bluuebunny/crossref_metadata_2025 huggingface dataset:
Etiopathogenesis of Canine Cruciate Ligament Disease: A Scoping Review
Authors: Niebauer Gert W. , Restucci Brunella
Published: January 2023

The spontaneous rupture of the cranial cruciate ligament in dogs remains a pathoetiologic puzzle. Despite much progress in research over the past years, the systemic and local mechanisms leading to ligament degeneration and structural failure remain largely obscure. This scoping review focuses on pathogenesis and aims at summarizing and interpreting today’s knowledge on causes of canine cruciate ligament rupture, i.e., the multifactorial mechanisms leading to degenerative stifle joint disease with collagen matrix degeneration and structural failures. Thus, the initial view of traumatic ligament rupture, fostered by “wear and tear”, has clearly been replaced by a new concept of systemic processes linked to progressive degenerative joint disease and ligament failure; thus, the term “cranial cruciate ligament disease” has been coined and is generally accepted. In addition, cruciate ligament rupture in people shares some similarities with the lesion in dogs; therefore, the review also includes comparative studies. The methods used were based on the PRISMA-ScR model (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews).
Inclusion of Soybean Hulls (Glycine max) and Pupunha Peach Palm (Bactris gasipaes) Nanofibers in the Diet of Growing Rabbits: Effects on Zootechnical Performance and Intestinal Health
Authors: de Oliveira Geovane Rosa , de Andrade Carla , Bez Isabela Cristina Colaço , Melo Antonio Diego Brandão , Almeida Vivian Vezzoni , Magalhães Washington Luiz Esteves , Weber Saulo Henrique , Sotomaior Cristina Santos , Luciano Fernando Bittencourt , Costa Leandro Batista
Published: January 2023

This study evaluated the inclusion of nanofibers from soybean hulls and pupunha peach palm heart sheaths in the diet of growing rabbits. Twenty-four New Zealand White rabbits (male and female) were allocated in three experimental groups: control, fed a basal diet; Nanosoy, fed a diet containing 7% soybean-hull nanofibers; and Nanopupunha, fed a diet containing 7% pupunha palm heart-sheath nanofibers. The Nanosoy-group rabbits showed poorer final weight, daily feed intake, and daily weight gain than those in other groups. In the duodenum, villus height, total mucosal thickness, and villus width were higher in rabbits that received nanofiber-supplemented diets than in the controls. Higher villus density and wall thickness were observed in Nanopupunha-fed rabbits than in the controls. In the jejunum, although the crypt depth was higher in Nanosoy-fed rabbits, the villus height:crypt depth ratio was higher in the Nanopupunha-fed group. Nanosoy-fed animals exhibited increased count Enterobacteriaceae populations. Rabbits in both nanofiber-fed groups exhibited higher lactic-acid bacterial counts than those in the control-diet group. Therefore, although the inclusion of 7% Nanopupunha in the diet of rabbits did not alter the performance, it improved intestinal health and increased the lactic-acid bacterial count in the cecum of growing rabbits.
Efficient AntiMycolata Agents by Increasing the Lipophilicity of Known Antibiotics through Multicomponent Reactions
Authors: Trejo Angela , Masdeu Carme , Serrano-Pérez Irene , Pedrola Marina , Juanola Narcís , Ghashghaei Ouldouz , Jiménez-Galisteo Guadalupe , Lavilla Rodolfo , Palacios Francisco , Alonso Concepción , Viñas Miguel
Published: January 2023

New antibiotic agents were prepared using Povarov and Ugi multicomponent reactions upon the known drugs sulfadoxine and dapsone. The prepared derivatives, with increased lipophilicity, showed improved efficiency against Mycolata bacteria. Microbiological guidance for medicinal chemistry is a powerful tool to design new and effective antimicrobials. In this case, the readily synthesized compounds open new possibilities in the search for antimicrobials active on mycolic acid-containing bacteria.
Resistivity and Density Structure of Limboto Lake—Pentadio, Gorontalo, Indonesia Based on Magnetotelluric and Gravity Data
Authors: Susilawati Anggie , Niode Mochtar , Surmayadi Mamay , Pratomo Prihandhanu Mukti , Nurhasan  , Mustopa Enjang Jaenal , Sutarno Doddy , Srigutomo Wahyu
Published: January 2023

Limboto Lake—Pentadio area is located in the province of Gorontalo on the northern arm of Sulawesi Island, Indonesia, which experienced a tectonic process from the Sula Platform collision in the mid-Miocene. This tectonic process led to the westward subduction of the early Miocene and post-collision rifting and uplifting of the arc and subduction along the North Sulawesi Trench during the Late Miocene to the Quaternary periods. The rifting process of the North Sulawesi arc resulted in the formation of the Gorontalo graben zone in the W–E direction. There are geothermal surface manifestations near Limboto Lake, such as hot spring complexes, with temperatures ranging from 74.8 °C to 78.5 °C. To understand the geological structure and prospective geothermal characteristics beneath the investigated area, we performed integrated magnetotelluric and gravity surveys. The preferred 3D resistivity model confirmed the presence of a fault system and a graben system that was filled with conductive bodies (~1–15 Ωm) corresponding to alluvium deposits. This result was in accordance with the 2D density model inferred from the gravity data, where a low-density value indicates the presence of a graben zone. The conceptual model of Limboto Lake—Pentadio was constructed using the information from the MT and gravity results, and from the geological study. The conceptual model illustrates the geothermal system in Limboto Lake—Pentadio, which is controlled by the fault system and the Gorontalo graben system.
Topology Optimization for Minimum Compliance with Material Volume and Buckling Constraints under Design-Dependent Loads
Authors: Jiang Yuanteng , Zhan Ke , Xia Jie , Zhao Min
Published: January 2023

