bluuebunny/crossref_metadata_2025 huggingface dataset:
Deciphering Molecular Underpinnings and Therapeutic Avenues for Eczema and Atopic Dermatitis through Integrated Omics and Immunohistochemical Analysis
Authors: Yang Fang , Lin Cong , Yan Youcai
Published: September 2024

Objective This study aims to comprehensively explore the comorbidity mechanisms of eczema and atopic dermatitis (AD) through the integrated application of weighted gene co-expression network analysis (WGCNA), machine learning, and bioinformatics methods. The goal is to identify potential therapeutic targets and provide a profound understanding of these two skin conditions.
Methods: We conducted weighted gene co-expression network analysis (WGCNA) and differential gene expression (DEGs) analysis using the Gene Expression Omnibus (GEO) databases GSE6012, GSE14550, GSE32924, and GSE120721. By intersecting the results, we identified 22 genes that are commonly expressed in eczema and atopic dermatitis. Functional enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), disease prediction, and protein-protein interaction (PPI), were performed on these genes. Subsequently, key hub genes—CCL18, GZMB, and IRF7—were selected using random forest in machine learning and the cytohubba function in Cytoscape. We further explored the relationships between these three genes and immune cells through CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA), establishing a mRNA-miRNA-lncRNA ceRNA regulatory network.
Results: Enrichment analysis revealed that these 22 genes are predominantly involved in processes such as cytokine-mediated signaling pathways, leukocyte migration, leukocyte chemotaxis, neutrophil chemotaxis, and humoral immune responses. Additionally, they are associated with various skin-related diseases, including atopic dermatitis. Machine learning and network analysis confirmed CCL18, GZMB, and IRF7 as key genes. Immunoinfiltration analysis further elucidated the associations of these genes with different immune cells.
Conclusion: The results of this study suggest that CCL18, GZMB, and IRF7 may serve as potential biomarkers for eczema and atopic dermatitis, holding significant clinical prospects. These genes play crucial roles in various biological processes and immune regulation, providing robust support for unraveling the comorbidity mechanisms of these two skin conditions. This discovery offers essential clues for future exploration of therapeutic targets and clinical interventions, potentially advancing research in the treatment of eczema and atopic dermatitis.
A Bootstraps Theory of Equity (and Why We Need to Change It)
Authors: Mueller Amy
Published: September 2024

The discourses educators use have power. Teacher talk positions students and educators and builds storylines in speech acts which speak to larger cultural narratives and norms. This article explores educators positioning of equity throughout emergency online schooling revealing a cultural storyline where educators feel they carry the burden of increasing social inequity while simultaneously often positioning themselves helpless or extremely limited in a system which they view as unchanging and unsupportive. Resulting, often, to ascribing a neoliberal bootstrap’s theory of equity in online education where learners are expected to succeed through rugged individualism in a perceived meritocracy which only serves to further ingratiate inequities. Moreover, the storylines and positioning of educators’ selves illustrate another crisis in education which began well before the pandemic, the disempowerment and deprofessionalization of educators and burnout and shortages that it helps fuel.
Toward safer flight training: The data-driven modeling of accident risk network using text mining based on deep learning
Authors: Zhuang Zibo , Hou Yongkang , Yang Lei , Gong Jingwei , Wang Lei
Published: September 2024

The flight training, a critical component of the general aviation industry, exhibits a relatively high severity of risk due to its complexity and the uncertainty inherent in risk interactions. To mine the risk factors and dynamic evolution characteristics affecting flight safety, a data-driven network modeling methodology that integrates text mining with domain knowledge in accident analysis is proposed for the analysis of accident risks specific to flight training. Firstly, flight training accident reports are labeled using domain knowledge gained from accident causation theory to provide basic data for subsequent study. Secondly, the adversarial training algorithm is introduced to enhance the generalization capability of BERT model in processing imbalanced accident textual data. The fine-tuned BERT, Bi-directional Long Short-Term Memory (Bi-LSTM) Conditional Random Field (CRF) algorithm is fused to construct an ensemble algorithm for risk identification, which accomplishes the joint entity-relationship extraction of accident reports. Thirdly, based on the risk identification results, data-driven modeling of the Flight Training Risk Network (FTRN) is performed to quantify the accident evolution characteristics. Then, the aforementioned tasks are meticulously optimized and integrated, subsequently applied to a case study focusing on loss of control in flight (LOCI) accidents. The findings suggest that the identification algorithm effectively and efficiently extracts risk information and interrelationships. Additionally, the network analysis results reveal the key insights into flight training accidents, facilitating the development of holistic risk control strategies. This study provides offers a powerful and innovative analytical tool for safety management departments, enhancing safety and reliability in flight training operations.
Assessment of Spring Passerine Migration Using Radar Over Magadino (Switzerland) Stopover Site
Authors: Giuntini Silvia , Tattoni Clara , Patocchi Nicola , Lardelli Roberto , Martinoli Alessio , Preatoni Damiano G.
Published: September 2024

