bluuebunny/crossref_metadata_2025_split huggingface dataset:
Signaling pathways and targeted therapy for myocardial infarction
Authors: Zhang Qing , Wang Lu , Wang Shiqi , Cheng Hongxin , Xu Lin , Pei Gaiqin , Wang Yang , Fu Chenying , Jiang Yangfu , He Chengqi , Wei Quan 
Published: March 2022

AbstractAlthough the treatment of myocardial infarction (MI) has improved considerably, it is still a worldwide disease with high morbidity and high mortality. Whilst there is still a long way to go for discovering ideal treatments, therapeutic strategies committed to cardioprotection and cardiac repair following cardiac ischemia are emerging. Evidence of pathological characteristics in MI illustrates cell signaling pathways that participate in the survival, proliferation, apoptosis, autophagy of cardiomyocytes, endothelial cells, fibroblasts, monocytes, and stem cells. These signaling pathways include the key players in inflammation response, e.g., NLRP3/caspase-1 and TLR4/MyD88/NF-κB; the crucial mediators in oxidative stress and apoptosis, for instance, Notch, Hippo/YAP, RhoA/ROCK, Nrf2/HO-1, and Sonic hedgehog; the controller of myocardial fibrosis such as TGF-β/SMADs and Wnt/β-catenin; and the main regulator of angiogenesis, PI3K/Akt, MAPK, JAK/STAT, Sonic hedgehog, etc. Since signaling pathways play an important role in administering the process of MI, aiming at targeting these aberrant signaling pathways and improving the pathological manifestations in MI is indispensable and promising. Hence, drug therapy, gene therapy, protein therapy, cell therapy, and exosome therapy have been emerging and are known as novel therapies. In this review, we summarize the therapeutic strategies for MI by regulating these associated pathways, which contribute to inhibiting cardiomyocytes death, attenuating inflammation, enhancing angiogenesis, etc. so as to repair and re-functionalize damaged hearts.
Potential educational and workforce strategies to meet the oral health challenges of an increasingly older population: a qualitative study
Authors: Prosser Georgina M. , Louca Chris , Radford David R. 
Published: March 2022

Abstract
Introduction
The demographic shift in the age profile of the UK is well established. Older people have more complex requirements to maintain their oral health.

Objectives
This research explored Gerodontology with influential and recognised UK experts in Dental Public Health, Dental Education and Gerodontology. Three main topics were explored: the dental challenges associated with the ageing population, the role of dental care professionals (DCPs) and the training of undergraduate dental professionals.

Methods
Quantitative data from the literature were used to develop a topic guide for semi-structured interviews with a purposeful sample of nine participants. Initial analysis of the qualitative data was undertaken using NVivo V12 software and themes were identified. Final themes and subthemes were confirmed after a series of remote round table discussions.

Results
Four themes and 14 subthemes were identified. These included disagreements and agreements, the challenges of providing dental care to the older adult population, and the delivery of dental care by the dental team and finally education. All participants had significant concerns about the oral and dental challenges of the older population.

Conclusions
The themes that emerged were complex and overlapping. Better utilisation of all members of the dental workforce was reported to be an essential approach, as was reorientation of existing care models with a focus on prevention. Regarding undergraduate education, the consensus was that the training was not adequate for both current and future needs.
Improved prediction of protein-protein interactions using AlphaFold2
Authors: Bryant Patrick , Pozzati Gabriele , Elofsson Arne 
Published: March 2022

AbstractPredicting the structure of interacting protein chains is a fundamental step towards understanding protein function. Unfortunately, no computational method can produce accurate structures of protein complexes. AlphaFold2, has shown unprecedented levels of accuracy in modelling single chain protein structures. Here, we apply AlphaFold2 for the prediction of heterodimeric protein complexes. We find that the AlphaFold2 protocol together with optimised multiple sequence alignments, generate models with acceptable quality (DockQ ≥ 0.23) for 63% of the dimers. From the predicted interfaces we create a simple function to predict the DockQ score which distinguishes acceptable from incorrect models as well as interacting from non-interacting proteins with state-of-art accuracy. We find that, using the predicted DockQ scores, we can identify 51% of all interacting pairs at 1% FPR.
Estrogen receptor inhibition mediates radiosensitization of ER-positive breast cancer models
Authors: Michmerhuizen Anna R. , Lerner Lynn M. , Pesch Andrea M. , Ward Connor , Schwartz Rachel , Wilder-Romans Kari , Liu Meilan , Nino Charles , Jungles Kassidy , Azaria Ruth , Jelley Alexa , Zambrana Garcia Nicole , Harold Alexis , Zhang Amanda , Wharram Bryan , Hayes Daniel F. , Rae James M. , Pierce Lori J. , Speers Corey W. 
Published: March 2022

