Evaluation of Freezanz automated misting system against mosquitoes.

Automated misting systems are a convenient way for homeowners or small businesses to control adult mosquitoes. One such system was presented to the Anastasia Mosquito Control District (AMCD) for evaluation to control caged Aedes aegypti. The system consisted of 3 spray tanks, 2 pumps, water level sensors, and flow meters, and was controlled through an Android tablet loaded with dedicated control software. The evaluation of the system included calibration tests, droplet characterization, spray dispersion in the open field, and effectiveness testing using bio-assay cages for mortality assessment. For these tests, a loop of 14 nozzles 4 m apart was connected and held at 1 m height utilizing a total of 120 m tube. All nozzles were arranged in a 16 × 12 m rectangle laid in the East-West direction. Water was sprayed for calibration and droplet size measurements at pressures of 13.0, 15.5, and 18 bar; water and 10 % red dye solution for spray dispersion at 18 bar pressure, and 0.17 % solution of equalizer 20-20 was sprayed at 18 bar pressure for mortality tests. All 3 replicated tests were conducted in the morning between 9:00 and 11:30am. During this time, temperature ranged from 21 to 26 °C, relative humidity from 54 to 95%, and wind speed from 0 - 2 km/hr. The combined flow rate from all 14 nozzles was significantly affected by pressure and was in agreement with the machine-calculated flow rate. There was a similar flow rate from all nozzles, indicated by a standard error of 0.82 mL/min. The droplet characteristics represented by DV0.1, DV0.5, and DV0.9 were not affected by nozzles but decreased with an increase in pressure as expected. The percentage of coverage on the cards, an indicator of spray dispersion, ranged from 20 -100%, and it was found to increase in the direction of the wind. Mosquito mortality showed a similar trend of increasing in the wind direction and ranged from 30 to 100 %. There was no effect of the location of cages on mosquito mortality. These results indicate that the effectiveness of this spray depends upon wind direction. The results, however, may be different when there is no wind, which may be the case during the times these applications are made.

Development and transfer of automated methods in neuroscience: The DADTA.

In the second half of the 20th century, neuroscientists across North America developed automated systems for use in their research laboratories. Their decisions to do so were complex and contingent, partly a result of global reasons, such as the need to increase efficiency and flexibility, and partly a result of local reasons, such as the need to amend perceived biases of earlier research methodologies. Automated methods were advancements but raised several challenges. Transferring a system from one location to another required that certain components of the system be standardized, such as the hardware, software, and programming language. This proved difficult as commercial manufacturers lacked incentives to create standardized products for the few neuroscientists working towards automation. Additionally, investing in automated systems required massive amounts of time, labor, funding, and computer expertise. Moreover, neuroscientists did not agree on the value of automation. My brief history investigates Karl Pribram's decisions to expand his newly created automated system by standardizing equipment, programming, and protocols. Although he was an eminent Stanford neuroscientist with strong institutional support and computer know-how, the development and transfer of his automated behavioral testing system was riddled with challenges. For Pribram and neuroscience more generally, automation was not so automatic.

Automated multi-attribute method sample preparation using high-throughput buffer exchange tips.

RATIONALE: The multi-attribute method (MAM) has become a valuable mass spectrometry (MS)-based tool that can identify and quantify the site-specific product attributes and purity information for biotherapeutics such as monoclonal antibodies (mAbs) and fusion molecules in recent years. As we expand the use of the MAM at various stages of drug development, it is critical to enhance the sample preparation throughput without additional chemical modifications and variability. METHODS: In this study, a fully automated MAM sample preparation protocol is presented, where rapid desalting in less than 15 minutes is achieved using miniaturized size-exclusion chromatography columns in pipette tips on an automated liquid handler. The peptide samples were analyzed using an electrospray ionization (ESI) orbitrap mass spectrometer coupled to an ultra-high-performance liquid chromatography (UHPLC) system with a dual column switching system. RESULTS: No significant change was observed in product attributes and their quantities compared with manual, low-artifact sample preparation. The sample recovery using the buffer exchange tips was greatly enhanced over the manual spin cartridges while still demonstrating excellent reproducibility for a wide variety of starting sample concentrations. Unlike a plate desalting system, the individual columns provide flexibility in the number of samples prepared at a time and sample locations within plates. CONCLUSIONS: This automated protocol enables the preparation of up to 96 samples with less "at-bench" time than the manual preparation of a smaller batch of samples, thereby greatly facilitating support of process development and the use of the MAM in quality control.