Radar technology has emerged as a vital tool for studying bird migration, particularly due to the predominantly nocturnal and high-altitude nature of the phenomenon. Avian Vertical-looking Radars (AVLRs) offer detailed insights into migratory patterns, including flight behavior and altitude. Bird ringing, on the other hand, although useful for describing migratory phenomena at the species level, has limitations when used to quantify migration itself. In this study, radar data from the Bolle di Magadino wetland area in Switzerland were analyzed to describe and quantify the spring migration of passerine birds during 2021 and 2022. Migration activity was significantly higher during the night, with migratory peaks reached at night in mid-April in 2021 and in the second half of April in 2022. Passerine flight altitudes remained consistently higher at night than during the day. Also, the analysis of wing-flapping frequency (WFF) revealed both seasonal and diel variations, with WFF slowly increasing at night as the season went on, but remaining higher and stable during the day. A GLM did not reveal significant effects of rain and wind intensity on migratory traffic, but it did show a positive and strongly significant relationship with the number of ringed birds (beta = 0.55, p < 0.001). This confirms for the first time a positive proportionality between ground-based monitoring and radar-based monitoring in a stoHpover area, where theoretically we would have expected a weaker relationship between the number of ringed birds and MTR, compared to places where the migratory flow is uninterrupted and the birds have no means to stop.
Developing and Validating the Habits of Mind Scale for Secondary School Students in Kuwait
Authors: Muneera Ghablan , Husni Mariwan , Khadhari Sulaiman Al
Published: September 2024

Title Developing and Validating the Habits of Mind Scale for Secondary School Students in Kuwait Introduction The purpose of this study is to develop and validate the habits of mind scale (HOMS) in the Kuwaiti context. Methods Survey data from 910 secondary-school students were collected in two phases and examined using an exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results The results of the second-order EFA revealed a single factor, which accounted for approximately 70% of the total variance. In the second-order confirmatory factor analysis, the statistical fit indices indicated a good fit for the one-factor model. The 97 items comprising this scale produced an alpha coefficient between .82 and .90 for the 16 domains (habits) and .93 for the entire scale. Conclusions The HOMS appeared to be a consistent measure of mind habits. These results demonstrate that the HOMS is a valid and reliable measure, which may be useful in guiding future research aimed at understanding student habits of mind.
Flood Hazard Area mapping Using GIS and AHP in Awash River Basin (ARB), Ethiopia
Authors: Tilahun Abayneh , Gebremariam Ephrem , Desta Hayal
Published: September 2024

Flood is the second major hazard in Ethiopia, next to drought. The reason behind this is the topography of highland mountains and lowland plains with natural drainage networks created by primary river lines. The study area, Awash River Basin nowadays, encounters several environmental challenges such as land degradation, high growth of population density, deterioration of natural water, wetland destruction, desertification, and salinity. Flooding is also the huge problem that can magnify how severe environmental degradation is in the Awash River Basin. Flood hazard mapping is a critical component of flood-prone land use planning and mitigation strategies. Various studies show that GIS-based flood hazard mapping is significant to hinder severe flood hazards. This paper was an attempt to produce a GIS-based flood hazard area map and discuss major causes and impacts of flooding in the Awash River basin. The main parameters used to produce maps were elevation, slope, drainage density, average annual rainfall, proximity to rivers, land use, land cover change, and soil types. Hence, the rasterized and reclassified potential flood-generating factors were weighted, and a pair-wise comparison had been made. As a result, the vast majority of the basin, or 5,855,130.12 ha (51.4%), is susceptible to high flood hazards, while 4,625,378.51 ha (40.6%) and 866,358.09 ha (7.6%) of the area covered are prone to moderate and low flood hazards, respectively. When compared to other factors, the drainage density, elevation, and slope level have a greater impact on the vulnerability to flood hazards. The outcomes of this research contribute to effective flood risk management and environmental planning strategies in the Awash River basin.
On the behavior of the hybrid system of flat steel shear walls and cold- formed S-shaped steel plate dampers under cyclic lateral loading
Authors: Rakan-Nasrabadi Tohid , Pourmahdi-Tazeabadi Saeed , karimi-gabalou Sayyad , haghollahi Abbas
Published: September 2024

This study investigates the performance of a steel shear wall system equipped with S-shaped dampers under cyclic loading. Initially, a previously tested flat steel shear wall was verified as a control model with the FEM method. Then, this control wall was equipped with S-shaped dampers in various configurations. The results showed that adding dampers reduced the plastic strain on boundary members, especially the columns. However, the maximum lateral strength of the walls with dampers was 14.3–44.5% less than the control wall, depending on the damper arrangement. The placement of the dampers also altered the formation and angle of the diagonal tensile fields in the infill plate. Additionally, the thickness of the dampers played a crucial role; thicker dampers increased the lateral load capacity and initial stiffness and reduced the "pinching" effect in the hysteresis curve. The study found that the viscous damping of walls with dampers ranged from 34.91–39.76%, compared to 33.11% for the control wall. Overall, the addition of dampers increased the equivalent viscous damping by an average of 13.9%.
REDInet: a TCN-based classifier for A-to-I RNA editing detection harnessing million known events
Authors: Fonzino Adriano , Mazzacuva Pietro Luca , Handen Adam , Silvestris Domenico Alessandro , Arnold Annette , Pecori Riccardo , Pesole Graziano , Picardi Ernesto
Published: September 2024