Stability is a critical factor in structural design. Although buckling-constrained topology optimization has been investigated in previous work, the problem has not been considered under design-dependent loads. In this study, a model of buckling constraints in topology optimization problems under design-dependent loads was proposed to solve the above problem. First, the Kreisselmeier–Steinhauser aggregation function was employed to reduce multiple constraints to a single constraint. Then, the problem was sequentially approximated using the optimality criteria method tailored to update the variables. After that, a gradient-based optimization algorithm was established based on finite element and sensitivity analyses for the topology optimization problem with design-dependent loads. Finally, four numerical examples with design-dependent loads were comparatively analyzed, with and without bucking-constrained solutions. The calculation results proved the effectiveness and reliability of the optimization algorithm. Therefore, in this study, it was suggested that the developed optimization algorithm gained improved applicability.
Settlement Analysis of Fractional-Order Generalised Kelvin Viscoelastic Foundation under Distributed Loads
Authors: Huang Bingcheng , Lu Aizhong , Zhang Ning
Published: January 2023

A solution is proposed for ground surface settlement induced in fractional-generalised Kelvin semi-infinite space by distributed loads, based on the fractional differential theory. The effects of four main parameters—the differential order, the two shear moduli and the coefficient of viscosity—on the settlements are analysed using a numerical example, and a parametric-sensitivity analysis is conducted. The results show that the fractional-order generalised Kelvin model is more flexible than the conventional integer-order generalised Kelvin model since it can account for the rate of the deceleration creep phase; therefore, a wider range of mechanical properties of viscoelastic materials can be described with fewer parameters, and the differential order has a higher sensitivity than the other three parameters. Finally, the model is used to identify and fit the parameters to the data of the field-bearing plate rheological tests. The fit results of the fractional-order generalised Kelvin model, unlike those of the integer-order generalised Kelvin model, are closer to the measured results and can more accurately describe the rock’s rheological behaviour at the test location.
Seismic Data Denoising Based on Wavelet Transform and the Residual Neural Network
Authors: Lan Tianwei , Zeng Zhaofa , Han Liguo , Zeng Jingwen
Published: January 2023

The neural network denoising technique has achieved impressive results by being able to automatically learn the effective signal from the data without any assumptions. However, it has been found experimentally that the performance of the method using neural networks gradually decreases with increasing pollution levels when processing contaminated seismic data, and how to improve the performance will become the direction of further development of the method. As a traditional method widely used for tainted seismic data, the wavelet transform can effectively separate the signal from the noise. Thus, we propose a method combining wavelet transform and a residual neural network that achieves good results in suppressing random noise data.
Fast Real-Time Data Process Analysis Based on NoSQL for IoT Pavement Quality Management Platform
Authors: Hong Sung-Sam , Lee Jaekang , Chung Suwan , Kim Byungkon
Published: January 2023

The quality of road pavements is highly impacted by environmental variables, such as temperature, humidity, and weather; and construction-related variables, such as material quality and time. In this paper, an advanced data collection and analysis system based on big data/cloud was proposed for the use of IoT location-based smart platforms for pavement quality big data at road pavement sites. For the big data platform, a relational database management system (RDBMS) for a general alphanumeric data-based infrastructure for IoT-based systems was designed based on distributed/parallel processing to enable rapid and big data collection and analysis. The structure was established based on a NoSQL-based database to enable real-time high-speed collection and analysis, and the big data platform was developed as a data collection and visualization infrastructure. When the big data system was studied using data analysis methods, the proposed system demonstrated improvements in data collection performance and analysis speed, indicating that analysis results could be derived in real time. Specifically, the data collection processing (create) speed of the NoSQL-based system (0.405 ms) was significantly higher than that of the compared existing system (21.146 ms). Real-time processing capacity was also verified based on quality big data generated on actual road pavements, and the proposed system was proven suitable for the real-time monitoring (the data collection processing) of road pavement quality big data.
Pavement Structure Characteristics and Behaviour Analysis with Digital Image Correlation
Authors: Barišić Ivana , Dokšanović Tihomir , Zvonarić Matija
Published: January 2023

Digital image correlation (DIC) is a method of point displacement measurement by an optical system. If two cameras are used for capturing the same point displacement, three-dimensional data are obtained using the 3D-DIC method. The areas of application of this method in pavement construction are diverse, but it is mainly used for displacement monitoring during standard tests of the failure of specimens due to load application. Furthermore, DIC technology was used only for testing particular material characteristics and assuming their influence on the overall pavement system. Within this research, DIC was applied in two areas: defining material mechanical characteristics and analyses of pavement structure behaviour under cyclic loading. The scope of this research was to gain more insights into DIC’s potential application within pavement behaviour analyses, specifically on cement-bound granular material (CBGM) characterisation. Results from this study confirm the suitability of 3D-DIC technology for pavement material characterisation. Furthermore, it is shown that certain trends of material behaviour defined on the simple material level of each independent pavement layer will significantly differ when it is placed in the system, and this kind of complex analysis is possible by using 3D-DIC technology.
Inspiring Real-Time Evaluation and Optimization of Human–Robot Interaction with Psychological Findings from Human–Human Interaction
Authors: Liu Huashuo , Wang Fei , Zhang Dan
Published: January 2023

