bluuebunny/crossref_metadata_2025_split huggingface dataset:
Marker for kidney fibrosis is associated with inflammation and deterioration of kidney function in people with type 2 diabetes and microalbuminuria
Authors: Poulsen Christina Gjerlev , Rasmussen Daniel G. K. , Genovese Federica , Hansen Tine W. , Nielsen Signe Holm , Reinhard Henrik , von Scholten Bernt Johan , Jacobsen Peter K. , Parving Hans-Henrik , Karsdal Morten Asser , Rossing Peter , Frimodt-Møller Marie 
Published: March 2023

Background
Diabetic kidney disease is a major cause of morbidity and mortality. Dysregulated turnover of collagen type III is associated with development of kidney fibrosis. We investigated whether a degradation product of collagen type III (C3M) was a risk marker for progression of chronic kidney disease (CKD), occurrence of cardiovascular disease (CVD), and mortality during follow up in people with type 2 diabetes (T2D) and microalbuminuria. Moreover, we investigated whether C3M was correlated with markers of inflammation and endothelial dysfunction at baseline.

Methods
C3M was measured in serum (sC3M) and urine (uC3M) in 200 participants with T2D and microalbuminuria included in an observational, prospective study at Steno Diabetes Center Copenhagen in Denmark from 2007–2008. Baseline measurements included 12 markers of inflammation and endothelial dysfunction. The endpoints were CVD, mortality, and CKD progression (>30% decline in eGFR).

Results
Mean (SD) age was 59 (9) years, eGFR 90 (17) ml/min/1.73m2 and median (IQR) urine albumin excretion rate 102 (39–229) mg/24-h. At baseline all markers for inflammation were positively correlated with sC3M (p≤0.034). Some, but not all, markers for endothelial dysfunction were correlated with C3M. Median follow-up ranged from 4.9 to 6.3 years. Higher sC3M was associated with CKD progression (with mortality as competing risk) with a hazard ratio (per doubling) of 2.98 (95% CI: 1.41–6.26; p = 0.004) adjusted for traditional risk factors. uC3M was not associated with CKD progression. Neither sC3M or uC3M were associated with risk of CVD or mortality.

Conclusions
Higher sC3M was a risk factor for chronic kidney disease progression and was correlated with markers of inflammation.
Clinical phenotypes of chronic cough categorised by cluster analysis
Authors: Kang Jiyeon , Seo Woo Jung , Kang Jieun , Park So Hee , Kang Hyung Koo , Park Hye Kyeong , Lee Sung-Soon , Moon Ji-Yong , Kim Deog Kyeom , Jang Seung Hun , Kim Jin Woo , Seo Minseok , Koo Hyeon-Kyoung 
Published: March 2023

Background
Chronic cough is a heterogeneous disease with various aetiologies that are difficult to determine. Our study aimed to categorise the phenotypes of chronic cough.

Methods
Adult patients with chronic cough were assessed based on the characteristics and severity of their cough using the COugh Assessment Test (COAT) and the Korean version of the Leicester Cough Questionnaire. A cluster analysis was performed using the K-prototype, and the variables to be included were determined using a correlation network.

Results
In total, 255 participants were included in the analysis. Based on the correlation network, age, score for each item, and total COAT score were selected for the cluster analysis. Four clusters were identified and characterised as follows: 1) elderly with mild cough, 2) middle-aged with less severe cough, 3) relatively male-predominant youth with severe cough, and 4) female-predominant elderly with severe cough. All clusters had distinct demographic and symptomatic characteristics and underlying causes.

