bluuebunny/crossref_metadata_2025_split huggingface dataset:
Uncertainty-Aware Traction Force Microscopy
Authors: Kandasamy Adithan , Yeh Yi-Ting , Serrano Ricardo , Mercola Mark , del Álamo Juan C. 
Published: July 2024

AbstractTraction Force Microscopy (TFM) is a versatile tool to quantify cell-exerted forces by imaging and tracking fiduciary markers embedded in elastic substrates. The computations involved in TFM are ill-conditioned, and data smoothing or regularization is required to avoid overfitting the noise in the tracked substrate displacements. Most TFM calculations depend critically on the heuristic selection of regularization (hyper)parameters affecting the balance between overfitting and smoothing. However, TFM methods rarely estimate or account for measurement errors in substrate deformation to adjust the regularization level accordingly. Moreover, there is a lack of tools to quantify how these errors propagate to the recovered traction stresses. These limitations make it difficult to interpret TFM readouts and hinder comparing different experiments. This manuscript presents an uncertainty-aware TFM technique that estimates the variability in the magnitude and direction of the traction stress vector recovered at each point in space and time of each experiment. In this technique, substrate deformation and its uncertainty are quantified using a non-parametric bootstrap PIV method by resampling the microscopy image pixels (PIV-UQ). This information is passed to a hierarchical Bayesian framework that automatically selects its hyperparameters to perform spatially adaptive regularization conditioned on image quality and propagates the uncertainty to the traction stress readouts (TFM-UQ). We validate the performance of PIV-UQ and TFM-UQ using synthetic datasets with prescribed image quality variations and demonstrate the application of PIV-UQ and TFM-UQ to experimental datasets. These studies show that TFM-UQ locally adapts the level of smoothing, outperforming traditional regularization methods. They also illustrate how uncertainty-aware TFM tools can be used to objectively choose key image analysis parameters like PIV-UQ interrogation window size. We anticipate that these tools will allow for decoupling biological heterogeneity from measurement variability and facilitate automating the analysis of large datasets by parameter-free, input data-based regularization.
scTail: precise polyadenylation site detection and its alternative usage analysis from reads 1 preserved 3’ scRNA-seq data
Authors: Hou Ruiyan , Huang Yuanhua 
Published: July 2024

AbstractThree-prime single-cell RNA-seq (scRNA-seq) has been widely employed to dissect the variability of cellular transcriptomes, while only the cDNAs on reads 2 are routinely used, including to analyze polyadenylation sites (PAS). However, despite of high sequencing noise, we found the cDNAs on reads 1 are highly informative in precisely detecting PAS. Here, we further develop a computational method, scTail, to identify PAS using reads 1 and quantify its expression leveraging reads 2, which enables effective detection of alternative PAS usage (PAU). When compared with other methods, scTail detects PAS more sensitively and precisely. With various experimental data sets, we demonstrated that the combination usage of scTail and BRIE2 can discover differential alternative PAS usage in various biological processes including cell types in human intestinal, disease status of esophageal squamous cell carcinoma, and time point of mouse forelimb histogenesis, revealing critical insights in PAS regulations.
Cell segmentation without annotation by unsupervised domain adaptation based on cooperative self-learning
Authors: Miyaki Shintaro , Nishimoto Shori , Tokuoka Yuta , Yamada Takahiro G , Morikura Takashi , Funahashi Akira 
Published: July 2024

