bluuebunny/crossref_metadata_2025 huggingface dataset:
Pilot Study for the Assessment of the Best Radiomic Features for Bosniak Cyst Classification Using Phantom and Radiologist Inter-Observer Selection
Authors: Aymerich María , Riveira-Martín Mercedes , García-Baizán Alejandra , González-Pena Mariña , Sebastià Carmen , López-Medina Antonio , Mesa-Álvarez Alicia , Tardágila de la Fuente Gonzalo , Méndez-Castrillón Marta , Berbel-Rodríguez Andrea , Matos-Ugas Alejandra C. , Berenguer Roberto , Sabater Sebastià , Otero-García Milagros
Published: April 2023

Since the Bosniak cysts classification is highly reader-dependent, automated tools based on radiomics could help in the diagnosis of the lesion. This study is an initial step in the search for radiomic features that may be good classifiers of benign–malignant Bosniak cysts in machine learning models. A CCR phantom was used through five CT scanners. Registration was performed with ARIA software, while Quibim Precision was used for feature extraction. R software was used for the statistical analysis. Robust radiomic features based on repeatability and reproducibility criteria were chosen. Excellent correlation criteria between different radiologists during lesion segmentation were imposed. With the selected features, their classification ability in benignity–malignity terms was assessed. From the phantom study, 25.3% of the features were robust. For the study of inter-observer correlation (ICC) in the segmentation of cystic masses, 82 subjects were prospectively selected, finding 48.4% of the features as excellent regarding concordance. Comparing both datasets, 12 features were established as repeatable, reproducible, and useful for the classification of Bosniak cysts and could serve as initial candidates for the elaboration of a classification model. With those features, the Linear Discriminant Analysis model classified the Bosniak cysts in terms of benignity or malignancy with 88.2% accuracy.
Prognosis Prediction in COVID-19 Patients through Deep Feature Space Reasoning
Authors: Ahmad Jamil , Saudagar Abdul Khader Jilani , Malik Khalid Mahmood , Khan Muhammad Badruddin , AlTameem Abdullah , Alkhathami Mohammed , Hasanat Mozaherul Hoque Abul
Published: April 2023

The COVID-19 pandemic has presented a unique challenge for physicians worldwide, as they grapple with limited data and uncertainty in diagnosing and predicting disease outcomes. In such dire circumstances, the need for innovative methods that can aid in making informed decisions with limited data is more critical than ever before. To allow prediction with limited COVID-19 data as a case study, we present a complete framework for progression and prognosis prediction in chest X-rays (CXR) through reasoning in a COVID-specific deep feature space. The proposed approach relies on a pre-trained deep learning model that has been fine-tuned specifically for COVID-19 CXRs to identify infection-sensitive features from chest radiographs. Using a neuronal attention-based mechanism, the proposed method determines dominant neural activations that lead to a feature subspace where neurons are more sensitive to COVID-related abnormalities. This process allows the input CXRs to be projected into a high-dimensional feature space where age and clinical attributes like comorbidities are associated with each CXR. The proposed method can accurately retrieve relevant cases from electronic health records (EHRs) using visual similarity, age group, and comorbidity similarities. These cases are then analyzed to gather evidence for reasoning, including diagnosis and treatment. By using a two-stage reasoning process based on the Dempster–Shafer theory of evidence, the proposed method can accurately predict the severity, progression, and prognosis of a COVID-19 patient when sufficient evidence is available. Experimental results on two large datasets show that the proposed method achieves 88% precision, 79% recall, and 83.7% F-score on the test sets.
Automatic Classification of GI Organs in Wireless Capsule Endoscopy Using a No-Code Platform-Based Deep Learning Model
Authors: Chung Joowon , Oh Dong Jun , Park Junseok , Kim Su Hwan , Lim Yun Jeong
Published: April 2023

The first step in reading a capsule endoscopy (CE) is determining the gastrointestinal (GI) organ. Because CE produces too many inappropriate and repetitive images, automatic organ classification cannot be directly applied to CE videos. In this study, we developed a deep learning algorithm to classify GI organs (the esophagus, stomach, small bowel, and colon) using a no-code platform, applied it to CE videos, and proposed a novel method to visualize the transitional area of each GI organ. We used training data (37,307 images from 24 CE videos) and test data (39,781 images from 30 CE videos) for model development. This model was validated using 100 CE videos that included “normal”, “blood”, “inflamed”, “vascular”, and “polypoid” lesions. Our model achieved an overall accuracy of 0.98, precision of 0.89, recall of 0.97, and F1 score of 0.92. When we validated this model relative to the 100 CE videos, it produced average accuracies for the esophagus, stomach, small bowel, and colon of 0.98, 0.96, 0.87, and 0.87, respectively. Increasing the AI score’s cut-off improved most performance metrics in each organ (p < 0.05). To locate a transitional area, we visualized the predicted results over time, and setting the cut-off of the AI score to 99.9% resulted in a better intuitive presentation than the baseline. In conclusion, the GI organ classification AI model demonstrated high accuracy on CE videos. The transitional area could be more easily located by adjusting the cut-off of the AI score and visualization of its result over time.
Text Matching in Insurance Question-Answering Community Based on an Integrated BiLSTM-TextCNN Model Fusing Multi-Feature
Authors: Li Zhaohui , Yang Xueru , Zhou Luli , Jia Hongyu , Li Wenli
Published: April 2023