A-to-I RNA editing detection is still a challenging task. Current bioinformatics tools rely on empirical filters and WGS/WES data to remove background noise, sequencing errors, and artifacts. Sometimes they make use of cumbersome and time-consuming computational procedures. We present here REDInet, a TCN-based Deep Learning algorithm, to profile RNA editing in human RNAseq data. It has been trained on REDIportal RNA editing sites, the largest collection of human A-to-I changes from > 8000 GTEx RNAseq data. REDInet can classify editing events with high accuracy harnessing RNAseq nucleotide frequencies of windows of 101 bases without the need for coupled genomic data.
Effects of Letrozole and Crocin Combination on Sperm Motility and Biochemical Markers in Azoospermia: Insights from Gene Expression Analysis
Authors: Zaeem Shahrzad Nokhbeh , Nasrabadi Mitra Heydari , Salehipour Masoud , Ehtsham Somayeh
Published: September 2024

Azoospermia, characterized by the absence of sperm in ejaculation, is a severe male infertility condition resulting from defects in spermatogenesis or the testicular duct system. DNA-alkylating agents, often from chemical drugs, contribute to infertility, while antioxidants play a crucial role in addressing fertility issues in couples facing subfertility. Traditional medicinal plants, particularly saffron, have been recognized for their fertility-enhancing effects. Crocins in saffron are noted for their potential to improve fertility indicators in rat models. This study aimed to investigate the effects of the combination of letrozole and crocin on sperm motility and biochemical markers in azoospermia, complemented by gene expression analysis. Thirty male Wistar rats were divided into five groups: control, azoospermia, azoospermia with letrozole, azoospermia with crocin, and azoospermia with both letrozole and crocin. Azoospermia was induced using a 10 mg intraperitoneal injection of busulfan over ten days. Subsequent analyses included histopathological, molecular, and hormonal assessments, with data analyzed using Graph Prism software. The combination treatment with letrozole and crocin significantly improved sperm motility compared to the azoospermia group, while reducing motility compared to the control group. Additionally, there was an increase in total sperm count, Total Antioxidant Capacity (TAC), and testosterone levels, accompanied by a decrease in Total Oxidant Status (TOS) enzyme activity (P < 0.05). QRT-PCR analysis indicated decreased expression of the GDNF gene compared to the control (P < 0.001) but increased expression compared to the azoospermia group (P < 0.001). Likewise, 5-alpha-reductase gene expression showed a significant decrease (P < 0.05). Therefore, the synergistic administration of crocin and letrozole holds promise for mitigating DNA damage caused by busulfan, potentially reducing long-term damage to bone marrow and improving fertility outcomes.
An Optimal Hybrid Deep Learning-Aided Facial Emotion Detection and Classification Scheme to Identify Criminal Activities
Authors: B Prabha , Poonkodi M , Joseph Linda
Published: September 2024

In general, the most significant field of research presently is identification & recognition of facial expressions or emotions. Moreover, recognition & categorization of face emotion are vital in several areas of research like criminal activities investigation, innovative card application, security, surveillance system, and so on. Among these, criminal investigation plays a vibrant part. Since there exists several methods on facial emotion/expression recognition (FER) system, however there were some drawbacks like low prediction rate, lower recognition rate, high error rate and so on. For rectifying these existing issues, a new enhanced optimal DL based model is presented in this manuscript. In this work, input facial dataset is extracted and are preprocessed using Weighted fuzzy Histogram Equalization (WF-HE). From this, the features are extracted using Deep CNN followed by Enhanced glowworm swarm optimization (EGSO)-based feature selection model at which hyper-parameter tuning is carried by attaining fitness function values. This in turn enhances the performance of classifier. The categorization for FER system is carried using Hybrid Deep Variational LSTM (DVLSTM) and DenseNet model. The results are estimated in terms of various performance measures like precision, Area under Curve (AUC), accuracy, F-Measure, sensitivity, specificity and recall, PPV, and error rate. The analysis is made on three input datasets like JAFFE, Extended CK+, and FER2013 dataset. The comparison for attained outcome is made with traditional models to validate proposed system efficiency over other compared schemes.
Occurrence, partition behavior and environmental risk of PAHs in water and sediment of a typical Karst wetland, southwest China
Authors: Xin Li , Xing Xinli , Cheng Cheng , Liu Weijie , Yanmin Zou , Hu Tianpeng , Yuan Zhang , Qi Shihua
Published: September 2024

