bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of additional body weight QTLs in the Berlin Fat Mouse BFMI861 lines using time series data
Authors: Delpero Manuel , Korkuć Paula , Arends Danny , Brockmann Gudrun A. , Hesse Deike 
Published: March 2024

AbstractThe Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and metabolic syndrome. The sublines BFMI861-S1 and BFMI861-S2 differ in weight despite high genetic similarity and a shared obesity-related locus. This study focused on identifying additional body weight quantitative trait loci (QTLs) by analyzing weekly weight measurements in a male population of the advanced intercross line BFMI861-S1 x BFMI861-S2. QTL analysis, utilizing 200 selectively genotyped mice (GigaMUGA) and 197 males genotyped for top SNPs, revealed a genome-wide significant QTL on Chr 15 (68.46 to 81.40 Mb) for body weight between weeks 9 to 20. Notably, this QTL disappeared (weeks 21 to 23) and reappeared (weeks 24 and 25) coinciding with a diet change. Additionally, a significant body weight QTL on Chr 16 (3.89 to 22.79 Mb) was identified from weeks 6 to 25. Candidate genes, including Gpt, Cbx6, Apol6, Apol8, Sun2 (Chr 15) and Trap1, Rrn3, Mapk1 (Chr 16), were prioritized. This study unveiled two additional body weight QTLs, one of which is novel and responsive to diet changes. These findings illuminate genomic regions influencing weight in BFMI and emphasize the utility of time series data in uncovering novel genetic factors.
Impedance-based in vitro eye irritation testing enables the categorization of diluted chemicals
Authors: Weissinger H. , Knetzger N. , Cleve C. , Lotz C. 
Published: March 2024

AbstractProducts containing chemicals with eye irritation potential need to be labeled with the respective hazard symbol. To avoid the testing of numerous dilutions of chemicals on animals, their labeling is directed by a theoretical approach. In this report, a previously described in vitro tissue model of the cornea based on human epithelial cells was used for eye irritation testing of dilutions. As a sensitive and non-destructive method to analyze the barrier function of the epithelium, impedance spectroscopy was applied. Moreover, the morphology and viability of the epithelial models were assessed. We tested four chemicals that, neatly, cause severe damage to the eye: tetrahydrofuran, acetic acid, diethylethanolamine, and benzalkonium chloride. With our test method, we were able to determine the concentrations of the chemicals which are critical for the integrity of the cornea. The threshold was < 0.1% for the most and > 5% for the least toxic substance. The described test system is not only an alternative for animal models but also for the theoretical examination of the hazard potential of diluted chemicals. By using the advantages of tissue engineering and non-destructive analysis tools, we can achieve more precise and safer labeling of the eye irritation potential of products.
Dual ensemble system for polyp segmentation with submodels adaptive selection ensemble
Authors: Xu Cun , Fan Kefeng , Mo Wei , Cao Xuguang , Jiao Kaijie 
Published: March 2024

AbstractColonoscopy is one of the main methods to detect colon polyps, and its detection is widely used to prevent and diagnose colon cancer. With the rapid development of computer vision, deep learning-based semantic segmentation methods for colon polyps have been widely researched. However, the accuracy and stability of some methods in colon polyp segmentation tasks show potential for further improvement. In addition, the issue of selecting appropriate sub-models in ensemble learning for the colon polyp segmentation task still needs to be explored. In order to solve the above problems, we first implement the utilization of multi-complementary high-level semantic features through the Multi-Head Control Ensemble. Then, to solve the sub-model selection problem in training, we propose SDBH-PSO Ensemble for sub-model selection and optimization of ensemble weights for different datasets. The experiments were conducted on the public datasets CVC-ClinicDB, Kvasir, CVC-ColonDB, ETIS-LaribPolypDB and PolypGen. The results show that the DET-Former, constructed based on the Multi-Head Control Ensemble and the SDBH-PSO Ensemble, consistently provides improved accuracy across different datasets. Among them, the Multi-Head Control Ensemble demonstrated superior feature fusion capability in the experiments, and the SDBH-PSO Ensemble demonstrated excellent sub-model selection capability. The sub-model selection capabilities of the SDBH-PSO Ensemble will continue to have significant reference value and practical utility as deep learning networks evolve.
A multi-source molecular network representation model for protein–protein interactions prediction
Authors: Zou Hai-Tao , Ji Bo-Ya , Xie Xiao-Lan 
Published: March 2024

