bluuebunny/crossref_metadata_2025_split huggingface dataset:
Frustration can Limit the Adaptation of Promiscuous Enzymes Through Gene Duplication and Specialisation
Authors: Schmutzer Michael , Dasmeh Pouria , Wagner Andreas 
Published: March 2024

AbstractVirtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a ‘frustrated’ state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.
A new incubation system to simultaneously measure N2 as well as N2O and CO2 fluxes from plant-soil mesocosms
Authors: Yankelzon Irina , Willibald Georg , Dannenmann Michael , Malique Francois , Ostler Ulrike , Scheer Clemens , Butterbach-Bahl Klaus 
Published: March 2024

AbstractThis study presents a novel plant-soil mesocosm system designed for cultivating plants over periods ranging from days to weeks while continuously measuring fluxes of N2, N2O and CO2. For proof of concept, we conducted a 33-day incubation experiment using six soil mesocosms, with three containing germinated wheat plants and three left plant-free. To validate the magnitude of N2 and N2O fluxes, we used 15N-enriched fertilizer and a 15N mass balance approach. The system inherent leakage rate was about 55 µg N m− 2 h− 1 for N2, while N2O leakage rates were below the detection limit (< 1 µg N m− 2 h− 1). In our experiment, we found higher cumulative gaseous N2 + N2O losses in sown soil (0.34 ± 0.02 g N m− 2) as compared to bare soil (0.23 ± 0.01 g N m− 2). N2 fluxes accounted for approximately 94–96% of total gaseous N losses in both planted and unplanted mesocosms. N losses, as determined by the 15N mass balance approach, were found to be 1.7 ± 0.5 g N m− 2 for the sown soil and 1.7 ± 0.6 g N m− 2 for the bare soil, indicating an inconsistency between the two assessment methods. Soil respiration rates were also higher in sown mesocosms, with cumulative soil and aboveground biomass CO2 respiration reaching 4.8 ± 0.1 and 4.0 ± 0.1 g C m− 2 over the 33-day incubation period, in sown and bare soil, respectively. Overall, this study measured the effect of wheat growth on soil denitrification, highlighting the sensitivity and utility of this advanced incubation system for such studies.
Stroke frequency, associated factors, and clinical features in primary systemic vasculitis: a multicentric observational study
Authors: Geraldes Ruth , Santos Monica , Ponte Cristina , Craven Anthea , Barra Lillian , Robson Joanna C. , Hammam Nevin , Springer Jason , Henes Jöerg , Hocevar Alojzija , Putaala Jukka , Santos Ernestina , Rajasekhar Liza , Daikeler Thomas , Karadag Omer , Costa Andreia , Khalidi Nader , Pagnoux Christian , Canhão Patrícia , Melo Teresa Pinho e , Fonseca Ana Catarina , Ferro José M. , Fonseca João Eurico , Suppiah Ravi , Watts Richard A. , Grayson Peter , Merkel Peter A. , Luqmani Raashid A. ,   the DCVAS Study Group
Published: March 2024

Abstract
Objectives
The cerebral vessels may be affected in primary systemic vasculitis (PSV), but little is known about cerebrovascular events (CVEs) in this population. This study aimed to determine the frequency of CVEs at the time of diagnosis of PSV, to identify factors associated with CVEs in PSV, and to explore features and outcomes of stroke in patients with PSV.

Methods
Data from adults newly diagnosed with PSV within the Diagnostic and Classification Criteria in VASculitis (DCVAS) study were analysed. Demographics, risk factors for vascular disease, and clinical features were compared between patients with PSV with and without CVE. Stroke subtypes and cumulative incidence of recurrent CVE during a prospective 6-month follow-up were also assessed.

