bluuebunny/crossref_metadata_2025 huggingface dataset:
A predictive model of subjective wellbeing in the elderly population
Authors: Trescato Isotta , Roversi Chiara , Vettoretti Martina , Camillo Barbara Di , Facchinetti Andrea
Published: November 2022

Background: The rapid growing proportion of elderly people on world’s population poses several challenges, especially related to public health. Among these, the increase in chronic diseases can be noted, which recent evidence attributes also to the lowering of the subjective assessment of wellbeing. Therefore, being able to predict changes in wellbeing could be key to manage this problem. In this study, we investigate for the first time the possibility of developing a purely predictive model of perceived wellbeing for population aged over 50.
Methods: Data from the European SHARE project were used, specifically the demographic, health, social and financial variables of 9649 subjects. The subjective wellbeing was measured through the CASP-12 scale. Study outcome was defined binary, i.e., worsening/not worsening of the variation of CASP-12 in2 years. Logistic regression, logistic regression with LASSO regularization, and random forest were considered as candidate models. Performance was assessed in terms of accuracy in correctly predicting the outcome and area under the curve(AUC).
Results: The best performing model was the logistic regression, achieving accuracy = 0.659 and AUC = 65.99%. All models proved to be able to generalize both across subjects and over time. The most predictive variables were CASP-12score at baseline, the presence of depression and financial difficulties.
Conclusions: Predicting 2-year variations in wellbeing via modeling techniques ispossible, albeit with some limitations, probably originating from the subjectivenature of the outcome.
Association of prediabetes with the risks of adverse health outcomes and complex multimorbidity: an observational study
Authors: Wu Yafei , Fan Xiude , Zhang Yue , Han Junming , Yuan Zhongshang , Cheng Yiping , Feng Xiaoshan , Wang Zhixiang , Shi Yingzhou , Xuan Ruirui , Dong Yingchun , Tian Yang , Yuan Zinuo , Dong Hang , Guo Qingling , Song Yongfeng , Zhao Jiajun
Published: November 2022

Background
As an abnormal state of glucose metabolism, prediabetes may cause serious damage to human health like diabetes, but it is often ignored in public health management. Here, we aim to evaluate prediabetes as a risk factor for common diseases across body system and assess whether prediabetes poses a health hazard like diabetes.
Methods
We conducted an observational study using data from the National Inpatient Sample (NIS) database from 2016 to 2018. A total of 16,650,296 patients were collected from NIS database, and 76 common diseases of various body systems were selected for analysis based on previous literature. Logistic regression model and further in-depth subgroup analysis were used to estimate the relationship between prediabetes and the risk of 76 health outcomes and prediabetes-related multimorbidity.
Main results:
Among 116,779 patients with prediabetes, the mean age was 61.4 years, 60,440 (51.8%) were female and 72,322 (64.2%) were white. Prediabetes mellitus was associated with the risk of 22 nonoverlapping diseases with significant multiple test results and odds ratios (ORs) greater than 1.50. Compared with normoglycemia, the adjusted OR for prediabetes was 4.74 (4.63–4.85) for accompanying two prediabetes-related diseases (i.e., simple multimorbidity), and 11.74 (11.43–12.05) for four or more diseases (i.e., complex multimorbidity). The proportion of older people (≥ 65 years of age) increases with the increase of number of prediabetes-related diseases.
Conclusions
Prediabetes was associated with a significantly higher risk of co-existing multiple adverse health outcomes and multimorbidity. Prediabetes, thus, might represent an important target for multimorbidity prevention, and stronger emphasis on its management and reduction seems necessary to reduce the risk of the development of multiple comorbidities, especially before the onset of overt diabetes.
Zebra finches (Taeniopygia guttata) demonstrate cognitive flexibility in using phonology and sequence of syllables in auditory discrimination
Authors: Ning Zhi-Yuan , Honing Henkjan , Cate Carel ten
Published: November 2022

Zebra finches rely mainly on syllable phonology rather than on syllable sequence when they discriminate between two songs. However, they can also learn to discriminate two strings of containing the same set of syllables by their sequence. How learning about the phonological characteristics of syllables and their sequence relate to each other and to the composition of the stimuli is still an open question. We compared whether and how the zebra finches’ relative sensitivity for syllable phonology and syllable sequence depends on the differences between syllable strings. Zebra finches were trained in a Go-Left/Go-Right task to discriminate either between two strings in which each string contained a unique set of song syllables or two strings in which both strings contained the same set of syllables, but in a different sequential order. We assessed to what extent the birds in the two experimental groups attend to the spectral characteristics and the sequence of the syllables by measuring the responses to test strings consisting of spectral modifications or sequence changes. Our results showed no difference in the number of trials needed to discriminate strings consisting of either different or identical sets of syllables. Both experimental groups attended to changes in spectral features in a similar way, but the group for which both training strings consisted of the same set of syllables responded more strongly to changes in sequence than the group for which the training strings consisted of different sets of syllables. This outcome suggests the presence of an additional learning process to learn about syllable sequence when learning about syllable phonology is not sufficient to discriminate two strings. Our study thus demonstrates that the relative importance of syllable phonology and sequence depends on which of these features vary among stimuli. This indicates cognitive flexibility in the acoustic features that songbirds might use in their song recognition.
Epigallocatechin-3-gallate (EGCG) based Metal-polyphenol nanoformulations alleviates chondrocytes inflammation by modulating synovial macrophages polarization
Authors: Wei Hong , Xu Sheng , Huang Quanxin , Jin Zhiqiang , Zheng Li , Zhao Jinmin , Qin Zainen
Published: November 2022

