bluuebunny/crossref_metadata_2025_split huggingface dataset:
SelSA-1, a novel HDAC inhibitor demonstrates enhanced chemotherapeutic potential by redox modulation
Authors: Garg Ayushi , Desai Dhimant , Bhalla Aman , Thakur Shalu , Rastogi Pulkit , Kaushal Naveen 
Published: June 2023

AbstractColorectal cancer (CRC) is a multistep disorder resulting from genetic and epigenetic genome changes. It is the third most common malignancy in developed nations accounting for roughly 600,000 deaths annually. Persistent gut inflammation, as observed in inflammatory bowel disease (IBD), is a key risk factor for CRC development. From an epigenetic viewpoint, the pharmacological inhibition of HDACs using HDAC inhibitors such as SAHA has emerged as a suitable anticancer strategy in the recent past. However, the clinical success of these strategies is limited and has risk factors associated with their uses. Thus, considering the critical involvement of epigenetic regulation of key molecular mechanisms in carcinogenesis as well as HDAC inhibitory and anti-tumorigenic properties of Selenium (Se), we aimed to explore the potentially safer and enhanced chemotherapeutic potential of a Se derivative of SAHA namely SelSA-1, in an experimental model of colitis-associated experimental cancer (CAC) model and mechanism involved therein. The in vitro study indicated improved efficiency, specificity, and better safety margin in terms of lower IC50 value of SelSA-1 than SAHA in both NIH3T3 (9.44 and 10.87 µM) and HCT 115 (5.70 and 7.49 µM) cell lines as well on primary colonocytes (5.61 and 6.30 µM) respectively. In an in vivo experimental model, SelSA-1 efficiently demonstrated amelioration of the multiple plaque lesions (MPLs), tumor burden/incidence, and modulation of various histological and morphological parameters. Further, redox-mediated alterations in apoptotic mediators suggested induction of cancer cell apoptosis by SelSA-1. These findings indicate the enhanced chemotherapeutic and pro-resolution effects of SelSA-1 in part mediated through redox modulation of multiple epigenetic and apoptotic pathways.
A single-cell RNA-seq analysis unravels the heterogeneity of primary cultured human corneal endothelial cells
Authors: Català Pere , Groen Nathalie , LaPointe Vanessa L. S. , Dickman Mor M. 
Published: June 2023

AbstractThe cornea is a transparent and avascular tissue located in front of the eye. Its inner surface is lined by a monolayer of corneal endothelial cells (CECs), which maintain the cornea transparency. CECs remain arrested in a non-proliferative state and damage to these cells can compromise their function leading to corneal opacity. The primary culture of donor-derived CECs is a promising cell therapy. It confers the potential to treat multiple patients from a single donor, alleviating the global donor shortage. Nevertheless, this approach has limitations preventing its adoption, particularly culture protocols allow limited expansion of CECs and there is a lack of clear parameters to identify therapy-grade CECs. To address this limitation, a better understanding of the molecular changes arising from the primary culture of CECs is required. Using single-cell RNA sequencing on primary cultured CECs, we identify their variable transcriptomic fingerprint at the single cell level, provide a pseudo-temporal reconstruction of the changes arising from primary culture, and suggest markers to assess the quality of primary CEC cultures. This research depicts a deep transcriptomic understanding of the cellular heterogeneity arising from the primary expansion of CECs and sets the basis for further improvement of culture protocols and therapies.
Green preparation of graphene oxide nanosheets as adsorbent
Authors: Cao Kesheng , Tian Zhengshan , Zhang Xunyou , Wang Yabo , Zhu Qiuxiang 
Published: June 2023

AbstractAs a basic building block of graphene-based materials, graphene oxide (GO) plays an important role in scientific research and industrial applications. At present, numerous methods have been employed to synthesize GO, there are still some issues that need to be solved, thus it is of importance to develop a green, safe and low-cost GO preparation method. Herein, a green, safe and fast method was designed to prepare GO, namely, graphite powder was firstly oxidized in a dilute sulfuric acid solution (H2SO4, 6 mol/L) with hydrogen peroxide (H2O2, 30 wt%) as oxidant, and then exfoliated to GO by ultrasonic treatment in water. In this process, H2O2 was the only oxidant, and no other oxidants were used, thus the explosive nature of GO preparation reaction in the conventional methods could be completely eliminated. This method has other advantages such as green, fast, low-cost and no Mn-based residues. The experimental results confirm that obtained GO with oxygen-containing groups has better adsorption property compared to the graphite powder. As adsorbent, GO can remove methylene blue (50 mg/L) and Cd2+ (56.2 mg/L) from water with removal capacity of 23.8 mg/g and 24.7 mg/g, respectively. It provides a green, fast and low-cost method to prepare GO for some applications such as adsorbent.
acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens
Authors: Ramesh Adithya , Trivedi Varun , Lee Sangcheon , Tafrishi Aida , Schwartz Cory , Mohseni Amirsadra , Li Mengwan , Lonardi Stefano , Wheeldon Ian 
Published: June 2023

