Effect of Gravity on Bacterial Adhesion to Heterogeneous Surfaces.

Bacterial adhesion is the first step in the formation of surface biofilms. The number of bacteria that bind to a surface from the solution depends on how many bacteria can reach the surface (bacterial transport) and the strength of interactions between bacterial adhesins and surface receptors (adhesivity). By using microfluidic channels and video microscopy as well as computational simulations, we investigated how the interplay between bacterial transport and adhesivity affects the number of the common human pathogen Escherichia coli that bind to heterogeneous surfaces with different receptor densities. We determined that gravitational sedimentation causes bacteria to concentrate at the lower surface over time as fluid moves over a non-adhesive region, so bacteria preferentially adhere to adhesive regions on the lower, inflow-proximal areas that are downstream of non-adhesive regions within the entered compartments. Also, initial bacterial attachment to an adhesive region of a heterogeneous lower surface may be inhibited by shear due to mass transport effects alone rather than shear forces per se, because higher shear washes out the sedimented bacteria. We also provide a conceptual framework and theory that predict the impact of sedimentation on adhesion between and within adhesive regions in flow, where bacteria would likely bind both in vitro and in vivo, and how to normalize the bacterial binding level under experimental set-ups based on the flow compartment configuration.

Sample-to-answer, extraction-free, real-time RT-LAMP test for SARS-CoV-2 in nasopharyngeal, nasal, and saliva samples: Implications and use for surveillance testing.

The global COVID-19 pandemic has highlighted the need for rapid, accurate and accessible nucleic acid tests to enable timely identification of infected individuals. We optimized a sample-to-answer nucleic acid test for SARS-CoV-2 that provides results in <1 hour using inexpensive and readily available reagents. The test workflow includes a simple lysis and viral inactivation protocol followed by direct isothermal amplification of viral RNA using RT-LAMP. The assay was validated using two different instruments, a portable isothermal fluorimeter and a standard thermocycler. Results of the RT-LAMP assay were compared to traditional RT-qPCR for nasopharyngeal swabs, nasal swabs, and saliva collected from a cohort of patients hospitalized due to COVID-19. For all three sample types, positive agreement with RT-LAMP performed using the isothermal fluorimeter was 100% for samples with Ct <30 and 69-91% for samples with Ct <40. Following validation, the test was successfully scaled to test the saliva of up to 400 asymptomatic individuals per day as part of the campus surveillance program at Rice University. Successful development, validation, and scaling of this sample-to-answer, extraction-free real-time RT-LAMP test for SARS-CoV-2 adds a highly adaptable tool to efforts to control the COVID-19 pandemic, and can inform test development strategies for future infectious disease threats.

Improving Performance of a SARS-CoV-2 RT-LAMP Assay for Use With a Portable Isothermal Fluorimeter: Towards a Point-of-Care Molecular Testing Strategy.

Frequent and accessible testing is a critical tool to contain the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To develop low-cost rapid tests, many researchers have used reverse transcription loop-mediated isothermal amplification (RT-LAMP) with fluorescent readout. Fluorescent LAMP-based assays can be performed using cost-effective, portable, isothermal instruments that are simpler to use and more rugged than polymerase chain reaction (PCR) instruments. However, false-positive results due to nonspecific priming and amplification have been reported for a number of LAMP-based assays. In this report, we implemented a RT-LAMP assay for SARS-CoV-2 on a portable isothermal fluorimeter and a traditional thermocycler; nonspecific amplification was not observed using the thermocycler but did occur frequently with the isothermal fluorimeter. We explored 4 strategies to optimize the SARS-CoV-2 RT-LAMP assay for use with an isothermal fluorimeter and found that overlaying the reaction with mineral oil and including the enzyme Tte UvrD helicase in the reaction eliminated the problem. We anticipate these results and strategies will be relevant for use with a wide range of portable isothermal instruments.

Disposable Autonomous Device for Swab-to-Result Diagnosis of Influenza.

A prototype of a self-contained, automated, disposable device for chemically amplified protein-based detection of influenza virus from nasal swab specimens was developed and evaluated in a clinical setting. The device required only simple specimen manipulation without any dedicated instrumentation or specialized training by the operator for interpretation. The device was based on a sandwich immunoassay for influenza virus nucleoprotein; it used an enzyme-labeled antibody and a chromogenic substrate to provide an amplified visible signal, in a two-dimensional paper network format. All reagents were stored within the device. Device performance was assessed at Seattle Children's Hospital; clinical staff collected nasal swab samples from 25 patients and then operated test devices on site to detect influenza A and B in those specimens. The total test time from device initiation to result was approximately 35 min. Device performance for influenza A detection was ∼70% accurate using in-house qRT-PCR influenza A as a gold-standard comparison. The ratio of valid to total completed device runs yielded a success rate of 92%, and the negative predictive value for both the influenza A and B assay was 81%. The ability to diagnose respiratory infections rapidly and close to the patient was well received by hospital staff, inspiring further optimization of device function.

