bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying misdiagnosed bipolar disorder using support vector machine: feature selection based on fMRI of follow-up confirmed affective disorders
Authors: Jiang Xiaowei , Cao Bo , Li Chao , Jia Linna , Jing Yi , Cai Wei , Zhao Wenhui , Sun Qikun , Wu Feng , Kong Lingtao , Tang Yanqing 
Published: January 2024

AbstractNearly a quarter of bipolar disorder (BD) patients were misdiagnosed as major depressive disorder (MDD) patients, which cannot be corrected until mania/hypomania develops. It is important to recognize these obstacles so that the appropriate treatment can be initiated. Thus, we sought to distinguish patients with BD from MDD, especially to identify misdiagnosed BD before mania/hypomania, and further explore potential trait features that allow accurate differential diagnosis independent of state matters. Functional magnetic resonance imaging scans were performed at baseline on 92 MDD patients and 48 BD patients. The MDD patients were then followed up for more than two years. After follow-up, 23 patients transformed into BD (tBD), and 69 patients whose diagnoses remained unchanged were eligible for unipolar depression (UD). A support vector machine classifier was trained on the amygdala-based functional connectivity (FC) of 48 BD and 50 UD patients using a novel region-based feature selection. Then, the classifier was tested on the dataset, encompassing tBD and the remaining UD. It performed well for known BD and UD and can also distinguish tBD from UD with an accuracy of 81%, sensitivity of 82.6%, specificity of 79%, and AUC of 74.6%, respectively. Feature selection results revealed that ten regions within the cortico-limbic neural circuit contributed most to classification. Furthermore, in the FC comparisons among diseases, BD and tBD shared almost overlapped FC patterns in the cortico-limbic neural circuit, and both of them presented pronounced differences in most regions within the circuit compared with UD. The FC values of the most discriminating brain regions had no prominent correlations with the severity of depression, anxiety, and mania/hypomania (FDR correction). It suggests that BD possesses some trait features in the cortico-limbic neural circuit, rendering it dichotomized by the classifier based on known-diagnosis data.
Fear extinction rescuing effects of dopamine and L-DOPA in the ventromedial prefrontal cortex
Authors: Sartori Simone B. , Keil Thomas M. V. , Kummer Kai K. , Murphy Conor P. , Gunduz-Cinar Ozge , Kress Michaela , Ebner Karl , Holmes Andrew , Singewald Nicolas 
Published: January 2024

AbstractThe ventromedial prefrontal cortex (vmPFC; rodent infralimbic cortex (IL)), is posited to be an important locus of fear extinction-facilitating effects of the dopamine (DA) bio-precursor, L-DOPA, but this hypothesis remains to be formally tested. Here, in a model of impaired fear extinction (the 129S1/SvImJ inbred mouse strain; S1), we monitored extracellular DA dynamics via in vivo microdialysis in IL during fear extinction and following L-DOPA administration. Systemic L-DOPA caused sustained elevation of extracellular DA levels in IL and increased neuronal activation in a subpopulation of IL neurons. Systemic L-DOPA enabled extinction learning and promoted extinction retention at one but not ten days after training. Conversely, direct microinfusion of DA into IL produced long-term fear extinction (an effect that was insensitive to ɑ-/ß-adrenoreceptor antagonism). However, intra-IL delivery of a D1-like or D2 receptor agonist did not facilitate extinction. Using ex vivo multi-electrode array IL neuronal recordings, along with ex vivo quantification of immediate early genes and DA receptor signalling markers in mPFC, we found evidence of reduced DA-evoked mPFC network responses in S1 as compared with extinction-competent C57BL/6J mice that were partially driven by D1 receptor activation. Together, our data demonstrate that locally increasing DA in IL is sufficient to produce lasting rescue of impaired extinction. The finding that systemic L-DOPA increased IL DA levels, but had only transient effects on extinction, suggests L-DOPA failed to reach a threshold level of IL DA or produced opposing behavioural effects in other brain regions. Collectively, our findings provide further insight into the neural basis of the extinction-promoting effects of DA and L-DOPA in a clinically relevant animal model, with possible implications for therapeutically targeting the DA system in anxiety and trauma-related disorders.
Mapping Gilles de la Tourette syndrome through the distress and relief associated with tic-related behaviors: an fMRI study
Authors: Zapparoli Laura , Devoto Francantonio , Mariano Marika , Seghezzi Silvia , Servello Domenico , Porta Mauro , Paulesu Eraldo 
Published: January 2024

