ReachingBot: an automated and scalable benchtop device for highly parallel Single Pellet Reach-and-Grasp training and assessment in mice

BACKGROUND

The single pellet reaching and grasp (SPRG) task is a behavioural assay widely used to study motor learning, control and recovery after nervous system injury in animals. The manual training and assessment of the SPRG is labour intensive and time consuming and has led to the development of multiple devices which automate the SPRG task.

NEW METHOD

Here, using robotics, computer vision, and machine learning analysis of videos, we describe a device that can be left unattended, presents pellets to mice, and, using two supervised learning algorithms, classifies the outcome of each trial with an accuracy of greater than 94% without the use of graphical processing units (GPUs). Our devices can also be operated using our cross-platform Graphical User Interface (GUI).

RESULTS

We show that these devices train and assess mice in parallel. 21 out of 30 mice retrieved >40% of pellets successfully following the training period. Following ischaemic stroke; some mice showed large persistent deficits whilst others showed only transient deficits. This highlights the heterogeneity in reaching outcomes following stroke.

COMPARISON WITH EXISTING METHOD(S)

Current state-of-the-art desktop methods either still require supervision, manual classification of trial outcome, or expensive locally-installed hardware such as graphical processing units (GPUs).

CONCLUSIONS

ReachingBots successfully automated SPRG training and assessment and revealed the heterogeneity in reaching outcomes following stroke. We conjecture that reach-and-grasp is represented in motor cortex bilaterally but with greater asymmetry in some mice than in others.

Towards robotic laboratory automation Plug & play: Survey and concept proposal on teaching-free robot integration with the lapp digital twin

The Laboratory Automation Plug & Play (LAPP) framework is an over-arching reference architecture concept for the integration of robots in life science laboratories. The plug & play nature lies in the fact that manual configuration is not required, including the teaching of the robots. In this paper a digital twin (DT) based concept is proposed that outlines the types of information that must be provided for each relevant component of the system. In particular, for the devices interfacing with the robot, the robot positions must be defined beforehand in a device-attached coordinate system (CS) by the vendor. This CS must be detectable by the vision system of the robot by means of optical markers placed on the front side of the device. With that, the robot is capable of tending the machine by performing the pick-and-place type transportation of standard sample carriers. This basic use case is the primary scope of the LAPP-DT framework. The hardware scope is limited to simple benchtop and mobile manipulators with parallel grippers at this stage. This paper first provides an overview of relevant literature and state-of-the-art solutions, after which it outlines the framework on the conceptual level, followed by the specification of the relevant DT parameters for the robot, for the devices and for the facility. Finally, appropriate technologies and strategies are identified for the implementation.

Sidekick: A Low-Cost Open-Source 3D-printed liquid dispensing robot

The Sidekick is a desktop liquid dispenser, compatible with standard SBS microplates and designed for accessible laboratory automation. It features an armature-based motion system and a fully 3D-printed chassis to reduce overall mechanical complexity and accommodate user modification. Liquid dispensing is achieved with four commercially available solenoid driven positive displacement pumps that deliver liquid in 10 µL increments. A Raspberry Pi Pico RP2040 processor programmed in MicroPython is used for control, and exposes a USB serial interface for users to submit commands using either a simple vocabulary of commands or a subset of G-Code. At a total cost of $710 USD, the Sidekick offers laboratories an easy to build, easily maintained, open-source liquid dispensing system for both research and pedagogical introductions to lab automation.

Evaluation of the Risk of Laboratory Microbial Contamination during Routine Testing in Automated Clinical Chemistry and Microbiology Laboratories

BACKGROUND

Every clinical specimen is potentially infectious, but data regarding risk for contamination of the laboratory environment during routine testing are scarce. We assessed contamination during routine sample analysis in automated clinical chemistry and microbiology laboratories.

METHODS

A fluorescent marker was applied to specimen container exteriors to assess the impact of gross contamination. Nonpathogenic MS2 virus was added to remnant blood, urine, and ESwab matrices as a biomarker of cross-contamination. Samples were processed and analyzed using Roche Cobas 8100 and ISE, c502, e602, and c702 modules (blood) and BD Kiestra total laboratory automation (blood, urine, ESwabs) over 3 experiments. Fluorescence transfer to laboratory surfaces and personnel was visualized using ultraviolet light. Surfaces were swabbed and assessed for MS2 cross-contamination by RT-PCR. Adherence to standard precautions by laboratory staff was assessed by observation.

RESULTS

Fluorescence was observed on 49 of 165 (30%) laboratory surfaces and personnel and 21 of 93 (23%) total laboratory automation instruments. Fluorescence transferred most frequently to gloves (31/40), computer accessories (9/18), and specimen loading racks (12/12). None of 123 areas swabbed were positive for MS2. Improper personal protective equipment use occurred at a rate of 0.36 and 0.15 events per staff per hour in the chemistry and microbiology laboratories, respectively. Hand-washing compliance was observed for 61 of 132 (46%) staff members evaluated.

CONCLUSIONS

Analysis of grossly contaminated specimens on automated chemistry and microbiology equipment elicits a low likelihood of instrument contamination. However, handling contaminated specimen containers can result in contamination of environmental laboratory surfaces, representing a source of risk that is heightened by low adherence to appropriate personal protective equipment.