bluuebunny/crossref_metadata_2025_split huggingface dataset:
INCOG 2.0 Guidelines for Cognitive Rehabilitation Following Traumatic Brain Injury, Part IV: Cognitive-Communication and Social Cognition Disorders
Authors: Togher Leanne , Douglas Jacinta , Turkstra Lyn S. , Welch-West Penny , Janzen Shannon , Harnett Amber , Kennedy Mary , Kua Ailene , Patsakos Eleni , Ponsford Jennie , Teasell Robert , Bayley Mark Theodore , Wiseman-Hakes Catherine 
Published: January 2023

Introduction:
Moderate to severe traumatic brain injury causes significant cognitive impairments, including impairments in social cognition, the ability to recognize others' emotions, and infer others' thoughts. These cognitive impairments can have profound negative effects on communication functions, resulting in a cognitive-communication disorder. Cognitive-communication disorders can significantly limit a person's ability to socialize, work, and study, and thus are critical targets for intervention. This article presents the updated INCOG 2.0 recommendations for management of cognitive-communication disorders. As social cognition is central to cognitive-communication disorders, this update includes interventions for social cognition.

Methods:
An expert panel of clinicians/researchers reviewed evidence published since 2014 and developed updated recommendations for interventions for cognitive-communication and social cognition disorders, a decision-making algorithm tool, and an audit tool for review of clinical practice.

Results:
Since INCOG 2014, there has been significant growth in cognitive-communication interventions and emergence of social cognition rehabilitation research. INCOG 2.0 has 9 recommendations, including 5 updated INCOG 2014 recommendations, and 4 new recommendations addressing cultural competence training, group interventions, telerehabilitation, and management of social cognition disorders. Cognitive-communication disorders should be individualized, goal- and outcome-oriented, and appropriate to the context in which the person lives and incorporate social communication and communication partner training. Group therapy and telerehabilitation are recommended to improve social communication. Augmentative and alternative communication (AAC) should be offered to the person with severe communication disability and their communication partners should also be trained to interact using AAC. Social cognition should be assessed and treated, with a focus on personally relevant contexts and outcomes.

Conclusions:
The INCOG 2.0 recommendations reflect new evidence for treatment of cognitive-communication disorders, particularly social interactions, communication partner training, group treatments to improve social communication, and telehealth delivery. Evidence is emerging for the rehabilitation of social cognition; however, the impact on participation outcomes needs further research.
INCOG 2.0 Guidelines for Cognitive Rehabilitation Following Traumatic Brain Injury, Part II: Attention and Information Processing Speed
Authors: Ponsford Jennie , Velikonja Diana , Janzen Shannon , Harnett Amber , McIntyre Amanda , Wiseman-Hakes Catherine , Togher Leanne , Teasell Robert , Kua Ailene , Patsakos Eleni , Welch-West Penny , Bayley Mark Theodore 
Published: January 2023

Introduction:
Moderate to severe traumatic brain injury (MS-TBI) commonly causes disruption in aspects of attention due to its diffuse nature and injury to frontotemporal and midbrain reticular activating systems. Attentional impairments are a common focus of cognitive rehabilitation, and increased awareness of evidence is needed to facilitate informed clinical practice.

Methods:
An expert panel of clinicians/researchers (known as INCOG) reviewed evidence published from 2014 and developed updated guidelines for the management of attention in adults, as well as a decision-making algorithm, and an audit tool for review of clinical practice.

Results:
This update incorporated 27 studies and made 11 recommendations. Two new recommendations regarding transcranial stimulation and an herbal supplement were made. Five were updated from INCOG 2014 and 4 were unchanged. The team recommends screening for and addressing factors contributing to attentional problems, including hearing, vision, fatigue, sleep-wake disturbance, anxiety, depression, pain, substance use, and medication. Metacognitive strategy training focused on everyday activities is recommended for individuals with mild-moderate attentional impairments. Practice on de-contextualized computer-based attentional tasks is not recommended because of lack of evidence of generalization, but direct training on everyday tasks, including dual tasks or dealing with background noise, may lead to gains for performance of those tasks. Potential usefulness of environmental modifications is also discussed. There is insufficient evidence to support mindfulness-based meditation, periodic alerting, or noninvasive brain stimulation for alleviating attentional impairments. Of pharmacological interventions, methylphenidate is recommended to improve information processing speed. Amantadine may facilitate arousal in comatose or vegetative patients but does not enhance performance on attentional measures over the longer term. The antioxidant Chinese herbal supplement MLC901 (NeuroAiD IITM) may enhance selective attention in individuals with mild-moderate TBI.