ZAF, the first open source fully automated feeder for aquatic facilities.

In the past few decades, aquatic animals have become popular model organisms in biology, spurring a growing need for establishing aquatic facilities. Zebrafish are widely studied and relatively easy to culture using commercial systems. However, a challenging aspect of maintaining aquatic facilities is animal feeding, which is both time- and resource-consuming. We have developed an open-source fully automatic daily feeding system, Zebrafish Automatic Feeder (ZAF). ZAF is reliable, provides a standardized amount of food to every tank, is cost-efficient and easy to build. The advanced version, ZAF+, allows for the precise control of food distribution as a function of fish density per tank, and has a user-friendly interface. Both ZAF and ZAF+ are adaptable to any laboratory environment and facilitate the implementation of aquatic colonies. Here, we provide all blueprints and instructions for building the mechanics, electronics, fluidics, as well as to setup the control software and its user-friendly graphical interface. Importantly, the design is modular and can be scaled to meet different user needs. Furthermore, our results show that ZAF and ZAF+ do not adversely affect zebrafish culture, enabling fully automatic feeding for any aquatic facility.

Live-imaging rate-of-kill compound profiling for Chagas disease drug discovery with a new automated high-content assay.

Chagas disease, caused by the protozoan intracellular parasite Trypanosoma cruzi, is a highly neglected tropical disease, causing significant morbidity and mortality in central and south America. Current treatments are inadequate, and recent clinical trials of drugs inhibiting CYP51 have failed, exposing a lack of understanding of how to translate laboratory findings to the clinic. Following these failures many new model systems have been developed, both in vitro and in vivo, that provide improved understanding of the causes for clinical trial failures. Amongst these are in vitro rate-of-kill (RoK) assays that reveal how fast compounds kill intracellular parasites. Such assays have shown clear distinctions between the compounds that failed in clinical trials and the standard of care. However, the published RoK assays have some key drawbacks, including low time-resolution and inability to track the same cell population over time. Here, we present a new, live-imaging RoK assay for intracellular T. cruzi that overcomes these issues. We show that the assay is highly reproducible and report high time-resolution RoK data for key clinical compounds as well as new chemical entities. The data generated by this assay allow fast acting compounds to be prioritised for progression, the fate of individual parasites to be tracked, shifts of mode-of-action within series to be monitored, better PKPD modelling and selection of suitable partners for combination therapy.

Development and clinical validation of an automated cell cytotoxicity neutralization assay for detecting Clostridioides difficile toxins in clinically relevant stools samples.

OBJECTIVES: To improve the diagnostic accuracy of Clostridioides difficile infection, current U.S. and E.U. guidelines recommend multistep testing that detects the presence of C. difficile and toxin in clinically relevant stool samples to confirm active disease. An accepted gold standard to detect C. difficile toxins is the cell cytotoxicity neutralization assay (CCNA). Although highly sensitive, the traditional CCNA has limitations. One such limitation is the subjective interpretation of an analyst to recognize cytopathic effects in cultured cells exposed to a fecal sample containing toxin. To overcome this limitation, an automated CCNA was developed that replaces most human pipetting steps with robotics and incorporates CellTiterGlo® for a semi-quantitative, non-subjective measure of cell viability instead of microscopy. METHODS: To determine sample positivity and control for non-specific cytopathic effects, two thresholds were defined and validated by evaluating the sample with/without antitoxin antisera (sample-antitoxin/sample + antitoxin): 1) a >70% cell viability threshold was validated with samples containing anti-toxin, and 2) a >1.2-fold difference cut-off where sample results above the cut-off are considered positive. RESULTS: Assay validation demonstrated excellent accuracy, precision, and sample linearity with an LOD of 126.9 pg/mL toxin-B in stool. The positivity cut-offs were clinically validated by comparing 322 diarrheal stool sample results with those run in a predicate, microscopic readout-based CCNA. The automated CCNA demonstrated 96% sensitivity and 100% specificity compared with the predicate CCNA. CONCLUSIONS: Overall, the automated CCNA provides a specific, sensitive, and reproducible tool to support determination of CDI epidemiology or the efficacy of interventions such as vaccines.