AbstractHigh throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.
Crowded environments tune the fold-switching in metamorphic proteins
Authors: Zhang Ning , Guan Wenyan , Cui Shouqi , Ai Nana 
Published: June 2023

AbstractMetamorphic proteins such as circadian clock protein KaiB and human chemokine XCL1 play vital roles in regulating biological processes, including gene expression, circadian clock and innate immune responses, and perform distinct functions in living cell by switching different structures in response to cellular environment stimuli. However, it is unclear how complex and crowded intracellular environments affect conformational rearrangement of metamorphic proteins. Here, the kinetics and thermodynamics of two well-characterized metamorphic proteins, circadian clock protein KaiB and human chemokine XCL1, were quantified in physiologically relevant environments by using NMR spectroscopy, indicating that crowded agents shift equilibrium towards the inactive form (ground-state KaiB and Ltn10-like state XCL1) without disturbing the corresponding structures, and crowded agents have predominantly impact on the exchange rate of XCL1 that switches folds on timescales of seconds, but have slightly impact on the exchange rate of KaiB that switches folds on timescales of hours. Our data shed light on how metamorphic proteins can respond immediately to the changed crowded intracellular conditions that induced by environmental cues and then execute different functions in living cell, and it also enhances our understanding of how environments enrich the sequence-structure-function paradigm.
Epidemic modelling of monitoring public behavior using surveys during pandemic-induced lockdowns
Authors: Koher Andreas , Jørgensen Frederik , Petersen Michael Bang , Lehmann Sune 
Published: June 2023

Abstract
Background
Implementing a lockdown for disease mitigation is a balancing act: Non-pharmaceutical interventions can reduce disease transmission significantly, but interventions also have considerable societal costs. Therefore, decision-makers need near real-time information to calibrate the level of restrictions.

Methods
We fielded daily surveys in Denmark during the second wave of the COVID-19 pandemic to monitor public response to the announced lockdown. A key question asked respondents to state their number of close contacts within the past 24 hours. Here, we establish a link between survey data, mobility data, and hospitalizations via epidemic modelling of a short time-interval around Denmark’s December 2020 lockdown. Using Bayesian analysis, we then evaluate the usefulness of survey responses as a tool to monitor the effects of lockdown and then compare the predictive performance to that of mobility data.

Results
We find that, unlike mobility, self-reported contacts decreased significantly in all regions before the nation-wide implementation of non-pharmaceutical interventions and improved predicting future hospitalizations compared to mobility data. A detailed analysis of contact types indicates that contact with friends and strangers outperforms contact with colleagues and family members (outside the household) on the same prediction task.

Conclusions
Representative surveys thus qualify as a reliable, non-privacy invasive monitoring tool to track the implementation of non-pharmaceutical interventions and study potential transmission paths.
Predicting microplastic masses in river networks with high spatial resolution at country level
Authors: Mennekes David , Nowack Bernd 
Published: June 2023

AbstractMicroplastics are a ubiquitous contaminant of natural waters, and a lot of field monitoring is currently performed. However, what is missing so far is a general understanding how emissions of microplastics are linked to environmental exposure, especially on larger geographic scales such as countries. Here we coupled a high-resolution microplastic release model with a fate model in rivers and lakes and parameterized it for Switzerland on a country scale to predict masses of microplastics in each river section for seven different polymers. The results show that catchment characteristics, for example, distribution of releases within the catchment, location and size of lakes or river connections, are as important as polymer properties such as density. There is no simple linear function of microplastic retention within a catchment in dependency of river length to the outlet. Instead, we found that different catchments cover a wide range of retained fractions for microplastics. Consequently, we argue that the availability and use of spatially distributed release data and performing modelling on high spatial resolution is of importance when estimating concentrations of microplastics in large areas such as countries.
Feature extraction method of HPLC communication signal based on genetic algorithm
Authors: Tang Chao , Chang Zhengwei , Liang Huihui , Zhang Linghao , Pang Bo 
Published: June 2023

