bluuebunny/crossref_metadata_2025 huggingface dataset:
Change in force profile of the hardstyle kettlebell swing in older adults is small following 16 weeks of training and may not be required to improve physical function: findings from the BELL trial
Authors: Meigh Neil J. , Keogh Justin W.L. , Rathbone Evelyne N. , Hing Wayne A.
Published: September 2021

Background

Hardstyle kettlebell training is characterised by the ballistic two-handed kettlebell swing with outcomes believed to be strongly influenced by swing proficiency. This study examines the effect of four months hardstyle kettlebell training on the force profile of the two-handed kettlebell swing, and peak ground reaction force during a kettlebell deadlift in older adults. These data will help inform healthcare providers and coaches about the use and prescription of kettlebell exercises with older adults.

Methods

Five males and five females <70 years of age who participated in the BELL trial were recruited. Two-handed hardstyle swings were performed with 8-16 kg, and deadlifts with 8-32 kg. Ground reaction force (GRF) was obtained from a floor-mounted force platform. Force-time curves (FTCs), peak force, forward force relative to vertical force, rate of force development (RFD), and swing cadence were investigated. Results were compared with the same data variables collected from the participants in an exploratory pre-intervention study, conducted approximately seven months before the present study. Participants completed approximately 90 kettlebell training sessions during a four-month training intervention.

Results

Participants used kettlebells to perform 3779 ± 802 swings, 923 ± 251 cleans, 825 ± 309 snatches and 744 ± 178 deadlifts during group-training sessions. Peak ground reaction force during kettlebell swings did not significantly change with any kettlebell weight. There was a significant 3% increase in the magnitude of forward force during 8 kg swings, and a significant 3% decrease in forward force during 16 kg swings. There were large significant improvements in swing cadence with a mean increase of three swings per minute and a small non-significant increase in RFD. Change in kettlebell swing force-time curve profiles were small. Change in peak ground reaction force during deadlifts were moderate to large. All participants increased in grip strength following training, with the magnitude of change greater than the minimum clinically important difference for seven participants. All participants had significant increases in multiple secondary outcomes.

Conclusion

Group-based and online kettlebell training is likely to be ineffective for improving the force profile of the hardstyle kettlebell swing in older adults. Insufficiently active older adults engaged in high-volume kettlebell training performed 3-5 times weekly, can however expect to see clinically meaningful improvements in health-related physical fitness irrespective of swing proficiency, and have increased confidence with heavy lifting tasks. Results of this study suggest that beyond safe and competent performance, striving to optimise hardstyle swing technique may provide no additional benefit to clinical outcomes in older adults.
Approbation of Self-directed Learning by first year medical students: a mixed method study
Authors: Bhandari Bharti , Chopra Deepti , Agarwal Prerna , Panwar Aprajita , Kaur Daljit , Sidhu Tanvir K
Published: September 2021

Background

One of the primary roles played by Indian medical graduates is to be a lifelong learner. For being a lifelong learner, the students should inculcate the habit of Self-Directed Learning (SDL). Lack of SDL skills among undergraduate medical students is a concern, hence the study was planned to introduce SDL in Physiology to phase-1 undergraduate medical students and assess its effectiveness through students’ and faculty’s perceptions.

Methodology

The project was commenced after obtaining clearance from the Institutional Ethics Committee. The faculty members and students were sensitized on SDL. Feedback questionnaire was framed and the topics for SDL were selected. Six topics were covered as part of the project. The effectiveness of the sessions was evaluated by administering the feedback questionnaire to the students and recording perceptions of the students and faculty on SDL. The quantitative and qualitative analysis of the data was done.

Results

A total of 96 phase-1 students participated in the study. Majority of the students felt that self-directed learning sessions have improved their SDL skills; they are more prepared and aware of their learning strengths and have started taking ownership of their learning. However some students felt the activity was not sufficient and SDL was not useful in improving their analytical skills. Both the students and the faculty were fairly satisfied by this teaching learning innovation.

Conclusions

Students and faculty were satisfied with the SDL strategy. SDL has shown to make them independent learner, who are aware of their learning goals and capable of evaluating their learning.
The COVID-19 pandemic and ophthalmic care: a qualitative study of patients with neovascular age-related macular degeneration (nAMD)
Authors: O’Connor Seán R , Treanor Charlene , Ward Elizabeth , Wickens Robin A , O’Connell Abby , Culliford Lucy A , Rogers Chris A , Gidman Eleanor A , Peto Tunde , Knox Paul C , Burton Benjamin J L , Lotery Andrew J , Sivaprasad Sobha , Reeves Barnaby C , Hogg Ruth E , Donnelly Michael ,   MONARCH Study Group
Published: September 2021

Background/aims

Concerns have been expressed about the relationship between reduced levels of health care utilisation and the COVID-19 pandemic. This study aimed to elicit and explore the views of patients with neovascular age-related macular degeneration (nAMD) regarding the COVID-19 pandemic and their ophthalmic care.

