bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leaching Experiments to Delineate Factors Governing Rock–water Interactions: Case of the North- Western Part of the Volta River Basin of Ghana
Authors: Lartsey Priscilla Esinu Selase 
Published: October 2023

Abstract
Leaching experiments were carried out on five silicate rock samples from the various geological units of the North-Western part of the Volta River Basin of Ghana. Four experimental conditions were tested: (1) room temperature experiments opened to only atmospheric conditions, (2) at a temperature of 50ºC, (3) experiment saturated with CO2 gas and (4) in acid environment (HNO3 & H2SO4). The aim of this study was to investigate the effects of these conditions on rock-water interactions that influence groundwater chemistry in the study area. Mineralogical composition of rocks analyzed prior to the experiment, through petrographic microscope and X-ray Diffraction (XRD) revealed that rocks are composed of Quartz, Albite, K-Feldspar, Ca- Amphibole, Epidote, Biotite, Chlorite and Muscovite, which are typical silicate minerals. Electrical Conductivity (EC) and pH of leachates measured periodically to monitor reaction progress, revealed that the variations of these parameters were influenced by the mineralogical composition of the rocks, reaction time and experimental conditions. The chemical facies of lixiviate samples from the environment saturated in CO2 at 1 bar were consistent with groundwater chemistry from the study area, corroborating the importance of CO2 gas on rock-water interactions. Mass balance calculations carried out on leachates from experiments saturated with CO2 revealed that major cation chemistry were largely a result of the dissolution of Albite, K-Feldspar, Biotite, Ca-Amphibole and Biotite.
Genotype by environment and genotype by yield*trait interactions in sugar beet: Analyzing yield stability and determining key traits association
Authors: Hassani Mahdi , Mahmoudi Seyed Bagher , Saremirad Ali , Taleghani Dariush 
Published: October 2023

Abstract
The GEI significantly influences plant yield, making it imperative to understand its nature for the creation of breeding programs to enhance crop production. However, this is not the only obstacle in the yield improvement process. Breeders also face the significant challenge of unfavorable and negative correlations among key traits. In this study, the stability of RY and WSY, and the association between the key traits of RY, SC, N, Na+, and K+ were examined in 20 sugar beet genotypes. The study was conducted using a randomized complete block design with four replications over two consecutive years across five locations. The combined analysis of variance results revealed significant main effects of year, location, and genotype on both RY and WSY. Notably, two-way and three-way interactions between these main effects on RY and WSY resulted in a significant difference. The AMMI method was used to analyze the GEI. The analysis revealed that the first five IPCs significantly impacted both the RY and WSY. The LMM results for RY and WSY indicated that the genotype effect and the GEI were significant. The WAASB biplot demonstrated that genotypes 20, 4, 7, 2, 16, 3, 6, 1, 14, and 15 were superior in terms of RY. For WSY, genotypes 4, 16, 3, 7, 5, 1, 10, 20, 2, and 6 stood out. These genotypes were not only stable but also had a yield value higher than the total average. According to the WAASBY, genotypes 16, 20, 2, and 14 exhibited high stability and RY. In terms of WSY and stability, genotypes 20, 3, 16, 4, and 10 were identified as the most suitable.
SSR marker based molecular diversity among advanced breeding lines of Katarni rice (Oryza sativa. L.) and validation of phenotypic selection through functional markers
Authors: Parveen Rabiya , Kumar Mankesh , Kashyap Neha , Imam Zafar , . Satyendra , Ranjan Tushar , Singh P K , Singh S P 
Published: October 2023

