bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantum transport of massless Dirac fermions through wormhole-shaped curved graphene in presence of constant axial magnetic flux
Authors: Naderi F. , Hasanirokh K. 
Published: April 2024

AbstractIn this work, we have studied the spin-dependent quantum transport of charged fermion on $$(2+1)$$

(
2
+
1
)

-dimensional spacetime, whose spatial part is described by a wormhole-type geometry in the presence of constant axial magnetic flux. Choosing the solutions of the Dirac equation associated with real energy and momentum, we explored the spin-dependent transmission probabilities and giant magnetoresistance (GMR) through a single layer of wormhole graphene with an external magnetic field, using the transition matrix (T-Matrix) approach. The spin-up and spin-down components within the A and B sublattices of graphene in the matrix of $$4\times 1$$

4
×
1

wave function are coupled to each other due to the wormhole structure and the magnetic field. We have found that transport properties strongly depend on the magnetic field, incident energy, and geometric parameters of the system. We observed that the transmission probability increases as the radius of the wormhole increases, and the length of the wormhole decreases. The higher energies lead to a decrease in the transmission probabilities of particles. Furthermore, we observed that the probability of the spin-flip effect is almost larger than that of the non-spin-flip effect, illustrating that electrons lose their spins during transmission. These findings highlight the complex and interesting behavior of wormhole graphene in the presence of external magnetic fields and suggest that these nano structures can have potential applications in electronic and spintronic devices.
Isolation of Streptomyces inhibiting multiple-phytopathogenic fungi and characterization of lucensomycin biosynthetic gene cluster
Authors: Park Heung-Soon , Kang Seung-Hoon , Choi Si-Sun , Kim Eung-Soo 
Published: April 2024

AbstractSoil microorganisms with diverse bioactive compounds such as Streptomyces are appreciated as valuable resources for the discovery of eco-friendly fungicides. This study isolated a novel Streptomyces from soil samples collected in the organic green tea fields in South Korea. The isolation process involved antifungal activity screening around 2400 culture extracts, revealing a strain designated as S. collinus Inha504 with remarkable antifungal activity against diverse phytopathogenic fungi. S. collinus Inha504 not only inhibited seven phytopathogenic fungi including Fusarium oxysporum and Aspergillus niger in bioassays and but also showed a control effect against F. oxysporum infected red pepper, strawberry, and tomato in the in vivo pot test. Genome mining of S. collinus Inha504 revealed the presence of the biosynthetic gene cluster (BGC) in the chromosome encoding a polyene macrolide which is highly homologous to the lucensomycin (LCM), a compound known for effective in crop disease control. Through genetic confirmation and bioassays, the antifungal activity of S. collinus Inha504 was attributed to the presence of LCM BGC in the chromosome. These results could serve as an effective strategy to select novel Streptomyces strains with valuable biological activity through bioassay-based screening and identify biosynthetic gene clusters responsible for the metabolites using genome mining approach.
Investigating the metabolite signature of an altered oral microbiota as a discriminant factor for multiple sclerosis: a pilot study
Authors: Boussamet Léo , Montassier Emmanuel , Mathé Camille , Garcia Alexandra , Morille Jérémy , Shah Sita , Dugast Emilie , Wiertlewski Sandrine , Gourdel Mathilde , Bang Corinna , Stürner Klarissa H. , Masson Damien , Nicot Arnaud B. , Vince Nicolas , Laplaud David-Axel , Feinstein Douglas L. , Berthelot Laureline 
Published: April 2024