AbstractCell segmentation, which extracts cells from microscopic images, is essential for quantitative evaluation of cell morphology. Recently, supervised deep-learning-based models have been shown to achieve highly accurate segmentation. However, the performance of these supervised models is often degraded when the models infer unknown cell types that are not included in the train dataset. One approach to overcoming the performance degradation is acquiring new annotated data for each cell type. However, constructing datasets for all cell types is not feasible because labeling every single pixel, rather than each image, is required in the segmentation task. Learning methods that can achieve highly accurate segmentation without annotation is strongly required.Here, we developed a cell segmentation method based on unsupervised domain adaptation with cooperative self-learning (CULPICO: Cooperative Unsupervised Learning for PIxel-wise COloring). The proposed method consists of two independent segmentation models and a mutual exchange mechanism of inference data. For the data with labels, the models are trained through supervised learning. For the data without labels, the models infer a label probability at each pixel and generate a pseudo-label as unsupervised learning. The pseudo-labels created by each model are mutually used as ground-truth in the other model. Loss function is corrected by considering pixel-level discrepancies between the label probabilities inferred by the two models. The proposed method, despite being an unsupervised learning method, can segment the unknown cell types without labels with an accuracy comparable to supervised learning models. Our method, which could solve the performance degradation problem without constructing new datasets, is expected to accelerate life science by reducing the cost of extracting quantitative biological knowledge.
Exercise and disease state influence the beneficial effects of Fn14-depletion on survival and muscle pathology in theSOD1G93Aamyotrophic lateral sclerosis (ALS) mouse model
Authors: Hazell Gareth , Ahlskog Nina , Sutton Emma R , Okoh Magnus , Hoolachan Joseph M , Scaife Taylor , Iqbal Sara , McCallion Eve , Bhomra Amarjit , Kordala Anna J , Scamps Frederique , Raoul Cedric , Wood Matthew JA , Bowerman Melissa 
Published: July 2024

ABSTRACTBackgroundAmyotrophic lateral sclerosis (ALS) is a devastating and incurable neurodegenerative disease. Accumulating evidence strongly suggests that intrinsic muscle defects exist and contribute to disease progression, including imbalances in whole-body metabolic homeostasis. We have previously reported that tumour necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) and fibroblast growth factor inducible 14 (Fn14) are significantly upregulated in skeletal muscle of theSOD1G93AALS mouse model. While antagonising TWEAK did not impact survival, we did observe positive effects in skeletal muscle. Given that Fn14 has been proposed as the main effector of the TWEAK/Fn14 activity and that Fn14 can act independently from TWEAK in muscle, we suggest that manipulating Fn14 instead of TWEAK in theSOD1G93AALS mice could lead to differential and potentially improved benefits.MethodsWe thus investigated the contribution of Fn14 to disease phenotypes in theSOD1G93AALS mice. To do so, Fn14 knockout mice (Fn14-/-) were crossed onto theSOD1G93Abackground to generateSOD1G93A;Fn14-/-mice. Investigations were performed on both unexercised and exercised (rotarod and/or grid test) animals (wild type (WT),Fn14-/-,SOD1G93AandSOD1G93A;Fn14-/-).ResultsHere, we firstly confirm that the TWEAK/Fn14 pathway is dysregulated in skeletal muscle ofSOD1G93Amice. We then show that Fn14-depletedSOD1G93Amice display an increased lifespan and decreased muscle pathology, without an impact on motor function, and that this is dependent on exposure to exercise. Indeed, we observe that endurance (rotarod) and resistance (grid test) exercises influence the positive effects of Fn14 deletion on survival and muscle phenotypes inSOD1G93Amice, which may be further influenced by genotype and disease state.ConclusionsOur study provides further insights on the different roles of the TWEAK/Fn14 pathway in pathological skeletal muscle and how they can be influenced by age, disease and metabolic state. This is particularly relevant in the ALS field, where combinatorial therapies that include exercise regimens are currently being explored. As such, a better understanding and consideration of the interactions between treatments, muscle metabolism and exercise will be of importance in future studies.
Potato cultivars use different root physiological and molecular mechanisms to acclimate to salt stress
Authors: Nicolas Michael , Bouma Jort , Venema Jan Henk , van der Schoot Hanneke , Verstappen Francel , de Zeeuw Thijs , Langedijk Sanne E. , Boer Damian , Bucher Johan , Staal Marten , Krom Ben , Elzenga J. Theo M. , Visser Richard G.F. , Testerink Christa , Karlova Rumyana 
Published: July 2024

