bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the effect of mechanical adaptation on mid-air ultrasound vibrotactile stimuli
Authors: Cataldo Antonio , Huang Tianhui , Frier William , Haggard Patrick 
Published: December 2024

ABSTRACTGesture control systems based on mid-air haptics are increasingly used in infotainment systems in cars, where they can provide rich haptic feedback to improve human-computer interactions. Laboratory studies show that mid-air haptic feedback reduces drivers’ distractions and improve safety. However, it is unclear how the perception of mid-air ultrasound stimuli is affected by prolonged exposure to vibrational noise, e.g., from the steering wheel of a moving vehicle. Studies on vibrotactile adaptation show that perception of mechanical vibration is impaired by prior exposure to stimuli of the same frequency. Here, we investigated the effect of mechanical adaptation on the perception of mid-air ultrasound stimuli. We measured participants’ detection threshold for ultrasound stimuli of different frequencies both before and after exposure to 30 s mechanical vibrations. Across two experiments, we systematically manipulated the frequency and amplitude of the adapting stimulus. We found that exposure to low-frequency mechanical vibrations significantly impaired the detection of low-frequency ultrasound stimuli. In contrast, exposure to high-frequency mechanical vibrations equally impaired perception of both low- and high-frequency ultrasound stimuli. This effect was mediated by the amplitude of the adapting stimulus, with stronger mechanical vibrations producing a larger increase in participants’ detection threshold. Overall, these findings show that perception of mid-air ultrasound stimuli is affected by specific sources of mechanical noise. Crucially, frequency-specificity in the low-frequency band also points toward possible mitigating solutions that could help minimising unwanted desensitization of mechanoreceptor channels during mid-air haptic interactions.
Multi-Stable Bimodal Perceptual Coding within the Ventral Premotor Cortex
Authors: Andrade-Ortega Bernardo , Díaz Héctor , Bayones Lucas , Alvarez Manuel , Zainos Antonio , Rivera-Yoshida Natsuko , Franci Alessio , Romo Ranulfo , Rossi-Pool Román 
Published: December 2024

AbstractNeurons of the primate ventral premotor cortex (VPC) respond to tactile or acoustic stimuli. But how VPC neurons process and integrate information from these two sensory modalities during perception remains unknown. To investigate this, we recorded the activity of VPC neurons in two trained monkeys performing a bimodal detection task (BDT). In the BDT, subjects reported the presence or absence of a tactile or an acoustic stimulus. Initial single-cell analyses revealed a diverse range of responses during the BDT: purely tactile, purely acoustic, bimodal and others that exhibited sustained activity during the decision maintenance delay—between the stimulus offset and motor report. To further explore the VPC’s role in the BDT, we applied dimensionality reduction techniques to uncover the low-dimensional latent dynamics of the neuronal population and conducted parallel analyses on a recurrent neural network (RNN) model trained on the same task. Neural trajectories associated with tactile responses diverged strongly from those related to acoustic responses. Conversely, during the stimulus-absent trials the neural dynamics remained at rest. During the delay, the trajectories demonstrated a pronounced rotational dynamic toward a subspace orthogonal to the sensory response space, supporting memory maintenance in stable equilibria. This suggests that the network dynamics can sustain distinct stable states corresponding to the three potential task outcomes. Using low-dimensional modeling, we propose a universal dynamical mechanism underlying the transition from sensory to mnemonic processing, consistent with our experimental and computational observations. These findings show that the VPC contains neurons capable of bimodal coding and that its population can integrate competing sensory information and maintain decisions throughout the delay period, regardless of the sensory modality.
Accurate nucleic acid-binding residue identification based on domain-adaptive protein language model and explainable geometric deep learning
Authors: Zeng Wenwu , Pan Liangrui , Ji Boya , Xu Liwen , Peng Shaoliang 
Published: December 2024