Methods

Between April 29th and September 4th 2020, semi-structured telephone interviews were conducted with thirty-five patients with nAMD taking part in a larger diagnostic accuracy study of home-monitoring tests. Participants were recruited using maximum variation sampling to capture a range of key characteristics including age, gender and time since initial treatment. Transcribed interview data were analysed using a deductive and inductive thematic approach.

Results

Three themes emerged from the analysis: i. access to eye clinic care. ii. COVID-19 mitigating factors and care delivery and iii. social and personal circumstances. Participants reported anxieties about cancelled or delayed appointments, limited communication from clinic-based services about appointments, and the impact of this on their ongoing care. Despite these concerns, there was apprehension about attending appointments due to infection risk and a perception that nAMD patients are a ‘high risk’ group. Views of those who attended clinics during the study period were, however, positive, with social distancing and infection control measures providing reassurance.

Conclusions

These findings contribute to our understanding about experiences of patients with nAMD during the COVID-19 pandemic and have potential implications for future planning of care services. Innovative approaches may be required to address issues related to access to care, including concerns about delayed or cancelled appointments.

Synopsis

Perspectives of patients with neovascular age-related macular degeneration regarding the COVID-19 pandemic identified important issues regarding access to, and experience of ophthalmic care. These findings have implications for future planning of services.
A scalable, clinically severe pig model for Duchenne muscular dystrophy
Authors: Stirm Michael , Fonteyne Lina Marie , Shashikadze Bachuki , Lindner Magdalena , Chirivi Maila , Lange Andreas , Kaufhold Clara , Mayer Christian , Medugorac Ivica , Kessler Barbara , Kurome Mayuko , Zakhartchenko Valeri , Hinrichs Arne , Kemter Elisabeth , Krause Sabine , Wanke Rüdiger , Arnold Georg J. , Wess Gerhard , Nagashima Hiroshi , de Angelis Martin Hrabĕ , Flenkenthaler Florian , Kobelke Levin Arne , Bearzi Claudia , Rizzi Roberto , Bähr Andrea , Matiasek Kaspar , Walter Maggie C. , Kupatt Christian , Ziegler Sibylle , Bartenstein Peter , Fröhlich Thomas , Klymiuk Nikolai , Blutke Andreas , Wolf Eckhard
Published: September 2021

Large animal models for Duchenne muscular dystrophy (DMD) are crucial for preclinical evaluation of novel diagnostic procedures and treatment strategies. Pigs cloned from male cells lackingDMDexon 52 (DMDΔ52) resemble molecular, clinical and pathological hallmarks of DMD, but cannot be propagated by breeding due to death before sexual maturity. Therefore, femaleDMD+/-carriers were generated. A single founder animal had 11 litters with 29DMDY/-, 34DMD+/-as well as 36 male and 29 female wild-type (WT) offspring. Breeding with F1 and F2DMD+/-carriers resulted in additional 114DMDY/-piglets. The majority of them survived for 3-4 months, providing large cohorts for experimental studies. Pathological investigations and proteome studies of skeletal muscles and myocardium confirmed the resemblance of human disease mechanisms. Importantly,DMDY/-pigs reveal progressive fibrosis of myocardium and increased expression of connexin-43, associated with significantly reduced left ventricular fractional shortening and ejection fraction already at age 3 months. Furthermore, behavioral tests provided evidence for impaired cognitive ability ofDMDY/-pigs. Our breeding cohort ofDMDΔ52 pigs and standardized tissue repositories fromDMDY/-pigs,DMD+/-carriers, and WT littermate controls provide important resources for studying DMD disease mechanisms and for testing novel diagnostic procedures and treatment strategies.
Increased pathogenicity of the nematophagous fungus Drechmeria coniospora following long-term laboratory culture
Authors: Courtine Damien , Zhang Xing , Ewbank Jonathan J.
Published: September 2021

Domestication provides a window into adaptive change. Over the course of 2 decades of laboratory culture, a strain of the nematode-specific fungus Drechmeria coniospora became more virulent during its infection of Caenorhabditis elegans. Through a close comparative examination of the genome sequences of the original strain and its more pathogenic derivative, we identified a small number of non-synonymous mutations in protein-coding genes. In one case, the mutation was predicted to affect a gene involved in hypoxia resistance and we provide direct corroborative evidence for such an effect. The mutated genes with functional annotation were all predicted to impact the general physiology of the fungus and this was reflected in an increased in vitro growth, even in the absence of C. elegans. While most cases involved single nucleotide substitutions predicted to lead to a loss of function, we also observed a predicted restoration of gene function through deletion of an extraneous tandem repeat. This latter change affected the regulatory subunit of a cAMP-dependent protein kinase. Remarkably, we also found a mutation in a gene for a second protein of the same, protein kinase A, pathway. Together, we predict that they result in a stronger repression of the pathway for given levels of ATP and adenylate cyclase activity. Finally, we also identified mutations in a few lineage-specific genes of unknown function that are candidates for factors that influence virulence in a more direct manner.
Motor learning in reaching tasks leads to homogenization of task space error distribution
Authors: Singh Puneet , Ghosal Oishee , Murthy Aditya , Ghosal Ashitava
Published: September 2021