The increasingly central role of robotic agents in daily life requires effective human–robot interaction (HRI). For roboticists to optimize interaction design, it is crucial to understand the potential effects of robotic agents on human performance. Yet a systematic specification of contributing factors is lacking, and objective measures of HRI performance are still limited. In these regards, the findings of research on human–human interaction can provide valuable insights. In this review, we break down the complex effects of robotic agents on interacting humans into some basic building blocks based on human–human interaction findings, i.e., the potential effects of physical presence, motor actions, and task co-representation in HRI. For each effect, we advise on future directions regarding its implication. Furthermore, we propose that the neural correlates of these effects could support real-time evaluation and optimization of HRI with electroencephalograph (EEG)-based brain–computer interface (BCI).
Evaluation and Comparison of Cortisol Levels in Saliva and Hair among Dental Students
Authors: AlSarhan Mohammed A. , AlJasser Reham N. , AlOraini Saleh , Habib Syed Rashid , Alayoub Rawan Ahmad , Almutib Lulwah Tawfiq , Aldokhi Haya Dokhi , AlKhalaf Heyam Humood
Published: January 2023

Cortisol has frequently been used as a stress marker, and the variation in cortisol levels in saliva and hair, as well as between males and females, has been reported. This study aimed to evaluate and compare the level of cortisol variation in hair and saliva among dental students of both genders. After giving written agreement, 151 students (79 males and 72 females) participated in the study. Saliva and hair samples were collected at two time intervals with a gap of three months from the same set of participants. Saliva and hair samples were utilized to measure the levels of cortisol using an enzyme-linked immunosorbent assay (ELISA). Each participant’s salivary and hair cortisol levels and demographic information, including age and gender, were recorded. To examine group comparisons, two-tailed Student’s t-tests were used (α < 0.05). The comparisons of salivary and hair cortisol levels showed significant difference (p < 0.05) at two time intervals. Genderwise comparisons of the salivary and hair cortisol’s levels showed significant differences (p < 0.05) for male students, while, for female students, the comparisons showed non-significant differences (p > 0.05). Comparisons between the cortisol levels of the two specimen collections at the two different time intervals indicated substantial variations (p = 0.000). Results confirm the variations in the cortisol levels in the saliva and hair samples. Cortisol concentrations in hair and saliva at the two times points varied. Significant variations between the male students salivary and hair cortisol levels and non-significant differences between the cortisol levels for the female students at the two time points were found. Cortisol levels in the selected subjects’ saliva and hair samples varied.
Alpha-Mangostin Suppresses LPS-Induced Inflammation in Human Dental Pulp Cells
Authors: Kim Yu-Seon , Jang Ji-Hyun , Koh Jeong-Tae , Hwang Yun-Chan , Oh Won-Mann , Lee Bin-Na
Published: January 2023

Xanthones are secondary metabolites isolated from the peel of mangosteen showing medicinal potencies. Alpha-mangostin (α-MG) is the most plentiful xanthone, which has been reported to possess anti-inflammatory, anti-oxidant, and anti-bacterial activities. We aimed to investigate the anti-inflammatory effects of xanthones on LPS-treated hDPCs. Cell viability was determined using the WST-1 assay. The mRNA and protein expression profiles of inflammatory mediators were evaluated using quantitative real-time polymerase chain reaction (qPCR) and Western blot analysis. Anti-inflammatory effects were assessed using the Western blot analysis to examine underlying mechanisms. A one-way analysis of variance followed by Tukey’s post hoc test was used to determine statistically significant differences (p < 0.05). The study found no significant differences between the cytotoxic effects in the α-MG-treated groups and controls. The mRNA and protein expression levels of inflammatory markers in the α-MG treated groups decreased. α-MG significantly inhibited LPS-induced phosphorylation of proteins associated with the MAPK and NF-κB pathways. This study suggests that α-MG exerts anti-inflammatory effects by suppressing the MAPK and NF-κB signaling pathways in LPS-treated hDPCs.
Blockchain for the Healthcare Supply Chain: A Systematic Literature Review
Authors: Fiore Matteo , Capodici Angelo , Rucci Paola , Bianconi Alessandro , Longo Giulia , Ricci Matteo , Sanmarchi Francesco , Golinelli Davide
Published: January 2023

A supply chain (SC) is a network of interests, information, and materials involved in processes that produce value for customers. The implementation of blockchain technology in SC management in healthcare has had results. This review aims to summarize how blockchain technology has been used to address SC challenges in healthcare, specifically for drugs, medical devices (DMDs), and blood, organs, and tissues (BOTs). A systematic review was conducted by following the PRISMA guidelines and searching the PubMed and Proquest databases. English-language studies were included, while non-primary studies, as well as surveys, were excluded. After full-text assessment, 28 articles met the criteria for inclusion. Of these, 15 (54%) were classified as simulation studies, 12 (43%) were classified as theoretical, and only one was classified as a real case study. Most of the articles (n = 23, 82%) included the adoption of smart contracts. The findings of this systematic review indicated a significant but immature interest in the topic, with diverse ideas and methodologies, but without effective real-life applications.
Rogue Node Detection Based on a Fog Network Utilizing Parked Vehicles
Authors: Hua Jiwei , Zhang Bo , Wang Jinao , Shao Xin , Zhu Jinqi
Published: January 2023