ABSTRACTProtein-nucleic acid interactions play a fundamental and critical role in a wide range of life activities. Accurate identification of nucleic acid-binding residues helps to understand the intrinsic mechanisms of the interactions. However, the accuracy and interpretability of existing computational methods for recognizing nucleic acid-binding residues need to be further improved. Here, we propose a novel method called GeSite based the domain adaptive protein language model and explainable E(3)-equivariant graph convolution neural network. Prediction results across multiple benchmark test sets demonstrate that GeSite is superior or comparable to state-of-the-art prediction methods. The performance comparison on low structure similarity and newly released test proteins demonstrates the robustness and generalization of the method. Detailed experimental results suggest that the advanced performance of GeSite lies in the well-designed nucleic acid-binding protein adaptive language model. Meanwhile, interpretability analysis exposes the perception of the prediction model on various remote and close functional domains, which is the source of its discernment. The data and source code of GeSite are freely accessible athttps://github.com/pengsl-lab/GeSite.
A central role for CCR2 in monocyte recruitment and blood-brain barrier disruption during Usutu virus encephalitis
Authors: Slowikowski Emily , Willems Céleste , Lemes Robertha Mariana Rodrigues , Schuermans Sara , Berghmans Nele , Rocha Rebeca Paiva Fróes , Martens Erik , Proost Paul , Delang Leen , Marques Rafael Elias , Filho José Carlos Alves , Marques Pedro Elias 
Published: December 2024

ABSTRACTUsutu virus (USUV) is an emerging neurotropic flavivirus capable of causing encephalitis in humans. Here, our main goal was to characterize the innate immune response in the brain during USUV encephalitis and to identify strategies to control disease severity. Using an immunocompetent mouse model of USUV encephalitis, we showed that microglia activation, blood-brain barrier (BBB) disruption and inflammatory monocyte recruitment are hallmarks of disease 6 days post infection. Activated microglia were in close association to USUV-infected cells, concomitantly with elevated levels of IL-6, IFN-γ, CCL2, CCL5, CXCL10 and CXCL1 in the brain. Monocyte recruitment was CCR2-dependent and driven by IFN-γ and CCL2 production beneath the brain vasculature. Moreover, CCR2 deficiency inhibited microglia activation and BBB disruption, showing the central role of CCR2 in USUV encephalitis. Accordingly, treatment with dexamethasone prevented pro-inflammatory mediator production and reduced leukocyte recruitment significantly, restraining encephalitis severity. Concluding, USUV encephalitis is driven by CCR2-mediated monocyte recruitment and BBB disruption, and blocked therapeutically by glucocorticoids.SUMMARYThe neurotropic Usutu virus can cause encephalitis driven by CCR2-mediated monocyte recruitment, microglia activation and blood-brain barrier disruption, all of which are inhibited by glucocorticoid treatment.
FeatureForest: the power of foundation models, the usability of random forests
Authors: Seifi Mehdi , Nogare Damian Dalle , Battagliotti Juan , Galinova Vera , Rao Ananya Kedige ,   AI4Life Horizon Europe Programme Consortium, Decelle Johan , Jug Florian , Deschamps Joran 
Published: December 2024

ABSTRACTOnce the work at the microscope is done, biological discoveries rely heavily on proper downstream analysis. This often amounts to first segmenting the biological objects of interest in the image before performing a quantitative analysis. Deep-learning (DL) is nowadays ubiquitous in such segmentation tasks. However, DL can be cumbersome to apply, as it often requires large amount of manual labeling to produce ground-truth data, and expert knowledge to train the models from scratch. Nonetheless, the performance of large foundation models, although trained on natural images, are improving on scientific images with every new model released. They, however, require either manual prompting or tedious post-processing to selectively segment the biological objects of interest. Classical machine learning algorithms, such as random forest classifiers, on the other hand, are well-established, easy to train, and often yield results of sufficient quality for downstream processing tasks, hence their continued popularity. Unfortunately, they are limited to objects with distinct, well-defined textures compared to their environment. This generally limits their usefulness to structures easy to recognize. Here, we present FeatureForest, an open-source tool that leverages the feature embeddings of large foundation models to train a random forest classifier, thereby providing users with a rapid way of semantically segmenting complex images using only a few labeling strokes. We demonstrate the improvement in performance over a variety of datasets, including large and complex volumetric electron microscopy stacks. Our implementation is available in napari, currently integrates four foundation models, and can easily be extended to any new model once they become available.
Neural dynamics of reselecting visual and motor contents in working memory after external interference
Authors: Gresch Daniela , Behnke Larissa , van Ede Freek , Nobre Anna C. , Boettcher Sage E.P. 
Published: December 2024