Conclusion:
Evidence for interventions to improve attention after TBI is slowly growing. However, more controlled trials are needed, especially evaluating behavioral or nonpharmacological interventions for attention.
Hospital Utilization for Coronary Artery Disease, 1997–2014
Authors: Shakya Shamatree , Cary Michael P. 
Published: January 2023

Background
Coronary artery disease (CAD) is the leading cause of cardiovascular morbidity, mortality, and healthcare costs in the United States. There are few reports on how public health and payment reforms might have influenced inpatient hospital use among patients with CAD.

Objective
This study describes trends in hospital discharges, hospital charges, and discharge destinations in a national sample of patients with CAD between 1997 and 2014.

Methods
This was a longitudinal study with descriptive analysis of the Healthcare Cost and Utilization Project of National Inpatient Sample data.

Findings
During this study period, the total number of discharges was 1 333 996. Patients with CAD between 65 and 84 years old were among the highest users of inpatient hospital services, followed by those in the 45- to 64-year age group. The death rate increased from 5961 to 7217 per 10 000 patients during this time. The mean charge increased more than 5 times, from $9100 to $49 643. There was a large difference in mean hospital charges in urban ($51 666) and rural ($25 548) locations in 2014. Coronary artery disease patients with private insurance paid more than those with Medicaid and Medicare plans. The discharge to home and healthcare costs increased by 4.1% and 4.8%, respectively.

Conclusion and Implications
Future researchers should use data sets, such as Medicare claims/Medical Expenditure Panel Study, that can provide comprehensive insights into patient-level factors influencing the use of inpatient care services among patients with CAD. Healthcare providers in posthospital settings should be well skilled in providing advanced cardiac rehabilitation and education to patients with CAD.
Fatty Acid Vesicles as Hard UV-C Shields for Early Life
Authors: Lechuga Iván , Michaelian Karo 
Published: January 2023

AbstractTheories on life’s origin generally acknowledge the advantage of a semi-permeable vesicle (protocell) for enhancing the chemical reaction-diffusion processes involved in abiogenesis. However, more and more evidence indicates that the origin of life concerned the photo-chemical dissipative structuring of the fundamental molecules under UV-C light. In this paper, we analyze the Mie UV scattering properties of such a vesicle made from long chain fatty acids. We find that the vesicle could have provided early life with a shield from the faint, but dangerous, hard UV-C ionizing light (180-210 nm) that probably bathed Earth’s surface from before the origin of life and until perhaps 1,500 million years after, until the formation of a protective ozone layer as a result of the evolution of oxygenic photosynthesis.
Learning Cortical Hierarchies with Temporal Hebbian Updates
Authors: Aceituno Pau Vilimelis , Farinha Matilde Tristany , Loidl Reinhard , Grewe Benjamin F. 
Published: January 2023