Along with the explosion of ChatGPT, the artificial intelligence question-answering system has been pushed to a climax. Intelligent question-answering enables computers to simulate people’s behavior habits of understanding a corpus through machine learning, so as to answer questions in professional fields. How to obtain more accurate answers to personalized questions in professional fields is the core content of intelligent question-answering research. As one of the key technologies of intelligent question-answering, the accuracy of text matching is related to the development of the intelligent question-answering community. Aiming to solve the problem of polysemy of text, the Enhanced Representation through Knowledge Integration (ERNIE) model is used to obtain the word vector representation of text, which makes up for the lack of prior knowledge in the traditional word vector representation model. Additionally, there are also problems of homophones and polyphones in Chinese, so this paper introduces the phonetic character sequence of the text to distinguish them. In addition, aiming at the problem that there are many proper nouns in the insurance field that are difficult to identify, after conventional part-of-speech tagging, proper nouns are distinguished by especially defining their parts of speech. After the above three types of text-based semantic feature extensions, this paper also uses the Bi-directional Long Short-Term Memory (BiLSTM) and TextCNN models to extract the global features and local features of the text, respectively. It can obtain the feature representation of the text more comprehensively. Thus, the text matching model integrating BiLSTM and TextCNN fusing Multi-Feature (namely MFBT) is proposed for the insurance question-answering community. The MFBT model aims to solve the problems that affect the answer selection in the insurance question-answering community, such as proper nouns, nonstandard sentences and sparse features. Taking the question-and-answer data of the insurance library as the sample, the MFBT text-matching model is compared and evaluated with other models. The experimental results show that the MFBT text-matching model has higher evaluation index values, including accuracy, recall and F1, than other models. The model trained by historical search data can better help users in the insurance question-and-answer community obtain the answers they need and improve their satisfaction.
A Multi-User Collaborative Access Control Scheme Based on New Hash Chain
Authors: Wang Zetian , Li Yunfa , Liu Guanxu , Zhang Di
Published: April 2023

As the threats to the Internet of Things (IoT) continue to increase, access control is widely used in various IoT information systems. However, due to the shortcomings of IoT devices such as low computing power, it is impossible to use high-performance methods to control user access. Although the emergence of the blockchain provides another way of thinking for access control, the implementation based on the blockchain requires the device to complete the proof of work (PoW) and requires the device to have high computing power. At the same time, most access control schemes existing today are intended for users to use alone, which cannot be applied to the field of multi-user coordinated access. Therefore, this paper proposes a multi-user collaborative access control scheme based on a new hash chain, which uses the identity information of multiple users as the seed value to construct the hash chain, and uses the hash chain as the PoW of the blockchain. An efficiency analysis showed that this method requires only a small amount of hash value calculation and can be applied to IoT systems with low computing power. The security analysis shows that the scheme can resist a variety of attack methods and has high security.
Research and Optimization of Hybrid On-Board Energy Storage System of an Electric Locomotive for Quarry Rail Transport
Authors: Goolak Sergey , Kondratieva Liliia , Riabov Ievgen , Lukoševičius Vaidas , Keršys Artūras , Makaras Rolandas
Published: April 2023

Operation modes of rolling stock at mining enterprises are considered and analyzed. The justification of the need to replace it with a modern specialized electric locomotive for quarry railway transport, equipped with an asynchronous traction electric drive and an on-board energy storage system, is presented. The determination of the parameters and structure of the on-board energy storage system, based on the condition of power compensation with limited power consumption from the traction network and ensuring the autonomous movement of the electric locomotive, is considered. This study was carried out by modeling the processes of energy exchange in the traction system of an electric locomotive. The use of lithium cells and supercapacitors in energy storage is considered. Variants of the hybridization of energy storage were studied from the standpoint of minimizing the weight, size, and cost indicators. It was established that reducing the mass of the energy storage device, which includes lithium cells and supercapacitors, leads to an increase in the cost of one kilowatt-hour of energy storage capacity, which reduces the attractiveness of capital expenditures for the creation of such an energy storage device. Hybridization of the energy storage device by combining lithium cells of different types practically does not improve its weight, size, and cost indicators. The recommended option is a storage capacity of energy based on LTO elements, for which it is necessary to select elements in order to minimize weight, size, and cost indicators.
Prediction Error-Based Power Forecasting of Wind Energy System Using Hybrid WT–ROPSO–NARMAX Model
Authors: Shah Aamer A. , Aftab Almani A. , Han Xueshan , Baloch Mazhar Hussain , Honnurvali Mohamed Shaik , Chauhdary Sohaib Tahir
Published: April 2023

