bluuebunny/crossref_metadata_2025 huggingface dataset:
Knowledge, attitude, and practice of e-cigarette use among undergraduate students: A comparative study between China and Indonesia
Authors: Hartono Ronald , Rui Deng , Ying Chen , Fang Yan Chao , Ting Ma Bo , Qi Deng Ya , Jia Sun Yi , Pan Li , Dao Yu Ye
Published: June 2024

Background
The health risks associated with e-cigarettes are currently the focus of tobacco control efforts and public health initiatives. Given that China and Indonesia have the highest rates of adult smoking worldwide, it is imperative to gain a comprehensive understanding of e-cigarette prevalence among college students in these two nations.
Methods
From May to June 2023, a random sampling method was employed to conduct an online questionnaire survey among college students in three universities located in Kunming (China) and Jakarta (Indonesia) respectively. The chi-square test was utilized for comparing the rates/ratios, while binary logistic regression analysis was applied to examine the influencing factors of e-cigarette knowledge, attitude, and practice.
Results
A total of 1327 individuals were included in the investigation. The proportion of Indonesian students (75.6%) with a high level of e-cigarette knowledge was lower than that observed among Chinese students (87.4%) (χ2 = 29.697, P < 0.001). Additionally, the prevalence of e-cigarette use among Indonesian students (9.4%) was higher compared to their Chinese counterparts (3.0%) (χ2 = 22.320, P < 0.001). Binary logistic regression analysis revealed that age, place of residence, major, gender, as well as friends' and family members' e-cigarette use significantly influenced knowledge levels and attitudes towards e-cigarettes in both countries (P < 0.05).
Conclusion
Despite the positive knowledge, attitudes, and practices towards e-cigarettes among undergraduate students in both countries, a notable knowledge gap exists concerning the harmful effects of e-cigarettes. In comparison, Chinese students exhibit a better comprehension of e-cigarette knowledge and demonstrate lower usage rates, suggesting that heightened awareness plays a favorable role in preventing e-cigarette use. Furthermore, it becomes imperative for policymakers and health educators to focus on specific factors such as the influence of close friends and family members, as well as the residency area.
Spousal age difference and risk of hypertension in women: evidence from India
Authors: Datta Biplab , Tiwari Ashwini , Jahan Murshed , Torres Natalia , Attari Sara
Published: June 2024

There has been steady progress in documenting the psychosocial risk factors of hypertension. However, most of the extant evidence is based on population from the developed countries. Using nationally representative data from India, this cross-sectional study explores whether spousal age gap is associated with risk of hypertension in married women aged 20 to 49 years. Based on the age difference with their husbands, women were grouped into four categories: husband was – i) of similar age, ii) 3–5 years older, iii) 6–9 years older, and iv) 10 + years older. Compared to women whose husbands were of similar age, the odds of having hypertension for the other categories were assessed by estimating multivariable logistic regression models. While the hypertension prevalence in our sample was 18.9%, it was 2.2%-points lower among women whose husbands were of similar age, and 3.3%-points higher among women whose husbands were 10 + years older. The adjusted odds of having hypertension for women with 10 + years of spousal age difference were 1.18 (95% CI: 1.13–1.24) times that of their counterparts who were of similar age to their husbands. These results were persistent in both younger (age 20–34) and older (age 35–49) women and robust across age at marriage, years in marriage, and various socioeconomic sub-groups including women’s educational attainment, husband’s educational level, household wealth, urban/rural residence, and geographic regions. The relationship also persisted after adjusting for husband’s hypertension status. Our findings thus highlight spousal age difference as a biopsychosocial factor influencing the risk of hypertension in women.
Dynamic Shaking Table Test of a Constructive Sytem With Timber Frame Structure and Light Earth Enclosure
Authors: Orihuela Germán Luis Francisco Becerra , Onnis Silvia , Meli Giuseppina , Rey Martin Franz Wieser , Schmidt Urbano Tejada
Published: June 2024

There is a large deficit of housing and equipment in Latin America, which needs to be addressed with more construction alternatives offering seismic safety, in addition to economical, comfortable, and sustainable solutions. The proposal of a modular system of prefabricated elements of a timber frame structure and light earth enclosure panels is a feasible option for seismic-prone regions. This article describes a shaking table test performed on a proposed timber frame structure with a light earth enclosure and sheathing of diagonal wooden laths as part of a larger framework that seeks to propose a constructive solution. The test aims to assess the model’s seismic performance, determine its fragilities, and calculate the system’s dynamic properties. The seismic performance showed two stages of damage: an elastic stage during frequent and rare earthquakes, where the immediate occupancy and operational states of the structure were proven, and an over-resistance stage during a very rare earthquake, where life-safety performance with reparable damage was observed. The model’s dynamic properties showed an overall increase in dumping related to the reduction of lateral stiffness, with the ability to deform and dissipate energy. Even though the system performed well, the test has shown some limits of the structure that should be considered for the construction of a future dwelling prototype.
Layered-Columnar Cathode Materials for Sodium-Ion Batteries
Authors: Liu Jianjun , Zhao Xiaolin , Li Yi , Wang Youwei , Song Erhong , Ma Ruguang
Published: June 2024

