bluuebunny/crossref_metadata_2025 huggingface dataset:
Inference Latency Prediction Approaches Using Statistical Information for Object Detection in Edge Computing
Authors: Kong Gyuyeol , Hong Yong-Geun
Published: August 2023

To seamlessly deliver artificial intelligence (AI) services using object detection, both inference latency from a system perspective as well as inference accuracy should be considered important. Although edge computing can be applied to efficiently operate these AI services by significantly reducing inference latency, deriving an optimized computational offloading policy for edge computing is a challenging problem. In this paper, we propose inference latency prediction approaches for determining the optimal offloading policy in edge computing. Since there is no correlation between the image size and inference latency during object detection, approaches to predict inference latency are required for finding the optimal offloading policy. The proposed approaches predict the inference latency between devices and object detection algorithms by using their statistical information on the inference latency. By exploiting the predicted inference latency, a client may efficiently determine whether to execute an object detection task locally or remotely. Through various experiments, the performances of predicted inference latency according to the object detection algorithms are compared and analyzed by considering two communication protocols in terms of the root mean square error. The simulation results show that the predicted inference latency matches the actual inference latency well.
Reference Broadcast-Based Secure Time Synchronization for Industrial Wireless Sensor Networks
Authors: Wang Zhaowei , Sun Dehua , Yu Chen
Published: August 2023

Security is an important factor that cannot be neglected in the design of time synchronization algorithms since industrial wireless sensor networks are prone to attacks against physical nodes and communication links. The Sybil attack is an intelligent attack with a high destructive capacity in pretending multiple identities and broadcasting illegitimate messages to destroy the network operation. Existing secure time synchronization algorithms mostly focus on distributed protocols; however, they pay less attention to Sybil attacks and centralized network time synchronization. In this paper, we propose a novel reference broadcast-based secure time synchronization (RSTS) for industrial wireless sensor networks with a time source against Sybil attacks. Different from previous protocols, in converging the network structure and the clock status, RSTS employs a public neighbor forwarding mechanism based on reference broadcast to filter the illegal time information automatically. Instead of establishing a table with timestamps of packet transmission and receipt, the least square linear regression is utilized to estimate the compensation relative to the source node with the recorded time and calculated time difference in receiving packets. The simulation results demonstrate that RSTS is resilient to Sybil attacks as well as message manipulation attacks in comparison with existing algorithms.
Exploring Performance Degradation in Virtual Machines Sharing a Cloud Server
Authors: Ahmed Hamza , Syed Hassan Jamil , Sadiq Amin , Ibrahim Ashraf Osman , Alohaly Manar , Elsadig Muna
Published: August 2023

Cloud computing has become a leading technology for IT infrastructure, with many companies migrating their services to cloud servers in recent years. As cloud services continue to expand, the issue of cloud monitoring has become increasingly important. One important metric to monitor is CPU steal time, which measures the amount of time a virtual CPU waits for the actual CPU. In this study, we focus on the impact of CPU steal time on virtual machine performance and the potential problems that can arise. We implement our work using an OpenStack-based cloud environment and investigate intrusive and non-intrusive monitoring methods. Our analysis provides insights into the importance of CPU steal time monitoring and its impact on cloud performance.
A Depression Recognition Method Based on the Alteration of Video Temporal Angle Features
Authors: Ding Zhiqiang , Hu Yahong , Jing Runhui , Sheng Weiguo , Mao Jiafa
Published: August 2023

In recent years, significant progress has been made in the auxiliary diagnosis system for depression. However, most of the research has focused on combining features from multiple modes to enhance classification accuracy. This approach results in increased space-time overhead and feature synchronization problems. To address this issue, this paper presents a single-modal framework for detecting depression based on changes in facial expressions. Firstly, we propose a robust method for extracting angle features from facial landmarks. Theoretical evidence is provided to demonstrate the translation and rotation invariance of these features. Additionally, we introduce a flip correction method to mitigate angle deviations caused by head flips. The proposed method not only preserves the spatial topological relationship of facial landmarks, but also maintains the temporal correlation between frames preceding and following the facial landmarks. Finally, the GhostNet network is employed for depression detection, and the effectiveness of various modal data is compared. In the depression binary classification task using the DAIC-WOZ dataset, our proposed framework significantly improves the classification performance, achieving an F1 value of 0.80 for depression detection. Experimental results demonstrate that our method outperforms other existing depression detection models based on a single modality.
Assessing the Structural Performance of Biodegradable Capsules
Authors: Hakula Harri
Published: August 2023

