Promoting FAIR Data Through Community-driven Agile Design: the Open Data Commons for Spinal Cord Injury (odc-sci.org)

Spinal cord injury-induced metabolic impairment and steatohepatitis develops in non-obese rats and is exacerbated by premorbid obesity

Impaired sensorimotor functions are prominent complications of spinal cord injury (SCI). A clinically important but less obvious consequence is development of metabolic syndrome (MetS), including increased adiposity, hyperglycemia/insulin resistance, and hyperlipidemia. MetS predisposes SCI individuals to earlier and more severe diabetes and cardiovascular disease compared to the general population, which trigger life-threatening complications (e.g., stroke, myocardial infarcts). Although each comorbidity is known to be a risk factor for diabetes and other health problems in obese individuals, their relative contribution or perceived importance in propagating systemic pathology after SCI has received less attention. This could be explained by an incomplete understanding of MetS promoted by SCI compared with that from the canonical trigger diet-induced obesity (DIO). Thus, here we compared metabolic-related outcomes after SCI in lean rats to those of uninjured rats with DIO. Surprisingly, SCI-induced MetS features were equal to or greater than those in obese uninjured rats, including insulin resistance, endotoxemia, hyperlipidemia, liver inflammation and steatosis. Considering the endemic nature of obesity, we also evaluated the effect of premorbid obesity in rats receiving SCI; the combination of DIO + SCI exacerbated MetS and liver pathology compared to either alone, suggesting that obese individuals that sustain a SCI are especially vulnerable to metabolic dysfunction. Notably, premorbid obesity also exacerbated intraspinal lesion pathology and worsened locomotor recovery after SCI. Overall, these results highlight that normal metabolic function requires intact spinal circuitry and that SCI is not just a sensory-motor disorder, but also has significant metabolic consequences.

Bayesian Methods: A Means of Improving Statistical Power in Preclinical Neurotrauma?

The field of neurotrauma is grappling with the effects of the recently identified replication crisis. As such, care must be taken to identify and perform the most appropriate statistical analyses. This will prevent misuse of research resources and ensure that conclusions are reasonable and within the scope of the data. We anticipate that Bayesian statistical methods will see increasing use in the coming years. Bayesian methods integrate prior beliefs (or prior data) into a statistical model to merge historical information and current experimental data. These methods may improve the ability to detect differences between experimental groups (i.e., statistical power) when used appropriately. However, researchers need to be aware of the strengths and limitations of such approaches if they are to implement or evaluate these analyses. Ultimately, an approach using Bayesian methodologies may have substantial benefits to statistical power, but caution needs to be taken when identifying and defining prior beliefs.

Effect-Size Discrepancies in Literature Versus Raw Datasets from Experimental Spinal Cord Injury Studies: A CLIMBER Meta-Analysis

Translation of spinal cord injury (SCI) therapeutics from pre-clinical animal studies into human studies is challenged by effect size variability, irreproducibility, and misalignment of evidence used by pre-clinical versus clinical literature. Clinical literature values reproducibility, with the highest grade evidence (class 1) consisting of meta-analysis demonstrating large therapeutic efficacy replicating across multiple studies. Conversely, pre-clinical literature values novelty over replication and lacks rigorous meta-analyses to assess reproducibility of effect sizes across multiple articles. Here, we applied modified clinical meta-analysis methods to pre-clinical studies, comparing effect sizes extracted from published literature to raw data on individual animals from these same studies. Literature-extracted data (LED) from numerical and graphical outcomes reported in publications were compared with individual animal data (IAD) deposited in a federally supported repository of SCI data. The animal groups from the IAD were matched with the same cohorts in the LED for a direct comparison. We applied random-effects meta-analysis to evaluate predictors of neuroconversion in LED versus IAD. We included publications with common injury models (contusive injuries) and standardized end-points (open field assessments). The extraction of data from 25 published articles yielded n = 1841 subjects, whereas IAD from these same articles included n = 2441 subjects. We observed differences in the number of experimental groups and animals per group, insufficient reporting of dropout animals, and missing information on experimental details. Meta-analysis revealed differences in effect sizes across LED versus IAD stratifications, for instance, severe injuries had the largest effect size in LED (standardized mean difference [SMD = 4.92]), but mild injuries had the largest effect size in IAD (SMD = 6.06). Publications with smaller sample sizes yielded larger effect sizes, while studies with larger sample sizes had smaller effects. The results demonstrate the feasibility of combining IAD analysis with traditional LED meta-analysis to assess effect size reproducibility in SCI.