The volatility and intermittency of wind energy result in highly unpredictable wind power output, which poses challenges to the stability of the intact power system when integrating large-scale wind power. The accuracy of wind power prediction is critical for maximizing the utilization of wind energy, improving the quality of power supply, and maintaining the stable operation of the power grid. To address this challenge, this paper proposes a novel hybrid forecasting model, referred to as Hybrid WT–PSO–NARMAX, which combines wavelet transform, randomness operator-based particle swarm optimization (ROPSO), and non-linear autoregressive moving average with external inputs (NARMAX). The model is specifically designed for power generation forecasting in wind energy systems, and it incorporates the interactions between the wind system’s supervisory control and data acquisition’s (SCADA) actual power record and numerical weather prediction (NWP) meteorological data for one year. In the proposed model, wavelet transform is utilized to significantly improve the quality of the chaotic meteorological and SCADA data. The NARMAX techniques are used to map the non-linear relationship between the NWP meteorological variables and SCADA wind power. ROPSO is then employed to optimize the parameters of NARMAX to achieve higher forecasting accuracy. The performance of the proposed model is compared with other forecasting strategies, and it outperforms in terms of forecasting accuracy improvement. Additionally, the proposed Prediction Error-Based Power Forecasting (PEBF) approach is introduced, which retrains the model to update the results whenever the difference between forecasted and actual wind powers exceeds a certain limit. The efficiency of the developed scheme is evaluated through a real case study involving a 180 MW grid-connected wind energy system located in Shenyang, China. The proposed model’s forecasting accuracy is evaluated using various assessment metrics, including mean absolute error (MAE) and root mean square error (RMSE), with the average values of MAE and RMSE being 0.27% and 0.30%, respectively. The simulation and numerical results demonstrated that the proposed model accurately predicts wind output power.
Anaerobic Digestion of Agricultural Waste Using Microbial Inocula: Performance and Characterization of Bacterial Communities Using 16S rRNA Sequencing Approach
Authors: Niya Btissam , Yaakoubi Kaoutar , Azaroual Salah , Beraich Fatima , Arouch Moha , Meftah Kadmiri Issam
Published: April 2023

Anaerobic digestion is considered a beneficial treatment for biogas production (BP). To improve the performance of this bioprocess, the addition of well-selected inocula could be an interesting approach that affects the overall efficiency of the BP. In this study, the reactor performance and energy analysis of liquid-state anaerobic digestion of cattle manure (CM) at high solids concentration (TS%) (94.87%) with six different inocula—two cellulosic (C.I1, C.I2), one lipidic (Li.I), two lactic (La.I1, La.I2), and one saccharidic (Sacc.I)—were investigated. The results showed that inocula improved the biogas production and yield during anaerobic digestion of CM by 109%, 86%, and 52.4%, respectively, when the cellulosic (C.I1), lipidic (Li.I), and lactic (La.I1) inocula were added, compared with the substrate production alone at a substrate/inoculum (S/I) ratio of 5:3 (v/v). The addition of inocula in an appropriate range is useful for the performance of the anaerobic digestion process. In our study, the 16S rRNA sequencing approach was followed to investigate microbial community structure and diversity in the substrate CM and the three inocula that showed a significant improvement in biogas production (C.I1, Li.I, and La.I). The most abundant bacterial populations were found to be Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria, with different abundance percentages. Interestingly, C.I1, which resulted in the highest biogas production, showed the dominance of Cyanobacteria (53.44%) belonging mainly to the class Nostocophycidae. This study highlighted the role of inocula in improving biogas production from cattle manure (CM) thanks to their microbial diversity.
Exploitation of Mediterranean Cooperation Projects’ Tools for the Development of Public Buildings’ Energy Efficiency Plans at Local Level: A Case Study in Greece
Authors: Stavrakakis George M. , Zervas Panagiotis L. , Terzis Konstantinos , Langouranis Panagiotis , Saranti Panagiota , Stephanedes Yorgos J.
Published: April 2023

Ever since European Directive 2012/27/EU, particular attention has been focused on the improvement of the energy efficiency of the public building stock. According to the directive, local public authorities, regions and municipalities, are expected to develop and implement energy efficiency retrofitting plans for their public building stocks. While conducting such plans, important challenges are raised mainly related to data collection and the manipulation of key performance indicators (KPIs) for many buildings. The present paper deals with the aforementioned challenges through (a) the evaluation of freely available tools developed in the framework of Mediterranean territorial cooperation projects, with respect to the main pillars of energy efficiency planning, and (b) the introduction of a stepwise methodology using selected tools toward a reliable energy efficiency plan extending from the classification of the building stock to the prioritization of projects in terms of a gradual renovation plan based on energy and cost criteria. The methodology is applied for a case study in Greece, which refers to 10 public buildings of the Municipality of Aigialeia in Greece. A reliable renovation plan is developed, taking into account the municipal authority’s directions in a specialized decision-making scheme. It is concluded that the suggested methodology is very practical for planning purposes, while for the case studied, a 6-year gradual renovation plan is emerged until a deep retrofit of all buildings, associated with an estimated primary energy saving and CO2 emissions avoidance of more than 1850 MWh and 400 tns, respectively, with a total investment of about EUR 3 million.
Influence of Combined Electrothermal Aging on Dielectric and Thermal Properties of HVAC XLPE Cable
Authors: Xu Zhihui , Yang Ming , Peng Huaqing , Zhao Yifeng , Liu Gang
Published: April 2023