Conclusions
Cluster analysis of age, score for each item, and total COAT score identified 4 distinct phenotypes of chronic cough with significant differences in the aetiologies. Subgrouping patients with chronic cough into homogenous phenotypes could provide a stratified medical approach for individualising diagnostic and therapeutic strategies.
A novel STAT3 splice-site variant in a kindred with autosomal dominant hyper IgE syndrome
Authors: Scott Ori , Sham Marina , Abrego Fuentes Laura , Pereira Myra , Merico Daniele , Kim Vy HD 
Published: March 2023

Background: Dominant negative STAT3 loss-of-function is the most common genetic cause of hyper-IgE syndrome (HIES). Patients may present with a host of both immune and non-immune manifestations, including connective tissue abnormalities, recurrent infections, malignant predisposition, and biochemical evidence of elevated serum IgE or eosinophilia. Aim: To describe a novel splice-site variant in STAT3 resulting in HIES. Methods: Case report of two family members with HIES. Results: A proband and his son presented with neonatal-onset pustular rash, recurrent skin and sinopulmonary infections and elevated serum IgE and were diagnosed with AD-HIES. They were identified to harbor a novel splice-site variant in the DNA-binding domain (DBD) of STAT3: c.1110-3C>G, predicted to result in defective splicing in exon 12. Interestingly, a number of other patients with AD-HIES have mutations affecting the same splice-site, suggesting this may be a hot-spot for mutagenesis. Conclusion: Splice-site mutations in the DBD of STAT3 are increasingly identified as a cause of AD-HIES. Future work is required to delineate whether patients with splice-site mutations have unique clinical characteristics, supporting efforts for genotype-phenotype correlation in this disease. Statement of Novelty: We present a novel splice-site mutation in the DNA-binding domain of STAT3 leading to autosomal dominant hyper-IgE syndrome.
Corrosion inhibition efficiency and quantum chemical studies of some organic compounds: theoretical evaluation
Authors: Mamand Dyari Mustafa , Qadr Hiwa Mohammad 
Published: March 2023

Abstract
When most or all of the atoms on a single metal surface are oxidized, corrosion takes place, causing damage to the whole surface. The effects of adsorption and corrosion inhibition on different types of functional groups were studied. A review of these inhibitors based on concentration effect was performed to establish the theoretical results. It has been investigated the effects of 5-(5-(3,5-diaminophenyl)-1,3,4-oxadiazol-2-yl)-N1,N3-di-p-tolylbenzene-1,3-diamine (BATP) on mild steel in 1 M H2SO4 at 30 °C, Levamisole (LMS) and 4-phenylimidazole (PIZ) on copper in 0.5 M H2SO4, 2-phenyl-1, 4-dihydroquinoxaline (PHQ) on carbon steel in 1.0 M HCl. Based on DFT calculations in the 6–311++G(d,p) basis set in gas and aqueous phases, several quantum chemical parameters were determined to evaluate the array of selected molecules such as HOMO, LUMO, ionization energy, bandgap energy, electronegativity, chemical potential, electrophilicity, nucleophilicity, electron transfer, back-donation energy and Fukui function analysis. The most stable low-energy adsorption configurations of the materials employed in this investigation on the Fe (110) surface were induced using Monte Carlo simulations.
CellML 2.0.1
Authors: Clerx Michael , Cooling Michael T. , Cooper Jonathan , Garny Alan , Moyle Keri , Nickerson David P. , Nielsen Poul M. F. , Sorby Hugh 
Published: March 2023

Abstract
We present here CellML 2.0.1, an XML-based language for describing and exchanging mathematical models of physiological systems. MathML embedded in CellML documents is used to define the underlying mathematics of models. Models consist of a network of reusable components, each with variables and equations giving relationships between those variables. Models may import other models to create systems of increasing complexity. CellML 2.0.1 is defined by the normative specification presented here, prescribing the CellML syntax and the rules by which it should be used. The normative specification is intended primarily for the developers of software tools which directly consume CellML syntax. Users of CellML models may prefer to browse the informative rendering of the specification (https://cellml.org/specifications/cellml_2.0/) which extends the normative specification with explanations of the rules combined with examples of their usage. This version improves the identification of rule statements and corrects errata present in the CellML 2.0 specification.
Predicting the performance of broadband passive optical networks using machine learning
Authors: Singh Kuldeep , Krupa Varma P. Ravi , Singh Rajandeep , Kaur Ramandeep 
Published: March 2023