The advancement of cathode materials possessing high-rate capability and extended cycle life is crucial for the viability of large-scale energy storage in sodium-ion batteries. A novel layered-columnar material NaFe[O3PCH(OH)CO2] is designed with a 2D grid-like channels for sodium ion migration. Operating on the Fe2+/Fe3+ redox reaction, NaFe[O3PCH(OH)CO2] exhibits a reversible specific capacity of 106.1 mAh g-1 after 50th cycles within the voltage range of 1.5-4.2 V, reaching 93.4% of the theoretical specific capacity. Experimental and theoretical investigations have both demonstrated that NaFe[O3PCH(OH)CO2] exhibits low-strain characteristics during discharge and charge processes. The presence of stable C-P covalent bonds between organic layers and inorganic columns ([FeO6] and [CPO3]) plays a pivotal role in achieving its long cycle life. Even under high current rates of 2C, it maintains satisfactory capacities, delivering 61.6 mAh g–1 after the 1000th cycle. This study indicates that layered-columnar structure design provides an effective pathway to develop a new generation of cathode materials with high performance in sodium-ion batteries.
Carbon Peak Trends and Stepped Emission Reduction Paths in Yangtze River Economic Belt Cities
Authors: xia yihan , ji kaiwen , wang wenqiang , tang wenying
Published: June 2024

Cities not only contribute significantly to carbon emissions but also serve as key drivers for promoting carbon emission reduction. They play a pivotal role in demonstrating the achievement of 'carbon peak' and 'carbon neutrality' objectives. This paper utilizes DMSP/OLS stable nighttime lighting data from 2000 to 2013 and NPP/VIIRS nighttime lighting data from 2013 to 2019 to simulate the carbon emissions of cities within the Yangtze River Economic Belt. A BP neural network model is constructed and combined with scenario analysis and a geographically weighted regression model to systematically analyze the carbon emission characteristics, carbon peak trends, and graded carbon emission reduction paths of cities within the Yangtze River Economic Belt. This analysis considers various factors such as time series, geography, and per capita metrics. Subsequently, tailored graded carbon emission reduction paths and countermeasures are proposed for different types of cities experiencing various carbon peak scenarios, aiming to accelerate carbon emission reduction efforts within the Yangtze River Economic Belt.
A Survey on Fault Detection in Industrial IoT: A Machine Learning Approach with Emphasis on Federated Learning and Intrusion Detection Systems
Authors: Elmazi Klea , Elmazi Donald , Lerga Jonatan
Published: June 2024

In recent years, the Internet of Things (IoT) has received a lot of attention and research. The concept of Industrial IoT (IIoT) has emerged from the con- vergence of information technology (IT) and industrial automation and control systems. The increasing number of disjointed IoT networks deployed in many industrial sectors has exposed vulnerabilities leading to security incidents, jeopar- dizing the overall security of IIoT systems. This paper provides a comprehensive survey, analyzing and comparing current technologies for securing IIoT networks. Researchers have developed various detection strategies supported by machine learning (ML) approaches. Federated Learning (FL) offers lower latency and pre- serves privacy, emerging as a promising distributed ML paradigm that enhances detection performance. Several challenges and recommendations are defined in the context of intrusion detection systems (IDS) as a security monitoring mechanism.
Antiviral Activity of Baicalin Against Infectious Bronchitis Virus
Authors: He Jiongjie , Wang Shengyi , Guo Huilin , Zhang Yong
Published: June 2024

Background
Baicalin, the main metabolic component of Scutellaria Baicalin Georgi, displays potent anti-inflammatory, anti-oxidant, anti-apoptotic, anti-bactericidal, and antiviral properties. Baicalin was found to be effective in the treatment of infectious bronchitis (IB) in chickens. However, the molecular mechanism of treatment remained unclear. Therefore, in this study, the antiviral activities of baicalin on infectious bronchitis virus (IBV) were evaluated in vitro and in vivo for the first time, to explore the molecular mechanism of baicalin inhibiting IBV replication.
Results
Treatment with 20 µg/mL baicalin significantly reduced relative mRNA expression and IBV viral titers, a finding confirmed by immunofluorescence studies in chicken embryo kidney (CEK) cells. Baicalin treatment at a dose of 45 mg/kg significantly reduced IBV induced injury in the trachea, lung and kidney. Baicalin treatment also led to an upregulation of both interferon-α (IFN-α) and Interferon-β (IFN-β), with IFN-β increased the most. Although treatment with baicalin did not influence the mRNA expression of melanoma differentiation associated gene 5 (MDA5), Toll-like receptor 3 (TLR3), and Toll-like receptor 9 (TLR9), mRNA levels of mitochondrial antiviral signaling gene (MAVS), TANK binding kinase 1 (TBK1), and Interferon regulatory factor 7 (IRF7) increased, with MAVS showing the largest increase amongst all cytokines measured in vitro. Overexpression of MAVS significantly upregulated the expression of IFN-β and reduced the viral titer of IBV. Knockdown of MAVS significantly affected the antiviral effect of baicalin on IBV.
Conclusions
Baicalin possesses significant anti-IBV effects in vitro and in vivo. Baicalin-induced increases in the expression of type I interferons in CEK cells after IBV infection is likely linked to increased signaling through the enhanced MAVS expression in the MDA5 pathway. Baicalin’s inhibition of IBV replication was also closely related to MAVS cytokines, but not dependent on MAVS expression. These findings are important to accelerate our understanding of the antiviral effects of baicalin and provide new insights into the development of effective therapeutic strategies.
Uridine diphosphate (UDP)- glycosyltransferases (UGTs) confer insecticide resistance in the major malaria vectors Anopheles gambiae s.l and Anopheles funestus
Authors: Logan Rhiannon Agnes Ellis , Mäurer Julia Bettina , Wapler Charlotte , Ingham Victoria Anne
Published: June 2024