The activation of M1-type macrophages are dominant cells secreting proinflammatory present within the inflamed synovium in the progression of osteoarthritis (OA). Increased oxidative stress, such as redundant ROS and hydrogen peroxide (H2O2), are important factors in driving macrophages to polarize into M1 type. In this study, metal-polyphenol nanoformulations (Cu-Epigallocatechin-3-gallate (Cu-EGCG) nanosheets) were synthesized through the coordination interaction between EGCG and copper ions, which possess the antioxidant effect of EGCG and anti-inflammatory of Cu2+. Results showed that Cu-EGCG nanosheets are biocompatible and the Cu2+could be sustained released from the nanoparticles. Exhibiting multienzyme-like antioxidative activity, Cu-EGCG nanosheets could effectively scavenge the excessive intracellular ROS, leading to significantly decreased expression of the pro-inflammatory cytokines, which could reduce the expression of M1-type macrophages and exhibit excellent promotion on shifting macrophages to M2 phenotypes. Moreover, the secreted factor from the cell supernatant of Cu-EGCG treated macrophages exhibited anti-inflammatory potential in chondrocytes of inflamed synovial joints. This study suggests a novel strategy for OA therapy by using metal-polyphenol nanoformulations targeting macrophages.
Identification and Prioritization of Critical Cyber Security Challenges and Practices for Software Vendor Organizations in Software Development: An AHP-Based Systematic Approach
Authors: Khan Abdul Wahid , Zaib Shah , Khan Faheem , Khan Javed , Khan Jawad , Lee Youngmoon
Published: November 2022

Small to medium enterprise (SME) organizations are enormous in number and don't have the controls set up to prevent effective attacks of cybersecurity. The majority of the attacks are conducted when the legitimate information check is not valid and because of the absence of arrangement in applying present-day classifications, for example, 'virus', 'worm', and 'trojan'. The need for cybersecurity showed up in the early years of the digital era when the initial mainframe computer systems were designed. Many software application systems are at risk of attacks if there is a rigorous adherence to leading-edge concepts of encryption and decryption. To deal with all issues, a detailed systematic literature review (SLR) study is conducted to identify the cybersecurity challenges faced by vendor organizations during software development. Through SLR, 13 challenges have been identified, which have a frequency of >=25%. The recognized cybersecurity challenges are “Security issues/Access of Cyberattacks”, “Lack of Right Knowledge”, “Framework”, “Lack of Technical Support”, “Disaster Issues”, “Cost Security issues”, “Lack of Confidentiality and Trust”, “Lack of Management”, “Unauthorized Access issues”, “Lack of Resources”, “Lack of Metrics”, “Administrative Mistakes during Development” and “Lack of Quality, Liability, and Reliability”. All these cybersecurity challenges are classified into awareness, management, security and eminence. An Analytic Hierarchy Process (AHP) approach prioritize and recognize the significance of each identified critical cybersecurity challenge. We also apply this method to practices recognized for these critical cybersecurity challenges.
Isoliquiritigenin, Liquiritigenin Rich Root Extract of Glycyrrhiza glabra Attenuates Inflammation in Macrophages and Collagen-Induced Arthritis in Rats
Authors: babu Vineet , Kapkoti Deepak Singh , Binwal Monika , Bhakuni Rajendra S. , Shanker Karuna , singh Manju , Tandon Sudeep , Mugale Madhav N. , Kumar Narendra , Bawankule Dnyaneshwar Umrao
Published: November 2022

The aim of this study was to evaluate the potential effect of root extract of Glycyrrhiza glabra (IVT-21), isoliquiritigenin (ISL), and liquiritigenin (LTG) present in G. glabra root extract in in-vitro anti-inflammatory activity and we also investigate the effects of IVT-21 in collagen-induced arthritis (CIA) rats. Primary peritoneal macrophage cells were used for check the anti-inflammatory effect of IVT-21. Apart from this Collagen-induced arthritis (CIA) was developed in Wistar rats. Animals were orally treated with IVT-21 at dose rate of 30,100 and 300 mg /kg for 21 days. The chemical signature of IVT-21 using HPLC analysis showed the presence of ISL and LTG as the main active ingredients. Treatment of IVT-21, ISL and LTG were able to reduce the production of pro-inflammatory cytokines (TNF-α, IL-6) in LPS-induced inflammation in primary peritoneal macrophages. In-vivo experimental pharmacology profile of IVT-21 against rheumatoid arthritis revealed that oral administration of IVT-21 significantly reduced the arthritis index, arthritis score, inflammatory mediators level in CIA rat’s serum, and also reduced the NFкB-p65 expression as evidence of immunohistochemistry in knee joint tissue of CIA rats, reduce the inflammatory mediator's gene expression in a dose-dependent manner in paw tissue of CIA rats. Further, in in-vivo safety studies of IVT-21 was found to be safe in experimental animals up to 2,000 mg/kg dose. The result of this study suggests the suitability of IVT-21 as a drug-like candidate for further investigation in the management of inflammation and rheumatoid arthritis.
Integration single-cell and Bulk RNA-sequencing Data to Reveal Senescence Gene Expression Profiles in Heart Failure
Authors: Kuai Zheng , Hu Yu
Published: November 2022

