Biology subjects

Morrison, K.

Publications and source records attributed to Morrison, K..

9 recordsLinked to original sources

bioRxiv2025

Underappreciated role of environmental enrichment in alleviating depression and anxiety: Quantitative evidence synthesis of rodent models

Environmental enrichment has long been recognized as a non-pharmacological intervention to mitigate mental health issues, yet its efficacy, and heterogeneity of treatment effects across experimental contexts remain underexplored. Heterogeneity of treatment effects, which reflects variability in individual responses to interventions, is a critical factor in determining the generalizability and personalization needs of treatments. Here, we conducted a registered meta-analysis of 62 studies and 1,112 comparisons in rodent models to evaluate the impact of environmental enrichment on depressive and anxiety-like behaviours. We found that environmental enrichment reduced these behaviours of animal models by 16% on average and decreased inter-individual variability by 12%, indicating not only effectiveness but also low heterogeneity of treatment effects, which suggests consistent effects across individuals. Environmental enrichment further nullified the adverse effects of stressors, demonstrating a significant antagonistic interaction. These effects were robust across multiple sensitivity analyses, including model-based predictions, post-stratification, multi-model inference, publication bias correction, and critical appraisal of study quality. Moderator analyses highlighted the importance of exposure timing and the inclusion of social enrichment components. Taken together, our pre-clinical evidence on rodent models supports environmental enrichment as a low-cost, scalable, and biologically grounded intervention with translational relevance for developing equitable and accessible treatments for depression and anxiety. Given the importance of innovation and personalization in mental health care, the low heterogeneity of treatment effects of environmental enrichment positions it as a promising avenue for non-pharmacological therapeutic strategies that can be broadly applied without extensive tailoring.

animal behavior and cognition↗

bioRxiv2025

Attractor-based models for sequences and pattern generation in neural circuits

Neural circuits in the brain perform a variety of essential functions, including input classification, pattern completion, and the generation of rhythms and oscillations that support functions such as breathing and locomotion. There is also substantial evidence that the brain encodes memories and processes information via sequences of neural activity. Traditionally, rhythmic activity and pattern generation have been modeled using coupled oscillators, whereas input classification and pattern completion have been modeled using attractor neural networks. Here, we present a theoretical framework that demonstrates how attractor-based networks can also generate diverse rhythmic patterns, such as those of central pattern generator circuits (CPGs). Additionally, we propose a mechanism for transitioning between patterns. Specifically, we construct a network that can step through a sequence of five different quadruped gaits. It is composed of two dynamically distinct modules: a "counter" network, that can count the number of external inputs it receives via a sequence of fixed points; and a locomotion network, that encodes five different quadruped gaits as limit cycles. A sequence of locomotive gaits is obtained by connecting the counter network with the locomotion network. Specifically, we introduce a new architecture for layering networks that produces "fusion" attractors, binding pairs of attractors from individual layers. All of this is accomplished within a unified framework of attractor-based models using threshold-linear networks.

neuroscience↗

bioRxiv2024

Bivariate multilevel meta-analysis of log response ratio and standardized mean difference for robust and reproducible environmental and biological sciences

Meta-analytic modelling plays a pivotal role in synthesizing research and informing relevant policies. Yet researchers face many analytical challenges. In environmental and biological sciences, one of the most common yet unrecognised issues is the selection between two common effect size metrics, log response ratio (lnRR) and standardized mean difference (SMD); these two are the most popular and alternative effect sizes. Having to choose between them creates room for analytical flexibility, which is susceptible to researcher degrees of freedom. Another common issue is failure to deal with statistical dependence between effect sizes, resulting in invalid inferences on evidence. We propose addressing these two issues through the joint synthesis (dual use) of lnRR and SMD. Using 75 meta-analyses, including 3,887 environmental/biological primary studies ([~]20,000 effect sizes), we show a high false positive rate (40%) in conventional meta-analytic practices (random-effects model) compared to the proposed bivariate multilevel meta-analysis of lnRR and SMD along with robust variance estimation. Relying solely on either lnRR or SMD results in non-trivial discrepancies in detecting statistically significant effects (18%) and occasional inconsistencies in sign (9%). Discrepancies in interpreting effect size, heterogeneity, and publication bias are prevalent between models using lnRR and SMD (e.g., 52% for publication bias). In contrast, bivariate synthesis of lnRR and SMD yields substantial information gain, reducing standard error in effect size estimates by 29%, equivalent to adding 40 additional effect sizes. We present a user-friendly website with a step-by-step implementation guide. Our proposed robust approach aspires to improve meta-analytic modelling using lnRR and SMD in environmental and biological evidence synthesis, amplifying their reproducibility and credibility.

ecology↗

bioRxiv2023

Keywords to success: a practical guide to maximise the visibility and impact of academic papers