To explore the influence of electrothermal aging on the properties of HVAC XLPE cable during its normal operation, two circuits of 110 kV XLPE cable were subjected to a combined electrothermal accelerated aging test for 180 days. The test voltage was set at 95 kV, and the test temperature was set at 90 °C. The constant temperature aging mode was adopted for one circuit, and the periodic thermal cycle aging mode was adopted for the other circuit. The dielectric property of the cable was diagnosed with dielectric spectroscopy measurement, and the thermal property was diagnosed with thermal parameters (thermal capacity and thermal resistance) measurement. Combined with Fourier infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC) measurements, morphological changes in the insulation under different electrothermal aging modes were analyzed to construct the correlation with the dielectric and thermal properties. The results show that the short-term electrothermal constant temperature aging mode effectively enhances the dielectric and thermal properties of the cable by modifying spherulite morphology and migrating polar compounds; the short-term electrothermal cycle aging mode also enhances the thermal properties of the cable due to the drop in small polar compounds. However, different distributions of polar compounds and crystal interfaces in the insulation lead to extreme distortion in the electric field distribution.
Enhanced Gas Production from Class II Gas Hydrate Reservoirs by the Multistage Fractured Horizontal Well
Authors: Sun Wei , Li Guiwang , Qin Huating , Li Shuxia , Xu Jianchun
Published: April 2023

In the two test productions that have been conducted in the hydrate reservoir test development zone in the South China Sea, the gas production capacity of single wells is low and the exploitation difficulty with the cost is too high for commercial demand economically. The low permeability of the hydrate-bearing layer (HBL) acts as the major barrier for pressure propagation during depressurization. Hydraulic fracturing by the combined depressurization is considered a promising hydrate production enhancement technology that can effectively improve the seepage state in the reservoir. In this study, to evaluate the effectiveness of the development methods association with fracturing, we established an idealized Class II hydrate reservoir and studied it using a multi-stage fractured horizontal well to assist in depressurization extraction. In order to evaluate the production enhancement effect of this method, we compared the gas production results of four methods, including single vertical well, vertical fractured well, horizontal well, and multistage fractured horizontal well through numerical simulation. In order to investigate the influence of key fracture parameters on the production enhancement effect, a sensitivity analysis of the production effect of Class II hydrate reservoirs with different fracture spacing, number of fractures, fracture conductivity, and fracture length was conducted, and the results were analyzed in terms of gas production and water production behavior curves as well as physical field evolution over time. The simulation results show that the multi-stage fractured horizontal wells have the best production increase in the comparison of well types. In the analysis of fracture parameters, it can be found that the selection of proper fracture spacing and dimensionless fracture conductivity can lead to a significant increase in gas production.
Statistic and Network Features of RGB and Hyperspectral Imaging for Determination of Black Root Mold Infection in Apples
Authors: Sha Wen , Hu Kang , Weng Shizhuang
Published: April 2023

Apples damaged by black root mold (BRM) lose moisture, vitamins, and minerals as well as carry dangerous toxins. Determination of the infection degree can allow for customized use of apples, reduce financial losses, and ensure food safety. In this study, red-green-blue (RGB) imaging and hyperspectral imaging (HSI) are combined to detect the infection degree of BRM in apple fruits. First, RGB and HSI images of healthy, mildly, moderately, and severely infected fruits are measured, and those with effective wavelengths (EWs) are screened from HSI by random frog. Second, the statistic and network features of images are extracted by using color moment and convolutional neural network. Meanwhile, random forest (RF), K-nearest neighbor, and support vector machine are used to construct classification models with the above two features of RGB and HSI images of EWs. Optimal results with the 100% accuracy of training set and 96% accuracy of prediction set are obtained by RF with the statistic and network features of the two images, outperforming the other cases. The proposed method furnishes an accurate and effective solution for determining the BRM infection degree in apples.
The Impact of Storage Temperature on the Development of Microbial Communities on the Surface of Blueberry Fruit
Authors: Wang Junying , Shi Chong , Fang Donglu , Che Jilu , Wu Wenlong , Lyu Lianfei , Li Weilin
Published: April 2023

Microbial contamination is one of the main reasons for the quality deterioration of postharvest blueberries during storage. In this study, we investigated the surface microbiota of blueberry fruits stored at different temperatures via high-throughput sequencing of the 16S and ITS rRNA genes. The results indicated that the α-diversity of the microbial communities in samples stored at 4 °C was much higher than that in samples stored at 25 °C. The composition of the bacterial and fungal communities on the surface of the blueberry fruits varied at different storage temperatures. Ascomycota, Basidiomycota, Anthophyta, Chlorophyta, Proteobacteria, and Cyanobacteria were the most abundant phyla in the bacterial community. Furthermore, five preservation quality indices were measured, and the influence on the α-diversity of the bacterial community was found to be significantly weaker than that of the fungal community. Based on the prediction of the bacterial flora function, the change in blueberry quality during storage was closely related to its surface microbial effect. This study provides a theoretical basis for an understanding of the microbiota on the surface of blueberry fruits to cause fruit spoilage, and the development of a targeted inhibition technology to preserve blueberry fruits under different storage and transportation environments.
Households’ Practices towards Rabies Prevention and Control in Rural Nepal
Authors: Dhakal Alok , Ghimire Ramjee P. , Regmi Sujit , Kaphle Krishna
Published: April 2023

