bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distribution, inducibility, and characteristics of Latilactobacillus curvatus temperate phages
Authors: Ambros Conrad L. , Ehrmann Matthias A. 
Published: September 2023

Aim: Temperate phages are known to heavily impact the growth of their host, be it in a positive way, e.g., when beneficial genes are provided by the phage, or negatively when lysis occurs after prophage induction. This study provides an in-depth look into the distribution and variety of prophages in Latilactobacillus curvatus. This species is found in a wide variety of ecological niches and is routinely used as a meat starter culture.
Methods: Fourty five L. curvatus genomes were screened for prophages. The intact predicted prophages and their chromosomal integration loci were described. Six L. curvatus lysogens were analysed for phage-mediated lysis post induction via UV light and/or mitomycin C. Their lysates were analysed for phage particles via viral DNA sequencing and transmission electron microscopy.
Results: Two hundred and six prophage sequences of any completeness were detected within L. curvatus genomes. The 50 as intact predicted prophages show high levels of genetic diversity on an intraspecies level with conserved regions mostly in the replication and head/tail gene clusters. Twelve chromosomal loci, mostly tRNA genes, were identified, where intact L. curvatus phages were integrated. The six analysed L. curvatus lysogens showed strain-dependent lysis in various degrees after induction, yet only four of their lysates appeared to contain fully assembled virions with the siphovirus morphotype.
Conclusion: Our data demonstrate that L. curvatus is a (pro)phage-susceptible species, harbouring multiple intact prophages and remnant sequences thereof. This knowledge provides a basis to study phage-host interaction influencing microbial communities in food fermentations.
Implementing the rasch model to assess the level of students' critical and reflective thinking skills on the photoelectric effect
Authors: Juandi Tarpin , Kaniawati Ida , Samsudin Achmad , Riza Lala Septem 
Published: September 2023

This study aims to determine the level of students’ critical and reflective thinking skills on the topic of photoelectric effects. In this study, the cross-sectional survey approach was employed in conjunction with purposive sampling techniques. The data collection instruments are questionnaires for critical thinking and reflective thinking skills, with 20 critical thinking items and 24 reflective thinking items. A total of 35 students, 6 males and 29 females, with an average age of 20 years, agreed to fill out the questionnaire that was distributed. The acquired quantitative data were evaluated using the Rasch model, with critical thinking skills showing that 11% of students were at a very low level, 49% were at a low level, 26% were at a high level, and 14% were at a very high level. Meanwhile, data analysis of reflective thinking skills revealed that 20% of pupils had low levels, 63% had moderate levels, and 17% had high levels. As a result, it is suggested that critical thinking and reflective thinking skills be continuously debriefed.
Isolation of extracellular vesicles from pine (Pinus sp.) needles (leaves) and roots
Authors: Kunene Sithembile , Steenkamp Emma , Motaung Thabiso 
Published: September 2023

Abstract
Plants release extracellular vesicles (EVs) for various reasons, such as unconventional protein secretion, RNA transport, and defence against pathogens. However, very little is known about plant EV biosynthesis and diverse and bioactive luminal contents, including how they alter recipient cell biology and function. To study EVs, researchers often isolate them from apoplastic wash or juice fluids using various methods. A method is needed to isolate EVs from non-model plants with tougher leaves such as species in the Pinus genus. Because of their spindly and sharp shape, pines have strong acicular-shaped leaves that are commonly called needles. Unlike all other taproots, pine seedlings grow into a primary root first, which gives rise to lateral roots later. There are also various dimensions and shapes of pine needles, but they are relatively strong compared to the leaves of other plants such as Arabidopsis thaliana, where most EV studies have been concentrated. Extracting EVs from a juice fluid is highly effective for plants with tougher leaves because it ensures that the cells have been broken down and the vesicles are present. Given these reasons, we describe our method for the isolation and purification of EVs from needles and roots of different pine species. A detailed protocol is provided that can guide the collection of juice fluid from pine needles and roots in a clean and efficient manner. A number of other plant species with similar morphologies can greatly benefit from the use of this protocol.
Comparative analysis of Phenolic and antioxidant profiling of white variety guava fruit (cv Arka Mridula) across the ripening stages, a statistical multi-facet study
Authors: Bylappa Yatheesharadhya , Nag Anish 
Published: September 2023