Results
The analysis included 4828 PSV patients, and a CVE was reported in 169 (3.50%, 95% CI 3.00–4.06): 102 (2.13% 95% CI 1.73–2.56) with stroke and 81 (1.68% 95% CI 1.33–2.08) with transient ischemic attack (TIA). The frequency of CVE was highest in Behçet’s disease (9.5%, 95% CI 5.79–14.37), polyarteritis nodosa (6.2%, 95% CI 3.25–10.61), and Takayasu’s arteritis (6.0%, 95% CI 4.30–8.19), and lowest in microscopic polyangiitis (2.2%, 95% CI 1.09–3.86), granulomatosis with polyangiitis (2.0%, 95% CI 1.20–3.01), cryoglobulinaemic vasculitis (1.9%, 95% CI 0.05–9.89), and IgA-vasculitis (Henoch-Schönlein) (0.4%, 95% CI 0.01–2.05). PSV patients had a 11.9% cumulative incidence of recurrent CVE during a 6-month follow-up period.

Conclusion
CVEs affect a significant proportion of patients at time of PSV diagnosis, and the frequency varies widely among different vasculitis, being higher in Behçet’s. Overall, CVE in PSV is not explained by traditional vascular risk factors and has a high risk of CVE recurrence.
Clinicopathological analysis of thyroid carcinomas with the RET and NTRK fusion genes: characterization for genetic analysis
Authors: Okubo Yoichiro , Toda Soji , Kadoya Mei , Sato Shinya , Yoshioka Emi , Hasegawa Chie , Ono Kyoko , Washimi Kota , Yokose Tomoyuki , Miyagi Yohei , Masudo Katsuhiko , Iwasaki Hiroyuki , Hayashi Hiroyuki 
Published: March 2024

AbstractThyroid carcinomas exhibit various genetic alterations, including the RET and NTRK fusion genes that are targets for molecular therapies. Thus, detecting fusion genes is crucial for devising effective treatment plans. This study characterized the pathological findings associated with these genes to identify the specimens suitable for genetic analysis. Thyroid carcinoma cases positive for the fusion genes were analyzed using the Oncomine Dx Target Test. Clinicopathological data were collected and assessed. Among the 74 patients tested, 8 had RET and 1 had NTRK3 fusion gene. Specifically, of the RET fusion gene cases, 6 exhibited “BRAF-like” atypia and 2 showed “RAS-like” atypia, while the single case with an NTRK3 fusion gene presented “RAS-like” atypia. Apart from one poorly differentiated thyroid carcinoma, most cases involved papillary thyroid carcinomas (PTCs). Primary tumors showed varied structural patterns and exhibited a high proportion of non-papillary structures. Dysmorphic clear cells were frequently observed. BRAF V600E immunoreactivity was negative in all cases. Interestingly, some cases exhibited similarities to diffuse sclerosing variant of PTC characteristics. While calcification in lymph node metastases was mild, primary tumors typically required hydrochloric acid-based decalcification for tissue preparation. This study highlights the benefits of combining morphological and immunohistochemical analyses for gene detection and posits that lymph node metastases are more suitable for genetic analysis owing to their mild calcification. Our results emphasize the importance of accurate sample processing in diagnosing and treating thyroid carcinomas.
Pyodermatitis-pyostomatitis vegetans: a case report and systematic review focusing on oral involvement
Authors: Chrcanovic Bruno Ramos , Martins-Chaves Roberta Rayra , Pontes Flávia Sirotheau Correa , Fonseca Felipe Paiva , Pontes Hélder Antônio Rebelo , Gomez Ricardo Santiago 
Published: March 2024

Abstract
Background
Pyodermatitis-pyostomatitis vegetans (PPV) is a rare mucocutaneous disease characterized by multiple pustules and it is considered a marker for inflammatory bowel disease (IBD). The oral manifestations of this condition are referred to as pyostomatitis vegetans (PSV).

Purpose
To investigate which features could help in establishing the diagnosis of PSV, with or without cutaneous lesions, based on information retrieved from all cases of PSV described in the literature. A case of PV from the authors was also included in the analysis.

Methods
An electronic search was undertaken, last updated in August 2022. Inclusion criteria included publications reporting cases of PSV, with the diagnosis confirmed by the pathological examination of oral or skin lesions, and presence of IBD.