SummarySoil salinity induces osmotic stress and ion toxicity in plants, detrimentally affecting their growth and development. Potato (Solanum tuberosum) faces yield reductions due to salt stress. The mechanisms of salt stress resilience, especially in adventitious roots, remain unknown.We investigated the resilience of three potato cultivars - Desirée, Innovator, and Mozart - by studying their physiological and transcriptomic responses to salt stress.Our findings reveal that under salt stress, the growth of stolons and stolon node roots is similarly reduced unlike tubers, even though they are physically connected. Surprisingly, tubers accumulate Cl-but not Na+under salt stress, suggesting an active Na+exclusion mechanism. Innovator showed the lowest suberin and lignin deposition before salt stress and higher K+leakage, leading to a stronger initial stress response with high ABA content and a distinct transcriptomic pattern. Nevertheless, Innovator was the most resilient, displaying lower growth, salt-tolerance index and tuber yield reduction. Transcriptomic analysis revealed several K+/Na+channel genes which might regulate ions homeostasis during salt stress, in particular in Innovator.Altogether, we conclude that acclimation ability, rather than initial protection of roots against salt, prevails in long term salt-stress resilience of potato.
Structural insights into thein situassembly of clustered protocadherin γB4
Authors: Zhang Ze , Chen Fabao , Zhang Zihan , Guo Luqiang , Feng Tingting , Fang Zhen , Xin Lihui , Yu Yang , Hu Hongyu , He Yongning 
Published: July 2024

AbstractClustered protocadherins (cPcdhs) belong to the cadherin superfamily and play important roles in neural development. cPcdhs can mediate homophilic adhesion and lead to self-avoidance and tiling by giving neurons specific identities in vertebrates. Structures and functions of cPcdhs have been studied extensively in the past decades, but the mechanisms behind the functions have not been fully understood. Here we investigate thein situassembly of cPcdh-γB4, a member in the γ subfamily of cPcdhs, by electron tomography and find that the full length cPcdh-γB4 does not show regular organization at the adhesion interfaces. By contrast, cPcdh-γB4 lacking the intracellular domain can generate an ordered zigzag pattern between cells and thecisinteracting mode is different from the crystal packing of the ectodomain. We also identify the residues on the ectodomain that might be important for the zigzag pattern formation by mutagenesis. Furthermore, truncation mutants of the intracellular domain of cPcdh-γB4 reveal different assembly patterns between cell membranes, suggesting that the intracellular domain plays a crucial role in the intermembrane organization of cPcdh-γB4. Taken together, these results suggest both ectodomain and intracellular domain regulate thein situassembly of cPcdh-γB4 at the adhesion interfaces, thereby providing mechanistic insights into the functional roles of cPcdhs during neuronal wiring.
Household level insecticide deployments (micro-mosaics) for insecticide resistance management: Evaluating deliberate and accidental deployments
Authors: Hobbs Neil Philip , Hastings Ian Michael 
Published: July 2024

AbstractMixtures of two insecticides in a single formulation at full-dose are frequently evaluated as the “best” insecticide resistance (IRM) strategy in public health. However, this requires both insecticides to be mixed together in a single formulation which may not be possible or practical. Deploying different insecticides in different households (“micro-mosaics”) may allow for mosquitoes to encounter different insecticides in subsequent gonotrophic cycles obtaining a “temporal mixture”. We evaluate micro-mosaics considering their deliberate use and their accidental use using a mathematical model assuming polygenic resistance. Deliberate micro-mosaics are evaluated against rotations and mixtures (full-dose or half-dose) over a range of scenarios allowing for cross resistance and insecticide decay on their ability to slow the development of resistance. Accidental micro-mosaics are evaluated to understand the implication of mixture insecticide-treated nets (ITNs) and standard (pyrethroid only) ITNs being deployed alongside one another on the development of resistance across a range of initial resistance scenarios. Deliberate micro-mosaics are found to not differ substantially in their IRM capability from either rotations or half-dose mixtures. When micro-mosaics do outperform rotations or half-dose mixtures the benefit is often small. Micro-mosaics are found to perform worse than full-dose mixtures. Accidental micro-mosaics are found to reduce the ability of mixtures to slow the development of resistance. The deployment of deliberate micro-mosaics was found to not be beneficial versus rotations or mixtures indicating this strategy should not be pursued. Micro-mosaics occurring accidentally due to multiple distribution channels inhibits the effectiveness of mixture ITNs in slowing the development of resistance. Where mixture ITNs are used keep the coverage of the mixture high relative to standard (pyrethroid-only) ITNs is key.
Advancing Thalamic Nuclei Segmentation: The Impact of Compressed Sensing and FastSurfer on MRI Processing
Authors: Hübner Sebastian , Tambalo Stefano , Novello Lisa , Hilbert Tom , Kober Tobias , Jovicich Jorge 
Published: July 2024

