bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative proteomics defines mechanisms of antiviral defence and cell death during modified vaccinia Ankara infection
Authors: Albarnaz Jonas D. , Kite Joanne , Oliveira Marisa , Li Hanqi , Di Ying , Christensen Maria H. , Paulo Joao A. , Antrobus Robin , Gygi Steven P. , Schmidt Florian I. , Huttlin Edward L. , Smith Geoffrey L. , Weekes Michael P. 
Published: December 2023

AbstractModified vaccinia Ankara (MVA) virus does not replicate in human cells and is the vaccine deployed to curb the current outbreak of mpox. Here, we conduct a multiplexed proteomic analysis to quantify >9000 cellular and ~80% of viral proteins throughout MVA infection of human fibroblasts and macrophages. >690 human proteins are down-regulated >2-fold by MVA, revealing a substantial remodelling of the host proteome. >25% of these MVA targets are not shared with replication-competent vaccinia. Viral intermediate/late gene expression is necessary for MVA antagonism of innate immunity, and suppression of interferon effectors such as ISG20 potentiates virus gene expression. Proteomic changes specific to infection of macrophages indicate modulation of the inflammatory response, including inflammasome activation. Our approach thus provides a global view of the impact of MVA on the human proteome and identifies mechanisms that may underpin its abortive infection. These discoveries will prove vital to design future generations of vaccines.
STalign: Alignment of spatial transcriptomics data using diffeomorphic metric mapping
Authors: Clifton Kalen , Anant Manjari , Aihara Gohta , Atta Lyla , Aimiuwu Osagie K. , Kebschull Justus M. , Miller Michael I. , Tward Daniel , Fan Jean 
Published: December 2023

AbstractSpatial transcriptomics (ST) technologies enable high throughput gene expression characterization within thin tissue sections. However, comparing spatial observations across sections, samples, and technologies remains challenging. To address this challenge, we develop STalign to align ST datasets in a manner that accounts for partially matched tissue sections and other local non-linear distortions using diffeomorphic metric mapping. We apply STalign to align ST datasets within and across technologies as well as to align ST datasets to a 3D common coordinate framework. We show that STalign achieves high gene expression and cell-type correspondence across matched spatial locations that is significantly improved over landmark-based affine alignments. Applying STalign to align ST datasets of the mouse brain to the 3D common coordinate framework from the Allen Brain Atlas, we highlight how STalign can be used to lift over brain region annotations and enable the interrogation of compositional heterogeneity across anatomical structures. STalign is available as an open-source Python toolkit at https://github.com/JEFworks-Lab/STalign and as Supplementary Software with additional documentation and tutorials available at https://jef.works/STalign.
IgG and IgM cooperate in coating of intestinal bacteria in IgA deficiency
Authors: Eriksen Carsten , Moll Janne Marie , Myers Pernille Neve , Pinto Ana Rosa Almeida , Danneskiold-Samsøe Niels Banhos , Dehli Rasmus Ibsen , Rosholm Lisbeth Buus , Dalgaard Marlene Danner , Penders John , Jonkers Daisy MAE , Pan-Hammarström Qiang , Hammarström Lennart , Kristiansen Karsten , Brix Susanne 
Published: December 2023

AbstractImmunoglobulin A (IgA) is acknowledged to play a role in the defence of the mucosal barrier by coating microorganisms. Surprisingly, IgA-deficient humans exhibit few infection-related complications, raising the question if the more specific IgG may help IgM in compensating for the lack of IgA. Here we employ a cohort of IgA-deficient humans, each paired with IgA-sufficient household members, to investigate multi-Ig bacterial coating. In IgA-deficient humans, IgM alone, and together with IgG, recapitulate coating of most bacterial families, despite an overall 3.6-fold lower Ig-coating. Bacterial IgG coating is dominated by IgG1 and IgG4. Single-IgG2 bacterial coating is sparse and linked to enhanced Escherichia coli load and TNF-α. Although single-IgG2 coating is 1.6-fold more prevalent in IgA deficiency than in healthy controls, it is 2-fold less prevalent than in inflammatory bowel disease. Altogether we demonstrate that IgG assists IgM in coating of most bacterial families in the absence of IgA and identify single-IgG2 bacterial coating as an inflammatory marker.
A toolkit for capturing a representative and equitable sample in health research
Authors: Retzer Ameeta , Ciytak Bircan , Khatsuria Foram , El-awaisi Juma , Harris Isobel M. , Chapman Laura , Kelly Tony , Richards Jenny , Lam Emily , Newsome Philip N. , Calvert Melanie ,   NIHR Birmingham Biomedical Research Centre REP-EQUITY Group, El-awaisi Juma , Filer Andrew , Shetty Shishir , Parish Jo , Watson Steve , Sapey Elizabeth , Gillet Caroline , Palmer Jo , Yonel Zehra , Miah Zohur , Alderman Joseph , Laws Elinor , Liu Xiaoxuan 
Published: December 2023

