bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Dietary Alpha-Lipoic Acid on Growth Performance, Serum Biochemical Indexes, Liver Antioxidant Capacity and Transcriptome of Juvenile Hybrid Grouper (Epinephelus fuscoguttatus♀ × Epinephelus polyphekadion♂)
Authors: Ou Guanghai , Xie Ruitao , Huang Jiansheng , Huang Jianpeng , Wen Zhenwei , Li Yu , Jiang Xintao , Ma Qian , Chen Gang
Published: March 2023

We aimed to investigate the effects of dietary alpha-lipoic acid (α-LA) on the growth performance, serum biochemical indexes, liver morphology, antioxidant capacity, and transcriptome of juvenile hybrid groupers (Epinephelus fuscoguttatus♀ × Epinephelus polyphekadion♂). Four experimental diets supplemented with 0 (SL0), 0.4 (L1), 0.6 (L2), and 1.2 (L3) g/kg α-LA were formulated and fed to three replicates of juvenile hybrid grouper (24.06 ± 0.15 g) for 56 d. The results indicated that dietary 0.4 and 0.6 g/kg α-LA significantly decreased the weight gain rate in juvenile hybrid groupers. Compared with SL0, the content of total protein in the serum of L1, L2, and L3 increased significantly, and alanine aminotransferase decreased significantly. The content of albumin in the serum of L3 increased significantly, and triglyceride, total cholesterol, and aspartate aminotransferase decreased significantly. In addition, the hepatocyte morphology in L1, L2, and L3 all showed varying degrees of improvement, and the activities of glutathione peroxidase and superoxide dismutase in the liver of L2 and L3 were significantly increased. A total of 42 differentially expressed genes were screened in the transcriptome data. KEGG showed that a total of 12 pathways were significantly enriched, including the pathway related to immune function and glucose homeostasis. The expression of genes (ifnk, prl4a1, prl3b1, and ctsl) related to immune were significantly up-regulated, and the expressions of gapdh and eno1 genes related to glucose homeostasis were significantly down-regulated and up-regulated, respectively. In summary, dietary supplementation of 0.4 and 0.6 g/kg α-LA inhibited the growth performance of juvenile hybrid groupers. A total of 1.2 g/kg α-LA could reduce the blood lipid level, improve hepatocyte damage, and increase the hepatic antioxidant enzyme activity. Dietary α-LA significantly affected the pathway related to immune function and glucose homeostasis.
The Oral Inactivated Porcine Epidemic Diarrhea Virus Presenting in the Intestine Induces Mucosal Immunity in Mice with Alginate–Chitosan Microcapsules
Authors: Qin Ziliang , Nai Zida , Li Gang , He Xinmiao , Wang Wentao , Xia Jiqiao , Chao Wang , Li Lu , Jiang Xinpeng , Liu Di
Published: March 2023

The porcine epidemic diarrhea virus, PEDV, which causes diarrhea, vomiting and death in piglets, causes huge economic losses. Therefore, understanding how to induce mucosal immune responses in piglets is essential in the mechanism and application against PEDV infection with mucosal immunity. A method of treatment in our research was used to make an oral vaccine that packaged the inactive PEDV with microencapsulation, which consisted of sodium alginate and chitosan, and adapted the condition of the gut in mice. The in vitro release experiment of microcapsules showed that inactive PEDV was not only easily released in saline and acid solutions but also had an excellent storage tolerance, and was suitable for use as an oral vaccine. Interestingly, both experimental groups with different doses of inactive virus enhanced the secretion of specific antibodies in the serum and intestinal mucus, which caused the effective neutralization against PEDV in the Vero cell by both IgG and IgA, respectively. Moreover, the microencapsulation could stimulate the differentiation of CD11b+ and CD11c+ dendritic cells, which means that the microencapsulation was also identified as an oral adjuvant to help phagocytosis of dendritic cells in mice. Flow cytometry revealed that the B220+ and CD23+ of the B cells could significantly increase antibody production with the stimulation from the antigens’ PEDV groups, and the microencapsulation could also increase the cell viability of B cells, stimulating the secretion of antibodies such as IgG and IgA in mice. In addition, the microencapsulation promoted the expression of anti-inflammatory cytokines, such as IL-10 and TGF-β. Moreover, proinflammatory cytokines, such as IL-1, TNF-α, and IL-17, were inhibited by alginate and chitosan in the microencapsulation groups compared with the inactivated PEDV group. Taken together, our results demonstrate that the microparticle could play the role of mucosal adjuvant, and release inactivated PEDV in the gut, which can effectively stimulate mucosal and systemic immune responses in mice.
The Effect of Neem Leaf Supplementation on Growth Performance, Rumen Fermentation, and Ruminal Microbial Population in Goats
Authors: Taethaisong Nittaya , Paengkoum Siwaporn , Kaewwongsa Walailuck , Onjai-uea Narawich , Thongpea Sorasak , Paengkoum Pramote
Published: March 2023