AbstractThe thalamus is a collection of gray matter nuclei that play a crucial role in sensorimotor processing and modulation of cortical activity. Characterizing thalamic nuclei non-invasively with structural MRI is particularly relevant for patient populations with Parkinson’s disease, epilepsy, dementia, and schizophrenia. However, severe head motion in these populations poses a significant challenge for in vivo mapping of thalamic nuclei. Recent advancements have leveraged the compressed sensing (CS) framework to accelerate structural MRI acquisition times in MPRAGE sequence variants, while fast segmentation tools like FastSurfer have reduced processing times in neuroimaging research.In this study, we evaluated thalamic nuclei segmentations derived from six different MPRAGE variants with varying degrees of CS acceleration (from about 9 to about 1 minute acquisitions), using both FreeSurfer and FastSurfer for segmentation. Our findings show minimal sequence effects with no systematic bias, and low volume variability across sequences for the whole thalamus and major thalamic nuclei. Notably, CS-accelerated sequences produced less variable volumes compared to non-CS sequences. Additionally, segmentations of thalamic nuclei by FreeSurfer and FastSurfer were highly comparable.We provide first evidence supporting that a good segmentation quality of thalamic nuclei with compressed sensing T1-weighted image acceleration in a clinical 3T MRI system is possible. Our findings encourage future applications of fast T1-weighted MRI to study deep gray matter. CS-accelerated sequences and rapid segmentation methods are promising tools for future studies aiming to characterize thalamic nuclei in vivo at 3T in both healthy individuals and clinical populations.
Sleep and circadian rhythm activity alterations during adolescence in a mouse model of neonatal fentanyl withdrawal syndrome
Authors: Williams Benjamin R. , Gamble Mackenzie C. , Singh Navsharan , Bryant Camron D. , Logan Beth A. , Logan Ryan W. 
Published: July 2024

ABSTRACTPurposeFentanyl, a highly potent synthetic opioid, is a major contributor to the ongoing opioid epidemic. During adulthood, fentanyl is known to induce pronounced sleep and circadian disturbances during use and withdrawal. Children exposed to opioidsin uteroare likely to develop neonatal opioid withdrawal syndrome, and display sleep disturbances after birth. However, it is currently unknown how neonatal opioid withdrawal from fentanyl impacts sleep and circadian rhythms in mice later in life.MethodsTo model neonatal opioid withdrawal syndrome, mice were treated with fentanyl from postnatal days 1 through 14, analogous to the third trimester of human gestation. After weaning, fentanyl and saline treated mice underwent non-invasive sleep and circadian rhythm monitoring during adolescence postnatal days 23 through 30.ResultsNeonatal fentanyl exposure led to reduced duration of wake and a decrease in the number of bouts of non-rapid eye movement sleep. Further, neonatally exposed mice displayed an increase in the average duration of rapid eye movement sleep bouts, reflecting an overall increase in the percent time spent in rapid eye movement sleep across days.ConclusionsNeonatal fentanyl exposure leads to altered sleep-wake states during adolescence in mice.
Exploring The Association of Student Perceptions of Their Teachers’ Science Instruction and Emotional Engagement and The Variance between Grade Level
Authors: Xia Xin , Tai Robert H. 
Published: July 2024