Effects of dim light at night in C57BL/6 J mice on recovery after spinal cord injury

Spinal cord injury (SCI) can cause long-lasting locomotor deficits, pain, and mood disorders. Anatomical and functional outcomes are exacerbated by inflammation after SCI, which causes secondary damage. One promising target after SCI is manipulating the circadian system, which optimizes biology and behavior for time of day - including neuroimmune responses and mood-related behaviors. Circadian disruption after SCI is likely worsened by a disruptive hospital environment, which typically includes dim light-at-night (dLAN). Here, we hypothesized that mice subjected to SCI, then placed in dLAN, would exhibit worsened locomotor deficits, pain-like behavior, and anxiety-depressive-like symptoms compared to mice maintained in light days with dark nights (LD). C57BL/6 J mice received sham surgery or moderate T9 contusion SCI, then were placed permanently in LD or dLAN. dLAN after SCI did not worsen locomotor deficits; rather, SCI-dLAN mice showed slight improvement in open-field locomotion at the final timepoint. Although dLAN did not alter SCI-induced heat hyperalgesia, SCI-dLAN mice exhibited an increase in mechanical allodynia at 13 days post-SCI compared to SCI-LD mice. SCI-LD and SCI-dLAN mice had similar outcomes using sucrose preference (depressive-like) and open-field (anxiety-like) tests. At 21 dpo, SCI-dLAN mice had reduced preference for a novel juvenile compared to SCI-LD, implying that dLAN combined with SCI may worsen this mood-related behavior. Finally, lesion size was similar between SCI-LD and SCI-dLAN mice. Therefore, newly placing C57BL/6 J mice in dLAN after SCI had modest effects on locomotor, pain-like, and mood-related behaviors. Future studies should consider whether clinically-relevant circadian disruptors, alone or in combination, could be ameliorated to enhance outcomes after SCI.

A minimal metadata set (MNMS) to repurpose nonclinical in vivo data for biomedical research

Although biomedical research is experiencing a data explosion, the accumulation of vast quantities of data alone does not guarantee a primary objective for science: building upon existing knowledge. Data collected that lack appropriate metadata cannot be fully interrogated or integrated into new research projects, leading to wasted resources and missed opportunities for data repurposing. This issue is particularly acute for research using animals, where concerns regarding data reproducibility and ensuring animal welfare are paramount. Here, to address this problem, we propose a minimal metadata set (MNMS) designed to enable the repurposing of in vivo data. MNMS aligns with an existing validated guideline for reporting in vivo data (ARRIVE 2.0) and contributes to making in vivo data FAIR-compliant. Scenarios where MNMS should be implemented in diverse research environments are presented, highlighting opportunities and challenges for data repurposing at different scales. We conclude with a 'call for action' to key stakeholders in biomedical research to adopt and apply MNMS to accelerate both the advancement of knowledge and the betterment of animal welfare.

Motor Rehabilitation Provides Modest Functional Benefits After Intracerebral Hemorrhage: a Systematic Review and Meta-Analysis of Translational Rehabilitation Studies

Few certainties exist regarding the optimal type, timing, or dosage of rehabilitation after stroke. Despite differing injury mechanisms and recovery patterns following ischemic and hemorrhagic stroke, most translational stroke research is conducted after ischemia. As we enter the era of personalized medicine, exploring subtype-specific treatment efficacy is essential to optimizing recovery. Our objective was to characterize common rehabilitation interventions used after in vivo preclinical intracerebral hemorrhage (ICH) and assess the impact of post-ICH rehabilitation (vs. no-rehabilitation) on recovery of motor function. Following PRISMA guidelines, a systematic review (Academic Search Complete, CINAHL, EMBASE, Medline, PubMed Central) identified eligible articles published up to December 2022. Risk of bias (SYRCLE) and study quality (CAMARADES) were evaluated, and random-effects meta-analysis was used to assess treatment efficacy in recovery of forelimb and locomotor functions. Thirty articles met inclusion criteria, and 48 rehabilitation intervention groups were identified. Most used collagenase to model striatal ICH in young, male rodents. Aerobic exercise, enriched rehabilitation, and constraint-induced movement therapy represented ~ 70% of interventions. Study quality was low (median 4/10, range 2-8), and risk of bias was unclear. Rehabilitation provided modest benefits in skilled reaching, spontaneous impaired forelimb use, and locomotor function; however, effects varied substantially by endpoint, treatment type, and study quality. Rehabilitation statistically improves motor function after preclinical ICH, but whether these effects are functionally meaningful is unclear. Incomplete reporting and variable research quality hinder our capacity to analyze and interpret how treatment factors influence rehabilitation efficacy and recovery after ICH.

