bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of LOXL2 induced by glucose metabolism-activated NF-κB in maintaining drug resistance through EMT and cancer stemness in gemcitabine-resistant PDAC
Authors: Lee Yun Sun , Kim Hyung Sun , KIM HYO JUNG , Kang Hyeon Woong , Lee Da Eun , Kim Myeong Jin , Hong Woosol Chris , Kim Ju Hyun , Kim Minsoo , Park Joon Seong 
Published: March 2023

Abstract
Gemcitabine is considered a standard treatment for pancreatic cancer, but developing drug resistance greatly limits the effectiveness of chemotherapy and increases the rate of recurrence. Lysyl oxide-like 2 (LOXL2) is highly expressed in pancreatic cancer and is involved in carcinogenesis and EMT regulation. However, studies on the role of LOXL2 in drug resistance are limited. Here, we investigated the mechanism of LOXL2 induction and the effect of LOXL2 on EMT and CSC in gemcitabine-resistant pancreatic cancer. Glucose metabolism was activated in gemcitabine-resistant pancreatic cancer cells, and NF-κB signaling was regulated accordingly.Activated NF-κB directly induces transcription by binding to the promoters of LOXL2 and ZEB1. The EMT process was significantly inhibited by the coregulation of ZEB1 and LOXL2. In addition, LOXL2 inhibition reduced the expression of cancer stemness markers and stemness by regulating MAPK signaling activity. LOXL2 inhibits tumor growth of gemcitabine-resistant pancreatic cancer cells and increases the sensitivity to gemcitabine in mouse models.
Student Academic Performance prognosticative Using optimized Hybrid Machine Learning Algorithms
Authors: Kannan Rajesh , Abarna K T Meena , Vairachilai S 
Published: March 2023

Abstract
Prediction of student performance at early stage in higher education is important for academic society so that strategic decisions can be made before students are placed to keep them from dropping out of the course. Due to India's massive student population and extremely ancient educational system, there are significant difficulties in measuring and forecasting students' performance. Every institution in India has its own unique set of criteria for measuring student achievement, and there is no formal process for keeping track of and evaluating a student's progress and improvement. Over the last decade, researchers in the education domain have presented numerous types of machine learning techniques. However, there are significant obstacles to dealing with imbalanced datasets in order to predict the performance of students. In this paper, the first phase of traditional classification algorithms has been applied to the dataset, which contains the progress of 4424 students. In the second phase, novel hybrid machine learning (ML) algorithms were used to get better predictions. The outcome of the proposed model makes it easier to predict how well students will do so that early decisions can be made about the growth of higher education institutions.
Rheological percolation, gel-like behavior and electrical conductivity of multi- walled carbon nanotubes filled ethylene-vinyl acetate copolymer/acrylonitrile- butadiene rubber nanocomposites
Authors: Razavi-Nouri Mohammad , Salavati Masoud 
Published: March 2023

Abstract
Rheological percolation, gel-like behavior and electrical properties of multi-walled carbon nanotubes (MWCNTs) filled ethylene-co-vinyl acetate/acrylonitrile-butadiene copolymer blends containing 0-7 wt% MWCNTs were studied. The Winter-Chambon criterion validity was evaluated for gelation of the system. The rheological and electrical percolation threshold, gel point (Pg), relaxation exponent (n), gel strength (Sg) and the fractal dimension (df) at the gel point were calculated. The formation of physical gel and rheological percolation threshold were both found to occur at 1 wt% MWCNTs concentration. Based on the df value determined, it was revealed that the system behaved similar to the one in which the excluded volume interactions were nearly screened. It was also found that the storage modulus (G') near the Pg followed a power law scaling relationship in the form G'=8257ε1.36 where ε=|P-Pg|/Pg is the distance from Pg. The electrical conductivity of the nanocomposites increased with the increase in MWCNTs loading after the nanofillers content surpassed a certain value. A schematic model was proposed to demonstrate electrical conduction with the increase in MWCNTs concentration. The excluded volume and hard core models were also employed to estimate the average aspect ratio of the nanofillers embedded in the system.
Desire for underweight among young Japanese women: perspectives on ideal body shape and measured body shape
Authors: Yasuda Tomohiro 
Published: March 2023