Abstract
Broadband passive optical networks is an established architecture for the high-speed data transfer. For effective fault diagnosis and self-configuration in these networks, analysis of network-generated data is essentially required. In this era, machine learning-based data analytics approaches could play a vital role in analyzing the performance of the networks. In this paper, a machine learning approach has been proposed for predicting the performance of broadband passive optical networks. For this task, a dataset consisting of fiber length, transmission power, number of power splitters, line width, and extinction ratio parameters has been generated to make an estimate of the Q factor for a given optical network. Out of these network parameters, fiber length, transmission power, and several power splitters are selected through the relief attribute evaluation technique. The selected parameters are fed into a regression-based model tree classification algorithm for estimating different levels of Q factor. This work also takes into account logistic regression, decision tree, decision table, PART, and random forest algorithms for the desired task. The analysis of simulation results proves that the regression-based model tree classification algorithm provides an effective estimate of Q factor in terms of accuracy of 93.23% and 95.74% for 7-class and 3-class problems. Thus, this algorithm appears to be a suitable choice to predict the performance of broadband passive optical networks accurately.
Machine learning to optimize additive manufacturing for visible photonics
Authors: Lininger Andrew , Aththanayake Akeshi , Boyd Jonathan , Ali Omar , Goel Madhav , Jizhe Yangheng , Hinczewski Michael , Strangi Giuseppe 
Published: March 2023

Abstract
Additive manufacturing has become an important tool for fabricating advanced systems and devices for visible nanophotonics. However, the lack of simulation and optimization methods taking into account the essential physics of the optimization process leads to barriers for greater adoption. This issue can often result in sub-optimal optical responses in fabricated devices on both local and global scales. We propose that physics-informed design and optimization methods, and in particular physics-informed machine learning, are particularly well-suited to overcome these challenges by incorporating known physics, constraints, and fabrication knowledge directly into the design framework.
Deformable Laplace transform and its applications
Authors: Ahuja Priyanka , Ujlayan Amit , Sharma Dinkar , Pratap Hari 
Published: March 2023

Abstract
Recently, the deformable derivative and its properties have been introduced. In this work, we have investigated the concept of deformable Laplace transform (DLT) in more detail. Furthermore, some classical properties of the DLT are also included. The Heaviside expansion formula and convolution theorem for deformable inverse Laplace transform are also discussed. Furthermore, some illustrative numerical examples are also discussed to validate the applicability of the proposed DLT and finally conclude the theory.
Addition of bentonite to cationic starch matrix for coating on kraftliner paper to improve grease resistance
Authors: Santos Allan de Amorim dos , Matos Lays Camila , Mendonça Maressa Carvalho , Muguet Marcelo Coelho dos Santos , Ponzecchi Andrea , Sanadi Anand Ramesh , Tonoli Gustavo Henrique Denzin 
Published: March 2023

Abstract
In this work, we aimed to analyze suspensions of cationic starch by adding 5 wt%, 7 wt%, and 10 wt% of bentonite as a bilayer coating on kraftliner paper (85 g/m2). The controls were doubly-wet-and-dry and uncoated kraftliner paper. In a coating machine, the formulations were applied until reaching a grammage of 15 g/m2 and then dried at 103 ± 2 °C. The test was carried out about pH, solids content, and viscosity of the suspensions. The physical characteristics of the coated papers were evaluated, as well as their ability to block water, water vapor, and oil/grease. We also analyzed with scanning electron microscopy, Raman spectroscopy, and Fourier transform infrared spectroscopy. The packaging, having a water contact angle of up to 78° and 189 g/m² for Cobb, showed a low resistance to water, which is further responsible for decreased mechanical resistance. Nevertheless, the coating did not change the permeability to water vapor, however, bentonite promoted a decrease in wettability and Cobb value of the paper. The addition of 7 wt% bentonite to the cationic starch matrix promoted high oil resistance with 12 for kit-oil, while 10 wt% bentonite promoted greater pencil hardness, with a value of 8H. Bentonite strength and cationic starch showed good interaction, increasing oil resistance.
Soil fertility and pomelo yield influenced by soil conservation practices
Authors: Van Dung Tran , Van Dang Le , Ngoc Ngo Phuong , Hung Ngo Ngoc 
Published: March 2023