This study aims to investigate the effect of neem leaf supplementation on the feed intake, digestibility, performance, fermentation characteristics, and ruminal microbes in goats. We included 24 Anglo-Nubian Thai native male goats with a body weight of 20 ± 2.0 kg, using 2 × 2 factorial in a completely randomized design for the following four treatments: (1) control, (2) control + 15% PEG in the concentrate, (3) 6% NL in concentrate, and (4) 6% NL + 15% PEG in concentrate. The results show that supplementation with 6% NL + 15% PEG in the concentrate had a higher (p < 0.05) feed intake gDM/d, % BW, g/kgBW0.75, nutrient intake, nutrient digestion, weight change, and ADG than did the goats that were fed with 0% NL + 0% PEG, 0% NL + 15% PEG, and 6% NL + 0% PEG in concentrate, respectively. The feeding with 6% NL + 15% PEG had a higher (p < 0.05) level of propionic acid at 2 and 4 h post feeding compared to the other treatments. Supplementation with 6% NL + 15% PEG in the concentrate had the lowest (p < 0.05) methanogen, protozoa, blood urea nitrogen, ammonia nitrogen, acetic acid, and butyric acid, as well as a lower ratio of acetic acid to propionic acid at 2 and 4 h post feeding than the other treatments. However, supplementation with 6% NL + 15% PEG in concentrate had the highest values of Butyrivibrio fibrisolvens and Streptococcus gallolyticus at 2 and 4 h post feeding compared to the other treatments (p < 0.05). Collectively, this study indicates that neem leaf supplements can increase growth performance and propionic acid and can modulate the abundance of Butyrivibrio fibrisolvens and Streptococcus gallolyticus. Thus, neem leaf could potentially be a good supplement for goat feed.
Hepatitis E Virus (HEV) Spreads from Pigs and Sheep in Mongolia
Authors: Batmagnai Enkhbaatar , Boldbaatar Bazartseren , Sodbayasgalan Amarbayasgalan , Kato-Mori Yuko , Hagiwara Katsuro
Published: March 2023

Hepatitis E is a viral infectious disease in pigs, wild boars, cows, deer, rabbits, camels, and humans as hosts caused by Paslahepevirus. Recently, it has been detected in a wide variety of animals including domestic small ruminants. Mongolia is a land of nomadic people living with livestock such as sheep, goats, and cattle. Due to how Mongolian lifestyles have changed, pork has become popular and swine diseases have emerged. Among them, Hepatitis E disease has become a zoonotic infectious disease that needs to be addressed. The HEV problem in pigs is that infected pigs excrete the virus without showing clinical symptoms and it spreads into the environment. We attempted to detect HEV RNA in sheep which had been raised in Mongolia for a long time, and those animals living together with pigs in the same region currently. We also conducted a longitudinal analysis of HEV infection in pigs in the same area and found that they were infected with HEV of the same genotype and cluster. In this study, we examined 400 feces and 120 livers (pigs and sheep) by RT-PCR in Töv Province, Mongolia. HEV detection in fecal samples was 2% (4/200) in sheep and 15% (30/200) in pigs. The results of ORF2 sequence analysis of the HEV RT-PCR-positive pigs and sheep confirmed genotype 4 in both animals. The results suggest that HEV infection is widespread in both pigs and sheep and that urgent measures to prevent infection are needed. This case study points to the changing nature of infectious diseases associated with livestock farming. It will be necessary to reconsider livestock husbandry and public health issues based on these cases.
Special Issue on Electroporation Systems and Applications
Authors: Novickij Vitalij
Published: March 2023

High pulsed electric fields (PEF) trigger the phenomenon of a transient increase in the permeability of the plasma membranes of biological cells, which is known as electroporation [...]
Unmanned Surface Vehicle Using a Leader–Follower Swarm Control Algorithm
Authors: Lee Ji-Hyeong , Jeong Sang-Ki , Ji Dae-Hyeong , Park Hae-Yong , Kim Do-Young , Choo Ki-Beom , Jung Dong-Wook , Kim Myung-Jun , Oh Myoung-Hak , Choi Hyeung-Sik
Published: March 2023

To overcome the limitations of a single unmanned surface vehicle (USV), this study investigated the swarm control algorithms of USVs. Among various swarm control methods, a leader–follower swarm control method was selected and studied. The performance of the swarm algorithm proposed in this study was verified through an actual sea area test. A USV was designed and manufactured by dividing the power and communication parts. The power system was equipped with a coulometer to monitor the battery state in real time to protect the system through a switch linked to the coulometer in the case of abnormalities in the battery and to prevent accidents. In addition, a communication system was established to process the sensor data and camera image data of the USV in real time. Consequently, the desired swarm formation was achieved through the separately constructed swarm control algorithm. Before the actual sea area test, individual performance tests of each sensor were conducted. Finally, the performance of the swarm algorithm was verified by conducting a sea area test. The performance of the controllers was confirmed to be good, and the swarm formation was confirmed to be successful.
Academic Teaching Quality Framework and Performance Evaluation Using Machine Learning
Authors: Almufarreh Ahmad , Noaman Khaled Mohammed , Saeed Muhammad Noman
Published: March 2023