In a growing digital landscape, enhancing the discoverability and resonance of scientific articles is essential. Here, we offer ten recommendations to amplify the discoverability of studies in scientific databases. Particularly, we argue that the strategic use and placement of key terms in the title, abstract, and keyword sections can boost indexing and appeal. By surveying 237 journals in ecology and evolutionary biology, we found that current author guidelines may unintentionally limit article discoverability. Our survey of 5842 studies revealed that authors frequently exhaust abstract word limits -- particularly those capped under 250 words. This suggests that current guidelines may be overly restrictive and not optimised to increase the dissemination and discoverability of digital publications. Additionally, 91.9% of studies used redundant keywords in the title or abstract, undermining optimal indexing in databases. We encourage adopting structured abstracts to maximise the incorporation of key terms in titles, abstracts, and keywords. In addition, we encourage the relaxation of abstract and keyword limitations in journals with strict guidelines, and the inclusion of multilingual abstracts to broaden global accessibility. These evidence-based recommendations to editors are designed to improve article engagement and facilitate evidence synthesis, thereby aligning scientific publishing with the modern needs of academic research.

scientific communication and education↗

bioRxiv2021

Active communities and growth of soil microorganisms are framed by mean annual precipitation in three California annual grasslands

Earth system models project altered precipitation regimes across much of the globe; in California, the winter wet season is predicted to extend into spring, and the summer dry period to lengthen. How these precipitation trends will affect microbial traits and soil carbon (C) cycling is a key knowledge gap. Specifically, we do not have a mechanistic understanding of the linkages between soil moisture legacy effects, microbial population dynamics and soil C persistence. Using quantitative stable isotope probing (qSIP), we compared total and growing soil microbial communities across three California annual grasslands that span a rainfall gradient yet developed on similar parent material. We also assessed multiple edaphic variables, including the radiocarbon (14C) age of soil C, and found soil C turnover time increased with annual precipitation, but that soil microbes respired recently-fixed C regardless of site rainfall history. Samples were assayed in the wet season, when we expected environmental conditions would be most similar across sites. We hypothesized that growing communities would be more compositionally similar across the gradient than the total background microbiome. We also predicted that the long-term legacy effect of soil water limitation would be reflected in a lower community growth capacity at the driest site. We found that the proportion of the total community that was detected as growing was 28%, 48% and 58% at the wet, intermediate and dry sites, respectively. The composition of growing communities strongly resembled that of total communities, and growing communities were no more similar across the gradient than total communities, indicating a strong effect of climate of the structure of growing microbial communities. Members of three phyla, Acidobacteria, Actinobacteria, and Proteobacteria, were responsible for [~]79% of the cumulative 18O assimilation and 80% of all taxa that we defined as growers. Bacterial growth rates were low at the driest site relative to the intermediate and wettest sites. Reduced growth at the driest site was observed across major phyla, including the Actinobacteria, Acidobacteria, Bacteroidetes, Gemmatimonadetes and Proteobacteria. Microbial communities at the driest site displayed phylogenetic clustering, suggesting that climate history impacts microbial growth through environmental filtering for slow growing taxa. Taxonomic identity was a strong predictor of growth, such that the growth rates of a taxon at one site predicted its growth rates at the others. This cross-site coherence in growth is likely a consequence of genetically determined physiological traits, and is consistent with the idea that evolutionary history influences growth rate.

ecology↗

bioRxiv2021

Belowground allocation and dynamics of recently fixed plant carbon in a California annual grassland soil

Plant roots and the organisms that surround them are a primary source for stabilized organic C, particularly in grassland soils, which have a large capacity to store organic carbon belowground. To quantify the flow and fate of plant fixed carbon (C) in a Northern California annual grassland, we tracked plant carbon from a five-day 13CO2 pulse field labeling for the following two years. Soil and plant samples were collected immediately after the pulse labeling, and again at three days, four weeks, six months, one year, and two years. Soil organic matter was fractionated using a sodium polytungstate density gradient to separate the free-light fraction (FLF), occluded-light fraction (OLF), and heavy fraction (HF). Using isotope ratio mass spectrometry, we measured 13C enrichment and total C content for plant shoots, roots, soil, soil dissolved organic carbon (DOC), and the FLF, OLF, and HF. The HF was further analyzed by solid state 13C NMR spectroscopy. At the end of the labeling period, the largest amount of 13C was recovered in plant shoots (60%), but a substantial amount (40%) was already found belowground in roots, soil, and soil DOC. Density fractionation of 4-week soil samples (from which living roots were removed) indicated that the highest isotope enrichment was in the mineral-rich heavy fraction, with similar enrichment of the FLF and OLF. At the 6-month sampling, after the dry summer period during which plants senesced and died, the amount of label in the FLF increased such that it was equal to that in the HF. By the 1-year sampling, 13C in the FLF had declined substantially and continued to decline by the 2-year sampling. 13C recovery in the OLF and HF, however, was qualitatively stable between sampling times. By the end of the 2-year experiment, 69% of remaining label was in the HF, 18% in the FLF and 13% in the OLF. While the total 13C content of the HF did not change significantly from the 4-week to the 2-year sample time, 13C NMR spectroscopic analysis of spring HF samples from 2018, 2019, and 2020 suggests that the relative proportion of aliphatic/alkyl functional groups declined in the newly formed SOC over the 2-year period. Simultaneously, aromatic and carbonyl functional groups increased, and the proportion of carbohydrate groups remained relatively constant. In summary, our results indicate that initial associations between minerals and root-derived organic matter are significant and form rapidly; by 4 weeks, a substantial amount (17%) of the total plant-derived 13C had become associated with the heavy fraction (HF) of soil. While the majority of annual C input cycles rapidly (<2-year timescale), a sizeable proportion ([~]12% of the original inputs) persisted for 2 years.