A human arm, up to the wrist, is often modelled as a redundant 7 degree-of-freedom serial robot. Despite its inherent nonlinearity, we can perform point-to-point reaching tasks reasonably fast and with reasonable accuracy in the presence of external disturbances and noise. In this work, we take a closer look at the task space error during point-to-point reaching tasks and learning during an external force-field perturbation. From experiments and quantitative data, we confirm a directional dependence of the peak task space error with certain directions showing larger errors than others at the start of a force-field perturbation, and the larger errors are reduced with repeated trials implying learning. The analysis of the experimental data further shows that a) the distribution of the peak error is made more uniform across directions with trials and the error magnitude and distribution approaches the value when no perturbation is applied, b) the redundancy present in the human arm is used more in the direction of the larger error, and c) homogenization of the error distribution is not seen when the reaching task is performed with the non-dominant hand. The results support the hypothesis that not only magnitude of task space error, but the directional dependence is reduced during motor learning and the workspace is homogenized possibly to increase the control efficiency and accuracy in point-to-point reaching tasks. The results also imply that redundancy in the arm is used to homogenize the workspace, and additionally since the bio-mechanically similar dominant and non-dominant arms show different behaviours, the homogenizing is actively done in the central nervous system.

Significance

The human arm is capable of executing point-to-point reaching tasks reasonably accurately and quickly everywhere in its workspace. This is despite the inherent nonlinearities in the mechanics and the sensorimotor system. In this work, we show that motor learning enables homogenization of the task space error thus overcoming the nonlinearities and leading to simpler internal models and control of the arm movement. It is shown, across subjects, that the redundancy present in the arm is used to homogenize the task space. It is further shown, across subjects, that the homogenization is not an artifact of the biomechanics of the arm and is actively performed in the central nervous system since homogenization is not seen in the non-dominant hand.
Seasonal migration as a life history trait facilitating adaptation to climate change
Authors: Carbeck Katherine , Wang Tongli , Reid Jane , Arcese Peter
Published: September 2021

Predicting the geographic range of species and their response to variation in climate are entwined goals in conservation and evolutionary ecology. Species distribution models (SDMs) are foundational in this effort and used to visualize the geographic range of species as the spatial representation of its realized niche, or when based only on climate, its climate niche. SDMs can also forecast shifts in species range given climate change, but often lack of empirical support for causal links between climate and demography, yielding uncertain predictions. We addressed such uncertainties whilst also exploring the role of migration and resident life-histories in climate adaptation in mobile animals using 48 years of detailed demographic and climate data for song sparrows (Melospiza melodia), a polytypic species that varies in migratory life history. We developed SDMs representing demographic and climate niches of migratory and resident populations in western North America from California (CA) to Alaska (AK) using data from a focal population in British Columbia (BC) and 1.2 million citizen science observations. Distributions of resident and migrant populations predicted by each model agreed strongly (72.8%) in the region of our focal population, but less well in regions with dissimilar climates. Mismatches were largest in CA, smaller in AK, but in all cases supported the hypothesis that climate influences the evolution of migration and limits year-round residency. Our results imply that migrants predominated in our focal population a century ago, but that climate change has favored range expansions by non-migratory phenotypes and facilitated an upward shift in the elevational range of residents. We suggest long-term studies are crucial to evaluating the predictions of SDMs positing causal links between climatic conditions and species demography. We found such links to be robust regionally and particularly useful to elucidating the potential for migration or residence to facilitate adaptation to climate change.
Learning to embed lifetime social behavior from interaction dynamics
Authors: Wild Benjamin , Dormagen David M , Smith Michael L , Landgraf Tim
Published: September 2021

Interactions of individuals in complex social systems give rise to emergent behaviors at the group level. Identifying the functional role that individuals take in the group at a specific time facilitates understanding the dynamics of these emergent processes. An individual’s behavior at a given time can be partially inferred by common factors, such as age, but internal and external factors also substantially influence behavior, making it difficult to disentangle common development from individuality. Here we show that such dependencies on common factors can be used as an implicit bias to learn a temporally consistent representation of a functional role from social interaction networks. Using a unique dataset containing lifetime trajectories of multiple generations of individually-marked honey bees in two colonies, we propose a new temporal matrix factorization model that jointly learns the average developmental path and structured variations of individuals in the social network over their entire lives. Our method yields inherently interpretable embeddings that are biologically relevant and consistent over time, allowing one to compare individuals’ functional roles regardless of when or in which colony they lived. Our method provides a quantitative framework for understanding behavioral heterogeneity in complex social systems, and is applicable to fields such as behavioral biology, social sciences, neuroscience, and information science.

