bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of the Wear of a Repeatedly Disassembled Interference-Fit Joint Operating under Rotational Bending Conditions
Authors: Kowalski Sławomir , Barta Dalibor , Dižo Ján , Dittrich Aleš
Published: March 2023

The purpose of the investigations was to assess the influence of repeated sleeve assembly on the wear of forced-in joint elements. The test methodology assumed operating a forced-in joint in rotational bending conditions, dismantling the joint after every thousand fatigue cycles, and then joint reassembling. The total number of fatigue cycles was 106, or as many as needed for fatigue cracking. The macroscopic observations of the shaft surface demonstrated the traces of fretting wear in the form of randomly spaced grey and dark brown stains at the axle seat circumference close to the joint edge. The size and number of the wear traces would increase with the number of fatigue cycles. The top layer wear also depended on the number of sleeve/shaft assembly processes. The microscopic observations confirmed fretting wear, which developed on the shaft surface. Numerous instances of surface microabrasion as well as micropullouts and surface scratches were observed. Material build-ups were also observed, which would crack and migrate. The chemical analysis of the composition of wear products demonstrated the presence of iron and oxygen atoms, which confirms the oxidation of wear products. The measurement of the maximum force needed to remove the sleeve from the shaft after the next fatigue cycle showed the need to use a greater force each time; however, a smaller force was needed to press the sleeve onto the shaft. As a result of the development of fretting wear, shafts would become fatigue-worn after 3.6 × 106 fatigue cycles.
On Predictive Modeling Using a New Three-Parameters Modification of Weibull Distribution and Application
Authors: Tashkandy Yusra , Emam Walid
Published: March 2023

In this article, a new modification of the Weibull model with three parameters, the new exponential Weibull distribution (E-WD), is defined. The new model has many statistical advantages, the heavy-tailed behavior and the regular variation property were offered. Many of the important statistical functions of the modified model are presented in closed forms. The flexibility of E-WD has been improved. The proposed model can be used to fit data with different shapes, it can be right-skewed, left-skewed, decreasing, curved and symmetric. Some distribution properties of the proposed model, including moment generating function, characteristic function, moment, quantile and identifiability property, have been derived. In addition to the information generating function, the Shannon entropy and information energy are also discussed. The maximum likelihood approach and Bayesian estimation are used to estimate the distribution parameters. In the Bayesian method, three different loss functions are used. The calculations show the biases and estimated risks to obtain the best estimator. The bootstrap confidence intervals, the asymptotic confidence intervals and the observed variance-covariance matrix are obtained. Metropolis Hastings’ MCMC procedure is used for the calculations. We apply the composite distribution to stock data for four variables. The goodness-of-fit results show that the model performs well compared to its competitors. The proposed model can be used for forecasting and decision making.
Influence of Ingestion of Lactulose on γ-Lactones Emanating from Human Skin Surface
Authors: Sekine Yoshika , Uchiyama Shiori , Todaka Michihito , Sakai Yohei , Sakiyama Ryo , Ochi Hiroshi , Muramatsu Maho , Asai Satomi , Umezawa Kazuo
Published: March 2023

Lactulose is known to grow health-promoting bacteria, with an increase in the production of beneficial metabolites, such as lactic acid and short-chain fatty acids (SCFAs) in the colon. Ingestion of lactulose powder at a food dosage level is known to reduce the dermal emanation of ammonia, a typical human skin gas which potentially affects body odour. However, no study has reported the effect of lactulose on human skin gases other than ammonia. In this study, the influence of lactulose ingestion on the dermal emissions of γ-lactones, volatile cyclic esters with sweet smells, was investigated in healthy subjects. Healthy participants ingested the lactulose powder with a food dosage of 4 g d−1 once a day for 2 weeks. γ-lactones emanating from the skin surface were collected from each participant’s forearm by using a passive flux sampler, and six kinds of γ-lactones, namely, γ-hexalactone (C6), γ-heptalactone (C7), γ-octalactone (C8), γ-nonalactone (C9), γ-decalactone (C10), and γ-undecalactone (C11), were determined by gas chromatography–mass spectrometry. Quantification of bifidobacteria in faeces collected before and after ingestion of lactulose for 2 weeks was carried out by using real-time PCR. The results showed a significant increase in the dermal emission fluxes of sweet-smelling C10 and C11 lactones as the number of bifidobacteria increased in the faeces, presumably mediated by SCFAs produced in the colon.
Research on Applying the “Shift” Concept to Deep Attention Matching
Authors: Hu Kai , Xiao Nanfeng
Published: March 2023

