bluuebunny/crossref_metadata_2025 huggingface dataset:
Behavioural changes in aposematicHeliconius melpomenebutterflies in response to their predatory bird calls
Authors: Potdar Sushant , Dinakar Madhuri , Westerman Erica L.
Published: October 2023

Prey-predator interactions have resulted in the evolution of many anti-predatory traits. One of them is the ability for prey to listen to predators and avoid them. Although prey anti-predatory behavioural responses to predator auditory cues are well described in a wide range of taxa, studies on whether butterflies change their behaviours in response to their predatory calls are lacking.Heliconiusbutterflies are unpalatable and form Müllerian mimicry rings as morphological defence strategies against their bird predators. Like many other butterflies in theNymphalidaefamily,Heliconiusbutterflies possess auditory organs, which are hypothesized to have evolved to assist with predator detection. Here we test whetherHeliconius melpomenechange their behaviour in response to their predatory bird calls by observing the behaviour of male and femaleH. m. plessiniexposed to calls ofHeliconiusavian predators: rufous-tailed jacamar, migratory Eastern kingbird, and resident tropical kingbird. We also exposed them to the calls of the toco toucan, a frugivorous bird as a control bird call, and an amplified greenhouse background noise as a noise control. We found that individuals changed their behaviour in response to jacamar calls only. Males increased their walking and fluttering behaviour, while females did not change their behaviour during the playback of the jacamar call. Intersexual behaviours like courtship, copulation, and abdomen lifting did not change in response to bird calls. Our findings suggest that despite having primary predatory defences like toxicity and being in a mimicry ring,H. m. plessinibutterflies changed their behaviour in response to predator calls. Furthermore, this response was predator specific, asH. m. plessenidid not respond to either the Eastern kingbird or the tropic kingbird calls. This suggests thatHeliconiusbutterflies may be able to differentiate predatory calls, and potentially the birds associated with those calls.

Highlights

Many prey animals change their behaviour in response to their predator’s calls.

Whether butterflies alter behaviour in response to bird predator calls is unknown.

We show thatHeliconius melpomenechange behaviour in response to jacamar calls.

Males increased walking and fluttering, but did not alter courting behaviour.

H. melpomenedid not respond to predatory Eastern kingbird or tropical kingbird calls.
Meta-analysis on the effects of chemical stressors on five ecosystem functions: are there generalizable relationships?
Authors: Feckler Alexander , Schulz Ralf , Schäfer Ralf B.
Published: October 2023

Despite considerable progress in our predictive capacity for the response of different trophic levels to chemicals, generalizable relations between chemicals and ecosystem functions are lacking. We addressed this knowledge gap by conducting the largest meta-analysis to date (136 studies; ∼350 observations) on the responses of ecosystem functions to chemicals. Based on this analysis, for selected classes of chemicals (pesticides, pharmaceuticals, and metals), we are the first to establish relations between chemical concentrations and the ecosystem functions organic matter decomposition and photosynthesis, showing monotonic dose-response relationships. These results concur with existing field data on chemical effects, which underpins the value of our findings. Taking into account the outlined research gaps and shortcomings, our findings and recommendations can be seen as a promising starting point to advance predictions of responses of ecosystem functions to selected chemical classes.
EV-Elute: a universal platform for enrichment of functional surface marker-defined extracellular vesicle subpopulations
Authors: de Voogt Willemijn S , Frunt Rowan , Leandro Raul M , Triesscheijn Casper S , Monica Bella , Paspali Ioanna , Tielemans Mark , Francois Jerney JJM , Seinen Cor W , de Jong Olivier G , Kooijmans Sander AA
Published: October 2023

Intercellular communication via extracellular vesicles (EVs) has been identified as a vital component of a steadily expanding number of physiological and pathological processes. To accommodate these roles, EVs are equipped with specific proteins, lipids, and RNA molecules by EV-secreting cells. Consequently, EVs have highly heterogeneous molecular compositions. Given that surface molecules on EVs determine their interactions with their environment, it is conceivable that EV functionality differs between subpopulations with varying surface compositions. However, it has been technically challenging to examine such functional heterogeneity due to a lack of non-destructive methods to separate EV subpopulations based on their surface markers. Here, we used Design-of-Experiments methodology to rapidly optimize a protocol, which we name ‘EV-Elute’, to elute intact EVs from commercially available Protein G-coated magnetic beads. We captured EVs from various cell types on these beads using antibodies against CD9, CD63, CD81 and a custom-made protein binding phosphatidylserine (PS). When applying EV-Elute, over 70% of bound EVs could be recovered from the beads in a pH– and incubation time-dependent fashion. EV subpopulations were found to be devoid of co-isolated protein contaminants observed in whole EV isolates and showed intact morphology by electron microscopy. Proteinase K protection assays showed a mild and reversible decrease of EV membrane integrity during elution. Depending on the type of capturing antibody used, some antibodies remained EV-associated after elution. EV subpopulations showed uptake patterns similar to whole EV isolates in co-cultures of peripheral blood mononuclear cells and endothelial cells. However, in Cas9/sgRNA delivery assays, CD63+EVs showed a lower capacity to functionally deliver cargo as compared to CD9+, CD81+and PS+EVs. Taken together, we developed a novel, easy-to-use platform to isolate and functionally compare surface marker-defined EV subpopulations. Importantly, this platform does not require specialized equipment or reagents and is universally applicable to any capturing antibody and EV source. Hence, EV-Elute can open new opportunities to study EV functionality at the subpopulation level.
Exploring Okra-Derived Compounds as Prospective Aromatase Inhibitors: A Computational Study for Enhanced Breast Cancer Therapy
Authors: Lavanya B , Mallur Dhrithi Jayasimha , Temkar Sheshadri S , Arun V , C Benedict Paul
Published: October 2023

