bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of spaceflight on the EEG alpha power and functional connectivity
Authors: Pusil Sandra , Zegarra-Valdivia Jonathan , Cuesta Pablo , Laohathai Christopher , Cebolla Ana Maria , Haueisen Jens , Fiedler Patrique , Funke Michael , Maestú Fernando , Cheron Guy 
Published: June 2023

AbstractElectroencephalography (EEG) can detect changes in cerebral activity during spaceflight. This study evaluates the effect of spaceflight on brain networks through analysis of the Default Mode Network (DMN)'s alpha frequency band power and functional connectivity (FC), and the persistence of these changes. Five astronauts' resting state EEGs under three conditions were analyzed (pre-flight, in-flight, and post-flight). DMN’s alpha band power and FC were computed using eLORETA and phase-locking value. Eyes-opened (EO) and eyes-closed (EC) conditions were differentiated. We found a DMN alpha band power reduction during in-flight (EC: p < 0.001; EO: p < 0.05) and post-flight (EC: p < 0.001; EO: p < 0.01) when compared to pre-flight condition. FC strength decreased during in-flight (EC: p < 0.01; EO: p < 0.01) and post-flight (EC: ns; EO: p < 0.01) compared to pre-flight condition. The DMN alpha band power and FC strength reduction persisted until 20 days after landing. Spaceflight caused electrocerebral alterations that persisted after return to earth. Periodic assessment by EEG-derived DMN analysis has the potential to become a neurophysiologic marker of cerebral functional integrity during exploration missions to space.
Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO)
Authors: Dang Yifang , Li Fang , Hu Xinyue , Keloth Vipina K , Zhang Meng , Fu Sunyang , Amith Muhammad F , Fan J Wilfred , Du Jingcheng , Yu Evan , Liu Hongfang , Jiang Xiaoqian , Xu Hua , Tao Cui 
Published: June 2023

Abstract

Objective
Social determinants of health (SDoH) play critical roles in health outcomes and well-being. Understanding the interplay of SDoH and health outcomes is critical to reducing healthcare inequalities and transforming a “sick care” system into a “health-promoting” system. To address the SDOH terminology gap and better embed relevant elements in advanced biomedical informatics, we propose an SDoH ontology (SDoHO), which represents fundamental SDoH factors and their relationships in a standardized and measurable way.

Material and Methods
Drawing on the content of existing ontologies relevant to certain aspects of SDoH, we used a top-down approach to formally model classes, relationships, and constraints based on multiple SDoH-related resources. Expert review and coverage evaluation, using a bottom-up approach employing clinical notes data and a national survey, were performed.

Results
We constructed the SDoHO with 708 classes, 106 object properties, and 20 data properties, with 1,561 logical axioms and 976 declaration axioms in the current version. Three experts achieved 0.967 agreement in the semantic evaluation of the ontology. A comparison between the coverage of the ontology and SDOH concepts in 2 sets of clinical notes and a national survey instrument also showed satisfactory results.

Discussion
SDoHO could potentially play an essential role in providing a foundation for a comprehensive understanding of the associations between SDoH and health outcomes and paving the way for health equity across populations.

Conclusion
SDoHO has well-designed hierarchies, practical objective properties, and versatile functionalities, and the comprehensive semantic and coverage evaluation achieved promising performance compared to the existing ontologies relevant to SDoH.
(Non-)deport to Discipline: The Daily Life of Afghans in Turkey
Authors: Karadağ Sibel , Sert Deniz Ş 
Published: June 2023

Abstract
This study contributes to discussions on the politics of (non-)deportability by focusing on the case of Afghans, the largest migrant community without a right to protection in Turkey, itself the country hosting the most refugees. This article examines how the politics of (non-)deportation is shaped and practiced for Afghans and the types of everyday strategies they employ to deal with deportability. We first argue that the politics of deportation in Turkey is predominantly shaped by the needs of the informal labour market, which accounts for one-third of the total labour force. Our findings suggest that forced labour and the hypermobility of Afghans is both tolerated and hidden by the state, while Afghans’ fear of deportability operates as a disciplining apparatus. Second, we argue that, when spectacles of deportation are performed, three crucial factors help Afghans avoid deportation, namely their qawm-based (ethnic or kinship) background, the involvement of Afghan associations, and street-level negotiations with the authorities.
Curriculum Choices for Refugees: What UNRWA’s History Can Tell Us about the Potential of UN Education Programs to Address Refugees’ ‘Unknowable Futures’
Authors: Kelcey Jo 
Published: June 2023