Author summary

Group-level emergent behaviors are the result of interactions between individual group members. To understand these social dynamics, one must objectively measure the function of an individual in their group at any given time. Ideally, one would also like to compare individuals from different groups, for example, to measure how specific environmental conditions or other external factors influence group behavior. Unfortunately, such an objective measure is hard to obtain because the group and its dynamics constantly change, making it challenging to define an individual’s role in the group as a function of its actions and interactions. We propose a principled approach to model individuals in complex social systems by considering that function often depends, at least partially, on common factors such as age. The model learns a meaningful and interpretable descriptor for all individuals, and can be used to understand how complex social systems function and the emergence of group behavior.
How much the response of rice genotypes to water deficit at the reproductive phase is dependent from environmental conditions?
Authors: de Lima Isabela Pereira , Lafarge Tanguy , de Castro Adriano Pereira , Roques Sandrine , Soutiras Armelle , Clément-Vidal Anne , Botelho Flávia Barbosa Silva , de Raïssac Marcel
Published: September 2021

Rice crop is known as particularly sensitive to water deficit, especially during the reproductive phase when growth of vegetative organs and formation of spikelets are simultaneous. Many works have focused on the response of rice plants to water deficits varying in timing, duration and intensity. Oppositely, the impact of the environmental conditions on the response to a given water deficit remains largely unknown. In order to test it, two experiments under contrasted conditions of temperature, radiation and VPD were conducted on six genotypes in greenhouse in Brazil (S) and in growth chamber in France (GC). The plants were submitted to the same mild water deficit at the reproductive phase, by adjusting FTSW at 0.4. Under irrigation, plant growth rate was reduced and crop duration extended in GC in relation to S: ultimately, this trade-off resulted in similar plant height and biomass in both environments. Under water deficit and in both environments, elongation rate decreased and was associated with an increase in soluble sugars in stem and flag leaf, while starch was reduced in S and negligible in GC because of the low radiation. This common biochemical response displayed a large gradient of values across environments and genotypes, but differentially impacted the branch and spikelet formation on the developing panicle: in carbon limiting conditions (GC), the increase in soluble sugars was associated with the reduction in branch and spikelet number, and conversely in S. At the morphological level, the maintenance of spikelet number on the panicle was correlated with the maintenance of flag leaf width in all genotypes and conditions, that was discussed according to the maintenance of the apical meristem size. Genotypes were discriminated and the study underlined the global tolerance of Cirad 409 and sensitivity of IAC 25.
Analysis and extension of exact mean-field theory with dynamic synaptic currents
Authors: Ruffini Giulio
Published: September 2021

Neural mass models such as the Jansen-Rit system provide a practical framework for representing and interpreting electrophysiological activity (1-6) in both local and global brain models (7). However, they are only partly derived from first principles. While the post-synaptic potential dynamics in NMM are inferred from data and can be grounded on diffusion physics (8-10), Freeman's wave to pulse sigmoid function (11-13), used to transduce mean population membrane potential into firing rate, rests on a weaker theoretical standing. On the other hand, Montbrio et al (14, 15) derive an exact mean-field theory (MPR) from a quadratic integrate and fire neuron model under some simplifying assumptions, thereby connecting microscale neural mechanisms and meso/macroscopic phenomena. The MPR model can be seen to replace Freeman's sigmoid function with a pair of differential equations for the mean membrane potential and firing rate variables - a dynamical relation between firing rate and membrane potential (firing rate potential relation or FPR)-, providing a mechanistic interpretation of NMM semi-empirical sigmoid parameters. In doing so, we show it sheds light on the mechanisms behind enhanced network response to weak but uniform perturbations. For example, in the exact mean-field theory, intrinsic population connectivity modulates the steady-state firing rate FPR in a monotonic manner, with increasing self-connectivity leading to higher firing rates. This provides a plausible mechanism for the enhanced response of densely connected networks to weak, uniform inputs such as the electric fields produced by non-invasive brain stimulation. The new, dynamic FPR also endows the neural mass model with a form of inertia, an intrinsic delay to external inputs that depends on, e.g., self-coupling strength and state of the system. Next, we complete the MPR model by adding the second-order equations for delayed post-synaptic currents, bringing together the MPR and the usual NMM formalisms into a unified exact mean-field theory (NMM2) displaying rich dynamical features. As an example, we analyze the dynamics of a single population model, and a model of two coupled populations with a simple excitation-inhibition (E-I) architecture, showing it displays rich dynamics with limit cycles, period doubling, bursting behavior, and enhanced sensitivity to external inputs.
Unmasking the cryptic immunopeptidome of EZH2 mutated diffuse large B-cell lymphomas through combination drug treatment
Authors: Bourne Christopher M. , Mun Sung Soo , Dao Tao , Aretz Zita E. H. , Gejman Ron S. , Daman Andrew , Takata Katsuyoshi , Steidl Christian , Klatt Martin G. , Scheinberg David A.
Published: September 2021