Biodegradable materials pose challenges over all aspects of computational mechanics. In this study, the focus is on the resulting domain uncertainty. Model structures or devices are shells of revolution subject to random variation of the outer surface. The novelty of the proposed computational approach is the possibility to restrict the variation to specific parts of the structure using a posteriori filtering, which is applied to the random process whose realisations are the profiles of the shells. The dimensionally reduced stochastic elasticity problems are solved using a collocation method where every realisation is discretised separately. The collocation scheme is validated against standard Monte Carlo. The reliability of the simulations is further confirmed via a posteriori error estimates that are computed using the same collocation scheme. The quantities of interest on the nominal domain are the expected displacement fields and their variances.
Effective Human Motor Imagery Recognition via Segment Pool Based on One-Dimensional Convolutional Neural Network with Bidirectional Recurrent Attention Unit Network
Authors: Hu Huawen , Yue Chenxi , Shi Enze , Yu Sigang , Kang Yanqing , Wu Jinru , Wang Jiaqi , Zhang Shu
Published: August 2023

Brain–computer interface (BCI) technology enables humans to interact with computers by collecting and decoding electroencephalogram (EEG) from the brain. For practical BCIs based on EEG, accurate recognition is crucial. However, existing methods often struggle to achieve a balance between accuracy and complexity. To overcome these challenges, we propose 1D convolutional neural networks with bidirectional recurrent attention unit network (1DCNN-BiRAU) based on a random segment recombination strategy (segment pool, SegPool). It has three main contributions. First, SegPool is proposed to increase training data diversity and reduce the impact of a single splicing method on model performance across different tasks. Second, it employs multiple 1D CNNs, including local and global models, to extract channel information with simplicity and efficiency. Third, BiRAU is introduced to learn temporal information and identify key features in time-series data, using forward–backward networks and an attention gate in the RAU. The experiments show that our model is effective and robust, achieving accuracy of 99.47% and 91.21% in binary classification at the individual and group levels, and 90.90% and 92.18% in four-category classification. Our model demonstrates promising results for recognizing human motor imagery and has the potential to be applied in practical scenarios such as brain–computer interfaces and neurological disorder diagnosis.
A Domain-Oriented Entity Alignment Approach Based on Filtering Multi-Type Graph Neural Networks
Authors: Xu Yaoli , Zhong Jinjun , Zhang Suzhi , Li Chenglin , Li Pu , Guo Yanbu , Li Yuhua , Liang Hui , Zhang Yazhou
Published: August 2023

Owing to the heterogeneity and incomplete information present in various domain knowledge graphs, the alignment of distinct source entities that represent an identical real-world entity becomes imperative. Existing methods focus on cross-lingual knowledge graph alignment, and assume that the entities of knowledge graphs in the same language are unique. However, due to the ambiguity of language, heterogeneous knowledge graphs in the same language are often duplicated, and relationship triples are far less than those of cross-lingual knowledge graphs. Moreover, existing methods rarely exclude noisy entities in the process of alignment. These make it impossible for existing methods to deal effectively with the entity alignment of domain knowledge graphs. In order to address these issues, we propose a novel entity alignment approach based on domain-oriented embedded representation (DomainEA). Firstly, a filtering mechanism employs the language model to extract the semantic features of entities and to exclude noisy entities for each entity. Secondly, a Structural Aggregator (SA) incorporates multiple hidden layers to generate high-order neighborhood-aware embeddings of entities that have few relationship connections. An Attribute Aggregator (AA) introduces self-attention to dynamically calculate weights that represent the importance of the attribute values of the entities. Finally, the approach calculates a transformation matrix to map the embeddings of distinct domain knowledge graphs onto a unified space, and matches entities via the joint embeddings of the SA and AA. Compared to six state-of-the-art methods, our experimental results on multiple food datasets show the following: (i) Our approach achieves an average improvement of 6.9% on MRR. (ii) The size of the dataset has a subtle influence on our approach; there is a positive correlation between the expansion of the dataset size and an improvement in most of the metrics. (iii) We can achieve a significant improvement in the level of recall by employing a filtering mechanism that is limited to the top-100 nearest entities as the candidate pairs.
Crack Detection of Concrete Images Using Dilatation and Crack Detection Algorithms
Authors: Kim Byeong-Cheol , Son Byung-Jik
Published: August 2023