AbstractThe prediction of potential protein–protein interactions (PPIs) is a critical step in decoding diseases and understanding cellular mechanisms. Traditional biological experiments have identified plenty of potential PPIs in recent years, but this problem is still far from being solved. Hence, there is urgent to develop computational models with good performance and high efficiency to predict potential PPIs. In this study, we propose a multi-source molecular network representation learning model (called MultiPPIs) to predict potential protein–protein interactions. Specifically, we first extract the protein sequence features according to the physicochemical properties of amino acids by utilizing the auto covariance method. Second, a multi-source association network is constructed by integrating the known associations among miRNAs, proteins, lncRNAs, drugs, and diseases. The graph representation learning method, DeepWalk, is adopted to extract the multisource association information of proteins with other biomolecules. In this way, the known protein–protein interaction pairs can be represented as a concatenation of the protein sequence and the multi-source association features of proteins. Finally, the Random Forest classifier and corresponding optimal parameters are used for training and prediction. In the results, MultiPPIs obtains an average 86.03% prediction accuracy with 82.69% sensitivity at the AUC of 93.03% under five-fold cross-validation. The experimental results indicate that MultiPPIs has a good prediction performance and provides valuable insights into the field of potential protein–protein interactions prediction. MultiPPIs is free available at https://github.com/jiboyalab/multiPPIs.
Proposing TODD-graphene as a novel porous 2D carbon allotrope designed for superior lithium-ion battery efficiency
Authors: Santos E. A. J. , Lima K. A. L. , Ribeiro Junior L. A. 
Published: March 2024

AbstractThe category of 2D carbon allotropes has gained considerable interest due to its outstanding optoelectronic and mechanical characteristics, which are crucial for various device applications, including energy storage. This study uses density functional theory calculations, ab initio molecular dynamics (AIMD), and classical reactive molecular dynamics (MD) simulations to introduce TODD-Graphene, an innovative 2D planar carbon allotrope with a distinctive porous arrangement comprising 3-8-10-12 carbon rings. TODD-G exhibits intrinsic metallic properties with a low formation energy and stability in thermal and mechanical behavior. Calculations indicate a substantial theoretical capacity for adsorbing Li atoms, revealing a low average diffusion barrier of 0.83 eV. The metallic framework boasts excellent conductivity and positioning TODD-G as an active layer for superior lithium-ion battery efficiency. Charge carrier mobility calculations for electrons and holes in TODD-G surpass those of graphene. Classical reactive MD simulation results affirm its structural integrity, maintaining stability without bond reconstructions at 2200 K.
Study on the impact of digital transformation on the innovation potential based on evidence from Chinese listed companies
Authors: Zhao Xu , Chen Qi-an , Yuan Xiaoshu , Yu Yannan , Zhang Haitao 
Published: March 2024

AbstractDigital transformation has emerged as a powerful force in reshaping the business landscape and enabling organizations to enhance their capabilities. One critical aspect of this change is how it impacts an enterprise’s innovation ability. To explore this question, we select data regarding China’s A-share listed enterprises from 2007 to 2021 as the research sample. We employ crawler technology to gather keywords related to “digital transformation” from annual reports, portraying detailed journeys of enterprises’ digital transformation. Through descriptive statistics and multiple covariance tests, a linear relationship is established between digital transformation and innovation ability. Benchmark regression is conducted and a robustness test is utilized to determine the robustness of the benchmark regression. The mechanism, heterogeneity, and moderating effects of this study are also tested. The results reveal that digital transformation makes a significant positive contribution to the innovation capability of enterprises. Meanwhile, among different types of enterprises, the impact of digital transformation on enterprise innovation capability shows heterogeneity. In terms of the impact mechanism, digital transformation can enhance the innovation output of enterprises by reducing the agency cost and improving the risk-taking level of enterprises, so as to further improve the innovation capability of enterprises. The research results of this paper provide essential theoretical support for the digital transformation of enterprises and the government’s formulation of enterprises’ digitalization strategies. More profoundly, it provides significant reference for how to further promote the digital transformation of Chinese enterprises.
Fruit encasing preserves the dispersal potential and viability of stranded Posidonia oceanica seeds
Authors: Sutera Alberto , Bonaviri Chiara , Spinelli Patrizia , Carimi Francesco , De Michele Roberto 
Published: March 2024