Breast cancer with estrogen receptor positivity represents itself as the most prevalent malignancy among postmenopausal women. One of the promising therapeutic approach involves the use of Aromatase Inhibitors, which competitively bind to aromatase, reducing estrone and estradiol levels. While current drugs have improved survival rates, they are not without adverse effects. Consequently, this study explores the computational screening of medicinally relevant compounds derived from Okra for potential Aromatase Inhibition. Molecular Docking, employing AMDock v1.5.2, was utilized to assess binding affinities with aromatase (PDB:3EQM). Subsequently, in-depth molecular interactions were examined using Discovery Studio Visualizer v4.5, and the stability of docked complexes was evaluated via Molecular Dynamics with the GROMACS package, focusing on RMSD, RMSF, H-bond count, and SASA. The pharmacokinetic properties of the Okra compounds were predicted using admetSAR v2.0. Our findings highlight Quercetin 3-gentiobioside as a standout candidate, demonstrating superior binding affinity (-10 kcal/mol) and an Estimated Ki of 46.77 nM compared to Letrozole and other Okra compounds. Molecular dynamics analysis confirms the stability of Quercetin 3-gentiobioside binding in terms of H-bonds and conformational integrity. In conclusion, our computational investigation identifies Quercetin 3-gentiobioside, along with Quercetin 3-O-rutinoside and Hyperin, as promising candidates for preclinical studies in the pursuit of potential Aromatase Inhibitors.
Comparative Genomics Exploration of Shared lncRNA-coding genes in Human and All Annotated Plant Genomes: Potential Implications for Cancer Research
Authors: Mateiu Ligia
Published: October 2023

Since their discovery in 1990, lncRNAs have been heavily investigated. It is already known that the genomes of plants and animals express large numbers of lncRNAs. In humans, many lncRNA are considered essential players in cancer biology, mainly acting as gene expression regulators in processes like cell proliferation, apoptosis, migration, invasion and stemness. In plants, lncRNAs are involved in vegetative growths, reproduction and stress responses. Yet, in the entirety of the animal and plant kingdoms, the functions and mechanisms of action for the majority of lncRNAs remain largely undiscovered, as do their orthology relationships. The poor conservation of the DNA sequences encoding for these transcripts is hindering the identification of lncRNAs orthologs especially among very distant evolutionary species. In this short study, using an uncomplicated, but creative bioinformatic approach, I searched for sequence homologies between human DNA and 175 annotated plant genomes from NCBI. Using stringent filtering, I found 20 human lncRNA-encoding genes overlapping plant genomic features, including lncRNAs. Evenmore, 3 of these human lncRNA-encoding genes with a potential plant ortholog are reported in multiple databases for lncRNA involved in cancers. This study opens the road for investigating the tumorigenesis in a deep homology context of lncRNAs.
Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis
Authors: Wang Beibei , Luan Yihui
Published: October 2023

Significant advancements have been made in metagenomic research for the prediction of phenotypes based on microbiome data. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes using 3 simulations and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in root mean squared error of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes.
Power and reproducibility in the external validation of brain-phenotype predictions
Authors: Rosenblatt Matthew , Tejavibulya Link , Camp Chris C. , Jiang Rongtao , Westwater Margaret L. , Noble Stephanie , Scheinost Dustin
Published: October 2023

Identifying reproducible and generalizable brain-phenotype associations is a central goal of neuroimaging. Consistent with this goal, prediction frameworks evaluate brain-phenotype models in unseen data. Most prediction studies train and evaluate a model in the same dataset. However, external validation, or the evaluation of a model in an external dataset, provides a better assessment of robustness and generalizability. Despite the promise of external validation and calls for its usage, the statistical power of such studies has yet to be investigated. In this work, we ran over 60 million simulations across several datasets, phenotypes, and sample sizes to better understand how the sizes of the training and external datasets affect statistical power. We found that prior external validation studies used sample sizes prone to low power, which may lead to false negatives and effect size inflation. Furthermore, increases in the external sample size led to increased simulated power directly following theoretical power curves, whereas changes in the training dataset size offset the simulated power curves. Finally, we compared the performance of a model within a dataset to the external performance. The within-dataset performance was typically withinr=0.2of the cross-dataset performance, which could help decide how to power future external validation studies. Overall, our results illustrate the importance of considering the sample sizes of both the training and external datasets when performing external validation.
Batch-effect correction in single-cell RNA sequencing data using JIVE
Authors: Hastings Joseph , Lee Donghyung , O’Connell Michael J.
Published: October 2023