AbstractPersonal distress associated with tic urges or inhibition and relief associated with tic production are defining features of the personal experience in Gilles de la Tourette syndrome (GTS). These affective phenomena have not been studied using fMRI, hindering our understanding of GTS pathophysiology and possible treatments. Here, we present a novel cross-sectional fMRI study designed to map tic-related phenomenology using distress and relief as predicting variables. We adopted a mental imagery approach and dissected the brain activity associated with different phases of tic behaviors, premonitory urges, and the ensuing tic execution or inhibition: these were compared with the mental simulation of “relaxed situations” and pre-determined stereotyped motor behaviors. We then explored whether the ensuing brain patterns correlated with the distress or relief perceived for the different phases of the tasks. Patients experienced a higher level of distress during the imagery of tic-triggering scenarios and no relief during tic inhibition. On the other hand, patients experienced significant relief during tic imagery. Distress during tic-triggering scenarios and relief during tic imagery were significantly correlated. The distress perceived during urges correlated with increased activation in cortical sensorimotor areas, suggesting a motor alarm. Conversely, relief during tic execution was positively associated with the activity of a subcortical network. The activity of the putamen was associated with both distress during urges and relief during tic execution. These findings highlight the importance of assessing the affective component of tic-related phenomenology. Subcortical structures may be causally involved in the affective component of tic pathophysiology, with the putamen playing a central role in both tic urge and generation. We believe that our results can be readily translated into clinical practice for the development of personalized treatment plans tailored to each patient’s unique needs.
Exploring the steps of learning: computational modeling of initiatory-actions among individuals with attention-deficit/hyperactivity disorder
Authors: Katabi Gili , Shahar Nitzan 
Published: January 2024

AbstractAttention-deficit/hyperactivity disorder (ADHD) is characterized by difficulty in acting in a goal-directed manner. While most environments require a sequence of actions for goal attainment, ADHD was never studied in the context of value-based sequence learning. Here, we made use of current advancements in hierarchical reinforcement-learning algorithms to track the internal value and choice policy of individuals with ADHD performing a three-stage sequence learning task. Specifically, 54 participants (28 ADHD, 26 controls) completed a value-based reinforcement-learning task that allowed us to estimate internal action values for each trial and stage using computational modeling. We found attenuated sensitivity to action values in ADHD compared to controls, both in choice and reaction-time variability estimates. Remarkably, this was found only for first-stage actions (i.e., initiatory actions), while for actions performed just before outcome delivery the two groups were strikingly indistinguishable. These results suggest a difficulty in following value estimation for initiatory actions in ADHD.
Anti-CTLA-4 nanobody as a promising approach in cancer immunotherapy
Authors: Babamohamadi Mehregan , Mohammadi Nastaran , Faryadi Elham , Haddadi Maryam , Merati Amirhossein , Ghobadinezhad Farbod , Amirian Roshanak , Izadi Zhila , Hadjati Jamshid 
Published: January 2024