Huixian wetland is one of the largest karst wetlands in China, existing both karst and wetland characteristics, thereby playing a pivotal role in ecological buffering within the Guilin region. Due to the toxicity and ubiquity of PAHs in aquatic systems, understanding the distribution, flux, sources, and risk assessment is crucial for the sustainable development of the reserve. To explore the PAHs pollution of this area, water and surface sediment samples in wet season and dry season were collected from Huixian wetland. The results revealed that PAHs in the study area exhibited a low level of pollution in the wet season, and the concentration of PAHs in the dry period was significantly higher compared to the wet season in both water and sediment. Both diagnostic ratios and Positive Matrix Factorization (PMF) model indicated that biomass burning and traffic emissions are potentially the primary sources of PAHs. Fugacity analysis revealed that sediment serves as a sink for PAHs, particularly for the high molecular weight PAHs (HMW-PAHs). Furthermore, the sediments also act as secondary sources of PAHs, capable of releasing them back into the water. Species sensitivity distribution analysis indicated that Phe and Fla should be closely monitored, as the concentrations of most sites exceeded the value of the Hazardous Concentration for 5% of species (HC5). Overall, the ecological risks within the study area generally were low-moderate, with certain individual sites, such as SD1-1 and SD2-1, have high levels of contamination, thus closer attention and monitoring should be paid.
Polycomb protein Bmi1 promotes odontoblast differentiation by accelerating Wnt and BMP signaling pathways
Authors: Hosoya Akihiro , Takebe Hiroaki , Kishimoto Yuri , Noguchi Yukiko , Ninomiya Tadashi , Yukita Akira , Yoshiba Nagako , Washio Ayako , Iijima Masahiro , Morotomi Takahiko , Kitamura Chiaki , Nakamura Hiroaki
Published: September 2024

Bmi1 is a polycomb protein localized in stem cells and maintains their stemness ability. This protein is also reported to regulate the expression of various differentiation genes. In this study, to analyze the role of Bmi1 during dentinogenesis, we examined the immunohistochemical localization of Bmi1 during rat tooth development as well as after cavity preparation. Bmi1 localization was hardly detected in the dental mesenchyme at the bud and cap stages. After the bell stage, however, this protein became detectable in preodontoblasts and early odontoblasts just beginning dentin matrix secretion. As dentin formation progressed, Bmi1 immunoreactivity in the odontoblasts decreased in intensity. After cavity preparation, cells lining the dentin and some pulp cells under the cavity were immunopositive for Bmi1 at 4 days. Odontoblast-like cells forming reparative dentin were immunopositive for Bmi1 at 1 week, whereas their immunoreactivity was not detected after 8 weeks. We further analyzed the function of Bmi1 by using KN-3 cells, a dental mesenchymal cell line. Overexpression of Bmi1 in KN-3 cells promoted mineralized tissue formation. In contrast, siRNA knockdown of Bmi1 in KN-3 cells reduced alkaline phosphatase activity and the expression of odontoblast differentiation marker genes such as Runx2, Osterix, and Osteocalcin. Additionally, KN-3 cells transfected with siRNA against Bmi1 showed reduced nuclear transition of β-catenin and expression of phosphorylated-Smad1/5/8. Taken together, these findings suggest that Bmi1 was localized in the odontoblast-lineage cells in their early differentiation stages. Bmi1 might positively regulate their differentiation by accelerating Wnt and BMP signaling pathways.
Uncertainty quantification in real-time parameter updating for digital twins using Bayesian inverse mapping models
Authors: Kessels Bas M. , Fey Rob H.B. , de Wouw Nathan van
Published: September 2024

To reach its full predictive potential, a digital twin should accurately represent its physical copy in the real world during its entire service lifespan. To this extent, model parameter updating is employed using the inverse mapping parameter updating method. This method enables physically interpretable parameters to be updated for a wide range of (nonlinear) dynamical models. It does so by inferring, in real-time, parameter values based on features extracted from measured data. This is achieved by using a regression model (e.g., based on machine learning) that is trained in an offline phase on simulated data. To allow for the quantification of the uncertainty in the inferred updating parameters, this paper proposes to use probabilistic Bayesian neural networks. This type of neural network infers probability distributions for the updating parameter values instead of the point estimates obtained when employing traditional (deterministic) artificial neural networks. Consequently, the user gains insight in how certain the neural network is about the inferred parameter values and can adjust his/her decision-making based on this knowledge.Besides the features of measured responses, additionally, known so-called `input parameters' that characterize the performed experiments (e.g., specific settings on the physical setup) can be provided as input to the neural network. This allows for a broader applicability of the trained neural network.To validate the proposed methodology, it is applied, using both simulated and real measurements, to a real-world mechanical ventilation system.
Automatic Speech Recognition Predicts Contemporaneous Earthquake Fault Displacement
Authors: Johnson Christopher , Wang Kun , Johnson Paul
Published: September 2024

Significant progress has been made in probing the current state of an earthquake fault by applying machine learning to continuous seismic waveforms. The breakthroughs were originally obtained from laboratory shear experiments and numerical simulations of fault shear, then successfully extended to slow-slipping faults. Here we apply the Wav2Vec 2.0 self-supervised framework for automatic speech recognition to continuous seismic signals emanating from a sequence of moderate magnitude earthquakes during the 2018 caldera collapse at the Kilauea volcano on the island of Hawai'i. We pre-train the Wav2Vec 2.0 model using caldera seismic waveforms and augment the model architecture to predict contemporaneous surface displacement during the caldera collapse sequence, a proxy for fault displacement. We find the model displacement predictions to be excellent. The model is adapted for near-future prediction information and found hints of prediction capability, but the results are not robust. The results demonstrate that earthquake faults emit seismic signatures in a similar manner to laboratory and numerical simulation faults, and artificial intelligent models developed for encoding audio of speech may have important applications in studying active fault zones.
Frailty, Physical Function Impairment and Pulmonary Function in Aging Men with and without HIV from the Multicenter AIDS Cohort Study (MACS)
Authors: Abdo Mona , Kunisaki Ken M , Morris Alison , Stosor Valentina , Chang Dong , D’Souza Gypsyamber , Crothers Kristina , Abdel-Maksoud Madiha , DiGuiseppi Carolyn , Brown Todd T , MaWhinney Samantha , Erlandson Kristine M
Published: September 2024