In single-cell RNA sequencing (scRNA-seq) data analysis, addressing batch effects — technical artifacts stemming from factors such as varying sequencing technologies, equipment, and capture times — is crucial. These factors cause unwanted variation in the data and often obfuscate the underlying biological signal of interest. The Joint and Individual Variation Explained (JIVE) method can be used to extract shared biological patterns from multi-source sequencing data while adjusting for individual non-biological variations (i.e., batch effect). However, its current implementation is originally designed for bulk sequencing data, making it computationally infeasible for large-scale single-cell sequencing datasets. In this study, we enhance JIVE for large-scale scRNA-seq data by boosting its computational efficiency and tailoring it to the single-cell context. Additionally, we introduce a novel application of JIVE which we use to perform batch-effect correction on multiple scRNA-seq datasets. Our enhanced JIVE method aims to decompose scRNA-seq datasets into a joint structure capturing the true biological variability and individual structures which capture technical variability within each batch. This joint structure is then suitable for use in downstream analyses. We employed four evaluation metrics and benchmarked the results against two other popular tools, Seurat v3 and Harmony, which were developed for this purpose. We found that JIVE performed best in metrics that consider local neighborhoods (kBET and LISI) and in scenarios in which the original data contained distinct differences between batches and cell types.
A Reinterpretation of the Relationship Between Persistent and Resurgent Sodium Currents
Authors: Brown Samuel P. , Lawson Ryan J. , Moreno Jonathan D. , Ransdell Joseph L.
Published: October 2023

The resurgent sodium current (INaR) activates on membrane repolarization, such as during the downstroke of neuronal action potentials. Due to its unique activation properties, INaRis thought to drive high rates of repetitive neuronal firing. However, INaRis often studied in combination with the persistent or non-inactivating portion of sodium currents (INaP). We used dynamic clamp to test how INaRand INaPindividually affect repetitive firing in adult cerebellar Purkinje neurons from male and female mice. We learned INaRdoes not scale repetitive firing rates due to its rapid decay at subthreshold voltages, and that subthreshold INaPis critical in regulating neuronal firing rate. Adjustments to the Nav conductance model used in these studies revealed INaPand INaRcan be inversely scaled by adjusting occupancy in the slow inactivated kinetic state. Together with additional dynamic clamp experiments, these data suggest the regulation of sodium channel slow inactivation can fine-tune INaPand Purkinje neuron repetitive firing rates.

Significance Statement

Across neuronal cell types, the resurgent sodium current (INaR) is often implicated in driving high rates of repetitive firing. Using dynamic clamp, we determined INaRis ineffective at driving subsequent action potentials, and that the subthreshold persistent sodium current (INaP) is the critical parameter for scaling repetitive firing rates. We propose INaRmeasured in native neurons may reflect a mechanism by which the magnitude of INaPis fine-tuned.
Self-perceived middle-distance race pace is faster in Advanced Footwear Technology spikes
Authors: Bertschy Montgomery , Rodrigo-Carranza Victor , Wilkie Ethan W.C. , Healey Laura A. , Noble Jeremy , Albert Wayne J. , Hoogkamer Wouter
Published: October 2023

Background

Quantifying the potential benefits of advanced footwear technology (AFT) track shoes (i.e., “spikes”) in middle-distance events is challenging, because repeated maximal effort trials (as in sprinting) or aerobic running economy trials (as in long-distance running) are not feasible.

Methods

We introduce a novel approach to assess the benefits of AFT spikes, consisting of a series of 200 m runs at self-perceived middle-distance race pace with 10 min recovery and conducted four experiments to evaluate its validity, sensitivity, reproducibility, and utility.

Results

In experiment 1, participants ran 1.2% slower in spikes with 200 g added mass vs. control spikes, exactly equal to the known effects of shoe mass on running performance. In experiment 2, participants ran significantly faster in AFT prototype spikes vs. traditional spikes. In experiment 3, we compared two other AFT prototype spikes against traditional spikes, on three separate days. Group-level results were consistent across days, but our data indicates that at least two separate sessions are needed to evaluate individual responses. In experiment 4, participants ran significantly faster in two AFT spike models vs. traditional spikes (2.1% and 1.6%). Speed was similar between a third AFT spike model and the traditional spikes. These speed results were mirrored by changes in step length, as participants took significantly longer steps in the two faster AFT spike models (2.3% and 1.9%), while step length was similar between the other spikes.

Conclusion

Our novel, interval-based approach is a valid and reliable method to quantify differences between spikes at middle-distance running intensity.
Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation
Authors: Tan Tian , Shull Peter B. , Hicks Jenifer L. , Uhlrich Scott D. , Chaudhari Akshay S.
Published: October 2023

Objective

Recent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing self-supervised learning (SSL) techniques to leverage large IMU datasets to pre-train deep learning models, which can improve the accuracy and data efficiency of IMU-based GRF estimation.