Abstract
We examined the actual situation of the desire to be thin among young Japanese women from the perspective of ideal body shape and actual measured body shape. In total, 90 young Japanese women were evaluated using a questionnaire (perceived body shape and desired body composition change) and assessments of physical fitness and sarcopenia (muscle strength, physical ability, and muscle mass). Participants were classified into the underweight (74%), normal (20%), or obesity (6%) groups. The normal weight group needed to gain 2.2 kg to become ideal, but participants desired a 4.5 kg weight loss (p<0.01). The underweight group needed to gain 10.3 kg to become ideal, but participants desired to maintain their present body weight. There were no differences (p>0.05) among the groups regarding the other physical fitness assessments, except for knee extension strength. Data on muscle mass for the sarcopenia diagnosis showed low values for the underweight group. Most participants were classified as the normal and underweight groups, but these groups showed a high percentage of a desire to be thin. The body shape of young adult women should be carefully considered not only as a health issue of thinness during the fertile period but also as a sarcopenia countermeasure (low skeletal muscle mass) for the ageing period.
A perspective of randomness in a clinical test of olfactory performance
Authors: Lötsch Jörn , Hummel Thomas , Ultsch Alfred 
Published: March 2023

AbstractBackground Random walks describe stochastic processes that result from a sequence of indeterminate changes in a random variable that are not correlated with past changes. This report describes a random walk component of a clinical sensory test of olfactory performance. The formal description of the stochastic process during the clinical test allows precise cutoffs to be set for the diagnosis of olfactory loss. Methods While odor discrimination (D) and odor identification (I) are tested in the Sniffin`Sticks olfactory test battery with four- and three-alternative forced-choice designs, respectively, the odor threshold (T) test embeds a three-alternative forced-choice paradigm in a seven-alternative staircase paradigm. This was investigated in computer simulation scenarios and then formally described. Results Odor threshold assessment test consists of two sequential parts, the first of which determines the starting point for the next. Both parts can be described as a biased random walk with highly unequal probabilities of moving toward higher (11%) or lower scores (89%). The odor concentration from which the first test part begins, and the length of the random walk in the subsequent second part were critical factors in the probability of accidentally achieving high test scores. Conclusions By changing the odor concentration from where the starting point determination for the second test part begins, the current cut-off of a composite test score at T + D + I < 16 indicating anosmia was raised from representing the 87th quantile of random test scores to representing the 97th quantile. The results likely apply to other sensory tests using the staircase paradigm that can also be described as random walks.
Automatic Identification of Posteroanterior Cephalometric Landmarks using a Novel Deep Learning Algorithm: A Comparative Study with Human Experts
Authors: Lee Hwangyu , Cho Jungmin , Ryu Susie , Ryu Seungmin , Chang Euijune , Jung Young-Soo , Kim Jun-Young 
Published: March 2023

Abstract
This aimed to propose a fully automatic posteroanterior (PA) cephalometric landmark identification model using deep learning algorithms and evaluate its accuracy and reliability compared with those of expert human examiners. In total, 1,032 PA cephalometric images were used for model training and validation. Two human expert examiners independently and manually identified 19 landmarks on 82 test set images. Similarly, the constructed artificial intelligence (AI) algorithm automatically identified the landmarks on the images. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the performance of the model. The performance of the model was comparable with that of the examiners. MRE of the model was 1.87 ± 1.53 mm, and SDR was 34.7%, 67.5%, and 91.5% within error ranges of < 1.0, < 2.0, and < 4.0 mm, respectively. The sphenoid points and mastoid processes had the lowest MRE and highest SDR in auto-identification; the condyle points had the highest MRE and lowest SDR. The fully automatic PA cephalometric landmark identification model showed promising accuracy and reliability, comparable with those of the examiners and can help clinicians perform cephalometric analysis more efficiently while saving time and effort. Future advancements in AI could further improve the model accuracy and efficiency.
A network analysis of risk and protective factors for suicidality among Chinese early adolescents: Based on a social-ecological perspective
Authors: Li Yuan , Li Peiying , Yuan Mengyuan , Li Yonghan , Zhang Xueying , Wang Gengfu , Su Puyu 
Published: March 2023