Impact of 24/7 loading of blood culture bottles in a new automated incubator on the diagnosis of bloodstream infections.

Blood culturing (BC) remains the gold standard for bloodstream diagnosis but its workflow is slow. We aimed reducing this time by implementing a new automated incubator with a 24/7 BC workflow. With this new strategy, time to incubation was shorter (1.52 h vs 6.82 h), positivity rates were higher (10.6% vs 8.9%, p<0.05), and the number of BSI diagnostics increased (16.1% vs 13.8% patients and 2.3 vs 1.9 density episode per 1000 hospital days). Our results show that implementing automatic loading of BC bottles with a 24/7 strategy not only shortened time to diagnosis but significantly increased the BSI diagnosis rate.

Automated antimicrobial susceptibility testing of slow-growing Pseudomonas aeruginosa strains in the presence of tetrazolium salt WST-1.

Slow growing, mucoid isolates of Pseudomonas aeruginosa require adaptation of the protocol used for automated antimicrobial susceptibility testing (AST). In the present study we used a water soluble tetrazolium salt WST-1 (4-[3-(4-iodophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1,3-benzene disulfonate) in combination with menadione for possibly improving AST of slow growing and biofilm-forming P. aeruginosa isolates from cystic fibrosis (CF) patients. WST-1 and menadione addition ensures sensitive detection of microbial growth increase in the presence of antibiotics that may remain undetected with the automated VITEK® 2 method. We observed that 32.8% of P. aeruginosa isolates from CF and bronchiectasis patients produced an elevated absorbance signal intensity thereby increasing the sensitivity while maintaining the accuracy of VITEK 2. Our study merits future investigation with other slow growing pathogenic bacterial species.

Performances of automated digital imaging of Gram-stained slides with on-screen reading against manual microscopy.

The objective of this study was to evaluate the performances of the automated digital imaging of Gram-stained slides against manual microscopy. Four hundred forty-three identified Gram-stained slides were included in this study. When both methods agreed, we considered the results as correct, and no further examination was carried out. Whenever the methods gave discrepant results, we reviewed the digital images and the glass slides by manual microscopy to avoid incorrectly read smears. The final result was a consensus of multiple independent reader interpretations. Among the 443 slides analyzed in this study, 101 (22.8%) showed discrepant results between the compared methods. The rates of discrepant results according to the specimen types were 5.7% (9/157) for positive blood cultures, 42% (60/142) for respiratory tract specimens, and 22% (32/144) for sterile site specimens. After a subsequent review of the discrepant slides, the final rate of discrepancies dropped to 7.0% (31/443). The overall agreement between the compared methods and the culture results reached 78% (345/443) and 79% (349/443) for manual microscopy and automated digital imaging, respectively. According to culture results, the specificity for automated digital imaging and manual microscopy were 90.8% and 87.7% respectively. In contrast, sensitivity was 84.1% for the two compared methods. The discrepant results were mostly encountered with microorganism morphologies of rare occurrence. The results reported in this study emphasize that on-screen reading is challenging, since the recognition of morphologies on-screen can appear different as compared to routine manual microscopy. Monitoring of Gram stain errors, which is facilitated by automated digital imaging, remains crucial for the quality control of reported Gram stain results.

An automated room disinfection system using ozone is highly active against surrogates for SARS-CoV-2.

