bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulation study on response characteristics of water rich fracture zone in metal mine monitored by resistivity method
Authors: Yao Xiwen , Zhao Zexi , Xu Kaili , Xu Xiaohu , Chen Mao 
Published: March 2023

Abstract
Water inrush accidents in metal mines are prone to occur during the construction and production process of mines, which can cause serious casualties and property losses. The prevention of accidents in metal mines is closely related to geophysics. In order to solve the problem of accurately monitoring water permeability, the resistivity method was proposed to effectively monitor water rich fault zones in metal mines. The typical metal mine and water rich fracture zone model are simulated by ANSYS. The calculated resistance data are processed by inversion image processing and compared with the original model; The inversion image clearly shows the abnormal area of the water fracture zone and the location is relatively accurate, which verifies the reliability of the numerical simulation method and the resistivity theory. At the same time, the response characteristics of water rich fracture zone of metal ore under different water content and different development distance are studied by using numerical simulation method. The results show that the resistivity measured by electrical method decreases with the increase of water content in the water rich fracture zone, and the resolution of low resistivity anomaly is strong. When the measuring node of high-density electrical method is inside the water rich fracture zone, the resistivity change curve tends to be a straight line; When the measuring node of high-density electrical method is not near the water rich fracture zone, the resistivity change line tends to curve. In addition, with the expansion and development of the water rich fracture zone, the electrical resistance at the measuring node decreases; When the water rich fracture zone is about to develop and reach the measuring node, the measured resistance value has an abnormal mutation. This paper reveals the characteristics of resistivity and pervious precursor response through numerical tests, and clarifies that resistivity decline and abnormal mutation are important pervious precursor information, which has important reference significance for the monitoring and prediction of pervious disasters in practical projects.
Current status of artificial intelligence in cancer management: emerging trends, limitations and future outlook
Authors: Ali Mohammad , Wani Shahid Ud Din , Khan Abdul Arif , Dey Tathagata , Salahuddin Md 
Published: March 2023

AbstractArtificial intelligence (AI) has been abetted in the progression of health care research including cancer research. Simultaneously, in this review, we anticipate the future outlook of AI. AI can adjust the usage of anticancer drugs and also can estimate the tolerance of anticancer drugs, thus improving cancer chemotherapy. AI can assist physicians to make accurate decisions for treatment, and decrease unnecessary surgeries, moreover AI aid oncologists to progress the strategies for cancer patient's treatment. NCI suggests that AI, Machine learning (ML), and deep learning (DL) all can be used to progress cancer care as well as patient outcomes. In cancer management, AI can progress the precision and rapid diagnosis, help in making a clinical decision, and also lead to better health outcomes. AI technologies i.e. ML can intensely enhance the current approach to anticancer drug research. We discuss cancer diagnostics in the oncology-associated area wherein clinically AI already has shown a huge effect. But currently recognized AI also has some limitations. In the current review, the progression of AI technology i.e. ML and DL in anticancer drug research, furthermore presents applications, limitations, and future directions in cancer. With the growing trend of the uses of AI in cancer research, ML has an important future in prognostication and decision-making.
PCSK7: a Novel Regulator of Apolipoprotein B and a Potential Target Against Non-Alcoholic Fatty Liver Disease
Authors: Seidah Nabil , Sachan Vatsal , Dévéhat Mailys Le , Roubtsova Anna , Essalmani Rachid , Garçon Damien , Susan-Resiga Delia , Duval Stéphanie , Mikaeeli Sahar , Hamelin Josée , Evagelidis Alexandra , Chong Michael , Pare Guillaume , Chernetsova Elizabeta , Gao Zu-hua , Robillard Isabelle , Ruiz Matthieu , Trinh Vincent Quoc-Huy , Estall Jennifer , Faraj May , Laurendeau Jean-Francois , Austin Richard , Sauvageau Martin , Prat Annik , Kiss Robert Scott 
Published: March 2023