Abstract
Background Early adolescence is a period with the sharp increase in suicidality, especially in China. Understanding risk factors for suicidality in this critical period is a priority to inform suicide intervention strategies. This study aimed to explore a broad range of risk and protective factors for suicidality among Chinese early adolescents based on the ideation-to-action framework from the social ecology perspective.
Methods A stratified random cluster sampling approach was used to select 5,724 middle school students in Anhui Province, China, in November 2020. We used network analysis to examine the potential associations between putative correlates (sex, academic performance, serious physical illness/disability, history of self-harm, depression, impulsivity, sleep problems, resilience, family economic status, relationship with mother, relationship with father, family violence, childhood abuse, parental mental illness, relationship with teachers, relationship with classmates, school bullying victimization and perpetration, social support, satisfaction with society) and suicidal ideation, plans, and attempts.
Results In the sample, 37.9%, 19.0%, and 5.5% of students reported suicidal ideation, plans, and attempts, respectively. The estimated network revealed that suicidal ideation, plans, and attempts were all significantly associated with individual- (history of self-harm, sleep problems), family- (childhood abuse), and school-level (school bullying victimization) factors. Based on centrality analysis, the most influential nodes in the network were childhood abuse and depression. Notably, the network results showed unique correlates of suicidal ideation (sex, impulsivity, family violence, relationship with teachers, school bullying perpetration), plans (social support), and attempts (relationship with mother, parental mental illness).
Conclusions This study findings have important implications for suicide prevention in Chinese early adolescents: 1) focusing on the key risk factors for suicidality in the network; 2) separately exploring risk and protective factors for specific suicidality; and 3) highlighting the importance of joint interventions across multiple sectors when developing suicide intervention strategies.
Probing amagmatic fluids in porphyry deposits via a mono- intrusion system at Tongchang (Dexing, SE China)
Authors: Liu Xuan , Richard Antonin , Pironon Jacques , Yang Kuifeng 
Published: March 2023

Abstract
Porphyry deposits contain large amounts of base metals, and bear important fingerprints of magmatic and hydrothermal processes in convergent and collided plate margins. For decades, source of amagmatic fluid and its role in sulfide deposition in porphyry systems has been equivocal.
The Tongchang mono-intrusion porphyry deposit is studied for fluid sources and depositional mechanisms. In-situ quartz O and anhydrite Sr isotope analyses revealed a coexistence of magmatic and amagmatic (groundwater and residue metamorphic) fluid reservoirs, spatially separated by an impermeable zone formed by quartz deposition near brittle-ductile transition in phyllite. The impermeable zone sealed inside amagmatic components. The early and early-intermediate fluid stages were dominated by magmatic fluids forming high-T disseminated Cu sulfides (>400 °C). The late-intermediate stage was marked by retreating of the brittle-ductile interface and creation of an intermediate zone below the impermeable quartz seal. Rupturing of the intermediate zone at 350 °C to 300 °C caused incursion of the sealed amagmatic fluids leading to deposition of vein-type Cu sulfides. The late fluid stage was characterized by massive invasion of evolved groundwater and ore remobilization in response to volumetric contraction of the fluid system. Four universal models are envisaged to account for variabilities in amagmatic availability and thermal histories in porphyry deposits.
Application of image recognition based on neural network algorithm in multimedia dance teaching
Authors: Jin Gao 
Published: March 2023