AbstractIn multiple sclerosis (MS), alterations of the gut microbiota lead to inflammation. However, the role of other microbiomes in the body in MS has not been fully elucidated. In a pilot case-controlled study, we carried out simultaneous characterization of faecal and oral microbiota and conducted an in-depth analysis of bacterial alterations associated with MS. Using 16S rRNA sequencing and metabolic inference tools, we compared the oral/faecal microbiota and bacterial metabolism pathways in French MS patients (n = 14) and healthy volunteers (HV, n = 21). A classification model based on metabolite flux balance was established and validated in an independent German cohort (MS n = 12, HV n = 38). Our analysis revealed decreases in diversity indices and oral/faecal compartmentalization, the depletion of commensal bacteria (Aggregatibacter and Streptococcus in saliva and Coprobacter and Roseburia in faeces) and enrichment of inflammation-associated bacteria in MS patients (Leptotrichia and Fusobacterium in saliva and Enterobacteriaceae and Actinomyces in faeces). Several microbial pathways were also altered (the polyamine pathway and remodelling of bacterial surface antigens and energetic metabolism) while flux balance analysis revealed associated alterations in metabolite production in MS (nitrogen and nucleoside). Based on this analysis, we identified a specific oral metabolite signature in MS patients, that could discriminate MS patients from HV and rheumatoid arthritis patients. This signature allowed us to create and validate a discrimination model on an independent cohort, which reached a specificity of 92%. Overall, the oral and faecal microbiomes were altered in MS patients. This pilot study highlights the need to study the oral microbiota and oral health implications in patients with autoimmune diseases on a larger scale and suggests that knowledge of the salivary microbiome could help guide the identification of new pathogenic mechanisms associated with the microbiota in MS patients.
Nano-scaled polyacrylonitrile for industrialization of nanofibers with photoluminescence and microbicide performance
Authors: Emam Hossam E. , Hamouda Tamer , Emam El-Amir M. , Darwesh Osama M. , Ahmed Hanan B. 
Published: April 2024

AbstractNanofibers are investigated to be superiorly applicable in different purposes such as drug delivery systems, air filters, wound dressing, water filters, and tissue engineering. Herein, polyacrylonitrile (PAN) is thermally treated for autocatalytic cyclization, to give optically active PAN-nanopolymer, which is subsequently applicable for preparation of nanofibers through solution blow spinning. Whereas, solution blow spinning is identified as a process for production of nanofibers characterized with high porosity and large surface area from a minimum amounts of polymer solution. The as-prepared nanofibers were shown with excellent photoluminescence and microbicide performance. According to rheological properties, to obtain spinnable PAN-nanopolymer, PAN (12.5–15% wt/vol, honey like solution, 678–834 mPa s), thermal treatment for 2–4 h must be performed, whereas, time prolongation resulted in PAN-nanopolymer gelling or rubbering. Size distribution of PAN-nanopolymer (12.5% wt/vol) is estimated (68.8 ± 22.2 nm), to reflect its compatibility for the production of carbon nanofibers with size distribution of 300–400 nm. Spectral mapping data for the photoluminescent emission showed that, PAN-nanopolymer were exhibited with two intense peaks at 498 nm and 545 nm, to affirm their superiority for production of fluorescent nanofibers. The microbial reduction % was estimated for carbon nanofibers prepared from PAN-nanopolymer (12.5% wt/vol) to be 61.5%, 71.4% and 81.9%, against S. aureus, E. coli and C. albicans, respectively. So, the prepared florescent carbon nanofibers can be potentially applicable in anti-infective therapy.
Conditioned pain modulation (CPM) paradigm type affects its sensitivity as a biomarker of fibromyalgia
Authors: Gil-Ugidos A. , Vázquez-Millán A. , Samartin-Veiga N. , Carrillo-de-la-Peña M. T. 
Published: April 2024

AbstractFibromyalgia (FM) is a widespread chronic pain syndrome, possibly associated with the presence of central dysfunction in descending pain inhibition pathways. Conditioned Pain Modulation (CPM) has been proposed as a biomarker of FM. Nonetheless, the wide variety of methods used to measure CPM has hampered robust conclusions being reached. To clarify the validity of CPM as a biomarker of FM, we tested two CPM paradigms (parallel and sequential) in a sample of 23 female patients and 23 healthy women by applying test (mechanical) stimuli and conditioning (pressure cuff) stimuli. We evaluated whether CPM indices could correctly classify patients and controls, and we also determined the correlations between the indices and clinical variables such as symptomatology, disease impact, depression, quality of life, pain intensity, pain interference, fatigue and numbness. In addition, we compared the clinical status of CPM responders (efficient pain inhibitory mechanism) and non-responders. We observed that only parallel CPM testing correctly classified about 70% of patients with FM. In addition, more than 80% of healthy participants were found to be responders, while the rate was about 50% in the FM patients. The sequential CPM test was not as sensitive, with a decrease of up to 40% in the response rate for both groups. On the other hand, we did not observe any correlation between CPM measures and clinical symptoms. In summary, our findings demonstrate the influence of the CPM paradigm used and confirm that CPM may be a useful marker to complement FM diagnosis. However, the findings also cast doubts on the sensitivity of CPM as a marker of pain severity in FM.
Tuberculosis treatment outcomes and associated factors among tuberculosis patients treated at healthcare facilities of Motta Town, Northwest Ethiopia: a five-year retrospective study
Authors: Limenh Liknaw Workie , Kasahun Asmamaw Emagn , Sendekie Ashenafi Kibret , Seid Abdulwase Mohammed , Mitku Melese Legesse , Fenta Eneyew Talie , Melese Mihret , Workye Mulualem , Simegn Wudneh , Ayenew Wondim 
Published: April 2024