Abstract
Quality education can help refugees navigate their ‘unknowable futures’. Yet, the potential of many education programs to fulfil this promise is shaped by the varied and at times, conflicting interests inherent in aid policy and practice. This article explores these tensions through a historical examination of UNRWA’s education program in the wake of the 1967 Arab-Israeli war. I show how an embedded state-centric approach to policy limited the UN’s influence over the education it provided to Palestine refugees. This manifested through a narrow focus on access to education, and refugees’ ability to get jobs, at the expense of education’s social and political roles. I argue that this case has wider resonance for understanding the institutional dynamics of global refugee education policies and points to the need for a more nuanced understanding of claims by aid agencies that education necessarily helps refugees navigate their unknowable futures.
Chronic Achilles tendon rupture in elderly treated with a combination of the side-locking loop suture technique and early rehabilitation protocol: two cases report
Authors: Kawai Akira , Morimoto Shota , Morio Futoshi , Tachibana Toshiya , Iseki Tomoya 
Published: June 2023

Abstract
A chronic Achilles tendon rupture (ATR) is generally defined as a rupture that occurs more than 4–6 weeks after the initial injury. A variety of corrective techniques have been reported, such as direct repair, V-Y plasty, turndown flap, tendon transfer and free tendon grafting. These procedures generally produce good results, but have the disadvantage of requiring prolonged immobilization and weight-bearing restrictions. This may be a risk factor for falls and decreased function in the lower limbs, especially in older patients. Side-locking loop sutures (SLLS) were first introduced in 2010 as a direct repair technique for acute ATR. This technique provides higher tensile strength, which may allow for early rehabilitation protocols such as early range of motion and early weight-bearing of the ankle without postoperative immobilization. In this report, we describe two cases of chronic ATR in elderly patients treated with SLLS and an early rehabilitation protocol.
Robotic-assisted sigmoidectomy with intracorporeal anastomosis and endoscopic management of deep infiltrating intestinal endometriosis
Authors: Lomeli-Reyes David , Montoya-Ramírez Jesús , Reyes-Rodríguez Enrique , López-Almanza Perla X , Ochoa-Ruiz Paola L 
Published: June 2023

Abstract
Deep endometriosis, defined as external adenomyosis, is a late stage of endometriosis. Associated with very severe pain, in addition to probably being a cofactor of infertility, with a low prevalence, the diagnosis is integrated by high clinical suspicion and confirmed with imaging studies. Deep infiltration can reach sigmoid colon, which would have surgical indication as resolving treatment. We report the case of deep infiltrating endometriosis affecting sigmoid colon of a 42-year-old woman, who was diagnosed with colicky pain in the left lower quadrant and chronic constipation. Colonoscopy revealed a 90% stenosis in the proximal portion of sigmoid colon, as well as mural thickening proximal to the site of stenosis, reported by computed tomography with oral contrast, for which it was decided to perform robot-assisted sigmoidectomy, with a 6-month follow-up and with imaging control, patient continues asymptomatic and without the presence of lesions suggestive of recurrence, and there is no functional impairment.
Leveraging Predictive Modelling from Multiple Sources of Big Data to Improve Sample Efficiency and Reduce Survey Nonresponse Error
Authors: Dutwin David , Coyle Patrick , Lerner Joshua , Bilgen Ipek , English Ned 
Published: June 2023