AbstractEndocrine therapy (ET) is an effective first-line therapy for women with estrogen receptor-positive (ER + ) breast cancers. While both ionizing radiation (RT) and ET are used for the treatment of women with ER+ breast cancer, the most effective sequencing of therapy and the effect of ET on tumor radiosensitization remains unclear. Here we sought to understand the effects of inhibiting estrogen receptor (ER) signaling in combination with RT in multiple preclinical ER+ breast cancer models. Clonogenic survival assays were performed using variable pre- and post-treatment conditions to assess radiosensitization with estradiol, estrogen deprivation, tamoxifen, fulvestrant, or AZD9496 in ER+ breast cancer cell lines. Estrogen stimulation was radioprotective (radiation enhancement ratios [rER]: 0.51–0.82). Conversely, when given one hour prior to RT, ER inhibition or estrogen depletion radiosensitized ER+ MCF-7 and T47D cells (tamoxifen rER: 1.50–1.60, fulvestrant rER: 1.76–2.81, AZD9496 rER: 1.33–1.48, estrogen depletion rER: 1.47–1.51). Combination treatment resulted in an increase in double-strand DNA (dsDNA) breaks as a result of inhibition of non-homologous end joining-mediated dsDNA break repair with no effect on homologous recombination. Treatment with tamoxifen or fulvestrant in combination with RT also increased the number of senescent cells but did not affect apoptosis or cell cycle distribution. Using an MCF-7 xenograft model, concurrent treatment with tamoxifen and RT was synergistic and resulted in a significant decrease in tumor volume and a delay in time to tumor doubling without significant toxicity. These findings provide preclinical evidence that concurrent treatment with ET and RT may be an effective radiosensitization strategy.
Novel indolic AMPK modulators induce vasodilatation through activation of the AMPK–eNOS–NO pathway
Authors: Sanz-Gómez Marta , Aledavood Elnaz , Beroiz-Salaverri Marina , Lagartera Laura , Vega-Martín Elena , Gil-Ortega Marta , Cumella Jose , Pérez Concepción , Luque Francisco Javier , Estarellas Carolina , Fernández-Alfonso María S. , Castro Ana 
Published: March 2022

AbstractEndothelial adenosine monophosphate-activated protein kinase (AMPK) plays a critical role in the regulation of vascular tone through stimulating nitric oxide (NO) release in endothelial cells. Since obesity leads to endothelial dysfunction and AMPK dysregulation, AMPK activation might be an important strategy to restore vascular function in cardiometabolic alterations. Here, we report the identification of a novel AMPK modulator, the indolic derivative IND6, which shows affinity for AMPKα1β1γ1, the primary AMPK isoform in human EA.Hy926 endothelial cells. IND6 shows inhibitory action of the enzymatic activity in vitro, but increases the levels of p-Thr174AMPK, p-Ser1177eNOS and p-Ser79ACC in EA.Hy926. This paradoxical finding might be explained by the ability of IND6 to act as a mixed-type inhibitor, but also to promote the enzyme activation by adopting two distinct binding modes at the ADaM site. Moreover, functional assays reveal that IND6 increased the eNOS-dependent production of NO and elicited a concentration-dependent vasodilation of endothelium-intact rat aorta due to AMPK and eNOS activation, demonstrating a functional activation of the AMPK–eNOS–NO endothelial pathway. This kinase inhibition profile, combined with the paradoxical AMPK activation in cells and arteries, suggests that these new chemical entities may constitute a valuable starting point for the development of new AMPK modulators with therapeutic potential for the treatment of vascular complications associated with obesity.
Ultrafast plasmonic photoemission in the single-cycle and few-cycle regimes
Authors: Kiss G. Zs , Földi P. , Dombi P. 
Published: March 2022