Exploring the repertoire of peptides presented on major histocompatibility complexes (MHC) has been utilized to identify targets for immunotherapy in many hematological malignancies. However, such data have not been described systematically for diffuse large B-cell lymphomas (DLBCL), which might be explained by the profound downregulation of MHC expression in many DLBCLs, and in particular in the EZH2-mutated subgroup. Epigenetic drug treatment, especially in the context of interferon gamma (IFNg), restored MHC expression in DLBCL. DLBCL MHC-presented peptides were identified via mass spectrometry following tazemetostat or decitabine treatments alone, or in combination with IFNg. Such treatment synergistically increased MHC class I surface protein expression up to 50-fold and class II expression up to 3-fold. Peptides presented on MHC complexes increased to a similar extent for MHC class I and remained constant for class II. Overall, these treatments restored the diversity of the immunopeptidome to levels described in healthy B cells and allowed the systematic search for new targets for immunotherapy. Consequently, we identified multiple MHC ligands from regulator of G protein signaling 13 (RGS13) and E2F transcription factor 8 (E2F8) on different MHC alleles, none of which have been described in healthy tissues and therefore represent tumor-specific MHC ligands, which are unmasked only after drug treatment. Overall, our results show that EZH2 inhibition in combination with decitabine and IFNg can expand the repertoire of MHC ligands presented on DLBCLs by revealing cryptic epitopes, thus allowing the systematic analysis and identification of new potential immunotherapy targets.

Key points

Combination therapy of interferon gamma with epigenetic regulators leads to large increases in the immunopeptidome of DLBCL.

HLA ligands from proteins RGS13 and E2F8 may provide DLBCL-specific targets for immunotherapy.
Wide-Angle, Monocular Head Tracking using Passive Markers
Authors: Vagvolgyi Balazs P. , Jayakumar Ravikrishnan P. , Madhav Manu S. , Knierim James J. , Cowan Noah J.
Published: September 2021

Camera images can encode large amounts of visual information of an animal and its environment, enabling high fidelity 3D reconstruction of the animal and its environment using computer vision methods. Most systems, both markerless (e.g. deep learning based) and marker-based, require multiple cameras to track features across multiple points of view to enable such 3D reconstruction. However, such systems can be expensive and are challenging to set up in small animal research apparatuses.

We present an open-source, marker-based system for tracking the head of a rodent for behavioral research that requires only a single camera with a potentially wide field of view. The system features a lightweight visual target and computer vision algorithms that together enable high-accuracy tracking of the six-degree-of-freedom position and orientation of the animal’s head. The system, which only requires a single camera positioned above the behavioral arena, robustly reconstructs the pose over a wide range of head angles (360◦ in yaw, and approximately ±120◦ in roll and pitch).

Experiments with live animals demonstrate that the system can reliably identify rat head position and orientation. Evaluations using a commercial optical tracker device show that the system achieves accuracy that rivals commercial multi-camera systems.

Our solution significantly improves upon existing monocular marker-based tracking methods, both in accuracy and in allowable range of motion.

The proposed system enables the study of complex behaviors by providing robust, fine-scale measurements of rodent head motions in a wide range of orientations.
Characterization of Mayer wave oscillations in functional near-infrared spectroscopy using a physiologically informed model of the neural power spectra
Authors: Luke Robert , Shader Maureen J , McAlpine David
Published: September 2021

Overview

Significance

Mayer waves are spontaneous oscillations in arterial blood pressure that can mask cortical hemodynamic responses associated with neural activity of interest.

Aim

To characterize the properties of oscillations in the fNIRS signal generated by Mayer waves in a large sample of fNIRS recordings. Further, we aim to determine the impact of short-channel correction for the attenuation of these unwanted signal components.

Approach

Mayer wave oscillation parameters were extracted from 310 fNIRS measurements using the Fitting Oscillations & One-Over-F (FOOOF) method to compute normative values. The effect of short-channel correction on Mayer wave oscillation power was quantified on 222 measurements. The practical benefit of the short-channel correction approach for reducing Mayer waves and improving response detection was also evaluated on a subgroup of 17 fNIRS measurements collected during a passive auditory speech detection experiment.

Results

Mayer-wave oscillations had a mean frequency of 0.108 Hz, bandwidth of 0.04 Hz, and power of 3.5 μM2/Hz. The distribution of oscillation signal power was positively skewed, with some measurements containing large Mayer waves. Short-channel correction significantly reduced the amplitude of these undesired signals; greater attenuation was observed for measurements containing larger Mayer-wave oscillations.