Malaria remains one of the highest causes of morbidity and mortality, with 249 million cases and over 608,000 deaths in 2022. Insecticides, which target the Anopheles mosquito vector, are the primary method to control malaria. The widespread nature of resistance to the most important insecticide class, the pyrethroids, threatens the control of this disease. To reverse the stall in malaria control there is urgent need for new vector control tools, which necessitates understanding the molecular basis of pyrethroid resistance. In this study we utilised multi-omics data to identify uridine-diphosphate (UDP)- glycosyltransferases (UGTs) potentially involved in resistance across multiple Anopheles species. Phylogenetic analysis identifies sequence similarities between Anopheline UGTs and those involved in agricultural pesticide resistance to pyrethroids, pyrroles and spinosyns. Expression of five UGTs was characterised in An. gambiae and An. coluzzii to determine constitutive over- expression, induction, and tissue specificity. Furthermore, a UGT inhibitor, sulfinpyrazone, restored susceptibility to pyrethroids and DDT in An. gambiae, An. coluzzii, An. arabiensis and An. funestus, the major African malaria vectors. Taken together, this study provides clear evidence of the role of UGTs in pyrethroid resistance as well as highlighting the potential use of sulfinpyrazone as a novel synergist for vector control.
Effect of acute exercise on gene expression in peripheral blood mononuclear cells of puberty children
Authors: Du Li-Jun , Song Yu-Hong , Tang Li-xu
Published: June 2024

Abstract Background: Studies have shown that acute exercise alters the expression of circulating neutrophil and peripheral blood mononuclear cell (PBMC) genes, affecting a wide range of processes from cellular growth to the promotion of inflammatory and anti-inflammatory responses.In this study, we identified differential gene expression associated with acute exercise and PBMC in puberty children through the GEO database. We utilized bioinformatics technology to analyze the impact of acute exercise on PBMC and identified key genes involving the puberty children.
Methods: Combining two datasets of gene expression, we identified 197 shared differentially expressed genes (DEGs) in PBMC before and after exercise. We conducted pathway analysis of these DEGs and built a gene co-expression network. The identification of hub genes was achieved through the utilization of protein-protein interaction (PPI) networks.
Results: 268 shared DEGs were identified in the GSE11761 dataset in pre- and post-exercise groups, while 352 differential genes were identified between the pre- and post-exercise groups of females in the GSE14642 dataset. A total of 197 shared genes were identified between the two datasets. Seven core genes were identified by MCODE and CytoHubba, namely IL2RB, KLRD1, GZMB, TBX21, PRF1, HAVCR2, and GZMA.
Conclusion: Bioinformatics techniques are effective in screening and analyzing PBMC-associated DECs in children undergoing acute pre- and post-exercise puberty. Microarray analysis of PBMCs in children undergoing puberty can identify molecules that may predict acute exercise responses. This study provides insights for further exploration of the mechanisms and targets of acute exercise on the organism.
Studies on the Probiotic, Adhesion and Induction Properties of Artisanal Lactic Acid Bacteria: To Customize a Gastrointestinal Niche to Trigger Anti-Obesity Functions
Authors: Kamber Aslihan , Albayrak Cisem Bulut , Harsa Hayriye Sebnem
Published: June 2024

Aims: The primary goals of this work are to explore the potential of probiotic LAB's mucin/mucus layer thickening properties and to identify anti-obesity candidate strains that improve appropriate habitat for use with the Akkermansia group population in the future.
Methods and Results: The HT-29 cell binding, antimicrobial properties, adhesion to the mucin/mucus layer, growth in the presence of mucin, stability during in vitrogastrointestinal (GI) conditions, biofilm formation, and mucin/mucus thickness increment abilities were all assessed for artisanal LAB strains. Sixteen LAB strains out of 40 were chosen for further analysis based on their ability to withstand GI conditions. Thirteen strains maintained their vitality in the simulated intestinal fluid, whereas the majority of the strains displayed high viability in the gastric juice simulation. Furthermore, 35.2-65.4% of those 16 bacteria adhered to the mucin layer. Besides, different lactate levels were produced, and Streptococcus thermophilusUIN9 exhibited the highest biofilm development. Also, with a 50 mM lactate concentration and the presence of mucin that had been injected originally, Lacticaseibacillus casei NRRL-B 441 had the maximum amount of mucin (321.6 µg/mL).
Conclusions: Two isolates of olive bacteria from Lactiplantibacillus plantarum were chosen as the anti-obesity prototype candidates; these strains did not consume mucin sugars.
Significance and Impact of the Study: Probiotic LAB's attachment to the colonic mucosa and its ability to stimulate HT-29 cells to secrete mucus are critical mechanisms that may support the development of Akkermansia.
Analysis of the Dissemination Effect and Related Factors of Articles on a Provincial CDC WeChat Official Account
Authors: Zhang Mengyuan , Xu Xuepeng , Zhen Shiqi , Zhu Chenyu , Zhu Lin , Ji Lili
Published: June 2024