Higher education institutions’ principal goal is to give their learners a high-quality education. The volume of research data gathered in the higher education industry has increased dramatically in recent years due to the fast development of information technologies. The Learning Management System (LMS) also appeared and is bringing courses online for an e-learning model at almost every level of education. Therefore, to ensure the highest level of excellence in the higher education system, finding information for predictions or forecasts about student performance is one of many tasks for ensuring the quality of education. Quality is vital in e-learning for several reasons: content, user experience, credibility, and effectiveness. Overall, quality is essential in e-learning because it helps ensure that learners receive a high-quality education and can effectively apply their knowledge. E-learning systems can be made more effective with machine learning, benefiting all stakeholders of the learning environment. Teachers must be of the highest caliber to get the most out of students and help them graduate as academically competent and well-rounded young adults. This research paper presents a Quality Teaching and Evaluation Framework (QTEF) to ensure teachers’ performance, especially in e-learning/distance learning courses. Teacher performance evaluation aims to support educators’ professional growth and better student learning environments. Therefore, to maintain the quality level, the QTEF presented in this research is further validated using a machine learning model that predicts the teachers’ competence. The results demonstrate that when combined with other factors particularly technical evaluation criteria, as opposed to strongly associated QTEF components, the anticipated result is more accurate. The integration and validation of this framework as well as research on student performance will be performed in the future.
Mitigation Effect of Helmholtz Resonator on the Micro-Pressure Wave Amplitude of a 600-km/h Maglev Train Tunnel
Authors: Li Dian-Qian , Yang Ming-Zhi , Lin Tong-Tong , Zhong Sha , Yang Peng
Published: March 2023

A 600-km/h maglev train can effectively close the speed gap between civil aviation and rail-based trains, thereby alleviating the conflict between the existing demand and actual capacity. However, the hazards caused by the micro-pressure wave amplitude of the tunnel that occurs when the train is running at higher speeds are also unacceptable. At this stage, mitigation measures to control the amplitude of micro-pressure waves generated by maglev trains at 600 km/h within reasonable limits are urgent to develop new mitigation measures. In this study, a three-dimensional, compressible, unsteady SST K–ω equation turbulence model, and an overlapping grid technique were used to investigate the mechanism and mitigation effect of Helmholtz resonators with different arrangement schemes on the micro-pressure wave amplitude at a tunnel exit in conjunction with a 600-km/h maglev train dynamic model test. The results of the study showed that a pressure wave forms when the train enters the tunnel and passes through the Helmholtz resonator. This in turn leads to resonance of air column at its neck, which causes pressure wave energy dissipation as the incident wave frequency is in the resonator band. This suppresses the rise of the initial compressional wave gradient, resulting in an effective reduction in the micro-pressure wave amplitude at the tunnel exit. Compared to conventional tunnels, the Helmholtz resonator scheme with a 94-cavity new tunnel resulted in a 31.87% reduction in the micro-pressure wave amplitude at 20 m from the tunnel exit but a 16.69% increase in the maximum pressure at the tunnel wall. After the Helmholtz resonators were arranged according to the 72-cavity optimization scheme, the maximum pressure at the tunnel wall decreased by 10.57% when compared with that before optimization. However, the micro-pressure wave mitigation effect at 20 m from the tunnel exit did not significantly differ from that before the optimization.
Exploring the Capabilities of a Lightweight CNN Model in Accurately Identifying Renal Abnormalities: Cysts, Stones, and Tumors, Using LIME and SHAP
Authors: Bhandari Mohan , Yogarajah Pratheepan , Kavitha Muthu Subash , Condell Joan
Published: March 2023

Kidney abnormality is one of the major concerns in modern society, and it affects millions of people around the world. To diagnose different abnormalities in human kidneys, a narrow-beam x-ray imaging procedure, computed tomography, is used, which creates cross-sectional slices of the kidneys. Several deep-learning models have been successfully applied to computer tomography images for classification and segmentation purposes. However, it has been difficult for clinicians to interpret the model’s specific decisions and, thus, creating a “black box” system. Additionally, it has been difficult to integrate complex deep-learning models for internet-of-medical-things devices due to demanding training parameters and memory-resource cost. To overcome these issues, this study proposed (1) a lightweight customized convolutional neural network to detect kidney cysts, stones, and tumors and (2) understandable AI Shapely values based on the Shapley additive explanation and predictive results based on the local interpretable model-agnostic explanations to illustrate the deep-learning model. The proposed CNN model performed better than other state-of-the-art methods and obtained an accuracy of 99.52 ± 0.84% for K = 10-fold of stratified sampling. With improved results and better interpretive power, the proposed work provides clinicians with conclusive and understandable results.
Reliability Analysis of Multi-Process Machining Based on Information Entropy
Authors: Qu Dongyue , Ma Junling , Wang Yiming , Zhan Yong
Published: March 2023

The reliability of the machining process is a vital indicator in the manufacturing process of mechanical parts, and directly related to the machining quality of mechanical products. In order to effectively utilize machining process information and machining quality inspection data to evaluate the reliability of the machining process, this paper extends the relevant concepts of information theory to the field of mechanical manufacturing error analysis and establishes a reliability analysis model of the machining process. The model introduces information entropy into the analysis of machining process reliability by defining vertex entropy to measure the uncertainty of the machining quality of each process, and thus realizing the determination of critical processes using a fully quantitative method. Meanwhile, the transfer coefficient defined by mutual information is used to measure the transfer of machining error between two processes. Through combining vertex entropy and the transfer coefficient, the quantitative analysis of machining process reliability is achieved. The model proposed in this paper addresses the issue that the subjective factors of researchers in other related studies have an impact on the analysis results. Finally, the correctness of the proposed model is verified using Monte Carlo simulations.
Improving the Performance of Convolutional GAN Using History-State Ensemble for Unsupervised Early Fault Detection with Acoustic Emission Signals
Authors: Wang Yu , Vinogradov Alexey
Published: March 2023

