bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-term behavioral adaptation of Oldowan toolmakers to resource-constrained environments at 2.3 Ma in the Lower Omo Valley (Ethiopia)
Authors: Delagnes Anne , Galland Aline , Gravina Brad , Bertran Pascal , Corbé Marion , Brenet Michel , Hailu Haregwin Belete , Sissay Fikeru Mekonenn , Araya Bisrat Gebreegziabher , Woldetsadik Misganaw Gebremichael , Boisserie Jean-Renaud 
Published: September 2023

AbstractThe long stratigraphic sequence of the Shungura Formation in the Lower Omo Valley documents 3 million years (Ma) of hominin evolution, which, when combined with detailed paleo-depositional environmental data, opens new perspectives for understanding the complex interactions between hominin landscape use and the development of stone tool-mediated activities. Stone tool assemblages produced by Paranthropus aethiopicus and/or a species of early Homo from ~ 2.3 Ma, reflect their ability to deal with the raw material scarce environment of the Lower Omo Valley. It remains to be seen whether this activity can be related to a single, brief occupation event or the expression of an emergent new adaptation. Here we report on the newly investigated site complex of OMO 79, which produced the first evidence for multiple phases of hominin tool-making and use in the Shungura Formation. The development of this long-lasting techno-economic behavior marks a cognitive tipping point around 2.3 Ma in the Lower Omo Valley, evidenced by the adaptability of the early hominins to resource-constrained environments.
Proteomic and phosphoproteomic analyses of myectomy tissue reveals difference between sarcomeric and genotype-negative hypertrophic cardiomyopathy
Authors: Garmany Ramin , Bos J. Martijn , Dasari Surendra , Johnson Kenneth L. , Tester David J. , Giudicessi John R. , dos Remedios Cristobal , Maleszewski Joseph J. , Ommen Steve R. , Dearani Joseph A. , Ackerman Michael J. 
Published: September 2023

AbstractHypertrophic cardiomyopathy (HCM) is a genetically heterogenous condition with about half of cases remaining genetically elusive or non-genetic in origin. HCM patients with a positive genetic test (HCMSarc) present earlier and with more severe disease than those with a negative genetic test (HCMNeg). We hypothesized these differences may be due to and/or reflect proteomic and phosphoproteomic differences between the two groups. TMT-labeled mass spectrometry was performed on 15 HCMSarc, 8 HCMNeg, and 7 control samples. There were 243 proteins differentially expressed and 257 proteins differentially phosphorylated between HCMSarc and HCMNeg. About 90% of pathways altered between genotypes were in disease-related pathways and HCMSarc showed enhanced proteomic and phosphoproteomic alterations in these pathways. Thus, we show HCMSarc has enhanced proteomic and phosphoproteomic dysregulation observed which may contribute to the more severe disease phenotype.
Extracting and visualizing hidden activations and computational graphs of PyTorch models with TorchLens
Authors: Taylor JohnMark , Kriegeskorte Nikolaus 
Published: September 2023

AbstractDeep neural network models (DNNs) are essential to modern AI and provide powerful models of information processing in biological neural networks. Researchers in both neuroscience and engineering are pursuing a better understanding of the internal representations and operations that undergird the successes and failures of DNNs. Neuroscientists additionally evaluate DNNs as models of brain computation by comparing their internal representations to those found in brains. It is therefore essential to have a method to easily and exhaustively extract and characterize the results of the internal operations of any DNN. Many models are implemented in PyTorch, the leading framework for building DNN models. Here we introduce TorchLens, a new open-source Python package for extracting and characterizing hidden-layer activations in PyTorch models. Uniquely among existing approaches to this problem, TorchLens has the following features: (1) it exhaustively extracts the results of all intermediate operations, not just those associated with PyTorch module objects, yielding a full record of every step in the model's computational graph, (2) it provides an intuitive visualization of the model's complete computational graph along with metadata about each computational step in a model's forward pass for further analysis, (3) it contains a built-in validation procedure to algorithmically verify the accuracy of all saved hidden-layer activations, and (4) the approach it uses can be automatically applied to any PyTorch model with no modifications, including models with conditional (if–then) logic in their forward pass, recurrent models, branching models where layer outputs are fed into multiple subsequent layers in parallel, and models with internally generated tensors (e.g., injections of noise). Furthermore, using TorchLens requires minimal additional code, making it easy to incorporate into existing pipelines for model development and analysis, and useful as a pedagogical aid when teaching deep learning concepts. We hope this contribution will help researchers in AI and neuroscience understand the internal representations of DNNs.
Generative design of large-scale fluid flow structures via steady-state diffusion-based dehomogenization
Authors: Hankins Sarah N. , Zhou Yuqing , Lohan Danny J. , Dede Ercan M. 
Published: September 2023

