Life Science Experiments Research Articles

The Charged Particle Detection System of the SRD Module onboard the China Space Station

The radiation field environment outside the Earth varies greatly with space location and the cycle of solar activity, and the radiation environment near the space station’s orbit is much more complex than that on the Earth’s surface. Various high-energy cosmic ray particles and secondary particles produced by them and the bulkhead of the space station greatly impact the health of astronauts and the working conditions of instruments. Each aircraft is always equipped with some dedicated radiation monitoring instruments to assess the exposure risk for astronauts, and to analyze the causes of instrument failures. The Space Radiation Detector Module (SRDM) is working in the China Space Station (CSS) to measure the radiation environment inside, including two parts: the Charged Particle Detection System (CPDS) and the Neutron Detection System (NDS). The CPDS, which is the main content of this paper, contains a detector unit, that consists of three silicon detectors a BGO calorimeter, and the corresponding readout electronics unit of the detector unit. Ground test results show that the detection system can detect various charged particles from hydrogen to nitrogen ions with an energy resolution of less than 15%. The actual measurement results for a period in orbit show that the main types of charged particles in the cabin are protons and α particles, with measured energies ranging from 0.8 to 265.2 MeV for protons and from 1.0 to 61.6 MeV/A for α particles(where A is the mass number), and linear energy density (LET) range mainly from 1.0 to 612.4 keV/μm. The radiation environment data measured in CSS can provide an important reference value for the exposure risk, life science experiments, and the status of instruments on board.

Drip Detection System based on STM32 Microcontroller

This design of the drip detection system is based on the STM32 microcontroller, making it highly practical and innovative. The system combines multiple sensors and control modules to achieve high-precision detection and monitoring of intravenous drip infusions. By integrating various sensors such as a drip rate detection module, a temperature sensor, and a water level detection module, the system can comprehensively monitor the status of the intravenous drip, including drip rate, liquid level, and temperature. Through data processing and control by the STM32 microcontroller, the system can real-time monitor the drip rate, liquid level, and temperature of the intravenous drip, and display these data on an OLED screen, providing intuitive information feedback. After conducting tests and analysis on the system, its stability and reliability have been verified. With its high-precision drip detection capability, the system can meet the needs of life science experiments for droplet detection. This system is widely applicable in various fields such as medical, chemistry, and biology. In the medical field, it can be used for precise drug delivery, thereby improving treatment effectiveness. In chemical and biological experiments, it can be used for accurate dispensing of liquid reagents, ensuring the accuracy of experimental results. The system features an OLED display, providing a user-friendly interface, and also comes with button operations, enabling users to conveniently set and operate system parameters. Overall, this drip detection system based on the STM32 microcontroller not only possesses a high level of technological sophistication but also has broad prospects for practical applications. It provides an efficient and accurate solution for droplet detection and will play a significant role in related fields.

Design of a Scanning Module in a Confocal Microscopic Imaging System for Live-Cell Imaging

This study proposes a Nipkow-based pinhole disk laser scanning confocal microscopic imaging system for ordinary optical microscopy, fluorescence microscopy, and confocal microscopy imaging of biological samples in order to realize the dynamic experimental monitoring of space-based life science experiments and the fine observation of biological samples. Confocal microscopic imaging is mainly completed by a scanning module that is composed of a spinning disk and other components. The parameters of the spinning disk directly determine the quality of the image. During the design process, the resolution and signal-to-noise ratios caused by different pinhole diameters in the spinning disk are the main considerations. Changes and image blurring caused by crosstalk due to the pinhole arrangement and different pinhole spacings are addressed. The high photon efficiency of the new EMCCD (electron-multiplying charge-coupled device) and CMOS (complementary metal-oxide-semiconductor) camera reduces the exposure time as much as possible, reduces damage to living cells, and achieves high-speed confocal imaging. It is shown in a confocal imaging experiment with a variable magnification of 1–40× that the imaging resolution of the system can reach a maximum of 2592 × 1944, the spatial resolution can reach 1 μm, and the highest sampling frequency is 10 fps, thus meeting the design requirements for high-speed live-cell imaging.