Background
Heart failure(HF) represents one of healthcare's biggest challenges. Although rarely noticed, aging is a crucial risk factor for cardiovascular disease. Our study aims to reveal senescence's role in HF by integrating single cell RNA-sequencing(scRNA-seq) and bulk RNA-sequencing databases.
Methods
We collected HF heart sample data from the Gene Expression Omnibus database and senescence gene data from CellAge. The FindCluster() package was used for cell cluster analysis. Differentially expressed genes (DEG) were identified operating the FindMarkers function. Cell activity score calculation was performed using the AUCell package. UpSetR plotted the intersection between DEGs of active cell types, bulk data DEGs, and genes associated with senescence. Using the DGIdb database gene-drug interaction data, we search for potential targeted therapeutics based on common senescence genes.
Results
The scRNA-seq data revealed myocardial heterogeneity in HF tissues. A series of crucial common senescence genes were found. The senescence gene expression profile hints at an intriguing connection between monocytes and HF. After analyzing the DEGs in the bulk dataset, the DEGs in scRNA-seq, the DEGs in each active cell type, and senescence genes, we identified ten genes as common senescence genes present in HF. Correlation analysis of transcriptomics, proteomics, and ceRNA was performed to individually provide ideas for future studies in the bulk database. Moreover, we discovered that common senescence genes and potential therapeutic drugs interact among different cell types. Further research is needed on the expression pattern of senescence genes and molecular regulation in HF.
Conclusions
In summary, we identified the functional significance of the senescence gene in HF using integrated data. It is possible that this more profound understanding of how senescence contributes to the development of HF will aid in unraveling the mechanisms that promote the disease and provide hints for developing therapeutics.
A risk model constructed from five copper death-related genes for predicting prognosis and immune microenvironment infiltration in ovarian cancer patients
Authors: LI Yan , CHEN Shu-ran , LIU Jian
Published: November 2022

Purpose
Copper-dependent death is a novel mode of cell death. The prognostic value of copper death-associated genes in ovarian cancer needs further elucidation. In this study, a risk model based on copper death-related genes was identified for predicting prognosis and immunotherapy sensitivity in ovarian cancer patients.
Methods
Copper death-related genes were obtained according to literature reports. Transcriptome and prognostic information of ovarian cancer patients were obtained from TCGA database. Based on the expression of 10 copper death-associated genes, ovarian cancer patients from TCGA were typed by consensus clustering algorithm. Multi-gene risk profiles were developed from the TCGA cohort using least absolute shrinkage and selection operator (LASSO) regression analysis, followed by external validation set validation using the GEO database. Immunological correlation of the models was calculated by the CIBERSORTx algorithm and ESTIMATE algorithm, and drug sensitivity analysis was performed for patients with different risk models.
Results
Based on the expression of 10 copper death-related genes, 367 TCGA-OV cases could be better classified into two subtypes. 23 inter-subgroup differential genes screened in TCGA-OV were corrected with GEO data and 15 intersecting genes were extracted. Univariate COX analysis showed a total of 5 inter-subgroup difference genes associated with ovarian cancer survival (P < 0.05), and lasso regression finally screened 5 genes for the construction of risk models. GO and KEGG functional analysis of differential genes between high and low risk groups showed that multiple immune components and immunomodulatory pathways were enriched to. Further analysis of the immune status between the high and low risk groups suggested that the low risk group had more active immune cell infiltration and multiple immune checkpoint enrichment. Drug sensitivity analysis suggested that patients in the risk group had higher sensitivity to multiple chemotherapeutic agents.
Conclusion
Copper death-related genes may be used as a new biomarker for predicting ovarian cancer prognosis, and treatment targeting copper death genes may be a new therapeutic modality to achieve efficient remission in OC.
Analysis of the Dynamic Buckling of a Viscously Damped Spherical Shell Under an Impulse Load
Authors: Ozoigbo G. E. , Chukwuchekwa J. U. , Osuji W. I. , Udo I. U. , Ette A. M.
Published: November 2022

A regular perturbation scheme is here developed for analyzing the dynamic buckling of a lightly damped, imperfect spherical shell struck by an impulse. For simplicity of mathematical analysis, the spherical shell is discretized into time dependent modes and the resultant formulation is that of a two – small parameter problem in which the small parameters serve as agents of asymptotic expansions in a multi-timing perturbation analysis. Unlike most earlier but similar studies, all imperfections and nonlinearities as well as pre-buckling inertia and coupling terms are retained and none is neglected. In the final analysis, the dynamic buckling load is determined and the contributions to buckling of each of the terms are highlighted.
Improved sulfur dioxide resistance of the Mn/Fe-PILC catalyst by the doping of ceria in the selective catalytic reduction of NO with NH3
Authors: Wang Xinpeng , Ye Qing , Liu Wenyi , Meng Fanwei , Yang Fan , Zhang Xin , Dai Hongxing
Published: November 2022

