Reproducible preclinical research-Is embracing variability the answer?

Combatting Pseudomonas aeruginosa with β-Lactam Antibiotics: A Revived Weapon?

Pseudomonas aeruginosa is a significant threat to public health as an aggressive, opportunistic pathogen. The use of β-lactam antibiotics such as penicillins, cephalosporins, monobactams, and carbapenems remains a front-line treatment against P. aeruginosa. However, the widespread use of β-lactams has led to the emergence of β-lactam-resistant isolates that significantly increase the economic burden and risk of mortality in patients. With the declining productivity of the antibiotic discovery pipeline, research has investigated synergistic agents to revive the use of β-lactam antibiotics against β-lactam-resistant P. aeruginosa. In this review, we summarize the mechanism of β-lactam antibiotics and provide an overview of major mechanisms associated with β-lactam resistance in P. aeruginosa. We then describe the background and use of three promising classes of agents that have shown extensive beneficial effects with β-lactam antibiotics against P. aeruginosa, namely β-lactamase inhibitors, bacteriophages, and antimicrobial peptides. The current understanding of the mechanisms of these synergistic agents is discussed. Lastly, we provide an overview of the current barriers impeding antibiotic development, and offer a glimpse into recent advances of artificial intelligence-based discovery that may serve as a new foundation for antimicrobial discovery and treatment.

Extraordinarily corrupt or statistically commonplace? Reproducibility crises may stem from a lack of understanding of outcome probabilities

Reports of crises of reproducibility have abounded in the scientific and popular press, and are often attributed to questionable research practices, lack of rigor in protocols, or fraud. On the other hand, it is a known fact that-just like observations in a single biological experiment-outcomes of biological replicates will vary; nevertheless, that variability is rarely assessed formally. Here I argue that some instances of failure to replicate experiments are in fact failures to properly describe the structure of variance. I formalize a hierarchy of distributions that represent the system-level and experiment-level effects, and correctly account for the between-and within-experiment variances, respectively. I also show that this formulation is straightforward to implement and generalize through Bayesian hierarchical models, although it doesn't preclude the use of Frequentist models. One of the main results of this approach is that a set of repetitions of an experiment, instead of being described by irreconcilable string of significant/nonsignificant results, are described and consolidated as a system-level distribution. As a corollary, stronger statements about a system can only be made by analyzing a number of replicates, so I argue that scientists should refrain from making them based on individual experiments.

Navigating the paradigm shift of sex inclusive preclinical research and lessons learnt

As progress is made in sex-inclusive preclinical research, the author highlights areas of research practice where significant development has been achieved & where more change is needed towards community accepted standards in equitable research

Current status of next-generation vaccines against mpox virus: a scoping review

Introduction

The mpox disease, caused by the mpox virus (MPXV), has become a rising public health issue due to its potential to cause outbreaks. Consistently, this investigation aims to evaluate the current advances in the development of novel immunotherapeutic approaches against MPXV, which are crucial for preventing and controlling mpox spread.

Methods

This scoping review was performed by analyzing the content of English-language articles published between 2018 and 2024, which reported the development of next-generation vaccines against MPXV and their assessment in animal models. Patents within the scope of this research were also included. Contrarywise, studies based solely on immunoinformatic methods, reviews, book chapters, news, and others were excluded. The literature search was executed in 11 databases, such as Scopus, MEDLINE, and PubMed.

Results

A total of 36 records (32 studies and 4 patents) were included in this review. All 32 articles contain preclinical studies with varied group sizes (4-16) in which the main animal models were BALB/c mice. Less commonly used models included CAST/Ei mice and cynomolgus macaques. Moreover, most vaccines targeted one or more MPXV antigens, such as A29L, A35R, B6R, and M1R, through active immunization (via mRNAs or recombinant antigens) or passive immunization (antibody delivery).

Conclusion

Overall, new generation vaccines might represent prospective candidates to combat the mpox health concern. Nonetheless, several of the analyzed studies possess drawbacks, including animal models with limited similarity to humans, small group sizes, and brief follow-up durations. Consequently, additional research is required to ascertain the long-term protection, efficacy, and safety of these immunotherapeutic approaches.

Characterization of commercial detectors for absolute proton UHDR dosimetry on a compact clinical proton synchrocyclotron

BACKGROUND

Modern compact proton synchrocyclotrons can achieve ultra-high dose rates ( ≥ $ \ge $ 40 Gy/s) to support ultra-high-dose-rate (UHDR) preclinical experiments utilizing pencil beam scanning (PBS) protons. Unique to synchrocyclotrons is a pulsed proton time structure as compared to the quasi-continuous nature of other proton accelerators like isochronous cyclotrons. Thus, high instantaneous proton currents in the order of several µA must be generated to achieve UHDRs. This will lead to high doses-per-pulse (DPP), which may cause significant charge recombination for ionization chambers, which must be characterized for accurate UHDR dosimetry programs.

PURPOSE

In this work, we investigate the suitability of various commercial radiation detectors for accurate proton UHDR dosimetry using PBS proton beams from a compact proton synchrocyclotron (IBA ProteusONE). This is achieved by cross-calibrating them with conventional dose rates, measuring UHDR recombination (Pion) and polarity correction factors (Ppol) for ionization chambers, and determining the absorbed proton UHDR dose delivered for all detectors.

METHODS

An IBA ProteusONE synchrocyclotron was initially tuned to achieve UHDRs with 228 MeV protons at 0° gantry angle. Various detectors, including Razor Chamber, Razor Nano Chamber, Razor Diode, and microDiamond, were cross-calibrated against a PPC05 plane-parallel ionization chamber (PPIC) that had an ADCL calibration coefficient of 59.23 cGy/nC. Then, all ionization chambers were exposed to UHDR protons with the Ppol and Pion subsequently calculated. Pion was calculated using two methods: TRS-398 methods and Niatel's model. Finally, the absolute UHDR proton doses delivered were determined for all detectors and cross-compared.