Abstract
Anatomical (Scanning Electron Microscopy), phenolic (total phenol and total flavonoid), antioxidant (DPPH, FRAP, and ABTS) and analytical profiling (LC and GC-MS) were performed for three different ripening stages (pre-ripe, ripe and over-ripe) of guava. Overall, the antioxidant-phenolic parameters showed a sigmoid pattern of change during the maturation progress of the fruit at room temperature (28±2ºC). Further, the PCA (Principal Component Analysis) established a strong correlation among different phenolic-antioxidant variables studied in this work. Analytical characterization by GC and LC-MS identified 55 (fifty-five) compounds from the guava extract. The PCA revealed a few compounds, namely, Glycine, Gamma Sitosterol, Kaempferol-4'-glucoside, Thiamine, Catechin and n-Hexadecanoic acid, could contribute significantly to the ripening process of guava. Finally, it is expected that an in-depth metabolic study of the guava ripening life cycle performed here could lead to the future development of highly stable fruit varies, with extended post-harvest shelf life at room temperature.
Iontronic Array with a Frequency-Coding Architecture for Transient Tactile Perception
Authors: Wang Taihong , Li Zhibin , Yang Jing , Zhang Yuxuan , Geng Peiyan , Feng Jiansong , Chen Bin , Zhang Xu , Yuan Guojiang , Chen Xiaolong 
Published: September 2023

Abstract
The artificial iontronic tactile system is a device that mimics the prompt and transient response of biological skin to mechanical stimuli, thereby enabling robots to perceive their environment. However, the surge in the number of tactile units in space constrains the data acquisition bandwidth when based on individual addressing, impeding the fast transient tactile sensing capability of the iontronic skin (I-skin). Here, we report a Frequency Coded Artificial Ion Mechanoreceptor Skin (FC-AIMS). Equipped with a fast-sensing readout circuit based on frequency coding, an array (8×8) of artificial ion mechanoreceptor (AIM) with high sensitivity (> (1.2 kPa)^-1) and ultra-wide pressure range (120 Pa - 2 MPa) successfully achieve real-time readout (within 2 ms) for the external dynamic spatiotemporal mechanical stimuli. Moreover, the parallel measurement mechanism of the circuit effectively mitigates crosstalk between sensing units. We have demonstrated that combination of proposed device and deep learning has a broad application prospect in intelligent human-machine interaction and real-time dynamic robotic manipulation.
Prognostic Factors in 448 Newly Diagnosed Multiple Myeloma Receiving Bortezomib-based Induction: Impact of ASCT, Transplant Refusal and High-Risk MM
Authors: Chim Chor Sang , Tang Hoi Ki Karen , Fung Chi Yeung , Hwang YY , Lee Harold , Lau Grace , YIP Sze , Kho Bonnie , Lau Chi Kuen , Leung Kwan Hung , Au Elaine Yuen Ling , Tse Eric , Sim Joycelyn , Kwong Yok-Lam 
Published: September 2023

Abstract
In Hong Kong, newly diagnosed multiple myeloma (NDMM) receives bortezomib-based triplet induction. Upfront autologous stem cell transplant (ASCT) is offered to transplant eligible (TE) patients (NDMM ≤65 years of age), unless medically unfit (TE-unfit) or refused (TE-refused). Data was retrieved for 448 patients to assess outcomes. For the entire cohort, multivariate analysis showed that male gender (p=0.011), international staging system (ISS) 3 (p=0.001), high lactate dehydrogenase (LDH) (p=0.000009) were adverse predictors for overall survival (OS), while complete response/ near complete response (CR/nCR) post-induction (p=0.000078) and ASCT (p=0.000478) were favorable factors for OS. In TE group, upfront ASCT was conducted in 252 (76.1%). Failure to undergo ASCT in TE patients rendered an inferior OS (TE-unfit p=1.06x10-8, TE-refused p=0.002) and event free survival (EFS) (TE-unfit p=0.00013, TE-refused p=0.002). Among TE patients with ASCT, multivariate analysis showed that age≥60 (p=0.001), ISS 3 (p=0.004) and high LDH (p=0.000251) were adverse factors for OS. In those with high-risk features (HR cytogenetics, ISS3, R-ISS 3), ASCT appeared to mitigate their adverse impact. Our data reaffirmed the importance of ASCT. The poor survival inherent with refusal of ASCT should be recognized by clinicians. Finally, improved outcome with ASCT in those with high risk features warrant further studies.
A Systematic Literature Review of Explainable Artificial Intelligence (XAI) in Software Engineering (SE)
Authors: khan Adam , Ali Asad , Khan Jahangir , Ullah Fasee , Khan Muhammad Asif 
Published: September 2023