AbstractResearch participants often do not represent the general population. Systematic exclusion of particular groups from research limits the generalizability of research findings and perpetuates health inequalities. Groups considered underserved by research include those whose inclusion is lower than expected based on population estimates, those with a high healthcare burden but limited research participation opportunities and those whose healthcare engagement is less than others. The REP-EQUITY toolkit guides representative and equitable inclusion in research. The toolkit was developed through a methodological systematic review and synthesis and finalized in a consensus workshop with 24 participants. The REP-EQUITY toolkit describes seven steps for investigators to consider in facilitating representative and equitable sample selection. This includes clearly defining (1) the relevant underserved groups, (2) the aims relating to equity and representativeness, (3) the sample proportion of individuals with characteristics associated with being underserved by research, (4) the recruitment goals, (5) the strategies by which external factors will be managed, (6) the methods by which representation in the final sample will be evaluated and (7) the legacy of having used the toolkit. Using the REP-EQUITY toolkit could promote trust between communities and research institutions, increase diverse participation in research and improve the generalizability of health research. National Institute for Health and Care Research PROSPERO identifier: CRD42022355391.
FilGAP regulates tumor growth in Glioma through the regulation of mTORC1 and mTORC2
Authors: Tsutsumi Koji , Nohara Ayumi , Tanaka Taiki , Murano Moe , Miyagaki Yurina , Ohta Yasutaka 
Published: December 2023

AbstractThe mechanistic target of rapamycin (mTOR) is a serine/threonine protein kinase that forms the two different protein complexes, known as mTORC1 and mTORC2. mTOR signaling is activated in a variety of tumors, including glioma that is one of the malignant brain tumors. FilGAP (ARHGAP24) is a negative regulator of Rac, a member of Rho family small GTPases. In this study, we found that FilGAP interacts with mTORC1/2 and is involved in tumor formation in glioma. FilGAP interacted with mTORC1 via Raptor and with mTORC2 via Rictor and Sin1. Depletion of FilGAP in KINGS-1 glioma cells decreased phosphorylation of S6K and AKT. Furthermore, overexpression of FilGAP increased phosphorylation of S6K and AKT, suggesting that FilGAP activates mTORC1/2. U-87MG, glioblastoma cells, showed higher mTOR activity than KINGS-1, and phosphorylation of S6K and AKT was not affected by suppression of FilGAP expression. However, in the presence of PI3K inhibitors, phosphorylation of S6K and AKT was also decreased in U-87MG by depletion of FilGAP, suggesting that FilGAP may also regulate mTORC2 in U-87MG. Finally, we showed that depletion of FilGAP in KINGS-1 and U-87MG cells significantly reduced spheroid growth. These results suggest that FilGAP may contribute to tumor growth in glioma by regulating mTORC1/2 activities.
Hippocampal CaMKII inhibition induces reactivation-dependent amnesia for extinction memory and causes fear relapse
Authors: Radiske Andressa , de Castro Carla Miranda , Rossato Janine I. , Gonzalez Maria Carolina , Cammarota Martín 
Published: December 2023