ABSTRACTA key driver of mammalian intelligence is the ability to represent incoming sensory information across multiple abstraction levels. For example, in the visual ventral stream, incoming signals are first represented as low-level edge filters and then transformed into high-level object representations. These same hierarchical structures routinely emerge in artificial neural networks (ANNs) trained for image/object recognition tasks, suggesting that a similar process might underlie biological neural networks. However, the classical ANN training algorithm, backpropagation, is considered biologically implausible, and thus several alternative biologically plausible methods have been developed. For instance, several cortical-inspired ANNs in which the apical dendrite of a pyramidal neuron encodes top-down prediction signals have been proposed. In this case, akin to theories of predictive coding, a prediction error can be calculated locally inside each neuron for updating its incoming weights. Notwithstanding, from a neuroscience perspective, it is unclear whether neurons could compare their apical vs. somatic spiking activities to compute prediction errors. Here, we propose a solution to this problem by adapting the framework of the apical-somatic prediction error to the temporal domain. In particular, we show that if the apical feedback signal changes the postsynaptic firing rate, we can use differential Hebbian updates, a rate-based version of the classical spiking time-dependent plasticity (STDP) updates. To the best of our knowledge, this is the first time a cortical-like deep ANN has been trained using such time-based learning rules. Overall, our work removes a key requirement of biologically plausible models for deep learning that does not align with plasticity rules observed in biology and proposes a learning mechanism that would explain how the timing of neuronal activity can allow supervised hierarchical learning.
Genome-wide temperature-sensitivity of PcG regulation and reduction thereof in temperateDrosophila melanogaster
Authors: Voigt Susanne , Froschauer Christin 
Published: January 2023

AbstractEpigenetic regulation varies with the environment. In the fruit flyDrosophila melanogaster, environmental temperature can affect chromatin-based gene regulation. Genes regulated by the Polycomb group (PcG) can vary in their transcriptional output in response to changes in temperature, which typically increases with decreasing temperature. Here, we studied temperature-sensitive expression of PcG target genes on a genome-wide scale, as well as temperature-sensitive enrichment of two histone modifications associated with the regulation of PcG target genes, H3K27me3 and H3K4me3. We investigated temperature-sensitivity in adult flies, and possible differences thereof between populations adapted to temperate and tropical climates. Compared to genes not targeted by the PcG, an elevated number of target genes showed higher expression at the lower temperature, as it is typically observed for PcG regulation. Many of the PcG target genes also exhibited temperature-sensitive H3K4me3 enrichment in the same direction, and the H3K4me3 temperature response correlated positively with that of expression. A small set of target sites also showed temperature-sensitive enrichment of H3K27me3, again with a higher proportion corresponding to increased transcriptional activation at the lower temperature. Overall, higher transcriptional activity at lower temperature was less pronounced in males compared to females, and in temperate compared to tropical flies. Possible trans- and cis-acting factors responsible for reduced expression plasticity in temperate flies were identified, including factors belonging to the Trithorax group (TrxG) and insulator binding proteins, respectively.
Grasping with a twist: Dissociating action goals from motor actions in human frontoparietal circuits
Authors: Rens Guy , Figley Teresa D. , Gallivan Jason P. , Liu Yuqi , Culham Jody C. 
Published: January 2023

AbstractIn daily life, prehension is typically not the end goal of hand-object interactions but a precursor for manipulation. Nevertheless, functional MRI (fMRI) studies investigating manual manipulation have primarily relied on prehension as the end goal of an action. Here, we used slow event-related fMRI to investigate differences in neural activation patterns between prehension in isolation and prehension for object manipulation. Sixteen participants were instructed either to simply grasp the handle of a rotatable dial (isolated prehension) or to grasp and turn it (prehension for object manipulation). We used representational similarity analysis to investigate whether the experimental conditions could be discriminated from each other based on differences in task-related brain activation patterns. We also used temporal multivoxel pattern analysis to examine the evolution of regional activation patterns over time. Importantly, we were able to differentiate isolated prehension and prehension for manipulation from activation patterns in the early visual cortex, the caudal intraparietal sulcus, and the superior parietal lobule. Our findings indicate that object manipulation extends beyond the putative cortical grasping network (anterior intraparietal sulcus, premotor and motor cortices) to include the superior parietal lobule and early visual cortex.Significance statementA simple act such as turning an oven dial requires not only that the central nervous system encode the initial state (starting dial orientation) of the object but also the appropriate posture to grasp it in order to achieve the desired end state (final dial orientation) and the motor commands to achieve that state. Using advanced temporal neuroimaging analysis techniques, we reveal how such actions unfold over time and how they differ between object manipulation (turning a dial) vs. grasping alone. We find that a combination of brain areas implicated in visual processing and sensorimotor integration can distinguish between the complex and simple tasks during planning, with neural patterns that approximate those during the actual execution of the action.
RNA-seq preprocessing and sample size considerations for gene network inference
Authors: Altay Gökmen , Zapardiel-Gonzalo Jose , Peters Bjoern 
Published: January 2023