Rogue nodes in the Internet of vehicles (IoV) bring traffic congestion, vehicle collision accidents and other problems, which will cause great social losses. Therefore, rogue node discovery plays an important role in building secure IoV environments. Existing machine learning-based rogue node detection methods rely too much on historical data, and these methods may lead to long network delay and slow detection speed. Moreover, methods based on Roadside Units (RSUs) have poor performance if the number of RSUs is insufficient. Based on the widespread presence of ground vehicles, we propose a rogue node detection scheme based on the fog network formed by roadside parked vehicles. To achieve efficient rogue node discovery, a fog network composed of stable roadside parked vehicles is dynamically established, in which each fog node firstly collects the information of moving vehicles on the road in its coverage range, and then fog nodes use the U-test method to determine the rogue nodes in parallel, so as to find the bad nodes efficiently. Simulation results show that the proposed algorithm has higher detection accuracy and stability than the other rogue node detection schemes.
A Mixed Integer Linear Programming Model with Heuristic Improvements for Single-Track Railway Rescheduling Problem
Authors: Aydın Gökçe , Şahin İsmail
Published: January 2023

A rescheduling algorithm for trains on a single-track railway was developed in case of disturbances that would cause conflicts between trains. This algorithm is based on mixed integer linear programming (MILP) with speed-up routines. The model considers station capacities explicitly (i.e., the number of available tracks for meeting and overtaking operations). Because the model is too hard for the solvers (CPLEX in this study) to tackle, three speed-up routines were devised when rescheduling trains. These routines are a greedy heuristic to reduce the solution space, using the lazy constraint attribute of the solver and a multiobjective approach to find a good initial feasible solution that conforms to actual railway operation. The algorithm was tested on a hypothetical rail line for different sizes of timetable instances with disturbed trains in a maximum two-hour time horizon. It managed to solve the hardest instances within a three-minute time limit thus minimizing the total weighted delay of rescheduled trains. The optimality gap metric is used to show the effectiveness and efficiencies of the speed-up heuristics developed.
The Definition of Perennial Streams Based on a Wet Channel Network Extracted from LiDAR Data
Authors: Kim Seoyoung , Yoon Sun-Kwon , Choi Namjeong
Published: January 2023

This study assesses the characteristics of perennial streams using the dimensionless relationship between streamflow exceedance probability and the wet channel ratio based on a wet channel network extracted from light detection and ranging (LiDAR) data. LiDAR provides topographic data and signals’ intensity in high-resolution and with high accuracy to provide useful information for drainage networks and channel network extraction. In this study, a valley network and wet channel are extracted from LiDAR topographic and signals’ intensity information with a spatial resolution of 1 meter. Based on the available LiDAR data and streamflow observations from across the United States, we selected 30 watersheds with various climate conditions and analyzed the characteristics of their perennial streams. The wet channel ratio and perennial stream ratio were developed to define a perennial stream using the observed streamflow and the identified wet channel. The results of this study are consistent with previous studies on the definition of a perennial stream through transformation into a dimensionless form and confirmed the possibility of applying the wet channel ratio as an alternative parameter to define a perennial stream.
Evaluation of the CAS-ESM2-0 Performance in Simulating the Global Ocean Salinity Change
Authors: Li Guancheng , Cheng Lijing , Wang Xutao
Published: January 2023

The second version of the Chinese Academy of Sciences Earth System Model, CAS-ESM2-0, is a newcomer that contributes to Coupled Model Intercomparison Project simulations in the community. We evaluated the model’s performance in simulating the salinity for climatology, seasonal cycles, long-term trends, and time series of climatic metrics by comparing it with the ensemble mean of available gridded observations. The results showed that CAS-ESM2-0 could reproduce large-scale patterns of ocean salinity climatology and seasonal variations, despite the fresh biases in the low- and mid-latitudes for climatology, stronger seasonal variation of sea surface salinity within 20° S–20° N, and large uncertainty with the zonal-band structure for 0–1000 m averaged salinity. For long-term changes, the model revealed increased contrast between the salinity of the Atlantic and Pacific basins. However, regional differences in locations and strengths for salinity pattern amplification suggest substantial uncertainty when simulating regional multidecadal salinity changes. The simulated variations in climate metrics for salinity pattern amplification are consistent with the observations and will continue to intensify until the end of this century. Our assessment provides new features of the CAS-ESM2-0 model and supports further studies on model development.
Quadrature Methods for Singular Integral Equations of Mellin Type Based on the Zeros of Classical Jacobi Polynomials
Authors: Junghanns Peter , Kaiser Robert
Published: January 2023