Abstract

Like Basmati, Katarni is a traditional aromatic rice cultivar grown primarily in its geographical indicated areas i.e. Bhagalpur, Banka and Munger districts of Bihar, India. However, known for exquisite grain quality characteristics, it suffers from lodging problem, and is very late maturing leading tolow productivity, constant decrease in acreage and farmer preference. Introgression of the semi-dwarfing gene (sd1) in Katarni was performed through marker assisted backcross breeding and advanced to obtain the homogeneous population. The derived lines were analyzed for the presence of genes for semi-dwarfism (sd1), aroma (badh2), flowering date (Hd3a) and kernel length (GS3) using functional markers. Improved lines of Katarni rice were found positive for sd1 gene in PCR and most of the entries simultaneously contained genes for short grain type, thus implicating the applicability of these markers in marker-assisted backcross breeding. Twenty three advanced breeding lines of Katarni were phenotypically evaluated for target traits viz., plant height, days to 50% flowering, grain length, grain width and leaf aroma through sensory test alongwith their parental checks. Molecular profiling of the entries was carried out to develop DNA fingerprint using 81 SSR markers which were found to be highly informative and capable of distinguishing between genotypes. The PIC value was highest for marker RM15189 and RM182. The genetic distance detected through UPGMA clustering indicated five distinct groups, and maximum degree of similarity was observed between lines namely, ASGL11 and ASGL12 followed by ASGL9 and ASGL11. Except Hd3A, the molecular profiling through functional markers were also in congruity with the morphological data.
Tropheryma whipplei detection by metagenomic next-generation sequencing in bronchoalveolar lavage fluid
Authors: lai lan min , zhu yu , zhao rui , chen qiang , Liu Jiao Jiao , Liu Yang , Yuan Lei 
Published: October 2023

Abstract
Background: Whipple's disease is a chronic systemic infectious disease that mainly affects the gastrointestinal tract. Tropheryma whipplei is common in healthy individuals, but in some cases, Tropheryma whipplei can cause infection at the implant site or even throughout the body. The delay between the first clinical symptoms and diagnosis of Whipple's disease and Whipple's trophoblast infection exceeds 6 years, and recurrence is often observed. Therefore, clinical doctors need to understand the characteristics of this infection.
Methods: We collected blood, sputum, and alveolar lavage fluid samples from all patients with Tropheryma whipplei from 2020 to 2022, and retrospectively analyzed the clinical data of Sample with Tropheryma whipplei. Patient's past history, clinical manifestations, laboratory examinations, chest CT findings, treatment, and prognosis were recorded.
Results: 16 BALFs (70/1725, 4.0%) from 16 patients were positive for Tropheryma whipplei. 8 patients were male with an average age of 50 years. The main clinical symptoms of patients included fever (9/16), cough (7/16), dyspnea(7/16), and Expectoration(5/16), but neurological symptoms and arthralgia and were rare. Cardiovascular and cerebrovascular diseases were the most common comorbidity (n=8).The main laboratory characteristics of the patient are red blood cell count, hemoglobin, total protein and albumin below normal levels(11/16) , and/or creatinine above normal levels(14/16). Most chest computer tomography manifestations include focal or patchy heterogeneous infection (n=5) and pleural effusion (n=8). Among the 6 samples, Tropheryma whipplei was the sole agent, and Klebsiella pneumoniae was the most common detected other pathogens.
Conclusions: Metagenomic next-generation sequencing technology has improved the detection rate and attention of Tropheryma whipplei. Further research is needed to distinguish whether Tropheryma whipplei present in respiratory samples is a pathogen or an innocent bystander.
Antimicrobial Resistant Pattern of Klebsiella pneumoniae Isolated from the Stool of Healthy Volunteers of Niger Delta University, Wilberforce Island, Amassoma, Bayelsa State
Authors: Germany Precious W. , Bunu Samuel J. , Adebola Onanuga A. 
Published: October 2023

Abstract
Background
Klebsiella pneumoniae bacteria is a normal flora of the human intestinal tract where they do not cause disease in normal circumstances but can also act as a human opportunistic pathogenic infection when it proliferates in increased amounts, where it may cause a host of health complaints and symptoms ranging from mild to serious infections (pneumonia, septicemia, Urinary tract infections). The virulence factors like capsule, lipopolysaccharide, and type 1 or type 3 fimbriae are responsible for K. pneumoniae to form biofilm. Klebsiella pneumonia responsible for serious outbreaks of multi-drug resistant diseases may be due to uncontrolled usage of antibiotics.
Method
The samples were isolated and identified using standard microbiological methods. The isolates were screened for possible virulence traits using the Blood agar test and Congo-Red test. Antibiotic susceptibility screening was carried out for the isolates.
Results
In this study (25.3%) Klebsiella pneumoniae isolates were recovered from the 300 stool samples of the healthy student volunteers, of which 29(38.2%) were from males and 47(61.8%) from females. The 76 Klebsiella pneumoniae isolates screened are biofilm producers while none produced hemolysin. The antimicrobial susceptibility pattern for the 76 Klebsiella pneumoniae isolates in this study revealed (Co-trimoxazole 3.9%, Ciprofloxacin 11.8%, Cefotaxime 9.2%, Ceftazidime 6.6% and Gentamicin 9.2%, Imipenem 17.1% and Ertapenem 40.8% and Nitrofurantoin (89.5%). In this study (17.1%) Klebsiella pneumoniae isolates exhibited multi-drug resistance.
Conclusion
Drug resistance surveillance has revealed that asymptomatic carriers in the community are often colonized with resistant bacteria that subsequently lead to infections.
The Antibacterial Activity and Mechanism of Emilia Sonchifolia Against Methicillin Resistant Staphylococcus Epidermidis
Authors: Liu Xin , An Lili , Wang Xuebing , yufeng Fu , Zhou Yonghui , Peng Wei 
Published: October 2023