Methods

We performed SSL by masking a random portion of the input IMU data and training a transformer model to reconstruct the masked portion. We systematically compared a series of masking ratios across three pre-training datasets that included real IMU data, synthetic IMU data, or a combination of the two. Finally, we built models that used pre-training and labeled data to estimate GRF during three prediction tasks: overground walking, treadmill walking, and drop landing.

Results

When using the same amount of labeled data, SSL pre-training significantly improved the accuracy of 3-axis GRF estimation during walking compared to baseline models trained by conventional supervised learning. Fine-tuning SSL model with 1–10% of walking data yielded comparable accuracy to training baseline model with 100% of walking data. The optimal masking ratio for SSL is 6.25–12.5%.

Conclusion

SSL leveraged large real and synthetic IMU datasets to increase the accuracy and data efficiency of deep-learning-based GRF estimation, reducing the need for labeled data.

Significance

This work, with its open-source code and models, may unlock broader use cases of IMU-driven kinetic assessment by mitigating the scarcity of GRF measurements in practical applications.
Enhancing Hi-C contact matrices for loop detection with Capricorn, a multi-view diffusion model
Authors: Fang Tangqi , Liu Yifeng , Woicik Addie , Lu Minsi , Jha Anupama , Wang Xiao , Li Gang , Hristov Borislav , Liu Zixuan , Xu Hanwen , Noble William S. , Wang Sheng
Published: October 2023

High-resolution Hi-C contact matrices reveal the detailed three-dimensional architecture of the genome, but high-coverage experimental Hi-C data are expensive to generate. On the other hand, chromatin structure analyses struggle with extremely sparse contact matrices. To address this problem, computational methods to enhance low-coverage contact matrices have been developed, but existing methods are largely based on resolution enhancement methods for natural images and hence often employ models that do not distinguish between biologically meaningful contacts, such as loops, and other stochastic contacts. We present Capricorn, a machine learning model for Hi-C resolution enhancement that incorporates small-scale chromatin features as additional views of the input Hi-C contact matrix and leverages a diffusion probability model backbone to generate a high-coverage matrix. We show that Capricorn outperforms the state of the art in a cross-cell-line setting, improving on existing methods by 17.8% in mean squared error and 22.9% in F1 score for chromatin loop identification from the generated high-coverage data. We also demonstrate that Capricorn performs well in the cross-chromosome setting and cross-chromosome, cross-cell-line setting, improving the downstream loop F1 score by 15.7% relative to existing methods. We further show that our multi-view idea can also be used to improve several existing methods, Hi-CARN and HiCNN, indicating the wide applicability of this approach. Finally, we use DNA sequence to validate discovered loops and find that the fraction of CTCF-supported loops from Capricorn is similar to those identified from the high-coverage data. Capricorn is a powerful Hi-C resolution enhancement method that enables scientists to find chromatin features that cannot be identified in the low-coverage contact matrix. Implementation of Capricorn and source code for reproducing all figures in this paper are available athttps://github.com/CHNFTQ/Capricorn.
Back to sequences: find the origin ofk-mers
Authors: Baire Anthony , Peterlongo Pierre
Published: October 2023

A vast majority of bioinformatics tools dedicated to the treatment of raw sequencing data heavily use the concept ofk-mers. This enables us to reduce the data redundancy (and thus the memory pressure), to discard sequencing errors, and to dispose of objects of fixed size that can be manipulated and easily compared to each others. A drawback is that the link between eachk-mer and the original set of sequences it belongs to is generally lost. Given the volume of data considered in this context, finding back this association is costly. In this work, we present “back_to_sequences”, a simple tool designed to index a set ofk-mers of interests, and to stream a set of sequences, extracting those containing at least one of the indexedk-mer. In addition, the number of occurrences ofk-mers in the sequences is provided. Our results show thatback_to_sequencesstreams≈200 short read per millisecond, enabling to searchk-mers in hundreds of millions of reads in a matter of a few minutes.

Availability

github.com/pierrepeterlongo/back_to_sequences
Changing variability is an overlooked aspect of protected area planning
Authors: Marcus Rekha , Noonan Michael J.
Published: October 2023

Protected areas are widely used management tools designed to support the long-term conservation of biodiversity. The effectiveness of protected areas is being challenged by human-induced climate change, however, which is causing three broad shifts away from the current distribution of climate trends: a change in mean conditions, a change in the variance around the mean, and/or a change in symmetry. Though changes in average conditions are certainly important, the second behaviour, a change in variance, brings a unique set of challenges that species must respond to. As conditions become more variable, phenological events become less predictable, extreme weather events become more frequent, food security and ecosystem stability are compromised, and extinction risk increases. It therefore stands to reason that changes in the variance of local conditions should be a core consideration when designing protected areas.