The main purpose of chat robots is to realize intelligent interaction between human beings and chat robots. Generally, a complete conversation involves chat contexts. Before responding, human beings need to extract information from their chat contexts, and human beings are very good at extracting information. However, how to make the chatbots more complete in extracting appropriate contextual information has become a key issue for the chatbots in multi-round dialogues. Most research in recent years has paid attention to the point-to-point matching of responses and utterances at reciprocal granularity, such as SMN (Sequential Matching Network) and DAM (Deep Attention Matching Network), for which these parsing methods affect the effectiveness of the above networks to some extent. For example, DAM introduces an attention mechanism, which can obtain good results by parsing five levels of granularity of response and utterance through a self-attention module, and then matching the same level of granularity to mine similar spatial information in it. Based on the structure of DAM, this paper proposes an information-mining idea for improving DAM, which applies to those models with a multi-layer matching structure. Therefore, based on this idea, this paper presents two improved methods for DAM, so as to improve the accuracy of the information extraction from the contexts of the multiple round chats. The experiments show that the improved DAM has better results than that of the unimproved DAM, which are, respectively, R_2@1 increased by 0.425%, R_10@1 increased by 0.515%, R_10@2 increased by 0.341%, MAP (Mean Average Precision) increased by 0.358% in Douban data set, P@1 increased by 1.16%, R_10@1 increased by 1.17%, and these results are better than those state-of-the-art methods, and the improved methods presented in this paper can be used not only in DAM but also in other models with similar the point-to-point matching structures.
Toward Comprehensive Chronic Kidney Disease Prediction Based on Ensemble Deep Learning Models
Authors: Alsekait Deema Mohammed , Saleh Hager , Gabralla Lubna Abdelkareim , Alnowaiser Khaled , El-Sappagh Shaker , Sahal Radhya , El-Rashidy Nora
Published: March 2023

Chronic kidney disease (CKD) refers to the gradual decline of kidney function over months or years. Early detection of CKD is crucial and significantly affects a patient’s decreasing health progression through several methods, including pharmacological intervention in mild cases or hemodialysis and kidney transportation in severe cases. In the recent past, machine learning (ML) and deep learning (DL) models have become important in the medical diagnosis domain due to their high prediction accuracy. The performance of the developed model mainly depends on choosing the appropriate features and suitable algorithms. Accordingly, the paper aims to introduce a novel ensemble DL approach to detect CKD; multiple methods of feature selection were used to select the optimal selected features. Moreover, we study the effect of the optimal features chosen on CKD from the medical side. The proposed ensemble model integrates pretrained DL models with the support vector machine (SVM) as the metalearner model. Extensive experiments were conducted by using 400 patients from the UCI machine learning repository. The results demonstrate the efficiency of the proposed model in CKD prediction compared to other models. The proposed model with selected features using mutual_info_classi obtained the highest performance.
TMVDPatch: A Trusted Multi-View Decision System for Security Patch Identification
Authors: Zhou Xin , Pang Jianmin , Shan Zheng , Yue Feng , Liu Fudong , Xu Jinlong , Wang Junchao , Liu Wenfu , Liu Guangming
Published: March 2023

Nowadays, the time lag between vulnerability discovery and the timely remediation of the vulnerability is extremely important to the current state of cybersecurity. Unfortunately, the silent security patch presents a significant challenge. Despite related work having been conducted in this area, the patch identification lacks interpretability. To solve this problem, this paper first proposes a trusted multi-view security patch identification system called TMVDPatch. The system obtains evidence from message commit and code diff views respectively, and models the uncertainty of each view based on the D-S evidence theory, thereby providing credible and interpretable security patch identification results. On this basis, this paper performs weighted training on the original evidence based on the grey relational analysis method to improve the ability to make credible decisions based on multi-views. Experimental results show that the multi-view learning method exhibits excellent capabilities in terms of the complementary information provided by control dependency and data dependency, and the model shows strong robustness across different hyperparameter settings. TMVDPatch outperforms other models in all evaluation metrics, achieving an accuracy of 85.29% and a F1 score of 0.9001, clearly verifying the superiority of TMVDPatch in terms of accuracy, scientificity, and reliability.
An Intelligent Waste Management Application Using IoT and a Genetic Algorithm–Fuzzy Inference System
Authors: Thaseen Ikram Sumaiya , Mohanraj Vanitha , Ramachandran Sakthivel , Balakrishnan Anbarasu
Published: March 2023

The Internet of Things (IoT) is being used to create new applications for smart cities. Waste management is one issue that requires various IoT components for assistance, such as RFIDs and sensors. An efficient and innovative waste collection system is required to minimize investment, operational, and expenditure costs. In this paper, the novel idea is to develop an intelligent waste management model for smart cities using a hybrid genetic algorithm (GA)–fuzzy inference engine. The system can read, collect, and process information intelligently using a fuzzy inference engine that decides dynamically how to manage a waste collection. The aim of this model is to enhance its correctness and robustness, primarily, in addition to reducing errors that arise due to working conditions. GA is used for optimization to determine the best combination of rules for the fuzzy inference system (FIS). A Mamdani model is used to estimate waste management. The proposed model uses sensors to collect vital information, and FIS is trained using fuzzy logic to determine the probability that the smart bin is nearly full. The primary issue with the traditional genetic algorithm is that during the execution of the algorithm, there is a possibility of essential gene loss. The essential gene loss refers to information relevant to location, details regarding waste filling parameters, etc., which may lead to efficiency or accuracy loss. This problem is overcome by integrating fuzzy logic with a genetic algorithm to identify crucial genes by preserving the FIS interpretability. Our system uses cost-effective, small-size sensors and ensures this solution is reproducible. The Proteus simulator is used for experiments, and satisfactory results are obtained. Overall accuracy, precision, and recall of 95.44%, 96.68%, and 93.96% are obtained in the proposed model. Classification of recyclable items is also performed, and accuracy is determined for every item, resulting in the minimization of resource waste. The cost of manual interpretation is minimized in the intelligent smart waste management system in comparison to the traditional approach, as shown in the experiments.
A Rule-Based Approach for Mining Creative Thinking Patterns from Big Educational Data
Authors: Shabani Nasrin , Beheshti Amin , Farhood Helia , Bower Matt , Garrett Michael , Alinejad-Rokny Hamid
Published: March 2023