Rabies is a vaccine-preventable, zoonotic, viral disease and a major public health concern for developing countries such as Nepal. A study was conducted from October–December 2021 among 308 household heads from three districts in Nepal (Siraha, Parsa, and Nawalparasi West) through an in-person interview to examine the rural people’s practices towards rabies. Of 70 respondents owning pet animals, 82.9% vaccinated them against rabies but 87.9% (51/58) of them kept a vaccination record. Nearly all respondents (99.7%, 307/308) said they would visit hospitals after being bitten by rabid or rabies suspected animals, and 18.2% (56/308) of them said they would also opt to visit traditional healers seeking treatment against rabies. Seven in ten respondents knew that they should wash bitten body area with soap and water. Around 60% (184/308) of respondents said they would not bother to notify or report to the local authorities if they saw someone bitten by a presumed rabid dog or observed animal behavior suggestive of rabies. The Chi-square test showed a significant association between the socio-demographic characteristics of respondents with practices (good practice and poor practice) towards rabies. The study findings suggest that rural people in Nepal need to be educated with applied rabies control and prevention practices and made aware of health seeking behavior and the role that a community members have to play to control, prevent, and eradicate rabies.
Medicinal Cannabis for Paediatric Developmental, Behavioural and Mental Health Disorders
Authors: Efron Daryl , Taylor Kaitlyn
Published: April 2023

Parents of children with developmental, behavioural and mental health disorders are increasingly asking whether medicinal cannabis might be a therapeutic option for their child. This paper presents the current evidence for medicinal cannabis in this population. Preliminary evidence from open-label studies suggests the potential for medicinal cannabis to ameliorate some symptoms in children with autism spectrum disorder. However, only one double-blind placebo-controlled trial has been completed, with inconclusive findings. Synthetic, transdermal cannabidiol gel has demonstrated efficacy for reducing social avoidance in a sub-group of children with Fragile X syndrome. Studies of medicinal cannabis are planned or underway for children and/or adolescents with autism, intellectual disability, Tourette’s syndrome, anxiety, psychosis, anorexia nervosa and a number of specific neurodevelopmental syndromes. High quality evidence from double-blind placebo-controlled trials is needed to guide clinical practice.
Managing Quartz Exposure in Apartment Building and Infrastructure Construction Work Tasks
Authors: Tuomi Tapani , Johnsson Tom , Heino Arto , Lainejoki Anniina , Salmi Kari , Poikkimäki Mikko , Kanerva Tomi , Säämänen Arto , Räsänen Tuula
Published: April 2023

The present report describes exposure to respirable silica and dust in the construction industry, as well as means to manage them. The average exposure in studied work tasks (n = 148) amounted to 64% of the Finnish OEL value of 0.05 mg/m3. While 10% of exposure estimates exceeded the OEL, the 60% percentile was well below 10% of the OEL, as was the median exposure. In other words, exposure was low in more than half of the tasks. Work tasks where exposure was low included construction cleaning, work management, installation of concrete elements, rebar laying, driving work machines equipped with cabin air intake filtration, and landscaping, in addition to some road construction tasks. Excessive exposure (>OEL) was related to not using respiratory protection at all or not using it for long enough after the dusty activity ceased. Excessive exposures were found in sandblasting, dismantling facade elements, diamond drilling, drilling hollow-core slabs, drilling with a drilling rig, priming of explosives, tiling, use of cabinless earthmoving machines, and jackhammering, regardless of whether the hammering took place in an underpressurized compartment or not. Even in these tasks, it was possible to perform the work safely, following good dust prevention measures and, when necessary, using respiratory protection suitable for the job. Furthermore, in all tasks with generally low exposure, one could be significantly exposed through the general air or by making poor choices in terms of dust control.
Editorial to the IJMS Special Issue on Sglt2 Inhibitors Vol. 1
Authors: Lymperopoulos Anastasios
Published: April 2023

The goal of this Special Issue is to highlight the ever-increasing progress in pharmacological research on sodium-glucose co-transporter (SGLT) type 2 (SGLT2) inhibitors or gliflozins [...]
Power Up Plant Genetic Research with Genomic Data
Authors: Li Man-Wah , Isobe Sachiko , Lam Hon-Ming
Published: April 2023

The official debut of the reference genome of Arabidopsis thaliana in 2000 [...]
Molecule Clustering Dynamics in the Molecular Doping Process of Si(111) with Diethyl-propyl-phosphonate
Authors: Pizzone Mattia , Grimaldi Maria Grazia , La Magna Antonino , Scalese Silvia , Adam Jost , Puglisi Rosaria A.
Published: April 2023

The molecular doping (MD) process is based on the deposition of dopant-containing molecules over the surface of a semiconductor substrate, followed by the thermal diffusion step. Previous studies suggest that, during the deposition, the molecules nucleate clusters, and at prolonged deposition times, they grow into self-assembled layers on the sample to be doped. Little is known about the influence of nucleation kinetics on the final properties of these layers and how they change when we modify the solution properties. In this work, we examine the nucleation rate and the molecular surface coverage kinetics of diethyl-propyl phosphonate on silicon at different solution concentrations and how these conditions influence the final electrical properties of the doped samples. We present a high-resolution morphological characterization of the as-deposited molecules together with the electrical results of the final doped samples. The experimental results show a non-obvious behavior, explained through understanding of the competition between the molecules’ physisorption and chemisorption mechanisms. As a consequence, due to the deeper knowledge of the deposition phase, a finer tuning of the conductive properties of MD-doped samples is achieved.
Paraoxonases at the Heart of Neurological Disorders
Authors: Khalaf Fatimah K. , Connolly Jacob , Khatib-Shahidi Bella , Albehadili Abdulsahib , Tassavvor Iman , Ranabothu Meghana , Eid Noha , Dube Prabhatchandra , Khouri Samer J. , Malhotra Deepak , Haller Steven T. , Kennedy David J.
Published: April 2023