RESULTS

Faraday cup measurements were performed for a single spot proton UHDR beam, and the nozzle current at the isocenter was determined to be 129.5 nA during UHDR irradiations at 98.61% of the maximum theoretical dose rate. Repeated Faraday cup measurements of the UHDR beam yielded a percentage standard deviation of 0.8%, which was higher than 0.120% when similar repeated measurements were performed with conventional proton beams. Ppol was found to be relatively dose-rate independent for all ionization chambers investigated. Pion was found to be the lowest for the PPC05 ionization chamber (1.0097) compared to corresponding values of 1.0214 and 1.0294 for the Razor and Razor Nano detectors, respectively, for UHDRs. Pion values calculated using Niatel's model closely matched values from TRS-398 if the VH/VL ratio were kept at 2.5 for the PPC05 and Razor detectors and 2.0 for the Razor Nano detector. Absolute proton UHDR doses determined using cross-calibration factors were generally within ± 1% of PPC05 measurements. However, Razor Diode was found to over-respond by up to 3.79% within UHDR proton beams, rendering them unsuitable for proton UHDR dosimetry.

CONCLUSION

In this work, we comprehensively evaluated the suitability of various commercial detectors for absolute dosimetry with a pulsed UHDR beam structure from a proton synchrocyclotron. PPC05 had the lowest ionic recombination correction compared to Razor and Razor Nano ion chambers. Other than the diode detector, all other investigated detectors (PPC05, Razor, Razor Nano, microDiamond) were within ± 1% of one another and can be used for accurate absolute proton UHDR dosimetry.

Nanoparticles of natural product-derived medicines: Beyond the pandemic

This review explores the synergistic potential of natural products and nanotechnology for viral infections, highlighting key antiviral, immunomodulatory, and antioxidant properties to combat pandemics caused by highly infectious viruses. These pandemics often result in severe public health crises, particularly affecting vulnerable populations due to respiratory complications and increased mortality rates. A cytokine storm is initiated when an overload of pro-inflammatory cytokines and chemokines is released, leading to a systemic inflammatory response. Viral mutations and the limited availability of effective drugs, vaccines, and therapies contribute to the continuous transmission of the virus. The coronavirus disease-19 (COVID-19) pandemic has sparked renewed interest in natural product-derived antivirals. The efficacy of traditional medicines against pandemic viral infections is examined. Their antiviral, immunomodulatory, anti-inflammatory, and antioxidant properties are highlighted. This review discusses how nanotechnology enhances the efficacy of herbal medicines in combating viral infections.

Multi-Institutional Audit of FLASH and Conventional Dosimetry With a 3D Printed Anatomically Realistic Mouse Phantom

PURPOSE

We conducted a multi-institutional dosimetric audit between FLASH and conventional dose rate (CONV) electron irradiations by using an anatomically realistic 3-dimensional (3D) printed mouse phantom.

METHODS AND MATERIALS

A computed tomography (CT) scan of a live mouse was used to create a 3D model of bony anatomy, lungs, and soft tissue. A dual-nozzle 3D printer was used to print the mouse phantom using acrylonitrile butadiene styrene (∼1.02 g/cm3) and polylactic acid (∼1.24 g/cm3) simultaneously to simulate soft tissue and bone densities, respectively. The lungs were printed separately using lightweight polylactic acid (∼0.64 g/cm3). Hounsfield units (HU), densities, and print-to-print stability of the phantoms were assessed. Three institutions were each provided a phantom and each institution performed 2 replicates of irradiations at selected anatomic regions. The average dose difference between FLASH and CONV dose distributions and deviation from the prescribed dose were measured with radiochromic film.

RESULTS

Compared with the reference CT scan, CT scans of the phantom demonstrated mass density differences of 0.10 g/cm3 for bone, 0.12 g/cm3 for lung, and 0.03 g/cm3 for soft tissue regions. Differences in HU between phantoms were <10 HU for soft tissue and bone, with lung showing the most variation (54 HU), but with minimal effect on dose distribution (<0.5%). Mean differences between FLASH and CONV decreased from the first to the second replicate (4.3%-1.2%), and differences from the prescribed dose decreased for both CONV (3.6%-2.5%) and FLASH (6.4%-2.7%). Total dose accuracy suggests consistent pulse dose and pulse number, although these were not specifically assessed. Positioning variability was observed, likely due to the absence of robust positioning aids or image guidance.

CONCLUSIONS

This study marks the first dosimetric audit for FLASH using a nonhomogeneous phantom, challenging conventional calibration practices reliant on homogeneous phantoms. The comparison protocol offers a framework for credentialing multi-institutional studies in FLASH preclinical research to enhance reproducibility of biologic findings.

Unbiased serum metabolomic analysis in cats with naturally occurring chronic enteropathies before and after medical intervention

Chronic enteropathies (CE) are common disorders in cats and the differentiation between the two main underlying diseases, inflammatory bowel disease (IBD) and low-grade intestinal T-cell lymphoma (LGITL), can be challenging. Characterization of the serum metabolome could provide further information on alterations of disease-associated metabolic pathways and may identify diagnostic or therapeutic targets. Unbiased metabolomics analysis of serum from 28 cats with CE (14 cats with IBD, 14 cats with LGITL) and 14 healthy controls identified 1,007 named metabolites, of which 129 were significantly different in cats with CE compared to healthy controls at baseline. Random Forest analysis revealed a predictive accuracy of 90% for differentiating controls from cats with chronic enteropathy. Metabolic pathways found to be significantly altered included phospholipids, amino acids, thiamine, and tryptophan metabolism. Several metabolites were found to be significantly different between cats with IBD versus LGITL, including several sphingolipids, phosphatidylcholine 40:7, uridine, pinitol, 3,4-dihydroxybenzoic acid, and glucuronic acid. However, random forest analysis revealed a poor group predictive accuracy of 60% for the differentiation of IBD from LGITL. Of 129 compounds found to be significantly different between healthy cats and cats with CE at baseline, 58 remained different following treatment.

The intervention of cannabinoid receptor in chronic and acute kidney disease animal models: a systematic review and meta-analysis

AIM

Cannabinoid receptors are components of the endocannabinoid system that affect various physiological functions. We aim to investigate the effect of cannabinoid receptor modulation on kidney disease.