Background
People aging with HIV (PAWH) experience greater impairment in physical and pulmonary function than individuals aging without HIV. We examined whether baseline physical function was associated with subsequent pulmonary impairments.
Methods
Associations of frailty and physical function (gait speed [m/sec], grip strength [kg]) with pulmonary function (< 80% predicted diffusing capacity for carbon monoxide [DLCO] and forced expiratory volume [FEV1]) 3 years later were modeled; age, HIV status, and smoking were assessed as effect modifiers.
Results
Among1,024 men, (54% PAWH, 10% frail, 51% pre-frail), mean (SD) age = 53 (12) years, cumulative smoking = 12 (19) pack-years, gait speed = 1.1 (0.2) m/sec, and grip strength = 36.6 (9.2) kg. Frailty, pre-frailty, and weak grip strength were associated with higher odds of subsequent impaired DLCO and FEV1. Slow gait speed was associated with higher odds of DLCO impairment but not FEV1. No statistically significant modifications were found.
Conclusion
Interventions to improve physical function may help preserve pulmonary function.
Multi-Modal Large Language Model Enables Protein Function Prediction
Authors: Xie Pengtao , Huo Mingjia , Guo Han , Cheng Xingyi , Singh Digvijay , Rahmani Hamidreza , Li Shen , Gerlof Philipp , Ideker Trey , Grotjahn Danielle , Villa Elizabeth , Song Le
Published: September 2024

Predicting the functions of proteins can greatly accelerate biological discovery and applications, where deep learning methods have recently shown great potential. However, these methods predominantly predict protein functions as discrete categories, which fails to capture the nuanced and complex nature of protein functions. Furthermore, existing methods require the development of separate models for each prediction task, a process that can be both resource-heavy and time-consuming. Here, we present ProteinChat, a versatile, multi-modal large language model that takes a protein's amino acid sequence as input and generates comprehensive narratives describing its function. ProteinChat is trained using over 1,500,000 (protein, prompt, answer) triplets curated from the Swiss-Prot dataset, covering diverse functions. This novel model can universally predict a wide range of protein functions, all within a single, unified framework. Furthermore, ProteinChat supports interactive dialogues with human users, allowing for iterative refinement of predictions and deeper exploration of protein functions. Our experimental results, evaluated through both human expert assessment and automated metrics, demonstrate that ProteinChat outperforms general-purpose LLMs like GPT-4, one of the flagship LLMs, by over ten-fold. In addition, ProteinChat exceeds or matches the performance of task-specific prediction models.
Optimization of Optical Systems for Background Oriented Schlieren
Authors: Zhou Tanbo , Gaskins Jonathan , Poggie Jonathan , Bane Sally
Published: September 2024

Background oriented schlieren (BOS) is a non-intrusive optical method for measuring density gradients in a fluid flow based on variations of the local refractive index. The type of BOS optical system used, i.e., entocentric vs. telecentric, and the system design determine the accuracy and quality of the measurement. This work aims to optimize both types of optical systems to minimize the error for measurements of high-speed compressible turbulent boundary layers. Claims of the advantages offered by telecentric optical systems over entocentric systems are investigated, as well as the out-of-focus effects for types of systems. Numerical ray tracing simulations are performed using density fields from large eddy simulations (LES) of a Mach 2 turbulent boundary layer to generate synthetic but realistic BOS images. The results show that telecentric systems have lower overall error and less sensitivity. The optimal standoff distance between the BOS background and the density gradient object is found to be 300% and 200% of the depth-of-field for entocentric and telecentric systems, respectively.
Perception of breastfeeding mothers’ perceptions of donating breast milk for nutritional
Authors: Kuenzang  , Vaswani Vina
Published: September 2024