BACKGROUND: The presence of coronaviruses on surfaces in the patient environment is a potential source of indirect transmission. Manual cleaning and disinfection measures do not always achieve sufficient removal of surface contamination. This increases the importance of automated solutions in the context of final disinfection of rooms in the hospital setting. Ozone is a highly effective disinfectant which, combined with high humidity, is an effective agent against respiratory viruses. Current devices allow continuous nebulization for high room humidity as well as ozone production without any consumables. AIM: In the following study, the effectiveness of a fully automatic room decontamination system based on ozone was tested against bacteriophage Φ6 (phi 6) and bovine coronavirus L9, as surrogate viruses for the pandemic coronavirus SARS-CoV-2. METHODS: For this purpose, various surfaces (ceramic tile, stainless steel surface and furniture board) were soiled with the surrogate viruses and placed at two different levels in a gas-tight test room. After using the automatic decontamination device according to the manufacturer's instructions, the surrogate viruses were recovered from the surfaces and examined by quantitative cultures. Then, reduction factors were calculated. FINDINGS: The ozone-based room decontamination device achieved virucidal efficacy (reduction factor >4 log10) against both surrogate organisms regardless of the different surfaces and positions confirming a high activity under the used conditions. CONCLUSION: Ozone is highly active against SARS-CoV-2 surrogate organisms. Further investigations are necessary for a safe application and efficacy in practice as well as integration into routine processes.

Comparison between Abbott m2000 RealTime and Alinity m STI systems for detection of Chlamydia trachomatis, Neisseria gonorrhoeae, and Mycoplasma genitalium.

The new Abbott Alinity m STI Assay was compared with Abbott m2000 RealTime PCR. For Chlamydia trachomatis, 26 (7.5%) of 347 samples were positive in the Alinity assay and 24 (6.9%) in the m2000 assay. Corresponding figures for Neisseria gonorrhoeae were 23 (6.6%) and 17 (4.9%). For Mycoplasma genitalium, 22 (7.9%) of 279 samples were positive in the Alinity assay and 18 (6.5%) in the m2000 assay, for which DNA extraction was performed on an m2000sp instrument combined with in-house real-time PCR. The Alinity assay has at least the same sensitivity as the m2000 assay. The specificity was evaluated by discrepancy analysis.

Applicability and performance of EUCAST's rapid antimicrobial susceptibility testing (RAST) on primarily sterile body fluids in blood culture bottles in laboratory routine with total lab automation.

Optimisation of microbiological diagnostics in primarily sterile body fluids is required. Our objective was to apply EUCAST's RAST on primarily sterile body fluids in blood culture bottles with total lab automation (TLA) and to compare results to our reference method Vitek2 in order to report susceptibility results earlier. Positive blood culture bottles (BACTEC™ Aerobic/Anaerobic/PEDS) inoculated with primarily sterile body fluids were semi-automatically subcultured onto Columbia 5% SB agar, chocolate agar, MacConkey agar, Schaedler/KV agar and Mueller-Hinton agar. On latter, cefoxitin, ampicillin, vancomycin, piperacillin/tazobactam, meropenem and ciprofloxacin were added. After 6 h, subcultures and RAST were imaged and MALDI-TOF MS was performed. Zone sizes were digitally measured and interpreted following RAST breakpoints for blood cultures. MIC values were determined using Vitek2 panels. During a 1-year period, 197 Staphylococcus aureus, 91 Enterococcus spp., 38 Escherichia coli, 11 Klebsiella pneumoniae and 8 Pseudomonas aeruginosa were found. Categorical agreement between RAST and MIC was 96.5%. Comparison showed no very major errors, 2/7 (28.6%) and 1/7 (14.3%) of major errors for P. aeruginosa and meropenem and ciprofloxacin, 1/9 (11.1%) for K. pneumoniae and ciprofloxacin, 4/69 (7.0%) and 3/43 (5.8%) for Enterococcus spp. and vancomycin and ampicillin, respectively. Minor errors for P. aeruginosa and meropenem (1/8; 12.8%) and for E. coli and ciprofloxacin (2/29; 6.5%) were found. 30/550 RAST measurements were within area of technical uncertainty. RAST is applicable and performs well for primarily sterile body fluids in blood culture bottles, partially better than blood-based RAST. Official EUCAST evaluation is needed.

A positive pressure workstation for semi-automated peptide purification of complex proteomic samples.