AbstractIn everyday tasks, we must often shift our focus away from internal representations held in working memory to engage with perceptual events in the external world. Here, we investigated how our internal focus is reestablished following an interrupting task by tracking the reselection of visual representations and their associated action plans in working memory. Specifically, we ask whether reselection occurs for both visual and motor memory attributes and when this reselection occurs. We developed a visual-motor working-memory task in which participants were retrospectively cued to select one of two memory items before being interrupted by a perceptual discrimination task. To determinewhatinformation was reselected, the memory items had distinct visual and motor attributes. To determinewheninternal representations were reselected, the interrupting task was presented at one of three distinct time points following the retro-cue. We employed electroencephalography time-frequency analyses to track the initial selection and later reselection of visual and motor representations, as operationalized through modulations of posterior alpha (8-12 Hz) activity relative to the memorized item location (visual) and of central beta (13-30 Hz) activity relative to the required response hand (motor). Our results showed that internal visual and motor contents were concurrently reselected immediately after completing the interrupting task, rather than only when internal information was required for memory-guided behavior. Thus, following interruption, we swiftly resume our internal focus in working memory through the simultaneous reselection of memorized visual representations and their associated action plans, thereby restoring internal contents to a ready-to-use state.Significance statementA key challenge for working memory is to maintain past visual representations and their associated actions while engaging with the external environment. Our cognitive system must, therefore, often juggle multiple tasks within a common time frame. Despite the ubiquity of multi-task situations in everyday life, working memory has predominantly been studied devoid of additional perceptual, attentional, and response demands during the retention interval. Here, we investigate the neural dynamics of returning to internal contents following task-relevant interruptions. Particularly, we identifywhich attributesof internal representations are reselected andwhenthis reselection occurs. Our findings demonstrate that both visual and motor contents are reselected immediately and in tandem after completion of an external, interrupting task.
The non-specific phospholipase C of common beanPvNPC4modulates roots and nodule development
Authors: Pacheco Ronal , Juárez-Verdayes MA , Chávez-Martínez A. I. , Palacios-Martínez Janet , Leija Alfonso , Nava Noreide , Cárdenas-Torres Luis , Quinto Carmen 
Published: December 2024

AbstractPlant phospholipase C (PLC) proteins are phospholipid-degrading enzymes classified into two subfamilies: phosphoinositide-specific PLCs (PI-PLCs) and non-specific PLCs (NPCs). PI-PLCs have been widely studied in various biological contexts, including responses to abiotic and biotic stresses and plant development; NPCs have been less thoroughly studied. No PLC subfamily has been characterized in relation to the symbiotic interaction between Fabaceae (legume) species and the nitrogen-fixing bacteria called rhizobia. However, lipids are reported to be crucial to this interaction, and PLCs may therefore contribute to regulating legume–rhizobia symbiosis. In this work, we functionally characterizedNPC4from common bean (Phaseolus vulgarisL.) during rhizobial symbiosis, finding evidence that NPC4 plays an important role in bean root development. The knockdown ofPvNPC4by RNA interference (RNAi) resulted in fewer and shorter primary roots and fewer lateral roots than were seen in control plants. Importantly, this phenotype seems to be related to altered auxin signaling. In the bean–rhizobia symbiosis,PvNPC4transcript abundance increased 3 days after inoculation withRhizobium tropici. Moreover, the number of infection threads and nodules, as well as the transcript abundance ofPvEnod40, a regulatory gene of early stages of symbiosis, decreased inPvNPC4-RNAi roots. Additionally, transcript abundance of genes involved in autoregulation of nodulation (AON) was altered byPvNPC4silencing. These results indicate thatPvNPC4is a key regulator of root and nodule development, underscoring the participation of PLC in rhizobial symbiosis.
In SilicoToxicity Assessment of Organophosphates: A DFT and Molecular Docking Study on Their Interaction with Human Serum Albumin (HSA)
Authors: Singh Tanya , Shankhwar Nisha , Sharma Neeta Raj , Kumar Anil , Verma Awadhesh Kumar 
Published: December 2024