METHODS

PubMed, Web of Science databases, and EMBASE were searched. Articles selection, data extraction and quality assessment were independently performed by two investigators. The SYRCLE's RoB tool was used to assess the risk of study bias, and pooled SMD using a random-effect model and 95% CIs were calculated. Subgroup analyses were conducted in preselected subgroups, and publication bias was evaluated. We compared the effects of CB1 and CB2 antagonists and/or knockout and agonists and/or genetic regulation on renal function, blood glucose levels, body weight, and pathological damage-related indicators in different models of chronic and acute kidney injury.

RESULTS

The blockade or knockout of CB1 could significantly reduce blood urea nitrogen [SMD,- 1.67 (95% CI - 2.27 to - 1.07)], serum creatinine [SMD, - 1.88 (95% CI - 2.91 to - 0.85)], and albuminuria [SMD, - 1.60 (95% CI - 2.16 to - 1.04)] in renal dysfunction animals compared with the control group. The activation of CB2 group could significantly reduce serum creatinine [SMD, - 0.97 (95% CI - 1.83 to - 0.11)] and albuminuria [SMD, - 2.43 (95% CI - 4.63 to - 0.23)] in renal dysfunction animals compared with the control group.

CONCLUSIONS

The results suggest that targeting cannabinoid receptors, particularly CB1 antagonists and CB2 agonists, can improve kidney function and reduce inflammatory responses, exerting a renal protective effect and maintaining therapeutic potential in various types of kidney disease.

Finding the right power balance: Better study design and collaboration can reduce dependence on statistical power

Power analysis currently dominates sample size determination for experiments, particularly in grant and ethics applications. Yet, this focus could paradoxically result in suboptimal study design because publication biases towards studies with the largest effects can lead to the overestimation of effect sizes. In this Essay, we propose a paradigm shift towards better study designs that focus less on statistical power. We also advocate for (pre)registration and obligatory reporting of all results (regardless of statistical significance), better facilitation of team science and multi-institutional collaboration that incorporates heterogenization, and the use of prospective and living meta-analyses to generate generalizable results. Such changes could make science more effective and, potentially, more equitable, helping to cultivate better collaborations.

Variability in variability: does variation in morphological and physiological traits differ between men and women?

Many researchers presume greater variability between female participants than between males due to the menstrual cycle. This view has encouraged a sex bias in health and medical research, resulting in considerable knowledge gaps with important clinical implications. Yet in another field-evolutionary biology-the received wisdom is the reverse: that men are more variable, possibly due to male heterogamety. To test these competing hypotheses, we compared variance between the sexes for 50 morphological and physiological traits, analysing data from the NHANES database. Nearly half the traits did not exhibit sexual dimorphism in variation, while 18 exhibited greater female variation (GFV), indicating GFV does not dominate human characteristics. Only eight traits exhibited greater male variation (GMV), indicating GMV also does not dominate, and in turn offering scant support for the heterogamety hypothesis. When our analysis was filtered to include only women with regular menstrual cycles (and men of equivalent age), the number of traits with GFV and GMV were low and not statistically different, suggesting that the menstrual cycle does not typically explain GFV when it occurs. In practical terms, health and medical researchers should no longer simply assume that female participants will induce additional variation in the traits of interest.

A multi-lab experimental assessment reveals that replicability can be improved by using empirical estimates of genotype-by-lab interaction

The utility of mouse and rat studies critically depends on their replicability in other laboratories. A widely advocated approach to improving replicability is through the rigorous control of predefined animal or experimental conditions, known as standardization. However, this approach limits the generalizability of the findings to only to the standardized conditions and is a potential cause rather than solution to what has been called a replicability crisis. Alternative strategies include estimating the heterogeneity of effects across laboratories, either through designs that vary testing conditions, or by direct statistical analysis of laboratory variation. We previously evaluated our statistical approach for estimating the interlaboratory replicability of a single laboratory discovery. Those results, however, were from a well-coordinated, multi-lab phenotyping study and did not extend to the more realistic setting in which laboratories are operating independently of each other. Here, we sought to test our statistical approach as a realistic prospective experiment, in mice, using 152 results from 5 independent published studies deposited in the Mouse Phenome Database (MPD). In independent replication experiments at 3 laboratories, we found that 53 of the results were replicable, so the other 99 were considered non-replicable. Of the 99 non-replicable results, 59 were statistically significant (at 0.05) in their original single-lab analysis, putting the probability that a single-lab statistical discovery was made even though it is non-replicable, at 59.6%. We then introduced the dimensionless "Genotype-by-Laboratory" (GxL) factor-the ratio between the standard deviations of the GxL interaction and the standard deviation within groups. Using the GxL factor reduced the number of single-lab statistical discoveries and alongside reduced the probability of a non-replicable result to be discovered in the single lab to 12.1%. Such reduction naturally leads to reduced power to make replicable discoveries, but this reduction was small (from 87% to 66%), indicating the small price paid for the large improvement in replicability. Tools and data needed for the above GxL adjustment are publicly available at the MPD and will become increasingly useful as the range of assays and testing conditions in this resource increases.

Large inherent variability in data derived from highly standardised cell culture experiments

Cancer drug development is hindered by high clinical attrition rates, which are blamed on weak predictive power by preclinical models and limited replicability of preclinical findings. However, the technically feasible level of replicability remains unknown. To fill this gap, we conducted an analysis of data from the NCI60 cancer cell line screen (2.8 million compound/cell line experiments), which is to our knowledge the largest depository of experiments that have been repeatedly performed over decades. The findings revealed profound intra-laboratory data variability, although all experiments were executed following highly standardised protocols that avoid all known confounders of data quality. All compound/ cell line combinations with > 100 independent biological replicates displayed maximum GI50 (50% growth inhibition) fold changes (highest/ lowest GI50) > 5% and 70.5% displayed maximum fold changes > 1000. The highest maximum fold change was 3.16 × 10¹⁰ (lowest GI50: 7.93 ×10^-10 µM, highest GI50: 25.0 µM). FDA-approved drugs and experimental agents displayed similar variation. Variability remained high after outlier removal, when only considering experiments that tested drugs at the same concentration range, and when only considering NCI60-provided quality-controlled data. In conclusion, high variability is an intrinsic feature of anti-cancer drug testing, even among standardised experiments in a world-leading research environment. Awareness of this inherent variability will support realistic data interpretation and inspire research to improve data robustness. Further research will have to show whether the inclusion of a wider variety of model systems, such as animal and/ or patient-derived models, may improve data robustness.