Numerous studies have established a correlation between creativity and intrinsic motivation to learn, with creativity defined as the process of generating original and valuable ideas, often by integrating perspectives from different fields. The field of educational technology has shown a growing interest in leveraging technology to promote creativity in the classroom, with several studies demonstrating the positive impact of creativity on learning outcomes. However, mining creative thinking patterns from educational data remains a challenging task, even with the proliferation of research on adaptive technology for education. This paper presents an initial effort towards formalizing educational knowledge by developing a domain-specific Knowledge Base that identifies key concepts, facts, and assumptions essential for identifying creativity patterns. Our proposed pipeline involves modeling raw educational data, such as assessments and class activities, as a graph to facilitate the contextualization of knowledge. We then leverage a rule-based approach to enable the mining of creative thinking patterns from the contextualized data and knowledge graph. To validate our approach, we evaluate it on real-world datasets and demonstrate how the proposed pipeline can enable instructors to gain insights into students’ creative thinking patterns from their activities and assessment tasks.
Reframing Migrant Narratives through Arts Practice
Authors: Marchevska Elena , Defrin Carolyn
Published: March 2023

In this article, we reflect on our collaborative practice-as-research piece Project Finding Home, that arose from our experiences of working and living in the UK as ‘non-British’ citizens. Engaging with other refugee and migrant artists over three years, we worked deliberately as co-researchers and co-creators in a non-hierarchical dynamic to produce a series of four films reflecting on how we find home when it is so impacted by government policy, social and cultural integration, and intergenerational relationships. This article focuses on two of these films, one made with the participatory theatre company of Sanctuary, PSYCHEdelight, and one made with conceptual artist, Khaled Barakeh. Through observations of their work, we discuss how their respective uses of comedy (in PSYCHEdelight’s show Mohand and Peter) and visual representation (in Barakeh’s installation On the Ropes) resist singular views of migrant narratives. Additionally, we analyse our creative and ethical processes for making films with them about their work. Discussing how their aesthetics informed our processes for showcasing who they are and what they do as artists to a wider audience, we examine how artistic practice, its documentation, and its dissemination can question dominant aesthetic norms and existing migration and cultural policies in the UK and Europe.
Performance Analysis of a Zero-Energy Building Using Photovoltaics and Hydrogen Storage
Authors: Bellos Evangelos , Lykas Panagiotis , Tzivanidis Christos
Published: March 2023

The exploitation of renewable energy sources in the building sector is a challenging aspect of achieving sustainability. The incorporation of a proper storage unit is a vital issue for managing properly renewable electricity production and so to avoid the use of grid electricity. The present investigation examines a zero-energy residential building that uses photovoltaics for covering all its energy needs (heating, cooling, domestic hot water, and appliances-lighting needs). The building uses a reversible heat pump and an electrical heater, so there is not any need for fuel. The novel aspect of the present analysis lies in the utilization of hydrogen as the storage technology in a power-to-hydrogen-to-power design. The residual electricity production from the photovoltaics feeds an electrolyzer for hydrogen production which is stored in the proper tank under high pressure. When there is a need for electricity, and the photovoltaics are not enough, the hydrogen is used in a fuel cell for producing the needed electricity. The present work examines a building of 400 m2 floor area in Athens with total yearly electrical demand of 23,656 kWh. It was found that the use of 203 m2 of photovoltaics with a hydrogen storage capacity of 34 m3 can make the building autonomous for the year period.
The Shapes of Stellar Spectra
Authors: Allende Prieto Carlos
Published: March 2023

Stellar atmospheres separate the hot and dense stellar interiors from the emptiness of space. Radiation escapes from the outermost layers of a star, carrying direct physical information. Underneath the atmosphere, the very high opacity keeps radiation thermalized and resembling a black body with the local temperature. In the atmosphere the opacity drops, and radiative energy leaks out, which is redistributed in wavelength according to the physical processes by which matter and radiation interact, in particular photoionization. In this article, I will evaluate the role of photoionization in shaping the stellar energy distribution of stars. To that end, I employ simple, state-of-the-art plane-parallel model atmospheres and a spectral synthesis code, dissecting the effects of photoionization from different chemical elements and species, for stars of different masses in the range of 0.3 to 2 M⊙. I examine and interpret the changes in the observed spectral energy distributions of the stars as a function of the atmospheric parameters. The photoionization of atomic hydrogen and H− are the most relevant contributors to the continuum opacity in the optical and near-infrared regions, while heavier elements become important in the ultraviolet region. In the spectra of the coolest stars (spectral types M and later), the continuum shape from photoionization is no longer recognizable due to the accumulation of lines, mainly from molecules. These facts have been known for a long time, but the calculations presented provide an updated quantitative evaluation and insight into the role of photoionization on the structure of stellar atmospheres.
New Iterative Scheme Involving Self-Adaptive Method for Solving Mixed Variational Inequalities
Authors: Mukheimer Aiman , Ullah Saleem , Bux Muhammad , Arif Muhammad Shoaib , Abodayeh Kamaleldin
Published: March 2023