AbstractPosidonia oceanica meadows are the most productive coastal ecosystem in the Mediterranean. Posidonia oceanica seeds are enclosed in buoyant fleshy fruits that allow dispersal. Many fruits eventually strand on beaches, imposing a remarkable energy cost for the plant. This study aims to assess whether stranded seeds retain functional reproductive potential under a variety of environmental conditions. First, we measured the possibility that seeds could be returned to the sea, by tagging fruits and seeds. Second, we quantified the effect of air, sun and heat exposure on the viability and fitness of stranded fruits and naked seeds. The results showed that on average more than half of fruits and seeds are returned to the sea after stranding events and that fruits significantly protect from desiccation and loss of viability. Furthermore, in fruits exposed to the sun and in naked seeds, seedlings development was slower. This study indicates that a significant portion of stranded P. oceanica fruits have a second chance to recruit and develop into young seedlings, relieving the paradox of large energy investment in seed production and apparent low recruitment rate. Additionally, we provide practical indications for seed collection aimed at maximizing seedling production, useful in meadow restoration campaigns.
Multiscale in-situ characterization of static recrystallization using dark-field X-ray microscopy and high-resolution X-ray diffraction
Authors: Lee Sangwon , Berman Tracy D. , Yildirim Can , Detlefs Carsten , Allison John E. , Bucsek Ashley 
Published: March 2024

AbstractDark-field X-ray microscopy (DFXM) is a high-resolution, X-ray-based diffraction microstructure imaging technique that uses an objective lens aligned with the diffracted beam to magnify a single Bragg reflection. DFXM can be used to spatially resolve local variations in elastic strain and orientation inside embedded crystals with high spatial (~ 60 nm) and angular (~ 0.001°) resolution. However, as with many high-resolution imaging techniques, there is a trade-off between resolution and field of view, and it is often desirable to enrich DFXM observations by combining it with a larger field-of-view technique. Here, we combine DFXM with high-resolution X-ray diffraction (HR-XRD) applied to an in-situ investigation of static recrystallization in an 80% hot-compressed Mg–3.2Zn–0.1Ca wt.% (ZX30) alloy. Using HR-XRD, we track the relative grain volume of > 8000 sub-surface grains during annealing in situ. Then, at several points during the annealing process, we “zoom in” to individual grains using DFXM. This combination of HR-XRD and DFXM enables multiscale characterization, used here to study why particular grains grow to consume a large volume fraction of the annealed microstructure. This technique pairing is particularly useful for small and/or highly deformed grains that are often difficult to resolve using more standard diffraction microstructure imaging techniques.
Genome-wide analysis of the C2H2-ZFP gene family in Stevia rebaudiana reveals involvement in abiotic stress response
Authors: Nikraftar Shahla , Ebrahimzadegan Rahman , Majdi Mohammad , Mirzaghaderi Ghader 
Published: March 2024

AbstractStevia (Stevia rebaudiana Bertoni) is a natural sweetener plant that accumulates highly sweet steviol glycosides (SGs) especially in leaves. Stevia is native to humid areas and does not have a high tolerance to drought which is the most serious abiotic stress restricting its production worldwide. C2H2 zinc finger proteins (C2H2-ZFPs) are a group of well-known transcription factors that involves in various developmental, physiological and biochemical activities as well as in response to abiotic stresses. Here we analyzed C2H2-ZFP gene family in stevia and identified a total of 185 putative SrC2H2-ZF proteins from the genome sequence of S. rebaudiana. We further characterized the identified C2H2-ZF domains and their organization, additional domains and motifs and analyzed their physicochemical properties, localization and gene expression patterns. The cis-element analysis suggested multiple roles of SrC2H2-ZFPs in response to light, phytohormone, and abiotic stresses. In silico analysis revealed that the stevia C2H2-ZFP genes are interactively expressed in different tissues and developmental stages and some C2H2-ZFP genes are involved in response to drought stress. This study provides a background for future exploration of the functional, and regulatory aspects of the C2H2-ZFP gene family in S. rebaudiana.
Fish oil ameliorates ethanol-induced gastric injury in rat by modulating gene related to apoptosis
Authors: Parham Nikoo , Rahimi Kaveh , Ghotbeddin Zohreh , Tabandeh Mohammad Reza 
Published: March 2024