AbstractA computationally efficient dehomogenization technique was developed based on a bioinspired diffusion-based pattern generation algorithm to convert an orientation field into explicit large-scale fluid flow channel structures. Due to the transient nature of diffusion and reaction, most diffusion-based pattern generation models were solved in both time and space. In this work, we remove the temporal dependency and directly solve a steady-state equation. The steady-state Swift-Hohenberg model was selected due to its simplistic form as a single variable equation and intuitive parameter setting for pattern geometry control. Through comparison studies, we demonstrated that the steady-state model can produce statistically equivalent solutions to the transient model with potential computational speedup. This work marks an early foray into the use of steady-state pattern generation models for rapid dehomogenization in multiphysics engineering design applications. To highlight the benefits of this approach, the steady-state model was used to dehomogenize optimized orientation fields for the design of microreactor flow structures involving hundreds of microchannels in combination with a porous gas diffusion layer. A homogenization-based multi-objective optimization routine was used to produce a multi-objective Pareto set that explored the trade-offs between flow resistance and reactant distribution variability. In total, the diffusion-based dehomogenization method enabled the generation of 200 unique and distinctly different microreactor flow channel designs. The proposed dehomogenization approach permits comprehensive exploration of numerous bioinspired solutions capturing the full complexity of the optimization and Swift-Hohenberg design space.
Health related quality of life in anti interferon γ autoantibody associated immunodeficiency syndrome measured with EQ5D5L and SF36
Authors: Temsangsukmanee Jirat , Laisuan Wannada , Thadanipon Kunlawat , Pisitkun Prapaporn , Ngamjanyaporn Pintip , Suangtamai Thanitta , Oncham Supa , Chantharit Prawat , Rotjanapan Porpon 
Published: September 2023

AbstractThe anti-IFN-γ disease is a rare condition characterized by recurrent and persistent infections, potentially impacting the quality of life (QoL). However, comprehensive data on QoL in this population are lacking. This study aims to evaluate the QoL of Anti-IFN-γ patients compared to healthy control and explore potential differences in QoL between patients in the active and remission stages. A cross-sectional study design was conducted, recruiting 38 Anti-IFN-γ patients and 38 sex- and age-matched healthy controls. QoL assessment utilized the 5-level EuroQol-5 Dimension (EQ-5D-5L) and the 36-Item Short Form Health Survey (SF-36). The Anti-IFN-γ group had a mean age of 57.37 (± 10.32) years, with females comprising 60.53%. Among the Anti-IFN-γ patients, 55.26% were classified as having active disease. 63% of Anti-IFN-γ patients received Immunosuppressive treatments. Anti-IFN-γ disease exhibited a significant negative impact on HRQoL, as evidenced by lower utility scores in EQ-5D-5L and lower physical and mental component scores in SF-36 across various domains, including physical function, role physical, general health, bodily pain, social functioning, role emotion and mental health, compared to healthy controls. Additionally, patients in the active disease displayed lower scores in multiple domains, including bodily pain, general health, role emotion and mental health, and a lower utility score in EQ-5D-5L compared to patients in remission. The anti-IFN-γ disease significantly impairs the HRQoL of affected individuals compared to healthy controls. However, effective treatment leading to remission holds promise for improving the HRQoL of patients with Anti-IFN-γ disease.
The transcription factor NRF1 (NFE2L1) activates aggrephagy by inducing p62 and GABARAPL1 after proteasome inhibition to maintain proteostasis
Authors: Hatanaka Atsushi , Nakada Sota , Matsumoto Gen , Satoh Katsuya , Aketa Iori , Watanabe Akira , Hirakawa Tomoaki , Tsujita Tadayuki , Waku Tsuyoshi , Kobayashi Akira 
Published: September 2023