Abstract
Epidemiological evidence links the proprotein convertase subtilisin/kexin 7 (PCSK7) to triglyceride (TG) metabolism. PCSK7-SNPs gain-of-function and loss-of-function variants were associated with higher and lower levels of plasma apoB and TGs, respectively. Herein, we biochemically defined the in vivo role of PCSK7 in lipid metabolism using full-body Pcsk7-/- mice and hepatic cell lines. Non-enzymatically membrane-bound PCSK7 binds apoB100 in the endoplasmic reticulum and enhances its secretion. Mechanistically, the loss of PCSK7/Pcsk7 leads to apoB degradation, triggering an unfolded protein response, autophagy, and β-oxidation, eventually reducing hepatic lipid accumulation. We investigated whether Pcsk7-/- mice could better recover from a NAFLD-inducing 12-weeks high fat/fructose/cholesterol diet when followed by a 4-weeks regular diet. Livers of Pcsk7-/- mice more effectively and safely recovered than those of wild-type mice. These findings were validated following subcutaneous administration of hepatocyte-targeted N-acetylgalactosamine (GalNac)-antisense-oligonucleotides (ASOs) against Pcsk7, strongly supporting the therapeutic intervention of hepatocyte PCSK7 mRNA silencing for NAFLD treatment.
An analysis of codon utilization patterns in the chloroplast genomes of three species of Coffea
Authors: Li Yaqi , Hu Xiang , Xiao Mingkun , Huang Jiaxiong , Lou Yuqiang , Hu Faguang , Fu Xingfei , Li Yanan , He Hongyan , Cheng Jinhuan 
Published: March 2023

Abstract
Background
Chloroplast genome has the characteristic of small genome size and low rate of mutation and recombination, which has been used in plant phylogeny, molecular evolution, and pedigree geography, normally. Codon usage bias is an important evolutionary feature of organisms, plays a crucial role in the study of species evolution, gene function and foreign gene expression. Coffee is extremely important in the world's tropical agricultural economy, international trade and human daily life. Studying the codon usage bias of coffee genome is of great significance to guide the subsequent coffee research work, such as the selection of efficient heterologous expression system required for coffee genetic transformation.
Results
The findings demonstrated a high degree of utilization pattern commonality among the three coffee genome codons. The three types of coffee had identical base chemical compositions, high A/T content, low G/C content, and A/T ends were favored for codons in all three types of coffee. The three types of coffee contained 30 high frequency codons, 96.67% of which were codons with the A/T ending. The ideal codons totaled fourteen. Natural selection was the primary impacting force, as seen by the findings of the ENc-GC3s mapping, PR2 analysis, and neutral analysis, which revealed that the three coffee codon utilization patterns were driven by a variety of mechanisms. The most effective heterologous expression receptor for the three coffee genes was tobacco, which could be employed in Arabidopsis thaliana, Nicotiana tabacum, Escherichia coli, and Saccharomyces cerevisiae.
Conclusion
This study demonstrates how the three coffee genomes' codon use patterns are remarkably similar and primarily influenced by natural selection. Understanding the gene expression properties of coffee and investigating the laws governing its genetic evolution are made possible by the study on the preference of the three coffee codons. The study's findings can help foreign genes express themselves more effectively and serve as a foundation for future coffee evolution guidelines.
Sonochemical Microstructuring of Sodium Alginate to Increase its Effectiveness in Bakery
Authors: Paymulina Anastasia , Potoroko Irina , Naumenko Natalia , Motovilov Oleg 
Published: March 2023