AbstractThis study presents anin silicoanalysis of the toxicity of Organophosphates (OPs) through their interaction with Human Serum Albumin (HSA) protein using density functional theory (DFT) and molecular docking approaches. Organophosphates, known for their widespread use as pesticides, have raised significant concerns due to their potential toxicological effects. To investigate the molecular mechanisms underlying OP toxicity, we conducted DFT calculations to determine the electronic properties and reactivity of selective OP compounds. Molecular docking simulations were performed to explore the binding affinity, interaction sites, and conformational changes of HSA upon exposure to OPs. The DFT analysis revealed key electronic descriptors, such as HOMO-LUMO gap and electrostatic potential, that indicate high reactivity of OPs with biological molecules. Docking results showed strong binding affinities between OPs and HSA, particularly at sites involved in metabolite and drug transport, suggesting potential interference with the protein’s native function. The interaction of OPs with HSA was further supported by molecular dynamics simulations, which confirmed the stability of the OP-HSA complex over time. These findings provide critical insights into the molecular basis of organophosphate toxicity, emphasizing the importance of their interaction with HSA. The combined DFT and molecular docking approach offers a valuable framework for predicting the toxicological behavior of OPs and lays the foundation for furtherin vitroandin vivostudies.Graphical Abstract
Optimization of protocols for immunohistochemical assessment of enteric nervous system in formalin fixed human tissue
Authors: Hong Su Min , Qian Xia , Deshpande Vikram , Kulkarni Subhash 
Published: December 2024

AbstractGastrointestinal (GI) motility is regulated in a large part by the cells of the enteric nervous system (ENS), suggesting that ENS dysfunctions either associate with, or drive GI dysmotility in patients. However, except for select diseases such as Hirschsprung’s Disease or Achalasia that show a significant loss of all neurons or a subset of neurons, our understanding of human ENS histopathology is extremely limited. Recent endoscopic advances allow biopsying patient’s full thickness gut tissues, which makes capturing ENS tissues simpler than biopsying other neuronal tissues, such as the brain. Yet, our understanding of ENS aberrations observed in GI dysmotility patients lags behind our understanding of central nervous system aberrations observed in patients with neurological disease. Paucity of optimized methods for histopathological assessment of ENS in pathological specimens represent an important bottleneck in ascertaining how the ENS is altered in diverse GI dysmotility conditions. While recent studies have interrogated ENS structure in surgically resected whole mount human gut, most pathological specimens are banked as formalin fixed paraffin embedded (FFPE) tissue blocks – suggesting that methods to interrogate ENS in FFPE tissue blocks would provide the biggest impetus for ENS histopathology in a clinical setting. In this report, we present optimized methods for immunohistochemical interrogation of the human ENS tissue on the basis of >25 important protein markers that include proteins expressed by all neurons, subset of neurons, hormones, and neurotransmitter receptors. This report provides a resource which will help pathologists and investigators assess ENS aberrations in patients with various GI dysmotility conditions.
A Comprehensive Study ofPiper chaba(Chui jhal): Phytochemistry and Antioxidant Effects
Authors: Kundu Monika , Kundu Konika , Joty Farhana Akter 
Published: December 2024