Paraoxonase enzymes serve as an important physiological redox system that participates in the protection against cellular injury caused by oxidative stress. The PON enzymes family consists of three members (PON-1, PON-2, and PON-3) that share a similar structure and location as a cluster on human chromosome 7. These enzymes exhibit anti-inflammatory and antioxidant properties with well-described roles in preventing cardiovascular disease. Perturbations in PON enzyme levels and their activity have also been linked with the development and progression of many neurological disorders and neurodegenerative diseases. The current review summarizes the available evidence on the role of PONs in these diseases and their ability to modify risk factors for neurological disorders. We present the current findings on the role of PONs in Alzheimer’s disease, Parkinson’s disease, and other neurodegenerative and neurological diseases.
Re-Evaluating the Relevance of the Oxygen–Glucose Deprivation Model in Ischemic Stroke: The Example of Cdk Inhibition
Authors: D’aes Tine , Marlier Quentin , Verteneuil Sébastien , Quatresooz Pascale , Vandenbosch Renaud , Malgrange Brigitte
Published: April 2023

Previous research has shown that cyclin-dependent kinases (Cdks) that play physiological roles in cell cycle regulation become activated in post-mitotic neurons after ischemic stroke, resulting in apoptotic neuronal death. In this article, we report our results using the widely used oxygen–glucose deprivation (OGD) in vitro model of ischemic stroke on primary mouse cortical neurons to investigate whether Cdk7, as part of the Cdk-activating kinase (CAK) complex that activates cell cycle Cdks, might be a regulator of ischemic neuronal death and may potentially constitute a therapeutic target for neuroprotection. We found no evidence of neuroprotection with either pharmacological or genetic invalidation of Cdk7. Despite the well-established idea that apoptosis contributes to cell death in the ischemic penumbra, we also found no evidence of apoptosis in the OGD model. This could explain the absence of neuroprotection following Cdk7 invalidation in this model. Neurons exposed to OGD seem predisposed to die in an NMDA receptor-dependent manner that could not be prevented further downstream. Given the direct exposure of neurons to anoxia or severe hypoxia, it is questionable how relevant OGD is for modeling the ischemic penumbra. Due to remaining uncertainties about cell death after OGD, caution is warranted when using this in vitro model to identify new stroke therapies.
Bromodomain and Extraterminal Domain (BET) Protein Inhibition Hinders Glioblastoma Progression by Inducing Autophagy-Dependent Differentiation
Authors: Colardo Mayra , Gargano Deborah , Russo Miriam , Petraroia Michele , Pensabene Daniele , D’Alessandro Giuseppina , Santoro Antonio , Limatola Cristina , Segatto Marco , Di Bartolomeo Sabrina
Published: April 2023

Glioblastoma multiforme (GBM) is the most common and aggressive type of malignant primary brain tumor, and it is characterized by a high recurrence incidence and poor prognosis due to the presence of a highly heterogeneous mass of stem cells with self-renewal capacity and stemness maintenance ability. In recent years, the epigenetic landscape of GBM has been explored and many epigenetic alterations have been investigated. Among the investigated epigenetic abnormalities, the bromodomain and extra-terminal domain (BET) chromatin readers have been found to be significantly overexpressed in GBM. In this work, we investigated the effects of BET protein inhibition on GBM cell reprogramming. We found that the pan-BET pharmacological inhibitor JQ1 was able to promote a differentiation program in GBM cells, thus impairing cell proliferation and enhancing the toxicity of the drug Temozolomide (TMZ). Notably, the pro-differentiation capability of JQ1 was prevented in autophagy-defective models, suggesting that autophagy activation is necessary for BET protein activity in regulating glioma cell fate. Given the growing interest in epigenetic therapy, our results further support the possibility of introducing a BET-based approach in GBM clinical management.
Selective Hepatic Cbs Knockout Aggravates Liver Damage, Endothelial Dysfunction and ROS Stress in Mice Fed a Western Diet
Authors: Lambooy Sebastiaan , Heida Andries , Joschko Christian , Nakladal Dalibor , van Buiten Azuwerus , Kloosterhuis Niels , Huijkman Nicolette , Gerding Albert , van de Sluis Bart , Henning Robert , Deelman Leo
Published: April 2023

Cystathionine-β-synthase (CBS) is highly expressed in the liver, and deficiencies in Cbs lead to hyperhomocysteinemia (HHCy) and disturbed production of antioxidants such as hydrogen sulfide. We therefore hypothesized that liver-specific Cbs deficient (LiCKO) mice would be particularly susceptible to the development of non-alcoholic fatty liver disease (NAFLD). NAFLD was induced by a high-fat high-cholesterol (HFC) diet; LiCKO and controls were split into eight groups based on genotype (con, LiCKO), diet (normal diet, HFC), and diet duration (12 weeks, 20 weeks). LiCKO mice displayed intermediate to severe HHCy. Plasma H2O2 was increased by HFC, and further aggravated in LiCKO. LiCKO mice fed an HFC diet had heavier livers, increased lipid peroxidation, elevated ALAT, aggravated hepatic steatosis, and inflammation. LiCKO mice showed decreased L-carnitine in the liver, but this did not result in impaired fatty acid oxidation. Moreover, HFC-fed LiCKO mice demonstrated vascular and renal endothelial dysfunction. Liver and endothelial damage correlated significantly with systemic ROS status. In conclusion, this study demonstrates an important role for CBS in the liver in the development of NAFLD, which is most probably mediated through impaired defense against oxidative stress.
Electrospun Hyaluronan Nanofiber Membrane Immobilizing Aromatic Doxorubicin as Therapeutic and Regenerative Biomaterial
Authors: Han Xiaowen , Zhao Mingda , Xu Ruiling , Zou Yaping , Wang Yuxiang , Liang Jie , Jiang Qing , Sun Yong , Fan Yujiang , Zhang Xingdong
Published: April 2023