AbstractCommunication quality is a key factor affecting the effectiveness of distribution network operation status management. Therefore, it is required that the communication performance of the distribution network management system be good, and the communication signal can directly reflect the communication quality. Therefore, a genetic algorithm (GA) based HPLC communication signal feature extraction method is proposed. The process of constructing reference samples, training recognition models, constructing noise samples, self‐coding denoising processing, and denoising sample recognition has completed the identification of power line channel transmission characteristics. The state feature quantity of the topological line is based on the positioning results of the diagnostic function, and the calculated value of the reflection coefficient calculation model at the head end of the topological line is compared with the measured value. By optimizing the feature quantities containing topological line states through GAs, abnormal feature quantities close to the true state of topological lines are obtained. Experimental analysis shows that this method can correctly identify the position of reactive power compensation in the transmission line, and can also correctly identify the extraction of topological anomaly features. Therefore, the research method is of great significance in improving the safe operation of power systems and extending the service life of topology lines.
A digital delay locked loop with a monotonic delay line
Authors: Liu Jen‐Chieh , Yang Chuan 
Published: June 2023

AbstractThis paper proposes a digital delay locked loop (DLL) with a monotonic delay line (DL). This DLL adopts the calibration mode to reduce the non‐monotonic effects for the coarse‐tuning delay line (CTDL) and the fine‐tuning delay line (FTDL). The calibration mode detects the delay time of the delay unit, the timing resolution of CTDL, to adjust the delay range of the FTDL. Thus, the calibration mode can limit the overlap range of the delay time between the CTDL and the FTDL. The proposed DLL was implemented using a 0.18‐μm CMOS process, and the RMS and the peak‐to‐peak jitters of the DLL were 0.21% and 1.72%, respectively, at 560 MHz.
Computational social science in smart power systems: Reliability, resilience, and restoration
Authors: Valinejad Jaber , Mili Lamine , Yu Xinghuo , van der Wal C. Natalie , Xu Yijun 
Published: June 2023

AbstractSmart grids are typically modelled as cyber–physical power systems, with limited consideration given to the social aspects. Specifically, traditional power system studies tend to overlook the behaviour of stakeholders, such as end‐users. However, the impact of end‐users and their behaviour on power system operation and response to disturbances is significant, particularly with respect to demand response and distributed energy resources. Therefore, it is essential to plan and operate smart grids by taking into account both the technical and social aspects, given the crucial role of active and passive end‐users, as well as the intermittency of renewable energy sources. In order to optimize system efficiency, reliability, and resilience, it is important to consider the level of cooperation, flexibility, and other social features of various stakeholders, including consumers, prosumers, and microgrids. This article aims to address the gaps and challenges associated with modelling social behaviour in power systems, as well as the human‐centred approach for future development and validation of socio‐technical power system models. As the cyber–physical–social system of energy emerges as an important topic, it is imperative to adopt a human‐centred approach in this domain. Considering the significance of computational social science for power system applications, this article proposes a list of research topics that must be addressed to improve the reliability and resilience of power systems in terms of both operation and planning. Solving these problems could have far‐reaching implications for power systems, energy markets, community usage, and energy strategies.
Investigation and 3E (economic, environmental and energy) analysis of a combined heat and power system based on renewable energies for supply energy of sport facilities
Authors: Fei Jiaming , Su Zhanguo , Yao Yuzhong , Fei Cheng , Shamel Ali 
Published: June 2023

AbstractDue to the regular reduction of fossil fuels and the increase in emissions as a result of fossil fuel consumption, the use of renewable energy‐based systems is increasing gradually and microgrid systems have developed significantly due to the simultaneous production of electricity and heat on a very large scale. Therefore, microgrid modelling has been done considering fossil and non‐fossil sources wind turbines and photovoltaic cells are considered the main sources of energy supply and a gas turbine is the supporting source that thermal energy production in the system is the responsibility of the boiler. The purpose of the system modelling is optimization by considering different conditions including maximum energy supply, reducing emissions, and reducing the cost of operation, which is why different scenarios were evaluated. For an accurate evaluation, different scenarios have been set for the production of energy from different sources. One of the important results is the lower cost of the first scenario compared to the other two scenarios, the total cost of which is $180.53. In this scenario, 72.2466 kWh of electricity is purchased and 43.62 kWh of electricity is sold.
Parking space number detection with multi‐branch convolution attention
Authors: Guo Yifan , Zhang Jianxun , Lin Yuting , Zhang Jie , Li Bowen 
Published: June 2023