Objective:To analyze the characteristics, reading, and sharing data of the articles published on the "Jiangsu CDC" WeChat Official Account, and provide a reference for further optimizing communication strategies.
Methods:Based on relevant primary data from the WeChat Official Account backend, the Read Index, Share Index, Read Index after Share, and Complete Index were calculated. Non-parametric tests and multiple linear regression analysis were used to analyze the factors influencing the dissemination effect.
Results: The median Read Index of the articles was 0.360 (0.160, 0.900). Headline article (B=0.408, 95% CI: 0.085, 0.731), video form (B=-0.499, 95% CI: -0.917, -0.081), and publicity report (B=-0.504, 95% CI: -0.933, -0.075) were influencing factors for article reading (P<0.05). The median Share Index was 3.040 (1.740, 4.640), and disease prevention knowledge (B=-1.443, 95% CI: -2.459, -0.427), publicity report (B=-2.677, 95% CI: -4.110, -1.245), and seasonal health tips (B=-1.861, 95% CI: -3.224, -0.498) were influencing factors for article sharing (P<0.05). The influencing factor regression analysis for the Read Index after Share showed no statistical difference. The median Complete Index was 21.280 (14.985, 86.665), and video form (B=32.967, 95% CI: 9.722, 56.211) was an influencing factor for complete article reading (P<0.05).
Conclusion: It is necessary to strengthen the supply of high-quality resources, pay attention to developing text-with-images and poster articles, strengthen integration and collaboration, build a multidimensional communication matrix, and expand the influence of science popularization brands.
Using structural equation modeling to determine the cognitive functions of older adults from their driving operation data
Authors: TANABE Hiroko , YOSHIHARA Yuki , KARATAS Nihan , TANAKA Takahiro , KOJIMA Motoshi , ENDO Masato , MANABE Shuhei
Published: June 2024

Declining cognitive and motor functions make safe driving difficult for older adults. Trail Making Test (TMT) scores are reported to facilitate the estimation of cognitive functions in older adults and enable correlations with parameters associated with driving skills and vehicle speed. However, the causal relationships between cognitive functions and discrete driving-related parameters remain unclear. First, this study examined the correlations between the TMT indices and driving-related parameters of older adult drivers. Next, it used structural equation modeling to express the causal relationships between the parameters and TMT indicators. Thirty older adult drivers accomplished an intersection passage task on a driving simulator (DS) and consecutively performed multiple TMT iterations. Vehicle operation data collected from DS logs, data on head motions to confirm safety at an intersection, and accumulated TMT scores indicating cognitive functions enabled this study to determine correlations between the TMT indices and the parameters of pedal operation (vehicle speed), steering (steering input and lateral vehicle position), and head motion (horizontal angle and velocity). Models were then created to discern relationships between these parameters and the cognitive functions of older adult drivers. The study results indicate the possibility of automatically estimating the cognitive functions of older adult drivers from their daily driving-related data.
Medical talent gap analysis based on natural language processing
Authors: Chen Yirui , Zhan Xinrui , Yang Wencan , Yan Xueying , Du Yuxin , Zhao Tieniu
Published: June 2024

As healthcare demands technical skills like data analysis and project management, there is a widening talent gap in the medical field. To bridge this gap, this paper uses natural language processing to analyze healthcare job listings, revealing specific skills and management capabilities in high demand.The study applied natural language processing techniques to analyze 42,032 healthcare job listings caught by web crawler technology, extracting and analyzing data on required skills, qualifications, and roles within the sector.The analysis found a need for tech skills like data analysis and AI in healthcare, alongside management expertise. The sector values innovation, research, and data privacy, crucial for strategic talent development and policy-making to enhance service quality and industry growth.The study shows healthcare's growing demand for tech and management skills, promising better patient care and efficiency. Responsible innovation, compliance, and data privacy are key. These insights help stakeholders bridge talent gaps and meet evolving healthcare needs.
Risk factors for all-cause mortality during the COVID-19 pandemic compared with the pre-pandemic period in an adult population of Arkhangelsk, Russia
Authors: Krieger Ekaterina , Kudryavtsev Alexander V. , Sharashova Ekaterina , Samodova Olga , Postoev Vitaly
Published: June 2024

We investigated and compared mortality rates and risk factors for pre-pandemic and pandemic all-cause mortality in a population-based cohort of men and women in Arkhangelsk, Russia. A prospective cohort study enrolled 2,324 participants aged 35 to 69 years between 2015 and 2017. All participants were followed up for all-cause deaths using the mortality registry. Mortality rates per 1000 person-years were calculated for men and women in the pre-pandemic and pandemic periods. Cox regression models were used to investigate demographic, lifestyle, and health characteristics associated with increased risk of death in both periods. During the pandemic, age-standardized all-cause mortality increased in women, but minor change was observed in men. Older age, smoking, and diabetes were associated with a higher risk of all-cause death in both periods and for both sexes. In women, higher risk during the pandemic was associated with obesity, angina, and elevated cystatin C levels. In men, asthma and elevated hs-Troponin T levels increased the risk of death during the pandemic, while elevated hs-CRP and NT-proBNP levels were associated with higher risk in both periods. Targeted preventive interventions for men and women with specific risk factors can be implemented during potential future infectious disease outbreaks.
Heat Transfer Enhancement and efficiency optimization of Novel Polygonal Collector Influence of Thermophysics Characteristic of Nanoparticles Using Response Surface Methodology
Authors: Baharloui Samaneh , Peiravi Mohammad Mohsen , Gorji Mofid
Published: June 2024