Lesioned tissue requires synchronous control of disease and regeneration progression after surgery. It is necessary to develop therapeutic and regenerative scaffolds. Here, hyaluronic acid (HA) was esterified with benzyl groups to prepare hyaluronic acid derivative (HA-Bn) nanofibers via electrospinning. Electrospun membranes with average fiber diameters of 407.64 ± 124.8 nm (H400), 642.3 ± 228.76 nm (H600), and 841.09 ± 236.86 nm (H800) were obtained by adjusting the spinning parameters. These fibrous membranes had good biocompatibility, among which the H400 group could promote the proliferation and spread of L929 cells. Using the postoperative treatment of malignant skin melanoma as an example, the anticancer drug doxorubicin (DOX) was encapsulated in nanofibers via hybrid electrospinning. The UV spectroscopy of DOX-loaded nanofibers (HA-DOX) revealed that DOX was successfully encapsulated, and there was a π–π interaction between aromatic DOX and HA-Bn. The drug release profile confirmed the sustained release of about 90%, achieved within 7 days. In vitro cell experiments proved that the HA-DOX nanofiber had a considerable inhibitory effect on B16F10 cells. Therefore, the HA-Bn electrospun membrane could facilitate the potential regeneration of injured skin tissues and be incorporated with drugs to achieve therapeutic effects, offering a powerful approach to developing therapeutic and regenerative biomaterial.
Antithrombotic Therapy in Peripheral Artery Disease: Current Evidence and Future Directions
Authors: Canonico Mario Enrico , Piccolo Raffaele , Avvedimento Marisa , Leone Attilio , Esposito Salvatore , Franzone Anna , Giugliano Giuseppe , Gargiulo Giuseppe , Hess Connie N. , Berkowitz Scott D. , Hsia Judith , Cirillo Plinio , Esposito Giovanni , Bonaca Marc P.
Published: April 2023

Patients with peripheral artery disease (PAD) are at an increased risk of major adverse cardiovascular events, and those with disease in the lower extremities are at risk of major adverse limb events primarily driven by atherothrombosis. Traditionally, PAD refers to diseases of the arteries outside of the coronary circulation, including carotid, visceral and lower extremity peripheral artery disease, and the heterogeneity of PAD patients is represented by different atherothrombotic pathophysiology, clinical features and related antithrombotic strategies. The risk in this diverse population includes systemic risk of cardiovascular events as well as risk related to the diseased territory (e.g., artery to artery embolic stroke for patients with carotid disease, lower extremity artery to artery embolism and atherothrombosis in patients with lower extremity disease). Moreover, until the last decade, clinical data on antithrombotic management of PAD patients have been drawn from subanalyses of randomized clinical trials addressing patients affected by coronary artery disease. The high prevalence and related poor prognosis in PAD patients highlight the pivotal role of tailored antithrombotic therapy in patients affected by cerebrovascular, aortic and lower extremity peripheral artery disease. Thus, the proper assessment of thrombotic and hemorrhagic risk in patients with PAD represents a key clinical challenge that must be met to permit the optimal antithrombotic prescription for the various clinical settings in daily practice. The aim of this updated review is to analyze different features of atherothrombotic disease as well as current evidence of antithrombotic management in asymptomatic and secondary prevention in PAD patients according to each arterial bed.
Dysnatremia in COVID-19 Patients—An Analysis of the COLOS Study
Authors: Królicka Anna , Letachowicz Krzysztof , Adamik Barbara , Doroszko Adrian , Kaliszewski Krzysztof , Kiliś-Pstrusińska Katarzyna , Kujawa Krzysztof , Matera-Witkiewicz Agnieszka , Madziarski Marcin , Pomorski Michał , Protasiewicz Marcin , Sokołowski Janusz , Trocha Małgorzata , Jankowska Ewa Anita , Madziarska Katarzyna
Published: April 2023

