bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hydrogen gas inhibits neuroinflammation after traumatic brain injury by promoting microglia M2 polarization via AMPK-dependent mediation of HDAC5
Authors: Zhai Jiayuan , Zhang Xin , Li Tingting , Tang Tianwei , Liu Xiangnan , Yang Yi , Yang WanChao 
Published: January 2024

Abstract
Microglia-associated neuroinflammation plays a role in secondary brain injury after traumatic brain injury (TBI). Hydrogen gas (H2) promotes microglial M2 polarization and alleviates neuroinflammation across brain disorders. However, little is known about the mechanism and target of H2 in treating neuroinflammation of TBI. In the present study, H2 inhalation conferred an improved neurological outcome after TBI by significantly decreasing neuroinflammation and activating microglial M2 polarization via inhibition of histone deacetylase 5 (HDAC5) expression. Furthermore, an AMPK inhibitor activated expression of HDAC5 and downstream GSK3β/AKT signaling; H2 treatment reversed these effects and rescued neurological function in vitro and in vivo. Mechanistically, H2 down-regulated GSK3β histone H3 acetylation levels through AMPK activation. Altogether, these data indicate that H2 inhalation inhibits neuroinflammation and rescues neurological function after TBI by promoting M2 polarization of microglia through GSK3β/AKT signaling and AMPK-dependent mediation of HDAC5. Our findings reveal novel targets for inhibiting neuroinflammation, and highlights the potential of H2 therapy for TBI.
Functional Dimensionality of Koopman Eigenfunction Space
Authors: Cohen Ido , Appleboim Eli , Wolansky Gershon 
Published: January 2024

Abstract
This work presents the general form solution of Koopman Partial Differential Equation and shows that its functional dimensionality is finite. The dimensionality is as the dimensionality of the dynamics. Thus, the representation of nonlinear dynamics as a linear one with a finite set of Koopman eigenfunctions without error is possible. This formulation justifies the flowbox statement and provides a simple numerical method to find such representation.
Exploring the biomedical potential and DNA interaction of some new mixed complexes incorporating 2-guanidinobenzimidazole and imidazole ligands supporting by DFT and molecular docking approaches
Authors: Abu-Dief Ahmed M. , El‐Dabea Tarek , El-Khatib Rafat M. , Abdou Aly , Aljohani Faizah S. , Alzahrani Seraj , Barnawi Ibrahim Omar , El-Remaily Mahmoud Abd El Aleem Ali Ali 
Published: January 2024

Abstract
Pd(II), VO(II), Cu(II), and Ag(I) interacted with Guanidinobenzimidazole (BIG) to form four mixed ligand metal chelates in the presence of Imidazole (I). The synthesized compounds were investigated employing CHN, mass spectra, FT-IR, NMR spectra, magnetic moment, electronic spectra, TGA, and molar conductance. The Ft-IR displayed that BIG interacts with selected metals as a bi-dentate ligand by NH and = N atoms, whereas imidazole coordinated through N2 atom. Relating to the values of conductance the studied Cu(II) and Ag(I) complexes are non-electrolytes. For Cu(II) and VO(II) mixed complexes the octahedral geometry and the Pd(II) & Ag(I) complexes were found to have a distorted square planar and tetrahedral geometry. Respectively, were verified by occupying the magnetic moments, theoretical studies and electronic spectra. The decomposition pathways for used ligands and their prepared complexes through TGA were estimated and thermodynamic factors (ΔH*, A, Ea, ΔG* and ΔS*) were calculated employing (Horowitz-Metzger & Coats-Redfern). To identify the ideal molecular geometry of the tested compounds, DFT simulations were completed. To supplement the proposed structures, we estimated the (HOMO & LUMO) molecular orbitals as well as the MEP. The prepared compounds were screened for their in vitro antimicrobial and antitumor efficacy against numerous pathogens through the disc diffusion technique and MTT assays, respectively. The DPPH technique was applied to estimate the antioxidant efficacy in vitro. The data display that the prepared complexes are extremely active than free ligands. Moreover, CT-DNA binding performance of tested chelates with CT-DNA was tested using electronic spectroscopy, viscosity study and Agarose-gel electrophoresis. MOE-docking was applied to estimate the interactions among the studied complexes and the possible binding sites of (PDB ID = 5IJT; 3t88; 3gcw; 3cku) receptors. Finally, the Pd(II) mixed complex displays the higher biological performance according to both (in vitro and computational analysis).
Changes in the Lifestyle of Older Adults in Khoy during the COVID-19 Era
Authors: Sherzavani Azizeh , Jahangiry Leila , Akbari Hossein , Mohammadpoorasl Asghar 
Published: January 2024