AbstractTuberculosis (TB) remains a significant public health concern, particularly in low-resource settings. The treatment outcome is a crucial indicator of the effectiveness of TB treatment programs. Assessing the current treatment outcome and its associated factors is essential for improving patient care and reducing the spread of TB. Therefore, this study aimed to assess TB treatment outcomes and their associated factors among TB patients who received treatment at public healthcare facilities in Motta Town, Northwest Ethiopia. A facility-based retrospective cross-sectional study design was employed in two TB treatment centers in Motta town from January 2017 to December 2021. The study participants were all patients diagnosed with TB who received treatment. A p-value of 0.05 with a 95% confidence interval (CI) was used to determine statistical significance. A total of 362 TB patients were included in the study. The overall treatment success rate was 88.4% (95% CI 85.1, 91.7). Male gender (AOR = 2.40, 95% CI 1.16, 4.98), normal nutritional status (AOR = 3.11, 95% CI 1.33, 7.25), HIV negative status (AOR = 3.35, 95% CI 1.31, 8.60), and non-presumptive drug resistance to TB (AOR = 3.72, 95% CI 1.74, 7.98) were significantly associated with successful TB treatment outcomes (p < 0.05). In the current study, nine out of ten study participants had successful TB treatment outcome rates. Male gender, normal nutritional status, non-presumed drug resistance to TB, and HIV-negative status were significantly associated with successful TB treatment outcomes. By taking risk factors associated with poor treatment outcomes like those found in this study into account, patient management and treatment can be optimized. Sufficient TB control measures for populations are imperative and could significantly reduce the nation's total TB burden.
Neuron-level explainable AI for Alzheimer’s Disease assessment from fundus images
Authors: Yousefzadeh Nooshin , Tran Charlie , Ramirez-Zamora Adolfo , Chen Jinghua , Fang Ruogu , Thai My T. 
Published: April 2024

AbstractAlzheimer’s Disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia. Early diagnosis is critical for patients to benefit from potential intervention and treatment. The retina has emerged as a plausible diagnostic site for AD detection owing to its anatomical connection with the brain. However, existing AI models for this purpose have yet to provide a rational explanation behind their decisions and have not been able to infer the stage of the disease’s progression. Along this direction, we propose a novel model-agnostic explainable-AI framework, called Granu$$\underline{la}$$

la

̲

r Neuron-le$$\underline{v}$$

v
̲

el Expl$$\underline{a}$$

a
̲

iner (LAVA), an interpretation prototype that probes into intermediate layers of the Convolutional Neural Network (CNN) models to directly assess the continuum of AD from the retinal imaging without the need for longitudinal or clinical evaluations. This innovative approach aims to validate retinal vasculature as a biomarker and diagnostic modality for evaluating Alzheimer’s Disease. Leveraged UK Biobank cognitive tests and vascular morphological features demonstrate significant promise and effectiveness of LAVA in identifying AD stages across the progression continuum.
Factors influencing smartphone overdependence among adolescents
Authors: Noh Dabok , Shim Mi-So 
Published: April 2024

AbstractAdolescents are particularly vulnerable to smartphone overdependence. Therefore, we identified the factors influencing smartphone overdependence and risk subgroups among adolescents. The current study is a secondary analysis of nationally representative data from the 2020 Korea Youth Risk Behavior Survey. The survey targeted middle- and high-school students in South Korea aged 12–18 using stratified, clustered, multistage probability sampling, and 53,457 students from 793 schools participated in this study. Complex sample data were analyzed considering the strata, clusters, and weights. Multiple logistic regression analysis revealed age, gender, household economic status, anxiety, loneliness, depressive symptoms, and experience of violent treatment as significant predictors of smartphone overdependence. Adolescents with severe anxiety were at a 3.326 times higher risk of smartphone overdependence than adolescents with minimal anxiety. Decision tree analysis showed that anxiety, gender, loneliness, and depressive symptoms were important in differentiating risk subgroups, with anxiety being the most significant factor. Group 13, comprising girls with severe anxiety, had the highest risk at 52.9%. Thus, early detection and prevention of issues such as anxiety, loneliness, and depressive symptoms, as well as treatment for violence, can prevent smartphone overdependence among adolescents. Additionally, more thorough interventions for anxiety are warranted to prevent smartphone overdependence.
Value of magnetic resonance angiography before prostatic artery embolization for intervention planning
Authors: Boschheidgen Matthias , Ullrich Tim , Al-Monajjed Rouvier , Ziayee Farid , Michalski Rene , Steuwe Andrea , Minko Peter , Albers Peter , Antoch Gerald , Schimmöller Lars 
Published: April 2024

