proposed aptasensor has higher detection sensitivity and less assay time (30 min), while high specificity and accuracy are kept. The proposed microfluidic thread-based electrochemical aptasensor grabs the potential to detect other pathogens by simply functionalizing the threaded electrodes with aptamers for targeted biological substances.

Electrokinetics is a good fluid control tool in microfluidics and usually microelectrodes play important roles in such approach such as generating a desired electric field. Though the fabrication of two-dimensional (2D) microelectrodes has been relatively mature, they cannot generate uniform electric field in space. Three-dimensional (3D) microelectrodes developed more recently may solve the problem, however the fabrication process is usually complicated and requires micro-alignment platform. Non-toxic liquid metal is a good material for making electrodes that has been introduced into microfluidics. It can be injected directly into a microchannel to form an electrode, but its special physical properties make the injection process complex and difficult to control. In this study, we investigated an optimized manufacturing method of liquid metal microelectrode in a microchip by numerical analysis and experimental study. High quality microelectrodes on morphology and stability were successfully fabricated. A fluorescent enrichment experiment was performed using the developed microelectrode in a microfluidic chip. The result shows that the optimized fabrication method of microelectrode in this study provides a promising way for high quality and good performance liquid metal microelectrode formation, and paves the way for its versatile applications.

Due to the lack of portable, field-deployable diagnostic tests for detecting cancer cells, especially for breast cancer, current detection techniques involve the collection of blood and/or tissue samples, which then need to be sent to laboratories for further analysis before decisions can be made by the treating physicians. Conventional techniques such as mammograms and blood analysis are time consuming, requiring specialized technical personnel, in addition to large and expensive laboratory equipment. Herein, we report the development of a novel sensing method to detect breast cancer-specific microRNAs (miRNAs) captured using a complementary sequence binding technique, and we quantify the mechanism using time-resolved Forster resonance energy transfer (TR-FRET). Using terbium-cryptate, the proposed technique reduces the number of steps required to detect the analyte biomarker in clinical serum samples. We also demonstrate the dual detection of biomarkers using the DNA supporter sequence in the proposed TR-FRET technique. We provide a validated proof-of-concept for a minimally invasive, breast cancer-specific, biomarker detection assay, and demonstrate detection limits in the picomolar range using microfluidics as a detection platform for clinical serum samples. The developed microfluidic biosensor has the potential for use as a portable, field-deployable, and highly sensitive diagnostic tool for the rapid and early detection of breast cancer-specific miRNA signatures.

The increasing prevalence of food allergies and the intake of packing foods in the past two decades urge the need for more rapid, accurate, and sensitive assays to detect potential allergens in food in order to control the allergen content. Most of the commercial analytical tools for allergen detection rely on immunoassays such as ELISA. As far as disadvantages, ELISA can be time-consuming and expensive. Biosensors appear as a suitable alternative for the detection of allergens because they are rapid, highly sensitive, selective, less expensive, environmentally friendly, and easy to handle. In this study, we developed a microfluidic system integrated with a quantum dots (Qdots) aptamer functionalized graphene oxide (GO) nano-biosensor for simple, rapid, and sensitive food allergen detection. The biosensor utilized Qdots-aptamer-GO complexes as probes to undergo conformational change upon interaction with the food allergens, resulting in fluorescence changes due to the fluorescence quenching and recovering properties of GO by adsorption and desorption of aptamer-conjugated Qdots. This one-step 'turn on' homogenous assay in a ready-to-use microfluidic chip took ~10 min to achieve a quantitative detection of Ara h 1, one of the major allergens appearing in peanuts. The results suggested this system had remarkable sensitivity and selectivity. The integration of a microfluidics platform in a homemade miniaturized optical analyzer provides a promising way for the rapid, cost-effective, and accurate on-site determination of food allergens. This biosensor can also be extended to the detection of other food allergens with a selection of corresponding aptamers.

Background Antimicrobial resistance is a great concern in the medical community, as well as food industry. Soy peptides were tested against bacterial biofilms for their antimicrobial activity. A high throughput drug screening assay was developed using microfluidic technology, RAMAN spectroscopy, and optical microscopy for rapid screening of antimicrobials and rapid identification of pathogens. Methods Synthesized PGTAVFK and IKAFKEATKVDKVVVLWTA soy peptides were tested against Pseudomonas aeruginosa and Listeria monocytogenes using a microdilution assay. Microfluidic technology in combination with Surface Enhanced RAMAN Spectroscopy (SERS) and optical microscopy was used for rapid screening of soy peptides, pathogen identification, and to visualize the impact of selected peptides. Results The PGTAVFK peptide did not significantly affect P. aeruginosa, although it had an inhibitory effect on L. monocytogenes above a concentration of 625 µM. IKAFKEATKVDKVVVLWTA was effective against both P. aeruginosa and L. monocytogenes above a concentration of 37.2 µM. High throughput drug screening assays were able to reduce the screening and bacterial detection time to 4 h. SERS spectra was used to distinguish the two bacterial species. Conclusions PGTAVFK and IKAFKEATKVDKVVVLWTA soy peptides showed antimicrobial activity against P. aeruginosa and L. monocytogenes. Development of high throughput assays could streamline the drug screening and bacterial detection process. General significance The results of this study show that the antimicrobial properties, biocompatibility, and biodegradability of soy peptides could possibly make them an alternative to the ineffective antimicrobials and antibiotics currently used in the food and medical fields. High throughput drug screening assays could help hasten pre-clinical trials in the medical field., Highlights • Soy peptide PGTAVFK above 312.5 µM concentrations inhibits Listeria monocytogenes. • IKAFKEATKVDKVVVLWTA restricts motility and aggregation of Listeria monocytogenes. • Microfluidic 3D device generate multiplex parallel drug concentration gradients. • RAMAN spectroscopy microfluidics provides a high throughput drug-screening assay.

Over the past decades, researchers have been seeking attractive substrate materials to keep microfluidics improving to outbalance the drawbacks and issues. Cellulose substrates, including thread, paper and hydrogels are alternatives due to their distinct structural and mechanical properties for a number of applications. Thread have gained considerable attention and become promising powerful tool due to its advantages over paper-based systems thus finds numerous applications in the development of diagnostic systems, smart bandages and tissue engineering. To the best of our knowledge, no comprehensive review articles on the topic of thread-based microfluidics have been published and it is of significance for many scientific communities working on Microfluidics, Biosensors and Lab-on-Chip. This review gives an overview of the advances of thread-based microfluidic diagnostic devices in a variety of applications. It begins with an overall introduction of the fabrication followed by an in-depth review on the detection techniques in such devices and various applications with respect to effort and performance to date. A few perspective directions of thread-based microfluidics in its development are also discussed. Thread-based microfluidics are still at an early development stage and further improvements in terms of fabrication, analytical strategies, and function to become low-cost, low-volume and easy-to-use point-of-care (POC) diagnostic devices that can be adapted or commercialized for real world applications., Highlights • Thread microfluidics is a powerful tool in making diagnostic systems. • This review focus on the advances of thread-based microfluidic diagnostic devices. • Thread microfluidic devices have numerous advantages over traditional and paper-based microfluidics. • A perspective on the future trends for the thread microfluidics is also given.