Conclusions

A robust method for quantifying Mayer-wave oscillations in the fNIRS signal spectrum was presented and used to provide normative parameterization. Short-channel correction is recommended as an approach for attenuating Mayer waves, particularly in participants with large oscillations.
Identification of Arhgef12 and Prkci as Genetic Modifiers of Retinal Dysplasia in the Crb1rd8 Mouse Model
Authors: Weatherly Sonia M. , Collin Gayle B. , Charette Jeremy R. , Stone Lisa , Damkham Nattaya , Hyde Lillian F. , Peterson James G. , Hicks Wanda , Carter Gregory W. , Naggert Jürgen K. , Krebs Mark P. , Nishina Patsy M.
Published: September 2021

Mutations in the apicobasal polarity gene CRB1 lead to diverse retinal diseases, such as Leber congenital amaurosis, cone-rod dystrophy, retinitis pigmentosa (with and without Coats-like vasculopathy), foveal retinoschisis, macular dystrophy, and pigmented paravenous chorioretinal atrophy. Limited correlation between disease phenotypes and CRB1 alleles, and evidence that patients sharing the same alleles often present with different disease features, suggest that genetic modifiers contribute to clinical variation. Similarly, the retinal phenotype of mice bearing the Crb1 retinal degeneration 8 (rd8) allele varies with genetic background. Here, we initiated a sensitized chemical mutagenesis screen in B6.Cg-Crb1rd8/Pjn, a strain with a mild clinical presentation, to identify genetic modifiers that cause a more severe disease phenotype. Two models from this screen, Tvrm266 and Tvrm323, exhibited increased retinal dysplasia. Genetic mapping with high-throughput exome and candidate-gene sequencing identified causative mutations in Arhgef12 and Prkci, respectively. Epistasis analysis of both strains indicated that the increased dysplastic phenotype required homozygosity of the Crb1rd8 allele. Retinal dysplastic lesions in Tvrm266 mice were smaller and caused less photoreceptor degeneration than those in Tvrm323 mice, which developed an early, large diffuse lesion phenotype. In both models at one month of age, Müller glia and microglia mislocalization at dysplastic lesions was similar to that in B6.Cg-Crb1rd8/Pjn mice, while photoreceptor cell mislocalization was more extensive. External limiting membrane disruption was comparable in Tvrm266 and B6.Cg- Crb1rd8/Pjn mice but milder in Tvrm323 mice. Immunohistological analysis of mice at postnatal day 0 indicated a normal distribution of mitotic cells in Tvrm266 and Tvrm323 mice, suggesting normal early development. Aberrant electroretinography responses were observed in both models but functional decline was significant only in Tvrm323 mice. These results identify Arhgef12 and Prkci as modifier genes that differentially shape Crb1-associated retinal disease, which may be relevant to understanding clinical variability and underlying disease mechanisms.
A climate-based model for tick life cycle: an infinite system of differential equation approach
Authors: Chenaoui Cyrine , Miled Slimane Ben , Ndongo Mamadou Sadio , Ndiaye Papa Ibrahima , Rekik Mourad , Darghouth Mohamed Aziz
Published: September 2021

The distribution of ticks is essentially determined by the presence of climatic conditions and ecological contexts suitable for their survival and development.

We have developed a general tick biology model to study the major trends due to climate change on tick population dynamics under different climate conditions.

We build a model that explicitly takes into account stage into each physiological state through a system of infinite differential equations where tick population density are structured on an infinite discrete set. We suppose that intrastage development process is temperature dependent (Arrhenius temperatures function) and that larvae hatching and adult mortality are temperature and precipitations dependent.

We analysed mathematically the model and have explicit theR0of the tick population. Therefore, we performed a numerical analysis of the model under three different climate conditions (tropical, Mediterranean and subarctic climates) over the short term using climatic data from 1995 to 2005, as well as long-term simulations from 1902 to 2005.
Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic
Authors: Chow Yuen Ler , Singh Shantanu , Carpenter Anne E. , Way Gregory P.
Published: September 2021

A variational autoencoder (VAE) is a machine learning algorithm, useful for generating a compressed and interpretable latent space. These representations have been generated from various biomedical data types and can be used to produce realistic-looking simulated data. However, standard vanilla VAEs suffer from entangled and uninformative latent spaces, which can be mitigated using other types of VAEs such as β-VAE and MMD-VAE. In this project, we evaluated the ability of VAEs to learn cell morphology characteristics derived from cell images. We trained and evaluated these three VAE variants—Vanilla VAE, β-VAE, and MMD-VAE—on cell morphology readouts and explored the generative capacity of each model to predict compound polypharmacology (the interactions of a drug with more than one target) using an approach called latent space arithmetic (LSA). To test the generalizability of the strategy, we also trained these VAEs using gene expression data of the same compound perturbations and found that gene expression provides complementary information. We found that the β-VAE and MMD-VAE disentangle morphology signals and reveal a more interpretable latent space. We reliably simulated morphology and gene expression readouts from certain compounds thereby predicting cell states perturbed with compounds of known polypharmacology. Inferring cell state for specific drug mechanisms could aid researchers in developing and identifying targeted therapeutics and categorizing off-target effects in the future.
Bakta: Rapid & standardized annotation of bacterial genomes via alignment-free sequence identification
Authors: Schwengers Oliver , Jelonek Lukas , Dieckmann Marius , Beyvers Sebastian , Blom Jochen , Goesmann Alexander
Published: September 2021