RATIONALE: High-throughput reliable data generation has become a substantial requirement in many "omics" investigations. In proteomics the sample preparation workflow consists of multiple steps adding more bias to the sample with each additional manual step. Especially for label-free quantification experiments, this drastically impedes reproducible quantification of proteins in replicates. Here, a positive pressure workstation was evaluated to increase automation of sample preparation and reduce workload as well as consumables. METHODS: Digested peptide samples were purified utilizing a new semi-automated sample preparation device, the Resolvex A200, followed by nanospray liquid chromatography/electrospray ionization (nLC/ESI) Orbitrap tandem mass spectrometry (MS/MS) measurements. In addition, the sorbents Maestro and WWP2 (available in conventional cartridge and dual-chamber narrow-bore extraction columns) were compared with Sep-Pak C18 cartridges. Raw data was analyzed by MaxQuant and Perseus software. RESULTS: The semi-automated workflow with the Resolvex A200 workstation and both new sorbents produced highly reproducible results within 10-300 µg of peptide starting material. The new workflow performed equally as well as the routinely conducted manual workflow with similar technical variability in MS/MS-based identifications of peptides and proteins. A first application of the system to a biological question contributed to highly reliable results, where time-resolved proteomic data was separated by principal component analysis (PCA) and hierarchical clustering. CONCLUSIONS: The new workstation was successfully established for proteolytic peptide purification in our proteomic workflow without any drawbacks. Highly reproducible results were obtained in decreased time per sample, which will facilitate further large-scale proteomic investigations.

Milestones for autonomous in vivo microrobots in medical applications.

In light of recent developments within both health care and robotics, the use of robots within the human body has become attainable. Here we discuss the milestones for the realization of autonomous microrobots in medical applications. The desired tasks were classified by identifying the difficulties and requirements faced by the robot. In addition, we classified the levels of autonomy seen in microrobots for these uses. The aim of this article is to provide readers with a good understanding of the current state and future possibilities in this field.

Accelerate Pheno™ blood culture detection system: a literature review.

Accelerate Pheno™ (ACC) is a fully automated system providing rapid identification of a panel of bacteria and yeasts, and antimicrobial susceptibility testing of common bacterial pathogens responsible for bloodstream infections and sepsis. Diagnostic accuracy for identification ranges from 87.9 to 100%, and antimicrobial susceptibility testing categorical agreement is higher than 91%. The present review includes peer-reviewed studies on ACC published to date. Both interventional and hypothetical studies evidenced the potential positive clinical role of ACC in the management and therapy of patients with bloodstream infections and sepsis, due to the important reduction in time to report, suggesting a crucial impact on the therapeutic management of these patients, provided the presence of a hospital antimicrobial stewardship program, a 24/7 laboratory operating time and a strict collaboration between clinical microbiologist and clinician. Further prospective multicenter studies are necessary to explore the impact of this system on mortality, length of stay and spread of multidrug-resistant organisms.

A ferrobotic system for automated microfluidic logistics.

Automated technologies that can perform massively parallelized and sequential fluidic operations at small length scales can resolve major bottlenecks encountered in various fields, including medical diagnostics, -omics, drug development, and chemical/material synthesis. Inspired by the transformational impact of automated guided vehicle systems on manufacturing, warehousing, and distribution industries, we devised a ferrobotic system that uses a network of individually addressable robots, each performing designated micro-/nanofluid manipulation-based tasks in cooperation with other robots toward a shared objective. The underlying robotic mechanism facilitating fluidic operations was realized by addressable electromagnetic actuation of miniature mobile magnets that exert localized magnetic body forces on aqueous droplets filled with biocompatible magnetic nanoparticles. The contactless and high-strength nature of the actuation mechanism inherently renders it rapid (~10 centimeters/second), repeatable (>10,000 cycles), and robust (>24 hours). The robustness and individual addressability of ferrobots provide a foundation for the deployment of a network of ferrobots to carry out cross-collaborative logistics efficiently. These traits, together with the reconfigurability of the system, were exploited to devise and integrate passive/active advanced functional components (e.g., droplet dispensing, generation, filtering, and merging), enabling versatile system-level functionalities. By applying this ferrobotic system within the framework of a microfluidic architecture, the ferrobots were tasked to work cross-collaboratively toward the quantification of active matrix metallopeptidases (a biomarker for cancer malignancy and inflammation) in human plasma, where various functionalities converged to achieve a fully automated assay.