A Systematic Review and Meta-Analysis on the Therapeutic Efficacy of Heparin and Low Molecular Weight Heparins in Animal Studies of Traumatic Brain Injury

The identification of effective pharmacotherapies for traumatic brain injury (TBI) remains a major challenge. Treatment with heparin and its derivatives is associated with neuroprotective effects after experimental TBI; however, the optimal dosage and method of administration, modes of action, and effects on hemorrhage remain unclear. Therefore, this review aimed to systematically evaluate, analyze, and summarize the available literature on the use of heparin and low molecular weight heparins (LMWHs) as treatment options for experimental TBI. We searched two online databases (PubMed and ISI Web of Science) to identify relevant studies. Data pertaining to TBI paradigm, animal subjects, drug administration, and all pathological and behavior outcomes were extracted. Eleven studies met our pre-specified inclusion criteria, and for outcomes with sufficient numbers, data from seven publications were analyzed in a weighted mean difference meta-analysis using a random-effects model. Study quality and risk of bias were also determined. Meta-analysis revealed that heparin and its derivatives decreased brain edema, leukocyte rolling, and vascular permeability, and improved neurological function. Further, treatment did not aggravate hemorrhage. These findings must be interpreted with caution, however, because they were determined from a limited number of studies with substantial heterogeneity. Also, overall study quality was low based on absences of data reporting, and potential publication bias was identified. Importantly, we found that there are insufficient data to evaluate the variables we had hoped to investigate. The beneficial effects of heparin and LMWHs, however, suggest that further pre-clinical studies are warranted.

Understanding the importance of quality control and quality assurance in preclinical PET/CT imaging

The fundamental principle of experimental design is to ensure efficiency and efficacy of the performed experiments. Therefore, it behoves the researcher to gain knowledge of the technological equipment to be used. This should include an understanding of the instrument quality control and assurance requirements to avoid inadequate or spurious results due to instrumentation bias whilst improving reproducibility. Here, the important role of preclinical positron emission tomography/computed tomography and the scanner's required quality control and assurance is presented along with the suggested guidelines for quality control and assurance. There are a multitude of factors impeding the continuity and reproducibility of preclinical research data within a single laboratory as well as across laboratories. A more robust experimental design incorporating validation or accreditation of the scanner performance can reduce inconsistencies. Moreover, the well-being and welfare of the laboratory animals being imaged is prime justification for refining experimental designs to include verification of instrumentation quality control and assurance. Suboptimal scanner performance is not consistent with the 3R principle (Replacement, Reduction, and Refinement) and potentially subjects animals to unnecessary harm. Thus, quality assurance and control should be of paramount interest to any scientist conducting animal studies. For this reason, through this work, we intend to raise the awareness of researchers using PET/CT regarding quality control/quality assurance (QC/QA) guidelines and instil the importance of confirming that these are routinely followed. We introduce a basic understanding of the PET/CT scanner, present the purpose of QC/QA as well as provide evidence of imaging data biases caused by lack of QC/QA. This is shown through a review of the literature, QC/QA accepted standard protocols and our research. We also want to encourage researchers to have discussions with the PET/CT facilities manager and/or technicians to develop the optimal designed PET/CT experiment for obtaining their scientific objective. Additionally, this work provides an easy gateway to multiple resources not only for PET/CT knowledge but for guidelines and assistance in preclinical experimental design to enhance scientific integrity of the data and ensure animal welfare.

Navigating regulatory pathways for translation of biologic cartilage repair products

Long-term clinical repair of articular cartilage remains elusive despite advances in cartilage tissue engineering. Only one cartilage repair therapy classified as a "cellular and gene therapy product" has obtained Food and Drug Administration (FDA) approval within the past decade although more than 200 large animal cartilage repair studies were published. Here, we identify the challenges impeding translation of strategies and technologies for cell-based cartilage repair, such as the disconnect between university funding and regulatory requirements. Understanding the barriers to translation and developing solutions to address them will be critical for advancing cell therapy products for cartilage repair to clinical use.

Role of Environment and Experimenter in Reproducibility of Behavioral Studies With Laboratory Mice

Behavioral phenotyping of mice has received a great deal of attention during the past three decades. However, there is still a pressing need to understand the variability caused by environmental and biological factors, human interference, and poorly standardized experimental protocols. The inconsistency of results is often attributed to the inter-individual difference between the experimenters and environmental conditions. The present work aims to dissect the combined influence of the experimenter and the environment on the detection of behavioral traits in two inbred strains most commonly used in behavioral genetics due to their contrasting phenotypes, the C57BL/6J and DBA/2J mice. To this purpose, the elevated O-maze, the open field with object, the accelerating rotarod and the Barnes maze tests were performed by two experimenters in two diverse laboratory environments. Our findings confirm the well-characterized behavioral differences between these strains in exploratory behavior, motor performance, learning and memory. Moreover, the results demonstrate how the experimenter and the environment influence the behavioral tests with a variable-dependent effect, often with mutually exclusive contributions. In this context, our study highlights how both the experimenter and the environment can have an impact on the strain effect size without altering the direction of the conclusions. Importantly, the general agreement on the results is reached by converging evidence from multiple measures addressing the same trait. In conclusion, the present work elucidates the contribution of both the experimenter and the laboratory environment in the intricate field of reproducibility in mouse behavioral phenotyping.