Abstract
Artificial intelligence (AI) is the most advanced developing area for enhancing Machine Intelligence and replicating the intelligence of humans. In this regard, Machine Learning (ML) is used to develop algorithms and models that help machines learn from data and predict problems. Although ML models provide accurate predictions, they are frequently considered black boxes due to their lack of interpretability. This can undermine trust and acceptance of AI systems, particularly in critical domains requiring transparency and accountability, such as Healthcare. Explainable Artificial Intelligence (XAI) techniques, which have emerged to make ML models more transparent and interpretable, can address the lack of interpretability challenge. They shed light on how ML models make decisions and explain and justify the results. This builds trust and makes AI systems more accessible to implement in various industries. The proposed research study investigates how much XAI is used in Software Engineering (SE). It intends to present a comprehensive view of the most recent advancements and address challenges and future directions for further investigation. This Systematic Literature Review (SLR) investigates the application of XAI techniques in SE. It is based on empirical studies published between January 2020 and September 2022 to analyze the XAI’s overall illustration. We developed a search string and six research questions, each answered briefly. According to our SLR findings, 14 of the 131 research studies extracted from various databases addressed XAI techniques. Additionally, 14 research studies using XAI techniques in the Healthcare and Finance domains were chosen to compare with the findings of this literature review. These studies were chosen because the researchers frequently cited them. Following our findings, XAI approaches were mainly employed in the Software Fault Predictions (SFP) subdomain of SE, and all studies used local explanations. Python programming libraries were used for implementation, with “sci-kit” being the most widely used, followed by “caret” of the R programming language. In addition, the “LIME” tool is the most commonly used in the SFP domain for local explanations, followed by the “SHAP” tool. The findings also show that local and global explanations were used in the Healthcare and Finance domains. The most widely used Python programming library is the “sci-kit learn” library, with the “SHAP” tool being the most commonly used explanation tool in the Finance and Healthcare domains. Finally, whereas XAI in SE is new, XAI methods have been used in conjunction with traditional machine learning models. However, there is a lack of benchmark evaluation metrics in the existing literature, leading to researcher confusion and unreliable comparison standards.
Transforming Inert CeCl3 into a Recyclable Heterogeneous Visible Light Photocatalyst
Authors: Mal Prasenjit , Dinda TARUN , Manna Anupam 
Published: September 2023

Abstract
Synthetic chemists encounter increasing financial and environmental challenges in their quest for innovative catalysis. We have discovered a method to harness visible light using inert CeCl3, transforming it into a recyclable heterogeneous photocatalyst. CeCl3 is a well-known Lewis acid, is insoluble in acetonitrile, and does not absorb light. However, when combined with NXS (NBS or NCS) in acetonitrile, a transient charge-transfer complex forms, enabling visible light absorption. The formed complex facilitated the photoexcitation of Ce(III) ions, transforming them into powerful reductants that donate electrons to NXS. This led to the generation of halide radicals from NXS radical anions, enabling the solar synthesis of gem-dihaloketones from terminal alkynes through C-X cross-coupling reactions. Remarkably, the catalyst could be recovered after the reactions and reused without significant decomposition.
Genotype-based “virtual” metabolomics in a clinical biobank identifies novel metabolite-disease associations
Authors: Ferguson Jane , Bagheri Minoo , Bombin Andrei , Shi Mingjian , Murthy Venkatesh , Shah Ravi , Mosley Jonathan 
Published: September 2023