Variational inequalities (VI) problems have been generalized and expanded in various ways. The VI principle has become a remarkable study area combining pure and applied research. The study of variational inequality in mathematics is significantly aided by providing an important framework by fixed-point theory. The concept of fixed-point theory can be considered an inherent component of the VI. We consider a mixed variational inequality (MVI) a useful generalization of a classical variational inequality. The projection method is not applicable to solve MVI due to the involvement of the nonlinear term ϕ. MVI is equivalent to fixed-point problems and the resolvent equation techniques. This technique is commonly used in the research on the existence of a solution to the MVI. This paper uses a new self-adaptive method using step size to modify the fixed-point formulation for solving the MVI. We will also provide the convergence of the proposed scheme. Our output could be seen as a significant refinement of the previously known results for MVI. A numerical example is also provided for the implementation of the generated algorithm.
Between Soft θ-Openness and Soft ω0-Openness
Authors: Al Ghour Samer
Published: March 2023

In this paper, we define and investigate soft ωθ-open sets as a novel type of soft set. We characterize them and demonstrate that they form a soft topology that lies strictly between the soft topologies of soft θ-open sets and soft ω0-open sets. Moreover, we show that soft ωθ-open sets and soft ω0-open sets are equivalent for soft regular spaces. Furthermore, we investigate the connections between particular types of soft sets in a given soft anti-locally countable space and the soft topological space of soft ωθ-open sets generated by it. In addition to these, we define soft ωθ,ω-sets and soft ωθ,θ-sets as two classes of sets, and via these sets, we introduce two decompositions of soft θ-open sets and soft ωθ-open sets, respectively. Finally, the relationships between these three new classes of soft sets and their analogs in general topology are examined.
MXene-Based Materials for Multivalent Metal-Ion Batteries
Authors: Wang Chunlei , Pan Zibing , Chen Huaqi , Pu Xiangjun , Chen Zhongxue
Published: March 2023

Multivalent metal ion (Mg2+, Zn2+, Ca2+, and Al3+) batteries (MMIBs) emerged as promising technologies for large-scale energy storage systems in recent years due to the abundant metal reserves in the Earth’s crust and potentially low cost. However, the lack of high-performance electrode materials is still the main obstacle to the development of MMIBs. As a newly large family of two-dimensional transition metal carbides, nitrides, and carbonitrides, MXenes have attracted growing focus in the energy storage field because of their large specific surface area, excellent conductivity, tunable interlayer spaces, and compositional diversity. In particular, the multifunctional chemistry and superior hydrophilicity enable MXenes to serve not only as electrode materials but also as important functional components for heterojunction composite electrodes. Herein, the advances of MXene-based materials since its discovery for MMIBs are summarized, with an emphasis on the rational design and controllable synthesis of MXenes. More importantly, the fundamental understanding of the relationship between the morphology, structure, and function of MXenes is highlighted. Finally, the existing challenges and future research directions on MXene-based materials toward MMIBs application are critically discussed and prospected.
Textile PAN Carbon Fibers Cathode for High-Voltage Seawater Batteries
Authors: Ferreira João , Salgueiro Tiago , Marcuzzo Jossano , Arruda Eduardo , Ventura João , Oliveira Joana
Published: March 2023

Rechargeable sodium seawater batteries (SWBs) are gaining the world leadership of high voltage energy storage devices for marine environments. With natural seawater as the source of active material, SWBs can be supplied infinitely with Na cations. Because of their open-structured cathode, the cathode material’s specific surface area, porosity and wettability need to be optimized to achieve a high-performance cell. In this work, activated textile polyacrylonitrile (PAN) fibers were used to produce an activated carbon felt with a facile manufacturing process. The easy and low-cost production of these fibers makes them excellent candidates for energy storage applications involving oxygen evolution and reduction reactions. The electrochemical performance results of the fabricated activated PAN fibers and of commercial carbon felts were measured and compared, being characterized through galvanostic charge discharge cycles, electrochemical impedance spectroscopy and cyclic voltammetries. A performance improvement was observed with PAN activated carbon felt as half cell with a capacitance increase (about 9000%), and as full cell with a smaller voltage gap (about 10%) and increased gravimetric capacitance (about 260%) when compared to the commercial carbon felt. The successful implementation of PAN activated carbon felts in an aqueous environment opens new paths toward high performance seawater battery’s cathodes.
Animal Disease Models and Patient-iPS-Cell-Derived In Vitro Disease Models for Cardiovascular Biology—How Close to Disease?
Authors: Kawaguchi Nanako , Nakanishi Toshio
Published: March 2023