Challenges in Translating Regenerative Therapies for Spinal Cord Injury

Regenerating the injured spinal cord is a substantial challenge with many obstacles that need to be overcome to achieve robust functional benefits. This abundance of hurdles can partly explain the limited success when applying regenerative intervention treatments in animal models and/or people. In this article, we elaborate on a few of these obstacles, starting with the applicability of animal models and how they compare to the clinical setting. We then discuss the requirement for combinatorial interventions and the associated problems in experimental design, including the addition of rehabilitative training. The article expands on differences in lesion sizes and locations between humans and common animal models, and how this difference can determine the success or failure of an intervention. An additional and frequently overlooked problem in the translation of interventions that applies beyond the field of neuroregeneration is the reporting bias and the lack of transparency in reporting findings. New data mandates are tackling this problem and will eventually result in a more balanced view of the field. Finally, we will discuss strategies to negotiate the challenging course of successful translation to facilitate successful translation of regeneration promoting interventions.

Intermediate gray matter interneurons in the lumbar spinal cord play a critical and necessary role in coordinated locomotion

Locomotion is a complex task involving excitatory and inhibitory circuitry in spinal gray matter. While genetic knockouts examine the function of individual spinal interneuron (SpIN) subtypes, the phenotype of combined SpIN loss remains to be explored. We modified a kainic acid lesion to damage intermediate gray matter (laminae V-VIII) in the lumbar spinal enlargement (spinal L2-L4) in female rats. A thorough, tailored behavioral evaluation revealed deficits in gross hindlimb function, skilled walking, coordination, balance and gait two weeks post-injury. Using a Random Forest algorithm, we combined these behavioral assessments into a highly predictive binary classification system that strongly correlated with structural deficits in the rostro-caudal axis. Machine-learning quantification confirmed interneuronal damage to laminae V-VIII in spinal L2-L4 correlates with hindlimb dysfunction. White matter alterations and lower motoneuron loss were not observed with this KA lesion. Animals did not regain lost sensorimotor function three months after injury, indicating that natural recovery mechanisms of the spinal cord cannot compensate for loss of laminae V-VIII neurons. As gray matter damage accounts for neurological/walking dysfunction in instances of spinal cord injury affecting the cervical or lumbar enlargement, this research lays the groundwork for new neuroregenerative therapies to replace these lost neuronal pools vital to sensorimotor function.

Harmonization-Information Trade-Offs for Sharing Individual Participant Data in Biomedicine

Biomedical practice is evidence-based. Peer-reviewed papers are the primary medium to present evidence and data-supported results to drive clinical practice. However, it could be argued that scientific literature does not contain data, but rather narratives about and summaries of data. Meta-analyses of published literature may produce biased conclusions due to the lack of transparency in data collection, publication bias, and inaccessibility to the data underlying a publication ('dark data'). Co-analysis of pooled data at the level of individual research participants can offer higher levels of evidence, but this requires that researchers share raw individual participant data (IPD). FAIR (findable, accessible, interoperable, and reusable) data governance principles aim to guide data lifecycle management by providing a framework for actionable data sharing. Here we discuss the implications of FAIR for data harmonization, an essential step for pooling data for IPD analysis. We describe the harmonization-information trade-off, which states that the level of granularity in harmonizing data determines the amount of information lost. Finally, we discuss a framework for managing the trade-off and the levels of harmonization. In the coming era of funder mandates for data sharing, research communities that effectively manage data harmonization will be empowered to harness big data and advanced analytics such as machine learning and artificial intelligence tools, leading to stunning new discoveries that augment our understanding of diseases and their treatments. By elevating scientific data to the status of a first-class citizen of the scientific enterprise, there is strong potential for biomedicine to transition from a narrative publication product orientation to a modern data-driven enterprise where data itself is viewed as a primary work product of biomedical research.