The novelty of present study is the improvement of thermal efficiency and energy management for novel polygonal collector, composed of chaotic TiO2 and LiBr nanoparticles. The optimization process of thermal efficiency is considered using response surface methodology. So, total temperature of octagonal collector influence of TiO2 Nano particles is 63.27% and 24.32% more than triangular and cubical collectors. Also, incident radiation of octagonal collector influence of TiO2 Nano particles is 3.56% and 4.52% more than triangular and cubical collectors. Moreover, the surface radiation absorption of the octagonal collector influence of LiBr Nano particles is 2.93% and 4.67% more than the triangular and cubical collectors. Moreover, the total ground heat flux of the octagonal collector influence of LiBr Nano particles is 74.26% and 74.63% more than the triangular and cubical collectors.
Spoofify: A Hybrid Anti-Spoofing Facial Recognition System
Authors: Zia Ayesha , Ejaz Syeda Ravia , Ahmad Sabeerah , Syed Farrukh Hasan
Published: June 2024

Facial recognition systems have gained widespread adoption as replacements for conventional authenti- cation methods due to their robustness, offering bet- ter security compared to systems such as PINs, pass- words, and fingerprints. However, despite their re- silience, facial recognition remains vulnerable to var- ious attacks , including picture, video, and replay at- tacks. To mitigate these risks, the implementation of a robust anti-spoofing mechanism is imperative. In this paper, we propose a novel hybrid anti-spoofing facial recognition system that combines unsupervised and supervised approaches to address spoofing vul- nerabilities effectively. Leveraging Generative Adver- sarial Networks (GANs) as the cornerstone model for anti-spoofing, our system employs their efficiency in feature learning to discriminate between genuine and spoofed images. The user identification is performed using a K-Nearest Neighbors (KNN) classifier, which analyzes facial features to match individuals against a database of registered users. We evaluate the perfor- mance of our proposed system on the CelebA-Spoof and CASIA-FASD Datasets, achieving a commend- able accuracy rate of 69% on CASIA-FASD. Through rigorous experimentation and analysis, we demon- strate the efficacy and reliability of our hybrid anti- spoofing facial recognition system, offering a promis- ing solution to enhance security in real-world appli- cations. The source code for the approach will be re- leased on: https://github.com/ayeshazia99/spoofify- a-hybrid-antispoofing-facial-recognition-system
Modeling of AP-HTPB Solid Propellant Viscoelastic Behavior Using Modified Maxwell Model
Authors: Eldin A. F. Nour , Adel Walid. M. , sabbagh Ahmed El
Published: June 2024

In this research, an initial exploration of the viscous effects present in heterogeneous solid rocket propellant is conducted through experimental analysis. To achieve this, uniaxial tensile and relaxation experiments were conducted on the Joint Army-Navy-NASA-Air Force Propulsion Committee (JANNAF) standard[1], specimens using the Zwick Z050 universal testing machine. The work involved conducting destructive tensile tests at different strain rates and relaxation tests at different strain levels and temperatures, with three values being considered. The resulting data from the experiments are illustrated in appropriate diagrams, and depending on these data, the viscoelastic behavior of this material was confirmed. Additionally, mathematical modeling of this studied phenomenon using the generalized Maxwell model, identified on the basis of experimental data, is presented. The material parameters of the constitutive model are determined numerically using MATLAB software based on the Prony series procedure. The efficiency of the model and the identification approach are discussed. A high agreement between the calculation and the experimental results was found based on the Prony coefficients of relaxation modulus, with a maximum error of about 2.35%. Finally, numerical modeling of the relaxation tests was conducted to simulate the stress relaxation behavior of the AP-HTPB composite solid propellant using the ANSYS program. The Prony coefficients were added to the nonlinear viscoelastic components to define the material model in ANSYS, and the maximum difference between the numerical and experimental results is 3.98%.
Signal-amplified surface-enhanced Raman scattering using core/shell satellite nanoparticles for norovirus detection
Authors: Park Enoch Y. , Maehata Syuei , Khoris Indra Memdi , Achadu Ojodomo
Published: June 2024