Currently, zebrafish, rodents, canines, and pigs are the primary disease models used in cardiovascular research. In general, larger animals have more physiological similarities to humans, making better disease models. However, they can have restricted or limited use because they are difficult to handle and maintain. Moreover, animal welfare laws regulate the use of experimental animals. Different species have different mechanisms of disease onset. Organs in each animal species have different characteristics depending on their evolutionary history and living environment. For example, mice have higher heart rates than humans. Nonetheless, preclinical studies have used animals to evaluate the safety and efficacy of human drugs because no other complementary method exists. Hence, we need to evaluate the similarities and differences in disease mechanisms between humans and experimental animals. The translation of animal data to humans contributes to eliminating the gap between these two. In vitro disease models have been used as another alternative for human disease models since the discovery of induced pluripotent stem cells (iPSCs). Human cardiomyocytes have been generated from patient-derived iPSCs, which are genetically identical to the derived patients. Researchers have attempted to develop in vivo mimicking 3D culture systems. In this review, we explore the possible uses of animal disease models, iPSC-derived in vitro disease models, humanized animals, and the recent challenges of machine learning. The combination of these methods will make disease models more similar to human disease.
Host Feeding Patterns of Mansonia (Diptera, Culicidae) in Rural Settlements near Porto Velho, State of Rondonia, Brazil
Authors: Alonso Diego Peres , Amorim Jandui Almeida , de Oliveira Tatiane Marques Porangaba , de Sá Ivy Luizi Rodrigues , Possebon Fábio Sossai , de Carvalho Dario Pires , Ribeiro Kaio Augusto Nabas , Ribolla Paulo Eduardo Martins , Sallum Maria Anice Mureb
Published: March 2023

Mosquito females of the genus Mansonia (Blanchard) can be a nuisance to humans and animals since they are voraciously hematophagous and feed on the blood of a variety of vertebrates. Despite their relevance, there is a lack of investigation into the blood-feeding patterns of the Mansonia species. Knowledge of the host preference is crucial in establishing the public health importance of a mosquito species and its potential to be involved in the transmission dynamics of pathogens. Species that are primarily anthropophilic can be more effective in spreading vector-borne pathogens to humans. In this study, we used an Illumina Nextera sequencing protocol and the QIIME2 workflow to assess the diversity of DNA sequences extracted in the ingested blood of mosquito species to evaluate the overall and local host choices for three species: Ma. titillans, Ma. Amazonensis, and Ma. humeralis, in rural areas alongside the Madeira River in the vicinities of the Santo Antonio Energia (SAE) reservoir in the municipality of Porto Velho, Rondônia, Western Brazil. By performing our analysis pipeline, we have found that host diversity per collection site showed a significant heterogeneity across the sample sites. In addition, in rural areas, Ma. amazonensis present a high affinity for B. taurus, Ma. humeralis shows an overall preference for C. familiaris and B. taurus, but also H. sapiens and E. caballus in urban areas, and Ma. titillans showed more opportunistic behavior in rural areas, feeding on wild animals and G. gallus, though with an overall preference for H. sapiens.
Association between Inflammation and Thrombotic Pathway Link with Pathogenesis of Depression and Anxiety in SLE Patients
Authors: Duca Liliana , Roman Nadinne , Teodorescu Andreea , Ifteni Petru
Published: March 2023

As a complication of systemic lupus erythematosus (SLE), the neuropsychiatric form may manifest with neurological and psychiatric symptoms. Diagnosing neuropsychiatric SLE can be challenging due to the heterogeneity of this disease manifestation and the possibilities of investigation. This research aims to identify the possible associations between inflammation and thrombotic biomarkers alongside anxiety and/or depression manifestations in SLE patients. A group of 65 outpatients were investigated regarding the levels of depression, anxiety, disability, quality of life and other specific serum biomarkers linked with inflammation or coagulopathies. The results showed severe depression in eight participants, moderate depression in 22 (33.85%), and 26 (40%) subjects with mild depression. Anxiety was more prevalent within 64 participants (98.46%), while a degree of disability was reported by 52 participants (80%). Quality of life evaluated by EQ5D revealed a medium value of 1.57, and EQ5D VAS health medium value was 57.95 and was correlated with anxiety. A strong positive correlation between depression, anxiety and antibodies associated with anti-cardiolipin and anti beta2 glycoprotein I antibodies, lupus anticoagulant, ICAM-1, low C4 a and anti-ribosomal P antibodies were identified. These data results suggest that autoimmune/inflammatory and ischemic/thrombotic pathways could contribute to depression and anxiety as neuropsychiatric SLE manifestations.
Likely Pathogenic Variants of Cav1.3 and Nav1.1 Encoding Genes in Amyotrophic Lateral Sclerosis Could Elucidate the Dysregulated Pain Pathways
Authors: Nagy Zsófia Flóra , Sonkodi Balázs , Pál Margit , Klivényi Péter , Széll Márta
Published: March 2023