Early fault detection (EFD) in run-to-failure processes plays a crucial role in the condition monitoring of modern industrial rotating facilities, which entail increasing demands for safety, energy and ecological savings and efficiency. To enable effective protection measures, the evolving faults have to be recognized and identified as early as possible. The major challenge is to distil discriminative features on the basis of only the ‘health’ signal, which is uniquely available from various possible sensors before damage sets in and before the signatures of incipient damage become obvious and well-understood in the signal. Acoustic emission (AE) signals have been frequently reported to be able to deliver early diagnostic information due to their inherently high sensitivity to the incipient fault activities, highlighting the great potential of the AE technique for EFD, which may outperform the traditional vibration-based analysis in many situations. To date, the ‘feature-based’ multivariate analysis dominates the interpretation of AE waveforms. In this way, the decision-making relies heavily on experts’ knowledge and experience, which is often a weak link in the entire EFD chain. With the advent of artificial intelligence, practitioners seek an intelligent method capable of tackling this challenge. In the present paper, we introduce a versatile approach towards intelligent data analysis adapted to AE signals streaming from the sensors used for the continuous monitoring of rotating machinery. A new architecture with a convolutional generative adversarial network (GAN) is designed to extract the deep information embedded in the AE waveforms. In order to improve the robustness of the proposed EFD framework, a novel ensemble technique referred to as ‘history-state ensemble’ (HSE) is introduced and paired with GAN. The primary merits of HSE are twofold: (1) it does not require extra computing time to obtain the base models, and (2) it does not require a special design of the network architecture and can be applied to different networks. To evaluate the proposed method, a durability rolling contact fatigue test was performed with the use of AE monitoring. The experimental results have demonstrated that the proposed ensemble method largely improves the robustness of GAN.
Token-Revocation Access Control to Cloud-Hosted Energy Optimization Utility for Environmental Sustainability
Authors: Riad Khaled
Published: March 2023

To increase the usage of renewable energy, it is vital to maximize local energy production by properly combining various renewable-energy sources by collecting their data and storing it on the cloud. The energy optimization utility, which is used for making decisions to optimize renewable-energy resources, is hosted on the cloud to benefit from cloud capabilities in data storage. Hosting such sensitive data and utilities on the cloud has created some cybersecurity challenges. This paper presents a new token-revocation access control (TR-AC) which revokes the authorization of malicious users before authorizing them to access cloud-hosted energy optimization utilities. TR-AC employs a set of multi-authorities to measure the authentic level for each authenticated user. Although the user is authenticated to access the online system, this authentication can be revoked to utilize the energy optimization utility based on the user’s level of authentication. The cloud storage servers are not fully trusted and, therefore, have no control over access controls. Finally, the proposed TR-AC has been proven to be secure against any attacker that is not authentic according to Diffie-Hellman assumptions. In addition, performance analysis has proven that the time elapsed for both encryption and decryption in TR-AC is very small compared with previously introduced schemes. Therefore, it will not affect the performance of the cloud-hosted system.
Crop Disease Diagnosis with Deep Learning-Based Image Captioning and Object Detection
Authors: Lee Dong In , Lee Ji Hwan , Jang Seung Ho , Oh Se Jong , Doo Ill Chul
Published: March 2023

The number of people participating in urban farming and its market size have been increasing recently. However, the technologies that assist the novice farmers are still limited. There are several previously researched deep learning-based crop disease diagnosis solutions. However, these techniques only focus on CNN-based disease detection and do not explain the characteristics of disease symptoms based on severity. In order to prevent the spread of diseases in crops, it is important to identify the characteristics of these disease symptoms in advance and cope with them as soon as possible. Therefore, we propose an improved crop disease diagnosis solution which can give practical help to novice farmers. The proposed solution consists of two representative deep learning-based methods: Image Captioning and Object Detection. The Image Captioning model describes prominent symptoms of the disease, according to severity in detail, by generating diagnostic sentences which are grammatically correct and semantically comprehensible, along with presenting the accurate name of it. Meanwhile, the Object Detection model detects the infected area to help farmers recognize which part is damaged and assure them of the accuracy of the diagnosis sentence generated by the Image Captioning model. The Image Captioning model in the proposed solution employs the InceptionV3 model as an encoder and the Transformer model as a decoder, while the Object Detection model of the proposed solution employs the YOLOv5 model. The average BLEU score of the Image Captioning model is 64.96%, which can be considered to have high performance of sentence generation and, meanwhile, the mAP50 for the Object Detection model is 0.382, which requires further improvement. Those results indicate that the proposed solution allows the precise and elaborate information of the crop diseases, thereby increasing the overall reliability of the diagnosis.
Dentin–Pulp Complex Response in Molars of Rats after Occlusal and Cervical Restorations with Conventional Glass Ionomer Cement and Nano-Hydroxyapatite Silica Glass Ionomer Cement
Authors: Niazi Fayez Hussain , Luddin Norhayati , Harun Masitah Hayati , Hasan Arshad , Kannan Thirumulu Ponnuraj , Mohamad Suharni , Mahmood Amer
Published: March 2023