The development of highly sensitive, rapid, and simple detection techniques for today's aging society is an essential subject, as seen by the rising prevalence of viral infections. Herein, we explore the development of an innovative approach to amplify the signal of a surface-enhanced Raman scattering (SERS)-based detection system using a novel nanotag: Au@Ag NPs covered by satellite AuNPs and conjugated by 4-mercaptbenzoic acid (4-MBA) as a Raman tag (Au@Ag-MBA-AuNPs). The Au@Ag-MBA-AuNPs nanotags showed strong SERS activities with an enhancement factor in the 108 order of magnitude. This indicates the formation of many hot spots due to the combination of core-shell nanoparticles and satellite AuNPs on the surface of Au@Ag-MBA NPs. The newly fabricated nanotags were employed in a small-sized Palmtop Raman spectrometer. A concentration-dependent increase in SERS intensity was observed in the norovirus-like particle (NoV-LP) concentration range of 10 fg/mL to 100 pg/mL with a detection limit of 0.76 fg/mL. Even in the severe interfering matrices, this detection method's coefficient of variation was less than 10%. This detection system was approximately 107 times more sensitive than commercially available ELISA kits. Norovirus in clinical samples was detected over a wide concentration range of 1.0 × 101 – 1.0 × 106 RNA copy number/mL with a detection limit of 7.8 RNA copy number/mL, indicating sensitivity comparable to real-time PCR. These results suggest that this detection system is stable in a complex matrix and has the potential for detecting clinical samples with a small Palmtop Raman spectrometer.
Multi-omics investigation reveals unique markers underpinning the success of Klebsiella pneumoniae over closely related species
Authors: Swiatek Lena-Sophie , Surmann Kristin , Eger Elias , Müller Justus Ursus , Salazar Manuela Gesell , Heiden Stefan E. , Werner Guido , Hübner Nils-Olaf , Bohnert Jürgen A. , Becker Karsten , Völker Uwe , Schwabe Michael , Schaufler Katharina
Published: June 2024

Background
The Klebsiella pneumoniae (KP) species complex comprises KP as the predominant species, and four others including Klebsiella variicola (KV) and Klebsiella quasipneumoniae (KQ), all capable of causing clinical infections and often challenging to differentiate. The emergence of multidrug-resistant and hypervirulent KP strains has led to severe infections with limited treatment options, underscoring the need to understand the factors contributing to KP's prevalence.
Methods
This study compared globally disseminated KP lineages with less abundant KV and KQ strains across multiple omics levels to identify characteristics potentially explaining KP's success over closely related species.
Results
We identified 107 genes of the core genome in eight clinical KP strains from four different sequence types (STs). Transcriptome and proteome analyses in human urine-like medium revealed different regulatory patterns between KP and KV strains, with metabolic responses playing a pivotal role. A total of 193 genes specific to the investigated KP STs were identified, exhibiting differential expression at the transcriptomic and/or proteomic levels. Comparison of these regulated genes to over 6,000 publicly available Klebsiella genomes highlighted genes adaptively regulated or uniquely present in KP genomes. For example, a gene cluster for the cellobiose phosphotransferase system, previously linked to bacterial virulence and biofilm formation, was found exclusively in KP.
Conclusion
Our study underscores the metabolic flexibility of KP strains in response to specific environmental conditions, potentially crucial for their success as opportunistic pathogens. We identified markers enriched in KP STs, providing a foundation for future investigations and potential utilization in alternative treatment strategies to conventional antibiotics.
Enhancing Speech Privacy through Dynamic Chaos- Driven Scrambling with Nested Segmentation
Authors: MERRAD Ahmed , NOURI Abdelkader Nabil
Published: June 2024

Designing speech cryptosystems presents huge challenges. This paper introduces a novel speech scrambling approach that leverages the strength of two chaotic maps and nested segments. Initially, the process of the scrambling determines the starting point of each segment after diverse parameters are provided, such as the starting point of the first piece and the length of each segment. Then, based on a rearranged chaotic signal generated by the Tent map, the process commences permuting the samples of the nested segments with a specific order that determined according to another rearranged chaotic signal created using the Logistic map. In order to allow the possibility of permuting the samples beyond their initial segment, the process of scrambling iterates throughout the whole signal several times, using a supplied key. The achieved outcomes shows the efficiency of the planned method, as SNR values can reach − 3 and infinity in scrambling and unscrambling operations, respectively, as well, the waveforms vividly depict the flawless diffusion of the samples across the length of the signal.
Uncovering Naringin’s Anticancer Mechanisms in Glioblastoma via Molecular Docking and Network Pharmacology Approaches
Authors: Rajendran Arunraj Tharamelveliyil , Rajesh Gupta Dheeraj , Ashtekar Harsha , Sairam Anusha , Kumar Pankaj , Vadakkepushpakath Anoop Narayanan
Published: June 2024

Naringin, a flavonoid, exhibits diverse therapeutic properties and has been proven to exert cytotoxic effects on cancer cells. Nevertheless, the precise mechanism of naringin maintaining its cytotoxic effect on glioblastoma (GBM) remains unknown. Thus, the current study aimed to establish a plausible cellular mechanism for Naringin's inhibition of GBM. We employed various system biology techniques to forecast the primary targets, including gene ontology and cluster analysis, KEGG enrichment pathway estimation, molecular docking, MD (molecular dynamic) simulation and MMPBSA analysis. Glioblastoma target sequences were obtained via DisGeNet and Therapeutic Target Prediction, aligned with naringin targets, and analyzed for gene enrichment and ontology. Gene enrichment analysis identified the top ten hub genes. Further, molecular docking was conducted on all identified targets. For molecular dynamics modelling, we selected the two complexes that exhibited the most docking affinity and the two most prominent genes of the hub identified through analysis of the enrichment of genes. The PARP1 and ALB1 signalling pathways were found to be the main regulated routes. Naringin exhibited the highest binding potential of -12.90 kcal/mol with PARP1 (4ZZZ), followed by ABL1 (2ABL), with naringin showing a -8.4 kcal/mol binding score, as determined by molecular docking. The molecular dynamic approach and MM-PBSA investigation revealed that the complex of Naringin, with 4ZZZ (PARP1) and, 2ABL(ABL1), demonstrated the highest stability. Analyses of the signalling pathway suggested that naringin may have anticancer effects against GBM by influencing the protein PARP and ALB1 levels. Since it was developed In-silico, this study will expand to validate the mechanism in wet labs.
A High Selective and Q Factor 4-Channel All Optical Demultiplexer: Numerical and Analytical Evaluation
Authors: Vali‑Nasab Aziz-Morad , Hasanvand Javad , Mir Ali , Hamouleh-Alipour Abbas
Published: June 2024