Here, we reviewed the literature to determine the extent to which changes in variance are being incorporated into protected area planning. Worryingly, we found that fewer than a quarter of the 100 studies we surveyed formally considered how climate change might change mean conditions, and only four considered climate change-induced changes in the variance around the mean. Our evaluation reveals an alarming gap in protected area research. The majority of researchers continue to make recommendations for protected areas without acknowledging that the area(s) they are recommending for protection may have markedly different conditions in the future. Whether variability is considered or not, stochastic events represent a serious threat to the persistence of species and complex ecosystems. Effective conservation requires actively considering how the stability of conditions within protected areas will be impacted by future climate change. As global climate patterns tend towards increasing unpredictability, protecting less variable habitat should be a priority to ensure local populations are not exposed to elevated extinction risk.
Rhodococcus equiEscapes Macrophage Autophagy: VapA Inhibits ATP6V0d1-Mediated Lysosomal Degradation
Authors: Luo Haixia , Feng Tingting , Xu Zhaokun
Published: October 2023

Rhodococcus equiis a gram-positive actinomycetales bacterial, which cause a pneumonia in foals and in immunocompromised humans. Virulence associated protein A (VapA) encoded from virulence plasmid is essential for intracellular proliferation in macrophage. It has reported that VapA participates in exclusion of proton-pumping vacuolar-ATPase complex from phagosome and causes membrane permeabilization, thus contributing to a pH-neutral phagosome lumen. However, there have been no reports about VapA-induced autophagy or its mechanism. In this study, we sought to determine the role of VapA in macrophage autophagy using western blotting, immunofluorescence, pull-down, Co-IP, LS/MS, pH detection LysoTracker and CFU analysis. We show that VapA inhibiting the macrophage autophagy by detecting the expression of autophagy related protein LC3II and P62 and autophagy flux in VapA treated macrophage. Furthermore, we using pull-down and MS analysis to selected ATP6V0D1 could interact with VapA, Co-IP was used to confirm its interaction. Furthermore, VapA treatment in ATP6V0D1 overexpressed cells weaken the lyso Tracker red stain comparing with ATP6V0D1 overexpressed J774A.1 cells. In addition, the expression of ATP6V0D1 significantly increased in J774A.1 post infected with vapA deletion strain,R. equi 103+/ΔVapA by comparing with wild typeR. equi 103+post-infection. And raise of raise of ATP6V0D1 actually reduceR. equi 103+intracellular multiplication. These results further suggesting a decrease of ATP6V0D1 were caused the exit of VapA inR. equi. Taken those date together, we reported that VapA mediated lysosome acidification by inhibiting the expression of ATP6V0D1, which contributing theR. equiescape macrophage autophagy.
Kinetics and functional consequences of BK Channels activation by N-type Ca2+channels in the dendrite of mouse neocortical layer-5 pyramidal neurons
Authors: Blömer Laila Ananda , Giacalone Elisabetta , Abbas Fatima , Filipis Luiza , Tegolo Domenico , Migliore Michele , Canepari Marco
Published: October 2023

The back-propagation of an action potential (AP) from the axon/soma to the dendrites plays a central role in dendritic integration. This process involves an intricate orchestration of various ion channels, but a comprehensive understanding of the contribution of each channel type remains elusive. In this study, we leverage ultrafast membrane potential recordings (Vm) and Ca2+imaging techniques to shed light on the involvement of N-type voltage-gated Ca2+channels (VGCCs) in layer-5 neocortical pyramidal neurons’ apical dendrites. We found a selective interaction between N-type VGCCs and large-conductance Ca2+-activated K+ channels (BK CAKCs). Remarkably, we observe that BK CAKCs are activated within a mere 500 µs after the AP peak, preceding the peak of the Ca2+current triggered by the AP. Consequently, when N-type VGCCs are inhibited, the early broadening of the AP shape amplifies the activity of other VGCCs, leading to an augmented total Ca2+influx. A NEURON model, constructed to replicate and support these experimental results, reveals the critical coupling between N-type and BK channels. This study not only redefines the conventional role of N-type VGCCs as primarily involved in presynaptic neurotransmitter release but also establishes their distinct and essential function as activators of BK CAKCs in neuronal dendrites. Furthermore, our results provide original functional validation of a physical interaction between Ca2+and K+channels, elucidated through ultrafast kinetic reconstruction. This insight enhances our understanding of the intricate mechanisms governing neuronal signaling and may have far-reaching implications in the field.
Selected Laboratory Equipment and Kitchen Utensils as an Alternative Sterilization Method for Sterilizing Plant Tissue Culture Media
Authors: Pamplona Reniel S. , Dela Cruz Christopher DV , Tayangona Maria Angie
Published: October 2023