Abstract

Background
The susceptibility of older adults to the detrimental effects of the coronavirus disease 2019 (COVID-19) has accentuated the need for comprehensive understanding and targeted interventions. While quarantine measures serve as a protective strategy against the spread of the disease, they concurrently instigate significant alterations in lifestyle among this demographic. This study aims to scrutinize the nuanced changes in the lifestyle of older adults during the COVID-19 pandemic, providing valuable insights for the development of intervention programs geared towards enhancing the quality of life for this vulnerable group.
Methods
This cross-sectional study was conducted in January 2022 involving 337 older adults living in Khoy, West Azerbaijan, Iran. The recruitment of participants was carried out at public healthcare centers, employing a meticulous multi-stage sampling approach to ensure representative inclusion. The data collection process relied upon the utilization of the EHLC-COVID-19 questionnaire, a tool specifically developed by the University of Rome Tor Vergata. This questionnaire was designed to comprehensively capture and assess various aspects of the participants' experiences, behaviors, and lifestyle changes during the COVID-19 pandemic, providing a robust foundation for a nuanced analysis of the study's objectives.
Results
The average age of older adults was 69.9 ± 7.04 (range: 60–90) years, and 54.6% were females. Over a third (35%) of participants stated that their eating habits worsened during theCOVID-19 era. About 15% reported an increase in smoking, 22% reported a decrease in exercise frequency, and 12% reported a decline in sleep. The most commonly consumed food items included vegetables (59.6%) and fruits (54.0%), while the least common ones were sugars/sweeteners (31.8%) and carbonated drinks (31.5%).
Conclusion
In light of the discernible decline in the lifestyle of older adults in Khoy amidst the COVID-19 era, marked by an inclination towards a sedentary lifestyle, a modest adherence to the Mediterranean diet, and a surge in smoking habits, it becomes imperative to institute intervention programs aimed at enhancing the overall quality of life for this demographic. Proactive measures, encompassing health education, lifestyle modification initiatives, and support systems, can play a pivotal role in mitigating the adverse effects observed.
Changes in income inequality and its determinants in Pakistan: A disaggregated analysis
Authors: Mumtaz Jazib , Hussain Syed Irshad 
Published: January 2024

Abstract

Investigating the determinants of inequality is crucial for understanding the root causes of unequal distribution of resources and opportunities in society. It can help identify the factors that contribute to inequality, such as world or market forces, social norms, ownership of real and human capital, and the role of government. By understanding these factors, we can develop policies and interventions that address the root causes of inequality and promote greater equality and social justice. With respect to Pakistan, the available literature has estimated the effects of household’s characteristics and other determinants on income inequality at aggregate level in a single period of time. However, the policymakers and economists suggested that household characteristics must be analyzed at disaggregated level incorporating time variations to develop a more impactful policy framework. Without it, we will continue to have limited understanding of the peculiarities of family behavior and how they react to different policy initiatives. In this context, the current study assesses the determinants of income inequality over various years and change in income inequality over various years for urban and rural areas of Pakistan. The data has been taken from HIES 2001-02, 2007-08, 2013-14 and 2018-19 respectively. Fields decomposition analysis has been used to measure the changes in income inequality over the years in Pakistan for urban and rural areas. The results from the study revealed that gender, education, assets holding, occupation, and paid employment have a positive contribution to increasing income inequality. Whereas, social safety nets, access to utilities, and access to affordable housing have a negative contribution to income inequality. The results indicated clearly that policies have failed to provide social justice to the households due to a lack of opportunities and unequal distribution of income. Therefore, the fruits of high-income growth have been nullified due to the prevalence of income inequality among households.
Enhancing Satellite Images of FACSAT-1 through Generative Adversarial Networks for Super-Resolution
Authors: Zarate Paola , Arroyo Christian , López Jesús , Jiménez Jorge 
Published: January 2024