In this paper we formulate necessary conditions for the stability of certain quadrature methods for Mellin type singular integral equations on an interval. These methods are based on the zeros of classical Jacobi polynomials, not only on the Chebyshev nodes. The method is considered as an element of a special C*-algebra such that the stability of this method can be reformulated as an invertibility problem of this element. At the end, the mentioned necessary conditions are invertibility properties of certain linear operators in Hilbert spaces. Moreover, for the proofs we need deep results on the zero distribution of the Jacobi polynomials.
New Developments in Geometric Function Theory
Authors: Oros Georgia Irina
Published: January 2023

This Special Issue aims to highlight the latest developments in the research concerning complex-valued functions from the perspective of geometric function theory [...]
High-Performance Metal–Chalcogen Batteries
Authors: Zhang Long
Published: January 2023

The rapid proliferation in the market for smart devices, electric vehicles, and power grids over the past decade has substantially increased the demand for commercial lithium-ion batteries (LIBs) [...]
Rapid Scan Electron Paramagnetic Resonance Spectroscopy Is a Suitable Tool to Study Intermolecular Interactions of Intrinsically Disordered Protein
Authors: Dröden Jessica , Drescher Malte
Published: January 2023

Intrinsically disordered proteins (IDPs) are involved in most crucial cellular processes. However, they lack a well-defined fold hampering the investigation of their structural ensemble and interactions. Suitable biophysical methods able to manage their inherent flexibility and broad conformational ensemble are scarce. Here, we used rapid scan (RS) electron paramagnetic resonance (EPR) spectroscopy to study the intermolecular interactions of the IDP α-synuclein (aS). aS aggregation and fibril deposition is the hallmark of Parkinson’s disease, and specific point mutations, among them A30P and A53T, were linked to the early onset of the disease. To understand the pathological processes, research intensively investigates aS aggregation kinetics, which was reported to be accelerated in the presence of ethanol. Conventional techniques fail to capture these fast processes due to their limited time resolution and, thus, lose kinetic information. We have demonstrated that RS EPR spectroscopy is suitable for studying aS aggregation by resolving underlying kinetics and highlighting differences in fibrillization behavior. RS EPR spectroscopy outperforms traditional EPR methods in terms of sensitivity by a factor of 5 in our case while significantly reducing data acquisition time. Thus, we were able to sample short time intervals capturing single events taking place during the aggregation process. Further studies will therefore be able to shed light on biological processes proceeding on fast time scales.
Biomechanics of Traumatic Head and Neck Injuries on Women: A State-of-the-Art Review and Future Directions
Authors: Carmo Gustavo P. , Grigioni Jeroen , Fernandes Fábio A. O. , Alves de Sousa Ricardo J.
Published: January 2023

The biomechanics of traumatic injuries of the human body as a consequence of road crashes, falling, contact sports, and military environments have been studied for decades. In particular, traumatic brain injury (TBI), the so-called “silent epidemic”, is the traumatic insult responsible for the greatest percentage of death and disability, justifying the relevance of this research topic. Despite its great importance, only recently have research groups started to seriously consider the sex differences regarding the morphology and physiology of women, which differs from men and may result in a specific outcome for a given traumatic event. This work aims to provide a summary of the contributions given in this field so far, from clinical reports to numerical models, covering not only the direct injuries from inertial loading scenarios but also the role sex plays in the conditions that precede an accident, and post-traumatic events, with an emphasis on neuroendocrine dysfunctions and chronic traumatic encephalopathy. A review on finite element head models and finite element neck models for the study of specific traumatic events is also performed, discussing whether sex was a factor in validating them. Based on the information collected, improvement perspectives and future directions are discussed.
Strategies to Ensure Fuel Security in Brazil Considering a Forecast of Ethanol Production
Authors: de Oliveira Gonçalves Felipe , Firmani Perna Rafael , Savioli Lopes Emília , Plazas Tovar Laura , Maciel Filho Rubens , Savioli Lopes Melina
Published: January 2023

Ethanol production in Brazil started in the early 1930s due to laws created by the Brazilian government. However, ethanol production only increased significantly with the National Program of Ethanol implementation in 1975. This program was another action taken by the Brazilian government aiming to provide conditions for the development of the ethanol industry in the country. With the program, it was possible to achieve significant progress; however, it finished in the mid-1980s. Currently, ethanol is produced on a large scale by more than 300 sugarcane mills all over the country. In 2016, the Brazilian government provided another incentive for ethanol production by creating the RenovaBio Program, which aimed to reduce greenhouse gas emissions. Besides the environmental aspect, Brazil’s ethanol industry needs to develop to supply future biofuel demand. According to the forecast provided in this paper, and considering technical, economic, and environmental aspects regarding the Brazilian ethanol industry, the current and only feedstock used is likely to be insufficient. Thus, the ethanol produced from corn would be an attractive secondary feedstock to complement sugarcane ethanol as the primary feedstock.
Mechanical and Biomimetic Characteristics of Bulk-Fill Resin Dental Composites Following Exposure in a Simulated Acidic Oral Environment
Authors: Dahri Waheed Murad , Kumar Naresh , Altaf Noorulain , Mughal Waqas , Zafar Muhammad Sohail
Published: January 2023