AbstractCancer is one of the most common diseases and causes of death worldwide. Since common treatment approaches do not yield acceptable results in many patients, developing innovative strategies for effective treatment is necessary. Immunotherapy is one of the promising approaches that has been highly regarded for preventing tumor recurrence and new metastases. Meanwhile, inhibiting immune checkpoints is one of the most attractive methods of cancer immunotherapy. Cytotoxic T lymphocyte-associated protein-4 (CTLA-4) is an essential immune molecule that plays a vital role in cell cycle modulation, regulation of T cell proliferation, and cytokine production. This molecule is classically expressed by stimulated T cells. Inhibition of overexpression of immune checkpoints such as CTLA-4 receptors has been confirmed as an effective strategy. In cancer immunotherapy, immune checkpoint-blocking drugs can be enhanced with nanobodies that target immune checkpoint molecules. Nanobodies are derived from the variable domain of heavy antibody chains. These small protein fragments have evolved entirely without a light chain and can be used as a powerful tool in imaging and treating diseases with their unique structure. They have a low molecular weight, which makes them smaller than conventional antibodies while still being able to bind to specific antigens. In addition to low molecular weight, specific binding to targets, resistance to temperature, pH, and enzymes, high ability to penetrate tumor tissues, and low toxicity make nanobodies an ideal approach to overcome the disadvantages of monoclonal antibody-based immunotherapy. In this article, while reviewing the cellular and molecular functions of CTLA-4, the structure and mechanisms of nanobodies’ activity, and their delivery methods, we will explain the advantages and challenges of using nanobodies, emphasizing immunotherapy treatments based on anti-CTLA-4 nanobodies.
Informing disaster-risk management policies for education infrastructure using scenario-based recovery analyses
Authors: Opabola Eyitayo A. , Galasso Carmine 
Published: January 2024

AbstractRecent natural-hazard events have shown that post-disaster education continuity is still a significant global challenge. Here, we propose a methodology to support various stakeholders in quantifying the impact of disaster management policies on education continuity in low- and lower-middle-income countries. We then apply the proposed methodology to a hypothetical earthquake scenario impacting a testbed education infrastructure in Central Sulawesi, Indonesia. This case study accounts for local practice influencing recovery through interviews with stakeholders involved in post-disaster management in the region. The analyses reveal that early response financing mechanisms can help speed up education recovery by a factor of three. Also, community-managed school reconstruction projects are likely to be completed up to three to five times faster than agency-managed projects. Furthermore, we demonstrate how the framework can be used to prioritize school reconstruction projects to ensure inclusive education continuity at the community level.
Interfacial self-healing polymer electrolytes for long-cycle solid-state lithium-sulfur batteries
Authors: Pei Fei , Wu Lin , Zhang Yi , Liao Yaqi , Kang Qi , Han Yan , Zhang Huangwei , Shen Yue , Xu Henghui , Li Zhen , Huang Yunhui 
Published: January 2024

AbstractCoupling high-capacity cathode and Li-anode with solid-state electrolyte has been demonstrated as an effective strategy for increasing the energy densities and safety of rechargeable batteries. However, the limited ion conductivity, the large interfacial resistance, and unconstrained Li-dendrite growth hinder the application of solid-state Li-metal batteries. Here, a poly(ether-urethane)-based solid-state polymer electrolyte with self-healing capability is designed to reduce the interfacial resistance and provides a high-performance solid-state Li-metal battery. With its dynamic covalent disulfide bonds and hydrogen bonds, the proposed solid-state polymer electrolyte exhibits excellent interfacial self-healing ability and maintains good interfacial contact. Full cells are assembled with the two integrated electrodes/electrolytes. As a result, the Li||Li symmetric cells exhibit stable long-term cycling for more than 6000 h, and the solid-state Li-S battery shows a prolonged cycling life of 700 cycles at 0.3 C. The use of ultrasound imaging technology shows that the interfacial contact of the integrated structure is much better than those of traditional laminated structure. This work provides an interesting interfacial dual-integrated strategy for designing high-performance solid-state Li-metal batteries.
Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing
Authors: Wang Yusong , Wang Tong , Li Shaoning , He Xinheng , Li Mingyu , Wang Zun , Zheng Nanning , Shao Bin , Liu Tie-Yan 
Published: January 2024

AbstractGeometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular property prediction, their applications, such as drug discovery and molecular dynamics (MD) simulation, have been hindered by insufficient utilization of geometric information and high computational costs. Here we propose an equivariant geometry-enhanced graph neural network called ViSNet, which elegantly extracts geometric features and efficiently models molecular structures with low computational costs. Our proposed ViSNet outperforms state-of-the-art approaches on multiple MD benchmarks, including MD17, revised MD17 and MD22, and achieves excellent chemical property prediction on QM9 and Molecule3D datasets. Furthermore, through a series of simulations and case studies, ViSNet can efficiently explore the conformational space and provide reasonable interpretability to map geometric representations to molecular structures.
Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage
Authors: Ghasemi David R. , Okonechnikov Konstantin , Rademacher Anne , Tirier Stephan , Maass Kendra K. , Schumacher Hanna , Joshi Piyush , Gold Maxwell P. , Sundheimer Julia , Statz Britta , Rifaioglu Ahmet S. , Bauer Katharina , Schumacher Sabrina , Bortolomeazzi Michele , Giangaspero Felice , Ernst Kati J. , Clifford Steven C. , Saez-Rodriguez Julio , Jones David T. W. , Kawauchi Daisuke , Fraenkel Ernest , Mallm Jan-Philipp , Rippe Karsten , Korshunov Andrey , Pfister Stefan M. , Pajtler Kristian W. 
Published: January 2024

AbstractMedulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.
Quick model-based viscoelastic clot strength predictions from blood protein concentrations for cybermedical coagulation control
Authors: Ghetmiri Damon E. , Venturi Alessia J. , Cohen Mitchell J. , Menezes Amor A. 
Published: January 2024

AbstractCybermedical systems that regulate patient clotting in real time with personalized blood product delivery will improve treatment outcomes. These systems will harness popular viscoelastic assays of clot strength such as thromboelastography (TEG), which help evaluate coagulation status in numerous conditions: major surgery (e.g., heart, vascular, hip fracture, and trauma); liver cirrhosis and transplants; COVID-19; ICU stays; sepsis; obstetrics; diabetes; and coagulopathies like hemophilia. But these measurements are time-consuming, and thus impractical for urgent care and automated coagulation control. Because protein concentrations in a blood sample can be measured in about five minutes, we develop personalized, phenomenological, quick, control-oriented models that predict TEG curve outputs from input blood protein concentrations, to facilitate treatment decisions based on TEG curves. Here, we accurately predict, experimentally validate, and mechanistically justify curves and parameters for common TEG assays (Functional Fibrinogen, Citrated Native, Platelet Mapping, and Rapid TEG), and verify results with trauma patient clotting data.
Selective knowledge sharing for privacy-preserving federated distillation without a good teacher
Authors: Shao Jiawei , Wu Fangzhao , Zhang Jun 
Published: January 2024

AbstractWhile federated learning (FL) is promising for efficient collaborative learning without revealing local data, it remains vulnerable to white-box privacy attacks, suffers from high communication overhead, and struggles to adapt to heterogeneous models. Federated distillation (FD) emerges as an alternative paradigm to tackle these challenges, which transfers knowledge among clients instead of model parameters. Nevertheless, challenges arise due to variations in local data distributions and the absence of a well-trained teacher model, which leads to misleading and ambiguous knowledge sharing that significantly degrades model performance. To address these issues, this paper proposes aselective knowledge sharingmechanism for FD, termedSelective-FD, to identify accurate and precise knowledge from local and ensemble predictions, respectively. Empirical studies, backed by theoretical insights, demonstrate that our approach enhances the generalization capabilities of the FD framework and consistently outperforms baseline methods. We anticipate our study to enable a privacy-preserving, communication-efficient, and heterogeneity-adaptive federated training framework.
Mesozoic evolution of cicadas and their origins of vocalization and root feeding
Authors: Jiang Hui , Szwedo Jacek , Labandeira Conrad C. , Chen Jun , Moulds Maxwell S. , Mähler Bastian , Muscente A. Drew , Zhuo De , Nyunt Thet Tin , Zhang Haichun , Wei Cong , Rust Jes , Wang Bo 
Published: January 2024