Abstract
Big data has been fruitfully leveraged as a supplement for survey data—and sometimes as its replacement—and in the best of worlds, as a “force multiplier” to improve survey analytics and insight. We detail a use case, the big data classifier (BDC), as a replacement to the more traditional methods of targeting households in survey sampling for given specific household and personal attributes. Much like geographic targeting and the use of commercial vendor flags, we detail the ability of BDCs to predict the likelihood that any given household is, for example, one that contains a child or someone who is Hispanic. We specifically build 15 BDCs with the combined data from a large nationally representative probability-based panel and a range of big data from public and private sources, and then assess the effectiveness of these BDCs to successfully predict their range of predicted attributes across three large survey datasets. For each BDC and each data application, we compare the relative effectiveness of the BDCs against historical sample targeting techniques of geographic clustering and vendor flags. Overall, BDCs offer a modest improvement in their ability to target subpopulations. We find classes of predictions that are consistently more effective, and others where the BDCs are on par with vendor flagging, though always superior to geographic clustering. We present some of the relative strengths and weaknesses of BDCs as a new method to identify and subsequently sample low incidence and other populations.
RING finger E3 ubiquitin ligase gene TaAIRP2-1B controls spike length in wheat
Authors: Zhang Jialing , Li Chaonan , Li Long , Xi Yajun , Wang Jingyi , Mao Xinguo , Jing Ruilian 
Published: June 2023

Abstract
E3 ubiquitin ligase genes play important roles in the regulation of plant development. They have been well studied in plants, but have not been sufficiently investigated in wheat. Here, we identified a highly expressed RING finger E3 ubiquitin ligase gene TaAIRP2-1B (ABA-insensitive RING protein 2) in wheat spike. Sequence polymorphism and association analysis showed that TaAIRP2-1B is significantly associated with spike length under various conditions. The genotype with haplotype Hap-1B-1 of TaAIRP2-1B has a longer spike than that of Hap-1B-2, and was positively selected in the process of wheat breeding in China. Moreover, the TaAIRP2-1B-overexpressing rice lines have longer panicles compared with wild-type plants. The expression levels of TaAIRP2-1B in Hap-1B-1 accessions were higher than in Hap-1B-2 accessions. Further study revealed that the expression of TaAIRP2-1B was negatively regulated by TaERF3 (ethylene-responsive factor 3) via binding to the Hap-1B-2 promoter, but not via binding of Hap-1B-1. Additionally, several candidate genes interacting with TaAIRP2-1B were obtained by screening the cDNA library of wheat in yeast cells. It was found that TaAIRP2-1B interacted with TaHIPP3 (heavy metal-associated isoprenylated protein 3) and promoted TaHIPP3 degradation. Our study demonstrates that TaAIRP2-1B controls spike length, and the haplotype Hap-1B-1 of TaAIRP2-1B is a favorable natural variation for spike length enhancement in wheat. This work also provides genetic resources and functional markers for wheat molecular breeding.
Conflict and natural disaster: the impacts on medical education in Ukraine and Türkiye
Authors: Armitage Richard C 
Published: June 2023

Abstract
In addition to causing enormous and enduring harms to the health of populations, the Russian invasion of Ukraine and the recent earthquakes in southeast Türkiye have greatly damaged the institutions of medical education at work in these countries. This paper explores these harms and encourages medical educationalists in unaffected countries to reflect on the virtues of their own educational institutions.
Focused Ultrasound Stimulates the Prefrontal Cortex and Prevents MK-801-Induced Psychiatric Symptoms of Schizophrenia in Rats
Authors: Pan Tsung-Yu , Pan Yi-Ju , Tsai Shih-Jen , Tsai Che-Wen , Yang Feng-Yi 
Published: June 2023

Abstract

Background and Hypothesis
Treatment of schizophrenia remains a major challenge. Recent studies have focused on glutamatergic signaling hypoactivity through N-methyl-D-aspartate (NMDA) receptors. Low-intensity pulsed ultrasound (LIPUS) improves behavioral deficits and ameliorates neuropathology in dizocilpine (MK-801)-treated rats. The aim of this study was to investigate the efficacy of LIPUS against psychiatric symptoms and anxiety-like behaviors.