Photonic crystals (PCs) are a field that is very important and interested in the design of a wide range of devices to control electromagnetic waves in different frequency regimes. Here, We try to introduce an all-optical device with practical applications such as fast response and high accuracy that have very critical and benchmark development in optical devices for photonic integrated circuits. In this paper, a novel modified shape 4-channel demultiplexer based on 2D-PCs by using suitable ring resonators is proposed to control light. The presented configuration includes three parts such as a direct input waveguide, a ring resonator, and four indirect waveguides for outputs of optical waves. Numerical analysis is investigated based on finite difference time domain (FDTD) method to achieve a four-band demultiplexer that has the capability to control the electromagnetic waves. Numerical results show that not only average quality factor (Q) of the 2D-PCs demultiplexer is 3969.25, but also average cross-talking value is -30.38 dB, the average transmission coefficient (T) is 0.998 and the lowest and highest channel bandwidths are 0.3 and 0.6 nm, respectively. Also, the minimum and maximum distance between any two adjacent channels is 0.6 and 1.1 nm. The all optical photonic demultiplexer has a compact footprint and occupies an area of 302 µm² and its operation is in long wavelength region. Based on the abovementioned practical performance and results, the presented optical demultiplexer is highly accurate by using a robust and low power-area that can be nominated to use photonic integrated circuits (PIC).
Towards Text Contextual Understanding: Text Feature Fusion GAN for Text-to-Image Generation
Authors: Jiang Xiaoyan , Chen Jize , Zhang Juan , Chen Zhichao , Gao Yongbin , Wu Xiang
Published: June 2024

Understanding texts and generating high-resolution realistic images from text descriptions is a meaningful and challenging topic. Most existing text-to-image generation methods follow the multi-stage generative adversarial network (GAN) framework. Therefore, the image quality of current stages relies heavily on the images generated in the previous stages. Additionally, current text-to-image generators do not so well guarantee a consistent relationship between the text description and the generated image. To address the above issues, we present a novel Text Feature Fusion GAN (TF-GAN) architecture, emphasizing on selecting useful local words and extracting semantic consistent global sentence features. First, useful keywords are extracted in the text description by the proposed sentence fusion attention mechanism (SFAttn) to optimize image features in early stages and provide fine-grained details for the images of the later stage. Second, we propose a new Conditional Fusion Block (CFBlock), which combines multiple non-linear affine transformations to constrain images on a global semantic level. This allows the model to more deeply fuse sentence and image features, leading to more semantically consistent generated images. Extensive experiments and Comparison with other state-of-the-art methods on the Caltech-UCSD Birds 200 (CUB) dataset and the Microsoft Common Objects in Context (COCO) dataset show that our generated images are more photo-realistic and closer to the text descriptions.
The Potential Chemotherapeutic Effect of Coenzyme Q10 against Liver Injury in a Leukemia Rat Model by 7,12-dimethylbenzanthracene; histological and morphometric study
Authors: Alshali Rasha A.
Published: June 2024

Introduction:
Coenzyme Q10 (CoQ10) is an essential cofactor in the mitochondrial electron transport chain that benefits liver disorders. The polycyclic aromatic hydrocarbon (PAH) 7,12-dimethylbenz[a]-anthracene (DMBA) originates and promotes carcinogenesis. This study investigated the potential anti-leukemic effects of CoQ10 in a DMBA-induced leukemic rat model. The biochemical, histological, and immunohistochemical analysis of the liver was assessed to determine that CoQ10 would modify liver injury caused by DMBA-induced Leukemia in rat model.
Methods
Forty adult male albino rats were split equally into four groups: control group (Group I), coenzyme Q10 group (Group II), DMBA group (Group III), and coenzyme Q10 plus DMBA group (Group IV). The first DMBA dose of 40 mg/kg body weight produced leukaemia in all rats except GI and GII rats. Three further injections were given at a rate of 30 mg/kg body weight every two weeks for a total of 6 weeks. Body weight and blood samples were evaluated once the experiment was complete. Biochemical, histological, immunohistochemical, and morphometric analyses were performed on liver tissue.
Results
CoQ10 treatment significantly reduced liver enzyme levels relative to leukemia-model animals. Malondialdehyde (MDA) levels were much lower in CoQ10 group compared to DMBA group, whereas glutathione (GSH) and Superoxide dismutase (SOD) levels were significantly increased. Histopathological examination of rat DMBA livers revealed a loss of normal hepatic architecture, which was restored after administration of CoQ10.
Conclusion
Treatment with CoQ10 attenuated the alleviation of DMBA-induced leukemia in rats, claiming its potential as an effective therapy for leukaemia and liver impairment caused by leukaemia.
Curcumin ameliorates hepatic steatosis and insulin resistance through the JNK2/FOXO1/Bcl6 axis and regulate the intestinal flora structure
Authors: Yang Ju , Song Biao zhang , Zhang Feng , Liu Bing , Yan Ji ai , Wang Yingyu , Sun Jing , Zhao Cheng guang , Li Dan , Cao Hong
Published: June 2024