Optical simulations in life-sciences: Benefiting from ray-tracing in biotechnology and photobiology

The advent of LED technology opened up new possibilities for the implementation of versatile and complex illumination systems for photobiological and biophotonic studies. However, these new lighting systems also increase the requirement for accurate and reproducible characterization of existing light parameters such as irradiance or photon flux density. A direct determination with radiometer or quantum-meter is not always possible due to complex experimental setups. Optical simulations based on ray-tracing software can compensate the limitation of direct measurements and make more information regarding light quantities available. In this paper, we provide a guideline to modeling life-science experiments using ray-tracing software and demonstrate the potential of optical simulations by addressing specific scientific questions. In detail, we discuss irradiance distribution in UV inactivation studies and the determination of photon flux density in light-stress experiments with microalgae using ray-tracing software and comparing simulation results with optical measurements. Furthermore, we demonstrate the possibility to improve existing irradiation conditions by common optical engineering optimization techniques. This will be shown by means of a photobioreactor illumination as well as an application in the field of photodynamic therapy. Our simulation results were in good agreement with direct measurements and allowed us to gain additional information regarding light quantities that could not be measured directly.

SAGAS: Simulated annealing and greedy algorithm scheduler for laboratory automation.

During laboratory automation of life science experiments, coordinating specialized instruments and human experimenters for various experimental procedures is important to minimize the execution time. In particular, the scheduling of life science experiments requires the consideration of time constraints by mutual boundaries (TCMB) and can be formulated as the "scheduling for laboratory automation in biology" (S-LAB) problem. However, existing scheduling methods for the S-LAB problems have difficulties in obtaining a feasible solution for large-size scheduling problems at a time sufficient for real-time use. In this study, we proposed a fast schedule-finding method for S-LAB problems, SAGAS (Simulated annealing and greedy algorithm scheduler). SAGAS combines simulated annealing and the greedy algorithm to find a scheduling solution with the shortest possible execution time. We have performed scheduling on real experimental protocols and shown that SAGAS can search for feasible or optimal solutions in practicable computation time for various S-LAB problems. Furthermore, the reduced computation time by SAGAS enables us to systematically search for laboratory automation with minimum execution time by simulating scheduling for various laboratory configurations. This study provides a convenient scheduling method for life science automation laboratories and presents a new possibility for designing laboratory configurations.

Comparison of biological measurement and physical estimates of space radiation in the International Space Station

Nowadays, ordinary people can travel in space, and the possibility of extended durations in an environment such as moon of the Earth and Mars with higher space radiation exposures compared to past missions, is increasing. Until now, the physical doses of space radiation have been measured, but measurement of direct biological effects has been hampered by its low dose and low dose-rate effect. To assess the biological effects of space radiation, we launched and kept frozen mouse embryonic stem (ES) cells in minus eighty degree Celsius freezer in ISS (MELFI) on the International Space Station (ISS) for a maximum of 1,584 days. The passive dosimeter for life science experiments in space (PADLES) was attached on the surface of the sample case of the ES cells. The physical dosimeter measured the absorbed dose in water. After return, the frozen cells were thawed and cultured and their chromosome aberrations were analyzed. Comparative experiments with proton and iron ion irradiation were performed at particle accelerators on Earth. The wild-type ES cells showed no differences in chromosomal aberrations between the ground control and ISS exposures. However, we detected an increase of chromosome aberrations in radio-sensitized histone H2AX heterozygous-deficient mouse ES cells and found that the rate of increase against the absorbed dose was 1.54-fold of proton irradiation at an accelerator. On the other hand, we estimated the quality factor of space radiation as 1.48 ± 0.2. using formulas of International Commission of Radiation Protection (ICRP) 60. The relative biological effectiveness (RBE) observed from our experiments (1.54-fold of proton) was almost equal (1.04-fold) to the physical estimation (1.48 ± 0.2). It should be important to clarify the relation between biological effect and physical estimates of space radiation. This comparative study paves a way to reveal the complex radiation environments to reduce the uncertainty for risk assessment of human stay in space.

Back Cover: Trapping X‐ray Radiation Damage from Homolytic Se−C Bond Cleavage in BnSeSeBn Crystals (Bn=benzyl, CH2C6H5) (Angew. Chem. Int. Ed. 26/2022)

Radiation damage in the form of radical formation by homolytic Se−C bond cleavage was trapped by high-resolution X-ray and EPR experiments, as reported by Dietmar Stalke et al. in their Communication (DOI: 10.1002/anie.202203665). Orange dibenzyldiselenide single crystals are X-ray exposed with various intensities and the benzyl radical formation is monitored by multipole refinement and quantum/molecular mechanics. In any interpretation of selenium containing structures, particularly in life science experiments from synchrotrons, it is important to consider those radical-induced processes.