Study Design
Rats assigned to 4 groups were pretreated with or without LIPUS for 5 days. The open field and prepulse inhibition tests were performed after saline or MK-801 (0.3 mg/kg) administration. Then, the neuroprotective effects of LIPUS on the MK-801-treated rats were evaluated using western blotting and immunohistochemical staining.

Study Results
LIPUS stimulation of the prefrontal cortex (PFC) prevented deficits in locomotor activity and sensorimotor gating and improved anxiety-like behavior. MK-801 downregulated the expression of NR1, the NMDA receptor, in rat medial PFC (mPFC). NR1 expression was significantly higher in animals receiving LIPUS pretreatment compared to those receiving only MK-801. In contrast, a significant increase in c-Fos-positive cells in the mPFC and ventral tegmental area was observed in the MK-801-treated rats compared to those receiving only saline; this change was suppressed by pretreatment with LIPUS.

Conclusions
This study provides new evidence for the role of LIPUS stimulation in regulating the NMDA receptor and modulating c-Fos activity, which makes it a potentially valuable antipsychotic treatment for schizophrenia.
Substantial variation in species ages among vertebrate clades
Authors: Pie Marcio R. , Caron Fernanda S. 
Published: June 2023

AbstractEcological and evolutionary studies traditionally assume that species are comparable units of biodiversity. However, not only this assumption is rarely tested, but also there have been few attempts even to assess variation in most emergent, species-level traits and their corresponding underlying mechanisms. One such trait is species age, here defined as the time since the most recent common ancestor between a given species and its sister lineage. In this study, we demonstrate that different terrestrial vertebrate clades vary considerably in the age of their constituent species. In particular, species ages were youngest in mammals and birds as opposed to squamates and amphibians, although considerable variation was found within those clades as well. Sensitivity analyses showed that these results are unaffected by phylogenetic uncertainty or incomplete taxonomic sampling. Interestingly, there was little geographical correspondence in mean species age across taxa, as well as with temperature and precipitation stability over the past 21,000 years. We discuss candidate mechanisms that might explain differences in species ages among clades, and explore the implications of these findings in relation to recent advances in age-dependent speciation and extinction models of diversification.
Effects of different immunomodulating liposome-based adjuvants and injection sites on immunogenicity in pigs
Authors: Šťastná Evelína , Erbs Gitte , Skovgaard Kerstin , Jakobsen Jeanne Toft , Pedersen Gabriel Kristian , Jungersen Gregers 
Published: June 2023

AbstractVaccine adjuvants are able to boost immune responses and steer immunity towards a desired direction. Liposome-based cationic adjuvant formulations (CAFs) are effective in inducing cell-mediated immune responses in mice, non-human primates and humans. In the translation from mouse to humans, pigs could play an important role. In this study, we thus used commercial pigs housed under field conditions to investigate the effects of four different CAFs incorporating distinct immunomodulators: C-type lectin receptor ligands trehalose-6,6’-dibehenate and monomycolyl glycerol, toll-like receptor ligand Poly(I:C) or retinoic acid. The vaccines were formulated with a recombinantChlamydiamodel protein antigen and administered via distinct injection routes. All adjuvants significantly increased antigen-specific IgA and IgG in serum, compared to non-adjuvanted antigen. Administering the vaccines through intramuscular and intraperitoneal routes induced significantly higher antigen-specific IgA and IgG serum antibodies, than the perirectal route. Although the immunizations triggered cell-mediated immunity, no significant differences between the adjuvants or injection sites were detected by intracellular flow cytometry or cytokine-release assays. Genes depicting T cell subtypes were monitored by qPCR, which revealed minor differences only. Our findings suggest that the adjuvant-specific signature of the tested adjuvant immunomodulation does not translate well from mice to pigs. This study provides new insights into immune responses to CAFs in the pig model, and highlights that adjuvant studies should be ideally carried out in the intended species of interest.
Integrative Analysis of Epilepsy-Associated Genes Reveals Expression-Phenotype Correlations
Authors: Chi Wanhao , Kiskinis Evangelos 
Published: June 2023