The yCe-xMn/Fe-PILC (x and y are the nominal weight percentages of Mn and Ce, respectively; x = 4.0 wt%, y = 2.0, 4.0, and 6.0 wt%) catalysts were prepared using the impregnation method. Physicochemical properties of the as-prepared materials were measured by means of the XRD, SEM, BET, TPR, XPS, TGA-DSC, and in situ DRIFTS techniques, and their catalytic activities for the selective catalytic reduction of NO with NH3 (NH3-SCR) at low temperatures were evaluated. The 4Ce-4Mn/Fe-PILC sample showed the highest NO conversion of 95% at 350 ℃ and better resistance to SO2 poisoning than the Ce-free 4Mn/Fe-PILC sample. The loading of ceria not only increased the concentrations of the active Mn4+ species and chemisorbed oxygen (Oads) species, but also improved redox ability of the 4Ce-4Mn/Fe-PILC sample. After sulfur dioxide poisoning, the concentrations of the active Mn4+ and Oads species in the ceria-loaded samples were decreased by less extents than those in the ceria-free sample. The in situ DRIFTS results further demonstrated that the doping of ceria increased the amount of the acid sites, enhanced the formation of NH3 intermediates (i.e., monodentate nitrite and bridging nitrate), and protected the main active Mn4+ species. Therefore, the samples containing ceria possessed better resistance to SO2 poisoning.
Direct-to-consumer genetic test and lifestyle questionnaire analysis of body mass index and body fat percentage in a large Korean population
Authors: Kim Hyo-Eun , Park Kyung Mi , Lee Dasom , Lee So-Ra , Kim Sang-Woon , Hwang Tae Soon , Hong Kyung-Won
Published: November 2022

Background
Direct-to-consumer (DTC) genetic testing provides genetic risk to consumers and motivates consumers to take care of their own customized health care. In 2018, we developed and provided a DTC genetic testing service (GENESTART™) in collaboration with Herbalife Korea Co. Ltd.
Methods
The analyzed dataset consisted of the body fat percentage (BFP), body mass index (BMI), 31 genetic polymorphism genotypes, and responses to 19 questionnaire items of 24,447 individuals. The genetic main effects for BFP and BMI were examined by linear regression analysis, and the interaction effects were examined using a generalized linear model that controlled age and sex as covariates. In the case of BFP, the sample average was 31.47% overall, 24.76% for men, and 32.79% for women, showing that men had an average BFP that was 8 percentage points lower than that of women. The average BMI was 25.38 overall, 26.45 for men, and 25.17 for women, showing that men had an average BMI of 1.2 kg/m2 higher than that of women.
Results
The FTO and MC4R genes, well-known obesity markers, showed a significant correlation with both phenotypes, and the BDNF gene, which is related to stress obesity, showed a highly significant association with BMI but only a weak association with BFP. Among the remaining genes, TRIB1, ABCA1, MYL2, G6PC, GCKR, GLIS3, CYP17A1, HECTD4, and NT5C2 genes showed significant associations with the obesity-related phenotypes. In this study, we found four interaction results for BFP (ABO and fruits, CYP1A2 and sugary foods, FTO and muscle exercise, MC4R and vitamins) and five interactions for BMI (MC4R and proteins, CSK and fruits, MC4R and calcium, DGKB and calcium, CSK and water).
Conclusions
This study is expected to enable the provision of personalized and accurate solutions for BFP and BMI management to customers who have undergone genetic testing.
Molecular mapping and transfer of sheath blight resistance QTLs from wild rice Oryza nivara to cultivated rice (Oryza sativa L.)
Authors: Neelam Kumari , Aggarwal Sumit , Kumari Saundriya , Kumar Kishor , Kaur Amandeep , Babbar Ankita , Lore Jagjeet Singh , Kaur Rupinder , Vikal Yogesh , Singh Kuldeep
Published: November 2022

Background
Sheath blight (ShB) is the most serious disease of rice (Oryza sativa L.), caused by a soil-borne fungus Rhizoctonia solani Kühn (R. solani). It limits global rice productivity by causing ~50% yield loss every year. Broad host range, rapid resurgence of new pathogen races, and the lack of highly resistant germplasm are the major caveat to managing this disease. Therefore, continuous scouting of new germplasm resources resistance to R. solani is urgently required.
Results
In this report, we identified a very promising resistance source O. nivara accession IRGC81941A which displays partial resistance across the five years of screening against R. solani. Quantitative trait loci (QTL) mapping was performed in F2 populations that identified a total of 29 QTLs with the total phenotypic variance explained (PVE) ranged from 4.70 to 48.05%. A cluster of four QTL qRLH1.1, qRLH1.2, qRLH1.5, and qRLH1.8 stably detected which showed consistent resistant response against R. solani. The size of these QTL ranging from 0.096-420.1 Kb, based on the rice reference genome harboring several important disease resistant genes such as Ser/Thr protein kinase, auxin-responsive protein, Protease inhibitor/seed storage/LTP family protein, MLO domain-containing protein, disease responsive protein, Thaumatin-like protein, Avr9/Cf9 eliciting protein, and many transcription factors. A simple sequence repeat (SSR) marker RM212 co-segregates with this QTL cluster.
Conclusion
Our finding suggests that a highly stable QTL cluster confers resistance to sheath blight disease. Effective transferring of this cluster as a single unit through backcross breeding marked the identification of three agronomically superior resistant lines. These promising germplasms could be an important pre-breeding material for varietal development. PCR-based SSR marker linked to these QTLs could facilitate efficient transfer of the QTLs into rice cultivars through marker-assisted selection programs.
Potential diagnostic value of circulating miRNAs in HFrEF and bioinformatics analysis
Authors: Kuai Zheng , Gao Wei , Ma Yuanji , Zhang Xiaoxue , Wang Xiaoyan , Ye Yangli , Zhang Xiaoyi , Yuan Jie
Published: November 2022