AbstractDue to the highly increased interest in the development of state-of-the-art applications of photoemission in ultrafast electron microscopy, development of photocathodes and many more applications, a correct theoretical understanding of the underlying phenomena is needed. Within the framework of the single active electron approximation the most accurate results can be obtained by the direct solution of the time-dependent Schrödinger equation (TDSE). In this work, after a brief presentation of a numerically improved version of a mixed 1D-TDSE method, we investigated the characteristics of electron spectra obtained from the surface of metal nanoparticles irradiated with ultrashort laser pulses. During our investigation different decay lengths of the plasmonic-enhanced incident field in the vicinity of the metal were considered. Using the simulated spectra we managed to identify the behavior of the cutoff energy as a function of decay length in the strong-field, multiphoton and transition regimes.
Natural language analyzed with AI-based transformers predict traditional subjective well-being measures approaching the theoretical upper limits in accuracy
Authors: Kjell Oscar N. E. , Sikström Sverker , Kjell Katarina , Schwartz H. Andrew 
Published: March 2022

AbstractWe show that using a recent break-through in artificial intelligence –transformers–, psychological assessments from text-responses can approach theoretical upper limits in accuracy, converging with standard psychological rating scales. Text-responses use people's primary form of communication –natural language– and have been suggested as a more ecologically-valid response format than closed-ended rating scales that dominate social science. However, previous language analysis techniques left a gap between how accurately they converged with standard rating scales and how well ratings scales converge with themselves – a theoretical upper-limit in accuracy. Most recently, AI-based language analysis has gone through a transformation as nearly all of its applications, from Web search to personalized assistants (e.g., Alexa and Siri), have shown unprecedented improvement by using transformers. We evaluate transformers for estimating psychological well-being from questionnaire text- and descriptive word-responses, and find accuracies converging with rating scales that approach the theoretical upper limits (Pearson r = 0.85, p < 0.001, N = 608; in line with most metrics of rating scale reliability). These findings suggest an avenue for modernizing the ubiquitous questionnaire and ultimately opening doors to a greater understanding of the human condition.
Causal biological network models for reactive astrogliosis: a systems approach to neuroinflammation
Authors: Barkhuizen Melinda , Renggli Kasper , Gubian Sylvain , Peitsch Manuel C. , Mathis Carole , Talikka Marja 
Published: March 2022

AbstractAstrocytes play a central role in the neuroimmune response by responding to CNS pathologies with diverse molecular and morphological changes during the process of reactive astrogliosis. Here, we used a computational biological network model and mathematical algorithms that allow the interpretation of high-throughput transcriptomic datasets in the context of known biology to study reactive astrogliosis. We gathered available mechanistic information from the literature into a comprehensive causal biological network (CBN) model of astrocyte reactivity. The CBN model was built in the Biological Expression Language, which is both human-readable and computable. We characterized the CBN with a network analysis of highly connected nodes and demonstrated that the CBN captures relevant astrocyte biology. Subsequently, we used the CBN and transcriptomic data to identify key molecular pathways driving the astrocyte phenotype in four CNS pathologies: samples from mouse models of lipopolysaccharide-induced endotoxemia, Alzheimer’s disease, and amyotrophic lateral sclerosis; and samples from multiple sclerosis patients. The astrocyte CBN provides a new tool to identify causal mechanisms and quantify astrogliosis based on transcriptomic data.
Small object detection method with shallow feature fusion network for chip surface defect detection
Authors: Huang Haixin , Tang Xueduo , Wen Feng , Jin Xin 
Published: March 2022