Validation of the mobile serious game application Touch Surgery™ for cognitive training and assessment of laparoscopic cholecystectomy.

BACKGROUND: Touch Surgery™ (TS) is a serious gaming application for cognitive task simulation and rehearsal of key steps in surgical procedures. The aim was to establish face, content, and construct validity of TS for laparoscopic cholecystectomy (LC). Furthermore, learning curves with TS and a virtual reality (VR) trainer were compared in a randomized trial. METHODS: The performance of medical students and general surgeons was compared for all three modules of LC in TS to establish construct validity. Questionnaires assessed face and content validity. For analysis of learning curves, students were randomized to train on VR or TS first, and then switched to the other training modality. Performance data were recorded. RESULTS: 54 Surgeons and 51 medical students completed the validation study. Surgeons outperformed students with TS: patient preparation (students = 45.0 ± 19.1%; surgeons = 57.3 ± 15.2%; p < 0.001), access and laparoscopy (students = 70.2 ± 10.9%; surgeons = 75.9 ± 9.7%; p = 0.008) and LC (students = 69.8 ± 12.4%; surgeons = 77.7 ± 9.6%; p < 0.001). Both groups agreed that TS was a highly useful and realistic application. 46 students were randomized for learning curve analysis. It took them 2-4 attempts to reach a 100% score with TS. Training with TS first did not improve students' performance on the VR trainer; however, students who trained with VR first scored significantly higher in module 3 of TS. CONCLUSION: TS is an accepted serious gaming application for learning cognitive aspects of LC with established construct, face, and content validity. There appeared to be a synergy between TS and the VR trainer. Therefore, the two training modalities should accompany one another in a multimodal training approach to laparoscopy.

Development and validation of a sensor- and expert model-based training system for laparoscopic surgery: the iSurgeon.

INTRODUCTION: Training and assessment outside of the operating room is crucial for minimally invasive surgery due to steep learning curves. Thus, we have developed and validated the sensor- and expert model-based laparoscopic training system, the iSurgeon. MATERIALS: Participants of different experience levels (novice, intermediate, expert) performed four standardized laparoscopic knots. Instruments and surgeons' joint motions were tracked with an NDI Polaris camera and Microsoft Kinect v1. With frame-by-frame image analysis, the key steps of suturing and knot tying were identified and registered with motion data. Construct validity, concurrent validity, and test-retest reliability were analyzed. The Objective Structured Assessment of Technical Skills (OSATS) was used as the gold standard for concurrent validity. RESULTS: The system showed construct validity by discrimination between experience levels by parameters such as time (novice = 442.9 ± 238.5 s; intermediate = 190.1 ± 50.3 s; expert = 115.1 ± 29.1 s; p < 0.001), total path length (novice = 18,817 ± 10318 mm; intermediate = 9995 ± 3286 mm; expert = 7265 ± 2232 mm; p < 0.001), average speed (novice = 42.9 ± 8.3 mm/s; intermediate = 52.7 ± 11.2 mm/s; expert = 63.6 ± 12.9 mm/s; p < 0.001), angular path (novice = 20,573 ± 12,611°; intermediate = 8652 ± 2692°; expert = 5654 ± 1746°; p < 0.001), number of movements (novice = 2197 ± 1405; intermediate = 987 ± 367; expert = 743 ± 238; p < 0.001), number of movements per second (novice = 5.0 ± 1.4; intermediate = 5.2 ± 1.5; expert = 6.6 ± 1.6; p = 0.025), and joint angle range (for different axes and joints all p < 0.001). Concurrent validity of OSATS and iSurgeon parameters was established. Test-retest reliability was given for 7 out of 8 parameters. The key steps "wrapping the thread around the instrument" and "needle positioning" were most difficult to learn. CONCLUSION: Validity and reliability of the self-developed sensor-and expert model-based laparoscopic training system "iSurgeon" were established. Using multiple parameters proved more reliable than single metric parameters. Wrapping of the needle around the thread and needle positioning were identified as difficult key steps for laparoscopic suturing and knot tying. The iSurgeon could generate automated real-time feedback based on expert models which may result in shorter learning curves for laparoscopic tasks. Our next steps will be the implementation and evaluation of full procedural training in an experimental model.