Few studies have compared the performances of those reported miRNAs as biomarkers for heart failure with reduced EF (HFrEF) in a population at high risk. The purpose of this study is to investigate comprehensively the performance of those miRNAs as biomarkers for HFrEF. By using bioinformatics methods, we also examined these miRNAs' target genes and possible signal transduction pathways. We collected serum samples from patients with HFrEF at Zhongshan Hospital. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of those miRNAs as biomarkers for HFrEF. miRWALK2.0, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to predict the target genes and pathways of selected miRNAs. The study included 48 participants, of whom 30 had HFrEF and 18 had hypertension with normal left ventricular ejection fraction (LVEF). MiR-378, miR-195-5p were significantly decreased meanwhile ten miRNAs were remarkably elevated (miR-21-3p, miR-21-5p, miR-106-5p, miR-23a-3p, miR-208a-3p, miR-1-3p, miR-126-5p, miR-133a-3p, miR-133b, miR-223-3p) in the serum of the HFrEF group. All miRNAs had an area under the curve (AUC) > 0.70, except for miR-21-5p and miR-22a-3p. The combination of miR 133a-3p, miR 106b-5p, miR 1-3p, miR 133b, and miR 378 has a good diagnostic performance for HFrEF and multitudes of possible mechanisms/pathways through which dysregulation of these miRNAs may affect the crapshoot of HFrEF.
Cauchy robust principal component analysis with applications to high-dimensional data sets
Authors: Fayomi Aisha , Pantazis Yannis , Tsagris Michail , Wood Andrew T.A.
Published: November 2022

Principal component analysis (PCA) is a standard dimensionality reduction technique used in various research and applied fields. From an algorithmic point of view, classical PCA can be formulated in terms of operations on a multivariate Gaussian likelihood. As a consequence of the implied Gaussian formulation, the principal components are not robust to outliers. In this paper, we propose a modified formulation, based on the use of a multivariate Cauchy likelihood instead of the Gaussian likelihood, which has the effect of robustifying the principal components. We present an algorithm to compute these robustified principal components. We additionally derive the relevant influence function of the first component and examine its theoretical properties. Simulation experiments on high-dimensional datasets demonstrate that the estimated principal components based on the Cauchy likelihood outperform or are on par with existing robust PCA techniques.
Low-pressure Ethylene/Air Laminar Premixed Flames: Characterisations and Soot Diagnostics
Authors: Algoraini Safa , Sun Zhiwei , Dally Bassam B , Alwahabi Zeyad T.
Published: November 2022

In this work, the structure of laminar premixed ethylene/air flat flames at low pressure are studied experimentally. The aim of the work is to exploit the spatial expansion of laminar 1-D flames and advanced laser techniques to better understand the conditions and precursors affecting soot particles inception. Soot volume fraction (fv) profiles were measured using laser-induced incandescence (LII), while spatial distribution of the CH* and C2* radicals were measured using spatially resolved emission spectroscopy. Spatially resolved laser induced fluorescence have been used to record emission from 2-3 rings 3-4 rings and > 5 rings. The temperature of soot particles (Ts) was evaluated through fitting the spectrally resolved soot luminosity, while flame gaseous temperature (Tg) was measured using a fine thermocouple. The laminar flow velocity was modelled and used to evaluate the reaction time at each HAB. Using the quantity dfv/dt and fv along with the reaction time, it was possible to reveal the soot volume fraction growth rate. At pressure of 27 KPa the growth rate, kSG, was evaluated as 20 s-1. Taking advantage of the expanded flame structure at low pressure, the profiles of CH* , C2* , soot and temperatures, as a function of the height above the burner were well resolved. It was found that CH* and C2* chemiluminescence overlap in space. The thickness of CH* layer is larger than that of C2* , and it peaks at slightly different location, CH* appears approximately 1 mm before C2*. The distance between the two peaks decreases linearly with the increase in pressure. The lowest value of the initial soot volume fraction (fv) was 0.19 ppb, measured at pressure 27KPa. It was found that fv scales with the pressure following a power function of the form 𝑓𝑣 𝛼 𝑃𝑟n where n is 2.15 ± 0.7. It was observed that, in all the flames investigated, the initial soot particles first appear at a common critical inception temperature, Tinception, of 1465 ± 66 K. It was found that the Tinception is lower than the maximum flame temperature, Tmax, by ~45° and appeared ~1mm further than the location of Tmax. Using the Langrangian quantity dfv/dt and fv, it was possible to reveal the soot growth rate, KSG. At pressure of 27 KPa the value of KSG was evaluated as 20 S-1.
Anti-tumor effect of IL-2 and TRAIL expressed by recombinant Salmonella: an immunotherapeutic proposal against bladder cancer by iNOS, Caspases activation and modulation of the immune system
Authors: Fragelli Bruna Dias de Lima , Rodolpho Joice Margareth de Almeida , de Godoy Krissia Franco , Camillo Luciana , de Castro Cynthia Aparecida , Brassolatti Patricia , Borra Ricardo Carneiro , Silva Adilson José da , Alexandrino André Vessoni , Novo-Mansur Maria Teresa Marques , Nogueira Camila Tita , Anibal Fernanda de Freitas
Published: November 2022