AbstractGastric ulcers are a type of digestive disease that can severely affect a person's quality of life. Our study aimed to investigate the effects of fish oil on ethanol-induced gastric ulcers in rats, with the purpose of providing more comprehensive information on the topic. The study looked at various factors such as gastric ulcer index, and nitric oxide (NO) levels in stomach tissue. To investigate apoptosis, the mRNA levels of Bax, Bcl-2, and Caspase 3 were analyzed. The results showed that fish oil can reduce gastric acidity and the gastric ulcer index in cases of ethanol-induced gastric ulcers. It was found that fish oil can increase NO levels and improve the anti-apoptotic system by increasing the expression of Bcl-2 while decreasing the expression of Bax and Caspase 3. In general, the study demonstrates that fish oil can protect the stomach from ethanol-induced damage by reducing the apoptosis pathway via nitric oxide.
Distribution of H2S in the 10103 excavation working face of the Baozigou coal mine
Authors: Jia Niujun , Jia Baoshan , Yan Jingxue , Zhang Jinyi 
Published: March 2024

AbstractBased on the production conditions of the 10103 excavation working face of the Baozigou coal mine, this paper analyzes the potential sources of H2S and the expected emission concentrations of H2S in the working face. Considering the previous engineering practice for controlling H2S disasters in coal mine working faces, numerical simulations were conducted to investigate air flow and H2S migration and diffusion in the tunnel in the excavation working face. The migration and distribution of H2S in the coal seam mining face were studied, and the effects of outlet wind speed, duct location, and duct diameter on the H2S concentration distribution were explored. The higher the outlet wind speed, the more conducive to the emission of H2S gas, but too high a wind speed will be detrimental to the concentrated extraction and purification absorption of H2S; the closer the outlet position of the air duct is to the end of the working surface, the lower the H2S concentration in the vortex area at the corner; the air duct If the diameter is too small, the harmful gases released from hard-to-break coal cannot be entrained and taken away. When the diameter of the air duct is too large, the entrainment volume during the jet process will be expanded. To verify the field distribution of H2S concentration at the bottom, middle, and top of the boring machine, a CD4-type portable H2S instrument was used to analyze the distribution of H2S near the excavation working face.
Deprescribing potential of commonly used medications among community-dwelling older adults: insights from a pharmacist’s geriatric assessment
Authors: Bužančić Iva , Držaić Margita , Kummer Ingrid , Ortner Hadžiabdić Maja , Brkić Jovana , Fialová Daniela 
Published: March 2024

AbstractPharmacist’s geriatric assessment can provide valuable insights into potential deprescribing targets, while including important information on various health-related domains. Data collected from a geriatric assessment questionnaire, for 388 patients, from the Croatian cohort of the EuroAgeism H2020 ESR 7 international project, along with guideline-based deprescribing criteria, were used to analyse potentially inappropriate prescribing of four medication groups (benzodiazepines (BZN), proton pump inhibitors (PPI), opioids, and non-steroidal anti-inflammatory drugs (NSAID)), and to assess the deprescribing potential. Binary logistic regression was used to explore the effects of age, gender, number of medicines and diagnoses, self-reported health, frailty score, and healthcare utilization on the likelihood of needing deprescribing. More than half of participants (n = 216, 55.2%) are candidates for deprescribing, with 31.1% of PPI, 74.8% of NSAID, 75% of opioid, and 96.1% of BZN users meeting at least one criterion. Most common criteria for deprescribing were inappropriately long use and safety concerns. Women (aOR = 2.58; p < 0.001), those reporting poor self-reported health (aOR = 5.14; p < 0.001), and those exposed to polypharmacy (aOR = 1.29; p < 0.001) had higher odds of needing to have medicines deprescribed. The high rate of deprescribing potential warrants prompt action to increase patient safety and decrease polypharmacy. Pharmacist’s geriatric assessment and deprescribing-focused medication review could be used to lead a personalised approach.
Gestational diabetes mellitus, hypertension, and dyslipidemia as the risk factors of preeclampsia
Authors: Aziz Farah , Khan Mohammad Fareed , Moiz Amna 
Published: March 2024