Crack detection in structures is an important and time-consuming element of monitoring the health of structures and ensuring structural safety. The traditional visual inspection of structures can be unsafe and may produce inconsistent results. Thus, there is a need for a method to easily and accurately identify and analyze cracks. In this study, algorithms for automatically detecting the size and location of cracks in concrete images were developed. Cracks were automatically detected in a total of 10 steps. In steps 5 and 9, two user algorithms were added to increase crack detection accuracy, where 1000 crack images and 1000 non-crack images were used, respectively. In the crack image, 100% of the cracks were detected, but 95.3% of the results were very good, even if the results that were not bad in terms of quality were excluded. In addition, the accuracy of detecting non-crack images was also very good (96.9%). Thus, it is expected that the crack detection algorithm presented in this study will be able to detect the location and size of cracks in concrete. Moreover, these algorithms will help in observing the soundness of structures and ensuring their safety.
Enrichment of Fermented Milk Drinks with Mespilus germanica and Crataegus azarolus Fruit Extracts
Authors: Papademas Photis , Ioannou Ioanna , Aspri Maria
Published: August 2023

The aim of the present study was to select the optimal extraction conditions for two underutilized wild fruits of the Rosaceae family (Mespilus germanica and Crataegus azarolus) in order to investigate the possibility of utilizing their potential bioactive properties by developing novel fermented milk drinks enriched with fruit extracts, with functional properties. The total phenolic and flavonoid contents of the extracts, as well as their antioxidant and antidiabetic activities, were evaluated, and based on the results, the optimal extraction conditions were selected. The technological characteristics (i.e., fermentation conditions) and microbiological and bioactive properties of the final products were evaluated over refrigerated storage for 28 days. The findings of the study showed that the incorporation of Mespilus germanica or Crataegus azarolus extracts had a positive influence on the bioactive properties of the end-products, decreased fermentation times and maintained high viable populations of lactic acid bacteria. Hence, it can be concluded that Mespilus germanica or Crataegus azarolus extracts can be exploited in the enrichment of an added-value fermented milk drink.
Increase of Trichoderma harzianum Production Using Mixed-Level Fractional Factorial Design
Authors: Yáñez-Hernández Oscar , Ríos-Lira Armando , Pantoja-Pacheco Yaquelin Verenice , Jiménez-García José Alfredo , Vázquez-López José Antonio , Hernández-González Salvador
Published: August 2023

This research presents the increase of the Trichoderma harzianum production process in a biotechnology company. The NOBA (Near-Orthogonal Balanced arrays) method was used to fractionate a mixed-level factorial design to minimize costs and experimentation times. Our objective is to determine the significant factors to maximize the production process of this fungus. The proposed 213242 mixed-level design involved five factors, including aeration, humidity, temperature, potential hydrogen (pH), and substrate; the response variable was spore production. The results of the statistical analysis showed that the type of substrate, the air supply, and the interaction of these two factors were significant. The maximization of spore production was achieved by using the breadfruit seed substrate and aeration, while it was shown that variations in pH, humidity, and temperature have no significant impact on the production levels of the fungus.
Comparative Efficacy of Systemic and Combination Fungicides for the Control of Alternaria Leaf Spot of Cabbage
Authors: Ishieze Patience U. , Amuji Chinedu F. , Ugwuoke Kevin I. , Baiyeri Paul K. , Eze Michael O.
Published: August 2023