Command line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command line software pipelines heavily depend on taxon specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command line software tool for the robust, taxon-independent, thorough and nonetheless fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross references. Annotation results are exported in GFF3 and INSDC-compliant flat files as well as comprehensive JSON files facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references whilst providing comparable wall clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio.
The effect of microbial selection on the occurrence-abundance patterns of microbiomes
Authors: Zapién-Campos Román , Sieber Michael , Traulsen Arne
Published: September 2021

Theoretical models are useful to investigate the drivers of community dynamics. Notable are models that consider the events of death, birth, and immigration of individuals assuming they only depend on their abundance – thus, all types share the same parameters. The community level expectations arising from these simple models and their agreement to empirical data have been discussed extensively, often suggesting that in nature, rates might indeed be neutral or their differences not important. But, how robust are these model predictions to type-specific rates? And, what are the consequences at the level of types? Here, we address these questions moving from simple to diverse communities. For this, we build a model where types are differently adapted to the environment. We adapt a computational method from the literature to compute equilibrium distributions of the abundance. Then, we look into the occurrence-abundance pattern often reported in microbial communities. We observe that large immigration and biodiversity – common in microbial systems – lead to such patterns, regardless of whether the rates are neutral or non-neutral. We conclude by discussing the implications to interpret and test empirical data.
Commensal Pseudomonas fluorescens protect Arabidopsis from closely-related Pseudomonas pathogens in a colonization-dependent manner
Authors: Wang Nicole R. , Melnyk Ryan A. , Wiesmann Christina L. , Hossain Sarzana S. , Chi Myoung-Hwan , Martens Kitoosepe , Haney Cara H.
Published: September 2021

Plants form commensal associations with soil microorganisms, creating a root microbiome that provides benefits to the host including protection against pathogens. While bacteria can inhibit pathogens through production of antimicrobial compounds in vitro, it is largely unknown how microbiota contribute to pathogen protection in planta. We developed a gnotobiotic model system consisting of Arabidopsis thaliana, and an opportunistic pathogen Pseudomonas sp. N2C3, to identify mechanisms that determine the outcome of plant-pathogen-microbiome interactions in the rhizosphere. We screened 25 phylogenetically diverse Pseudomonas strains for their ability to protect against N2C3 and found that commensal strains closely related to N2C3 were more likely to protect against pathogenesis. We used a comparative genomics approach to identify unique genes in the protective strains that revealed no genes that correlate with protection, suggesting that variable regulation of components of the core Pseudomonas genome may contribute to pathogen protection. We found that commensal colonization level was highly predictive of protection and so tested deletions in genes previously shown to be required for Arabidopsis rhizosphere colonization. We identified a response regulator colR that is required for Pseudomonas protection from N2C3 and fitness in competition with N2C3 indicating that competitive exclusion may contribute to pathogen protection. We found that Pseudomonas WCS365 also protects against the agricultural pathogen Pseudomonas fuscovaginae SE-1, the causal agent of bacterial sheath brown rot of rice. This work establishes a gnotobiotic model to uncover mechanisms by which members of the microbiome can protect hosts from pathogens and informs our understanding of the use of beneficial strains for microbiome engineering in dysbiotic soil systems.
Multiplexed triage of candidate biomarkers in plasma using internal standard triggered-parallel reaction monitoring mass spectrometry
Authors: Kennedy Jacob J. , Whiteaker Jeffrey R. , Ivey Richard G. , Burian Aura , Chowdhury Shrabanti , Tsai Chia-Feng , Liu Tao , Lin ChenWei , Murillo Oscar , Lundeen Rachel , Jones Lisa A. , Gafken Philip R. , Longton Gary , Rodland Karin D. , Skates Steven , Landua John , Wang Pei , Lewis Michael T. , Paulovich Amanda G.
Published: September 2021

Despite advances in proteomic technologies, clinical translation of plasma biomarkers remains low, partly due to a major bottleneck between the discovery of candidate biomarkers and downstream costly clinical validation studies. Due to a dearth of multiplexable assays, generally only a few candidate biomarkers are tested, and the validation success rate is accordingly low. Here, we demonstrate the capability of internal standard triggered-parallel reaction monitoring (IS-PRM) to prioritize candidate biomarkers for validation studies. A 5,176-plex assay coupling immunodepletion and fractionation with IS-PRM was developed and implemented in human plasma to quantify peptides representing 1,314 breast cancer biomarker candidates. Compared to prior approaches using data-dependent analysis, IS-PRM showed improved sensitivity (912 vs 295 proteins quantified) and precision (CV 0.1 vs 0.27) enabling rank-ordering of candidate biomarkers for validation studies. The assay greatly expands capabilities for quantification of large numbers of proteins and is well suited for prioritization of viable candidate biomarkers.
miR-34bassociates with epithelial-mesenchymal transition and regulatesBMP7, CAV1, ID2andFN1in human cervical cancer
Authors: Venkatesan Nalini , Xavier Ashley , K.J. Sindhu , Sundhram Sandhya , Sinha Himanshu , Karunagaran Devarajan
Published: September 2021

Purpose

We aimed to identify the epithelial-mesenchymal transition and associated putative targets of themiR-34family in transcriptomic data of cervical epithelial squamous cell carcinoma (CESC) to find new therapeutic targets for better disease management.