Home automation using general purpose household electric appliances with Raspberry Pi and commercial smartphone.

This study presents the design and implementation of a home automation system that focuses on the use of ordinary electrical appliances for remote control using Raspberry Pi and relay circuits and does not use expensive IP-based devices. Common Lights, Heating, Ventilation, and Air Conditioning (HVAC), fans, and other electronic devices are among the appliances that can be used in this system. A smartphone app is designed that helps the user to design the smart home to his actual home via easy and interactive drag & drop option. The system provides control over the appliances via both the local network and remote access. Data logging over the Microsoft Azure cloud database ensures system recovery in case of gateway failure and data record for lateral use. Periodical notifications also help the user to optimize the usage of home appliances. Moreover, the user can set his preferences and the appliances are auto turned off and on to meet user-specific requirements. Raspberry Pi acting as the server maintains the database of each appliance. HTTP web interface and apache server are used for communication between the android app and raspberry pi. With a 5v relay circuit and micro-processor Raspberry Pi, the proposed system is low-cost, energy-efficient, easy to operate, and affordable for low-income houses.

Saving time maintaining reliability: a new method for quantification of Tetranychus urticae damage in Arabidopsis whole rosettes.

BACKGROUND: The model species Tetranychus urticae produces important plant injury and economic losses in the field. The current accepted method for the quantification of the spider mite damage in Arabidopsis whole rosettes is time consuming and entails a bottleneck for large-scale studies such as mutant screening or quantitative genetic analyses. Here, we describe an improved version of the existing method by designing an automatic protocol. The accuracy, precision, reproducibility and concordance of the new enhanced approach are validated in two Arabidopsis accessions with opposite damage phenotypes. Results are compared to the currently available manual method. RESULTS: Image acquisition experiments revealed that the automatic settings plus 10 values of brightness and the black background are the optimal conditions for a specific recognition of spider mite damage by software programs. Among the different tested methods, the Ilastik-Fiji tandem based on machine learning was the best procedure able to quantify the damage maintaining the differential range of damage between accessions. In addition, the Ilastik-Fiji tandem method showed the lowest variability within a set of conditions and the highest stability under different lighting or background surroundings. Bland-Altman concordance results pointed out a negative value for Ilastik-Fiji, which implies a minor estimation of the damage when compared to the manual standard method. CONCLUSIONS: The novel approach using Ilastik and Fiji programs entails a great improvement for the quantification of the specific spider mite damage in Arabidopsis whole rosettes. The automation of the proposed method based on interactive machine learning eliminates the subjectivity and inter-rater-variability of the previous manual protocol. Besides, this method offers a robust tool for time saving and to avoid the damage overestimation observed with other methods.

Expert Drivers' Prospective Thinking-Aloud to Enhance Automated Driving Technologies - Investigating Uncertainty and Anticipation in Traffic.

Current automated driving technology cannot cope in numerous conditions that are basic daily driving situations for human drivers. Previous studies show that profound understanding of human drivers' capability to interpret and anticipate traffic situations is required in order to provide similar capacities for automated driving technologies. There is currently not enough a priori understanding of these anticipatory capacities for safe driving applicable to any given driving situation. To enable the development of safer, more economical, and more comfortable automated driving experience, expert drivers' anticipations and related uncertainties were studied on public roads. First, driving instructors' expertise in anticipating traffic situations was validated with a hazard prediction test. Then, selected driving instructors drove in real traffic while thinking aloud anticipations of unfolding events. The results indicate sources of uncertainty and related adaptive and social behaviors in specific traffic situations and environments. In addition, the applicability of these anticipatory capabilities to current automated driving technology is discussed. The presented method and results can be utilized to enhance automated driving technologies by indicating their potential limitations and may enable improved situation awareness for automated vehicles. Furthermore, the produced data can be utilized for recognizing such upcoming situations, in which the human should take over the vehicle, to enable timely take-over requests.