Plant Tissue Culture (PTC) is defined as a technique in culturing different plant partsin vitrounder sterile conditions, and supplemented with optimum nutrients. Due to COVID-19 pandemic which forced everyone to isolate and lock up themselves inside their respective homes, this PTC, which is a heavily laboratory-dependent activity of the students, professors, researchers, and other PTC enthusiasts, was halted. As a response to continuing the PTC remotely, the alternative options for sterilizing PTC media using inexpensive and commercially available laboratory equipment (UV ray and microwave) and kitchen utensils (steamer and casserole) were explored in this study. The commercially available 30mL hinge sauce cup was selected as anin vitromedia container. The addition of the autoclavable plastic or ziplock significantly reduced the deformity of the containers, and contamination rate of the media. Among the laboratory set-up, the two-minute exposure of PTC media to the microwave produced almost the same sterile media in the autoclave method (control). On the other hand, both boiling, and steaming methods had no significant difference compared with the control. Among all the treatments, the steaming method for 20 min had maintained sterile cultures for 3 weeks, and consistent pH like in the control, making it highly recommended for sterilizing PTC media at remote places, particularly at home. Thus, the alternative sterilization protocol of PTC media has been established through this study.
Characterizing Treatment Non-responders vs. Responders in Completed Alzheimer’s Disease Clinical Trials
Authors: Wang Dulin , Ling Yaobin , Harris Kristofer , Schulz Paul E. , Jiang Xiaoqian , Kim Yejin
Published: October 2023

Alzheimer’s disease (AD) patients have varying responses to AD drugs and there may be no single treatment for all AD patients. Trial after trial shows that identifying non-responsive and responsive subgroups and their corresponding moderators will provide better insights into subject selection and interpretation in future clinical trials. We aim to extensively investigate pre-treatment features that moderate treatment effect of Galantamine, Bapineuzumab, and Semagacestat from completed trial data. We obtained individual-level patient data from ten randomized clinical trials. Six Galantamine trials and two Bapineuzumab trials were from Yale University Open Data Access Project and two Semagacestat trials were from the Center for Global Clinical Research Data. We included a total of 10,948 subjects. The trials were conducted worldwide from 2001 to 2012. We estimated treatment effect using causal forest modeling on each trial. Finally, we identified important pre-treatment features that determine treatment efficacy and identified responsive or nonresponsive subgroups. As a result, patient’s pre-treatment conditions that determined the treatment efficacy of Galantamine differed by dementia stages, but we consistently observed that non-responders in Galantamine trials had lower BMI (25 vs 28,P< .001) and increased ages (74 vs 68,P< .001). Responders in Bapineuzumab and Semagacestat trials had lower Aβ42levels (6.41 vs 6.53 pg/ml,P< .001) and smaller whole brain volumes (983.13 vs 1052.78 ml,P< .001). 6 ‘positive’ treatment trials had subsets of patients who had, in fact, not responded. 4 “negative” treatment trials had subsets of patients who had, in fact, responded. This study suggests that analyzing heterogeneity in treatment effects in “positive” or “negative” trials may be a very powerful tool for identifying distinct subgroups that are responsive to treatments, which may significantly benefit future clinical trial design and interpretation.
ProA and ProB repeat sequences shape genome organization, and enhancers open domains
Authors: Bonnet Konstantinn Acen , Hulo Nicolas , Mourad Raphaël , Ewing Adam , Croce Olivier , Naville Magali , Vassetzky Nikita , Gilson Eric , Picard Didier , Fourel Geneviève
Published: October 2023

There is a growing awareness that repeat sequences (RepSeq) - the main constituents of the human genome - are also prime players in its organization. Here we propose that the genome should be envisioned as a supersystem with three main subsystems, each composed of functionally redundant, cooperating elements. We define herein ProA and ProB RepSeqs as sequences that promote either the A/euchromatin or the B/heterochromatin compartment. ProA and ProB RepSeqs shape A/B partitioning, such that the relative proportions of ProA and ProB RepSeqs determine the propensity of a chromosome segment to adopt either an A or a B configuration. In human, core ProA RepSeqs are essentially made of Alu elements, whereas core ProB RepSeqs consist of young L1 and some Endogenous Retroviruses (ERVs) as well as a panel of AT-rich microsatellites and pericentromeric and telomeric satellites. Additionally, RepSeqs with more indefinite character and, importantly, their derivatives known as “transcriptional enhancers”, can shift between ProA and ProB functions and thus act to open or close specific chromatin domains depending on the cellular context. In this framework, genes and their promoters appear as a special class of RepSeqs that, in their active, transcribed state, reinforce the openness of their surroundings. Molecular mechanisms involve cooperativity between ProB elements, presumably underpinned by the condensate-like properties of heterochromatin, which ProA elements oppose in several ways. We provide strong arguments that altered CpG methylation patterns in cancer including a marked loss in the B compartment, result primarily from a global imbalance in the process of CpG methylation and its erasure. Our results suggest that the resulting altered methylation and impaired function of ProB RepSeqs globally weaken the B compartment, rendering it more plastic, which in turn may confer fate plasticity to the cancer cell.
Calcitriol treatment is safe and increases frataxin levels in Friedreich Ataxia patients
Authors: Alemany Perna Berta , Tamarit Jordi , López Domínguez Daniel , Quiroga-Varela Anna , Merchan Ruiz Miguel , Ramió i Torrentà Lluís , Genís David , Ros Joaquim
Published: October 2023

Background

Calcitriol, the active form of vitamin D (also known as 1,25-dihydroxycholecalciferol), improves the phenotype and increases frataxin levels in cell models of Friedreich Ataxia (FRDA).