PathwAX II: network-based pathway analysis with interactive visualization of network crosstalk.

MotivationPathway annotation tools are indispensable for the interpretation of a wide range of experiments in life sciences. Network-based algorithms have recently been developed which are more sensitive than traditional overlap-based algorithms, but there is still a lack of good online tools for network-based pathway analysis.ResultsWe present PathwAX II—a pathway analysis web tool based on network crosstalk analysis using the BinoX algorithm. It offers several new features compared with the first version, including interactive graphical network visualization of the crosstalk between a query gene set and an enriched pathway, and the addition of Reactome pathways.Availability and implementationPathwAX II is available at http://pathwax.sbc.su.se.Supplementary information Supplementary data are available at Bioinformatics online.

Pushing the Limits in Real-Time Measurements of Quantum Dynamics.

Time-resolved studies of quantum systems are the key to understanding quantum dynamics at its core. The real-time measurement of individual quantum numbers as they switch between certain discrete values, well known as a "random telegraph signal," is expected to yield maximal physical insight. However, the signal suffers from both systematic errors, such as a limited time resolution and noise from the measurement apparatus, as well as statistical errors due to a limited amount of data. Here we demonstrate that an evaluation scheme based on factorial cumulants can reduce the influence of such errors by orders of magnitude. The error resilience is supported by a general theory for the detection errors as well as experimental data of single-electron tunneling through a self-assembled quantum dot. Thus, factorial cumulants push the limits in the analysis of random telegraph data, which represent a wide class of experiments in physics, chemistry, engineering, and life sciences.

Damping of vibration-isolated structures: A review

Vibration presents a major challenge to advanced experiments in physics and life sciences, as well as to precise manufacturing processes. A vibration-isolated platform had become an indispensable element of precision experimental and manufacturing systems. Ideally, the platform should behave as an absolutely rigid body; unfortunately, absolutely rigid bodies do not exist: any structure deviates from the rigid behavior at its resonance frequencies. Resonance vibrations of the platform carrying precision optomechanical or acoustical equipment can be excited by acoustical inputs, residual vibrations coming from the floor through vibration isolators, and atmospheric turbulence. These vibrations must be mitigated by dissipation of mechanical energy, or damping. This paper summarizes current methods and achievements in active and passive damping of optical tables and breadboards, applicable also to other types of structures. Dynamic response of an isolated platform is analyzed. Physical principles of active damping systems, multiple tuned dynamic absorbers, and elastomeric constrained-layer damping links are presented; various designs of damping devices are considered, and their operation illustrated by experimental results; advantages and shortcomings of each method are discussed.

Subgroup identification in individual participant data meta-analysis using model-based recursive partitioning

Model-based recursive partitioning (MOB) can be used to identify subgroups with differing treatment effects. The detection rate of treatment-by-covariate interactions and the accuracy of identified subgroups using MOB depend strongly on the sample size. Using data from multiple randomized controlled clinical trials can overcome the problem of too small samples. However, naively pooling data from multiple trials may result in the identification of spurious subgroups as differences in study design, subject selection and other sources of between-trial heterogeneity are ignored. In order to account for between-trial heterogeneity in individual participant data (IPD) meta-analysis random-effect models are frequently used. Commonly, heterogeneity in the treatment effect is modelled using random effects whereas heterogeneity in the baseline risks is modelled by either fixed effects or random effects. In this article, we propose metaMOB, a procedure using the generalized mixed-effects model tree (GLMM tree) algorithm for subgroup identification in IPD meta-analysis. Although the application of metaMOB is potentially wider, e.g. randomized experiments with participants in social sciences or preclinical experiments in life sciences, we focus on randomized controlled clinical trials. In a simulation study, metaMOB outperformed GLMM trees assuming a random intercept only and model-based recursive partitioning (MOB), whose algorithm is the basis for GLMM trees, with respect to the false discovery rates, accuracy of identified subgroups and accuracy of estimated treatment effect. The most robust and therefore most promising method is metaMOB with fixed effects for modelling the between-trial heterogeneity in the baseline risks.

Optimal Scheduling for Laboratory Automation of Life Science Experiments with Time Constraints.