AbstractThe development of intelligent manufacturing often focuses on production flexibility, customization and quality control, which are crucial for chip manufacturing. Specifically, defect detection and classification are important for manufacturing processes in the semiconductor and electronics industries. The intelligent detection methods of chip defects are still challenge and have always been a particular concern of chip processing manufactures in an automated industrial production line. YOLOv4 method has been widely used for object detection due to its accuracy and speed. However, there are still difficulties and challenges in the detection for small targets, especially defects on chip surface. This study proposed a small object detection method based on YOLOv4 for small object in order to improve the performance of detection. It includes expanding feature fusion of shallow features; using k-means++ clustering to optimize the number and size of anchor box; and removing redundant YOLO head network branches to increase detection efficiency. The results of experiments reflect that SO-YOLO is superior to the original YOLOv4, YOLOv5s, and YOLOv5l models in terms of the number of parameters, classification and detection accuracy.
Multiscale heterogeneous optimal lockdown control for COVID-19 using geographic information
Authors: Neary Cyrus , Cubuktepe Murat , Lauffer Niklas , Jin Xueting , Phillips Alexander J. , Xu Zhe , Tong Daoqin , Topcu Ufuk 
Published: March 2022

AbstractWe study the problem of synthesizing lockdown policies—schedules of maximum capacities for different types of activity sites—to minimize the number of deceased individuals due to a pandemic within a given metropolitan statistical area (MSA) while controlling the severity of the imposed lockdown. To synthesize and evaluate lockdown policies, we develop a multiscale susceptible, infected, recovered, and deceased model that partitions a given MSA into geographic subregions, and that incorporates data on the behaviors of the populations of these subregions. This modeling approach allows for the analysis of heterogeneous lockdown policies that vary across the different types of activity sites within each subregion of the MSA. We formulate the synthesis of optimal lockdown policies as a nonconvex optimization problem and we develop an iterative algorithm that addresses this nonconvexity through sequential convex programming. We empirically demonstrate the effectiveness of the developed approach by applying it to six of the largest MSAs in the United States. The developed heterogeneous lockdown policies not only reduce the number of deceased individuals by up to 45 percent over a 100 day period in comparison with three baseline lockdown policies that are less heterogeneous, but they also impose lockdowns that are less severe.
Global gene expression profiling under nitrogen stress identifies key genes involved in nitrogen stress adaptation in maize (Zea mays L.)
Authors: Singh Prabha , Kumar Krishan , Jha Abhishek Kumar , Yadava Pranjal , Pal Madan , Rakshit Sujay , Singh Ishwar 
Published: March 2022

AbstractMaize is a heavy consumer of fertilizer nitrogen (N) which not only results in the high cost of cultivation but may also lead to environmental pollution. Therefore, there is a need to develop N-use efficient genotypes, a prerequisite for which is a greater understanding of N-deficiency stress adaptation. In this study, comparative transcriptome analysis was performed using leaf and root tissues from contrasting inbred lines, viz., DMI 56 (tolerant to N stress) and DMI 81 (susceptible to N stress) to delineate the differentially expressed genes (DEGs) under low-N stress. The contrasting lines were grown hydroponically in modified Hoagland solution having either sufficient- or deficient-N, followed by high-throughput RNA-sequencing. A total of 8 sequencing libraries were prepared and 88–97% of the sequenced raw reads were mapped to the reference B73 maize genome. Genes with a p value ≤ 0.05 and fold change of ≥ 2.0 or ≤ − 2 were considered as DEGs in various combinations performed between susceptible and tolerant genotypes. DEGs were further classified into different functional categories and pathways according to their putative functions. Gene Ontology based annotation of these DEGs identified three different functional categories: biological processes, molecular function, and cellular component. The KEGG and Mapman based analysis revealed that most of the DEGs fall into various metabolic pathways, biosynthesis of secondary metabolites, signal transduction, amino acid metabolism, N-assimilation and metabolism, and starch metabolism. Some of the key genes involved in N uptake (high-affinity nitrate transporter 2.2 and 2.5), N assimilation and metabolism (glutamine synthetase, asparagine synthetase), redox homeostasis (SOD, POX), and transcription factors (MYB36, AP2-EREBP) were found to be highly expressed in the tolerant genotype compared to susceptible one. The candidate genes identified in the present study might be playing a pivotal role in low-N stress adaptation in maize and hence could be useful in augmenting further research on N metabolism and development of N-deficiency tolerant maize cultivars.
Value priorities and value conflicts in patients with mental disorders compared to a general population sample
Authors: Arens Elisabeth A. , Christoffel Muriel , Stangier Ulrich 
Published: March 2022