During the last 10 years, various companies have marketed different “bulk-fill” resin dental composites for the restoration of posterior stress-bearing teeth; however, the impact of acidic conditions on these relatively newer materials has not been thoroughly investigated. Therefore, an attempt was made to evaluate the effect of acidic beverages on the mechanical biomimetic characteristics of four bulk-fill and one conventional nanohybrid resin-based dental composites (RBCs). The specimens of each RBC were stored in two acidic beverages namely ‘Orange Juice’ and ‘Coca-Cola’, whereas ‘dry’ and ‘distilled water’ storage of specimens served as controls. After 1 week of storage, flexural and surface hardness properties of specimens were determined using a universal testing machine and Vickers hardness tester, respectively. In general, the ‘Coca-Cola’ beverage caused the greatest degradation of flexural strength, flexural modulus, and surface hardness characteristics in all RBCs in contrast to the ‘dry’, ‘distilled water’ controls and ‘Orange Juice’ storage conditions. However, the overall mechanical biomimetic performance of nanohybrid RBCs was relatively better than all other bulk-fill RBCs and may, therefore, be considered a suitable candidate for the restoration of posterior stress-bearing permanent dentition.
Balance Rehabilitation through Robot-Assisted Gait Training in Post-Stroke Patients: A Systematic Review and Meta-Analysis
Authors: Loro Alberto , Borg Margherita Beatrice , Battaglia Marco , Amico Angelo Paolo , Antenucci Roberto , Benanti Paolo , Bertoni Michele , Bissolotti Luciano , Boldrini Paolo , Bonaiuti Donatella , Bowman Thomas , Capecci Marianna , Castelli Enrico , Cavalli Loredana , Cinone Nicoletta , Cosenza Lucia , Di Censo Rita , Di Stefano Giuseppina , Draicchio Francesco , Falabella Vincenzo , Filippetti Mirko , Galeri Silvia , Gimigliano Francesca , Grigioni Mauro , Invernizzi Marco , Jonsdottir Johanna , Lentino Carmelo , Massai Perla , Mazzoleni Stefano , Mazzon Stefano , Molteni Franco , Morelli Sandra , Morone Giovanni , Nardone Antonio , Panzeri Daniele , Petrarca Maurizio , Posteraro Federico , Santamato Andrea , Scotti Lorenza , Senatore Michele , Spina Stefania , Taglione Elisa , Turchetti Giuseppe , Varalta Valentina , Picelli Alessandro , Baricich Alessio
Published: January 2023

Background: Balance impairment is a common disability in post-stroke survivors, leading to reduced mobility and increased fall risk. Robotic gait training (RAGT) is largely used, along with traditional training. There is, however, no strong evidence about RAGT superiority, especially on balance. This study aims to determine RAGT efficacy on balance of post-stroke survivors. Methods: PubMed, Cochrane Library, and PeDRO databases were investigated. Randomized clinical trials evaluating RAGT efficacy on post-stroke survivor balance with Berg Balance Scale (BBS) or Timed Up and Go test (TUG) were searched. Meta-regression analyses were performed, considering weekly sessions, single-session duration, and robotic device used. Results: A total of 18 trials have been included. BBS pre-post treatment mean difference is higher in RAGT-treated patients, with a pMD of 2.17 (95% CI 0.79; 3.55). TUG pre-post mean difference is in favor of RAGT, but not statistically, with a pMD of −0.62 (95%CI − 3.66; 2.43). Meta-regression analyses showed no relevant association, except for TUG and treatment duration (β = −1.019, 95% CI − 1.827; −0.210, p-value = 0.0135). Conclusions: RAGT efficacy is equal to traditional therapy, while the combination of the two seems to lead to better outcomes than each individually performed. Robot-assisted balance training should be the focus of experimentation in the following years, given the great results in the first available trials. Given the massive heterogeneity of included patients, trials with more strict inclusion criteria (especially time from stroke) must be performed to finally define if and when RAGT is superior to traditional therapy.
Prediction of Mortality in Geriatric Traumatic Brain Injury Patients Using Machine Learning Algorithms
Authors: Wang Ruoran , Zeng Xihang , Long Yujuan , Zhang Jing , Bo Hong , He Min , Xu Jianguo
Published: January 2023

Background: The number of geriatric traumatic brain injury (TBI) patients is increasing every year due to the population’s aging in most of the developed countries. Unfortunately, there is no widely recognized tool for specifically evaluating the prognosis of geriatric TBI patients. We designed this study to compare the prognostic value of different machine learning algorithm-based predictive models for geriatric TBI. Methods: TBI patients aged ≥65 from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were eligible for this study. To develop and validate machine learning algorithm-based prognostic models, included patients were divided into a training set and a testing set, with a ratio of 7:3. The predictive value of different machine learning based models was evaluated by calculating the area under the receiver operating characteristic curve, sensitivity, specificity, accuracy and F score. Results: A total of 1123 geriatric TBI patients were included, with a mortality of 24.8%. Non-survivors had higher age (82.2 vs. 80.7, p = 0.010) and lower Glasgow Coma Scale (14 vs. 7, p < 0.001) than survivors. The rate of mechanical ventilation was significantly higher (67.6% vs. 25.9%, p < 0.001) in non-survivors while the rate of neurosurgical operation did not differ between survivors and non-survivors (24.3% vs. 23.0%, p = 0.735). Among different machine learning algorithms, Adaboost (AUC: 0.799) and Random Forest (AUC: 0.795) performed slightly better than the logistic regression (AUC: 0.792) on predicting mortality in geriatric TBI patients in the testing set. Conclusion: Adaboost, Random Forest and logistic regression all performed well in predicting mortality of geriatric TBI patients. Prognostication tools utilizing these algorithms are helpful for physicians to evaluate the risk of poor outcomes in geriatric TBI patients and adopt personalized therapeutic options for them.
New Fuzzy-Heuristic Methodology for Analyzing Compression Load Capacity of Composite Columns
Authors: Karimi Sharafshadeh Bizhan , Ketabdari Mohammad Javad , Azarsina Farhood , Amiri Mohammad , Nehdi Moncef L.
Published: January 2023