Results/Conclusions
Sixty-two publications with 77 cases of PSV and an associated IBD were included. Features that are helpful in establishing the diagnosis of PSV are snail track appearance of oral lesions, an associated IBD (which is not always symptomatic), evidence of intraepithelial clefting on microscopic examination of oral lesions, and peripheral blood eosinophilia. A gold standard for the management of PSV does not exist and high-level evidence is limited. There is no established therapeutic protocol for PSV and management primarily consists of topical and/or systemic corticosteroids, antirheumatic drugs (sulfasalazine, mesalazine), monoclonal antibody (infliximab, adalimumab) immunosuppressives (azathioprine, methotrexate), antibiotics (dapsone), or a combination of these. The risk of recurrence of oral lesions is considerable when the medication dose is decreased or fully interrupted.
Structured interpolation for multivariate transfer functions of quadratic-bilinear systems
Authors: Benner Peter , Gugercin Serkan , Werner Steffen W. R. 
Published: March 2024

AbstractHigh-dimensional/high-fidelity nonlinear dynamical systems appear naturally when the goal is to accurately model real-world phenomena. Many physical properties are thereby encoded in the internal differential structure of these resulting large-scale nonlinear systems. The high dimensionality of the dynamics causes computational bottlenecks, especially when these large-scale systems need to be simulated for a variety of situations such as different forcing terms. This motivates model reduction where the goal is to replace the full-order dynamics with accurate reduced-order surrogates. Interpolation-based model reduction has been proven to be an effective tool for the construction of cheap-to-evaluate surrogate models that preserve the internal structure in the case of weak nonlinearities. In this paper, we consider the construction of multivariate interpolants in frequency domain for structured quadratic-bilinear systems. We propose definitions for structured variants of the symmetric subsystem and generalized transfer functions of quadratic-bilinear systems and provide conditions for structure-preserving interpolation by projection. The theoretical results are illustrated using two numerical examples including the simulation of molecular dynamics in crystal structures.
A chaotic based image encryption scheme using elliptic curve cryptography and genetic algorithm
Authors: Kumar Sanjay , Sharma Deepmala 
Published: March 2024

AbstractIn the era of digital communication and data security, image encryption plays a crucial role in safeguarding sensitive information. Protecting sensitive visual data from unauthorized access drives the pursuit of advanced image encryption methods. This paper proposes a novel approach to enhance image encryption by combining the power of a chaotic map, elliptic curve cryptography, and genetic algorithm. The chaotic map, specifically Arnold’s cat map, is employed to introduce chaos and randomness into the encryption process. The proposed image encryption process involves applying Arnold’s cat map for shuffling the pixel positions, followed by elliptic curve cryptography for encrypting the pixel values using public and private keys. Additionally, a genetic algorithm is employed to optimize the key generation process, enhancing the security of the encryption scheme. The combined utilization of these techniques aims to achieve a high level of confidentiality and robustness in image encryption. The algorithm underwent thorough analysis. It achieved a maximum entropy score of 7.99, indicating a high level of randomness and unpredictability in the encrypted data. Additionally, it exhibited near-zero correlation, which suggests strong resistance against statistical attacks. Moreover, the cryptographic range of possible keys was found to be $$2^{511}$$

2
511

. This extensive key space makes the algorithm highly resilient against brute force attacks. It took only 0.5634 s to encrypt a moderately sized $$512\times 512$$

512
×
512

pixel image with an 8-bit image on a standard desktop computer with a 2.3 GHz processor and 16 GB of RAM. The experimental findings confirm that the proposed approach is highly effective and efficient in safeguarding sensitive image data from unauthorized access and potential attacks. This scheme has the benefit of allowing us to protect our private image data while it’s being transmitted.
Toxicological insight of magnetite nanogel: neuro-ethological, hepato-renal, antioxidant, and histopathological traits in Clarias gariepinus
Authors: Kamel Samar , Ahmed Shaimaa A. A. , Elsayyad Asmaa , Abdelwarith Abdelwahab A. , Younis Elsayed M. , Shaalan Mohamed , Gaballa Mohamed M. S. , Mahboub Heba H. , Khamis Tarek , Ismail Sameh H. , Davies Simon J. , Hassan Zeinab 
Published: March 2024