Background: Sodium imbalance is one of the most common electrolyte disturbances encountered in the medical practice, and it may present with either hyponatremia or hypernatremia. Both sodium abnormalities are related with unfavorable outcomes. Objective: Elucidation of the prevalence of dysnatremia among COVID-19 patients and its impact on 30- and 90-day mortality and need for ICU admission was the goal. Design and participants: A single-center, retrospective, observational study was conducted. A total of 2026 adult, SARS-CoV-2 positive patients, admitted to Wroclaw University Hospital between 02.2020 and 06.2021, were included. On admission, patients were divided into groups: normonatremic (N), hyponatremic (L), and hypernatremic (H). Acquired data was processed, and Cox hazards regression and logistic regression were implemented. Key results: Hyponatremia on admission occurred in 17.47% (n = 354) of patients and hypernatremia occurred in 5.03% (n = 102). Dysnatremic patients presented with more comorbidities, used more drugs, and were statistically more often admitted to the ICU. Level of consciousness was the strongest predictor of ICU admission (OR = 1.21, CI: 1.16–1.27, p < 0.001). Thirty-day mortality was significantly higher in both the L and H groups (28.52%, p = 0.0001 and 47.95%, p < 0.0001, respectively), in comparison to 17.67% in the N group. Ninety-day mortality showed a similar trend in all study groups: 34.37% in the L group (p = 0.0001), 60.27% (p < 0.0001) in the H group, and 23.32% in the N group. In multivariable analyses, hypo- and hypernatremia were found to be independent predictors of 30- and 90-day mortality. Conclusions: Both hypo- and hypernatremia are strong predictors of mortality and disease severity in COVID-19 patients. Extraordinary care should be taken when dealing with hypernatremic, COVID-positive patients, as this group exhibits the highest mortality rates.
Crohn’s Disease as a Possible Risk Factor for Failed Healing in Ileocolic Anastomoses
Authors: Schweer Julian , Neumann Philipp-Alexander , Doebler Philipp , Doebler Anna , Pascher Andreas , Mennigen Rudolf , Rijcken Emile
Published: April 2023

Anastomotic leakage (AL) after colorectal resections is a serious complication in abdominal surgery. Especially in patients with Crohn’s disease (CD), devastating courses are observed. Various risk factors for the failure of anastomotic healing have been identified; however, whether CD itself is independently associated with anastomotic complications still remains to be validated. A retrospective analysis of a single-institution inflammatory bowel disease (IBD) database was conducted. Only patients with elective surgery and ileocolic anastomoses were included. Patients with emergency surgery, more than one anastomosis, or protective ileostomies were excluded. For the investigation of the effect of CD on AL 141, patients with CD-type L1, B1–3 were compared to 141 patients with ileocolic anastomoses for other indications. Univariate statistics and multivariate analysis with logistic regression and backward stepwise elimination were performed. CD patients had a non-significant higher percentage of AL compared to non-IBD patients (12% vs. 5%, p = 0.053); although, the two samples differed in terms of age, body mass index (BMI), Charlson comorbidity index (CCI), and other clinical variables. However, Akaike information criterion (AIC)-based stepwise logistic regression identified CD as a factor for impaired anastomotic healing (final model: p = 0.027, OR: 17.043, CI: 1.703–257.992). Additionally, a CCI ≥ 2 (p = 0.010) and abscesses (p = 0.038) increased the disease risk. The alternative point estimate for CD as a risk factor for AL based on propensity score weighting also resulted in an increased risk, albeit lower (p = 0.005, OR 7.36, CI 1.82–29.71). CD might bear a disease-specific risk for the impaired healing of ileocolic anastomoses. CD patients are prone to postoperative complications, even in absence of other risk factors, and might benefit from treatment in dedicated centers.
Living-Donor Liver Transplant and Improved Post-Transplant Survival in Patients with Primary Sclerosing Cholangitis
Authors: Sierra Leandro , Barba Romelia , Ferrigno Bryan , Goyes Daniela , Diaz Wilfor , Patwardhan Vilas R. , Saberi Behnam , Bonder Alan
Published: April 2023

Primary sclerosing cholangitis (PSC) is the leading indication of liver transplantation (LT) among autoimmune liver disease patients. There is a scarcity of studies comparing survival outcomes between living-donor liver transplants (LDLT)s and deceased-donor liver transplants (DDLTs) in this population. Using the United Network for Organ Sharing database, we compared 4679 DDLTs and 805 LDLTs. Our outcome of interest was post-LT patient survival and post-LT graft survival. A stepwise multivariate analysis was performed, adjusting for recipient age, gender, diabetes mellitus, ascites, hepatic encephalopathy, cholangiocarcinoma, hepatocellular carcinoma, race, and the model for end-stage liver disease (MELD) score; donor’ age and sex were also included to the analysis. According to univariate and multivariate analysis, LDLT had a patient and graft survival benefit compared to DDLT (HR, 0.77, 95% CI 0.65–0.92; p < 0.002). LDLT patient survival (95.2%, 92.6%, 90.1%, and 81.9%) and graft survival (94.1%, 91.1%, 88.5%, and 80.5%) at 1, 3, 5, and 10 years were significantly better than DDLT patient survival (93.2%, 87.6%, 83.3%, and 72.7%) and graft survival (92.1%, 86.5%, 82.1%, and 70.9%) (p < 0.001) in the same interval. Variables including donor and recipient age, male recipient gender, MELD score, diabetes mellitus, hepatocellular carcinoma, and cholangiocarcinoma were associated with mortality and graft failure in PSC patients. Interestingly, Asians were more protected than Whites (HR, 0.61; 95% CI, 0.35–0.99; p < 0.047), and cholangiocarcinoma was associated with the highest hazard of mortality (HR, 2.07; 95% CI, 1.71–2.50; p < 0.001) in multivariate analysis. LDLT in PSC patients were associated with greater post-transplant patient and graft survival compared to DDLT patients.