AbstractKnowledge about anatomical details seems to facilitate the procedure and planning of prostatic artery embolization (PAE) in patients with symptomatic benign prostatic hyperplasia (BPS). The aim of our study was the pre-interventional visualization of the prostatic artery (PA) with MRA and the correlation of iliac elongation and bifurcation angles with technical success of PAE and technical parameters. MRA data of patients with PAE were analysed retrospectively regarding PA visibility, PA type, vessel elongation, and defined angles were correlated with intervention time, fluoroscopy time, dose area product (DAP), cumulative air kerma (CAK), contrast media (CM) dose and technical success of embolization. T-test, ANOVA, Pearson correlation, and Kruskal–Wallis test was applied for statistical analysis. Between April 2018 and March 2021, a total of 78 patients were included. MRA identified the PA origin in 126 of 147 cases (accuracy 86%). Vessel elongation affected time for catheterization of right PA (p = 0.02), fluoroscopy time (p = 0.05), and CM dose (p = 0.02) significantly. Moderate correlation was observed for iliac bifurcation angles with DAP (r = 0.30 left; r = 0.34 right; p = 0.01) and CAK (r = 0.32 left; r = 0.36 right; p = 0.01) on both sides. Comparing the first half and second half of patients, median intervention time (125 vs. 105 min.) and number of iliac CBCT could be reduced (p < 0.001). We conclude that MRA could depict exact pelvic artery configuration, identify PA origin, and might obviate iliac CBCT. Vessel elongation of pelvic arteries increased intervention time and contrast media dose while the PA origin had no significant influence on intervention time and/or technical success.
Methodological considerations for behavioral studies relying on response time outcomes through online crowdsourcing platforms
Authors: McConnell Patrick A. , Finetto Christian , Heise Kirstin-Friederike 
Published: April 2024

AbstractThis perspective paper explores challenges associated with online crowdsourced data collection, particularly focusing on longitudinal tasks with time-sensitive outcomes like response latencies. Based on our research, we identify two significant sources of bias: technical shortcomings such as low, variable frame rates, and human factors, contributing to high attrition rates. We explored potential solutions to these problems, such as enforcing hardware acceleration and defining study-specific frame rate thresholds, as well as pre-screening participants and monitoring hardware performance and task engagement over each experimental session. With this discussion, we intend to provide recommendations on how to improve the quality and reliability of data collected via online crowdsourced platforms and emphasize the need for researchers to be cognizant of potential pitfalls in online research.
Synthesis of N,N′-alkylidene bisamides and Suzuki–Miyaura coupling reaction derivatives with Pd organometallic catalyst anchored to channels of mesoporous silica MCM-41
Authors: Ibraheem Shelash Al-Hawary Sulieman , Saleh Raed Obaid , AlBajalan Ahmed Rafiq , Fayzullaev Normurot , Alshuhri Mohammed , Hayif Jasim Ali Saad , Alawadi Ahmed , Jawad Mohammed Abed , Alsaadi Salim B. , Ghorayshi Nejad Maryam Sadat 
Published: April 2024

AbstractAt first, an organometallic catalyst namely, Pd-DPyE@MCM-41@MNP was prepared through magnetic (Fe3O4) nanoparticles-doped into channels of mesoporous silica MCM-41 and then, anchoring a novel complex composed of di(4-pyridyl)ethylene and palladium on the inner surface of the support. This immobilized catalyst was successfully identified via VSM, ICP-OES, TEM, FTIR, TGA, SEM, BET, XRD, EDX and elemental mapping analyses. After that, it was used as a versatile, heterogeneous, and magnetically reproducible catalyst in the generation of N,N′-alkylidene bisamides (1a-13a, 8–20 min, 90–98%, 50 °C, solvent-free) and Suzuki–Miyaura coupling (SMC) reaction derivatives (1b-26b, 10–140 min, 86–98%, 60 °C, PEG-400). The VSM plot of Pd-DPyE@MCM-41@MNP displays that this nanocatalyst can be easily recycled by applying an external magnetic field. In both synthetic paths, this nanocatalyst was reused at least seven times without palladium leaching and significantly reducing its catalytic performance. Also, stability and heterogeneous nature of catalyst were approved via ICP-OES technique and hot filtration test.
Efficient DNA-based data storage using shortmer combinatorial encoding
Authors: Preuss Inbal , Rosenberg Michael , Yakhini Zohar , Anavy Leon 
Published: April 2024