The purpose of this in vivo study was to evaluate and compare the dentin–pulp complex response following occlusal and cervical restorations in rat molars restored with nano-hydroxyapatite silica glass ionomer cement (nano-HA-SiO2-GIC) and conventional glass ionomer cement (c-GIC). In total, 64 maxillary first molars of 32 male Wistar rats were restored using Fuji IX (c-GIC) and nano-HA-SiO2-GIC using a split-mouth design. Half of them were reserved for the occlusal type of restoration while the other half was for cervical restorations. After one week and one month, rats were euthanized and were stained with hematoxylin and eosin, Masson’s trichrome, and Brown and Brenn techniques for histological examination. Parameters such as disorganization of the pulp tissue, inflammatory cell infiltration, detection of bacteria, and tertiary dentin deposition were measured for each group. One week after sacrifice, the odontoblastic layer was disrupted, and moderate inflammation in the pulp area close to the cut dentin was observed in both types of restorations. Nano-HA-SiO2-GIC showed significantly superior properties when assessed based on tertiary dentin formation as compared to c-GIC. One month after sacrifice, there was no evidence of disruptions of the odontoblast layer, which exhibited a normal palisade appearance in both groups. In terms of inflammation, the pulp tissue recovered in almost all cases except one of c-GIC, but a few cases of the nano-HA-SiO2-GIC group still displayed mild-to-moderate inflammatory reactions, especially of the occlusal type. Both c-GIC and nano-HA-SiO2-GIC exhibited favorable responses in terms of biocompatibility. Nano-HA-SiO2-GIC exerted more inflammation but encouraged better tertiary dentin formation compared to c-GIC.
Implementing Gamification for Blind and Autistic People with Tangible Interfaces, Extended Reality, and Universal Design for Learning: Two Case Studies
Authors: Ramos Aguiar Luis Roberto , Álvarez Rodríguez Francisco Javier , Madero Aguilar Jesús Roldán , Navarro Plascencia Valeria , Peña Mendoza Luisa María , Quintero Valdez José Rodrigo , Vázquez Pech Juan Román , Mendieta Leon Adriana , Lazcano Ortiz Luis Eloy
Published: March 2023

The present study investigates the use of gamification to foster commitment and engagement among users with disabilities. Two case studies demonstrating the application of gamification are provided. The first is the development of an application to teach a blind person Mexican currency, and the second one is the creation of an application to aid individuals with autism spectrum disorder (ASD) in navigating their environment. The study reveals that universal design for learning principles can be used indirectly to adjust apps for users to utilize the software consistently. This study provides preliminary evaluations for both case studies, which were undertaken with relatively small samples. The first case study revealed that three blind individuals who took part in the review scored an average of 91.7 on the system usability scale. At the same time, the second case study involving the observation of a single individual with ASD also revealed that utilizing the designed app improved performance. Despite the limited sample size, the findings suggest that gamification may effectively encourage and generate commitment among the users with disabilities.
Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED
Authors: Zhong Wei , Jiang Yueqiu , Zhang Xin
Published: March 2023

Automatic target recognition technology is an important research direction in the field of machine vision. Artificial ground targets, such as bridges, airports and houses, are mostly composed of straight lines. The ratio of geometric primitive lines to the triangle area formed by their combination is used as the feature quantity to describe the group of lines, so as to characterize the artificial ground target. In view of the shortcomings of traditional edge detection methods, such as background suppression, non-prominent targets, missing positions, etc., this paper proposed an image edge detection method based on depth learning. By combining the traditional edge detection algorithm with the edge detection algorithm based on an improved HED network, the real-time target image edge detection was completed. An automatic target recognition method based on template matching was proposed. This method solved the problem of both homologous template matching and heterogeneous template matching, which has important theoretical value. First, the lines were combined to form the geometric primitives of the line group, and then the relationship of the lines in the group was determined by using the characteristic quantity of the line group. The best line group matching the target template was found in the image edge, and the homonymous points in the real-time image and the target template were calculated. The affine transformation matrix between the two images was obtained according to the homonymous points, and then the accurate position of the target in the real-time image was found.
Reversible Transitions in a Fluctuation Assay Modify the Tail of Luria–Delbrück Distribution
Authors: Bokes Pavol , Hlubinová Anna , Singh Abhyudai
Published: March 2023

We consider a fluctuation test experiment in which cell colonies were grown from a single cell until they reach a given population size and were then exposed to treatment. While they grow, the cells may, with a low probability, acquire resistance to treatment and pass it on to their offspring. Unlike the classical Luria–Delbrück fluctuation test, and motivated by recent work on drug-resistance acquisition in cancer/microbial cells, we allowed the resistant cell state to switch back to a drug-sensitive state. This modification did not affect the central part of the Luria–Delbrück distribution of the number of resistant survivors: the previously developed approximation by the Landau probability density function applied. However, the right tail of the modified distribution deviated from the power law decay of the Landau distribution. Here, we demonstrate that the correction factor was equal to the Landau cumulative distribution function. We interpreted the appearance of the Landau laws from the standpoint of singular perturbation theory and used the asymptotic matching principle to construct uniformly valid approximations. Additionally, we describe the corrections to the distribution tails in populations initially consisting of multiple sensitive cells, a mixture of sensitive and resistant cells, and a cell with a randomly drawn state.
Lean-BIM Approach for Improving the Performance of a Construction Project in the Design Phase
Authors: EL Mounla Karim , Beladjine Djaoued , Beddiar Karim , Mazari Bélahcène
Published: March 2023

