Microfluidic paper-based analytical devices with instrument-free detection and miniaturized portable detectors

icrofluidic paper-based analytical devices (mu PADs) have attracted much attention over the past decade because they offer clinicians the ability to deliver point-of-care testing and onsite analysis. Many of the advantages of mu PADs, however, are limited to work in a laboratory setting due to the difficulties of processing data when using electronic devices in the field. This review focuses on the use of mu PADs that have the potential to work without batteries or with only small and portable devices such as smartphones, timers, or miniaturized detectors. The mu PADs that can be operated without batteries are, in general, those that allow the visual judgment of analyte concentrations via readouts that are measured in time, distance, count, or text. Conversely, a smartphone works as a camera to permit the capture and processing of an image that digitizes the color intensity produced by the reaction of an analyte with a colorimetric reagent. Miniaturized detectors for electrochemical, fluorometric, chemiluminescence, and electrochemiluminescence methods are also discussed, although some of them require the use of a laptop computer for operation and data processing

Emulsification liquid-liquid microextraction coupled with droplet digital image colorimetric detection for determination of rhodamine B in food and beverage samples

An analytical method combining fatty acid-emulsification liquid-liquid microextraction (FA-ELLME) with solidification of floating drops (SFD) and droplet digital image colorimetry (DDIC) was developed for the analysis of rhodamine B (RhB) in food and beverage samples. This work applied an emulsified amphiphilic fatty acid as an extracting solvent and a freezing procedure for extracting phase separation. A 7 mL sample volume adjusted to pH 5 was extracted with a drop of 35 μL of octanoic acid (0.5%v/v). The emulsification was initiated by shaking for 10 s followed by centrifugation for 5 min. The floating drops containing RhB were solidified in an ice bath, separated from the solution, defrosted, and dropped on the paper platform for DDIC analysis. The limit of detection (LOD) and limit of quantification (LOQ) were 1.8 μg L−1 and 6.0 μg L−1, respectively. The linear range was 10 - 40 μg L−1 (R2 = 0.997). The method was applied to determine RhB in beverage, candy, jelly, and chili sauce samples. The relative recovery percentages (RR%) between 73% and 113% were achieved

Combining graphite with hollow-fiber liquid-phase microextraction for improving the extraction efficiency of relatively polar organic compounds

[eng] In this study, we have developed a simple and effective hybrid extraction method based on the incorporation of raw carbon nanosorbents and octanol in the pores of a hollow-fiber membrane for improving the extraction efficiency of relatively polar organic compounds. Trihalomethanes (THMs) were used as model analytes. Three types of carbon nanosorbents (graphite, graphene, and multi-walled carbon nanotubes) were studied. The carbon sorbent incorporating membrane was used in a two-phase mode liquid-phase microextraction, with 1-octanol as the acceptor solution. Using a graphite-reinforced hollow-fiber membrane and an extraction time of 10 min, enrichment factors of 40-71 were obtained for trichloromethane, bromodichloromethane, bromoform, and chlorodibromomethane. Linear working ranges of 0.2-100 μg L−1 and limits of detection ranging from 0.01 μg L−1 (for CHCl2Br and CHClBr2) to 0.1 μg L−1 (for CHCl3) were achieved. The minimum detectable concentrations were far below the maximum concentration levels (60-200 μg L−1) set by the WHO for drinking water. The carbon-sorbent-reinforced hollow-fiber liquid-phase microextraction afforded higher extraction efficiency and shorter extraction time compared with conventional hollow-fiber liquid-phase microextraction. Finally, the method was applied to the analysis of real water samples, such as drinking water, tap water, and swimming pool water samples

In-line gas purging exploiting a novel converging flow-on paper optosensing device for the determination of total ammonia-nitrogen in water samples

A novel, inexpensive, and sensitive microanalytical system for the determination of total ammonia-nitrogen (ammonia-N) in water was developed. The system was designed to detect ammonia using an in-line purging system coupled with a newly designed gas converging flow cell incorporating in-line paper-based colorimetric detection. The gas converging flow cell served as a gas chamber, a paper-based device holder, and a color detection cell. The paper-based device was impregnated with butterfly pea extract (a natural acid-base indicator), the color of which changed on the basis of the generated ammonia gas. Analytical parameters such as concentration of natural indicator and purging time were studied and optimized. The color image could be captured by an integrated endoscope camera or smartphone and analyzed by ImageJ software in RGB mode. Under optimal conditions, two linear dynamic ranges were observed. By using 1:2 (v/v) diluted 2% (w/v) butterfly pea extract in Milli-Q water, a low linear concentration range of 0.05–0.9 mg L−1 with a limit of detection (LOD) of 0.02 mg L−1 and limit of quantification (LOQ) of 0.05 mg L−1 was achieved. By using a non-diluted 2% (w/v) butterfly pea extract, a high linear concentration range of 0.5–4 mg L−1 with an LOD of 0.1 mg L−1 and LOQ of 0.3 mg L−1 was obtained. Finally, the optimized method was leveraged to determine ammonia-N in various water samples from shrimp farming

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population