AbstractData storage in DNA has recently emerged as a promising archival solution, offering space-efficient and long-lasting digital storage solutions. Recent studies suggest leveraging the inherent redundancy of synthesis and sequencing technologies by using composite DNA alphabets. A major challenge of this approach involves the noisy inference process, obstructing large composite alphabets. This paper introduces a novel approach for DNA-based data storage, offering, in some implementations, a 6.5-fold increase in logical density over standard DNA-based storage systems, with near-zero reconstruction error. Combinatorial DNA encoding uses a set of clearly distinguishable DNA shortmers to construct large combinatorial alphabets, where each letter consists of a subset of shortmers. We formally define various combinatorial encoding schemes and investigate their theoretical properties. These include information density and reconstruction probabilities, as well as required synthesis and sequencing multiplicities. We then propose an end-to-end design for a combinatorial DNA-based data storage system, including encoding schemes, two-dimensional (2D) error correction codes, and reconstruction algorithms, under different error regimes. We performed simulations and show, for example, that the use of 2D Reed-Solomon error correction has significantly improved reconstruction rates. We validated our approach by constructing two combinatorial sequences using Gibson assembly, imitating a 4-cycle combinatorial synthesis process. We confirmed the successful reconstruction, and established the robustness of our approach for different error types. Subsampling experiments supported the important role of sampling rate and its effect on the overall performance. Our work demonstrates the potential of combinatorial shortmer encoding for DNA-based data storage and describes some theoretical research questions and technical challenges. Combining combinatorial principles with error-correcting strategies, and investing in the development of DNA synthesis technologies that efficiently support combinatorial synthesis, can pave the way to efficient, error-resilient DNA-based storage solutions.
6-Gingerol attenuates hepatic ischemia/reperfusion injury through regulating MKP5-mediated P38/JNK pathway
Authors: Yu Qiwen , Li Jiye , Cui Mengwei , Mei Chaopeng , He Qianqian , Du Xiaoxiao 
Published: April 2024

Abstract6-Gingerol, the main bioactive compound of ginger, has antioxidant, anti-inflammatory, anti-cancer and neuroprotective effects. However, it is unclear whether 6-Gingerol has protective effects against hepatic ischemia/reperfusion (I/R) injury. In this study, the mouse liver I/R injury model and the mouse AML12 cell hypoxia/reoxygenation (H/R) model were established by pretreatment with 6-Gingerol at different concentrations to explore the potential effects of 6-Gingerol. Serum transaminase levels, liver necrotic area, cell viability, inflammatory response, and cell apoptosis were used to assess the effect of 6-Gingerol on hepatic I/R or cell H/R injury. Quantitative polymerase chain reaction (qPCR) and Western blotting were used to detect the mRNA and protein expression. The results show that 6-Gingerol decreased serum alanine aminotransferase (ALT), aspartate aminotransferase (AST) levels, liver necrosis, inflammatory cytokines IL-1β, IL-6, MCP-1, TNF-α expression, Ly6g+ inflammatory cell infiltration, protein phosphorylation of NF-κB signaling pathway, Terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) positive cells, cell apoptosis rate, the protein expression of pro-apoptotic protein BAX and C-Caspase3, increased cell viability, and expression of anti-apoptotic protein BCL-2. Moreover, 6-Gingerol could increase the mRNA and protein expression of mitogen activated protein kinase phosphatase 5 (MKP5) and inhibit the activation of P38/JNK signaling pathway. In MKP5 knockout (KO) mice, the protective effect of 6-gingerol and the inhibition of P38/JNK pathway were significantly weakened. Therefore, our results suggest that 6-Gingerol exerts anti-inflammatory and anti-apoptotic effects to attenuate hepatic I/R injury by regulating the MKP5-mediated P38/JNK signaling pathway.