AbstractHippocampal GluN2B subunit-containing NMDAR (GluN2B-NMDAR) activation during recall destabilizes fear extinction memory, which must undergo brain-derived neurotrophic factor (BDNF)-dependent reconsolidation to persist. Ca2+/calmodulin-dependent protein kinase II (CaMKII) is a Ser/Thr protein kinase essential for hippocampus-dependent memory processing that acts downstream GluN2B-NMDAR and controls BDNF expression, but its participation in fear extinction memory reconsolidation has not yet been studied. Using a combination of pharmacological and behavioral tools, we found that in adult male Wistar rats, intra dorsal-CA1 administration of the CaMKII inhibitors autocamtide-2-related inhibitory peptide (AIP) and KN-93, but not of their inactive analogs scrambled AIP and KN-92, after fear extinction memory recall impaired extinction and caused GluN2B-NMDAR-dependent recovery of fear. Our results indicate that hippocampal CaMKII is necessary for fear extinction reconsolidation, and suggest that modulation of its activity around the time of recall controls the inhibition that extinction exerts on learned fear.
Designing secure PUF-based authentication protocols for constrained environments
Authors: Lee Sang-Woong , Safkhani Masoumeh , Le Quynh , Ahmed Omed Hassan , Hosseinzadeh Mehdi , Rahmani Amir Masoud , Bagheri Nasour 
Published: December 2023

AbstractPhysical Unclonable Functions (PUFs) are widely used in cryptographic authentication and key-agreement protocols due to their unique physical properties. This article presents a comprehensive cryptanalysis of two recently developed authentication protocols, namely PLAKE and EV-PUF, both relying on PUFs. Our analysis reveals significant vulnerabilities in these protocols, including susceptibility to impersonation and key leakage attacks, which pose serious threats to the security of the underlying systems. In the case of PLAKE, we propose an attack that can extract the shared secret key with negligible complexity by eavesdropping on consecutive protocol sessions. Similarly, we demonstrate an efficient attack against EV-PUF that enables the determination of the shared key between specific entities. Furthermore, we highlight the potential for a single compromised client in the EV-PUF protocol to compromise the security of the entire network, leaving it vulnerable to pandemic attacks. These findings underscore the critical importance of careful design and rigorous evaluation when developing PUF-based authentication protocols. To address the identified vulnerabilities, we present an improved PUF-based authentication protocol that ensures robust security against all the attacks described in the context of PLAKE and EV-PUF. Through this research, we contribute to the field by exposing vulnerabilities in existing PUF-based authentication protocols and offering an improved protocol that enhances security and safeguards against various attack vectors. This work serves as a valuable reference for researchers and practitioners involved in the design and implementation of secure authentication schemes for IoT systems and dynamic charging systems for electric vehicles.
Effects of mobile phone electromagnetic fields on brain waves in healthy volunteers
Authors: van der Meer Johan N. , Eisma Yke B. , Meester Ronald , Jacobs Marc , Nederveen Aart J. 
Published: December 2023

AbstractThe interaction between biological tissue and electromagnetic fields (EMF) is a topic of increasing interest due to the rising prevalence of background EMF in the past decades. Previous studies have attempted to measure the effects of EMF on brainwaves using EEG recordings, but are typically hampered by experimental and environmental factors. In this study, we present a framework for measuring the impact of EMF on EEG while controlling for these factors. A Bayesian statistical approach is employed to provide robust statistical evidence of the observed EMF effects. This study included 32 healthy participants in a double-blinded crossover counterbalanced design. EEG recordings were taken from 63 electrodes across 6 brain regions. Participants underwent a measurement protocol comprising two 18-min sessions with alternating blocks of eyes open (EO) and eyes closed (EC) conditions. Group 1 (n = 16) had EMF during the first session and sham during the second session; group 2 (n = 16) had the opposite. Power spectral density plots were generated for all sessions and brain regions. The Bayesian analysis provided statistical evidence for the presence of an EMF effect in the alpha band power density in the EO condition. This measurement protocol holds potential for future research on the impact of novel transmission protocols.
Dictionary-based matching graph network for biomedical named entity recognition
Authors: Lou Yinxia , Zhu Xun , Tan Kai 
Published: December 2023