Predicting the mechanical strength of structural elements is a crucial task for the efficient design of buildings. Considering the shortcomings of experimental and empirical approaches, there is growing interest in using artificial intelligence techniques to develop data-driven tools for this purpose. In this research, empowered machine learning was employed to analyze the axial compression capacity (CC) of circular concrete-filled steel tube (CCFST) composite columns. Accordingly, the adaptive neuro-fuzzy inference system (ANFIS) was trained using four metaheuristic techniques, namely earthworm algorithm (EWA), particle swarm optimization (PSO), salp swarm algorithm (SSA), and teaching learning-based optimization (TLBO). The models were first applied to capture the relationship between the CC and column characteristics. Subsequently, they were requested to predict the CC for new column conditions. According to the results of both phases, all four models could achieve dependable accuracy. However, the PSO-ANFIS was tangibly more efficient than the other models in terms of computational time and accuracy and could attain more accurate predictions for extreme conditions. This model could predict the CC with a relative error below 2% and a correlation exceeding 99%. The PSO-ANFIS is therefore recommended as an effective tool for practical applications in analyzing the behavior of the CCFST columns.
Modulating Effects of Cancer-Derived Exosomal miRNAs and Exosomal Processing by Natural Products
Authors: Chuang Ya-Ting , Tang Jen-Yang , Shiau Jun-Ping , Yen Ching-Yu , Chang Fang-Rong , Yang Kun-Han , Hou Ming-Feng , Farooqi Ammad Ahmad , Chang Hsueh-Wei
Published: January 2023

Cancer-derived exosomes exhibit sophisticated functions, such as proliferation, apoptosis, migration, resistance, and tumor microenvironment changes. Several clinical drugs modulate these exosome functions, but the impacts of natural products are not well understood. Exosome functions are regulated by exosome processing, such as secretion and assembly. The modulation of these exosome-processing genes can exert the anticancer and precancer effects of cancer-derived exosomes. This review focuses on the cancer-derived exosomal miRNAs that regulate exosome processing, acting on the natural-product-modulating cell functions of cancer cells. However, the role of exosomal processing has been overlooked in several studies of exosomal miRNAs and natural products. In this study, utilizing the bioinformatics database (miRDB), the exosome-processing genes of natural-product-modulated exosomal miRNAs were predicted. Consequently, several natural drugs that modulate exosome processing and exosomal miRNAs and regulate cancer cell functions are described here. This review sheds light on and improves our understanding of the modulating effects of exosomal miRNAs and their potential exosomal processing targets on anticancer treatments based on the use of natural products.
Discovering the Clinical and Prognostic Role of Pan-Immune-Inflammation Values on Oral Cavity Squamous Cell Carcinoma
Authors: Yeh Chia-Chi , Kao Huang-Kai , Huang Yenlin , Tsai Tsung-You , Young Chi-Kuang , Hung Shao-Yu , Lu Chuieng-Yi , Chang Kai-Ping
Published: January 2023

A newly introduced pan-immune-inflammation value (PIV) was not evaluated for its role in oral cavity squamous cell carcinoma (OSCC). In this study, the PIV was calculated with the following equation (neutrophil count × platelet count × monocyte count)/lymphocyte count from the results of the automated hematology analyzers in 853 OSCC patients from 2005 to 2017. The optimal cutoff for the preoperative PIV was 268, as determined by a receiver operating characteristic curve. Significant differences were observed for alcohol consumption, smoking, pT status, pN status, overall pathological status, extranodal extension, cell differentiation, depth of invasion, and perineural invasion between higher and lower PIV patients (all p values < 0.05). Kaplan-Meier and univariate regression analyses indicated that higher PIV was associated with worse overall survival, disease-free survival, locoregional recurrence-free survival, and distant metastasis-free survival (all p values < 0.001). Multivariate analyses adjusted by various factors further demonstrated that PIV was an independent prognostic factor for overall and distant metastasis-free survival (p = 0.027, HR: 1.281 and p = 0.031, HR: 1.274, respectively). In conclusion, a higher PIV level was associated with poor clinicopathological factors in OSCC patients and could be used to predict poor posttreatment outcomes, especially for overall and distant metastasis-free survival.
Early Subcellular Hepatocellular Alterations in Mice Post Hydrodynamic Transfection: An Explorative Study
Authors: Yasser Mohd , Ribback Silvia , Evert Katja , Utpatel Kirsten , Annweiler Katharina , Evert Matthias , Dombrowski Frank , Calvisi Diego F.
Published: January 2023

