bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lysine specific demethylase 1 inhibits sodium arsenite activation of HSCs by regulating SESN2/AMPK/ULK1 signaling pathway activity
Authors: Zhang Yingwan , Tian Tian , Liang Cai , Wang Junli , Zhang Jiayuan , Tian Shanshan , Xie Rujia , Yang Ting , Han Bing 
Published: March 2024

AbstractLysine specific demethylase 1 (LSD1) is a histone demethylase that specifically catalyzes the demethylation of histone H3K4 (H3K4me1/2) and regulates gene expression. In addition, it can mediate the process of autophagy through its demethylase activity. Sestrin2 (SESN2) is a stress‐induced protein and a positive regulator of autophagy. In NaAsO2‐induced mouse fibrotic livers and activated hepatic stellate cells (HSCs), LSD1 expression is decreased, SESN2 expression is increased, and autophagy levels are also increased. Overexpression of LSD1 and silencing of SESN2 decreased the level of autophagy and attenuated the activation of HSCs induced by NaAsO2. LSD1 promoted SESN2 gene transcription by increasing H3K4me1/2 in the SESN2 promoter region. 3‐methyladenine (3‐MA) and chloroquine were used to inhibit autophagy of HSCs, and the degree of activation was also alleviated. Taken together, LSD1 positively regulates SESN2 by increasing H3K4me1/2 enrichment in the SESN2 promoter region, which in turn increases the level of autophagy and promotes the activation of HSCs. Our results may provide new evidence for the importance of LSD1 in the process of autophagy and activation of HSCs induced by arsenic poisoning. Increasing the expression and activity of LSD1 is expected to be an effective way to reverse the autophagy and activation of HSCs induced by arsenic poisoning.
Enhancing Reading and Writing Skills through Systematically Integrated Instruction
Authors: Kim Young‐Suk Grace , Zagata Elizabeth 
Published: March 2024

AbstractReading and writing are often taught separately. This article explores the crucial relations between these skills, emphasizing the importance of understanding the "what" and "why" to effectively plan the "how" of integrated reading–writing instruction. The Interactive Dynamic Literacy Model (Kim,Reading‐writing connections: Towards integrative literacy science. Springer;Journal of Learning Disabilities, 2022,55, 447), supported by empirical evidence, illustrates how reading and writing skills are interwoven, forming hierarchical, interactive, and dynamic relations, and advocates for integrated teaching to enhance the development of both skills. Understanding these relations is essential for educators to design comprehensive and effective literacy instruction that supports the development of both foundational and higher‐order reading and writing skills. We propose three principles for effective integrated reading‐writing instruction: (a) leveraging assessment data in reading and writing to inform effective integrated instruction; (b) ensuring the development of lower‐order skills while also supporting the development of higher‐order skills; and (c) making reading‐writing connections visible. Illustrative examples are provided.
Click, See, Do: Using Digital Scaffolding to Support Persuasive Writing Instruction for Emerging Bilingual Learners
Authors: Hutchison Amy , Evmenova Anya , Regan Kelley , Gafurov Boris 
Published: March 2024

AbstractThis article using a persuasive writing example to showcase how digital technologies can be used to support all students, especially emerging bilingual learners, as they learn genre‐specific norms for writing.
Making quantum chemistry compressive and expressive: Toward practical ab‐initio simulation
Authors: Yang Jun 
Published: March 2024

AbstractAb‐initio quantum chemistry simulations are essential for understanding electronic structure of molecules and materials in almost all areas of chemistry. A broad variety of electronic structure theories and implementations has been developed in the past decades to hopefully solve the many‐body Schrödinger equation in an approximate manner on modern computers. In this review, we present recent progress in advancing low‐rank electronic structure methodologies that rely on the wavefunction sparsity and compressibility to select the important subset of electronic configurations for both weakly and strongly correlated molecules. Representative chemistry applications that require the many‐body treatment beyond traditional density functional approximations are discussed. The low‐rank electronic structure theories have further prompted us to highlight compressive and expressive principles that are useful to catalyze idea of quantum learning models. The intersection of the low‐rank correlated feature design and the modern deep neural network learning provides new feasibilities to predict chemically accurate correlation energies of unknown molecules that are not represented in the training dataset. The results by others and us are discussed to reveal that the electronic feature sets from an extremely low‐rank correlation representation, which is very poor for explicit energy computation, are however sufficiently expressive for capturing and transferring electron correlation patterns across distinct molecular compositions, bond types and geometries.This article is categorized under:
Electronic Structure Theory > Ab Initio Electronic Structure Methods
Software > Quantum Chemistry
Software > Simulation Methods
Designing a Dynamic Map of Circular Economy in the Tourism Sector of the Valencian Community
Authors: Carrascosa-Lopez Conrado , Perello-Marin M. Rosario , Carabal-Montagud María Ángeles 
Published: March 2024