Algae are a source of many biologically active compounds that can be used in food production to expand the range of functional products. For instance, sodium alginate possesses a complex of scientifically proven biologically active properties. In the food industry, it usually serves as a thickener, stabilizer, gelatio n agent, and water-retaining agent. The biological activity of this polysaccharide and its effect on the technological properties of food systems depend on the molecular weight and particle size uniformity. The present research objective was to study the method of sonochemical microstructuring of sodium alginate to increase its biological activity and efficiency as part of v arious bakery formulations.
The research featured alginate gels, yeast suspensions of Saccharomyces cerevisiae, and bakery products. The sonochemical microstructuring of sodium alginate involved a low-frequency ultrasonic treatment at 240, 435, and 630 W/L and 50°C for 20, 25, and 30 min. The effect of the treatment included the following indicators: particle morphology vs. distribution of the hydrodynamic particle diameter in a dispersed medium, antioxidant activity, dynamic viscosity, in vitro bioactivity, and bioavailability against Paramecium caudatum and S. cerevisiae. The quality assessment of bakery products followed State Standard 58233-2018.
The process of sonochemical microstructuring depolymerized large particles of sodium alginate into shorter ones: 5670 nm – 30.6%, 502 nm – 53.4%, 56.1 nm – 16%. It increased the antioxidant activity by 7 times and the potential in vitro bioactivity by 3.9%. The microstructured sodium alginate improved the fermentation activity of S. cerevisiae and reduced the yeast biomass by 8%. The resulting bakery products had a greater porosity by 5.9% and antioxidant activity by 3.7 times.
The sonochemical microstructuring reduced the particle size of sodium alginate, as well as increased its biological activity. The sonochemically microstructured sodium alginate demonstrated a great potential for baked foods.
Effect of Whole Barley Tolokno on the Quality of Biscuits
Authors: Misteneva Svetlana , Shcherbakova Natalia , Kondrat’ev Nikolay 
Published: March 2023

Benefit of dietary fiber has proven by clinical studies. Dietary fiber can be incorporated into food products with whole grain cereals. Whole barley tolokno is a valuable source of soluble dietary fiber β-glucans. As a result, it is often used in fortified bakery products. The research objective was to modify the dietary profile of biscuits by substituting refined wheat flour with barley tolokno.
The study featured refined wheat flour, barley tolokno, composite flours, model suspensions, and formulations of biscuits. Standard methods helped to measure the sensory profile, physicochemical parameters, fatty acid composition, structural characteristics, and mechanical properties of the research objects.
The content of dietary fiber in the flour and the tolokno was 3.7 and 19.8%, respectively. The fatty acid composition of the tolokno differed from that of the wheat flour. The content of oleic acid was 21.1 in the tolokno and 15.9% in the flour, while the content of linoleic acid was 46.8 in the tolokno and 54.0% in the flour. A greater proportion of tolokno in the composite flour led to an increase in the content of dietary fiber (3.7–11.8%), protein (11.5–12.8%), and fat (1.4–2.7%). The water and fat absorption capacity of composite flours increased by 125 and 65.7%, respectively, when the share of tolokno reached 50%. As the proportion of tolokno increased, the viscosity of the model suspensions rose from 3.1 to 17.3 Pa·s at a minimal shear rate. The water absorption capacity of the control sample was 190%: in the experimental biscuits, it rose from to 221 and 227% at 30 and 40% of tolokno, respectively. Extra tolokno also increased the content of dietary fiber in the biscuit, which reached 7.53% in the sample with 50% tolokno. The experimental biscuits were even in shape, surface, and porosity; they had a balanced taste and a pleasant smell with a slight grainy tint.
The optimal proportion of barley tolokno was 40%. This amount brought up the content of dietary fiber to 6.5 g per 100 g. The resulting biscuits could be classified as products rich in dietary fiber (Technical Regulations of the Customs Union 022/2011). The research made it possible to expand the range of functional biscuits fortified with native dietary fiber and whole grain raw materials.
Effect of Microwave Radiation on the Chemical Composition of Chickpeas
Authors: Khramova Valentina , Surkov Dmitry , Lubchinsky Kirill 
Published: March 2023

Chickpea (Cicer arietinum L.) is rich in protein and has a balanced amino acid profile. However, its characteristic bean flavor limits its use as a functional food ingredient. Microwave treatment may help to solve this problem. The research objective was to select the optimal parameters of microwave treatment to obtain chickpea samples with no bean flavor and to study their chemical composition.
The study featured chickpeas of the Volzhanin variety. The experimental samples were processed in a microwave oven with a magnetron frequency of 2450 MHz at different power and time values. The protein tests, the analysis of amino acid profile, and the sensory assessment involved standard research methods.
The microwave processing loosened the consistency of chickpeas and eliminated the bean flavor after 5–6 min at 200 W or 3 min at 400 W. A longer treatment time resulted in a peanut flavor followed by bitterness. The microwave treatment reduced the mass fraction of protein and the amount of essential amino acids. This process could be slowed down by increasing the power of microwave radiation and reducing the processing time. However, the intensification had a negative effect on the content of arginine, methionine, and tyrosine in chickpea protein.
The results obtained can make it possible to use chickpeas as a functional food ingredient.
Assessing the Biological Safety of Dairy Products with Residual Antibiotics
Authors: Chaplygina Olga , Kozlova Oksana , Zharko Maria , Petrov Andrey 
Published: March 2023