Abstract
Background: Bloodstream infections (BSIs) are a public health concern and cause substantial morbidity and mortality.The pathogen Staphylococcus epidermidis causes a significant number of BSIs. Antibiotics targeting Staphylococcus epidermidis have been the mainstay in BSIs. However, Conventional antibiotics have been eclipsed in combating with drug-resistant bacteria. Alternate ways of treating these antibiotic-resistant infections are thus urgently needed. Numerous studies have demonstrated that certain Chinese medicines exhibit notable antimicrobial activity and possess the ability to impede the development of bacterial resistance. Based on an extensive body of research in the field of traditional Chinese medicine(TCM), it has been determined that the Compositae plant exhibits a noteworthy anti-Methicillin-Resistant Staphylococcus Epidermidis (MRSE) effect.
Methods: Initially, the Compositae plant Emilia sonchifolia underwent a screening process, followed by crushing and extraction using water. Subsequently, the extract was concentrated based on a specific ratio, dried, partitioned, and subsequently prepared for utilization.Therefore, the objective of this study was to examine the antibacterial efficacy and underlying antibacterial mechanism of Emilia sonchifolia against methicillin-resistant Staphylococcus epidermidis( MRSE). The antibacterial activity of Emilia sonchifolia against MRSE was assessed through in vitro tests measuring minimum inhibitory concentration(MIC) and minimum bactericidal concentration(MBC). Furthermore, the antibacterial activity of Emilia sonchifolia against MRSE was evaluated in vivo using a mouse bloodstream infections model. Additionally, various aspects such as bacteria cell morphology and energy metabolism and defense mechanisms were investigated to explore the underlying antibacterial mechanisms of Emilia sonchifolia.
Results: The results showed that MIC and MBC values of Emilia sonchifolia against MRSE were 5mg/mL and 20mg/mL, respectively. Meanwhile, Emilia sonchifolia can effectively treat MRSE induced bloodstream infections. Furthermore, the utilization of scanning electron microscopy and transmission electron microscopy techniques unveiled that the administration of Emilia sonchifolia induced alterations in the cellular structure of MRSE, leading to the disruption of both cell wall and membrane integrity. Additionally, exposure to Emilia sonchifolia resulted in a decrease in the enzymatic activities of succinate dehydrogenase, NADP-malate dehydrogenase, catalase, and superoxide dismutase.
Conclusions: Thus, the aforementioned observations have contributed novel insights into the mechanistic understanding of Emilia sonchifolia's efficacy against MRSE, thereby offering potential strategies for managing MRSE infections.
Half dome carbon nitride nanostructures
Authors: Torre Alessandro La 
Published: October 2023

Abstract
We report on a new form of nanoscale carbon nitride in the shape of single layer half dome structures grown on the step edges of boron nitride sheets. The half dome structures are formed spontaneously at high temperature in high vacuum using Fe2O3 capped with N(CH3)4OH supported on BN sheets. During the combustion process the BN support, firstly, acted as a reducing agent for the transformation of the iron oxide in metallic iron, secondly, as a source of nitrogen that permitted the transformation of the organic capping agent in sp1 CN chains linked with sp2 CN domains. During the Ostwald ripening processes smaller nanoparticles migrates towards bigger nanoparticle, when the nanoparticles come across the step edges of few layer boron nitrides sheets the half dome structure is formed. The propensity of FeNPs to catalyse the formation of the half dome containing cyanopolyynes species has been shown for the first time. The coexistence of carbon nitride atoms in two well-defined hybridization states within the CN@HDS may offer functional features characteristic of carbyne and carbon nitride.
Genome-wide Systematic Survey and Analysis of the RNA Helicase Gene Family and their Response to Abiotic Stress in Sweetpotato
Authors: Mu mufangfang , Zheng Hao , Zhao Qiaorui , Zhu Mingku , Dong Tingting , Kai Lei , Li Zongyun 
Published: October 2023