AbstractAdopting circular economy (CE) principles has become crucial for companies to sustain their competitive advantage. CE can be defined as an economic system that aims to eliminate waste and keep resources in continuous use, thereby minimizing the consumption of raw materials, energy usage, and environmental impact. Companies in the hospitality sector, especially small-medium-sized ones, face significant challenges when implementing CE strategies. Limited accessibility and comprehensibility of information on CE practices hinder the effective design and implementation of CE initiatives for these companies.To overcome these difficulties, this chapter shows the development of a dynamic map that displays up-to-date and agile information about the circularity practices of companies in the tourism value chain. The main goal is to map the CE tourism value chain to get a more significant impact on local communities and tourists themselves. To be listed on the map, a company has to demonstrate that it has a sustainability certification or seal that includes some aspect of CE.As a result, this map can facilitate the search for suppliers with a demonstrated concern and circular mentality to increase the circularity of the entire ecosystem.
Wine Tourism, Circular Economy Practices and Hospitality in the Spanish Wine Industry: The Case of Bodegas Casa Sicilia Wine Restaurant
Authors: Marco-Lajara Bartolomé , Martínez-Falcó Javier , Sánchez-García Eduardo , Millán-Tudela Luis A. 
Published: March 2024

AbstractThe objective of this research is to analyze the link between wine tourism, winery restaurant activity, circular economy practices, and sustainable performance in the Spanish wine context. In order to contrast the propositions put forward in the study, the single case method is employed. The results of the research show that wine tourism has a positive influence on the sustainable performance of the winery examined, with circular economy practices and hospitality activities moderating and mediating this link, respectively. The research may be useful, therefore, both for wine professionals who are considering developing and/or intensifying wine tourism in their wineries, as well as for academics who wish to delve deeper into the catalytic effects of this type of tourism.
Good Practices of Circular Economy in Tourism in Castellón
Authors: Serbanescu Andrei , Cháfer Luís Martínez , Fernández Teresa Martínez 
Published: March 2024

AbstractThis chapter examines the significance of circular economy (CE) in the context of the tourism industry in Castellón, Spain. Tourism plays a vital role in the country’s economy, contributing a substantial share to the GDP and generating employment opportunities. However, the environmental impact of tourism, including waste management and pollution, poses significant challenges. Adopting a CE approach becomes crucial in minimizing waste, optimizing resource utilization, and promoting sustainability. The chapter explores the concept of CE, its potential benefits, and its role in creating a more sustainable tourism model. It emphasizes the need for active participation from both producers and consumers to shift away from a linear economy mentality. The chapter also highlights the positive economic, environmental, and social outcomes associated with CE, including job creation and enhanced well-being. By showcasing good practices and a case study of a hotel in Castellón, this chapter aims to promote awareness and encourage the transition towards a fairer and more environmentally friendly tourism model.
Analytic decay width of the Higgs boson to massive bottom quarks at next-to-next-to-leading order in QCD
Authors: Wang Jian , Wang Yefan , Zhang Da-Jiang 
Published: March 2024

Abstract
The Higgs boson decay to a massive bottom quark pair provides the dominant contribution to the Higgs boson width. We present an exact result for such a decay induced by the bottom quark Yukawa coupling with next-to-next-to-leading order (NNLO) QCD corrections. We have adopted the canonical differential equations in the calculation and obtained the result in terms of multiple polylogarithms. We also compute the contribution from the decay to four bottom quarks which consists of complete elliptic integrals or their one-fold integrals. The result in the small bottom quark mass limit coincides with the previous calculation using the large momentum expansion. The threshold expansion exhibits power divergent terms in the bottom quark velocity, which has a structure different from that in $${e}^{+}{e}^{-}\to t\overline{t }$$ but can be reproduced by computing the corresponding Coulomb Green function. The NNLO corrections significantly reduce the uncertainties from both the renormalization scale and the renormalization scheme of the bottom quark Yukawa coupling. Our result can be applied to a heavy scalar decay to a top quark pair.
Externalisierendes Problemverhalten mit Freund:innen im Jugendalter: Welche Rolle spielen Faktoren der emotionalen Unbeteiligtheit?
Authors: Schön Sara-Marie , Daseking Monika 
Published: March 2024