Data Management Schema Design for Effective Nanoparticle Formulation for Neurotherapeutics

Translation of nanotherapeutics from preclinical research to clinical application is difficult due to the complex and dynamic interaction space between the nanotherapeutic and the brain environment. To improve translation, increased insight into nanoformulation-brain interactions in preclinical research is necessary. We developed a nanoformulation-brain database and wrote queries to connect the complex physical, chemical, and biological features of neurotherapeutics based on experimental data. We queried the database to select nanoformulations based on specific physical characteristics that enable effective penetration within the brain, including size, polydispersity index, and zeta potential. Additionally, we demonstrate the ability to query the database to return select nanoformulation characteristics, including nanoformulation methodology or methodological variables such as surfactant, polymer, drug loading, and sonication times. Finally, we show the capacity of our database to produce correlations relating nanoparticle formulation parameters to biological outcomes, including nanotherapeutic impact on cell viability in cultured brain slices.

Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research

The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research.

Untargeted metabolomic analysis in cats with naturally occurring inflammatory bowel disease and alimentary small cell lymphoma

Feline chronic enteropathy (CE) is a common gastrointestinal disorder in cats and mainly comprises inflammatory bowel disease (IBD) and small cell lymphoma (SCL). Differentiation between IBD and SCL can be diagnostically challenging. We characterized the fecal metabolome of 14 healthy cats and 22 cats with naturally occurring CE (11 cats with IBD and 11 cats with SCL). Principal component analysis and heat map analysis showed distinct clustering between cats with CE and healthy controls. Random forest classification revealed good group prediction for healthy cats and cats with CE, with an overall out-of-bag error rate of 16.7%. Univariate analysis indicated that levels of 84 compounds in cats with CE differed from those in healthy cats. Polyunsaturated fatty acids held discriminatory power in differentiating IBD from SCL. Metabolomic profiles of cats with CE resembled those in people with CE with significant alterations of metabolites related to tryptophan, arachidonic acid, and glutathione pathways.

Increasing the statistical power of animal experiments with historical control data

Low statistical power reduces the reliability of animal research; yet, increasing sample sizes to increase statistical power is problematic for both ethical and practical reasons. We present an alternative solution using Bayesian priors based on historical control data, which capitalizes on the observation that control groups in general are expected to be similar to each other. In a simulation study, we show that including data from control groups of previous studies could halve the minimum sample size required to reach the canonical 80% power or increase power when using the same number of animals. We validated the approach on a dataset based on seven independent rodent studies on the cognitive effects of early-life adversity. We present an open-source tool, RePAIR, that can be widely used to apply this approach and increase statistical power, thereby improving the reliability of animal experiments.

Translational Intracerebral Hemorrhage Research: Has Current Neuroprotection Research ARRIVEd at a Standard for Experimental Design and Reporting?

One major aim of preclinical intracerebral hemorrhage (ICH) research is to develop and test potential neuroprotectants. Published guidelines for experimental design and reporting stress the importance of clearly and completely reporting results and methodological details to ensure reproducibility and maximize information availability. The current review has two objectives: first, to characterize current ICH neuroprotection research and, second, to analyze aspects of translational design in preclinical ICH studies. Translational design is the adoption and reporting of experimental design characteristics that are thought to be clinically relevant and critical to reproducibility in animal studies (e.g., conducting and reporting experiments according to the STAIR and ARRIVE guidelines, respectively). Given that ICH has no current neuroprotective treatments and an ongoing reproducibility crisis in preclinical research, translational design should be considered by investigators. We conducted a systematic review of ICH research from 2015 to 2019 using the PubMed database. Our search returned 281 published manuscripts studying putative neuroprotectants in animal models. Contemporary ICH research predominantly uses young, healthy male rodents. The collagenase model is the most commonly used. Reporting of group sizes, blinding, and randomization are almost unanimous, but group size calculations, mortality and exclusion criteria, and animal model characteristics are infrequently reported. Overall, current ICH neuroprotection research somewhat aligns with experimental design and reporting guidelines. However, there are areas for improvement. Because failure to consider translational design is associated with inflation of effect sizes (and possibly hindered reproducibility), we suggest that researchers, editors, and publishers collaboratively consider enhanced adherence to published guidelines.

The Influence of Feed and Drinking Water on Terrestrial Animal Research and Study Replicability

For more than 50 years, the research community has made strides to better determine the nutrient requirements for many common laboratory animal species. This work has resulted in high-quality animal feeds that can optimize growth, maintenance, and reproduction in most species. We have a much better understanding of the role that individual nutrients play in physiological responses. Today, diet is often considered as an independent variable in experimental design, and specialized diet formulations for experimental purposes are widely used. In contrast, drinking water provided to laboratory animals has rarely been a consideration in experimental design except in studies of specific water-borne microbial or chemical contaminants. As we advance in the precision of scientific measurements, we are constantly discovering previously unrecognized sources of experimental variability. This is the nature of science. However, science is suffering from a lack of experimental reproducibility or replicability that undermines public trust. The issue of reproducibility/replicability is especially sensitive when laboratory animals are involved since we have the ethical responsibility to assure that laboratory animals are used wisely. One way to reduce problems with reproducibility/replicability is to have a strong understanding of potential sources of inherent variability in the system under study and to provide "…a clear, specific, and complete description of how the reported results were reached [1]." A primary intent of this review is to provide the reader with a high-level overview of some basic elements of laboratory animal nutrition, methods used in the manufacturing of feeds, sources of drinking water, and general methods of water purification. The goal is to provide background on contemporary issues regarding how diet and drinking water might serve as a source of extrinsic variability that can impact animal health, study design, and experimental outcomes and provide suggestions on how to mitigate these effects.