Abstract
Exchangeable cations and soil nutrients leach out/lost in the raised bed soils system through irrigation water and rainwater. Cover crops or crop residue mulching are considered sustainable agricultural measures because they prevent soil degradation and compaction and increase the soil ecological diversity. However, the impact of these on soil quality in fruit orchards in the Vietnamese Mekong Delta is not well studied. The present work aimed to assess the effect of cover crops (grass, pinto peanut) and rice straw mulching on change in soil chemical properties and productivity of pomelo. The 3-year (2019–2021) field experiment was conducted at Phu Huu Commune, Chau Thanh District, Hau Giang Province, Vietnam. Four treatments, control (no-cover crop), grass cover crop, mulching with rice straw (MRS), and pinto peanut cover crop were used. Soil samples were collected from the depth of 0–20 and 20–40 cm for analyzing soil pH, total nitrogen (TN), total phosphorus (TP), available phosphorus (AP), and soil organic matter (SOM). Results showed that MRS or cover crop by pinto peanut significantly decreased soil acidity in the topsoil layer. Soil fertility properties (TN, TP, AP, and SOM) at the depth 0–20 cm were greatly improved after the application of the mulched rice straw and cover crop by legume, thus improving pomelo yield. Further study is required to understand the effects of the cover crop with pinto peanut and rice straw mulching on the physical and biological properties of soil as well as nutrient uptake of pomelo orchards.
Bioconvection effect in the Carreau nanofluid with Cattaneo–Christov heat flux using stagnation point flow in the entropy generation: Micromachines level study
Authors: Li Shuguang , Ali Farhan , Zaib A. , Loganathan K. , Eldin Sayed M. , Ijaz Khan M. 
Published: March 2023

Abstract
The addition of gyrotactic microbes in the nanoparticles is essential to embellish the thermal efficiency of many systems such as microbial fuel cells, bacteria-powered micro-mixers, micro-volumes like microfluidics devices, enzyme biosensor, and chip-shaped microdevices like bio-microsystems. This analysis investigates the second law analysis in the bioconvection flow of a Carreau nanoliquid through a convectively stretching surface. The heat transports characteristics encountered with Cattaneo–Christove heat flux and thermal radiation. The Buongiorno model is used for nanoliquid, which comprises the Brownian motion and thermophoretic. The appropriate transformation is invoked to change the system of the partial differential equation into ordinary differential equations. Afterward, these equations are classified analytically with the help of the homotopy analysis method. The influence of numerous physical variables is interpreted and elaborated via graphs. The tabular result shows the numerical consequences of different physical flow parameters. It is examined that a more significant Weissenber number

We

{\rm{We}}

results in deprecation in the velocity field. It is appraised that the temperature profile reduces to augment the value of thermal relaxation time. Justification of the current work has existed through previous publishing results. The utilization of Carreau nanoparticles in the shear rate-dependent viscous fluid is of significant importance due to their potential to improve heat and mass transmission.
A systematic review of the effects of transcranial photobiomodulation on brain activity in humans
Authors: Dole Marjorie , Auboiroux Vincent , Langar Lilia , Mitrofanis John 
Published: March 2023