AbstractExtant cicada (Hemiptera: Cicadoidea) includes widely distributed Cicadidae and relictual Tettigarctidae, with fossils ascribed to these two groups based on several distinct, minimally varying morphological differences that define their extant counterparts. However, directly assigning Mesozoic fossils to modern taxa may overlook the role of unique and transitional features provided by fossils in tracking their early evolutionary paths. Here, based on adult and nymphal fossils from mid-Cretaceous Kachin amber of Myanmar, we explore the phylogenetic relationships and morphological disparities of fossil and extant cicadoids. Our results suggest that Cicadidae and Tettigarctidae might have diverged at or by the Middle Jurassic, with morphological evolution possibly shaped by host plant changes. The discovery of tymbal structures and anatomical analysis of adult fossils indicate that mid-Cretaceous cicadas were silent as modern Tettigarctidae or could have produced faint tymbal-related sounds. The discovery of final-instar nymphal and exuviae cicadoid fossils with fossorial forelegs and piercing-sucking mouthparts indicates that they had most likely adopted a subterranean lifestyle by the mid-Cretaceous, occupying the ecological niche of underground feeding on root. Our study traces the morphological, behavioral, and ecological evolution of Cicadoidea from the Mesozoic, emphasizing their adaptive traits and interactions with their living environments.
Genomic and panproteomic analysis of the development of infant immune responses to antigenically-diverse pneumococci
Authors: Croucher Nicholas J. , Campo Joseph J. , Le Timothy Q. , Pablo Jozelyn V. , Hung Christopher , Teng Andy A. , Turner Claudia , Nosten François , Bentley Stephen D. , Liang Xiaowu , Turner Paul , Goldblatt David 
Published: January 2024

AbstractStreptococcus pneumoniae (pneumococcus) is a nasopharyngeal commensal and respiratory pathogen. This study characterises the immunoglobulin G (IgG) repertoire recognising pneumococci from birth to 24 months old (mo) in a prospectively-sampled cohort of 63 children using a panproteome array. IgG levels are highest at birth, due to transplacental transmission of maternal antibodies. The subsequent emergence of responses to individual antigens exhibit distinct kinetics across the cohort. Stable differences in the strength of individuals’ responses, correlating with maternal IgG concentrations, are established by 6 mo. By 12 mo, children develop unique antibody profiles that are boosted by re-exposure. However, some proteins only stimulate substantial responses in adults. Integrating genomic data on nasopharyngeal colonisation demonstrates rare pneumococcal antigens can elicit strong IgG levels post-exposure. Quantifying such responses to the diverse core loci (DCL) proteins is complicated by cross-immunity between variants. In particular, the conserved N terminus of DCL protein zinc metalloprotease B provokes the strongest early IgG responses. DCL proteins’ ability to inhibit mucosal immunity likely explains continued pneumococcal carriage despite hosts’ polyvalent antibody repertoire. Yet higher IgG levels are associated with reduced incidence, and severity, of pneumonia, demonstrating the importance of the heterogeneity in response strength and kinetics across antigens and individuals.
Animating hydrogel knotbots with topology-invoked self-regulation
Authors: Zhu Qing Li , Liu Weixuan , Khoruzhenko Olena , Breu Josef , Hong Wei , Zheng Qiang , Wu Zi Liang 
Published: January 2024

AbstractSteering soft robots in a self-regulated manner remains a grand challenge, which often requires continuous symmetry breaking and recovery steps for persistent motion. Although structural morphology is found significant for robotic functions, geometric topology has rarely been considered and appreciated. Here we demonstrate a series of knotbots, namely hydrogel-based robots with knotted structures, capable of autonomous rolling and spinning/rotating motions. With symmetry broken by external stimuli and restored by self-regulation, the coupling between self-constraint-induced prestress and photothermal strain animates the knotbots continuously. Experiments and simulations reveal that nonequilibrium processes are regulated dynamically and cooperatively by self-constraints, active deformations, and self-shadowing effect of the photo-responsive gel. The active motions enable the knotbots to execute tasks including gear rotation and rod climbing. This work paves the way to devise advanced soft robots with self-regulated sustainable motions by harnessing the topology.