Over the last decade, the construction industry has suffered from various issues affecting the planning processes, team management, and decision-making during the design phase. Today, the concepts of Lean construction and Building Information Modeling (BIM) overlap and bring solutions to all phases of a construction project. Numerous studies have shown that leveraging BIM data through Lean principles can significantly improve the overall management of a project. However, the literature is still limited to optimizing the design phase to anticipate any deviation before the start of the work. This article aims to provide an updated review of the interaction between BIM and Lean in the design phase. The study is based on a systematic review of 61 articles selected using the Systematic Literature Review (SLR) approach. The obtained results allowed for the analysis of different Lean methods and tools that interact with BIM. Digitizing these methods and using them together is necessary to facilitate their application in a construction project. Finally, our study provides recommendations for researchers and professionals by identifying future scientific challenges.
Thyroid Profile in the First Three Months after Starting Treatment in Children with Newly Diagnosed Cancer
Authors: Lebbink Chantal A. , van den Bos Cor , Dierselhuis Miranda P. , Fiocco Marta , Verrijn Stuart Annemarie A. , Lentjes Eef G. W. M. , Plasschaert Sabine L. A. , Tissing Wim J. E. , van Santen Hanneke M.
Published: March 2023

Background: Thyroid hormone anomalies during childhood might affect neurological development, school performance and quality of life, as well as daily energy, growth, body mass index and bone development. Thyroid dysfunction (hypo- or hyperthyroidism) may occur during childhood cancer treatment, although its prevalence is unknown. The thyroid profile may also change as a form of adaptation during illness, which is called euthyroid sick syndrome (ESS). In children with central hypothyroidism, a decline in FT4 of >20% has been shown to be clinically relevant. We aimed to quantify the percentage, severity and risk factors of a changing thyroid profile in the first three months of childhood cancer treatment. Methods: In 284 children with newly diagnosed cancer, a prospective evaluation of the thyroid profile was performed at diagnosis and three months after starting treatment. Results: Subclinical hypothyroidism was found in 8.2% and 2.9% of children and subclinical hyperthyroidism in 3.6% and in 0.7% of children at diagnosis and after three months, respectively. ESS was present in 1.5% of children after three months. In 28% of children, FT4 concentration decreased by ≥20%. Conclusions: Children with cancer are at low risk of developing hypo- or hyperthyroidism in the first three months after starting treatment but may develop a significant decline in FT4 concentrations. Future studies are needed to investigate the clinical consequences thereof.
Periplocin Overcomes Bortezomib Resistance by Suppressing the Growth and Down-Regulation of Cell Adhesion Molecules in Multiple Myeloma
Authors: Aziz Abdul , Wang Haiqin , Wang Yanpeng , Li Zhenzhen , Yang Chaoying , Ma Zekang , Xiao Xiaojuan , Liu Jing
Published: March 2023

Multiple myeloma (MM) is an incurable hematological malignant disorder of bone marrow. Patients with MM receive multiple lines of chemotherapeutic treatments which often develop bortezomib (BTZ) resistance and relapse. Therefore, it is crucial to identify an anti-MM agent to overcome the BTZ resistance of MM. In this study, we screened a library of 2370 compounds against MM wild-type (ARP1) and BTZ-resistant type (ARP1-BR) cell lines and found that periplocin (PP) was the most significant anti-MM natural compound. We further investigated the anti-MM effect of PP by using annexin V assay, clonogenic assays, aldefluor assay, and transwell assay. Furthermore, RNA sequencing (RNA-seq) was performed to predict the molecular effects of PP in MM followed by verification through qRT-PCR and Western blot analysis. Moreover, ARP1 and ARP1-BR xenograft mice models of MM were established to confirm the anti-MM effects of PP invivo. The results showed that PP significantly induced apoptosis, inhibited proliferation, suppressed stemness, and reduced the cell migration of MM. The expression of cell adhesion molecules (CAMs) was suppressed upon PP treatment in vitro and in vivo. Overall, our data recommend PP as an anti-MM natural compound with the potential to overcome BTZ resistance and downregulate CAMs in MM.
Internal Guidelines for Reducing Lymph Node Contour Variability in Total Marrow and Lymph Node Irradiation
Authors: Dei Damiano , Lambri Nicola , Stefanini Sara , Vernier Veronica , Brioso Ricardo Coimbra , Crespi Leonardo , Clerici Elena , Bellu Luisa , De Philippis Chiara , Loiacono Daniele , Navarria Pierina , Reggiori Giacomo , Bramanti Stefania , Rodari Marcello , Tomatis Stefano , Chiti Arturo , Carlo-Stella Carmelo , Scorsetti Marta , Mancosu Pietro
Published: March 2023