Alternaria leaf spot of cabbage, caused by the Alternaria brassicicola, affects leaves of cabbages and often results in head rots causing severe decline in yield. In this work, the effects of systemic and combination fungicides on A. brassicicola mycelia growth in vitro and disease severity in field trials were investigated. The results of in vitro evaluation revealed that both fungicides significantly inhibited (p < 0.05) the growth of A. brassicicola under in vitro conditions. However, metalaxyl-M 6% was less effective with 100 μg/mL having only 30 ± 3.5% inhibition. On the other hand, 100 μg/mL of mancozeb 63% + carbendazim 12% had 94 ± 3.5% growth inhibition of A. brassicicola, respectively, under the same conditions. Dose-response analysis of the efficacy of the two fungicides showed that the LC50 of metalaxyl-M 6% and mancozeb 63% + carbendazim 12% were 125.52 ppm and 57.22 ppm, respectively, indicating the superiority of combination fungicide over systemic fungicide alone. Field studies showed that while manure type significantly impacted on biomass production (p < 0.001), it did not significantly affect disease severity. On the other hand, the frequency of fungicide application impacted on disease severity, with biweekly application leading to a significant reduction in disease severity after 10 weeks.
Mechatronics: A Study on Its Scientific Constitution and Association with Innovative Products
Authors: Cintra Faria Ana Carolina , Barbalho Sanderson César Macêdo
Published: August 2023

Mechatronics as a science is a synergic combination of mechanical engineering, electronic control, and software design in product development and manufacturing processes. To understand how the field of knowledge that incorporates mechatronics in innovative products, given that it is not in itself a basic engineering discipline but an integration of fields of knowledge, has advanced, it was developed a bibliometric and qualitative study through systematic review with an analytical framework for the establishment of variables to subsidize the construction of the selected theoretical body. The results and conclusions of the sampled publications show that mechatronics performs one of the principal roles in innovation due to the multidisciplinary integration that the scope of innovation in product engineering is propitiating. The study classified five global scenarios: practical approaches aimed at product development, research that studies curricula and education in engineering, studies involving components of a mechatronic system, use of artificial intelligence, and methodologies for designing mechatronic systems. In addition to underscoring that the use of the term innovation associated with mechatronics in a large proportion of the publications extrapolates the operational level, characterizing an attribution to the term that is always associated with the applications, ramifications, and perspectives that the respective product, design, robot, or system could offer to the market or future research. Similarly, it was found that the results of many publications associate the term innovation with a return on investments or operational costs and emphasize the advantages of using the technology for commercial ends.
Spatiotemporal Distributions and Related Large-Scale Environmental Conditions of Extreme Rainfall from Tropical Cyclones with Different Tracks and Seasons in Guangxi, South China: A Comparative Climatological Study
Authors: Cai Yuexing , Zheng Fengqin , Yao Cai , Lu Qianqian , Qin Weijian , He Hui , Huang Cuiyin
Published: August 2023