Abstract
Satellite images have diverse applications across scientific, commercial, and other domains. As a result, institutions are increasingly deploying Earth observation satellites to cater to their specific needs. This is the case of the Colombian Aerospace Force, which launched its nanosatellite, the FACSAT-1, to contribute to developing the space sector in Colombia. However, in some cases, captured images may need more quality and resolution for their intended purposes. Numerous image processing tools have been developed to enhance and optimize satellite imagery to address this challenge. Deep learning techniques, particularly Generative Adversarial Networks, have recently shown significant advancements in image processing. This paper investigates the widespread application of Generative Networks for satellite and aerial imagery, specifically focusing on super-resolution tasks. Super-resolution involves increasing the resolution of satellite images by up to four times their original size. The study presents the implementation and training of four different generative models and evaluates their performance using qualitative and quantitative measures. Two metrics, namely the maximum signal-to-noise ratio and the structural similarity index, are employed for comparative analysis. By assessing the output of each generative model, this research aims to determine their efficacy in enhancing satellite imagery resolution.
Research on the Analysis Method of Mental Fatigue in Medical Personnel Based on EEG Signals
Authors: Chen First Zelong , Zhang Second Zhenchang , Zhang zhanghuaiyong , Lin Third Shaowei , Li Third Xueding , Liu Third Haiyun 
Published: January 2024

Abstract
Study the correlation between the multi-scale entropy values of electroencephalo-gram (EEG) signals in medical personnel and the degree of mental fatigue, and analyze the detection of mental fatigue status in healthcare workers. Utilizing singular value analysis to eliminate noise in EEG signal data, calculating multi-scale entropy values of the original EEG signals, referencing the FS-4 fatigue scale, and analyzing entropy value stability; proposing three fatigue analysis algorithms?random forest, BP neural network, and XGBoost comparing them with traditional machine learning methods and artificial neural network methods , investigating the relationship between multi-scale entropy values of EEG 1 signals and fatigue in healthcare personnel, and analyzing the determination of mental fatigue status. This paper employs the multi-scale entropy method to extract multi-scale information from original EEG signals. The combination of multi-scale information with three fatigue analysis algorithms enables the detection and analysis of mental fatigue status in healthcare personnel. Experimental results indicate that the XGBoost algorithm exhibits the highest sensitivity at 75%, while the random forest algorithm demonstrates the best specificity at 80% and an AUC value of 95%. The random forest algorithm demonstrates superior performance in studying mental fatigue.
A Fused Multi-subfrequency Bands and CBAM SSVEP-BCI Classification Method Based on Convolutional Neural Network
Authors: Lei Dongyang , Dong Chaoyi , Guo Hongfei , Ma Pengfei , Liu Huanzi , Bao Naqin , Kang Hongzhuo , Chen Xiaoyan , Wu Yi 
Published: January 2024

Abstract
For the brain-computer interface (BCI) system based on steady-state visual evoked potential (SSVEP), it is difficult to obtain satisfactory classification performance for short-time window SSVEP signals by traditional methods. In this paper, a fused multi-subfrequency bands and convolutional block attention module (CBAM) classification method based on convolutional neural network (CBAM-CNN) is proposed for discerning SSVEP-BCI tasks. This method extracts multi-subfrequency bands SSVEP signals as the initial input of the network model, and then carries out feature fusion on all feature inputs. In addition, CBAM is embedded in both parts of the initial input and feature fusion for adaptive feature refinement. To verify the effectiveness of the proposed method, this study uses the datasets of Inner Mongolia University of Technology (IMUT) and Tsinghua University (THU) to evaluate the performance of the proposed method. The experimental results show that the highest accuracy of CBAM-CNN reaches 98.13%. Within 0.1s-2s time window, the accuracy of CBAM-CNN is 2.01%-16.17%, 2.54%-25.38%, 4.74%-48.85%, 5.40%-49.94%, and 12.76%-53.88% higher than that of CNN, CCA-CWT-SVM, CCA-SVM, CCA-GNB, and CCA, respectively. Especially in the short-time window range of 0.1s-1s, the performance advantage of CBAM-CNN is more significant. The maximum information transmission rate (ITR) of CBAM-CNN is 503.87bit/min, which is 227.53bit/min-503.41bit/min higher than the above five EEG decoding methods. Moreover, CBAM-CNN is 0.39% -16.17% higher than the typical CNN in terms of accuracy, recall, precision, and macro-F1 performance metrics. The study further results show that CBAM-CNN has potential application value in SSVEP decoding.
A priori estimates for solutions of g-Laplace type problems
Authors: Ceresa-Dussel Ignacio , Bonder Julian Fernandez , Silva Analia 
Published: January 2024