Antibiotics have traditionally been used to prevent and treat common diseases in farm animals. However, residual antibiotics in dairy products and meat remain a serious public health problem, which is associated with antibiotic resistance. The research objective was to assess the impact of antibiotic contamination on the quality and safety of dairy products, the microbiological composition of milk, and antibiotic-resistant bacteria.
The study featured six years of Russian and foreign scientific articles registered in PubMed (National Center for Biotechnology Information, USA), Scopus and ScienceDirect (Elsevier, the Netherlands), Web of Science (Clarivate, USA), and eLibrary.ru.
The analysis involved 63 foreign and domestic sources. Residual antibiotics in milk inhibits the vital activity of lactic acid bacteria, which, in its turn, disrupts the technological process of yogurts, cheeses, etc. After such processing as normalization, pasteurization, and homogenization, antibiotics accumulate in fermented dairy products and bind with milk proteins and fats. Antibiotics, in their initial amount, enter yoghurts from dairy raw materials. In cheese production, antibiotics usually pass into the whey, but aminoglycosides, quinolones, and tetracyclines remain in the finished product because they bind with the protein fraction.
The problem of biological safety of dairy products is associated with antibiotic resistance developed by human intestinal microbiota. This problem remains understudied, and the number of scientific papers on the matter is limited.
Enabling Early Health Care Intervention by Detecting Depression in Users of Web-Based Forums using Language Models: Longitudinal Analysis and Evaluation
Authors: Owen David , Antypas Dimosthenis , Hassoulas Athanasios , Pardiñas Antonio F , Espinosa-Anke Luis , Collados Jose Camacho 
Published: March 2023

Background
Major depressive disorder is a common mental disorder affecting 5% of adults worldwide. Early contact with health care services is critical for achieving accurate diagnosis and improving patient outcomes. Key symptoms of major depressive disorder (depression hereafter) such as cognitive distortions are observed in verbal communication, which can also manifest in the structure of written language. Thus, the automatic analysis of text outputs may provide opportunities for early intervention in settings where written communication is rich and regular, such as social media and web-based forums.

Objective
The objective of this study was 2-fold. We sought to gauge the effectiveness of different machine learning approaches to identify users of the mass web-based forum Reddit, who eventually disclose a diagnosis of depression. We then aimed to determine whether the time between a forum post and a depression diagnosis date was a relevant factor in performing this detection.

Methods
A total of 2 Reddit data sets containing posts belonging to users with and without a history of depression diagnosis were obtained. The intersection of these data sets provided users with an estimated date of depression diagnosis. This derived data set was used as an input for several machine learning classifiers, including transformer-based language models (LMs).

Results
Bidirectional Encoder Representations from Transformers (BERT) and MentalBERT transformer-based LMs proved the most effective in distinguishing forum users with a known depression diagnosis from those without. They each obtained a mean F1-score of 0.64 across the experimental setups used for binary classification. The results also suggested that the final 12 to 16 weeks (about 3-4 months) of posts before a depressed user’s estimated diagnosis date are the most indicative of their illness, with data before that period not helping the models detect more accurately. Furthermore, in the 4- to 8-week period before the user’s estimated diagnosis date, their posts exhibited more negative sentiment than any other 4-week period in their post history.

Conclusions
Transformer-based LMs may be used on data from web-based social media forums to identify users at risk for psychiatric conditions such as depression. Language features picked up by these classifiers might predate depression onset by weeks to months, enabling proactive mental health care interventions to support those at risk for this condition.
Predicting Undesired Treatment Outcomes With Machine Learning in Mental Health Care: Multisite Study
Authors: Van Mens Kasper , Lokkerbol Joran , Wijnen Ben , Janssen Richard , de Lange Robert , Tiemens Bea 
Published: March 2023

Abstract

Background
Predicting which treatment will work for which patient in mental health care remains a challenge.