Amyotrophic lateral sclerosis (ALS) is a lethal multisystem neurodegenerative disease associated with progressive loss of motor neurons, leading to death. Not only is the clinical picture of ALS heterogenous, but also the pain sensation due to different types of pain involvement. ALS used to be considered a painless disease, but research has been emerging and depicting a more complex pain representation in ALS. Pain has been detected even a couple years before the symptomatic stage of ALS, referring to primary pain associated with muscle denervation, although secondary pain due to nociceptive causes is also a part of the clinical picture. A new non-contact dying-back injury mechanism theory of ALS recently postulated that the irreversible intrafusal proprioceptive Piezo2 microinjury could be the primary damage, with underlying genetic and environmental risk factors. Moreover, this Piezo2 primary damage is also proposed to dysregulate the primary pain pathways in the spinal dorsal horn in ALS due to the lost imbalanced subthreshold Ca2+ currents, NMDA activation and lost L-type Ca2+ currents, leading to the lost activation of wide dynamic range neurons. Our investigation is the first to show that the likely pathogenic variants of the Cav1.3 encoding CACNA1D gene may play a role in ALS pathology and the associated dysregulation or loss of the pain sensation. Furthermore, our reanalysis also shows that the SCN1A gene might also contribute to the dysregulated pain sensation in ALS. Finally, the absence of pathogenic variants of Piezo2 points toward the new non-contact dying-back injury mechanism theory of ALS. However, molecular and genetic investigations are needed to identify the functionally diverse features of this proposed novel critical pathway.
Development of an Animal Model for Traumatic Brain Injury Augmentation of Heterotopic Ossification in Response to Local Injury
Authors: Kesavan Chandrasekhar , Gomez Gustavo A. , Pourteymoor Sheila , Mohan Subburaman
Published: March 2023

Heterotopic ossification (HO) is the abnormal growth of bone in soft connective tissues that occurs as a frequent complication in individuals with traumatic brain injury (TBI) and in rare genetic disorders. Therefore, understanding the mechanisms behind ectopic bone formation in response to TBI is likely to have a significant impact on identification of novel therapeutic targets for HO treatment. In this study, we induced repetitive mild TBI (mTBI) using a weight drop model in mice and then stimulated HO formation via a local injury to the Achilles tendon or fibula. The amount of ectopic bone, as evaluated by micro-CT analyses, was increased by four-fold in the injured leg of mTBI mice compared to control mice. However, there was no evidence of HO formation in the uninjured leg of mTBI mice. Since tissue injury leads to the activation of hypoxia signaling, which is known to promote endochondral ossification, we evaluated the effect of IOX2, a chemical inhibitor of PHD2 and a known inducer of hypoxia signaling on HO development in response to fibular injury. IOX2 treatment increased HO volume by five-fold compared to vehicle. Since pericytes located in the endothelium of microvascular capillaries are known to function as multipotent tissue-resident progenitors, we determined if activation of hypoxia signaling promotes pericyte recruitment at the injury site. We found that markers of pericytes, NG2 and PDGFRβ, were abundantly expressed at the site of injury in IOX2 treated mice. Treatment of pericytes with IOX2 for 72 h stimulated expression of targets of hypoxia signaling (Vegf and Epo), as well as markers of chondrocyte differentiation (Col2α1 and Col10α1). Furthermore, serum collected from TBI mice was more effective in promoting the proliferation and differentiation of pericytes than control mouse serum. In conclusion, our data show that the hypoxic state at the injury site in soft tissues of TBI mice provides an environment leading to increased accumulation and activation of pericytes to form endochondral bone.
Therapeutic Drug Monitoring in Oncohematological Patients: A Fast and Accurate HPLC-UV Method for the Quantification of Nilotinib in Human Plasma and Its Clinical Application
Authors: Escudero-Ortiz Vanesa , Rodríguez-Lucena Francisco José , Estan-Cerezo Gabriel , Mancheño-Maciá Esther , Conesa-García Venancio , García-Monsalve Ana , Soriano-Irigaray Leticia , Navarro-Ruiz Andrés
Published: March 2023

Nilotinib, a second-generation tyrosine kinase inhibitor, has demonstrated clinical activity in chronic myeloid leukemia. As an exposure–response relationship has been observed for nilotinib, its therapeutic drug monitoring could be a valuable tool in clinical practice. Therefore, the aim of this study was to develop and validate a selective and precise high performance liquid chromatography–ultraviolet method for the measurement of nilotinib in plasma from patients with cancer. After protein precipitation extraction with acetonitrile, nilotinib and rilpivirine were separated using isocratic elution on a Tracer Excel 120 ODS C18 column using a mobile phase consisting of a mixture of potassium dihydrogen phosphate-buffered solution (pH 5.5; 0.037 M)–methanol–acetonitrile (45:45:10, v/v/v), pumped at a flow rate of 1.7 mL·min−1. A wavelength of 254 nm was selected for the quantification of the analyte and the internal standard (IS). The technique was validated following the guidelines for the validation of analytical methods of regulatory agencies (Food and Drug Administration (FDA) and the European Medicines Agency (EMA)). Linearity was established in a concentration range between 125 and 7000 ng/mL. The detection limit was 90 ng/mL, and the lower limit of quantification was 125 ng/mL. For all concentrations in the calibration curve, the intraday and interday coefficients of variation were less than 4.1%. Median recovery of nilotinib from plasma was ≥65.1% (±21.4%). The method described is sensitive, selective, reproducible, and rapid, and can be used for the accurate determination of nilotinib in human plasma for pharmacokinetics studies and for therapeutic drug monitoring (TDM) of nilotinib in routine clinical practice.
Preservation of Mitochondrial Health in Liver Ischemia/Reperfusion Injury
Authors: Machado Ivo F. , Palmeira Carlos M. , Rolo Anabela P.
Published: March 2023