Zusammenfassung
Einleitung
Eine Erklärung dafür, dass Jugendliche externalisierendes Problemverhalten (regelverletzendes und dissoziales Verhalten) zeigen, sind affektive Beeinträchtigungen. Ein abgeflachter Affekt ist ein Kernmerkmal der Callous-Unemotional Traits (CU-Traits, dt.: emotionale Unbeteiligtheit). CU-Traits setzen sich aus den 3 Faktoren Callousness (Mangel an Empathie und Reue), Uncaring (gleichgültige Haltung ggü. der Erfüllung von Aufgaben und den Gefühlen anderer) und Unemotional (oberflächlicher oder abgeflachter Affekt) zusammen. Externalisierendes Problemverhalten findet im Jugendalter zumeist in Gruppen statt. Daher ist es wichtig, den Zusammenhang von CU-Traits und externalisierendem Problemverhalten zu betrachten, das explizit gemeinsam mit bzw. in Anwesenheit von Freund:innen gezeigt wird. Diese Perspektive fehlt bisher in der Forschung zu CU-Traits. Die vorliegende Studie hat das Ziel, diese Forschungslücke zu schließen.

Methode
Von N = 169 Jugendlichen (54 % weiblich; M = 14,95 Jahre) wurden im Zeitraum von Juni 2021 bis März 2023 Selbstberichtsdaten mit einer online oder handschriftlich ausfüllbaren Fragebogenbatterie erhoben, die neben CU-Traits (ICU) auch Einschätzungen zu regelbrechendem und dissozialem Verhalten mit Freund:innen (CBCL: YSR 11–18 R) enthielten.

Ergebnisse
Ausschließlich die Subskala Callousness trägt zur Erklärung von externalisierendem Problemverhalten mit Freund:innen bei (6 % Varianzaufklärung).

Diskussion
Die 3 Faktoren der CU-Traits sollten getrennt voneinander betrachtet werden. Außerdem scheint es bei der Untersuchung von externalisierendem Problemverhalten wichtig zu sein, ob es allein oder gemeinsam mit bzw. in Anwesenheit von Freund:innen gezeigt wird. Limitationen der Studie, Ideen für weiterführende Forschung und praktische Implikationen werden diskutiert.
Ice cage: new records and cryptic, isolated lineages in wingless snow flies (Diptera, Limoniidae: Chionea spp.) in German lower mountain ranges
Authors: Klesser Robert , Blick Theo , Fritze Michael-Andreas , Marten Andreas , Hemauer Michael , Kastner Laura , Höfer Hubert , Jäger Gero , Husemann Martin 
Published: March 2024

AbstractIn Earth’s history warm and cold periods have alternated. Especially, during the Pleistocene, the alternation between these different climatic conditions has led to frequent range expansions and retractions of many species: while thermophilic species dispersed during warm periods, cold adapted species retracted to cold refugia and vice versa. After the last Pleistocene cycle many cold adapted taxa found refuges in relict habitats in mountain ranges. One example for such a cold adapted relict is the flightless snow fly Chionea araneoides (Dalman, 1816). It can be found in lower mountain ranges of Central Europe exclusively in stone runs and stony accumulations which provide cold microclimates. Imagines develop only in winter. They have strongly restricted ranges and hence experienced strong isolation predicting that local populations may show local adaptation and hence also genetic differentiation. We investigated this for several middle mountain ranges of Germany using the COI barcoding gene. Our analyses revealed two distinct lineages, one in the Bavarian Forest and a second one in all other more northern locations up to Scandinavia. These lineages likely go back to post-Pleistocene isolation and should be studied in more detail in the future, also to confirm the taxonomic status of both lineages. Further, we confirmed former records of the species for Germany and report new records for the federal states of Saxony, Lower Saxony, Saxony-Anhalt and Thuringia. Finally, we provide the first evidence of two types of males for the species, a small and a larger male type.
Chemically derived quinary Cu2Co1–xNaxSnS4 photon absorber material and its photocatalytic application
Authors: Tumbul A. , Aslan E. , Göktaş A. , Mutlu I. H. , Arslan F. , Aslan F. 
Published: March 2024