Abstract
Circulating metabolites act as biomarkers of dysregulated metabolism, and may inform disease pathophysiology. A portion of the inter-individual variability in circulating metabolites is influenced by common genetic variation. We evaluated whether a genetics-based “virtual” metabolomics approach can identify novel metabolite-disease associations. We examined the association between polygenic scores for 726 metabolites (derived from OMICSPRED) with 1,247 clinical phenotypes in 57,735 European ancestry and 15,754 African ancestry participants from the BioVU DNA Biobank. We probed significant relationships through Mendelian randomization (MR) using genetic instruments constructed from the METSIM Study, and validated significant MR associations using independent GWAS of candidate phenotypes. We found significant associations between 336 metabolites and 168 phenotypes in European ancestry and 107 metabolites and 56 phenotypes among African ancestry. Of these metabolite-disease pairs, MR analyses confirmed associations between 73 metabolites and 53 phenotypes in European ancestry. Of 22 metabolite-phenotype pairs evaluated for replication in independent GWAS, 16 were significant (false discovery rate p<0.05). Validated findings included the metabolites bilirubin and X–21796 with cholelithiasis, phosphatidylcholine(16:0/22:5n3,18:1/20:4) and arachidonate(20:4n6) with inflammatory bowel disease and Crohn's disease, and campesterol with coronary artery disease and myocardial infarction. These associations may represent biomarkers or potentially targetable mediators of disease risk.
Nutritional Intervention and Therapeutic Use of Azadirachta Indica (Neem) Fruit Juice as It Clears Malaria Parasites and Replenishes Depleted Blood Levels in Plasmodium Berghei Infected Swiss Albino Mice
Authors: IGWENYI Ikechuku , ONODUGO Chinemelum Adaora , AJA Patrick Maduabuchi , ELOM Sunday Oge , AWOKE Joshua Nonso , IBHADODE Osarieme Sandra , URAKU Anayo Joseph , EDWIN Nzubechukwu , OBASI Ajuka Nwogo , DAVID Ebuka Elijah , IGWENYI Ijeoma Precious , OGBU Patience Nkemjika , EGWU Chinedu , ATOKI Ayomide Victor 
Published: September 2023

Abstract
One of the major pathogenesis of malaria parasite infection is the invasion and destruction of the Red Blood Cells, which requires the synergistic administration of antimalarial and most times essential nutrients for effective treatment. Previous studies have shown that various non-edible parts of Azadirachta indica tree may have anti-malarial potentials, hence the investigation on the effects of edible fresh juice of Azadirachta indica fruit on various hematological parameters in addition to its potential to clear Plasmodium berghei in infected mice. The phytochemical constituents of A. indica fruit juice were carried out by Gas Chromatography-Mass Spectroscopic (GC-MS) method. Determinations of creatinine, urea, and lipid profile were carried out using Auto-analyzer. The chromatogram of GC-MS analysis of A. indica fruit juice showed four (4) peaks as follows dodecanoic acid (4.37%), oleic acid (14.19%), 13-octadecyl (17.05%) and 15-tetracosanoic acid methyl ester (47.13%) as the major constituent. The unique pathway for plasmodial fatty acid synthesis has become a possible target of drug action. Adult male mice were placed in six groups (n = 6). Group A mice were fed a normal diet and water ad libitum only while groups B to E were fed a normal diet and water ad libitum and further infected with Plasmodium berghei. The parasitemia was confirmed on the third day of infection. Groups C, D, E, and F were further given 5mg/kg body weight of Artesunate, 4.3ml/kg, 8.6 ml/kg, and 12.9 ml/kg of fruit juice respectively for fourteen days and then sacrificed. The percentage of parasitemia in infected groups was very high but treatment with Artesunate and various doses of fruit juice significantly reduced the percentage of parasitemia. Interestingly, 0.86mg/kg dose of the fruit juice caused a high significant reduction in the percentage of parasitemia comparable to the potency of Artesunate. Additionally, infection with Plasmodium berghei yielded a significant decrease in the levels of various hematological indices in the infected mice which were normalized with the administration of Artesunate and the fruit juice of Azadirachta indica. Fruit juice of Azadirachta indica has been shown to have novel dual benefits of clearing malaria parasites, serving as a blood tonic and nutritional supplement.
Development and Validation of a Prognostic Nomogram for Gastroenteropancreatic Neuroendocrine Carcinoma: A SEER Database Analysis
Authors: Chen Qishuang , Guo Yiying , Wang Zihan , Chen Xiaoying , Tian Chao , Zheng Jiabin , Tan Huangying 
Published: September 2023