Abstract
Neural network recognition algorithm is a deep learning-based convolutional neural network, which has been applied to target detection, image recognition, sound recognition and other fields. Although the recognition technology of convolutional neural network has been gradually stabilized, it is mainly implemented in single machine serial mode. Therefore, there will be problems such as too long training time and insufficient memory capacity. According to the previous work, this paper has carried out related research and obtained some useful results. This paper focuses on the introduction of image recognition technology based on neural network algorithm. At the same time, this paper proposes a fast real-time image recognition algorithm, which has high recognition accuracy. In this paper, the existing algorithms mentioned in the paper are analyzed, the characteristics and shortcomings of all algorithms are summarized, and the appropriate combination of algorithms is selected for specific problems. On this basis, the acceleration method of artificial neural network is used to improve the algorithm of convolutional neural network image recognition technology. With the continuous development of education and the increase of the number of students year by year, the effect of classroom teaching becomes particularly important. Therefore, modern information technology is used to transfer the classroom teaching mode to the network and realize a new method of online remote online dance teaching. According to the actual situation of dance teaching, the advantages of multimedia dance teaching are analyzed. The software of multimedia dance teaching system is tested comprehensively, from the aspects of computer system memory occupancy rate and temperature, to test whether the activities of B/S mode multimedia dance teaching system meet the expected goals and requirements of each core module of multimedia dance teaching system.
Application of User Behavior Recognition Based on edge computing Resource Allocation in English Online Teaching
Authors: Wang Sufang 
Published: March 2023

Abstract
In recent years, task offloading and resource allocation schemes in edge computing systems have received extensive attention from scholars, but many of them only focus on static offloading schemes without considering long-term performance. In order to optimize the long-term average performance, the randomness of task arrival, the dynamic changes of wireless channels and the dynamics of terminals, making the research on dynamic unloading and resource allocation full of challenges. In order to improve the accuracy of user behavior identification, this paper summarizes the theory of mobile edge computing, discusses the technical theory of task loading in MEC systems, and further expands the research on MEC servers, This paper proposes a deep learning system based on SDAL-DNM, which uses edge computing to generate user behavior data and target user behavior data in the same space, constantly narrowing the distance between the characteristics of user behavior data, and the deep network adjusts itself to be as close to user behavior data as possible, and improves the accuracy of user behavior. Therefore, the resource allocation method of mobile edge computing in this paper summarizes the background and importance of user behavior recognition in the application of English online teaching, and then introduces several specific examples of online teaching platforms. Therefore, this paper summarizes the guiding ideology of the design of a network English teaching platform.
The Complete Mitochondrial Genome of Morishitium polonicum (Trematoda,Cyclocoelidae) and its phylogenetic implications
Authors: Liu Shuang , Liu Yafang , Chen Bin , Lu Xinyan , Jiang Dandan , Yang Guoping , Geng Ling , Wang Xuan , Peng Kexin , Du Chunhong , Ren Tianguang , Yang Xing 
Published: March 2023

Abstract
In wild animals, trematodes can result adversely impact the health and survival. Cyclocoelidae Stossich, large digenean bird parasites, lacks of molecular analysis that reclassifications have not been supported. This study produced the first fully determined and annotated mitochondrial genome sequence for the trematode Morishitium polonicum. The whole length of the M. polonicum (GenBank accession number: OP930879) mitogenome is 14083 bp, containing 22 transfer ribonucleic acids (tRNAs), 2 ribosomal RNAs (rRNAs, rrnL and rrnS), and a non-coding control section (D-loop) 13777 to 13854 bp in length. The 12 PCGs area has 3269 codons and a total length of 10053 bp, which making up 71.38% of the mitochondrial genome’s overall sequence. Most (10/12) of the PCGs that code for proteins began with ATG, while the nad4L and nad1 genes had a GTG start codon. Phylogenetic analysis using the concatenated nucleotide sequences of 12 PCGs, and the ML tree analysis results showed that M. polonicum is more closely related to with Echinostomatidae and Fasciolidae, which indicates that the family Cyclocoelidae is more closely associated with these Echinochasmidae. This study will provide mtDNA information, increasing analysis of mitogenomic structure and evolution. Moreover, understand the phylogenetic relationship of the fluke.
IL-27 enhances peripheral B cell glycolysis of rheumatoid arthritis patients via activating mTOR signaling
Authors: Qi Jingjing , Liu Jiaqing , Zhao Xiangge , Huang Huina , Tang Yawei , Li Xia 
Published: March 2023