AbstractPiper chaba, a valuable medicinal plant from the family Piperaceae is widely cultivated for its use in traditional medicine and as a spice. This study aimed to evaluate the phytochemical composition and antioxidant potential ofPiper chaba. Phytochemical analysis was conducted using standard chemical reaction methods, and antioxidant activity was assessed through the free radical scavenging assay. The phytochemical screening revealed the presence of alkaloids, carbohydrates, flavonoids, glycosides, resin, steroids, terpenoids, and tannin inPiper chaba. The presence of flavonoids indicates significant antioxidant potential. By using the DPPH scavenging method, the plant showed an IC50value of 5.81. Further analysis is required to identify the potentiality of the plant in various areas.
Quantification of CAR T cell performance against acute myeloid leukemia using Bayesian inference
Authors: Shah Saumil , Mueller Jan , Raatz Michael , Boettcher Steffen , Traulsen Arne , Manz Markus G. , Altrock Philipp M. 
Published: December 2024

AbstractChimeric Antigen Receptor (CAR) T cell therapy offers promising avenues for cancer treatment. Insights into CAR T cell kinetics and cellular dynamics may help identify better dosing and targeting regimens. Mathematical models of cancer and immune cell interactions are valuable tools that integrate existing knowledge with predictive capabilities, thereby narrowing the experimental search space. We formulated a mathematical model with a general T cell expansion functional form by drawing a parallel between predator-prey and immune-tumor interactions. We then compared the abilities of different T cell expansion candidate models to recapitulate a novelin vitrodata set of CAR T cells targeting various myeloid antigens on leukemic target cells with differentTP53genotypes. We used Bayesian parameter inference for each candidate model based on thein vitroassay. This approach enabled us to statistically compare candidate models with competing assumptions and select a model that best described thein vitrocytolytic assay longitudinal dynamics. The best-performing CAR T cell expansion model accounts for the detrimental effects of a T cell’s average time to eliminate a leukemia cell and for effector T cell self-interference. We validated this model on unseen data and used it to predict the expected long-term outcomes of single- and multi-dose CAR T cell therapy against acute myeloid leukemia. Our work demonstrates the utility of predator-prey-like mathematical models and Bayesian inference to investigate and assess the performance of novel CAR T cell constructs, helping to guide the translation to clinically relevant and feasible dosing strategies.
Efficient cell-free translation from diverse human cell types
Authors: Ziegelmüller Jana , Kouvelas Nikolaos , Thambythurai Priyanka , Hofer Alexander M. , Mühlemann Oliver , Karousis Evangelos D. 
Published: December 2024

MotivationThe difficulties in producing cell-free translation systems from different cell types limit the ability to study regulatory mechanisms that depend on different biological contexts. Developing systems tailored to diverse cell types would be instrumental in investigating cell-type-specific translational control, co- and post-translational modifications, and viral manipulation strategies. Our method addresses this gap by providing a scalable and adaptable solution for producing high-quality lysates that reflect the specific needs of different cell types.SummaryCell-free translation systems are indispensable for studying protein synthesis, enabling researchers to explore translational regulation across different cell types. Here, we present a scalable method for preparing translation-competent lysates from a range of frequently used human cell lines using dual centrifugation. We optimized lysis conditions for adherent and suspension cells, producing high-quality lysates from HEK-293 (adherent and in suspension), HeLa, SH-SY5Y, and U2OS cells. Our results demonstrate that cell-specific factors influence translation efficiency, with adherent HeLa cells showing the highest activity. We also observed that sensitivity to lysis conditions varies between cell lines, underscoring the importance of fine-tuning parameters for efficient protein production. Our method provides a robust and adaptable approach for generating cell-type-specific lysates, broadening the application ofin vitrotranslation systems in studying translational mechanisms.