AbstractThe solar absorbing materials attract attention for the opto-electronic device applications such as solar cells and photocatalysis. Interest in photocatalytic materials to clean up the wastewater has started to increase. Generally, semiconductors sensitive to UV region are used. However, most of the light from the sun is in the visible region. Cu2CoSnS4 is a promising material that exhibits superior photo-response in the visible regions with an appropriate band gap. In this study, Cu2CoSnS4 films were prepared by the sol–gel method. Cu2Co1–xNaxSnS4 was synthesized for the first time by partly substituting sodium with cobalt. With this approach, noticeable improvements were observed in the physical properties of the material. With the sodium replacement, the Cu2Co1–xNaxSnS4 exhibited high photocatalytic performance toward the degradation of methylene blue (MB) under visible-light irradiation. According to the results, Cu2CoSnS4 and Cu2Co1–xNaxSnS4 samples degraded the MB solution by degradation efficacy values of 89.69% and 94.57%, respectively, in a short time like 40 min under visible light. This study shows that the substitution of sodium boosted the degradation efficiency by 5.4%. For the Cu2CoSnS4 and Cu2Co1–xNaxSnS4 samples, the computed reaction rate constants are 0.059 min−1 and 0.077 min−1, respectively.
Balloon technologies for pulmonary vein isolation—12-month outcome and comparison of the novel radiofrequency balloon with the cryoballoon in patients with paroxysmal atrial fibrillation
Authors: van den Bruck Jan-Hendrik , Wörmann Jonas , Sultan Arian , Filipovic Karlo , Seuthe Katharina , Erlhöfer Susanne , Scheurlen Cornelia , Dittrich Sebastian , Schipper Jan-Hendrik , Lüker Jakob , Steven Daniel 
Published: March 2024

Abstract

Background
The cryoballoon (CB) has become a standard tool for pulmonary vein isolation (PVI), but the technology is limited in certain ways. A novel RF-balloon (Heliostar™, Biosense Webster, CA, USA) promises the advantages of a balloon technology in combination with 3D mapping.

Methods
To assess procedural data and outcome, all patients undergoing RF-balloon PVI were included and compared with data from consecutive patients undergoing CB PVI for paroxysmal AF.

Results
A total of 254 patients (63 ± 13 years, 54% male) were included: 30 patients undergoing RF-balloon and 224 patients CB PVI. Baseline parameters were comparable. Procedure duration (104.3 ± 35.3 min vs. 69.9 ± 23.1 min; p ≤ 0.001) and fluoroscopy time (16.3 ± 7.1 min vs. 11.6 ± 4.9 min; p ≤ 0.001) were longer using the RF-balloon; ablation time (43.5 ± 17.9 vs. 36.4 ± 15.6; p = 0.08) did not differ, and time-to-isolation (TTI) was shorter (18.2 ± 7.0 s vs. 62.8 ± 35.1 s; p ≤ 0.001). Second-generation RF-balloon cases showed shorter ablation time and TTI at comparable procedure duration and fluoroscopy time. One pericardial effusion occurred with the RF-balloon due to complicated transseptal access. During CB PVI in 4/224 patients (1.8%), a phrenic nerve palsy was observed. After 12 months, 78% of patients after RF-balloon and 81% of patients after CB PVI (p = 0.5) were free from atrial arrhythmias.

Conclusion
The RF-balloon was safe and effective. Compared with the CB, TTI was shorter, but procedure durations and fluoroscopy times were longer. This can be attributed to a learning curve and the initial necessity for separate 3D map preparation. Considering the results with the second-generation RF-balloon, more experience is needed to determine the potential benefits.