Abstract
Objective Our previous study found that increased serum IL-27 could promote rheumatoid arthritis (RA) B cell dysfunction via activating mTOR signaling pathway. This study aimed to explore the effects of IL-27 on B cell metabolism and clarify the mechanisms via which IL-27 enhancing glycolysis to induce B cells hyperactivation.
Methods Peripheral CD19+ B cells were purified from healthy controls (HC) and RA patients and then cultured with or without anti-CD40/CpG and glycolysis inhibitor 2-deoxy-D-glucose (2-DG) or mTOR inhibitor rapamycin. Furthermore, the isolated CD19+ B cells were treated by HC serum or RA serum in the presence and absence of recombinant human IL-27 or anti-IL-27 neutralizing antibodies or 2-DG or rapamycin. The B cell glycolysis level, proliferation, differentiation, and inflammatory actions were detected by qPCR, flow cytometry or ELISA.
Results Compared to HC B cells, glycolysis was increased significantly in RA B cells and glycolysis inhibition downregulated the proliferation, differentiation, and inflammatory actions of RA B cells. RA serum and IL-27 promoted B cell glycolysis, which could be obviously rescued by anti-IL-27 antibodies or mTOR inhibitor rapamycin.
Conclusion Enhanced cellular glycolysis of RA B cells induced by IL-27 might contribute to B cells hyperactivation through activating the mTOR signaling pathway.
Spring migration patterns of red knots in the Southeast United States disentangled using automated telemetry
Authors: Smith Adam D. , Sanders Felicia J. , Lefevre Kara L. , Thibault Janet M. , Kalasz Kevin S. , Handmaker Maina C. , Smith Fletcher M. , Keyes Tim 
Published: March 2023

Abstract
Background and Methods
Shorebirds evolved flexibility in their migration strategies, with demonstrated variation even within the same population. Research in the last decade revealed diverse migration routes for red knots using the Western Atlantic flyway. Red Knots use the Southeast United States (North and South Carolina, Georgia, and Florida) as a stopover during north and southbound migration and during the winter. We examined northbound red knot migration routes and timing from the Southeast United States using an automated telemetry network. Our primary goal was to evaluate the relative use of an Atlantic migratory route through Delaware Bayversus an inland route through the Great Lakes en route to Arctic breeding grounds and to identify areas of apparent stopovers. Secondarily, we explored the association of red knot routes and ground speeds with prevailing atmospheric conditions.
Results
Most Red Knots migrating north from the Southeast United States skipped or likely skipped Delaware Bay (73%) while 27% of the knots stopped in Delaware Bay for at least 1 day. Most birds that skipped Delaware Bay traveled north, through the eastern Great Lake Basin. A few knots used an Atlantic Coast strategy that did not include Delaware Bay, relying instead on the areas around Chesapeake Bay or New York Bay for stopovers. We did not detect stopovers in the Great Lakes Basin suggesting that knots move quickly through this region. Nearly half of the red knots were detected in either James Bay or Hudson Bay with the first day of detection ranging from 19 May to 7 June. Nearly 80% of migratory trajectories were associated with tailwinds at departure.
Conclusions
Most knots tracked in our study did not stop in the Great Lakes, thus making the Southeast United States the last terminal stopover for some knots before reaching Arctic habitats. This study demonstrates the diversity of red knot spring migration routes and underscores how critically important the Southeast United States is as a spring stopover site for red knots. Future conservation planning must include the full network of sites that support the varied migratory routes and strategies used by this declining shorebird species.