Abstract
RNA helicase is a large family that plays a significant role in plant evolution and in the abiotic stress response. Sweetpotato is one of the majority essential foods in the world, and their yields are often contrived by environmental stresses. Previously, the RNA helicase gene family has not been described in sweetpotato, hence we went a comprehensive genome-wide examination of the sweetpotato RNA helicase family, containing chromosome distribution, promoter elements, and motif compositions. All of 300 RNA helicase genes were divided into three subfamilies, including IbDEAD, IbDEAH and IbDExDH, and they are unevenly scattered across 15 chromosomes of the sweetpotato. Furthermore, tandem replication and segmental replication events played a key role in the amplification of sweetpotato RNA helicase genes. The collinear relationship amidst sweetpotato RNA helicase genes and 8 other related homologous genes in plants was deeply explored, which supplied a reliable basis for studying the development of sweetpotato RNA helicase gene family. RNA-seq examination and qRT-PCR recognition showed that the expression of eight RNA helicase genes was significantly diverse under four abiotic stresses (cold, drought, heat, salt). At the same time, the expression of these RNA helicases in different tissues of the 10 sweetpotato varieties also differed significantly. The promoters of the RNA helicase genes contain a great deal of cis-acting elements related to temperature, hormone and light response. The results indicated that sweetpotato RNA helicase genes played a key role in development or the abiotic stress response.
ECG-Based Arrhythmia Detection by A Shallow CNN Model
Authors: rasti tara , zhu quanmin 
Published: October 2023

Abstract
Recent advances in biomedical applications have focused a lot of emphasis on the detection of which could be caused by cardiovascular disease (CVD) The electrocardiogram (ECG), which depicts the electrical activity of the heart, is the foundation for arrhythmia analysis. Different machine learning methods used on ECG datasets have demonstrated excellent performance in detecting arrhythmias. Nevertheless, feature extraction is necessary for machine learning algorithms. Modern deep learning techniques don't require feature extraction because they learn all the parameters simultaneously, in contrast to these techniques. In this study, a 1D CNN approach is presented and tested on the arrhythmia database of the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH). The proposed model, which only has three layers, attained an accuracy of 97.40%.
Study on morphology reconstruction of SiC ceramics ground by monolayer patterned grinding wheel considering strain-rate effect
Authors: Zhu Yejun , Hou Zhiheng , Huang Zixuan , Li Benkai , Zhang Zhaoqin , Xu Jiaxuan , Ding Wenfeng 
Published: October 2023

Abstract
For the purpose of optimizing grinding wheel profiles and grinding parameters, the prediction of the morphology of the grinding workpiece is essential. In this study, a new simulation model is developed to forecast the grinding workpiece surface morphology of ceramic material while accounting for the strain-rate effect. The effects of grinding parameters and patterned grinding wheel characteristics (e.g., grain geometry, grain size, grain protrusion height, and grain placement) on the surface and subsurface damage are explored. The results show that the simulation findings agree well with the theoretical approach, which takes the strain-rate impact into account. Additionally, the magnitude of the change in surface roughness increases as the properties of the patterned grinding wheel grow, whereas the magnitude of the change in surface roughness reduces as the grinding parameters increase. Furthermore, the grinding parameters have a greater impact on subsurface damage than the patterned grinding wheel options.
Advancing Urban Health Assessment through Generative AI-Driven Indicators: GCR Case Study
Authors: Bakir Rasha Ahmed , Attia Sahar Abdel Moneim 
Published: October 2023