Background: The total marrow and lymph node irradiation (TMLI) target includes the bones, spleen, and lymph node chains, with the latter being the most challenging structures to contour. We evaluated the impact of introducing internal contour guidelines to reduce the inter- and intraobserver lymph node delineation variability in TMLI treatments. Methods: A total of 10 patients were randomly selected from our database of 104 TMLI patients so as to evaluate the guidelines’ efficacy. The lymph node clinical target volume (CTV_LN) was recontoured according to the guidelines (CTV_LN_GL_RO1) and compared to the historical guidelines (CTV_LN_Old). Both topological (i.e., Dice similarity coefficient (DSC)) and dosimetric (i.e., V95 (the volume receiving 95% of the prescription dose) metrics were calculated for all paired contours. Results: The mean DSCs were 0.82 ± 0.09, 0.97 ± 0.01, and 0.98 ± 0.02, respectively, for CTV_LN_Old vs. CTV_LN_GL_RO1, and between the inter- and intraobserver contours following the guidelines. Correspondingly, the mean CTV_LN-V95 dose differences were 4.8 ± 4.7%, 0.03 ± 0.5%, and 0.1 ± 0.1%. Conclusions: The guidelines reduced the CTV_LN contour variability. The high target coverage agreement revealed that historical CTV-to-planning-target-volume margins were safe, even if a relatively low DSC was observed.
PET/CT May Assist in Avoiding Pointless Thyroidectomy in Indeterminate Thyroid Nodules: A Narrative Review
Authors: Abou Karam Gaby , Malhotra Ajay
Published: March 2023

Indeterminate thyroid nodules (ITN) are commonly encountered among the general population, with a malignancy rate of 10 to 40%. However, many patients may be overtreated with futile surgery for benign ITN. To avoid unnecessary surgery, PET/CT scan is a possible alternative to help differentiate between benign and malignant ITN. In this narrative review, the major results and limitations of the most recent studies on PET/CT efficacy (from PET/CT visual assessment to quantitative PET parameters and recent radiomic features analysis) and on cost-effectiveness (compared to other alternatives (such as surgery)) are presented. PET/CT can reduce futile surgery with visual assessment (around 40%; if ITN ≥ 10 mm). Moreover, PET/CT conventional parameters and radiomic features extracted from PET/CT imaging can be associated together in a predictive model to rule out malignancy in ITN, with a high NPV (96%) when certain criteria are met. Even though promising results were obtained in these recent PET/CT studies, further studies are needed to enable PET/CT to become the definitive diagnostic tool once a thyroid nodule is identified as indeterminate.
Mesostructured γ-Al2O3-Based Bifunctional Catalysts for Direct Synthesis of Dimethyl Ether from CO2
Authors: Secci Fausto , Sanna Angotzi Marco , Mameli Valentina , Lai Sarah , Russo Patrícia A. , Pinna Nicola , Mureddu Mauro , Rombi Elisabetta , Cannas Carla
Published: March 2023

In this work, we propose two bifunctional nanocomposite catalysts based on acidic mesostructured γ-Al2O3 and a Cu/ZnO/ZrO2 redox phase. γ-Al2O3 was synthesized by an Evaporation-Induced Self-Assembly (EISA) method using two different templating agents (block copolymers Pluronic P123 and F127) and subsequently functionalized with the redox phase using an impregnation method modified with a self-combustion reaction. These nanocomposite catalysts and their corresponding mesostructured supports were characterized in terms of structural, textural, and morphological features as well as their acidic properties. The bifunctional catalysts were tested for the CO2-to-DME process, and their performances were compared with a physical mixture consisting of the most promising support as a dehydration catalyst together with the most common Cu-based commercial redox catalyst (CZA). The results highlight that the most appropriate Pluronic for the synthesis of γ-Al2O3 is P123; the use of this templating agent allows us to obtain a mesostructure with a smaller pore size and a higher number of acid sites. Furthermore, the corresponding composite catalyst shows a better dispersion of the redox phase and, consequently, a higher CO2 conversion. However, the incorporation of the redox phase into the porous structure of the acidic support (chemical mixing), favoring an intimate contact between the two phases, has detrimental effects on the dehydration performances due to the coverage of the acid sites with the redox nanophase. On the other hand, the strategy involving the physical mixing of the two phases, distinctly preserving the two catalytic functions, assures better performances.
Synthesis of Cobalt Complex Containing Trans-Cinnamate and Its Electrocatalytic Activity for Oxygen Evolution Reaction
Authors: Lee Jimin , Shin Hyewon , Geum Sunwoo , Lee Sowon , Ok Kang Min , Do Junghwan , Kwon Seong Jung
Published: March 2023

There are many efforts reported on finding effective catalysts for oxygen evolution reactions (OERs), which are important reactions in the energy field. Coordination polymers, including metal–organic frameworks (MOFs), are attracting attention as electrocatalysts for OERs due to their versatility and modulating properties. A new cobalt complex containing trans-cinnamate and 2-aminopyridmidine ligands was synthesized using a hydrothermal method. The cobalt complex showed a 1D chain structure. The electrocatalytic activity and stability of the cobalt complex with or without an electrochemical supporter, such as reduced graphene oxide (rGO), OERs were investigated and compared with a metal oxide reference material. Due to the π-conjugated trans-cinnamate, which has electron flexibility near the Co centers, the catalyst/rGO composite showed significant catalytic activities, with an overpotential of 386 mV and a Tafel slope of 64 mV/dec.
CFTR Inhibitors Display In Vitro Antiviral Activity against SARS-CoV-2
Authors: Lagni Anna , Lotti Virginia , Diani Erica , Rossini Giada , Concia Ercole , Sorio Claudio , Gibellini Davide
Published: March 2023