AbstractAssessment of acute toxicity of magnetic nanogel (MNG) is crucial to conclude the safe applicable dose and to warrant its application in aquaculture. Therefore, the current study is a novel step to assess behavior, neuro-stress response, hepato-renal, oxidative, and histopathological variations produced by MNG’ acute toxicity in Clarias gariepinus. Two experiments were conducted: the first was a determination of the 96-h lethal concentration 50 (LC50) of MNG in C. gariepinus. Meanwhile, the second was an assessment of the toxicological impacts of three different concentrations of MNG in C. gariepinus following a 10-day exposure period and a subsequent 10-day depuration trial. One hundred and eighty fish were allotted to four groups exposed to 0, 1/10, 1/8, or 1/5 96-h LC50 of MNG. The outcomes exhibited that 96-h LC50 of MNG for C. gariepinus was 44 mg/L. The subjected group to MNG induced a concentration-dependent elevation in the serum values of cortisol, alanine transaminase, aspartate transaminase, urea, and creatinine following MNG exposure. Marked elevation in the oxidative stress indicators (catalase (CAT), glutathione S-transferase activity (GST), and superoxide dismutase (SOD)) was also evident. Meanwhile, the value of the neurological biomarker, acetylcholinesterase (AChE), was markedly reduced in a concentration-dependent way. These biochemical changes were complemented by pathological alterations in the hepato-renal architecture. Interestingly, in response to the 10-day depuration period, most of the tested parameters were eliminated in C. gariepinus exposed to 1/10 of LC50. Conclusively, MNG can induce numerous adverse effects only at higher doses (1/5 and 1/8 of LC50). Meanwhile, the lowest tested concentration of MNG (1/10 of LC50) was safe for application in aquaculture practices with only mild disruptions in the bio-indices. In addition, a retrieval period of 10 days was sufficient to renovate these alterations only in fish exposed to the same concentration.
Effectiveness of Vasopressin Against Cardiac Arrest: A Systematic Review of Systematic Reviews
Authors: Ho Jonathan Ka-Ming , Tam Hon-Lon , Leung Leona Yuen-Ling 
Published: March 2024

AbstractPurposeThis systematic review (SR) of SRs evaluates the effectiveness of vasopressin alone or in combination with other drugs in improving the outcomes of cardiac arrest (CA).MethodsUsing a three-step approach, we searched five databases to identify all relevant SRs. Two reviewers independently selected suitable studies, assessed study quality, and extracted relevant data. If an outcome was reported by multiple SRs, a re-meta-analysis was conducted as needed; otherwise, a narrative analysis was performed.ResultsTwelve SRs covering 16 original studies were included in this review. The meta-analysis results revealed a significant increase in survival to hospital admission for patients with in-hospital CA (IHCA) or out-of-hospital CA (OHCA) receiving vasopressin alone compared with that for those receiving epinephrine alone. Furthermore, the return of spontaneous circulation (ROSC) was significantly increased in patients with OHCA receiving vasopressin with epinephrine compared with that in those receiving epinephrine alone. Compared with patients with IHCA receiving epinephrine with placebo, those receiving vasopressin, steroids, and epinephrine (VSE) exhibited significant increases in ROSC, survival to hospital discharge, favorable neurological outcomes, mean arterial pressure, renal failure–free days, coagulation failure–free days, and insulin requirement.ConclusionVSE is the most effective drug combination for improving the short- and long-term outcomes of IHCA. It is recommended to use VSE in patients with IHCA. Future studies should investigate the effectiveness of VSE against OHCA and CA of various etiologies, the types and standard dosages of steroids for cardiac resuscitation, and the effectiveness of vasopressin–steroid in improving CA outcomes.
Decision making in complex land systems: outline of a holistic theory of agency
Authors: Christensen Andreas Aagaard , Van Eetvelde Veerle 
Published: March 2024

Abstract
Context
Models of human agency within research on land systems and landscapes do not fully account for social and cultural factors in decision making. Conversely, within social theory, parallel concepts of agency do not fully take biophysical and spatial factors into account. This calls for a synthesis of conceptual models addressing human decision making in land systems.