Methods

Based on these results, we started a pilot clinical trial in which a dose of 0.25mcg/24h was administered to 15 FRDA patients for a year. Evaluations of neurological function changes (SARA scale, 9-HPT, 8-MWT, PATA test) and quality of life (Barthel Scale and SF-36 quality of life questionnaire) were performed. Frataxin amounts were measured in isolated platelets obtained from these FRDA patients, from heterozygous FRDA carriers (relatives of the FA patients) and from non-heterozygous sex and age matched controls.

Results

Although the patients did not experience any observable neurological improvement, there was a statistically significant increase in frataxin levels from initial values, 5,6 pg/μg, to 7,0 pg/μg after 12 months. Differences in frataxin levels referred to total protein amounts were observed amongst sex and age matched controls (18.11 pg/μg), relative controls (10.07 pg/μg), and FRDA patients (5.71 pg/μg). The treatment was well tolerated by most patients, and only some of them experienced minor adverse effects at the beginning of the trial.

Conclusion

Calcitriol dosage used (0.25mcg/24h) is safe for FRDA patients and it increases frataxin levels. We cannot rule out that higher doses administered longer could yield neurological benefits.
Post-pandemic memory T-cell response to SARS-CoV-2 is durable, broadly targeted and cross-reactive to hypermutated BA.2.86
Authors: Nesamari Rofhiwa , Omondi Millicent A. , Höft Maxine A. , Ngomti Amkele , Baguma Richard , Nkayi Anathi A. , Besethi Asiphe S. , Magugu Siyabulela F. J. , Mosala Paballo , Walters Avril , Clark Gesina M. , Mennen Mathilda , Skelem Sango , Adriaanse Marguerite , Grifoni Alba , Sette Alessandro , Keeton Roanne S. , Ntusi Ntobeko A.B. , Riou Catherine , Burgers Wendy A.
Published: October 2023

The COVID-19 post-pandemic period is characterised by infection waves of uncertain size (due to low rates of SARS-CoV-2 testing and notification), as well as limited uptake or global access to updated variant vaccines. Ongoing SARS-CoV-2 evolution has given rise to recombinant Omicron lineages that dominate globally (XBB.1), as well as the emergence of hypermutated variants (BA.2.86). In this context, durable and cross-reactive T-cell immune memory is critical for continued protection against severe COVID-19. We examined T-cell responses to SARS-CoV-2 approximately 1.5 years since Omicron first emerged. We describe sustained CD4+ and CD8+ spike-specific T-cell memory responses in healthcare workers in South Africa (n=39), most of whom had received 2 doses of Ad26.CoV2.S (Johnson & Johnson/Janssen) vaccine and experienced at least one SARS-CoV-2 infection. Spike-specific T cells were highly cross-reactive with all Omicron variants tested, including BA.2.86. Abundant non-spike (nucleocapsid and membrane)-specific T cells were detectable in most participants, augmenting the total T-cell resources available for protection. The bulk of SARS-CoV-2-specific T-cell responses had an early-differentiated phenotype, explaining their persistent nature. Thus, hybrid immunity leads to the accumulation of spike and non-spike T cells evident 3.5 years after the start of the pandemic, with preserved recognition of highly mutated SARS-CoV-2 variants. Long-term T-cell immune memory is likely to provide continued protection against severe outcomes of COVID-19.

In Brief

Nesamariet al.investigate T-cell responses in the context of hybrid immunity 3.5 years after the start of the COVID-19 pandemic. They show that T-cell memory is highly durable and cross-reactive with recombinant variants XBB.1 and hypermutated BA.2.86. Abundant non-spike responses augment the overall T-cell response.
White matter hyperintensities modify relationships between corticospinal tract damage and motor outcomes after stroke
Authors: Ferris Jennifer K. , Lo Bethany P. , Barisano Giuseppe , Brodtmann Amy , Buetefisch Cathrin M. , Conforto Adriana B. , Donnelly Miranda H. , Egorova-Brumley Natalia , Hayward Kathryn S. , Khlif Mohamed Salah , Revill Kate P. , Zavaliangos-Petropulu Artemis , Boyd Lara A. , Liew Sook-Lei
Published: October 2023

Motor outcomes after stroke relate to corticospinal tract (CST) damage. Concurrent damage from white matter hyperintensities (WMHs) might impact neurological capacity for recovery after CST injury. Here, we evaluated if WMHs modulate the relationship between CST damage and post-stroke motor impairment outcome.

We included 223 individuals from the ENIGMA Stroke Recovery Working Group. CST damage was indexed with weighted CST lesion load (CST-LL). Mixed effects beta-regression models were fit to test the impact of CST-LL, WMH volume, and their interaction on motor impairment.

WMH volume related to motor impairment above and beyond CST-LL (β = 0.178, p = 0.022). We tested if relationships varied by WMH severity (mild vs. moderate-severe). In individuals with mild WMHs, motor impairment related to CST-LL (β = 0.888, p < 0.001) with a CST-LL x WMH interaction (β = -0.211, 0.026). In individuals with moderate-severe WMHs, motor impairment related to WMH volume (β = 0.299, p = 0.044), but did not significantly relate to CST-LL or a CST-LL x WMH interaction.