In automated laboratories consisting of multiple different types of instruments, scheduling algorithms are useful for determining the optimal allocations of instruments to minimize the time required to complete experimental procedures. However, previous studies on scheduling algorithms for laboratory automation have not emphasized the time constraints by mutual boundaries (TCMBs) among operations, which is important in procedures involving live cells or unstable biomolecules. Here, we define the “scheduling for laboratory automation in biology” (S-LAB) problem as a scheduling problem for automated laboratories in which operations with TCMBs are performed by multiple different instruments. We formulate an S-LAB problem as a mixed-integer programming (MIP) problem and propose a scheduling method using the branch-and-bound algorithm. Simulations show that our method can find the optimal schedules of S-LAB problems that minimize overall execution time while satisfying the TCMBs. Furthermore, we propose the use of our scheduling method for the simulation-based design of job definitions and laboratory configurations.

The XBI BioLab for life science experiments at the European XFEL.

The science of X-ray free-electron lasers (XFELs) critically depends on the performance of the X-ray laser and on the quality of the samples placed into the X-ray beam. The stability of biological samples is limited and key biomolecular transformations occur on short timescales. Experiments in biology require a support laboratory in the immediate vicinity of the beamlines. The XBI BioLab of the European XFEL (XBI denotes XFEL Biology Infrastructure) is an integrated user facility connected to the beamlines for supporting a wide range of biological experiments. The laboratory was financed and built by a collaboration between the European XFEL and the XBI User Consortium, whose members come from Finland, Germany, the Slovak Republic, Sweden and the USA, with observers from Denmark and the Russian Federation. Arranged around a central wet laboratory, the XBI BioLab provides facilities for sample preparation and scoring, laboratories for growing prokaryotic and eukaryotic cells, a Bio Safety Level 2 laboratory, sample purification and characterization facilities, a crystallization laboratory, an anaerobic laboratory, an aerosol laboratory, a vacuum laboratory for injector tests, and laboratories for optical microscopy, atomic force microscopy and electron microscopy. Here, an overview of the XBI facility is given and some of the results of the first user experiments are highlighted.

ASSESSING PRE-SERVICE TEACHERS’ RECEPTION AND ATTITUDES TOWARDS VIRTUAL LABORATORY EXPERIMENTS IN LIFE SCIENCES

This research reports the assessment of pre-service teachers’ reception and attitudes towards virtual laboratory experiments in Life Sciences with the aim of advancing adaptability to digital learning. Using sequential mixed-methods in a quasi-experimental design, 68 pre-service teachers in the 3rd year of a Bachelor of Education (B.Ed) program were surveyed before and after virtual learning interventions. This phase was followed by qualitative data gathering using focus group interviews with all participants. Findings from quantitative data analysis revealed a positive significant difference in pre-service teachers’ attitudes towards virtual laboratory experiments post learning interventions. From qualitative data pre-service teachers found the progression from using only traditional to including virtual experiments was useful in enhancing their conceptual understandings of Life Sciences concepts, convenience, inquiry-based learning, self-directed and autonomous learning. However, pre-service teachers noted that using virtual laboratories did not significantly develop their science process skills and as a result could not replace the experiences in a traditional biology laboratory. The implications of these findings project virtual laboratories as a supporting tool for experimentation in Life Sciences especially within and post the COVID-19 pandemic where issues of social distancing pose a threat to collaborative and inquiry-based science learning. Recommendations from these findings are discussed herein. Keywords: inquiry-based learning, life sciences, pre-service teachers, virtual laboratory experiments

Share the details of your experimental methods

Incomplete methods sections have made it difficult for researchers to replicate and build on the work of others, contributing to problems in reproducibility. It is important to increase the level of detail in our methods sections and to share step-by-step protocols in protocol repositories or journals. Request a Protocol is a new feature in Molecular Biology of the Cell that allows readers to request detailed protocols directly from the methods section of the research article, with links between the protocols and the research articles, and has the potential to improve research reproducibility and help everyone design and execute robust life science experiments.

SmartPeak Automates Targeted and Quantitative Metabolomics Data Processing.

Technological advances in high-resolution mass spectrometry (MS) vastly increased the number of samples that can be processed in a life science experiment, as well as volume and complexity of the generated data. To address the bottleneck of high-throughput data processing, we present SmartPeak (https://github.com/AutoFlowResearch/SmartPeak), an application that encapsulates advanced algorithms to enable fast, accurate, and automated processing of capillary electrophoresis-, gas chromatography-, and liquid chromatography (LC)-MS(/MS) data and high-pressure LC data for targeted and semitargeted metabolomics, lipidomics, and fluxomics experiments. The application allows for an approximate 100-fold reduction in the data processing time compared to manual processing while enhancing quality and reproducibility of the results.