Liver ischemia-reperfusion injury (LIRI) is a major cause of the development of complications in different clinical settings such as liver resection and liver transplantation. Damage arising from LIRI is a major risk factor for early graft rejection and is associated with higher morbidity and mortality after surgery. Although the mechanisms leading to the injury of parenchymal and non-parenchymal liver cells are not yet fully understood, mitochondrial dysfunction is recognized as a hallmark of LIRI that exacerbates cellular injury. Mitochondria play a major role in glucose metabolism, energy production, reactive oxygen species (ROS) signaling, calcium homeostasis and cell death. The diverse roles of mitochondria make it essential to preserve mitochondrial health in order to maintain cellular activity and liver integrity during liver ischemia/reperfusion (I/R). A growing body of studies suggest that protecting mitochondria by regulating mitochondrial biogenesis, fission/fusion and mitophagy during liver I/R ameliorates LIRI. Targeting mitochondria in conditions that exacerbate mitochondrial dysfunction, such as steatosis and aging, has been successful in decreasing their susceptibility to LIRI. Studying mitochondrial dysfunction will help understand the underlying mechanisms of cellular damage during LIRI which is important for the development of new therapeutic strategies aimed at improving patient outcomes. In this review, we highlight the progress made in recent years regarding the role of mitochondria in liver I/R and discuss the impact of liver conditions on LIRI.
Molecular Alterations in Cutaneous Squamous Cell Carcinoma in Immunocompetent and Immunosuppressed Hosts—A Systematic Review
Authors: Tsang Denise Ann , Tam Steve Y. C. , Oh Choon Chiat
Published: March 2023

The characterization of cutaneous squamous cell carcinoma (cSCC) at the molecular level is lacking in the current literature due to the high mutational burden of this disease. Immunosuppressed patients afflicted with cSCC experience considerable morbidity and mortality. In this article, we review the molecular profile of cSCC among the immunosuppressed and immunocompetent populations at the genetic, epigenetic, transcriptomic, and proteometabolomic levels, as well as describing key differences in the tumor immune microenvironment between these two populations. We feature novel biomarkers from the recent literature which may serve as potential targets for therapy.
Differences in Cerebral Glucose Metabolism in ALS Patients with and without C9orf72 and SOD1 Mutations
Authors: De Vocht Joke , Van Weehaeghe Donatienne , Ombelet Fouke , Masrori Pegah , Lamaire Nikita , Devrome Martijn , Van Esch Hilde , Moisse Mathieu , Koole Michel , Dupont Patrick , Van Laere Koen , Van Damme Philip
Published: March 2023

Amyotrophic lateral sclerosis (ALS) is characterized by progressive loss of upper and lower motor neurons. In 10% of patients, the disorder runs in the family. Our aim was to study the impact of ALS-causing gene mutations on cerebral glucose metabolism. Between October 2010 and October 2022, 538 patients underwent genetic testing for mutations with strong evidence of causality for ALS and 18F-2-fluoro-2-deoxy-D-glucose-PET (FDG PET), at University Hospitals Leuven. We identified 48 C9orf72-ALS and 22 SOD1-ALS patients. After propensity score matching, two cohorts of 48 and 21 matched sporadic ALS patients, as well as 20 healthy controls were included. FDG PET images were assessed using a voxel-based and volume-of-interest approach. We observed widespread frontotemporal involvement in all ALS groups, in comparison to healthy controls. The degree of relative glucose metabolism in SOD1-ALS in motor and extra-motor regions did not differ significantly from matched sporadic ALS patients. In C9orf72-ALS, we found more pronounced hypometabolism in the peri-rolandic region and thalamus, and hypermetabolism in the medulla extending to the pons, in comparison to matched sporadic ALS patients. Our study revealed C9orf72-dependent differences in glucose metabolism in the peri-rolandic region, thalamus, and brainstem (i.e., medulla, extending to the pons) in relation to matched sporadic ALS patients.
Correlating Pure Component Properties with MOSCED Solubility Parameters: Enthalpy of Vaporization and Vapor Pressure
Authors: Wong Nick H. , Dhakal Pratik , Roese Sydnee N. , Paluch Andrew S.
Published: March 2023

Tools to predict vapor–liquid phase equilibria are indispensable for the conceptualization and design of separation processes. Modified separation of cohesive energy density (MOSCED) is a solubility-parameter-based method parameterized to make accurate predictions of the limiting activity coefficient. As a solubility-parameter-based method, MOSCED can not only make quantitative predictions, but can shed light on the underlying intermolecular interactions. In the present study, we demonstrated the ability of MOSCED to correlate the enthalpy of vaporization and vapor pressure at a specific temperature using multiple linear regression. With this addition, MOSCED is able to predict vapor–liquid phase equilibria in the absence of reference data. This was demonstrated for the prediction of the Henry’s constant and solvation free energy of organic solutes in water, which was found to be superior to mod-UNIFAC. In addition to being able to make phase equilibrium predictions, the ability to correlate the enthalpy of vaporization and vapor pressure offers the opportunity to include additional properties in the regression of the MOSCED parameters. Given this success, we additionally attempted to correlate a wide range of physical properties using a similar expression. While, in some cases, the results were reasonable, they were inferior to the correlations of the enthalpy of vaporization and vapor pressure. Future efforts will be needed to improve the correlations.
Micro/Nano Soft Film Sensors for Intelligent Plant Systems: Materials, Fabrications, and Applications
Authors: Jiang Qin , Chai Zhiping , Zong Zisheng , Hu Zhitong , Zhang Shuo , Wu Zhigang
Published: March 2023