IL-2 and TRAIL are therapeutic agents known for their antitumor role, but they can be cleared quickly by the body or be cytotoxic, compromising their function. To reverse this impasse, the synthesis of these agents by live bacteria directly in the tumor is a viable approach, due to bacteria’s preference to colonize tumor tissue. It happens because of the high nutrient grid in this microenvironment and possible escape from the immune system since solid tumors are ischemic and have regions of hypoxia. In this context, attenuated Salmonella represents a promising live vector for delivery of antitumor molecules. The present study investigated the effects of IL-2, TRAIL and mixture of proteins expressed by recombinant Salmonella, strain SL3261, with unique and innovative construction with IL-2 and TRAIL proteins, on bladder cancer cells and in mice od C57BL/6. Human bladder cancer cell line RT4 was exposed for 24 and 48 hours to these proteins and were analyzed with flow cytometry, ELISA, dyes and fluorescent antibodies. In the animal model, tumor induction was performed with MB49 cells, followed by treatment with bacterial strains and collection of tissues and organs for analysis. The results demonstrated that both agents are cytotoxic to the tumor cells, as they cause a decrease in cell viability, modification of its proper morphology and induction of apoptosis. This effect is caused by the activation of the iNOS enzyme by IL-2, which leads to the production of nitric oxide with consequent activation of genes that lead to DNA degradation and by the activation of the Caspase family by TRAIL, causing apoptosis. In mice, there was an important regression of tumor progression and modulation of the immune system. Therefore, IL-2, TRAIL and MIX synthesized by recombinant Salmonella show promising potential in bladder cancer therapy.
Multi-Objective Optimization with Transformation-Interaction-Rational Representation for Symbolic Regression
Authors: de Franca Fabricio Olivetti
Published: November 2022

The Transformation-Interaction-Rational is a representation for symbolic regression that limits the search space of function forms to well structured functions enabling the use of efficient numerical coefficient determination. The performance of using Genetic Programming with this representation was substantially better than with its predecessor (Interaction-Transformation) while ranking close to the state-of-the-art on a contemporary Symbolic Regression benchmark. In this same benchmark, we observed that the performance could be further improved with an additional selective pressure on smaller datasets for the expression size, thus creating smaller expressions and generalizing better. This was verified with a penalization term applied to the fitness measure together with heuristic rules to determine what is a small dataset. Possibly a better strategy is to adopt a multi-objective search to find a set of non-dominated solutions taking accuracy and model size in consideration. This will automatically stimulate the preference for simpler models whenever two equally accurate model exists, possibly the need for heuristic rules and penalty functions. In this paper, we extend the evolution library used by TIR to support multi-objective optimization, specifically the NSGA-II algorithm, and apply that to the same benchmark. The results show that the use of multi-objective optimization improves the results on a selection of the benchmarks increasing the overall rank of the algorithm to a second place in the benchmark. However, this strategy is still sensitive to overfitting on small data sets.
A Rare Case of Acute Abdomen Caused by Perforation of Jejunal Gastrointestinal Stromal Tumor (Gist): A Case Report and Literature Review
Authors: Mirovic Milos , Stojanovic Milica Dimitrijevic , Stankovic Vesna , Milosev Danijela , Milosevic Bojan , Cvetkovic Aleksandar , Spasic Marko , Vekic Berislav , Stojanovic Bojana S. , Petrovic Marko , Stojanovic Bojan
Published: November 2022

Background: Gastrointestinal stromal tumor (GIST) is the most common mesenchymal neoplasm of the gastrointestinal system and it accounts for between 1-3% of all gastrointestinal malignancies. GIST arises most commonly from the stomach in 60 – 70% of cases. The clinical presentation of acute abdomen, due to GIST perforation, was a particularly rare described complication of this disease. Our case report aimed to present a case of acute abdomen in an elderly female patient, due to jejunal GIST perforation.
Case presentation: A 76-year-old female patient presented with acute abdomen to the emergency surgical unit University Clinical Center of Kragujevac. Computed tomography (CT) scan with intravenous contrast showed pneumoperitoneum, the presence of a 75 x 35 mm irregular fluid collection in the left lower quadrant of the abdomen with air inclusions and signs of small intestine perforations. The patient underwent an emergency laparotomy. Intraoperative findings showed the acute inflammatory reaction of the peritoneum with free bowel contents in the abdominal cavity due to jejunal tumor perforation. Partial resection of the small intestine with tumor was performed followed by intestine anastomosis. Histopathological examination of a specimen revealed a completed resected jejunal gastrointestinal stromal tumor.
CONCLUSIONS: GIST arises from the small intestine in 25-30% of cases, and jejunum in 10% of cases. Perforation of GIST and acute diffuse peritoneal inflammation was rare complication of the disease. Emergency laparotomy and complete resection of tumors are essential.
An EOQ model for three deteriorating items with substitutable and mutual complementary price, stock, and time dependent demand
Authors: Mahlangu David , Adetunji Olufemi , Sebatjane Makoena
Published: November 2022