AbstractThe ubiquitin‒proteasome system (UPS) and autophagy are the two primary cellular pathways of misfolded or damaged protein degradation that maintain cellular proteostasis. When the proteasome is dysfunctional, cells compensate for impaired protein clearance by activating aggrephagy, a type of selective autophagy, to eliminate ubiquitinated protein aggregates; however, the molecular mechanisms by which impaired proteasome function activates aggrephagy remain poorly understood. Here, we demonstrate that activation of aggrephagy is transcriptionally induced by the transcription factor NRF1 (NFE2L1) in response to proteasome dysfunction. Although NRF1 has been previously shown to induce the expression of proteasome genes after proteasome inhibition (i.e., the proteasome bounce-back response), our genome-wide transcriptome analyses identified autophagy-related p62/SQSTM1 and GABARAPL1 as genes directly targeted by NRF1. Intriguingly, NRF1 was also found to be indispensable for the formation of p62-positive puncta and their colocalization with ULK1 and TBK1, which play roles in p62 activation via phosphorylation. Consistently, NRF1 knockdown substantially reduced the phosphorylation rate of Ser403 in p62. Finally, NRF1 selectively upregulated the expression of GABARAPL1, an ATG8 family gene, to induce the clearance of ubiquitinated proteins. Our findings highlight the discovery of an activation mechanism underlying NRF1-mediated aggrephagy through gene regulation when proteasome activity is impaired.
Study on spatiotemporal distribution characteristics and driving factors of carbon emission in Anhui Province
Authors: Xu Jing 
Published: September 2023

AbstractCarbon emission is related to global ecological security, and economic development inevitably leads to an increase in carbon emission. In recent years, as a rapidly developing province in China's economy, Anhui Province has experienced significant differences in the spatiotemporal distribution of carbon emission in different regions due to differences in development foundation, urbanization level, population size, industrial structure, etc., providing representative empirical cases for research. Based on the carbon emission data of Anhui Province before the COVID-19, this study used exploratory spatial data analysis method and Geodetector to analyze the spatial and temporal distribution characteristics and drivers of carbon emission in Anhui Province. The study found that (1) the spatial differentiation and spatial correlation of carbon emission in Anhui Province are significant, At the beginning, it shows the characteristics of "high north and low south" and "high west and low east", and then the "core–edge" structure of carbon emission becomes obvious. Carbon emission hotspot areas increase and then decrease, mainly in Hefei, Fuyang and Chuzhou City, etc. The coldspot areas are mainly located in the southern and western mountainous areas, and the degree of aggregation is decreasing year by year. (3) The level of urbanization, economic development and population size are the main driving factors of the spatial variation of carbon emissions, while the industrial structure has the least influence. And most factors produce nonlinear enhancement when spatially superimposed with other factors. (4) The high value areas of economic development, population density, secondary industry structure, and energy intensity are all at high levels of carbon emission, and a combination of factors leads to the creation of high risk areas for carbon emission. The study provides a basis for reducing carbon emission in the next stage of Anhui Province, focusing on key carbon emission areas, and sustainable development.
TNFα induces matrix metalloproteinase-9 expression in monocytic cells through ACSL1/JNK/ERK/NF-kB signaling pathways
Authors: Al-Roub Areej , Akhter Nadeem , Al-Rashed Fatema , Wilson Ajit , Alzaid Fawaz , Al-Mulla Fahd , Sindhu Sardar , Ahmad Rasheed 
Published: September 2023