Hydrodynamic transfection (HT) or hydrodynamic tail vein injection (HTVi) is among the leading technique that is used to deliver plasmid genes mainly into the liver of live mice or rats. The DNA constructs are composed of coupled plasmids, while one contains the gene of interest that stably integrate into the hepatocyte genome with help of the other consisting sleeping beauty transposase system. The rapid injection of a large volume of DNA-solution through the tail vein induces an acute cardiac congestion that refluxed into the liver, mainly in acinus zone 3, also found through our EM study. Although, HT mediated hydrodynamic force can permeabilizes the fenestrated sinusoidal endothelium of liver, but the mechanism of plasmid incorporation into the hepatocytes remains unclear. Therefore, in the present study, we have hydrodynamically injected 2 mL volume of empty plasmid (transposon vector) or saline solution (control) into the tail vein of anesthetized C57BL/6J/129Sv mice. Liver tissue was resected at different time points from two animal group conditions, i.e., one time point per animal (1, 5, 10–20, 60 min or 24 and 48 hrs after HT) or multiple time points per animal (0, 1, 2, 5, 10, 20 min) and quickly fixed with buffered 4% osmium tetroxide. The tissues fed with only saline solution was also resected and fixed in the similar way. EM evaluation from the liver ultrathin sections reveals that swiftly after 1 min, the hepatocytes near to the central venule in the acinus zone 3 shows cytoplasmic membrane-bound vesicles. Such vesicles increased in both numbers and size to vacuoles and precisely often found in the proximity to the nucleus. Further, EM affirm these vacuoles are also optically empty and do not contain any electron dense material. Although, some of the other hepatocytes reveals sign of cell damage including swollen mitochondria, dilated endoplasmic reticulum, Golgi apparatus and disrupted plasma membrane, but most of the hepatocytes appeared normal. The ultrastructural findings in the mice injected with empty vector or saline injected control mice were similar. Therefore, we have interpreted the vacuole formation as nonspecific endocytosis without specific interactions at the plasma membrane.
A Review on Properties and Environmental Applications of Graphene and Its Derivative-Based Composites
Authors: Kumar Sanjay , Himanshi  , Prakash Jyoti , Verma Ankit , Suman  , Jasrotia Rohit , Kandwal Abhishek , Verma Ritesh , Kumar Godara Sachin , Khan M. A. Majeed , Alshehri Saad M. , Ahmed Jahangeer
Published: January 2023

Graphene-based materials have gained a lot of scientific interest in the research era of modern technology, which can be quite flexible. Graphene has become popular as a potential material for the manufacture of a wide range of technologies due to its remarkable electrical, mechanical, and optical traits. Due to these excellent characteristics, the derivatives of graphene can be functionalized in various applications including environmental, medical, electronic, defence applications, and many more. In this review paper, we discussed the different synthesis methods for the extraction of graphene and its derivatives. The different traits of graphene and its derivatives such as structural, mechanical, and optical were also discussed. An extensive literature review on the application of graphene-based composites is presented in this work. We also outlined graphene’s potential in the realm of environmental purification through different techniques such as filtration, adsorption, and photocatalysis. Lastly, the challenges and opportunities of graphene and its derivatives for advanced environmental applications were reported.
Pseudomonas aeruginosa Cytotoxins: Mechanisms of Cytotoxicity and Impact on Inflammatory Responses
Authors: Wood Stephen J. , Goldufsky Josef W. , Seu Michelle Y. , Dorafshar Amir H. , Shafikhani Sasha H.
Published: January 2023

Pseudomonas aeruginosa is one of the most virulent opportunistic Gram-negative bacterial pathogens in humans. It causes many acute and chronic infections with morbidity and mortality rates as high as 40%. P. aeruginosa owes its pathogenic versatility to a large arsenal of cell-associated and secreted virulence factors which enable this pathogen to colonize various niches within hosts and protect it from host innate immune defenses. Induction of cytotoxicity in target host cells is a major virulence strategy for P. aeruginosa during the course of infection. P. aeruginosa has invested heavily in this strategy, as manifested by a plethora of cytotoxins that can induce various forms of cell death in target host cells. In this review, we provide an in-depth review of P. aeruginosa cytotoxins based on their mechanisms of cytotoxicity and the possible consequences of their cytotoxicity on host immune responses.
Dynamic 3D Modeling for Human Sperm Motility through the Female Cervical Canal and Uterine Cavity to Predict Sperm Chance of Reaching the Oocyte
Authors: Nassir Mayssam , Levi Mattan , Shaked Natan T.
Published: January 2023

Sperm motility in the female genital tract is a key factor in the natural selection of competent cells that will produce a healthy offspring. We created a dynamic three-dimensional (3D) mechanical model of human sperm cells swimming inside cervical canal and uterine cavity dynamic 3D models, all generated based on experimental studies. Using these simulations, we described the sperm cells’ behaviors during swimming inside the 3D tract model as a function of 3D displacement and time. We evaluated normal- and abnormal-morphology sperm cells according to their chances of reaching the oocyte site. As expected, we verified that the number of normal sperm cells that succeeded in reaching the fallopian tube sites is greater than the number of abnormal sperm cells. However, interestingly, after inspecting various abnormal sperm cells, we found out that their scores changed compared to swimming in an infinite medium, as is the case with in vitro fertilization. Thus, the interactions of abnormal sperm cells and the complicated geometry and dynamics of the uterus are significant factors in the filtering of abnormal sperm cells until they reach the oocyte site. Our study provides an advanced tool for sperm analysis and selection criteria for fertility treatments.