Background: Rapid advancements in technology have improved the premature survival rate globally. However, the majority of neonatal deaths occur in third-world countries during the neonatal period due to infections and complications. Vulnerablepremature infants need to meet basic nutritional needs, such as breast milk.
Research aim: We aimed to explore mothers’ perceptions ofdonating breast milk fornutrition vis-à-vis research and nurses as a facilitator of donation.
Methods: A qualitative exploratory study was conducted in 2022 with breastfeeding mothers and nurses as facilitators atJigme Dorji Wangchuck National Referral Hospital, Bhutan.
Results:The findings concerningdonation for nutrition werefavorable and revealed the importance and benefits of donation, current practices related to breastfeeding and motives for sharing. Unfavorable conditions includedfear of pathogen transmission; unfavorable experiences with donating; cultural practices; family pressure; and undecided-no experience. The study identified the enablers and barriers perceived by breastfeeding mothers for donating breast milk for research purposes. The benefits that the research can offer for infant survival were enabler, while sociocultural and religious beliefs wereconsidered barriers to donation. The nurses who facilitated donation were involved in the current practice of breastfeeding, the importance of breastfeeding and its technique, and the consent process. Barriers to internal factors include difficulty communicating, beliefs, research hesitancy and disadvantages in research use. The external factor includes beliefs. Nurses toward research had advantages and essential qualities.
Conclusions: Breastfeeding mothers were aware of the importance of donation as a source of nutrition, and these research outcomes could also be beneficial to society. As facilitators, nurses who obtainverbal consent during the donation process and research could improvethe clinical field. Establishing ahuman milk bank is necessary.
Genetic engineering in oncology based on CRISPR-Cas9 technology
Authors: Polatova D. Sh. , Madaminov A. Yu. , Savkin A. V. , Ibragimova D. A.
Published: September 2024

Purpose of the study: analysis of modern scientific data on the molecular mechanisms of the CRISPR-Cas9 system in gene editing, advantages and disadvantages in cancer research and the development of new treatment methods. Material and Methods. A comprehensive electronic search of relevant published studies was conducted in the scientific databases PubMed/MEDLINE, ScienceDirect, Wiley and Google Scholar published between 2014 and 2024. The search was tailored to the specific requirements of each database based on the following keywords: CRISPR-Cas9, sgRNA, genome editing, cancer immunotherapy, CAR-T. The search yielded 487 studies on the topic of interest, of which 54 were used to write the literature review. Additionally, the article discretely highlights the importance and challenges of CRISPR-Cas9 in the production of genetically engineered T cells for potential use in treating certain types of cancer. Results. Accordingly, CAR-T (chimeric antigen receptor T-cell) therapy is widely used as one of the main components of immunotherapy in the treatment of leukemia, lymphoma and some solid tumors. The development of programmed single guide RNAs (sgRNAs) and new modifications of the Cas9 protein has made the technology flexible and universal. CRISPR-Cas9 is often used to modify T and NK cells by designing antigen receptors to improve their sensory circuits with complex functionality capable of recognizing and killing tumor cells. At the same time, delivery of the finished ribonucleoprotein (Cas9+sgRNA) complex into the cell avoids the constitutive processes of transcription and translation, which ensures the fastest possible gene editing. Conclusion. In this review, we reviewed the scientific evidence highlighting the promising impact of CRISPR technologies in cancer research and treatment. CRISPR-Cas9 is considered a unique and effective technology in the field of genetic and biomolecular engineering.
Pathological complete response of locally advanced triple-negative breast cancer: case report
Authors: Konstantinova V. V. , Dashyan G. A. , Ahmedov R. M. , Belousov A. M.
Published: September 2024

Background. Triple-negative breast cancer is the most aggressive molecular subtype among breast malignancies. Due to the high proliferative activity of tumor cells and the lack of targets for targeted therapy, neoadjuvant chemotherapy plays the main role in complex treatment of this subtype. The optimal time to start neoadjuvant chemotherapy is defined as less than 8 weeks. Delays in time to treatment initiation may adversely affect treatment outcomes, as well as cause local or systemic disease progression. Achieving complete pathological response after neoadjuvant chemotherapy reduces the relative risk of relapse by more than 70 %, which, in turn, leads to a significant improvement in long-term survival of these patients. Description of the clinical case. A 32-year-old woman came to the clinic 15 months after being diagnosed with triple-negative breast cancer. The patient was treated with alternative medicine methods for 15 months, and upon admission to the hospital, the patient had pronounced local tumor growth with massive decay, tumor lysis syndrome and nutritional disorders. We decided to perform neoadjuvant chemotherapy: 12 cycles of weekly paclitaxel + carboplatin, followed by 4 cycles of dose-dense doxorubicin + cyclophosphamide. Chemotherapy resulted in a significant reduction in tumor size and improvement of health status of the patient. There were no clinically significant side effects requiring hospitalization or dose reduction. Upon completion of neoadjuvant treatment, the patient underwent mastectomy. The histological examination revealed a complete pathological response of the primary tumor and regional lymph nodes. The patient underwent adjuvant external beam radiation therapy. The patient is alive 3 years after diagnosis and 1.5 years after treatment completion. She plans delayed breast reconstruction with contralateral breast augmentation. Conclusion. This is a rare case of locally advanced triple-negative breast cancer with pathological complete response to neoadjuvant chemotherapy 15 months after diagnosis.
Experimental study of radioprotective properties of lithium pyruvate in vitro
Authors: Plotnikov E. V. , Belousov M. V. , Brazovsky K. S. , Larkina M. S. , Artamonov A. A. , Stuchebrov S. G. , Chernov V. I.
Published: September 2024