Curcumin, a polyphenol extracted from the plant turmeric rhizoma, is well known for its strong antioxidant capacity and beneficial effects on the treatment of obesity induced by a high-fat diet in mice. However, the exact mechanism of action by which it improves obesity remains elusive. We hypothesize that curcumin exerts its anti-obesity effects on high-fat-diet (HFD) induced obesity through both direct effects on metabolic pathways and indirect effects on metabolism by improving the intestinal flora structure. The aim of this study was to investigate the effect of curcumin on the biological phenotype of HFD-induced obese mice, to determine the related metabolic pathways and to determine whether the intestinal flora is involved. C57BL/6 mice were fed a HFD for 8 weeks and then gavaged with 200 mg/kg curcumin or the same volume of vehicle for 16 weeks. The body weight, blood glucose level, blood lipid level, insulin resistance and oxidative stress level of the mice were detected to determine the effect of the treatment on lipid metabolism. Liver transcriptome analysis combined with qPCR and cell experiments revealed that curcumin improves hepatic steatosis and insulin resistance in mice fed a high-fat diet by downregulating the JNK2/FOXO1/Bcl6 axis. Curcumin treatment can regulate the composition and structure of gut microbiota in high-fat diet-fed mice, increase gut microbiota diversity, and increase the relative abundance of beneficial bacteria such as Coriobacteriaceae, Mailhella, Faecalibaculum, Phocaeicola vulgatus, Parvibacter vulgatus, and Bacteroides intestinalis, which are associated with obesity and metabolic disorders, while reducing the relative abundance of harmful bacteria such as Alistipes, Oscillibacter, Lactobacillus johnsonii, and Acutalibacter muris. In conclusion, curcumin ameliorated hepatic steatosis and insulin resistance in HFD-fed mice by down-regulating hepatic JNK2/FOXO1/Bcl6 axis and altering the composition and structure of gut microbiota.
Analysis and control of new invariant JN.1 under generalized incidence rate for low immune: Mathematical modeling and bifurcation
Authors: Junjua Moin-ud-Din , Faheem Muhammad , Ahmad Aqeel , Akram Muhammad Saeed , Hincal Evren
Published: June 2024

The goal of this study is to analyze and control the new variant JN.1 under generalized incidence rate for low immune individuals by taking combine measures of vaccination as well as quarantine. By incorporating vaccination and quarantine together with generalized incidence rate a new mathematical model is developed based on generated novel hypothesis. To ascertain the stable status of the recently constructed SEVIQR system which is analysis both qualitatively and quantitatively to understand the dynamics of spread as well as control under bounded domain including bifurcation analysis. Stability analysis have been derived on local as well as global scale using Lyapunov’s first derivative functions to evaluate the overall effects of disease propagation and control. The existence and positive solutions property is also derived under non local operator. To ensure reliable bounded findings, the boundedness and uniqueness are examined, those are necessary characteristics for epidemic models. We use Lipschit’z conditions and linear growth to fully validate the global derivative that characterizes the rate of change of disease impact on each sub-compartment. The bounded approximate solutions for new invariant JN.1 derived sing Mittag-Leffler kernel with fractal fractional operator for continuous monitoring. Simulations are derived using MATLAB coding to observe the real impact of spread as well as control of virus caused by new variant JN.1 with generalized incidence rate, a variety of factors are imposed with constant monitoring. To observe the asymptomatic and symptomatic consequences of the corona virus illness under new variant JN.1, simulations are developed with combine actions of vaccination as well as quarantine effects for low immunity people to capture the disease’s true behavior. To comprehend how the virus spreads for low immune individuals and to create efficient control plans based on the results that make sense such investigations are valuable.
CA1 Engram Cell Dynamics Before and After Learning
Authors: Ramirez Steve , Monasterio Amy , Lienkaemper Caitlin , Coello Siria , Ocker Gabriel , Scott Benjamin
Published: June 2024

A fundamental question in neuroscience is how memory formation shapes brain activity at the level of populations of neurons. Recent studies of hippocampal ‘engram’ cells, identified by immediate-early genes (IEGs) induced by learning, propose that these populations act as a neuronal substrate for memory storage. The current framework for engram formation proposes that cells join ensembles based on increased intrinsic excitability, and that after initial learning, they co-activate to support memory retrieval. However, direct evidence of how engram population dynamics evolve across learning is limited. Here we combined activity-dependent genetic tagging and two-photon calcium imaging to characterize CA1 engram population activity before and after learning. We observed that spontaneous activity two days before learning predicted genetic tagging, consistent with a model in which spontaneous fluctuations bias cells into forming engram assemblies. Surprisingly, we were unable to detect increased spontaneous activity rates or pairwise correlations amongst tagged CA1 neurons after learning. These results were consistent with computational network models that incorporate strong and specific inhibitory connections, supporting the idea that excitatory/inhibitory balance in CA1 may play a key role in engram dynamics. Together these results highlight a potential role for slow time scale excitability fluctuations in driving engram formation and suggest that excitatory-inhibitory balance may regulate engram cell co-activation.