AbstractStudies have established the association between increased plasma levels of matrix metalloproteinase (MMP)-9 and adipose tissue inflammation. Tumor necrosis factor α (TNFα) was elevated in obesity and is involved in the induction of MMP-9 in monocytic cells. However, the underlying molecular mechanism was incompletely understood. As per our recent report, TNFα mediates inflammatory responses through long-chain acyl-CoA synthetase 1 (ACSL1). Therefore, we further investigated the role of ACSL1 in TNFα-mediated MMP-9 secretion in monocytic cells. THP-1 cells and primary monocytes were used to study MMP-9 expression. mRNA and protein levels of MMP-9 were determined by qRT-PCR and ELISA, respectively. Signaling pathways were studied using Western blotting, inhibitors, and NF-kB/AP1 reporter cells. We found that THP-1 cells and primary human monocytes displayed increased MMP-9 mRNA expression and protein secretion after incubation with TNFα. ACSL1 inhibition using triacsin C significantly reduced the expression of MMP-9 in the THP-1 cells. However, the inhibition of β-oxidation and ceramide biosynthesis did not affect the TNFα-induced MMP-9 production. Using small interfering RNA-mediated ACSL1 knockdown, we further confirmed that TNFα-induced MMP-9 expression/secretion was significantly reduced in ACSL1-deficient cells. TNFα-mediated MMP-9 expression was also significantly reduced by the inhibition of ERK1/ERK2, JNK, and NF-kB. We further observed that TNFα induced phosphorylation of SAPK/JNK (p54/46), ERK1/2 (p44/42 MAPK), and NF-kB p65. ACSL1 inhibition reduced the TNFα-mediated phosphorylation of SAPK/JNK, c-Jun, ERK1/2, and NF-kB. In addition, increased NF-κB/AP-1 activity was inhibited in triacsin C treated cells. Altogether, our findings suggest that ACSL1/JNK/ERK/NF-kB axis plays an important role in the regulation of MMP-9 induced by TNFα in monocytic THP-1 cells.
A molecular analysis of substituted phenylethylamines as potential microtubule targeting agents through in silico methods and in vitro microtubule-polymerization activity
Authors: De Abreu Isadora Rocha , Barkdull Allison , Munoz James R. , Smith Robert P. , Craddock Travis J. A. 
Published: September 2023

AbstractNatural phenethylamines are trace amine neurotransmitters associated with dopamine transmission and related illnesses such Parkinson’s disease, and addiction. Synthetic phenethylamines can have psychoactive and hallucinogenic effects due to their high affinity with the 5-HT2A receptor. Evidence indicates phenethylamines can directly alter the microtubule cytoskeleton being structurally similar to the microtubule destabilizing agent colchicine, however little work has been done on this interaction. As microtubules provide neuron structure, intracellular transport, and influence synaptic plasticity the interaction of phenethylamines with microtubules is important for understanding the potential harms, or potential pharmaceutical use of phenethylamines. We investigated 110 phenethylamines and their interaction with microtubules. Here we performed molecular docking of these compounds at the colchicine binding site and ranked them via binding energy. The top 10% of phenethylamines were further screened based on pharmacokinetic and physicochemical properties derived from SwissADME and LightBBB. Based on these properties 25B-NBF, 25C-NBF, and DMBMPP were tested in in vitro microtubule polymerization assays showing that they alter microtubule polymerization dynamics in a dose dependent manner. As these compounds can rapidly cross the blood brain barrier and directly affect cytoskeletal dynamics, they have the potential to modulate cytoskeletal based neural plasticity. Further investigations into these mechanisms are warranted.
Single-trial visually evoked potentials predict both individual choice and market outcomes
Authors: Veillette John P. , Heald Shannon L. M. , Wittenbrink Benjamin , Reis Katherine S. , Nusbaum Howard C. 
Published: September 2023