LiMM‐PCA: Combining ASCA+ and linear mixed models to analyse high‐dimensional designed data

AbstractNowadays, life science experiments—and especially “omics” fields—often imply a high volume of information from high throughput technologies that is gathered in the form of a wide and short multivariate response. These data are intrinsically correlated and generally produced by another multivariate set of factors or continuous variables, collected in what is defined as the design matrix. Such design factors usually involve the presence of a treatment, but other sources of biological or technical variability in the data are often measured as well. The ASCA framework, based on ANOVA and PCA, leads to promising results. By combining dimension reduction projection methods and classic statistical modelling, it enables to decipher the main sources of variability in the produced response and offers attractive graphical representations of the factors' effect. However, this approach has not yet been extended to more advanced designs involving random factors, being typically involved in longitudinal, hierarchical, or repeatability/reproducibility studies. This paper has its roots in the GLM version of ASCA, called ASCA+, that leads to unbiased estimators of the factors' effects for unbalanced data. It is here extended by replacing GLM by LMM and adapting the methodology. Taking into account the error structure of the data indeed leads to more accurate data modelling and more generalisable results. The suggested methodology is applied to two experimental case studies that highlight the benefits of this approach as it leads to a refined data analysis with interesting inferential properties, while keeping the powerful visualisation outputs produced by ASCA.

PurifyR: An R Package for Highly Automated, Reproducible Variable Extraction and Standardization

Life science experiments that employ automated technologies, such as high-content screens, frequently produce large datasets that require substantial amounts of preprocessing before analysis can be carried out. Standardization of this preprocessing becomes impossible as the dataset size increases if there are manual steps involved. Virtually no standards for preprocessing currently exist and few user-friendly tools are available that allow the cleaning of data files in a simple and transparent manner while also allowing for reproducibility. We demonstrate in a publicly available R package, PurifyR, how preprocessing steps can be streamlined and automated. PurifyR supports multithreading and the standardization of large-matrix preprocessing. These steps provide transparent and reproducible preprocessing for matrix-oriented datasets. The PurifyR package is open source and can be downloaded from github.

The MAPHEUS module CellFix for studying the influence of altered gravity on the physiology of single cells.

Gravity is the only constant stimulus during the evolution of life. To investigate the impact of the absence of gravity on living systems, their molecular and morphological status has to be studied under microgravity conditions. The experiment unit CellFix was developed in order to provide the possibility of exposure and chemical fixation of small biological systems, such as neurons, stem cells, small animals, yeast cultures, plants, etc., at dedicated time points during a sounding rocket flight. The current version of CellFix consists of two culture bags containing cell cultures in a temperature-controlled pressure vessel. The biosystems in the culture bags can be fixed by pumping the fixative [e.g., paraformaldehyde (PFA), methanol, RNAlater, or others] from a connected bag into the cell suspension. The mechatronic basis of the experiment unit is constructed from compartments of the shelf parts. Open source microcontroller systems (Arduino) or gear pumps, accumulators, etc., from the model making sector are affordable and reliable components to build up an experiment on an unmanned space mission such as a sounding rocket flight. Also, new technologies such as fused deposition modeling were used to construct structures and brackets, which were tested successfully in environmental tests and real space flights (MAPHEUS 7 and 8 sounding rocket missions). In combination with the possibility to handle the experiment as a late access insert in a standardized rocket compartment, CellFix provides a multiusable experiment unit for performing life science experiments in space.

Interactive programming paradigm for real-time experimentation with remote living matter

Recent advancements in life-science instrumentation and automation enable entirely new modes of human interaction with microbiological processes and corresponding applications for science and education through biology cloud laboratories. A critical barrier for remote and on-site life-science experimentation (for both experts and nonexperts alike) is the absence of suitable abstractions and interfaces for programming living matter. To this end we conceptualize a programming paradigm that provides stimulus and sensor control functions for real-time manipulation of physical biological matter. Additionally, a simulation mode facilitates higher user throughput, program debugging, and biophysical modeling. To evaluate this paradigm, we implemented a JavaScript-based web toolkit, "Bioty," that supports real-time interaction with swarms of phototactic Euglena cells hosted on a cloud laboratory. Studies with remote and on-site users demonstrate that individuals with little to no biology knowledge and intermediate programming knowledge were able to successfully create and use scientific applications and games. This work informs the design of programming environments for controlling living matter in general, for living material microfabrication and swarm robotics applications, and for lowering the access barriers to the life sciences for professional and citizen scientists, learners, and the lay public.