Radiotoxicity is a serious problem for patients undergoing radiotherapy, so the search for new radioprotective drugs to mitigate its effects is highly relevant. Radioprotectors should have a number of properties, including direct antioxidant action, reduction of oxidative stress, ability to induce DNA repair or inhibit apoptosis, and at the same time not cause their own side effects. Antioxidants based on lithium salts look promising in terms of their properties. The aim of study was to study the radioprotective properties of lithium pyruvate in vitro. Material and Methods. Relatively radiosensitive blood mononuclear cells and relatively radioresistant fibroblasts of 3T3L1 line were used as biomodels for x-ray exposure. Cells were incubated and irradiated in 96-well plates. Lithium pyruvate was used at a final concentration of 1.2 mM. Cells were irradiated at a dose rate of 15 mGy/s in the absorbed-dose range from 0 to 5 Gy using an x-ray unit (anode voltage: 160 kV, average current: 3.5 mA). Cell viability was assessed by MTT test and resazurin test. The evaluation of cell death variants and the level of oxidative stress were determined by cytofluorimetric method. Results. The cytoprotective effect of lithium pyruvate was established. Cytoprotection was manifested in the increased cell survival and decreased oxidative stress level under lithium pyruvate after x-ray in a wide range of absorbed doses. Relatively high efficiency was shown in relation to blood mononuclear cells with an increase in the viable fraction by 5–7 % and a decrease in oxidative stress level during irradiation in the range of 1.0–3.0 Gy. Apoptosis was found to be the main mechanism of cell death after irradiation. Lithium pyruvate reduced the level of apoptosis in cell population under irradiation and chemically induced oxidative stress. Conclusion. Radioprotective effect of lithium pyruvate under x-ray irradiation in vitro has been shown. Reduction of oxidative stress under the action of pyruvate provides a pathogenetic basis for the potential use of this compound as a radioprotector, which requires further studies on in vivo models.
Integrin profle of circulating tumour cells in breast cancer patients
Authors: Grigoryeva E. S. , Tashireva L. A. , Alifanov V. V. , Zavyalova M. V. , Perelmuter V. M.
Published: September 2024

Background. Integrins, as adhesion molecules, play a key role in the interaction of cells with the basal membrane and intercellular matrix. Numerous studies demonstrate evidence of increased expression of integrins on tumor cells in different types of cancer. Thus, β3 and αV integrins are associated with stem-like features of tumor cells, and β4 integrin as α6β4 heterodimer provides anchorage-independent survival of malignant mammary epithelial cells. However, all the described functions of integrins have been investigated exclusively on primary tumor cells. The functional significance and expression pattern of integrins on circulating tumor cells (CTCs) remains unclear. The aim of the study was to evaluate the β3, β4 and αvβ5 integrin expression on CTCs and its association with molecular subtype, stage and lymph node metastasis in breast cancer patients Material and Methods. The study included 22 patients with T1–4N0–3M0 invasive ductal breast carcinoma. Venous blood was taken from patients without neoadjuvant chemotherapy (group 1) and after neoadjuvant chemotherapy (group 2) in the volume of 12 ml into vacuum tubes with EDTA. The expression of CTC integrins including stemness features CD44/CD24, CD133 and ALDH1, and epithelial-mesenchymal transition (EMT) (N-cadherin) was evaluated by flow cytometry. Results. CTCs with β3+β4-αvβ5- and β3-β4+αvβ5+ phenotypes and stemness properties were associated with larger tumor size (T4) in breast cancer patients. The β3 integrin expression was associated with more aggressive molecular subtypes of breast cancer. Administration of neoadjuvant chemotherapy did not affect the expression pattern of β3, β4 and αvβ5 integrins in CTCs. Conclusion. In breast cancer, most CTCs expressed β3, β4 and αvβ5 integrins despite the lack of attachment to the basal membrane and intercellular matrix. The expression of the above integrins on CTCs was associated with breast cancer molecular subtype, stage and lymph node metastasis, and therefore its evaluation can be considered as one of the objectives of liquid biopsy study.
An introduction to infinite projected entangled-pair state methods for variational ground state simulations using automatic differentiation
Authors: Naumann Jan , Weerda Erik Lennart , Rizzi Matteo , Eisert Jens , Schmoll Philipp
Published: September 2024

Tensor networks capture large classes of ground states of phases of quantum matter faithfully and efficiently. Their manipulation and contraction has remained a challenge over the years, however. For most of the history, ground state simulations of two-dimensional quantum lattice systems using (infinite) projected entangled pair states have relied on what is called a time-evolving block decimation. In recent years, multiple proposals for the variational optimization of the quantum state have been put forward, overcoming accuracy and convergence problems of previously known methods. The incorporation of automatic differentiation in tensor networks algorithms has ultimately enabled a new, flexible way for variational simulation of ground states and excited states. In this work we review the state-of-the-art of the variational iPEPS framework, providing a detailed introduction to automatic differentiation, a description of a general foundation into which various two-dimensional lattices can be conveniently incorporated, and demonstrative benchmarking results.
EFFECTIVENESS OF PASSIVE STRETCHING IN TREATING JUVENILE IDIOPATHIC RHEUMATOID ARTHRITIS- A CASE STUDY
Authors: Nissee Neelima Raj Y.
Published: September 2024