Abstract
In recent years, transcranial photobiomodulation (tPBM) has been developing as a promising method to protect and repair brain tissues against damages. The aim of our systematic review is to examine the results available in the literature concerning the efficacy of tPBM in changing brain activity in humans, either in healthy individuals, or in patients with neurological diseases. Four databases were screened for references containing terms encompassing photobiomodulation, brain activity, brain imaging, and human. We also analysed the quality of the included studies using validated tools. Results in healthy subjects showed that even after a single session, tPBM can be effective in influencing brain activity. In particular, the different transcranial approaches – using a focal stimulation or helmet for global brain stimulation – seemed to act at both the vascular level by increasing regional cerebral blood flow (rCBF) and at the neural level by changing the activity of the neurons. In addition, studies also showed that even a focal stimulation was sufficient to induce a global change in functional connectivity across brain networks. Results in patients with neurological disease were sparser; nevertheless, they indicated that tPBM could improve rCBF and functional connectivity in several regions. Our systematic review also highlighted the heterogeneity in the methods and results generated, together with the need for more randomised controlled trials in patients with neurological diseases. In summary, tPBM could be a promising method to act on brain function, but more consistency is needed in order appreciate fully the underlying mechanisms and the precise outcomes.
Prolegomena a una nuova edizione critica delle opere volgari di Bonvesin da la Riva
Authors: Wilhelm Raymund 
Published: March 2023

Abstract
Our perception of the vernacular works of Bonvesin da la Riva is still largely shaped by the editions of Gianfranco Contini (1941 and 1960). A reassessment of Bonvesin in terms of language and literary history can only start from a reflection on the textual basis of his works. The high quality of the Berlin manuscript (ca. 1300), which contains about half of Bonvesin’s oeuvre, is undisputed. However, the “retranslation” of the texts contained exclusively in later manuscripts which converts them into the form of the codex optimus, as still practised by Gökçen (2001), seems unacceptable today. Rather, the aim should be to identify different linguistic, stylistic and textual tendencies of the individual works by making recourse to the entire textual tradition. In this context, the assumption of an absolutely regular metrical form of the alexandrine, which has been advocated since Salvioni and Contini, is becoming increasingly questionable. It is suggested that Bonvesin’s poetry should be considered in the light of the tradition of anisosyllabism, which was well attested in the 13th century. The hypothesis of a “dialectal authenticity” of Bonvesin’s language is also problematic. Rather, an edition must preserve the constitutive polymorphism of the medieval scripta. Overall, the aim must be to recognise the distinctive personality of the medieval poet in the heterogeneity and variability of the surviving texts, beyond anachronistic expectations of a “classic”.
Neural Index of Reinforcement Learning Predicts Improved Stimulus–Response Retention under High Working Memory Load
Authors: Rac-Lubashevsky Rachel , Cremer Anna , Collins Anne G.E. , Frank Michael J. , Schwabe Lars 
Published: March 2023

Human learning and decision-making are supported by multiple systems operating in parallel. Recent studies isolating the contributions of reinforcement learning (RL) and working memory (WM) have revealed a trade-off between the two. An interactive WM/RL computational model predicts that although high WM load slows behavioral acquisition, it also induces larger prediction errors in the RL system that enhance robustness and retention of learned behaviors. Here, we tested this account by parametrically manipulating WM load during RL in conjunction with EEG in both male and female participants and administered two surprise memory tests. We further leveraged single-trial decoding of EEG signatures of RL and WM to determine whether their interaction predicted robust retention. Consistent with the model, behavioral learning was slower for associations acquired under higher load but showed parametrically improved future retention. This paradoxical result was mirrored by EEG indices of RL, which were strengthened under higher WM loads and predictive of more robust future behavioral retention of learned stimulus–response contingencies. We further tested whether stress alters the ability to shift between the two systems strategically to maximize immediate learning versus retention of information and found that induced stress had only a limited effect on this trade-off. The present results offer a deeper understanding of the cooperative interaction between WM and RL and show that relying on WM can benefit the rapid acquisition of choice behavior during learning but impairs retention.SIGNIFICANCE STATEMENTSuccessful learning is achieved by the joint contribution of the dopaminergic RL system and WM. The cooperative WM/RL model was productive in improving our understanding of the interplay between the two systems during learning, demonstrating that reliance on RL computations is modulated by WM load. However, the role of WM/RL systems in the retention of learned stimulus–response associations remained unestablished. Our results show that increased neural signatures of learning, indicative of greater RL computation, under high WM load also predicted better stimulus–response retention. This result supports a trade-off between the two systems, where degraded WM increases RL processing, which improves retention. Notably, we show that this cooperative interplay remains largely unaffected by acute stress.