Graphical Abstract
A comprehensive multi-omics analysis identifies a robust scoring system for cancer-associated fibroblasts and intervention targets in colorectal cancer
Authors: Wang Feng , Li Zhenlin , Xu Tianlei , Zhang Qian , Ma Tianyi , Li Sijia , Wang Xiaohui 
Published: March 2024

Abstract
Background
Cancer-associated fibroblasts (CAF) play a critical role in promoting tumor growth, metastasis, and immune evasion. While numerous studies have investigated CAF, there remains a paucity of research on their clinical application in colorectal cancer (CRC).

Methods
In this study, we collected differentially expressed genes between CAF and normal fibroblasts (NF) from previous CRC studies, and utilized machine learning analysis to differentiate two distinct subtypes of CAF in CRC. To enable practical application, a CAF-related genes (CAFGs) scoring system was developed based on multivariate Cox regression. We then conducted functional enrichment analysis, Kaplan–Meier plot, consensus molecular subtypes (CMS) classification, and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm to investigate the relationship between the CAFGs scoring system and various biological mechanisms, prognostic value, tumor microenvironment, and response to immune checkpoint blockade (ICB) therapy. Moreover, single-cell transcriptomics and proteomics analyses have been employed to validate the significance of scoring system-related molecules in the identity and function of CAF.

Results
We unveiled significant distinctions in tumor immune status and prognosis not only between the CAF clusters, but also across high and low CAFGs groups. Specifically, patients in CAF cluster 2 or with high CAFGs scores exhibited higher CAF markers and were enriched for CAF-related biological pathways such as epithelial–mesenchymal transition (EMT) and angiogenesis. In addition, CAFGs score was identified as a risk index and correlated with poor overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and recurrence-free survival (RFS). High CAFGs scores were observed in patients with advanced stages, CMS4, as well as lymphatic invasion. Furthermore, elevated CAFG scores in patients signified a suppressive tumor microenvironment characterized by the upregulation of programmed death-ligand 1 (PD-L1), T-cell dysfunction, exclusion, and TIDE score. And high CAFGs scores can differentiate patients with lower response rates and poor prognosis under ICB therapy. Notably, single-cell transcriptomics and proteomics analyses identified several molecules related to CAF identity and function, such as FSTL1, IGFBP7, and FBN1.

Conclusion
We constructed a robust CAFGs score system with clinical significance using multiple CRC cohorts. In addition, we identified several molecules related to CAF identity and function that could be potential intervention targets for CRC patients.
Metal oxide-based gas sensor array for VOCs determination in complex mixtures using machine learning
Authors: Singh Shivam , S Sajana , Varma Poornima , Sreelekha Gajje , Adak Chandranath , Shukla Rajendra P. , Kamble Vinayak B. 
Published: March 2024

AbstractDetection of volatile organic compounds (VOCs) from the breath is becoming a viable route for the early detection of diseases non-invasively. This paper presents a sensor array of 3 component metal oxides that give maximal cross-sensitivity and can successfully use machine learning methods to identify four distinct VOCs in a mixture. The metal oxide sensor array comprises NiO-Au (ohmic), CuO-Au (Schottky), and ZnO–Au (Schottky) sensors made by the DC reactive sputtering method and having a film thickness of 80–100 nm. The NiO and CuO films have ultrafine particle sizes of < 50 nm and rough surface texture, while ZnO films consist of nanoscale platelets. This array was subjected to various VOC concentrations, including ethanol, acetone, toluene, and chloroform, one by one and in a pair/mix of gases. Thus, the response values show severe interference and departure from commonly observed power law behavior. The dataset obtained from individual gases and their mixtures were analyzed using multiple machine learning algorithms, such as Random Forest (RF), K-Nearest Neighbor (KNN), Decision Tree, Linear Regression, Logistic Regression, Naive Bayes, Linear Discriminant Analysis, Artificial Neural Network, and Support Vector Machine. KNN and RF have shown more than 99% accuracy in classifying different varying chemicals in the gas mixtures. In regression analysis, KNN has delivered the best results with an R2 value of more than 0.99 and LOD of 0.012 ppm, 0.015 ppm, 0.014 ppm, and 0.025 ppm for predicting the concentrations of acetone, toluene, ethanol, and chloroform, respectively, in complex mixtures. Therefore, it is demonstrated that the array utilizing the provided algorithms can classify and predict the concentrations of the four gases simultaneously for disease diagnosis and treatment monitoring.
Graphical Abstract