AbstractGestational diabetes mellitus (GDM) is a known risk factor for gestational hypertension which further progress toward conditions like proteinuria, dyslipidemia, thrombocytopenia, pulmonary edema leading to Preeclampsia (PE). Pregnancy can be a challenging time for many women, especially those diagnosed with GDM and PE. Thus, the current prospective study investigates the association of OGTT glucose levels with systolic and diastolic blood pressure and lipid profile parameters in pregnant women diagnosed with GDM and PE. A total of 140 pregnant women were stratified into GDM (n = 50), PE (n = 40) and controls (n = 50). Two hour 75 g oral glucose tolerance test (OGTT) was performed for screening GDM. Biochemical parameters analysis of OGTT, total cholesterol (TC), triglyceride (Tg), high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), urinary albumin and creatinine were tested to find urinary albumin creatinine ratio (uACR). Statistical analysis was performed using ANOVA followed by post hoc test and regression analysis. Among the studied groups, GDM and PE groups showed no significant difference in age and increased BMI. Increased 2 h OGTT & TC in GDM group; elevated uACR, systolic/diastolic blood pressure, Tg, HDL-C, LDL-C in PE group was observed and differ significantly (p < 0.0001) with other groups. A significant positive effect of 2 h OGTT was observed on blood pressure (R2: GDM = 0.85, PE = 0.71) and lipid profile determinants (R2: GDM = 0.85, PE = 0.33) at p < 0.0001. The current study concludes that glucose intolerance during the later weeks of pregnancy is associated with gestational hypertension and hyperlipidemia as a risk factor for PE. Further research is needed for a detailed assessment of maternal glucose metabolism at various pregnancy stages, including the use of more sensitive markers such as C-peptide and their relation to pregnancy-related hypertensive disorders.
Ultra-high throughput-based screening for the discovery of antiplatelet drugs affecting receptor dependent calcium signaling dynamics
Authors: Fernández Delia I. , Troitiño Sara , Sobota Vladimír , Tullemans Bibian M. E. , Zou Jinmi , van den Hurk Helma , García Ángel , Honarnejad Saman , Kuijpers Marijke J. E. , Heemskerk Johan W. M. 
Published: March 2024

AbstractDistinct platelet activation patterns are elicited by the tyrosine kinase-linked collagen receptor glycoprotein VI (GPVI) and the G-protein coupled protease-activated receptors (PAR1/4) for thrombin. This is reflected in the different platelet Ca2+ responses induced by the GPVI agonist collagen-related peptide (CRP) and the PAR1/4 agonist thrombin. Using a 96 well-plate assay with human Calcium-6-loaded platelets and a panel of 22 pharmacological inhibitors, we assessed the cytosolic Ca2+ signaling domains of these receptors and developed an automated Ca2+ curve algorithm. The algorithm was used to evaluate an ultra-high throughput (UHT) based screening of 16,635 chemically diverse small molecules with orally active physicochemical properties for effects on platelets stimulated with CRP or thrombin. Stringent agonist-specific selection criteria resulted in the identification of 151 drug-like molecules, of which three hit compounds were further characterized. The dibenzyl formamide derivative ANO61 selectively modulated thrombin-induced Ca2+ responses, whereas the aromatic sulfonyl imidazole AF299 and the phenothiazine ethopropazine affected CRP-induced responses. Platelet functional assays confirmed selectivity of these hits. Ethopropazine retained its inhibitory potential in the presence of plasma, and suppressed collagen-dependent thrombus buildup at arterial shear rate. In conclusion, targeting of platelet Ca2+ signaling dynamics in a screening campaign has the potential of identifying novel platelet-inhibiting molecules.