WMH-related damage may be under-recognised in stroke research as a factor contributing to variability in motor outcomes. Our findings emphasize the importance of brain structural reserve in motor outcomes after brain injury.
Comparative Analysis of Machine Learning Models for Efficient Low Back Pain Prediction Using Demographic and Lifestyle Factors
Authors: Kim Jun-hee
Published: October 2023

Background

Low back pain (LBP) is one of the most frequently occurring musculoskeletal disorders, and factors such as lifestyle as well as individual characteristics are associated with LBP. The purpose of this study was to develop and compare efficient low back pain prediction models using easily obtainable demographic and lifestyle factors.

Methods

Data from adult men and women aged 50 years or older collected from the Korean National Health and Nutrition Examination Survey (KNHANES) were used. The dataset included 22 predictor variables, including demographic, physical activity, occupational, and lifestyle factors. Four machine learning algorithms, including XGBoost, LGBM, CatBoost, and RandomForest, were used to develop predictive models.

Results

All models achieved an accuracy greater than 0.8, with the LGBM model outperforming the others with an accuracy of 0.830. The CatBoost model had the highest sensitivity (0.804), while the LGBM model showed the highest specificity (0.884) and F1-Score (0.821). Feature importance analysis revealed that EQ-5D was the most critical variable across all models.

Conclusion

In this study, an efficient LBP prediction model was developed using easily accessible variables. Using this model, it may be helpful to identify the risk of LBP in advance or establish prevention strategies in subjects who have difficulty accessing medical facilities.
Protein language models-assisted engineering of Uracil-N glycosylase enables programmable T-to-G and T-to-C base editing
Authors: He Yan , Zhou Xibin , Chang Chong , Chen Ge , Liu Weikuan , Li Geng , Fan Xiaoqi , Ma Yunqing , Yuan Fajie , Chang Xing
Published: October 2023

Current base editors use DNA deamination enzymes, such as cytidine deaminase (CBE) or adenine deaminase (ABE), to facilitate transition nucleotide substitutions. Combining CBE or ABE with glycosylase enzymes, including CGBE and AYBE, can induce limited transversion mutations. Nonetheless, a critical demand remains for base editors capable of generating alternative mutation types, such as T>G corrections, which could address over 17% of monogenic SNVs responsible for human genetic diseases. In this study, we leveraged protein language models to engineer a uracil-N-glycosylase (UNG) variant with altered substrate specificities to thymines (eTDG). Notably, after only two rounds of testing fewer than 50 predicted variants, more than 50% exhibited a 1.5-11-fold enhancement in enzymatic activities, a success rate much greater than random mutagenesis. When eTDG was fused with Cas9 nickase without deaminases, it effectively induced programmable T to G or T to C substitutions and precisely corrected db/db diabetic mutation in mice (up to 55%). Our findings not only establish orthogonal strategies for developing novel base editors, but also demonstrate the capacities of protein language models for optimizing enzymes without extensive task-specific training data or laborious experimental procedures.
Impairment of hippocampal astrocyte-mediated striatal dopamine release and locomotion in Alzheimer’s disease
Authors: Tournier Benjamin B. , Ceyzériat Kelly , Badina Aurélien M. , Gloria Yessica , Fall Aïda , Amossé Quentin , Tsartsalis Stergios , Millet Philippe
Published: October 2023

Clinical and translational research has identified deficits in the dopaminergic neurotransmission in the striatum in Alzheimer’s disease (AD) and this could be related to the pathophysiology of psychiatric symptoms appearing even at early stages of the pathology. We hypothesized that AD pathology in the hippocampus may influence dopaminergic neurotransmission even in the absence of AD-related lesion in the mesostriatal circuit. We thus chemogenetically manipulated the activity of hippocampal neurons and astrocytes in wild-type and hemizygous TgF344-AD (Tg) rats, an animal model of AD pathology. We assessed the brain-wide functional output of this manipulation usingin vivoSingle Photon Emission Computed Tomography to measure cerebral blood flow and D2/3receptor binding. We also assessed the effects of the chemogenetic manipulations on astrocytic and microglial capacity to surround and phagocytize Aβ both locally and in the striatum. Our results show that acute and chronic neuronal and astrocytic stimulation induces widespread effects on the brain regional activation pattern, notably with an inhibition of striatal activation. In the TgF344-AD rats, both these effects were blunted. Chemogenetic stimulation in the hippocampus increased microglial density and its capacity to limit AD pathology, whereas these effects were absent in the striatum perhaps as a consequence of the altered connectivity between the hippocampus and the striatum. Our work suggests that hippocampal AD pathology may alter mesostriatal signalling and induce widespread alterations of brain activity. Neuronal and astrocytic activation may induce a protective, Aβ-limiting phenotype of microglia, which surrounds Aβ plaques and limits Αβ concentration more efficiently.