Abstract
In this work we study a priori bounds for weak solution to elliptic problems with nonstandard growth that involves the so-called $g-$Laplace operator. The $g-$Laplacian is a generalization of the $p-$Laplace operator that takes into account different behaviors than pure powers. The method to obtain this a priori estimates is the so called ''blow-up'' argument developed by Gidas and Spruck. Then we applied this a priori bounds to show some existence results for these problems.
2000 Mathematics Subject Classification. 35J20; 35J60.
Placental-derived mesenchymal stem cells improve ovarian folliculogenesis, imbalanced hormone levels, and metabolic parameters in an animal model of polycystic ovarian syndrome
Authors: Sarvestani Mojtaba , Rajabzadeh Alireza , Mazoochi Tahereh , Samimi Mansooreh , Navar Mohsen , Moradi Faezeh 
Published: January 2024

Abstract

Introduction
Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disturbance that affects many women worldwide and is characterized by chronic anovulation, hyperandrogenism, and ovarian dysfunction. insulin resistance, dyslipidemia, and liver dysfunction are perturbations induced by PCOS. Mesenchymal stem cells (MSCs) have recently emerged as a potential therapy for metabolic disorders such as PCOS due to their anti-inflammatory, antiapoptotic, proangiogenic, and proliferative properties. Placenta-derived mesenchymal stem cells (PDMSCs) are derived from the placenta and have advantages over other sources of MSCs in terms of availability, safety, and immunomodulation.
Materials and Methods
In this experimental study, we assigned twenty female Wistar rats into four groups (n = 5): control, sham, PCOS, and PCOS-PDMSCs. We induced PCOS in the rats by administering letrozole for 21 days. PDMSCs (1 × 106 cells) were injected through the tail vein. Fourteen days after cell infusion, we evaluated the number of healthy follicles, corpus luteum, and cystic follicles, as well as the levels of testosterone, follicle-stimulating hormone (FSH), luteinizing hormone (LH), fasting blood glucose, fasting insulin, and insulin resistance. Moreover, we measured the serum levels of cholesterol, triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). Liver function was determined by evaluating aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels.
Results
The number of corpora luteum, primordial, primary, secondary, and antral follicles significantly elevated in the PCOS-PDMSCs group versus the PCOS group. The number of cystic follicles significantly decreased in the PCOS-PDMSCs group. LH and testosterone levels decreased significantly, while FSH levels increased significantly in the PCOS-PDMSCs group. Fasting blood glucose levels, fasting insulin levels, and insulin resistance notably decreased in the PCOS-PDMSCs group. The lipid profile improved in the PCOS-PDMSCs group with significant cholesterol, LDL, and TG decreases and an increase in HDL. The PCOS-PDMSCs group exhibited marked decreases in the AST and ALT levels.
Conclusion
Our results suggest that PDMSCs are a potential treatment option for PCOS because they can effectively restore folliculogenesis, correct hormonal imbalances, modify metabolic/lipid profiles, and alleviate liver dysfunction in a rat model of PCOS. However, further research is needed to establish the safety and effectiveness of PDMSCs for treating PCOS.
A study of the comparison of some laser beams spreading through human and mouse biological tissues
Authors: Nossir N. , Dalil-Essakali L. , Belafhal A. 
Published: January 2024