Being abundant as natural intelligence, plants have attracted huge attention from researchers. Soft film sensors present a novel and promising approach to connect plants with artificial devices, helping us to investigate plants’ intelligence further. Here, recent developments for micro/nano soft film sensors that can be used for establishing intelligent plant systems are summarized, including essential materials, fabrications, and application scenarios. Conductive metals, nanomaterials, and polymers are discussed as basic materials for active layers and substrates of soft film sensors. The corresponding fabrication techniques, such as laser machining, printing, coating, and vapor deposition, have also been surveyed and discussed. Moreover, by combining soft film sensors with plants, applications for intelligent plant systems are also investigated, including plant physiology detection and plant-hybrid systems. Finally, the existing challenges and future opportunities are prospected.
Pediatric Laryngopharyngeal Reflux: An Evidence-Based Review
Authors: Lechien Jerome R.
Published: March 2023

Purpose: Pediatric laryngopharyngeal reflux (P-LPR) is associated with the development of common otolaryngological symptoms and findings. In the present study, the findings about epidemiology, clinical presentation, diagnostic and therapeutic outcomes of pediatric population were reviewed. Methods: A PubMed, Cochrane Library, and Scopus literature search was conducted about evidence-based findings in epidemiology, clinical presentation, diagnostic and therapeutic outcomes of P-LPR. Findings: The prevalence of LPR remains unknown in infant and child populations. The clinical presentation depends on age. Infants with LPR symptoms commonly have both gastroesophageal reflux disease (GERD) and laryngopharyngeal reflux and related digestive, respiratory and ear, nose and throat symptoms. The GERD prevalence appears to decrease over the growth, and the clinical picture is increasingly associated with LPR symptoms and findings without GERD. The prevalence of LPR and proximal acid and nonacid esophageal reflux events may be high in some prevalent otolaryngological conditions (chronic otitis media, laryngolomalacia and apnea). However, the lack of use of hypopharyngeal–esophageal multichannel intraluminal impedance pH monitoring (HEMII-pH) limits the establishment of etiological associations. Proton pump inhibitors are less effective in P-LPR patients compared to GERD populations, which may be related to the high prevalence of weakly or nonacid reflux events. Conclusions: Many gray areas persist in P-LPR and should be not resolved without the establishment of diagnostic criteria (guidelines) based on HEMII-pH. The unavailability of HEMII-pH and the poor acid-suppressive therapeutic response are all issues requiring future investigations. Future controlled studies using HEMII-pH and enzyme measurements in ear, nose or throat fluids may clarify the epidemiology of P-LPR according to age and its association with many otolaryngological conditions.
Medication Intake as a Factor for Non-Initiation and Cessation of Breastfeeding: A Prospective Cohort Study in Greece during the COVID-19 Pandemic
Authors: Tigka Maria , Metallinou Dimitra , Nanou Christina , Iliodromiti Zoi , Gryparis Alexandros , Lykeridou Katerina
Published: March 2023

Pharmacological treatment may become a barrier for a mother’s breastfeeding goals. We aimed to investigate maternal medication intake as a factor for non-initiation and cessation of breastfeeding and the effect of professional counseling on maternal decision-making. Throughout 2020, 847 women were recruited from five healthcare institutions. Information was gathered prospectively with an organized questionnaire through interview during hospitalization and through telephone at 1, 3 and 6 months postpartum. Results revealed that from the 57 cases of breastfeeding cessation due to medication intake, only 10.5% received evidence-based counseling from a physician. Unfortunately, 68.4% (n = 39/57) of the participants ceased breastfeeding due to erroneous professional advice. The compatibility of medicines with breastfeeding was examined according to the Lactmed and Hale classification systems, which showed discrepancy in 8 out of 114 medicines used, while 17.5% and 13.2% of the medicines, respectively, were not classified. Educational level, employment at six months postpartum, mode of delivery, previous breastfeeding experience, medication intake for chronic diseases, physician’s recommendation and smoking before pregnancy were factors significantly correlated with breastfeeding discontinuation due to medication intake. The COVID-19 restrictions protected women from ceasing breastfeeding due to medication intake. Maternal and lactation consultancy should be strictly related to evidence-based approaches.
Autoimmune Polyendocrine Syndromes in the Pediatric Age
Authors: Paparella Roberto , Menghi Michela , Micangeli Ginevra , Leonardi Lucia , Profeta Giovanni , Tarani Francesca , Petrella Carla , Ferraguti Giampiero , Fiore Marco , Tarani Luigi
Published: March 2023

Autoimmune polyendocrine syndromes (APSs) encompass a heterogeneous group of rare diseases characterized by autoimmune activity against two or more endocrine or non-endocrine organs. Three types of APSs are reported, including both monogenic and multifactorial, heterogeneous disorders. The aim of this manuscript is to present the main clinical and epidemiological characteristics of APS-1, APS-2, and IPEX syndrome in the pediatric age, describing the mechanisms of autoimmunity and the currently available treatments for these rare conditions.