AbstractPrevious research has consistently shown students have higher learning interests attitudes, and motivation toward science in elementary compared to middle and high school. However, the key predictors behind the observed differences in engagement levels across grade levels remain unclear. This study aims to identify the association between students’ perceptions of science instruction and their emotional engagement, as well as examine the differences across various educational stages. A multilevel random effect model was employed to investigate this association. In addition, the analysis examined whether the associations vary between grade levels. A sample of 6465 students from 25 schools participated in the study.This study shows that students in higher grades have significantly lower emotional engagement compared to third-grade students. Similarly, students in higher grades have significantly lower values on perceptions of science instruction of interesting science and understandable science decrease compared to third grade. Findings reveal significant associations between students’ perceptions of science instruction, both in perceiving interesting science instruction and understandable science instruction, and their emotional engagement in science learning. The interaction term (Perception of Interesting Science Instruction × Grade) of Grades four, six through eight, and grade 12 are statistically significantly related to emotional engagement, indicating that more positive slopes correspond to high-grade level than third-grade students. The increase in students’ perception of interesting science has the steepest slope of improvement in students’ emotional engagement in 6thgrade. We find no statistically significant difference between grades in students’ perception of understandable science and emotional engagement.Interesting and understandable science classes have positive correlations with students’ emotional engagement in science learning. For future studies, it is worth exploring science instruction during transition grades to better address and mitigate the observed difference in emotional engagement.
Beta-frequency sensory stimulation enhances gait rhythmicity through strengthened coupling between striatal networks and stepping movement
Authors: Sridhar Sudiksha , Lowet Eric , Gritton Howard J. , Freire Jennifer , Zhou Chengqian , Liang Florence , Han Xue 
Published: July 2024

AbstractStepping movement is delta (1-4 Hz) rhythmic and depends on sensory inputs. In addition to delta rhythms, beta (10-30 Hz) frequency dynamics are also prominent in the motor circuits and are coupled to neuronal delta rhythms both at the network and the cellular levels. Since beta rhythms are broadly supported by cortical and subcortical sensorimotor circuits, we explore how beta-frequency sensory stimulation influences delta-rhythmic stepping movement, and dorsal striatal circuit regulation of stepping. We delivered audiovisual stimulation at 10 Hz or 145 Hz to mice voluntarily locomoting, while simultaneously recording stepping movement, striatal cellular calcium dynamics and local field potentials (LFPs). We found that 10 Hz, but not 145 Hz stimulation prominently entrained striatal LFPs. Even though sensory stimulation at both frequencies promoted locomotion and desynchronized striatal network, only 10 Hz stimulation enhanced the delta rhythmicity of stepping movement and strengthened the coupling between stepping and striatal LFP delta and beta oscillations. These results demonstrate that higher frequency sensory stimulation can modulate lower frequency dorsal striatal neural dynamics and improve stepping rhythmicity, highlighting the translational potential of non-invasive beta-frequency sensory stimulation for improving gait.
Coordination of transcription-coupled repair and repair-independent release of stalled RNA polymerase II in response to transcription-blocking lesions
Authors: Zhu Yongchang , Zhang Xiping , Gao Meng , Huang Yanchao , Tan Yuanqing , Parnas Avital , Wu Sizhong , Zhan Delin , Adar Sheera , Hu Jinchuan 
Published: July 2024

ABSTRACTTranscription-blocking lesions (TBLs) stall elongating RNA polymerase II (PolII), which then initiates transcription-coupled repair (TCR) to remove TBLs and allow transcription recovery. In the absence of TCR, eviction of lesion-stalled PolII is required for alternative pathways to address the damage, but the mechanism is unclear. This study, utilizing Protein-Associated DNA Damage Sequencing (PADD-seq), reveals that the p97-proteasome pathway can evict lesion-stalled PolII independently of repair. Both TCR and repair-independent eviction require CSA and ubiquitination. However, p97 is dispensable for TCR and PolII eviction in TCR-proficient cells, highlighting repair’s prioritization over repair-independent eviction. Moreover, ubiquitination of RPB1-K1268 is important for both pathways, with USP7’s deubiquitinase activity promoting TCR without abolishing repair-independent PolII release. In summary, this study elucidates the fate of lesion-stalled PolII, and may shed light on the molecular basis of genetic diseases caused by the defects of TCR genes.