Abstract
The nexus between urban environment and health has been firmly established by the research community. Despite recognition of the importance of well-being and health within the urban context, and the existence of over 145 indices related to health that have been developed within this realm. A noticeable gap exists in the Egyptian context, marked by the absence of an established urban health index framework. This issue underscores the pressing need for the development of a standardized cohesive set of urban health indicators tailored to the Egyptian urban environment. Furthermore, the fast-paced nature of contemporary life increased reliance on Artificial Intelligence (AI) technology. In this context, the present investigation delves into the employment of AI in the derivation of urban health indicators, aiming to comprehensively assess health within the urban context. The adopted methodology integrates AI-language tools, survey mechanisms, and statistics to formulate and validate an AI-derived index. This study aims to examine the reliability and validity of indicators developed by AI for assessing the health of urban environments. The study initially incorporated 78 indicators derived from four distinct AI-tools, which were then evaluated through an online survey targeting urban experts. This evaluative process culminated in the identification of 34 indicators that exhibited robustness and aptitude for inclusion in the refined index. The study additionally demonstrated that agreement with AI-derived index varied depending on gender, professional role, and years of experience. This study underscores potential for AI-driven methodologies to inform urban planners, policymakers, and decision-makers about creation of healthier, more sustainable, and resilient cities.
Interpretable Machine Learning for Early Prediction of Multidrug-Resistant Organism Infection：A Discovery and Validation Study
Authors: Sun Pei , Zhao Wenting , Wen Jinqi , Yang Yuanhui , Guo Wei , Shang Linping 
Published: October 2023

Abstract
Background Multidrug-resistant organisms (MDRO) infection is a major public health threat in the world. We aim to predict risk of MDRO infections in Intensive Care Unit (ICU) patients by developing and validating a machine learning (ML) model.Methods This study included patients in the ICU from January 1, 2020 to December 31, 2022, and retrospectively analyzed the clinical characteristics of the patients. Lasso regression was used for feature selection. We use 6 machine learning methods to analyze clinical features and build prediction models. Furthermore, we illustrate the effects of the features attributed to the model and interpret the prediction process based on the SHapley Additive exPlanation(SHAP).Results A total of 888 cases were collected, 63 cases were excluded based on inclusion and exclusion criteria, and 825 final cases were included in the analysis, of which 375 were MDRO-infected patients. A total of 45 clinical variables were collected, and after selection, 31 variables were associated with outcomes and were used to develop machine learning models. We have build six ML models to predict MDRO infections, among which, the Random Forest (RF) model performs the best with an AUC of 0.83 and an accuracy of 0.767.Conclusions We built and validated an ML model for predicting patients who will develop MDRO infections, and the SHAP improves the interpretability of machine learning models and helps clinicians better understand the mechanisms behind the results. The model can provide guidance to ICU healthcare professionals in the prevention and control of patients at high risk of infection.
α7nAChR Activation Combined with Endothelial Progenitor Cell Transplantation Attenuates Lung Injury in Diabetic Rats with Sepsis through the NF-κB Pathway
Authors: Zhang Xiaoyun , Wang Haixu , Cai Xuemin , Zhang Aijia , Liu Enran , Li Zhiyuan , Jiang Tao , Li Dongmei , Ding Wengang 
Published: October 2023

Abstract
Chronic diabetes mellitus compromises the vascular system, which causes organ injury, including in the lung. Due to the strong compensatory ability of the lung, it always shows subclinical symptoms. Once sepsis occurs, the degree of lung injury is more severe under hyperglycemia. α7 nicotinic acetylcholine receptors (α7nAChRs) play an important role in regulating inflammation and metabolism, which could improve endothelial progenitor cell functions. In this study, we examined the role of diabetes mellitus during sepsis and whether α7nAChR activation combined with endothelial progenitor cell transplantation can protect the lung from septic and diabetic impairments. Type 2 diabetic model rats were induced by a high-fat diet and streptozotocin. Then, these rats were exposed to lipopolysaccharide in a two-hit manner to cause sepsis. The oxygenation index, wet-to-dry ratio and histopathological score of the lungs were tested after PNU282987 treatment and EPC transplantation. IL-6, IL-8, TNF-α and IL-10 levels were measured. Caspase-3, Bax, Bcl-2, NF-κB levels were blotted. Sepsis caused obvious lung injury, which was exacerbated by diabetic conditions. α7nAChR activation and endothelial progenitor cell injection reduced injury in diabetic rats with sepsis, alleviating inflammation and decreasing apoptosis. This treatment was more effective when PNU282987 and endothelial progenitor cells were administered together. The phosphorylation of NF-κB was inhibited during this process. Activating α7nAChRs and endothelial progenitor cell transplantation alleviated the lung injury in diabetic rats with sepsis. During this process, the phosphorylation of NF-κB was reduced.