Methods

A combined computational analysis of themiR-34family; gene expression in heterogeneous primary CESCs derived from TCGA; and the integration ofmiR-34band EMT-regulated genes was performed. Four EMT-associatedmiR-34bgene targets were analysed in primary human CESC and non-cancerous cervical tissues by qRT-PCR. Effects of endogenousmiR-34bexpression and its associated gene modulations in cervical cancer cells (C33A and HeLa) were analysed using qRT-PCR, western blotting and immunofluorescence, transwell migration and invasion assays.

Results

The results showed that themiR-34family might regulate the mTOR pathway, cell cycle (CCND2) and cell adhesion functions (FZD4). Further, we showed that a low negative correlation (r2= −0.07) betweenmiR-34b/EMĨscore and four EMT signature genes (E>MP7, CAV1, ID2, FN1) were significantly regulated bymiR-34b. Also,FN1was indicated as its putative target with the highest negative EMT score and high binding energy between MRE/3’UTR. Further, these transcriptomic signatures in CESC revealed a significant inverse correlation across the stages of primary human CESC. These genes were repressed at transcriptional and translational levels inmiR-34b-3pexpressing C33A and HeLa cells, contributing to their reduced cell migration and invasive properties.

Conclusions

Our studies revealed the potential targets of themiR-34family, especiallymiR-34b, that can emerge as potential biomarkers and promising therapeutic targets in CESC disease management.
Cluster mean-field theory accurately predicts statistical properties of large-scale DNA methylation patterns
Authors: Kerr Lyndsay , Sproul Duncan , Grima Ramon
Published: September 2021

The accurate establishment and maintenance of DNA methylation patterns is vital for mammalian development and disruption to these processes causes human disease. Our understanding of DNA methylation mechanisms has been facilitated by mathematical modelling, particularly stochastic simulations. Mega-base scale variation in DNA methylation patterns is observed in development, cancer and ageing and the mechanisms generating these patterns are little understood. However, the computational cost of stochastic simulations prevents them from modelling such large genomic regions. Here we test the utility of three different mean-field models to predict large-scale DNA methylation patterns. By comparison to stochastic simulations, we show that a cluster mean-field model accurately predicts the statistical properties of steady-state DNA methylation patterns, including the mean and variance of methylation levels calculated across a system of CpG sites, as well as the covariance and correlation of methylation levels between neighbouring sites. We also demonstrate that a cluster mean-field model can be used within an approximate Bayesian computation framework to accurately infer model parameters from data. As mean-field models can be solved numerically in a few seconds, our work demonstrates their utility for understanding the processes underpinning large-scale DNA methylation patterns.
A systematic literature review of community disaster resilience: main and related research areas and agendas
Authors: Upadhyay Arvind , Sa-ngiamwibool Amporn
Published: September 2021

Purpose

This study aims to characterize the main research areas of published works, identify the disciplines that associated with the works and propose research agendas for future inquiries, based on a systematic literature review that encompasses 89 research papers from 2010 to 2020.

Design/methodology/approach

This review commenced with the definition of the three research questions, and subsequently three steps were followed: (1) defining criteria for research paper selection; (2) specifying the data bases and selecting the papers based on the criteria and (3) data analysis, conclusion and discussion of selected papers. The search was limited to the selection of research papers in English, focusing on “community disaster resilience” which is the subject of this review and referred to as keywords which were used for the online search for papers. All these three words must be present in the title of the selected papers.

Findings

The area “resilience management” and “disaster resilience assessment” accounted for 43% of the studies, and it indicates that research has emphasized the description of how community disaster resilience has been managed and assessed. Three disciplines relating to disaster resilience are disaster risk science, public health and environment, and it indicates that research has fostered core areas of community disaster resilience. Three key research agenda include a growing trend to describe successful efforts to avert a potentially catastrophic disaster through solution-based case studies; a paradigmatic shift and implementation of how communities could help the disaster victims recuperate from disasters.

Research limitations/implications

This review is limited to the numbers of chosen papers, as only full papers were chosen. However, in order to establish more rigorous and inclusive results of the study, the numbers of citations of published papers to be chosen for future inquiry should be taken into account.

Originality/value

This present review originally investigated how the concept of disaster resilience has been applied at the community level and in related areas. As resilience is a multidisciplinary concept that has been investigated by several different disciplines, such as sustainability, psychology, economy and sociology, this study looked into how disciplines related to community disaster resilience to provide agenda for future inquiries. This study therefore characterized the main research areas of published works, identified the disciplines that associated with the works and proposed a research agenda for future inquiries.