Design and Elementary Evaluation of a Highly-Automated Fluorescence-Based Instrument System for On-Site Detection of Food-Borne Pathogens.

A simple, highly-automated instrument system used for on-site detection of foodborne pathogens based on fluorescence was designed, fabricated, and preliminarily tested in this paper. A corresponding method has been proved effective in our previous studies. This system utilizes a light-emitting diode (LED) to excite fluorescent labels and a spectrometer to record the fluorescence signal from samples. A rotation stage for positioning and switching samples was innovatively designed for high-throughput detection, ten at most in one single run. We also developed software based on LabVIEW for data receiving, processing, and the control of the whole system. In the test of using a pure quantum dot (QD) solution as a standard sample, detection results from this home-made system were highly-relevant with that from a well-commercialized product and even slightly better reproducibility was found. And in the test of three typical kinds of food-borne pathogens, fluorescence signals recorded by this system are highly proportional to the variation of the sample concentration, with a satisfied limit of detection (LOD) (nearly 10²-10³ CFU·mL-1 in food samples). Additionally, this instrument system is low-cost and easy-to-use, showing a promising potential for on-site rapid detection of food-borne pathogens.

Evaluating surgical expertise with AI-based automated instrument recognition for robotic distal gastrectomy.

Introduction: Complexities of robotic distal gastrectomy (RDG) give reason to assess physician's surgical skill. Varying levels in surgical skill affect patient outcomes. We aim to investigate how a novel artificial intelligence (AI) model can be used to evaluate surgical skill in RDG by recognizing surgical instruments. Methods: Fifty-five consecutive robotic surgical videos of RDG for gastric cancer were analyzed. We used Deeplab, a multi-stage temporal convolutional network, and it trained on 1234 manually annotated images. The model was then tested on 149 annotated images for accuracy. Deep learning metrics such as Intersection over Union (IoU) and accuracy were assessed, and the comparison between experienced and non-experienced surgeons based on usage of instruments during infrapyloric lymph node dissection was performed. Results: We annotated 540 Cadiere forceps, 898 Fenestrated bipolars, 359 Suction tubes, 307 Maryland bipolars, 688 Harmonic scalpels, 400 Staplers, and 59 Large clips. The average IoU and accuracy were 0.82 ± 0.12 and 87.2 ± 11.9% respectively. Moreover, the percentage of each instrument's usage to overall infrapyloric lymphadenectomy duration predicted by AI were compared. The use of Stapler and Large clip were significantly shorter in the experienced group compared to the non-experienced group. Conclusions: This study is the first to report that surgical skill can be successfully and accurately determined by an AI model for RDG. Our AI gives us a way to recognize and automatically generate instance segmentation of the surgical instruments present in this procedure. Use of this technology allows unbiased, more accessible RDG surgical skill.

Automated test apparatus for bench-testing the magnetic field homogeneity of NMR transceiver coils.

We describe an automated hands-off bench testing method for measuring the magnetic field profile of transceiver coils for nuclear magnetic resonance (NMR). The scattering parameter (S-parameter) data is measured using a portable network analyzer, and the results are automatically exported to a computer for plotting and viewing. This assay dramatically reduces the time needed to measure the magnetic field (B1) homogeneity profile of a transceiver coil while also improving accuracy relative to manual operation. Here, we demonstrate the method on a saddle coil of a solution-state NMR probe in comparison to profiles obtained using NMR spectroscopy measurements. We also measure the axial and radial homogeneity of a variable-pitch solenoid.

[Do liquid wastes from automated instruments in medical laboratories have their proper microbicide effect?] / Les rejets liquides des automates de biologie médicale ont-ils un effet microbicide propre qui permettrait de s'affranchir de leur traitement pour risque infectieux ?

Liquid wastes from clinical biology automated systems are currently evacuated in the urban network after chemical treatment to eliminate a possible risk of infection. Since these wastes are ecotoxic because of the presence of numerous chemical reagents, we studied their intrinsic microbicidal power towards a selection of infectious agents widely found in clinical specimens. The objective was to determine if an additional anti-infectious treatment before elimination is necessary. Thus, we evaluated the bactericidal effect of liquid wastes of several automated systems towards four bacterial species (Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Enterococcus faecalis) and their virucidal activity against a non-enveloped virus, resistant in the environment (adenovirus). This effect was determined for different exposure times. Our results showed that the antibacterial activity was highly variable depending on the waste-bacteria pair considered (varying from no activity to complete sterilization of a strong bacterial inoculum). The liquid wastes were on the other hand globally inactive towards adenovirus.

Facile electrochemical method and corresponding automated instrument for the detection of furfural in insulation oil.

Determining the concentration of furfural contained in the insulation oil of a transformer has been established as a method to evaluate the health status of the transformer. However, the detection of furfural involves the employment of expensive instruments and/or time-consuming laboratorial operations. In this paper, we proposed a convenient electrochemical method to make the detection. The quantification of furfural was realized by extraction of furfural from oil phase to aqueous phase followed by reductive detection of furfural with differential pulse voltammetry (DPV) at a mercury electrode. This method is very sensitive and the limit of detection, corresponding to furfural contained in oil, is estimated to be 0.03 µg g(-1). Furthermore, excellent linearity can be obtained in the range of 0-10 µg g(-1). These features make the method very suitable for the determination of furfural in real situation. A fully automated instrument that can perform the operations of extraction and detection was developed, and this instrument enables the whole measurement to be finished within eight minutes. The methodology and the instrument were tested with real samples, and very favorable agreement between results obtained with this instrument and HPLC indicates that the proposed method along with instrument can be employed as a facile tool to diagnose the health status of aged transformers.

Automated hollow fiber microextraction based on two immiscible organic solvents for the extraction of two hormonal drugs.

In this research, a rapid efficient and automated instrument based on hollow fiber liquid-phase microextraction (HF-LPME) followed by high performance liquid chromatography (HPLC) with UV-vis detection was applied for the preconcentration and determination of two hormonal drugs (megestrol acetate and levonorgestrel) in water and urinary samples. n-Dodecane was used as the supported liquid membrane (SLM) and methanol was used as the acceptor phase in the hollow fiber lumen. The effects of different parameters such as fiber length, extraction time, stirring rate, and ionic strength on the extraction efficiency were investigated using modified simplex and central composite design as the screening and optimization methods, respectively. The composition effect of SLM and type of acceptor phase were optimized separately. For adjustment of the SLM composition, trioctylphosphine oxide (TOPO) was chosen. Under optimized condition, the calibration curves were linear (r(2)>0.997) in the range of 0.5-200 µg L(-1). LOD for both of the drugs were 0.25 µg L(-1). The applicability of this technique was examined by analyzing drugs in water and urine samples. The relative recoveries of the drugs were in the range of 86.2-102.3% that show the capability of the method for the determination of the drugs in various matrices.