Objective
The aim of this multisite study was 2-fold: (1) to predict patients’ response to treatment in Dutch basic mental health care using commonly available data from routine care and (2) to compare the performance of these machine learning models across three different mental health care organizations in the Netherlands by using clinically interpretable models.

Methods
Using anonymized data sets from three different mental health care organizations in the Netherlands (n=6452), we applied a least absolute shrinkage and selection operator regression 3 times to predict the treatment outcome. The algorithms were internally validated with cross-validation within each site and externally validated on the data from the other sites.

Results
The performance of the algorithms, measured by the area under the curve of the internal validations as well as the corresponding external validations, ranged from 0.77 to 0.80.

Conclusions
Machine learning models provide a robust and generalizable approach in automated risk signaling technology to identify cases at risk of poor treatment outcomes. The results of this study hold substantial implications for clinical practice by demonstrating that the performance of a model derived from one site is similar when applied to another site (ie, good external validation).
Litoesculturas del período Formativo en Chillia (Patáz, La Libertad-Perú): una aproximación a su cronología y significado.
Authors: Villar Quintana Anthony 
Published: March 2023

El artículo presenta el estudio de las representaciones de dos litoesculturas provenientes de Chillia y Ushno de Agotuna, dos sitios arqueológicos del distrito de Chillia, en la provincia de Pataz, departamento de La Libertad, en el norte peruano. Dicha investigación consistió en un estudio inicial y general de las representaciones iconográficas plasmadas en estos soportes líticos.
Mediante esta investigación se busca reconocer el estilo y posición cronológica de ambas esculturas dentro del período Formativo. De esta manera, también buscamos aproximarnos a las implicancias de estas representaciones en la cosmovisión de quienes las elaboraron. Consideramos así, que la litoescultura de Chillia fue elaborada entre el Formativo Temprano y Medio, mientras que la de Ushno de Agotuna entre el Formativo Medio y Tardío. Las representaciones plasmadas en ambas litoesculturas presentan rasgos que podrían definirlos como seres míticos, deidades u oficiantes de cultos religiosos. Por otra parte, también notamos que algunos aspectos de estas representaciones reflejan que esta área estuvo inserta dentro de flujos de interacción interregionales.
Validación del cuestionario de experiencia sexual en línea (OSEQ) en estudiantes universitarios mexicanos
Authors: Guajardo Garcini Daniel Arturo , De la Rosa Gómez Anabel , Mancilla Díaz Juan Manuel , Serrano Zárate Berenice 
Published: March 2023

Antecedentes: el Cuestionario de Experiencia Sexual en Línea (OSEQ) es un instrumento diseñado para medir las actividades sexuales en línea en población canadiense. Por la novedad del tema y el impacto en las prácticas y conductas sexuales de los jóvenes adultos, es relevante su estudio en población mexicana, en donde la investigación es incipiente, a pesar de que la contingencia sanitaria, generada por la COVID-19, haya provocado un aumento en el consumo de esta clase de conductas.
Objetivo: adaptar, confiabilizar y validar en población universitaria de México el Online Sexual Experience Questionnaire.
Método: participaron 483 estudiantes (145 hombres y 338 mujeres) del sistema de universidad a distancia, de entre 18 y 69 años (M= 32.58, D. E.=9.21), quienes fueron seleccionados a partir de un muestreo no probabilístico por conveniencia y se les aplicaron los cuestionarios vía internet.
Resultados: del análisis factorial exploratorio se respetaron los factores originales del instrumento, reduciendo de 48 a 13 ítems, con una alfa de .85; del análisis factorial confirmatorio, los valores obtenidos (Chi= 134.72, gl= 58, Cmin/Df=2.323.135, p= .000, NFI= .961, RFI= .948, CFI= .977 y RMSEA= .052) fueron adecuados.
Conclusión: el instrumento muestra niveles aceptables, similares a los obtenidos en el cuestionario original.