Prevalence and Prevention of Reproducibility Deficiencies in Life Sciences Research: Large-Scale Meta-Analyses

BACKGROUND Studies have found that many published life sciences research results are irreproducible. Our goal was to provide comprehensive risk estimates of familiar reproducibility deficiencies to support quality improvement in research. MATERIAL AND METHODS Reports included were peer-reviewed, published between 1980 and 2016, and presented frequency data of basic biomedical research deficiencies. Manual and electronic literature searches were performed in seven bibliographic databases. For deficiency concepts with at least four frequency studies and with a sample size of at least 15 units in each, a meta-analysis was performed. RESULTS Overall, 68 publications met our inclusion criteria. The study identified several major groups of research quality defects: study design, cell lines, statistical analysis, and reporting. In the study design group of 3 deficiencies, missing power calculation was the most frequent (82.3% [95% Confidence Interval (CI): 69.9-94.6]). Among the 6 cell line deficiencies, mixed contamination was the most frequent (22.4% [95% CI: 10.4-34.3]). Among the 3 statistical analysis deficiencies, the use of chi-square test when expected cells frequency was <5 was the most prevalent (15.7% [95% CI: -3.2-34.7]). In the reporting group of 12 deficiencies, failure to state the number of tails was the most frequent (65% [95% CI: 39.3-90.8]). CONCLUSIONS The results of this study could serve as a general reference when consistently measurable sources of deficiencies need to be identified in research quality improvement.

An individual based, multidimensional approach to identify emotional reactivity profiles in inbred mice

BACKGROUND

Despite extensive environmental standardization and the use of genetically and microbiologically defined mice of similar age and sex, individuals of the same mouse inbred strain commonly differ in quantitative traits. This is a major issue as it affects the quality of experimental results. Standard analysis practices summarize numerical data by means and associated measures of dispersion, while individual values are ignored. Perhaps taking individual values into account in statistical analysis may improve the quality of results.

NEW METHOD

The present study re-inspected existing data on emotional reactivity profiles in 125 BALB/cJ and 129 mice, which displayed contrasting patterns of habituation and sensitization when repeatedly exposed to a novel environment (modified Hole Board). Behaviors were re-analyzed on an individual level, using a multivariate approach, in order to explore whether this yielded new information regarding subtypes of response, and their expression between and within strains.

RESULTS

Clustering individual mice across multiple behavioral dimensions identified two response profiles: a habituation and a sensitization cluster.

COMPARISON WITH EXISTING METHOD(S)

These retrospect analyses identified habituation and sensitization profiles that were similar to those observed in the original data but also yielded new information such as a more pronounced sensitization response. Also, it allowed for the identification of individuals that deviated from the predominant response profile within a strain.

CONCLUSIONS

The present approach allows for the behavioral characterization of experimental animals on an individual level and as such provides a valuable contribution to existing approaches that take individual variation into account in statistical analysis.

A New Non-invasive Technique for Measuring 3D-Oxygen Gradients in Wells During Mammalian Cell Culture

Oxygen tension plays an important role in overall cell function and fate, regulating gene expression, and cell differentiation. Although there is extensive literature available that supports the previous statement, little information is to be found about accurate O2 measurements during culture. In fact, O2 concentration at the cell layer during culture is commonly assumed to be equal to that of the incubator atmosphere. This assumption does not consider oxygen diffusion properties, cell type, cell density, media composition, time in culture nor height of the cell culture medium column. In this study, we developed a non-invasive, optical sensor foil-based technique suitable for measuring the 3D oxygen gradient that is formed during cell culture as a result of normal cell respiration. For this propose, we created a 3D printed ramp to which surface an oxygen optode sensor foil was attached. The ramps were positioned inside the culture wells of 24 well plate prior cell seeding. This set up in conjunction with the VisiSens TD camera system allows to investigate the oxygen gradient formation during culture. Cultivation was performed with three different initial cell densities of the cell line A549 that were seeded on the plate containing the ramps with the oxygen sensors. The O2 gradient obtained after 96 h of culture showed significantly lower O2 concentrations closer to the bottom of the well in high cell density cultures compared to that of lower cell density cultures. Furthermore, it was very interesting to observe that even with low cell density culture, oxygen concentration near the cell layer was lower than that of the incubator atmosphere. The obtained oxygen gradient after 96 h was used to calculate the oxygen consumption rate (OCR) of the A549 cells, and the obtained value of ~100 fmol/h/cell matches the OCR value already reported in the literature for this cell line. Moreover, we found our set up to be unique in its ability to measure oxygen gradient formation in several wells of a cell culture plate simultaneously and in a non-invasive manner.

Reproducibility of animal research in light of biological variation

Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms' responses to experimental treatments can vary with both genotype and environmental conditions. In March 2019, experts in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss strategies addressing this challenge. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift. We also present a road map towards better practices in view of improving the reproducibility of animal research.

A multi-batch design to deliver robust estimates of efficacy and reduce animal use - a syngeneic tumour case study

Phenotypic plasticity, the ability of a living organism to respond to the environment, can lead to conclusions from experiments that are idiosyncratic to a particular environment. The level of environmental responsiveness can result in difficulties in reproducing studies from the same institute with the same standardised environment. Here we present a multi-batch approach to in-vivo studies to improve replicability of the results for a defined environment. These multi-batch experiments consist of small independent mini-experiments where the data are combined in an integrated data analysis to appropriately assess the treatment effect after accounting for the structure in the data. We demonstrate the method on two case studies with syngeneic tumour models which are challenging due to high variability both within and between studies. Through simulations and discussions, we explore several data analysis options and the optimum design that balances practical constraints of working with animals versus sensitivity and replicability. Through the increased confidence from the multi-batch design, we reduce the need to replicate the experiment, which can reduce the total number of animals used.

Differentiation of lymphocytic-plasmacytic enteropathy and small cell lymphoma in cats using histology-guided mass spectrometry

BACKGROUND

Differentiation of lymphocytic-plasmacytic enteropathy (LPE) from small cell lymphoma (SCL) in cats can be challenging.

HYPOTHESIS/OBJECTIVE

Histology-guided mass spectrometry (HGMS) is a suitable method for the differentiation of LPE from SCL in cats.

ANIMALS

Forty-one cats with LPE and 52 cats with SCL.