AbstractWith the increase of large shopping malls, there are many large parking spaces in complex environments, which increases the difficulty of finding vehicles in such environments. To upgrade the consumer's experience, some car manufacturers have proposed detecting parking space numbers in parking spaces. The detection of parking space number in parking spaces in complex environments has problems such as the diversified background of parking space numbers, tilted direction of parking space numbers, and small parking space number scale. Since no scholar has proposed a high‐performance method for such problems, a parking space number detection model based on the multi‐branch convolutional attention is presented. Firstly, using ResNet50 as the backbone network, a multi‐branch convolutional structure is proposed in the backbone network, which aims to process and fuse the feature map through three parallel branches, and enhance the network to represent ability information by convolutional attention, learn global features to selectively strengthen the features containing helpful information, and improve the ability of the model to detect the parking space number area. Secondly, a high‐level feature enhancement unit is designed to adjust the features channel by channel, obtain more spatial correlation, and reduce the loss of information in the process of feature map generation. The data results of the model on the parking space number dataset CCAG show that the precision, recall, and F‐measure are 84.8%, 84.6%, and 84.7%, respectively, which has certain advantages for parking space number detection.
Long-term optical spectral monitoring of a changing-look active galactic nucleus NGC 3516
Authors: Popović Luka Č. , Ilić Dragana , Burenkov Alexander , Patiño Alvarez Victor Manuel , Marčeta-Mandić Sladjana , Kovačević-Dojčinović Jelena , Shablovinskaya Elena , Kovačević Andjelka B. , Marziani Paola , Chavushyan Vahram , Wang Jian-Min , Li Yan-Rong , Mediavilla Evencio G. 
Published: June 2023

Context.We analyze the broad Hβline profile variability of a “changing look” active galactic nucleus (CL-AGN) NGC 3516 over an extensive period of 25 years (from 1996 to 2021). The observed change in the broad line profile may indicate a change in the geometry of the broad line region (BLR). The main objective is to follow and understand the change in the BLR over a long period as well as its connection to the CL mechanism.Aims.Using spectral line profiles, we aim to explore changes in the kinematics and dimensions of the BLR in NGC 3516. We consider two possible scenarios: the changes in the broad-line emission are either caused by a decrease of ionisation continuum emission or by the BLR obscuration by outer dusty regions. With this investigation, we aim to clarify the CL mechanism of this AGN.Methods.We analyzed the spectral band around the Hβline as well as the broad Hβline parameters and how they change over time. We modelled the broad-line profiles, assuming that there is an emission from the accretion disc superposed with emission from a surrounding region that is outside the disc.Results.We find that in the type 1 activity phase occurring when the strong broad emission lines are observed, the BLR is very complex. There is a clear disc-like BLR that contributes to the broad line wings and an additional intermediate line region (ILR) that contributes to the line core. In the high-activity phase, the ILR emission is close to the center of the line, although in some cases, it is slightly shifted to the red. In the low-activity phase (i.e. type 2 phase), the ILR component has a significant shift to the blue, indicating an outflow.Conclusions.We propose that the changing-look mechanism in NGC 3516 is rather connected with the intrinsic effects than with an outer obscuring region. It may still be possible that the dust plays an important role in the low-activity phase when it is coming from within the BLR, leading to a dusty BLR. In this way, it would cause a decrease in the ionisation and recombination rates.
Patient-Reported Outcomes Measures in Rhinoplasty: Need for Use and Implementation
Authors: Warinner Chloe , Loyo Myriam , Gu Jeffrey , Wamkpah Nneoma S. , Chi John J. , Lindsay Robin W. 
Published: June 2023

AbstractPatient-reported outcome metrics (PROMs) are increasingly utilized to capture data about patients' quality of life. PROMs play an important role in the value-based health care movement by providing a patient-centered metric of quality. There are many barriers to the implementation of PROMs, and widespread adoption requires buy-in from numerous stakeholders including patients, clinicians, institutions, and payers. Several validated PROMs have been utilized by facial plastic surgeons to measure both functional and aesthetic outcomes among rhinoplasty patients. These PROMs can help clinicians and rhinoplasty patients participate in shared decision making (SDM), a process via which clinicians and patients arrive at treatment decisions together through a patient-centered approach. However, widespread adoption of PROMs and SDM has not yet been achieved. Further work should focus on overcoming barriers to implementation and engaging key stakeholders to increase the utilization of PROMs in rhinoplasty.
What motivates business to donate to politics? A framework and an empirical application
Authors: McMenamin Iain , Power Sam 
Published: June 2023

AbstractThe secrecy, subtlety, and diversity of party-firm relations have proven challenging to synthesize. We introduce a new heuristic framework for the study business donors on the basis of pragmatic, partisan, and social motivations. We illustrate our framework with an analysis of donors to the UK Conservative Party from the property services and construction industries. While actors make it almost impossible to place particular events in our framework, in the aggregate the framework is empirically tractable. We triangulate a study of over twenty years of donations data, news on social events, and qualitative data to argue that the construction industry is motivated by a combination of pragmatic and social motivations, while the property services industry is best described by a combination of the social and partisan motivations.