Background:Rheumatoid Arthritis (RA) a systemic autoimmune disease characterized by inflammatory arthritis and extra-articular involvement. It is a chronic inflammatory disease that mostly affects the synovial joints.A diverse subset of idiopathic inflammatory arthritis that affects children under 16 and lasts for six weeks or more is known as juvenile idiopathic arthritis (JIA). Methodology:A 15-year-old female had juvenile idiopathic arthritis with medical treatment, there was no reduction of pain and led to difficulties in her ADL with restricted joint mobility and reduced ROM. Whereas she was evaluated and treated with specific physiotherapeutic measures for eight months period seven days in a week with specific stretching exercises. Result:The significant difference were reported from the pre and post test values of pain and also functional improvement with regards to kartz index Conclusion: Passive stretching, when implemented as part of a comprehensive physiotherapeutic approach, can effectively alleviate the symptoms and improve the quality of life.
Enhancing SME performance in East Java through competency development, leadership, entrepreneurial intent, and resilience
Authors: Fiernaningsih Nilawati , Widayani Anna , Herijanto Pudji , Himmah Mahmudatul , Utamaningsih Arni
Published: September 2024

Small and medium enterprises (SMEs) are crucial in economic growth and industrial diversification. Despite their importance, SMEs encounter challenges of intense competition, global market penetration, and rapid technological advancements. This study explores the factors affecting SME performance, focusing on entrepreneurial competence, leadership, and intention. A survey was conducted involving 400 SME respondents in East Java, Indonesia. The data were analyzed using a quantitative approach and the PLS-SEM method. The findings indicate that entrepreneurial competence and intention significantly influence entrepreneurial resilience and SME performance. Specifically, entrepreneurial competence has a path coefficient of 0.348 on entrepreneurial resilience and 0.567 on SME performance, both significant with p-value < 0.05. Entrepreneurial intention has a path coefficient of 0.649 on entrepreneurial resilience and –0.722 on SME performance, both significant with p-value < 0.05. These results highlight the necessity of enhancing entrepreneurial competencies and intentions to boost SMEs’ resilience and performance. Entrepreneurs and policymakers should focus on training and development programs to reinforce these competencies and intentions, thereby promoting an environment that supports innovation and prudent risk-taking.
Lean management methods: Evidence from the manufacturing industry in the Czech Republic
Authors: Heinzova Romana , Hoke Eva , Janova Nikola
Published: September 2024

Lean management is a way to satisfy the increasing customer demands while maintaining production efficiency. This paper aims to map and analyze the level of use of lean management methods in the manufacturing industry in the Czech Republic. It searched for links and dependencies between company size, production type, and lean management methods in operational processes. The data were obtained from a nationwide survey within the manufacturing industry companies and were presented using descriptive statistics. A structured questionnaire was sent to 469 manufacturing companies with a return rate of 18.8%. Nonparametric statistical analysis (Fisher’s exact test) was used to confirm or reject the hypotheses. The research results confirmed the dependence of lean management methods on company size and production type. Lean management methods are used mainly by large enterprises, while micro- and small enterprises rarely employ them. Considering production typology, lean management is applied in serial production, and Single Minute Exchange of Dies (SMED) prevails. The most used techniques in mass production include the method of order in the workplace (5S) and Kaizen. The findings suggest that the future of industrial output should focus on sustainability and rationalization of production resources, which is offered by the synergy of lean management and Industry 5.0.
AcknowledgmentThis paper is co-financed by IGA/FLKR/2023/002 Rationalization and Sustainability of Resources in Production-Logistics Processes the Czech Republic and RVO/FLKŘ/2024/01 Logistic Systems Safety.
Al-Ghazali's Eco-Sufism for Environmental Preservation: Living Sufism at Pesantren Al-Anwar 3 of Central Java
Authors: Khikamuddin M , Ainiyah Mahfudhoh , Anwar Moh. Kamil
Published: September 2024

Natural destruction is a severe problem faced by human beings up to the present. Many factors are identified, including less awareness of its preservation, no matter how much research is exposed. This study investigates how Al-Ghazali’s ecosufism theory is implemented at Pesantren Al-Anwar 3 of Central Java. This study employs a qualitative method with field research, which involves an anthropological approach to observe and analyze the implementation of al-Ghazali’s ecosufism concept regarding environmental ethics and waste management at Pesantren Al-Anwar 3 in Central Java. The research findings reveal al-Ghazali’s concept in dealing with environmental issues, including shukr (thankfulness), zuhd (asceticism), ‘uzla (seclusion) and maḥabba (love). They are practiced by Pesantren Al-Anwar 3 by creating innovative waste management systems, such as burning without emitting smoke, optimizing organic waste as worm feed, and utilizing the remaining combustion as material for paving. This shows how Al-Ghazali’s ecosufism theory is implemented in waste management and can effectively reduce the impact of natural damage.Contribution: This research contributes to overcoming natural damage by applying al-Ghazali’s ecosufism theory and combining it with ecological principles. It can be one of the effective ways to offer a sustainable ecological management model that can be widely adopted to overcome environmental problems that modern humans face today.