In this paper, a three-item EOQ model is proposed, where Product 1 is the main item and has a demand that is dependent on the following: its selling price and stock level, the selling price of the mutual complement (Product 2), selling price of its substitute (Product 3), and time. Product 2 has a demand that is dependent on its selling price, the selling price of its complement (Product 1) and time. Product 3 has a demand that is dependent on its selling price, the selling price of its substitute (Product 1) and time. A practical scenario for this model is in the perishable chicken feed supply chain between the supplier of medicines used in chicken feed production and a manufacturer of animal feed. Typical in this node of the supply chain the manufacturer of animal feed may source various medications from the same supplier. Due to certain nutritional specification of the feed formula, some of these medicines must be used together (complementarily), while some of these medicines can be used interchangeably (substitutes). Furthermore, stock availability of these medicines has potential to stimulate their prices, and consequently the demands. The mathematical model presented helps to determine optimal values of the selling prices of the three products and the cycle time that will maximise the total profit. The solution procedure was proposed, followed by numerical example Sensitivity analysis was conducted to assess how the model outputs respond to certain parameter changes. Result obtained from the study indicates that, certain parameter changes on the model have significant impacts on the cycle time, pricing, and the profitability of the inventory system.
Cisplatin resistance driver claspin is a target for immunotherapy in urothelial carcinoma
Authors: Yamada Shuhei , Miyata Haruka , Isono Makoto , Hori Kanta , Yanagawa Junko , Murai Aiko , Minowa Tomoyuki , Mizue Yuka , Sasaki Kenta , Murata Kenji , Tokita Serina , Nakatsugawa Munehide , Iwabuchi Sadahiro , Hashimoto Shinichi , Kubo Terufumi , Kanaseki Takayuki , Tsukahara Tomohide , Abe Takashige , Shinohara Nobuo , Hirohashi Yoshihiko , Torigoe Toshihiko
Published: November 2022

Bladder cancer is a major and fatal urological disease. Cisplatin is a key drug for the treatment of bladder cancer, especially in muscle-invasive cases. In most cases of bladder cancer, cisplatin is effective; however, resistance to cisplatin has a significant negative impact on prognosis. Thus, a treatment strategy for cisplatin-resistant bladder cancer is essential to improve the prognosis. In this study, we established a cisplatin-resistant (CR) bladder cancer cell line using a urothelial carcinoma cell line (UM-UC-3 cells). We screened for potential targets in CR cells and found that claspin (CLSPN) was overexpressed.CLSPNmRNA knockdown revealed that CLSPN had a role in cisplatin resistance in CR cells. In our previous study, we identified human leukocyte antigen (HLA)-A*02:01-restricted CLSPN peptide by HLA ligandome analysis. Thus, we generated a CLSPN peptide-specific cytotoxic T lymphocyte (CTL) clone that recognized CR cells at a higher level than wild-type UM-UC-3 cells. These findings indicate that CLSPN is a driver of cisplatin resistance and CLSPN peptide-specific immunotherapy may be effective for cisplatin-resistant cases.
Quantifying social interventions in combating COVID-19 via a symmetry-based model
Authors: Zhang Lei , She Guang-Hui , She Yu-Rong , Li Rong , She Zhen-Su
Published: November 2022

The COVID-19 pandemic reveals new features of substantial changes in rates of infection, cure, and death, resulting from social intervention, which significantly challenges traditional SEIR-type models. This paper develops a symmetry-based model for quantifying social interventions in combating COVID-19. We find three key order parameters, separating degree (S) for susceptible populations, healing degree (H) for mild cases, and rescuing degree (R) for server cases, all display logistic dynamics, which establish a novel dynamic model named SHR. Furthermore, we discover two evolutionary patterns of healing degree with a universal power law in 23 areas in the first wave. Remarkably, the model yields a quantitative evaluation of the ‘dynamic back-to-zero’ policy in the third wave in Beijing by 12 datasets of different sizes. In conclusion, the SHR model constitutes a rational basis to understand this complex epidemic, and for policymakers to carry out sustainable anti-epidemic measures to minimize its impact.
A brief story of spatial modeling at southwestern Atlantic Ocean
Authors: Rodrigues Lucas
Published: November 2022

Spatial modeling of marine species is widely developed for biogeography, ecology and management purposes. However, hundreds of articles have been concentrated in the northern hemisphere marine environments and only a few dozens for the southern hemisphere. Through a bibliometric analysis I identified strong and weak aspects of studies approaching spatial modeling for species inhabiting the southwestern South Atlantic Ocean – SWAO. Studies on marine mammals and seabirds, based on presence-only and scenopoetic input data and through maximum entropy (MaxEnt) and generalized linear/additive models (GLM/GAM) are the highlights. A tiny quantity of articles have investigated the regional impacts of climate changes over species distribution (e.g., species displacement) or added alternatives for the management of fishing activities and its impacts on non-target species (e.g. incidental catch). I listed the articles used as baseline, discuss the aspects of my findings and claim to scientific community the need to strengthen the spatial modeling routine over SWAO.
Thermodynamic Analysis of Climate Change
Authors: Swedan Nabil
Published: November 2022

The climate change assessment of the Intergovernmental Panel on Climate change is based on a radiative forcing methodology and thermodynamic analysis of the climate does not appear to be utilized. Although equivalent to the radiative model, the thermodynamic model captures details of thermodynamic interactions among the earth’s subsystems. Carbon dioxide emission returns the net chemical energy exchanged with the climate system to the surface of the earth as heat. The heat is equal to the sum of the heat produced by fossil fuels and deforestation minus the heat of surface greening. Accordingly, trends of climate parameters are calculated. Nearly 51.40% of carbon dioxide production has been sequestered by green matter, and surface greening is approximately 3.0% per decade. Through 2020, the heat removed by surface greening has approached 12.84% of the total heat. Deforestation on the other hand has contributed nearly 22.85% of the total heat of carbon conversion to carbon dioxide. The increase in marine and average land surface air temperatures are 0.80 °C and 1.39 °C respectively. Present annual sea level rise is nearly 3.35 mm, and the calculated reductions in the temperature and geopotential height of the lower stratosphere are about -0.66 °C and -67.24 m per decade respectively. Unlike natural sequestration of carbon dioxide, artificial sequestration is not a photosynthetic heat sink process and does not appear to be a viable methodology for mitigating climate change.
Rhizosphere functioning and rhizo-microbiome of two contrasting genotypes of rice under drought-induced conditions
Authors: Nunna Sai Aparna Devi , Balachandar Dananjeyan
Published: November 2022