METHODS

This is a retrospective clinicopathologic study. Duodenal tissue samples of 17 cats with LPE and 22 cats with SCL were subjected to HGMS, and the acquired data were used to develop a linear discriminate analysis (LDA) machine learning algorithm. The algorithm was subsequently validated using a separate set of 24 cats with LPE and 30 cats with SCL. Cases were classified as LPE or SCL based on a consensus by an expert panel consisting of 5-7 board-certified veterinary specialists. Histopathology, immunohistochemistry, and clonality testing were available for all cats. The panel consensus classification served as a reference for the calculation of test performance parameters.

RESULTS

Relative sensitivity, specificity, and accuracy of HGMS were 86.7% (95% confidence interval [CI]: 74.5%-98.8%), 91.7% (95% CI: 80.6%-100%), and 88.9% (95% CI: 80.5%-97.3%), respectively. Comparatively, the clonality testing had a sensitivity, specificity, and accuracy of 85.7% (95% CI: 72.8%-98.7%), 33.3% (95% CI: 14.5%-52.2%), and 61.5% (95% CI: 48.3%-74.8%) relative to the panel decision.

CONCLUSIONS AND CLINICAL IMPORTANCE

Histology-guided mass spectrometry was a reliable technique for the differentiation of LPE from SCL in duodenal formalin-fixed paraffin-embedded samples of cats and might have advantages over tests currently considered state of the art.

A failure modes and effects analysis quality management framework for image-guided small animal irradiators: A change in paradigm for radiation biology

PURPOSE

Image-guided small animal irradiators (IGSAI) are increasingly being adopted in radiation biology research. These animal irradiators, designed to deliver radiation with submillimeter accuracy, exhibit complexity similar to that of clinical radiation delivery systems, including image guidance, robotic stage motion, and treatment planning systems. However, physics expertise and resources are scarcer in radiation biology, which makes implementation of conventional prescriptive QA infeasible. In this study, we apply the failure modes and effect analysis (FMEA) popularized by the AAPM task group 100 (TG-100) report to IGSAI and radiation biological research.

METHODS

Radiation biological research requires a change in paradigm where small errors to large populations of animals are more severe than grievous errors that only affect individuals. To this end, we created a new adverse effects severity table adapted to radiation biology research based on the original AAPM TG-100 severity table. We also produced a process tree which outlines the main components of radiation biology studies performed on an IGSAI, adapted from the original clinical IMRT process tree from TG-100. Using this process tree, we created and distributed a preliminary survey to eight expert IGSAI operators in four institutions. Operators rated proposed failure modes for occurrence, severity, and lack of detectability, and were invited to share their own experienced failure modes. Risk probability numbers (RPN) were calculated and used to identify the failure modes which most urgently require intervention.

RESULTS

Surveyed operators indicated a number of high (RPN >125) failure modes specific to small animal irradiators. Errors due to equipment breakdown, such as loss of anesthesia or thermal control, received relatively low RPN (12-48) while errors related to the delivery of radiation dose received relatively high RPN (72-360). Errors identified could either be improved by manufacturer intervention (e.g., electronic interlocks for filter/collimator) or physics oversight (errors related to tube calibration or treatment planning system commissioning). Operators identified a number of failure modes including collision between the collimator and the stage, misalignment between imaging and treatment isocenter, inaccurate robotic stage homing/translation, and incorrect SSD applied to hand calculations. These were all relatively highly rated (90-192), indicating a possible bias in operators towards reporting high RPN failure modes.

CONCLUSIONS

The first FMEA specific to radiation biology research was applied to image-guided small animal irradiators following the TG-100 methodology. A new adverse effects severity table and a process tree recognizing the need for a new paradigm were produced, which will be of great use to future investigators wishing to pursue FMEA in radiation biology research. Future work will focus on expanding scope of user surveys to users of all commercial IGSAI and collaborating with manufacturers to increase the breadth of surveyed expert operators.

Characterization of the fecal microbiome in cats with inflammatory bowel disease or alimentary small cell lymphoma

Feline chronic enteropathy (CE) is a common gastrointestinal disorder in cats and mainly comprises inflammatory bowel disease (IBD) and small cell lymphoma (SCL). Both IBD and SCL in cats share features with chronic enteropathies such as IBD and monomorphic epitheliotropic intestinal T-cell lymphoma in humans. The aim of this study was to characterize the fecal microbiome of 38 healthy cats and 27 cats with CE (13 cats with IBD and 14 cats with SCL). Alpha diversity indices were significantly decreased in cats with CE (OTU p = 0.003, Shannon Index p = 0.008, Phylogenetic Diversity p = 0.019). ANOSIM showed a significant difference in bacterial communities, albeit with a small effect size (P = 0.023, R = 0.073). Univariate analysis and LEfSE showed a lower abundance of facultative anaerobic taxa of the phyla Firmicutes (families Ruminococcaceae and Turicibacteraceae), Actinobacteria (genus Bifidobacterium) and Bacteroidetes (i.a. Bacteroides plebeius) in cats with CE. The facultative anaerobic taxa Enterobacteriaceae and Streptococcaceae were increased in cats with CE. No significant difference between the microbiome of cats with IBD and those with SCL was found. Cats with CE showed patterns of dysbiosis similar to those in found people with IBD.

The Role of the Three Rs in Improving the Planning and Reproducibility of Animal Experiments

Training in the design of animal experiments focuses all too often on those aspects which can be approached mathematically, such as the number of animals needed to deliver a robust result, allocation of group size, and techniques such as randomization, blocking and statistical analysis. Important as they are, these are only a small part of the process of planning animal experiments. Additional key elements include refinements of housing, husbandry and procedures, health and safety, and attention at all stages to animal welfare. Advances in technology and laboratory animal science have led to improvements in care and husbandry, better provision of anesthetics and analgesics, refined methods of drug administration, greater competence in welfare assessment and application of humane endpoints. These improvements require continual dialogue between scientists, facility managers and technical staff, a practice that is a key feature of what has become known as the culture of care. This embodies a commitment to improving animal welfare, scientific quality, staff care and transparency for all stakeholders. Attention to both the physical and mental health of all those directly or indirectly involved in animal research is now an important part of the process of planning and conducting animal experiments. Efforts during the last 30 years to increase the internal and external validity of animal experiments have tended to concentrate on the production of guidelines to improve the quality of reporting animal experiments, rather than for planning them. Recently, comprehensive guidelines for planning animal studies have been published, to redress this imbalance. These will be described in this paper. Endorsement of this overarching influence of the Three R concept, by all the stakeholders, will not only reduce animal numbers and improve animal welfare, but also lead to more reliable and reproducible research which should improve translation of pre-clinical studies into tangible clinical benefit.