AbstractA central assumption in the behavioral sciences is that choice behavior generalizes enough across individuals that measurements from a sampled group can predict the behavior of the population. Following from this assumption, the unit of behavioral sampling or measurement for most neuroimaging studies is the individual; however, cognitive neuroscience is increasingly acknowledging a dissociation between neural activity that predicts individual behavior and that which predicts the average or aggregate behavior of the population suggesting a greater importance of individual differences than is typically acknowledged. For instance, past work has demonstrated that some, but not all, of the neural activity observed during value-based decision-making is able to predict not just individual subjects’ choices but also the success of products on large, online marketplaces—even when those two behavioral outcomes deviate from one another—suggesting that some neural component processes of decision-making generalize to aggregate market responses more readily across individuals than others do. While the bulk of such research has highlighted affect-related neural responses (i.e. in the nucleus accumbens) as a better predictor of group-level behavior than frontal cortical activity associated with the integration of more idiosyncratic choice components, more recent evidence has implicated responses in visual cortical regions as strong predictors of group preference. Taken together, these findings suggest a role of neural responses during early perception in reinforcing choice consistency across individuals and raise fundamental scientific questions about the role sensory systems in value-based decision-making processes. We use a multivariate pattern analysis approach to show that single-trial visually evoked electroencephalographic (EEG) activity can predict individual choice throughout the post-stimulus epoch; however, a nominally sparser set of activity predicts the aggregate behavior of the population. These findings support an account in which a subset of the neural activity underlying individual choice processes can scale to predict behavioral consistency across people, even when the choice behavior of the sample does not match the aggregate behavior of the population.
An example of governance for AI in health services from Aotearoa New Zealand
Authors: Whittaker R. , Dobson R. , Jin C. K. , Style R. , Jayathissa P. , Hiini K. , Ross K. , Kawamura K. , Muir P. ,   the Waitematā AI Governance Group, Mark A. , Armstrong D. , Frost E. , Buxton J. , Lunny J. , Andrew P. , Bloomfield S. , Puddle S. , Miles W. 
Published: September 2023

AbstractArtificial Intelligence (AI) is undergoing rapid development, meaning that potential risks in application are not able to be fully understood. Multiple international principles and guidance documents have been published to guide the implementation of AI tools in various industries, including healthcare practice. In Aotearoa New Zealand (NZ) we recognised that the challenge went beyond simply adapting existing risk frameworks and governance guidance to our specific health service context and population. We also deemed prioritising the voice of Māori (the indigenous people of Aotearoa NZ) a necessary aspect of honouring Te Tiriti (the Treaty of Waitangi), as well as prioritising the needs of healthcare service users and their families. Here we report on the development and establishment of comprehensive and effective governance over the development and implementation of AI tools within a health service in Aotearoa NZ. The implementation of the framework in practice includes testing with real-world proposals and ongoing iteration and refinement of our processes.
Transcriptome-wide association studies: recent advances in methods, applications and available databases
Authors: Mai Jialin , Lu Mingming , Gao Qianwen , Zeng Jingyao , Xiao Jingfa 
Published: September 2023

AbstractGenome-wide association study has identified fruitful variants impacting heritable traits. Nevertheless, identifying critical genes underlying those significant variants has been a great task. Transcriptome-wide association study (TWAS) is an instrumental post-analysis to detect significant gene-trait associations focusing on modeling transcription-level regulations, which has made numerous progresses in recent years. Leveraging from expression quantitative loci (eQTL) regulation information, TWAS has advantages in detecting functioning genes regulated by disease-associated variants, thus providing insight into mechanisms of diseases and other phenotypes. Considering its vast potential, this review article comprehensively summarizes TWAS, including the methodology, applications and available resources.
Real-time 31P NMR reveals different gradient strengths in polyphosphoester copolymers as potential MRI-traceable nanomaterials
Authors: Rheinberger Timo , Flögel Ulrich , Koshkina Olga , Wurm Frederik R. 
Published: September 2023

AbstractPolyphosphoesters (PPEs) are used in tissue engineering and drug delivery, as polyelectrolytes, and flame-retardants. Mostly polyphosphates have been investigated but copolymers involving different PPE subclasses have been rarely explored and the reactivity ratios of different cyclic phospholanes have not been reported. We synthesized binary and ternary PPE copolymers using cyclic comonomers, including side-chain phosphonates, phosphates, thiophosphate, and in-chain phosphonates, through organocatalyzed ring-opening copolymerization. Reactivity ratios were determined for all cases, including ternary PPE copolymers, using different nonterminal models. By combining different comonomers and organocatalysts, we created gradient copolymers with adjustable amphiphilicity and microstructure. Reactivity ratios ranging from 0.02 to 44 were observed for different comonomer sets. Statistical ring-opening copolymerization enabled the synthesis of amphiphilic gradient copolymers in a one-pot procedure, exhibiting tunable interfacial and magnetic resonance imaging (MRI) properties. These copolymers self-assembled in aqueous solutions, 31 P MRI imaging confirmed their potential as MRI-traceable nanostructures. This systematic study expands the possibilities of PPE-copolymers for drug delivery and theranostics.