This study investigates the main climatological features of extreme precipitation (TCER) induced by tropical cyclones (TCs) affecting Guangxi (GX), South China using multiple datasets and a 99th percentile threshold during 1981–2020, with an emphasis on the rainfall diversities of different high-impact TC groups and their associated mechanisms. Results show that there are large regional differences and a seasonal imbalance in the climatological features of TCER in GX. In summer (fall), TCs with TCER events primarily move northward or eastward (northwestward or westward), namely, S-NWTCs and S-ETCs (F-WTCs and F-NWTCs). The rainfall centers exhibit asymmetrical features with S-NWTCs and F-NWTCs located in the northeast quadrant, but S-ETCs and F-WTCs in the southwest and northeast quadrants, respectively. Comparisons of atmospheric circulations and environmental factors indicate that the intense rainfall of F-WTCs is mainly attributed to the trough–TC interaction, which is accompanied by stronger upper-level westerly jet and cold air intrusion, thus increasing baroclinic energy and uplifting for the strongest rainfall among these four groups. This interaction is absent for other groups due to a greater South Asian high and western North Pacific subtropical high. Instead, the increased rainfall in S-NWTCs and F-NWTCs can mainly be attributed to the stronger low-level southwesterly jet, which, in combination with low-level warm advection and convergence induced by land–sea friction, promotes the release of latent heat through moisture condensation. S-ETCs differ from S-NWTCs and F-NWTCs in that moisture convergence is weaker due to the much-weakened TC circulation.
Spatial Distribution of Snow Cover in Tibet and Topographic Dependence
Authors: Chu Duo , Liu Linshan , Wang Zhaofeng
Published: August 2023

Many major river systems in Asia, such as the Yangtze, Yarlung Zangbo, Indus, Ganges and Salween originate in the Tibetan mountains and snow cover in Tibet provides substantial water resources for these rivers, in addition to its weather-related and climatic significance. The high mountain terrain of Tibet is the main condition that snow cover exists and persists at mid–low altitudes. However, the relationships between snow cover and topographic factors of the plateau have not been fully addressed. In this study, the overall spatial distribution of snow cover and the impacts of topography (elevation, aspect and slope) on snow cover distribution in Tibet were analyzed based on the MODIS snow cover product and digital elevation model (DEM) using GIS spatial analysis techniques. The results showed that (1) snow cover in Tibet is spatially very uneven and is characterized by rich snow and high SCF (snow cover frequency) on Nyainqentanglha mountain and the surrounding high mountains, with less snow and a low SCF in the southern Tibetan valley and central part of northern Tibet. (2) Snow cover in Tibet has a strong elevation dependence and a higher SCF corresponds well with high mountain ranges. The mean SCF below 2000 m above sea level (m a.s.l) was less than 4%, while above 6000 m a.s.l, it reached 75%. (3) Intra-annual snow cover distribution below 4000 m a.s.l was characterized by unimodal patterns, while above 4000 m a.s.l, it was characterized by bimodal patterns. The lowest SCF below 6000 m a.s.l occurred in summer, while above 6000 m it occurred in winter. (4) The mountain slope and aspect affect snow cover distribution through changing radiation and energy balances in the mountain regions. The mean SCF generally increased with mountain slopes, with the highest on the north-facing aspect and the lowest on the south-facing aspect.
Constraint Qualifications for Vector Optimization Problems in Real Topological Spaces
Authors: Zeng Renying
Published: August 2023

In this paper, we introduce a series of definitions of generalized affine functions for vector-valued functions by use of “linear set”. We prove that our generalized affine functions have some similar properties to generalized convex functions. We present examples to show that our generalized affinenesses are different from one another, and also provide an example to show that our definition of presubaffinelikeness is non-trivial; presubaffinelikeness is the weakest generalized affineness introduced in this article. We work with optimization problems that are defined and taking values in linear topological spaces. We devote to the study of constraint qualifications, and derive some optimality conditions as well as a strong duality theorem. Our optimization problems have inequality constraints, equality constraints, and abstract constraints; our inequality constraints are generalized convex functions and equality constraints are generalized affine functions.
The Impact of Rocuronium and Sugammadex on Length of Stay in Patients Undergoing Open Spine Surgery: A Propensity Score-Matched Analysis
Authors: Wu En-Bo , Li Yan-Yi , Hung Kuo-Chuan , Illias Amina M. , Tsai Yung-Fong , Yang Ya-Ling , Chin Jo-Chi , Wu Shao-Chun
Published: August 2023