AbstractBiomedical named entity recognition (BioNER) is an essential task in biomedical information analysis. Recently, deep neural approaches have become widely utilized for BioNER. Biomedical dictionaries, implemented through a masked manner, are frequently employed in these methods to enhance entity recognition. However, their performance remains limited. In this work, we propose a dictionary-based matching graph network for BioNER. This approach utilizes the matching graph method to project all possible dictionary-based entity combinations in the text onto a directional graph. The network is implemented coherently with a bi-directional graph convolutional network (BiGCN) that incorporates the matching graph information. Our proposed approach fully leverages the dictionary-based matching graph instead of a simple masked manner. We have conducted numerous experiments on five typical Bio-NER datasets. The proposed model shows significant improvements in F1 score compared to the state-of-the-art (SOTA) models: 2.8% on BC2GM, 1.3% on BC4CHEMD, 1.1% on BC5CDR, 1.6% on NCBI-disease, and 0.5% on JNLPBA. The results show that our model, which is superior to other models, can effectively recognize natural biomedical named entities.
Socioeconomic status and healthcare utilization disparities among children with epilepsy in the United States: Results from a nationally representative sample
Authors: Muthiah Nallammai , Rothenberger Scott , Abel Taylor J. 
Published: December 2023

AbstractEpilepsy affects 1% of the US population. Healthcare disparities are well-studied among adults with epilepsy but less so among children. We examined whether children with epilepsy (1) have lower income than or (2) utilize the emergency department (ED) differently from children without epilepsy, and (3) if income moderates ED utilization. Data from the 2016–2019 National Survey of Children’s Health were used to identify children with active “epilepsy or seizure disorder”. Children with versus without epilepsy were compared. Income and ED visits were modeled with logistic and Poisson regressions. This analysis included 131,326 children; 835 were diagnosed with epilepsy. Estimated population prevalence of epilepsy was 0.6%. Children from higher-income-households were less likely to have epilepsy (aOR: 0.7). Children with epilepsy were more likely to visit EDs (aOR = 10.2), see healthcare professionals (aOR: 2.7), and receive care from specialists (aOR: 10.3). Income moderated the relationship between having epilepsy and ED visits. 7.7% of children with epilepsy did not receive needed healthcare. Some barriers were acquiring appointments (aOR: 3.9) and transportation (aOR: 4.7). In conclusion, children with epilepsy were more likely than children without epilepsy to live in lower-income-households, visit EDs, see healthcare professionals, and not receive needed healthcare. Barrier-specific policy interventions may improve medical access for children with epilepsy.
Stability analysis of dual solutions for mixed convection and thermal radiation with hybrid nanofluid flow past shrinking/stretching curved surface
Authors: Ibrahim Wubshet , Gizewu Tezera 
Published: December 2023

AbstractThis study portrays the stability analysis and dual solutions of mixed convection and thermal radiation of hybrid nano-fluid flow past stretching/shrinking a curved surface in the presence of injection/suction conditions. A hybrid nano-fluid, in which water is used as the base fluid, copper and alumina are used as nano-particles, and the magnetic field is taken into account. The present study’s findings will provide fruitful implications for future research in the field of fluid dynamics. The bvp4c method using Matlab software is implemented to get the numerical solution of the nonlinear partial differential equation transformed into the ordinary differential equation. The behavior of the first and second solutions under the governing parameters on the curved surface of dimensionless velocity $$g'(\xi )$$

g
′

(
ξ
)

, shear stress profile $$g''(\xi )$$

g

′
′

(
ξ
)

, temperature profile $$\theta (\xi )$$

θ
(
ξ
)

, skin friction coefficient Cfs, and local Nusselt’s number Nus were visualized in figurative and tabular form. From this the following are investigated: as the values of $$\phi j$$

ϕ
j

increase, the velocity profile for the second solution decreases, and the opposite trend is observed for the first solution. For the values of K and $$\lambda 1$$

λ
1

, the shear stress profile increased for the first solution, and the opposite trend was observed for the second solution, though after some interval points, the inverse of this statement was observed.For the values of $$S,Pr,Rd,M, \;\text{and}\; \lambda$$

S
,
P
r
,
R
d
,
M
,

and

λ

, the upwind thermal boundary layer of the first solution is larger than the second solution.For the value of M uphill, the estimation of the absolute value of $$\lambda ci$$