Several reports have indicated that SARS-CoV-2 infection displays unexpected mild clinical manifestations in people with cystic fibrosis (pwCF), suggesting that CFTR expression and function may be involved in the SARS-CoV-2 life cycle. To evaluate the possible association of CFTR activity with SARS-CoV-2 replication, we tested the antiviral activity of two well-known CFTR inhibitors (IOWH-032 and PPQ-102) in wild type (WT)-CFTR bronchial cells. SARS-CoV-2 replication was inhibited by IOWH-032 treatment, with an IC50 of 4.52 μM, and by PPQ-102, with an IC50 of 15.92 μM. We confirmed this antiviral effect on primary cells (MucilAirTM wt-CFTR) using 10 μM IOWH-032. According to our results, CFTR inhibition can effectively tackle SARS-CoV-2 infection, suggesting that CFTR expression and function might play an important role in SARS-CoV-2 replication, revealing new perspectives on the mechanisms governing SARS-CoV-2 infection in both normal and CF individuals, as well as leading to potential novel treatments.
An Emerging Role for Type I Interferons as Critical Regulators of Blood Coagulation
Authors: Ryan Tristram A. J. , O’Neill Luke A. J.
Published: March 2023

Type I interferons (IFNs) are central mediators of anti-viral and anti-bacterial host defence. Detection of microbes by innate immune cells via pattern recognition receptors (PRRs), including Toll-like receptors (TLRs) and cGAS-STING, induces the expression of type I IFN-stimulated genes. Primarily comprising the cytokines IFN-α and IFN-β, type I IFNs act via the type I IFN receptor in an autocrine or exocrine manner to orchestrate rapid and diverse innate immune responses. Growing evidence pinpoints type I IFN signalling as a fulcrum that not only induces blood coagulation as a core feature of the inflammatory response but is also activated by components of the coagulation cascade. In this review, we describe in detail recent studies identifying the type I IFN pathway as a modulator of vascular function and thrombosis. In addition, we profile discoveries showing that thrombin signalling via protease-activated receptors (PARs), which can synergize with TLRs, regulates the host response to infection via induction of type I IFN signalling. Thus, type I IFNs can have both protective (via maintenance of haemostasis) and pathological (facilitating thrombosis) effects on inflammation and coagulation signalling. These can manifest as an increased risk of thrombotic complications in infection and in type I interferonopathies such as systemic lupus erythematosus (SLE) and STING-associated vasculopathy with onset in infancy (SAVI). We also consider the effects on coagulation of recombinant type I IFN therapies in the clinic and discuss pharmacological regulation of type I IFN signalling as a potential mechanism by which aberrant coagulation and thrombosis may be treated therapeutically.
Metallurgical and Mechanical Characteristics of an AA5183 Alloy Plate Performed by a Cold Metal Low-Power Additive Manufacturing Technology
Authors: Li Lu , Jia Xianjun , Hayat Muhammad Dilawer , Shan Quan , Li Zulai , Yuan Zhentao , Xu Baoqiang , Jiang Yehua , Yang Bin
Published: March 2023

In this work, an AA5183 alloy plate was successfully deposited by low-power cold metal transfer technology. The forming defects, microstructural characteristics, and mechanical properties were investigated. The results show that the number of defects increases gradually along the building direction of the deposited plate. X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, electron probe microanalysis, electron backscatter diffraction, and transmission electron microscopy were employed to study the distribution of alloying elements, deposited microstructural characteristics, and the crystal structure of intermetallic compounds in the Al alloy plate. The tensile samples perpendicular to the building direction presented greater tensile strength and superior plasticity compared to those parallel to the deposition direction. The average UTS was 327 ± 0.65 MPa and the average EL was 30.6 ± 2.0%. The UTS of conventionally forged 5083-H32 (Al-Mg4.5) alloy is 324 MPa; the UTS of extruded 5083-H116 (Al-Mg4.5) alloy is 305 MPa. Further, the strength of our prepared plate reaches the value needed for industrial applications of the 5083 Al alloy. The differences in the strength and plasticity of the samples assessed under multiple sampling methods were analyzed based on a synergistic strength–ductility mechanism.
Species Composition and Structure of Beetle Associations in Caves of the Częstochowa Upland, Poland
Authors: Kocot-Zalewska Joanna , Lis Barbara
Published: March 2023

This paper presents the study’s results on beetles (Insecta: Coleoptera) inhabiting caves in the Częstochowa Upland, southern Poland. During two years of research, 2084 specimens, representing 105 species from 19 beetle families, were collected. The obtained results indicate that many beetle species choose to inhabit caves despite lacking specific adaptations for living in such environments. The cave entrance zone is the most attractive place for surface species to inhabit because its climatic conditions are more stable than outside the cave, some sunlight is present, and the availability of organic matter is high. In the deeper parts of the studied caves, the number of occurring species rapidly decreased. Three species were recognised as troglobionts, four as troglophiles and 32 as subtroglophiles. Speonomus normandi hydrophilus, Choleva lederiana gracilenta and Quedius mesomelinus mesomelinus were identified as the most frequent in the studied caves. Speonomus normandi hydrophilus is endemic to the Arize massif in the Central Pyrenees (France) and was experimentally introduced into the Dzwonnica cave (Poland) in 1982, while Ch. lederiana gracilenta is one of two troglobitic beetles native to Polish caves and Q. imesomelinus mesomelinus is a widespread, very common troglophile.