AbstractBackgroundGene network inference (GNI) methods have the potential to reveal functional relationships between different genes and their products. Most GNI algorithms have been developed for microarray gene expression datasets and their application to RNA-seq data is relatively recent. As the characteristics of RNA-seq data are different from microarray data, it is an unanswered question what preprocessing methods for RNA-seq data should be applied prior to GNI to attain optimal performance, or what the required sample size for RNA-seq data is to obtain reliable GNI estimates.ResultsWe ran 9144 analysis of 7 different RNA-seq datasets to evaluate 300 different preprocessing combinations that include data transformations, normalizations and association estimators. We found that there was no single best performing preprocessing combination but that there were several good ones. The performance varied widely over various datasets, which emphasized the importance of choosing an appropriate preprocessing configuration before GNI. Two preprocessing combinations appeared promising in general: First, Log-2 TPM (transcript per million) with Variance-stabilizing transformation (VST) and Pearson Correlation Coefficient (PCC) association estimator. Second, raw RNA-seq count data with PCC. Along with these two, we also identified 18 other good preprocessing combinations. Any of these algorithms might perform best in different datasets. Therefore, the GNI performances of these approaches should be measured on any new dataset to select the best performing one for it. In terms of the required biological sample size of RNA-seq data, we found that between 30 to 85 samples were required to generate reliable GNI estimates.ConclusionsThis study provides practical recommendations on default choices for data preprocessing prior to GNI analysis of RNA-seq data to obtain optimal performance results.
Neural correlates of face perception modeled with a convolutional recurrent neural network
Authors: O’Reilly Jamie A. , Wehrman Jordan , Carey Aaron , Bedwin Jennifer , Hourn Thomas , Asadi Fawad , Sowman Paul F. 
Published: January 2023

AbstractEvent-related potential (ERP) sensitivity to faces is predominantly characterized by an N170 peak that has greater amplitude and shorter latency when elicited by human faces than images of other objects. We developed a computational model of visual ERP generation to study this phenomenon which consisted of a convolutional neural network (CNN) connected to a recurrent neural network (RNN). We used open-access data to develop the model, generated synthetic images for simulating experiments, then collected additional data to validate predictions of these simulations. For modeling, visual stimuli presented during ERP experiments were represented as sequences of images (time x pixels). These were provided as inputs to the model. The CNN transformed these inputs into sequences of vectors that were passed to the RNN. The ERP waveforms evoked by visual stimuli were provided to the RNN as labels for supervised learning. The whole model was trained end-to-end using data from the open-access dataset to reproduce ERP waveforms evoked by visual events. Cross-validation model outputs strongly correlated with open-access (r = 0.98) and validation study data (r = 0.78). Open-access and validation study data correlated similarly (r = 0.81). Some aspects of model behavior were consistent with neural recordings while others were not, suggesting promising albeit limited capacity for modeling the neurophysiology of face-sensitive ERP generation.
In VivoDelivery of Therapeutic Molecules by Transplantation of Genome-Edited Induced Pluripotent Stem Cells
Authors: Nakajima Ittetsu , Tsukimura Takahiro , Ono Terumi , Shiga Tomoko , Shitara Hiroshi , Togawa Tadayasu , Sakuraba Hitoshi , Miyaoka Yuichiro 
Published: January 2023