Enhanced Recovery After Surgery (ERAS), an all-encompassing perioperative care approach, has been demonstrated to enhance surgical results, mitigate postoperative issues, and decrease the length of hospital stay (LOS) in diverse surgical specialties. In this retrospective study, our objective was to examine the influence of muscle relaxant selection on LOS and perioperative results in adult patients undergoing open spine surgery. Specifically, we compared 201 patients who received cisatracurium and neostigmine with 201 patients who received rocuronium and sugammadex, after 1:1 propensity score matching. The utilization of the rocuronium and sugammadex combination in anesthesia for open spinal surgery did not lead to a reduction in the LOS but was associated with a decreased incidence of postoperative chest radiographic abnormalities, including infiltration, consolidation, atelectasis, or pneumonia (p = 0.027). In our secondary analysis, multivariate analysis revealed multiple determinants influencing the prolonged LOS (>7 days) during open spine surgery. Bispectral index-guided anesthesia emerged as a protective factor, while variables such as excessive intraoperative blood loss and fluid administration as well as postoperative chest radiographic abnormalities independently contributed to prolonged LOS.
A Study of DNA Methylation of Bladder Cancer Biomarkers in the Urine of Patients with Neurogenic Lower Urinary Tract Dysfunction
Authors: Koukourikis Periklis , Papaioannou Maria , Georgopoulos Petros , Apostolidis Ioannis , Pervana Stavroula , Apostolidis Apostolos
Published: August 2023

Background: Bladder cancer (BCa) in patients suffering from neurogenic lower urinary tract dysfunction (NLUTD) is a significant concern due to its advanced stage at diagnosis and high mortality rate. Currently, there is a scarcity of specific guidelines for BCa screening in these patients. The development of urine biomarkers for BCa seems to be an attractive non-invasive method of screening or risk stratification in this patient population. DNA methylation is an epigenetic modification, resulting in the transcriptional silencing of tumor suppression genes, that is frequently detected in the urine of BCa patients. Objectives: We aimed to investigate DNA hypermethylation in five gene promoters, previously associated with BCa, in the urine of NLUTD patients, and in comparison with healthy controls. Design, setting and participants: This was a prospective case–control study that recruited neurourology outpatients from a public teaching hospital who had suffered from NLUTD for at least 5 years. They all underwent cystoscopy combined with biopsy for BCa screening following written informed consent. DNA was extracted and DNA methylation was assessed for the RASSF1, RARβ, DAPK, TERT and APC gene promoters via quantitative methylation-specific PCR in urine specimens from the patients and controls. Results: Forty-one patients of mixed NLUTD etiology and 35 controls were enrolled. DNA was detected in 36 patients’ urine specimens and in those of 22 controls. In the urine specimens, DNA was hypermethylated in at least one of five gene promoters in 17/36 patients and in 3/22 controls (47.22% vs. 13.64%, respectively, p = 0.009). RASSF1 was hypermethylated in 10/17 (58.82%) specimens with detected methylation, APC in 7/17 (41.18%), DAPK in 4/17 (23.53%), RAR-β2 in 3/17 (17.56%) and TERT in none. According to a multivariate logistic regression analysis, NLUTD and male gender were significantly associated with hypermethylation (OR = 7.43, p = 0.007 and OR = 4.21; p = 0.04, respectively). In the tissue specimens, histology revealed TaLG BCa in two patients and urothelial squamous metaplasia in five patients. Chronic bladder inflammation was present in 35/41 bladder biopsies. Conclusions: DNA hypermethylation in a panel of five BCa-associated genes in the urine was significantly more frequent in NLUTD patients than in the controls. Our results warrant further evaluation in longitudinal studies assessing the clinical implications and possible associations between DNA hypermethylation, chronic inflammation and BCa in the NLUTD population.
Pan-Cancer Identification of Prognostic-Associated Metabolic Pathways
Authors: Chen Wenbo , Chen Xin , Zhao Zhenyu , Li Menglu , Dong Shuang , Hu Sheng , Li Xiaoyu , Feng Mingqian , Chen Ke , Zhong Shan , He Chunjiang
Published: August 2023