Abstract
Aiming at the Bessel higher-order cosh-Gaussian (BHoChG) beam and the Bessel higher-order sinh-Gaussian (BHoShG) beam, we investigate their propagation properties through turbulent biological tissues. In this respect, the analytical expression of the considered beams is obtained and developed, based on the extended Huygens-Fresnel integral. By numerical simulation, the intensity distributions of these beams for biological tissue types including intestinal epithelium and deep dermis of mouse in addition the human upper dermis versus the propagation distance as a function of the variations of the laser beam parameters. The obtained results indicate that the resistance of our beams against turbulent biological tissues increases as the source parameter increases counting the decentered parameter, the beam-order of the considered beams and the beam waist width. The findings show that the intensity distribution of the propagation of these beams occurs more quickly when they pass through the deep dermis of the mouse. The results presented in this paper are significant due to their potential application in determining the deterioration or disruption of biological tissue, medical imaging and medical diagnosis.
Enhancement of Thermal Efficiency on a Upstream Wedge Ribs Microchannel using Lattice Boltzmann Approach
Authors: Biswas Runu , Sohel Md. Nurunnabi , Akhi Fatema Amin , Rahman Md. Mahabubur , Khanom Afruza , Taher Mohammad Abu 
Published: January 2024

Abstract
Numerical analysis of flow friction and thermal performances in upstream wedge ribs microchannel at the slip flow condition has been intended in the current study employing a Thermal Lattice Boltzmann Method (TLBM). A D2Q9 single relaxation time TLBM is used to investigate and discuss the thermal-fluid flow behavior namely the streamlines in terms of velocity vectors, isotherms in terms of temperature profiles, pressure gradient as well as friction coefficient for different Knudsen numbers (Kn) ranging from 0.01~0.10 with ribs height 20% of channel height. Finally, the overall performance enhancement ratio is calculated for wedge ribs microchannel to compare with smooth one. The results have been compared with previously published works and are found a very good agreement and thus the model has been used to predict the heat transfer and friction factor in wedge ribs microchannel. In this study, it is illustrated that the vortices are strongly influenced and the strength of vortices are decreased as the Kn increases and hence the pressure gradient also responsible for changing the Knudsen number. The flow friction, the average rate of heat transfer as well mass flow linearly decreased with increasing Kn but compare to smooth channel, the friction is significantly increased and the heat transfer rate as well mass flow decreased for upstream wedge ribs microchannel. Finally, the performance enhancement (PE) namely the thermal efficiency are calculated and it is found that the PE decreased slightly with Kn for upstream wedge ribs microchannel. However, compare to smooth one, the lower PE identified in the present study.
Non-mass Lesions on Preoperative MRI in Breast Cancer: Clinical Implications and Prognostic Significance
Authors: Moon Joon Suk , Yoo Tae Kyung , Kim Jisun , Chung Il Yong , Ko Beom Seok , Kim Hee Jeong , Lee Jong Won , Son Byung Ho , Lee Sae Byul 
Published: January 2024

Abstract
Purpose
This study aims to investigate the clinical importance and prognostic value of non-mass lesions (NMLs) identified on preoperative magnetic resonance imaging (MRI) in patients with breast cancer, with an emphasis on understanding how these lesions affect treatment decisions and survival outcomes.
Methods
A retrospective analysis was conducted on 6,971 patients diagnosed with breast cancer who underwent surgery at Asan Medical Center, Seoul, between January 2000 and December 2021. Patients were categorized based on the presence or absence of NMLs on preoperative MRI. Various clinicopathological parameters were compared, and survival outcomes such as overall survival (OS), distant metastasis-free survival (DMFS), regional recurrence-free survival (RFS), and local recurrence-free survival (LFS) were analyzed using Kaplan–Meier and Cox regression methods. Subgroup analyses were performed based on the type of surgery and the administration of neoadjuvant chemotherapy and adjuvant radiation therapy.
Results
Of the total cohort, 21.9% (n = 1,524) had NMLs. The presence of NMLs was associated with a significant improvement in OS (P = 0.017) for the entire patient group. Multivariate analysis identified presence of NML as a favorable prognostic factor (hazard ratio: 0.47, 95% confidence intervals: 0.25–0.90, P = 0.022). Subgroup analyses demonstrated significantly improved OS, DMFS, and RFS outcomes for patients with NMLs who underwent mastectomy after neoadjuvant chemotherapy.
Conclusion
NMLs on preoperative MRI in patients with breast cancer are associated with improved overall survival and serve as an independent prognostic factor. The findings of this study require further research to elucidate the underlying reasons for these outcomes.