biochemistry↗

bioRxiv2020

Toward Minimally Invasive Therapeutic Ultrasound: Ultrasound-guided Ablation in Neuro-oncology

IntroductionTo improve patient outcomes (eg, reducing blood loss and infection), practitioners have gravitated toward noninvasive and minimally invasive surgeries (MIS), which demand specialized toolkits. Focused ultrasound, for example, facilitates thermal ablation from a distance, thereby reducing injury to surrounding tissue. Focused ultrasound can often be performed noninvasively; however, it is more difficult to carry out in neuro-oncological tumors, as ultrasound is dramatically attenuated while propagating through the skull. This shortcoming has prompted exploration of MIS options for intracranial placement of focused ultrasound probes, such as within the BrainPath (NICO Corporation, Indianapolis, IN). Herein, we present the design, development, and in vitro testing of an image-guided, focused ultrasound prototype designed for use in MIS procedures. This probe can ablate neuro-oncological lesions despite its small size. Materials & MethodsPreliminary prototypes were iteratively designed, built, and tested. The final prototype consisted of three 8-mm-diameter therapeutic elements guided by an imaging probe. Probe functionality was validated on a series of tissue-mimicking phantoms. ResultsLesions were created in tissue-mimicking phantoms with average dimensions of 2.5x1.2x6.5mm and 3.4x3.25x9.36mm after 10- and 30-second sonification, respectively. 30s sonification with 118W power at 50% duty cycle generated a peak temperature of 68{degrees}C. Each ablation was visualized in real time by the built-in imaging probe. ConclusionWe developed and validated an ultrasound-guided focused ultrasound probe for use in MIS procedures. The dimensional constraints of the prototype were designed to reflect those of BrainPath trocars, which are MIS tools used to create atraumatic access to deep-seated brain pathologies. HIGHLIGHTSO_LIAn ultrasound-guided, focused ultrasound prototype was developed and validated C_LIO_LIThe therapeutic transducer (1.5MHz) consisted of three 8-mm circular elements C_LIO_LIElements were placed on a 9x32mm curved rectangular aperture: 45mm radius curvature C_LIO_LIFunctionality was examined on tissue-mimicking phantoms C_LIO_LI2.5x1.2x6.5mm and 3.4x3.25x9.36mm lesions were seen for 10 and 30s sonification C_LI

bioengineering↗

bioRxiv2019

The oncogenic Kaposi sarcoma-associated herpesvirus encodes a mimic of the tumor suppressive miR-15/16 miRNA family

Many tumor viruses encode oncogenes of cellular origin. Here, we report the first instance of an oncoviral mimic of a cellular tumor suppressor. The Kaposis sarcoma-associated herpesvirus (KSHV) miRNA miR-K6-5p shares sequence similarity to the tumor suppressive cellular miR-15/16 miRNA family. We show that miR-K6-5p inhibits cell cycle progression, a hallmark function of miR-16. miR-K6-5p regulates conserved miR-15/16 targets, including many cell cycle regulators. Inhibition of miR-K6-5p in KSHV-transformed B cells conferred a significant growth advantage. Altogether, our data show that KSHV encodes a functional mimic of the miR-15/16 miRNA family. While it is exceedingly well established that oncogenic viruses encode oncogenes of cellular origin, this is the first example of an oncogenic virus that encodes a viral mimic of a cellular tumor suppressor. Encoding a tumor suppressive miRNA could help KSHV balance viral oncogene expression and thereby avoid severe pathogenesis in the healthy host.

microbiology↗

bioRxiv2017

Neurochondrin interacts with the SMN protein suggesting a novel mechanism for Spinal Muscular Atrophy pathology.

Spinal Muscular Atrophy (SMA) is an inherited neurodegenerative condition caused by reduction in functional Survival Motor Neurones Protein (SMN). SMN has been implicated in transport of mRNA in neural cells for local translation. We previously identified microtubule-dependant mobile vesicles rich in SMN and the splicing factor SmB, a member of the Sm protein family, in neural cells. By comparing the proteome of SmB to that of SmN, a neural-specific Sm protein, we now show that the essential neural protein neurochondrin (NCDN) interacts with Sm proteins and SMN in the context of mobile vesicles in neurites. NCDN has roles in protein localisation in neural cells, and in maintenance of cell polarity. NCDN is required for the correct localisation of SMN, suggesting they may both be required for formation and transport of trafficking vesicles. NCDN provides a potential therapeutic target for SMA together with, or in place of, those targeting SMN expression.

cell biology↗