λ
c
i

increases for both the skin friction coefficient and the local Nusselt number. In the second solution, increasing the values of $$\beta$$
β
, Pr, S, Ec, and M has a similar effect on $$g''(0)$$

g

′
′

(
0
)

, Cfs, -$$\theta '(0)$$

θ
′

(
0
)

, and Nus. In the first solution, increasing the values of Ec, S, and Pr on $$g''(0)$$

g

′
′

(
0
)

and Cfs results in a decrease. The first solution has a positive eigenvalue, whereas the second solution has a negative eigenvalue. Agreement between the present analysis and literature is acceptable.
Self-supervised representation learning using feature pyramid siamese networks for colorectal polyp detection
Authors: Gan Tianyuan , Jin Ziyi , Yu Liangliang , Liang Xiao , Zhang Hong , Ye Xuesong 
Published: December 2023

AbstractColorectal cancer is a leading cause of cancer-related deaths globally. In recent years, the use of convolutional neural networks in computer-aided diagnosis (CAD) has facilitated simpler detection of early lesions like polyps during real-time colonoscopy. However, the majority of existing techniques require a large training dataset annotated by experienced experts. To alleviate the laborious task of image annotation and utilize the vast amounts of readily available unlabeled colonoscopy data to further improve the polyp detection ability, this study proposed a novel self-supervised representation learning method called feature pyramid siamese networks (FPSiam). First, a feature pyramid encoder module was proposed to effectively extract and fuse both local and global feature representations among colonoscopic images, which is important for dense prediction tasks like polyp detection. Next, a self-supervised visual feature representation containing the general feature of colonoscopic images is learned by the siamese networks. Finally, the feature representation will be transferred to the downstream colorectal polyp detection task. A total of 103 videos (861,400 frames), 100 videos (24,789 frames), and 60 videos (15,397 frames) in the LDPolypVideo dataset are used to pre-train, train, and test the performance of the proposed FPSiam and its counterparts, respectively. The experimental results have illustrated that our FPSiam approach obtains the optimal capability, which is better than that of other state-of-the-art self-supervised learning methods and is also higher than the method based on transfer learning by 2.3 mAP and 3.6 mAP for two typical detectors. In conclusion, FPSiam provides a cost-efficient solution for developing colorectal polyp detection systems, especially in conditions where only a small fraction of the dataset is labeled while the majority remains unlabeled. Besides, it also brings fresh perspectives into other endoscopic image analysis tasks.
Phenolic profiles and in vitro biochemical properties of Thai herb ingredients for chronic diseases prevention
Authors: On-Nom Nattira , Thangsiri Sirinapa , Inthachat Woorawee , Temviriyanukul Piya , Trisonthi Piyapat , Chupeerach Chaowanee , Siriwan Dalad , Suttisansanee Uthaiwan 
Published: December 2023

AbstractTraditional remedies using natural ingredients have been handed down over generations, providing collective information for the development of modern therapeutics. These natural products have a long history of safe consumption with curative effects but lack of scientific-based evidence hinders the mass production of new remedies containing active ingredients with particular medicinal properties. This research investigated the phenolic profiles and biochemical properties of 29 herbal ingredients identified in two traditional Thai remedies, Prasachandaeng (PSCD) and Chantaharuethai (CHRT), and their effectiveness in combating chronic diseases. These two traditional remedies are used to reduce fever but some ingredients have been previously reported to possess other health-related properties. Statistical analysis by TOPSIS indicated that Biancaea sappan (L.) Tod. extract exhibited the highest overall closeness coefficient (C) score analyzed from all variables including total phenolic contents, antioxidant potentials, and enzyme inhibitions. Bouea macrophylla Griff. extract showed potential as an effective agent against diabetes through inhibition of two carbohydrate degrading enzymes, α-glucosidase and α-amylase, while Dischidia major (Vahl) Merr. showed strong properties as an anti-angiotensin-converting enzyme, leading to the control of hypertension. Dracaena cochinchinensis (Lour.) S.C. Chen effectively controlled the progression of Alzheimer’s disease through the inhibition of cholinergic and β-amyloid formation enzymes. These results can be used as preliminary data for the development of new remedies to prevent or treat particular chronic diseases.