AbstractPersonal values are considered as guiding principles for humans’ attitudes and behavior, what makes them an essential component of mental health. Although these notions are widely recognized, investigations in clinical samples examining the link between values and mental health are lacking. We assessed n = 209 patients with affective disorders, neurotic disorders, reaction to severe stress, and adjustment disorders and personality disorders and compared them to a stratified random sample (n = 209) drawn from the European Social Survey. Personal values were assessed using the Portraits Value Questionnaire. Severity of psychopathology was assessed using the Beck Depression Inventory and the Brief Symptom Inventory. Clinical participants showed a higher preference for the values power, achievement and tradition/conformity and a lower preference for hedonism compared to controls. Patients exhibited more incompatible value patterns than controls. Across diagnostic groups, patients with neurotic disorders reported incompatible values most frequently. Value priorities and value conflicts may have the potential to contribute to a better understanding of current and future actions and experiences in patients with mental disorders.
Modeling material transport regulation and traffic jam in neurons using PDE-constrained optimization
Authors: Li Angran , Zhang Yongjie Jessica 
Published: March 2022

AbstractThe intracellular transport process plays an important role in delivering essential materials throughout branched geometries of neurons for their survival and function. Many neurodegenerative diseases have been associated with the disruption of transport. Therefore, it is essential to study how neurons control the transport process to localize materials to necessary locations. Here, we develop a novel optimization model to simulate the traffic regulation mechanism of material transport in complex geometries of neurons. The transport is controlled to avoid traffic jam of materials by minimizing a pre-defined objective function. The optimization subjects to a set of partial differential equation (PDE) constraints that describe the material transport process based on a macroscopic molecular-motor-assisted transport model of intracellular particles. The proposed PDE-constrained optimization model is solved in complex tree structures by using isogeometric analysis (IGA). Different simulation parameters are used to introduce traffic jams and study how neurons handle the transport issue. Specifically, we successfully model and explain the traffic jam caused by reduced number of microtubules (MTs) and MT swirls. In summary, our model effectively simulates the material transport process in healthy neurons and also explains the formation of a traffic jam in abnormal neurons. Our results demonstrate that both geometry and MT structure play important roles in achieving an optimal transport process in neuron.
New discovery on the nematode activity of aureothin and alloaureothin isolated from endophytic bacteria Streptomyces sp. AE170020
Authors: Kang Min-Kyoung , Kim Jong-Hoon , Liu Min-Jiao , Jin Chun-Zhi , Park Dong-Jin , Kim Junheon , Sung Bong-Hyun , Kim Chang-Jin , Son Kwang-Hee 
Published: March 2022

AbstractEndophytic bacteria, a rich source of bioactive secondary metabolites, are ideal candidates for environmentally benign agents. In this study, an endophytic strain, Streptomyces sp. AE170020, was isolated and selected for the purification of nematicidal substances based on its high nematicidal activity. Two highly active components, aureothin and alloaureothin, were identified, and their chemical structures were determined using spectroscopic analysis. Both compounds suppressed the growth, reproduction, and behavior of Bursaphelenchus xylophilus. In in vivo experiments, the extracts of strain Streptomyces sp. AE170020 effectively suppressed the development of pine wilt disease in 4-year-old plants of Pinus densiflora. The potency of secondary metabolites isolated from endophytic strains suggests applications in controlling Bursaphelenchus xylophilus and opens an avenue for further research on exploring bioactive substances against the pine wood nematode.
Cost-effective wideband dielectric planar lens antenna for millimeter wave applications
Authors: Poyanco José-Manuel , Pizarro Francisco , Rajo-Iglesias Eva 
Published: March 2022

AbstractThis article presents a fully 3D-printed dielectric planar lens operating in the entire Ka-band manufactured using additive manufacturing and a relatively low-cost 3D-printer. The lens consists of ten concentric rings implemented using low-loss ABS filaments with high permittivity values. By varying the infill percentages of them the required refractive indexes of each section are achieved. An additional 3D-printed matching layer, using the same manufacturing and design method was included in the lens, to reduce reflections. Simulation and measurement results show a very good agreement, which confirms the possibility of manufacturing a cost-effective broadband and planar lens solution operating in millimeter wave bands, where Low Earth Orbit Satellites (LEO) networks, future mobile communication systems (5G, 6G) and radar systems operate.