AbstractEpilepsy is a highly prevalent neurological disorder characterized by recurrent seizures. Patients exhibit broad genetic, molecular, and clinical diversity involving mild to severe comorbidities. The factors that contribute to this phenotypic diversity remain unclear. We used publicly available datasets to systematically interrogate the expression pattern of 247 epilepsy-associated genes across human tissues, developmental stages, and central nervous system (CNS) cellular subtypes. We grouped genes based on their curated phenotypes into 3 broad classes: core epilepsy genes (CEG), where seizures are the core syndrome, developmental and epileptic encephalopathy genes (DEEG) that are associated with developmental delay, and seizure-related genes (SRG), which are characterized by developmental delay and gross brain malformations. We find that DEEGs are highly expressed within the CNS, while SRGs are most abundant in non-CNS tissues. DEEGs and CEGs exhibit highly dynamic expression in various brain regions across development, spiking during the prenatal to infancy transition. Lastly, the abundance of CEGs and SRGs is comparable within cellular subtypes in the brain, while the average expression level of DEEGs is significantly higher in GABAergic neurons and non-neuronal cells. Our analysis provides an overview of the expression pattern of epilepsy-associated genes with spatiotemporal resolution and establishes a broad expression-phenotype correlation in epilepsy.
KIF1A neurodegenerative disease mutations modulate motor motility and force generation
Authors: Shewale Dipeshwari J. , Soppina Pushpanjali , Soppina Virupakshi 
Published: June 2023

AbstractKIF1A is involved in fast axonal transport of synaptic vesicle precursor, neurofilament, and dense-core vesicle, essential for neuronal development and maintenance. Several point mutations in the KIF1A motor domain have been identified in patients with various motor neuron diseases. Recent studies have shown that these mutations affected the motor and cargo localization in cultured hippocampal andC.elegansneurons. However, a detailed analysis of these mutations on KIF1A motility, force generation, and cargo transport is largely unexplored. Here, we have analyzed the effect of 16 point mutations and showed that these mutations significantly decreased the motor velocity and landing rates compared to wild-type motors. Except for A255V, mutations V144F, V220I, and E233D mildly affected motor mechanical outputs. S58L, A202P, R216P, R216H, L249Q, T312M, and R316W mutants exhibited drastic impairments in the motility properties, force generation, and cargo transport. Notably, T46M, T99M, G102D, S215R, and E253K mutants showed strong microtubule binding, resulting in complete disruption of cargo transport. Our study provides the first comprehensive demonstration of KIF1A disease mutations at the molecular level. The observed changes in motility properties and cargo transport align with the severity of disease phenotype observed in KIF1A-associated neurological disorders)
Machine Learning to Predict Continuous Protein Properties from Simple Binary Sorting and Deep Sequencing Data
Authors: Case Marshall , Smith Matthew , Vinh Jordan , Thurber Greg 
Published: June 2023

AbstractProteins are a diverse class of biomolecules responsible for wide-ranging cellular functions, from catalyzing reactions and recognizing pathogens to forming dynamic cellular structure. The ability to evolve proteins rapidly and inexpensively towards improved properties is a common objective for protein engineers. Powerful high-throughput methods like fluorescent activated cell sorting (FACS) and next-generation sequencing (NGS) have dramatically improved directed evolution experiments. However, it is unclear how to best leverage this data to characterize protein fitness landscapes more completely and identify lead candidates. In this work, we develop a simple yet powerful framework to improve protein optimization by predicting continuous protein properties from simple directed evolution experiments using interpretable machine learning. Evaluated across five diverse protein engineering tasks, continuous properties are consistently predicted from readily available deep sequencing data. To prospectively test the utility of this approach, we generated a library of stapled peptides and applied the framework to predict and optimize both affinity and specificity. We coupled integer linear programming with the interpretable machine learning model coefficients to identify new variants from experimentally unseen sequence space that have desired properties. This approach represents a versatile tool for improved analysis and identification of protein variants across many domains of protein engineering.