Background and aim

Rhizosphere function is the key determinant of crop growth and fitness under moisture-stress conditions. Human-centered breeding adversely affects microbiome recruitment of crops. Hence, during drought, wild types and landraces adapt to stress, while modern cultivars and hybrids fail to do so and are susceptible to drought. Understanding the rhizosphere difference between landraces and cultivars will help to improve microbiome-mediated drought mitigation.

Methods

We compared rhizospheres of rice landrace, Norungan, and high-yielding cultivar, Co51, grown under normal moisture and drought-induced conditions using soil biochemical and 16S rRNA gene sequencing approach.

Results

Soil carbon pools, enzymes, and respiration were adversely affected due to drought in both genotypes' rhizospheres. However, Norungan rhizosphere accounted for less harm to the soil attributes than Co51. Reduction in soil organic carbon (3.94%), microbial biomass carbon (14.26%), labile carbon (1.94%), dehydrogenase (10.1%), urease (21.27%), phosphatase (9.61%), and respiration rate (15.02%) was accounted in Co51 than Norungan, during drought. Alpha diversity of bacterial communities in rice's rhizosphere was significantly lower than in bulk soil, and drought further reduced the diversity in both genotypes. Moisture-stress reduced the abundance of Firmicutes (180%) and Bacteroidetes (57%) in Norungan's rhizosphere, while, Acidobacteria (51%), Actinobacteria (54%), Chlolorflexi (41%), and Proteobacteria (34%) got increased. On the other hand, Co51 rhizosphere acquired an enhanced abundance of Firmicutes (79%) and Bacteriodetes (170%) and lessened abundance of Acidobacteria (15%) and Proteobacteria (31%) due to drought.

Conclusion

These results suggest that landrace Norungan under moisture-stress conditions recruits less-diversified, specific groups of microorganisms to augment rhizosphere functioning.
A literature review of methods for assessment of reproducibility in science
Authors: Nordling Torbjörn , Peralta Tomas Melo
Published: November 2022

Introduction: In response to the US Congress petition, the National Academies of Sci- ences, Engineering, and Medicine investigated the status of reproducibility and replicability in science. A piece of work is reproducible if the same results can be obtained while fol- lowing the methods under the same conditions and using the same data. Unavailable data, missing code, and unclear or incomplete method descriptions are common reasons for failure to reproduce results.
Objectives: The motivation behind this review is to investigate the current methods for reproducibility assessment, and analyze their strengths and weaknesses so that we can determine where there is room for improvement.
Methods: We followed the PRISMA 2020 standard and conducted a literature review to find the current methods to assess the reproducibility of scientific articles. We made use of three databases for our search: Web of Science, Scopus, and Engineering Village. Our criteria to find relevant articles was to look for methods, algorithms, or techniques to evaluate, assess, or predict reproducibility in science. We discarded methods that were specific to a single study, or that could not be adapted to scientific articles in general.
Results: We found ten articles describing methods to evaluate reproducibility, and classified them as either a prediction market, a survey, a machine learning algorithm, or a numerical method. A prediction market requires participants to bet on the reproducibility of a study. The surveys are simple and straightforward, but their performance has not been assessed rigorously. Two types of machine learning methods have been applied: handpicked features and natural language processing.
Conclusion: While the machine learning methods are promising because they can be scaled to reduce time and cost for researchers, none of the models reviewed achieved an accuracy above 75%. Given the prominence of transformer models for state-of-the-art NLP tasks, we believe a transformer model can achieve better accuracy.
Productivity Spillovers from Foreign Direct Investment to Ethiopian Manufacturing Sector
Authors: Wajebo Temesgen Woldamanuel
Published: November 2022

The study investigates productivity spillover from foreign direct investment to domestic firms in the Ethiopian manufacturing industries. The System Generalized Method of Moments (SYS-GMM) estimator using panel data of manufacturing firms for the years 2011 to 2016 with 12006 observations grouped under 102 industries was employed. The results show a coexistence of both negative and positive productivity spillover effects from FDI to domestic firms at moderate level of absorptive capacity. Specifically, foreign presence in the industries contributed a positive and significant horizontal and backward productivity spillover effect to domestic firms on an average level. The horizontal productivity spillover is transmitted to local firms through demonstration and competition effects at a moderate level. Likewise, vertical productivity spillover occurred through the channel of sales of intermediate goods and services to foreign firms. We have observed that the technology gap is a critical factor among those factors that determine the productivity spillover occurrence. Finally, policy measures aimed at minimizing the technology gap between foreign and domestic firms to maximize the productivity spillover effect are suggested. Since the result shows that the spillover effects in all firms are not equal, prioritization as per their promise is recommendable in an FDI attracting framework.