SummaryHuman induced pluripotent stem cells (iPSCs) have already been used in transplantation therapies. Currently, cells from healthy people are transplanted into patients with diseases. With the rapid evolution of genome editing technology, genetic modification could be applied to enhance the therapeutic effects of iPSCs, such as the introduction of secreted molecules to make the cells a drug delivery system. Here, we addressed this possibility by utilizing a Fabry disease mouse model, as a proof of concept. Fabry disease is caused by the lack of α-Galactosidase A (GLA). We previously developed an immunotolerant therapeutic molecule, modified α-N-acetylgalactosaminidase (mNAGA). We confirmed that secreted mNAGA from genome-edited iPSCs compensated for the GLA activity in GLA-deficient cells using anin vitroco-culture system. Moreover, iPSCs transplanted into Fabry model mice secreted mNAGA and supplied GLA activity to the liver. This study demonstrates the great potential of genome-edited iPSCs secreting therapeutic molecules.
A Gamma-adapted recombinant subunit vaccine induces broadly neutralizing antibodies against SARS-CoV-2 variants and protects mice from infection
Authors: Coria Lorena M. , Rodriguez Juan Manuel , Demaria Agostina , Bruno Laura A. , Rios Medrano Mayra , Pueblas Castro Celeste , Castro Eliana F. , Del Priore Sabrina A. , Hernando Insua Andres C. , Kaufmann Ingrid G. , Saposnik Lucas M. , Stone William B. , Prado Lineia , Krum Valeria , Zurvarra Francisco M. , Sidabra Johanna E. , Drehe Ignacio , Baqué Jonathan A. , Li Causi Mariana , De Nichilo Analia V. , Payes Cristian J. , Auguste Albert J. , Vega Julio C. , Álvarez Diego E. , Flo Juan M. , Pasquevich Karina A. , Cassataro Juliana 
Published: January 2023

AbstractThe COVID-19 pandemic continues with the emergence of successive new variants of concern (VOC). One strategy to prevent breakthrough infections is developing safe and effective broad-spectrum vaccines. Here, we present preclinical studies of a RBD recombinant vaccine candidate derived from the Gamma SARS-CoV-2 variant adjuvanted with alum. Gamma RBD-derived antigen elicited better neutralizing antibody and T cell responses than formulation containing ancestral RBD antigen. The Gamma-adapted subunit vaccine elicited a long-lasting antibody response with cross-neutralizing activity against different VOC including the Omicron variant. Additionally, Gamma variant RBD-adapted vaccine elicited robust T cells responses with induction of Th1 and CD8+T cell responses in spleen and lung. Vaccine-induced immunity protected K18-hACE2 mice from intranasal challenge with SARS-CoV-2 increasing survival, reducing body weight loss and viral burden in the lungs and brain. Importantly, the subunit vaccine demonstrated a potent effect as heterologous booster of different vaccine platforms including the non-replicating adenovirus vaccine ChAdOx1-S, the mRNA vaccine BNT162b2 and the inactivated SARS-CoV-2 vaccine BBIBP-CorV, increasing cross-reactive antibody responses. Our study indicates that the adjuvanted Gamma RBD vaccine is highly immunogenic and a broad-spectrum vaccine candidate to combat SARS-CoV-2 variants including Omicron.
Research on multiple transient modeling scheme for full-cycle design of the 12-pulse PSR rectifier
Authors: Yuan Dongsheng , Yin Zhonggang , Wang Shuhong , Duan Nana , Zhang Yanqing 
Published: January 2023

Purpose
This paper aims to propose a novel multiple transient modeling scheme for the 12-pulse phase-shifting reactor (PSR) rectifier to enhance the efficiency of full-cycle design evaluation.

Design/methodology/approach
The detailed time-domain method is adopted to model the rectifier at the behavioral layer. The diode bridges/transformer model at the architecture layer is established by using the switch function and Park transformation. The frequency domain model at the functional layer is derived with the time-varying Fourier decomposition and frequency-shifting. At the component layer, the magneto-thermal characteristics of the rectifier are analyzed with field-circuit and magnetic-thermal coupling methods. A computer-aided design program integrating multiple modeling is also developed for industrial product design.

Findings
The function layer modeling is preferred in the initial design stage, making up for the lack of modeling accuracy at the architectural layer and the lack of modeling rapidity at the behavioral layer. The component modeling is irreplaceable for the detailed evaluation in the latter design stage. The multiple modeling scheme based on the four-layer modeling helps the designers achieve high-quality products with a short development cycle.

Originality/value
The singular transient modeling cannot cover the needs of different stages in the full-cycle design evaluation. This paper fills this gap with a novel multiple modeling scheme. Meanwhile, the proposed multiple modeling scheme and developed computer-aided design program provide a great convenience for full cycle design evaluation of the 12-pulse PSR rectifier.