The Search for Clinically Useful Biomarkers of Complex Disease: A Data Analysis Perspective

Unmet clinical diagnostic needs exist for many complex diseases, which (it is hoped) will be solved by the discovery of metabolomics biomarkers. However, at present, no diagnostic tests based on metabolomics have yet been introduced to the clinic. This review is presented as a research perspective on how data analysis methods in metabolomics biomarker discovery may contribute to the failure of biomarker studies and suggests how such failures might be mitigated. The study design and data pretreatment steps are reviewed briefly in this context, and the actual data analysis step is examined more closely.

The behavioral phenotype of early life adversity: A 3-level meta-analysis of rodent studies

Altered cognitive performance is considered an intermediate phenotype mediating early life adversity (ELA) effects on later-life development of mental disorders, e.g. depression. Whereas most human studies are limited to correlational conclusions, rodent studies can prospectively investigate how ELA alters cognitive performance in several domains. Despite the volume of reports, there is no consensus on i) the behavioral domains being affected by ELA and ii) the extent of these effects. To test how ELA (here: aberrant maternal care) affects specific behavioral domains, we used a 3-level mixed-effect meta-analysis, and thoroughly explored heterogeneity with MetaForest, a novel machine-learning approach. Our results are based on >400 independent experiments, involving ∼8600 animals. Especially in males, ELA promotes memory formation during stressful learning but impairs non-stressful learning. Furthermore, ELA increases anxiety-like and decreases social behavior. The ELA phenotype was strongest when i) combined with other negative experiences ("hits"); ii) in rats; iii) in ELA models of ∼10days duration. All data is easily accessible with MaBapp (https://osf.io/ra947/), allowing researchers to run tailor-made meta-analyses, thereby revealing the optimal choice of experimental protocols and study power.

Understanding of researcher behavior is required to improve data reliability

BACKGROUND

A lack of data reproducibility ("reproducibility crisis") has been extensively debated across many academic disciplines.

RESULTS

Although a reproducibility crisis is widely perceived, conclusive data on the scale of the problem and the underlying reasons are largely lacking. The debate is primarily focused on methodological issues. However, examples such as the use of misidentified cell lines illustrate that the availability of reliable methods does not guarantee good practice. Moreover, research is often characterized by a lack of established methods. Despite the crucial importance of researcher conduct, research and conclusive data on the determinants of researcher behavior are widely missing.

CONCLUSION

Meta-research that establishes an understanding of the factors that determine researcher behavior is urgently needed. This knowledge can then be used to implement and iteratively improve measures that incentivize researchers to apply the highest standards, resulting in high-quality data.

Oxygenation in cell culture: Critical parameters for reproducibility are routinely not reported

Mammalian cell culture is foundational to biomedical research, and the reproducibility of research findings across the sciences is drawing increasing attention. While many components contribute to reproducibility, the reporting of factors that impact oxygen delivery in the general biomedical literature has the potential for both significant impact, and immediate improvement. The relationship between the oxygen consumption rate of cells and the diffusive delivery of oxygen through the overlying medium layer means parameters such as medium depth and cell type can cause significant differences in oxygenation for cultures nominally maintained under the same conditions. While oxygenation levels are widely understood to significantly impact the phenotype of cultured cells in the abstract, in practise the importance of the above parameters does not appear to be well recognized in the non-specialist research community. On analyzing two hundred articles from high-impact journals we find a large majority missing at least one key piece of information necessary to ensure consistency in replication. We propose that explicitly reporting these values should be a requirement for publication.

Living inside the box: environmental effects on mouse models of human disease

The impact of the laboratory environment on animal models of human disease, particularly the mouse, has recently come under intense scrutiny regarding both the reproducibility of such environments and their ability to accurately recapitulate elements of human environmental conditions. One common objection to the use of mice in highly controlled facilities is that humans live in much more diverse and stressful environments, which affects the expression and characteristics of disease phenotypes. In this Special Article, we review some of the known effects of the laboratory environment on mouse phenotypes and compare them with environmental effects on humans that modify phenotypes or, in some cases, have driven genetic adaptation. We conclude that the 'boxes' inhabited by mice and humans have much in common, but that, when attempting to tease out the effects of environment on phenotype, a controlled and, importantly, well-characterized environment is essential.

Engineering Intravenously Administered Nanoparticles to Reduce Infusion Reaction and Stop Bleeding in a Large Animal Model of Trauma

Bleeding from traumatic injury is the leading cause of death for young people across the world, but interventions are lacking. While many agents have shown promise in small animal models, translating the work to large animal models has been exceptionally difficult in great part because of infusion-associated complement activation to nanomaterials that leads to cardiopulmonary complications. Unfortunately, this reaction is seen in at least 10% of the population. We developed intravenously infusible hemostatic nanoparticles that were effective in stopping bleeding and improving survival in rodent models of trauma. To translate this work, we developed a porcine liver injury model. Infusion of the first generation of hemostatic nanoparticles and controls 5 min after injury led to massive vasodilation and exsanguination even at extremely low doses. In naïve animals, the physiological changes were consistent with a complement-associated infusion reaction. By tailoring the zeta potential, we were able to engineer a second generation of hemostatic nanoparticles and controls that did not exhibit the complement response at low and moderate doses but did at the highest doses. These second-generation nanoparticles led to cessation of bleeding within 10 min of administration even though some signs of vasodilation were still seen. While the complement response is still a challenge, this work is extremely encouraging in that it demonstrates that when the infusion-associated complement response is managed, hemostatic nanoparticles are capable of rapidly stopping bleeding in a large animal model of trauma.