Objectives
The review identifies parallels between social and ecological perspectives on humans as co-constituent parts of complex land systems. On this basis selected models of agency combining insights from social theory and land systems research are outlined and compared, and improved concepts are outlined.

Methods
Elements of agency in modern agricultural land systems are reviewed. A case study illustrating the application of agency concepts in an analysis of decision making among farmers on the Canterbury Plains (New Zealand) is presented. On this basis it is discussed how to improve understandings of human agency in land systems.

Results
The review identifies and compares parallel conceptions of agency, practice and holism in landscape ecology and social theory. Taking the agency of farmers in contemporary agricultural landscapes as an example, theories currently used to characterise and interpret the agency of farmers are discussed and improvements considered. Potentials for improvement of current conceptual models are indicated and discussed, and an improved model of agency is suggested.

Conclusions
Based on the review, the article presents an improved conceptual model of agency in land systems emphasizing the position of agents in social-ecological contexts of action.
Multi-back-propagation Algorithm for Signal Neural Network Decomposition
Authors: Salgado Paulo , Perdicoúlis T.-P. Azevedo 
Published: March 2024

AbstractIn this paper, a novel back-propagation error technique is presented. This neural network structure allows for two fundamental basic modes: (1) To decompose the neurones by transforming their variables, weights, and scalar functions into vectors. This conveys for the decomposition of the transfer function of every neurone (where the output variables are the components of the decomposition) and, consequently, to be written as the invariant sum of orthogonal functions, with the safeguard of preserving information This orthogonality is proven using Fourier theory. (2) In a second mode, a tuned neural network that occupies one of the channels of the neural network can see the weights of its supplementary channels adjusted to retain additional information. Only the decomposition algorithm of the network is presented here—Multi-back-propagation algorithm. The adopted methodology is validated step-by-step with some representative examples. Namely, to assess the performance of the splitting method, two different examples have been constructed from scratch: (1) a 2D classification problem and (2) a 3D surface. In both problems, the signal and transfer functions of the neural network are successfully decomposed without information losses. Therefore, since the main contribution of this work is to allow for the organisation of the information stored in neural network structure, through a split process, this promising method shows potential use in various areas—e.g. classification and/or pattern recognition problems, data analysis, modelling and so on. In the future, we expect to work further in the method computational aspects to render it more efficient, versatile and robust.
Predictive machine learning for gully susceptibility modeling with geo-environmental covariates: main drivers, model performance, and computational efficiency
Authors: Phinzi Kwanele , Szabó Szilárd 
Published: March 2024

AbstractCurrently, machine learning (ML) based gully susceptibility prediction is a rapidly expanding research area. However, when assessing the predictive performance of ML models, previous research frequently overlooked the critical component of computational efficiency in favor of accuracy. This study aimed to evaluate and compare the predictive performance of six commonly used algorithms in gully susceptibility modeling. Artificial neural networks (ANN), partial least squares, regularized discriminant analysis, random forest (RF), stochastic gradient boosting, and support vector machine (SVM) were applied. The comparison was conducted under three scenarios of input feature set sizes: small (six features), medium (twelve features), and large (sixteen features). Results indicated that SVM was the most efficient algorithm with a medium-sized feature set, outperforming other algorithms across all overall accuracy (OA) metrics (OA = 0.898, F1-score = 0.897) and required a relatively short computation time (< 1 min). Conversely, ensemble-based algorithms, mainly RF, required a larger feature set to reach optimal accuracy and were computationally demanding, taking about 15 min to compute. ANN also showed sensitivity to the number of input features, but unlike RF, its accuracy consistently decreased with larger feature sets. Among geo-environmental covariates, NDVI, followed by elevation, TWI, population density, SPI, and LULC, were critical for gully susceptibility modeling. Therefore, using SVM and involving these covariates in gully susceptibility modeling in similar environmental settings is strongly suggested to ensure higher accuracy and minimal computation time.