Abstract
Background
Gastroenteropancreatic neuroendocrine carcinoma (GEP-NEC) is a rare group of diseases with poor prognosis. This study aimed to develop and validate a prognostic nomogram to assess overall survival (OS) in patients with GEP-NEC.
Methods
Patients diagnosed with poorly differentiated GEP-NEC were collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2011 and 2015 and divided into a training cohort and a validation cohort. Multivariate Cox regression analysis was used to identify independent prognostic factors. Nomogram was used to predict OS at 1 and 2 years. The nomogram was internally validated with validation cohort, and its predictive ability was evaluated using C-index, receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA), and integrated discrimination improvement (IDI) index.
Results
A total of 887 patients were divided into the training group (n = 623) and the validation group (n = 264). Based on multivariate analysis, a nomogram was constructed with age, gender, N stage, tumor size, primary tumor resection, radiotherapy and chemotherapy (P < 0.05). The C-index was 0.701 (95% CI: 0.677–0.725) and 0.731 (95% CI: 0.698–0.764) for the training and validation groups, respectively. The C-index, ROC, IDI and DCA results indicated that this nomogram model has a good predictive value.
Conclusions
This study screened for seven independent prognostic factors for GEP-NEC. A nomogram model based on the seven variables provided visualization of the risk for each prognostic factor and could help clinicians predict the 1-year and 2-year OS of GEP-NEC.
Bioinformatic gene analysis for potential biomarkers and therapeutic targets of heart fibrillation and stroke
Authors: Zhang Xiaojing , Chen Xinye 
Published: September 2023

Abstract
Background
Heart failure (HF) is a complex clinical syndrome associated with high morbidity and mortality. Additionally, HF is also a potent and persistent risk factor for ischemic stroke. We studied co-expressed genes to understand relationships between HF and stroke and reveal potential biomarkers and therapeutic targets of HF-related stroke.
Methods
HF- and stroke-related differentially expressed genes (DEGs), and lncRNAs (DELs), were identified via bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE76701 and GSE58294, respectively. Subsequently, extensive target prediction and network analyses methods were used to assess protein–protein interaction (PPI) and ceRNA networks, Gene Ontology (GO) terms and KEGG pathway enrichment for DEGs, and the function and expression of the co-expressed DEGs coupled with corresponding predicted miRNAs involved in HF and stroke were assessed.
Results
We identified 384 DEGs and 45 DELs in the left ventricle specimens of HF patients, respectively. Meanwhile, 884 DEGs and 266 DELs were identified in the blood samples of patients with stroke. Subsequently, 21 co-expressed DEGs and two co-expressed DELs (MALAT1 and GABPB1-AS1) may be significantly associated with HF-related stroke. Through the eDGAR online dataset, only ESR1 among 21 co-DEGs was related to myocardial infarction.
Conclusion
ESR1 is significantly associated with novel biomarkers involved in HF-related stroke, and may serve as a potential biomarker and therapeutic target for disease.
Assessment of Left Atrial Function in Normal Fetuses Using Speckle Tracking Analysis: Implications for Diastolic Function
Authors: Ye Xiaoguang , Li Yidan , Cai Qizhe , Sun Lanlan , Zhu Weiwei , Ding Xueyan , Lu Xiuzhang 
Published: September 2023

Abstract
Introduction:
Fetal echocardiography is a valuable diagnostic tool for evaluating the structure and function of the fetal heart. However, assessing fetal left atrial (LA) function in various phases remains challenging, and the relationship between fetal LA and diastolic function is unknown. We used two-dimensional speckle-tracking echocardiography (2D-STE) to assess LA function in healthy fetuses in different stages and evaluated the relationship between fetal LA function and diastolic function.
Materials and methods
This single-center prospective study included 225 healthy women with normal singleton pregnancies. At three gestational ages, 23–24 weeks, 32–33 weeks, and 36–37 weeks, 2D-STE was performed to obtain the LA strain and strain rate in the reservoir, conduit, and contraction phases. Parameters of left ventricular (LV) diastolic function, including global longitudinal early peak LV strain rate, global longitudinal late peak LV strain rate, diastolic strain rate e/a ratio, and mitral Doppler inflow pattern E/A ratio were measured and correlated with LA strain parameters.
Results
Of the 225 cases, 198 (88%) were included in the analysis. Compared with measurements in the second trimester, during the third trimester, both LA strain and strain rate were lower during the reservoir and contraction phases, while the LA strain was more significant during the conduit phase (all p < 0.05). The LA strain and strain rate in the contraction phase showed a significant correlation with the parameters of LV diastolic function.
Conclusions
Our study findings suggest that LA contraction function correlates strongly with LV diastolic function in fetuses. Thus, monitoring changes in atrial function throughout gestation can be valuable for assessing fetal cardiac maturation and identifying abnormal fetal cardiac position.