Metabolic dysregulation has been reported involving in the clinical outcomes of multiple cancers. However, systematical identification of the impact of metabolic pathways on cancer prognosis is still lacking. Here, we performed a pan-cancer analysis of popular metabolic checkpoint genes and pathways with cancer prognosis by integrating information of clinical survival with gene expression and pathway activity in multiple cancer patients. By discarding the effects of age and sex, we revealed extensive and significant associations between the survival of cancer patients and the expression of metabolic checkpoint genes, as well as the activities of three primary metabolic pathways: amino acid metabolism, carbohydrate metabolism, lipid metabolism, and eight nonprimary metabolic pathways. Among multiple cancers, we found the survival of kidney renal clear cell carcinoma and low-grade glioma exhibit high metabolic dependence. Our work systematically assesses the impact of metabolic checkpoint genes and pathways on cancer prognosis, providing clues for further study of cancer diagnosis and therapy.
Nitrogen Addition Affects Interannual Variation in Seed Production in a Tibetan Perennial Herb
Authors: Lou Yuanxin , Wang Ruolan , Che Peiyue , Zhao Chuan , Chen Yali , Yang Yangheshan , Mu Junpeng
Published: August 2023

The variability observed in the annual seed production of perennial plants can be seen as an indication of changes in the allocation of resources between growth and reproduction, which can be attributed to fluctuations in the environment. However, a significant knowledge gap exists concerning the impacts of nitrogen addition on the interannual seed production patterns of perennial plants. We hypothesized that the addition of nitrogen would impact the annual variations in the seed production of perennial plants, ultimately affecting their overall reproductive efficiency. A multiyear field experiment was conducted to investigate the effects of varying nitrogen supply levels (e.g., 0, 4, and 8 kg N ha−1 yr−1 of N0, N4, and N8) on vegetative and floral traits, pollinator visitation rates, and seed traits over a period of four consecutive years. The results showed that the N0 treatment exhibited the highest levels of seed production and reproductive efficiency within the initial two years. In contrast, the N4 treatment displayed its highest level of performance in these metrics in the second and third years, whereas the N8 treatment showcased its most favorable outcomes in the third and fourth years. Similar patterns were found in the number of flowers per capitulum and the number of capitula per plant. There exists a positive correlation between aboveground biomass and several factors, including the number of flowers per capitulum, the number of capitula per plant, the volume of nectar per capitulum, and the seed production per plant. A positive correlation was found between pollinator visitation and the number of flowers per capitulum or the number of capitula per plant. This implies that the addition of N affected the maintenance of plant aboveground biomass, flower trait stability, pollinator visitation, and, subsequently, the frequency of seed production and reproductive efficiency. Our results suggest that augmenting the nitrogen content in the soil may have the capacity to modify the inherent variability in seed production that is observed across various years and enhance the effectiveness of reproductive processes. These findings have the potential to enhance our comprehension of the impact of nitrogen addition on the reproductive performance of perennial herbaceous plants and the underlying mechanisms of biodiversity in the context of global environmental changes.
Computationally Modelling Cholesterol Metabolism and Atherosclerosis
Authors: Davies Callum , Morgan Amy E. , Mc Auley Mark T.
Published: August 2023

Cardiovascular disease (CVD) is the leading cause of death globally. The underlying pathological driver of CVD is atherosclerosis. The primary risk factor for atherosclerosis is elevated low-density lipoprotein cholesterol (LDL-C). Dysregulation of cholesterol metabolism is synonymous with a rise in LDL-C. Due to the complexity of cholesterol metabolism and atherosclerosis mathematical models are routinely used to explore their non-trivial dynamics. Mathematical modelling has generated a wealth of useful biological insights, which have deepened our understanding of these processes. To date however, no model has been developed which fully captures how whole-body cholesterol metabolism intersects with atherosclerosis. The main reason for this is one of scale. Whole body cholesterol metabolism is defined by macroscale physiological processes, while atherosclerosis operates mainly at a microscale. This work describes how a model of cholesterol metabolism was combined with a model of atherosclerotic plaque formation. This new model is capable of reproducing the output from its parent models. Using the new model, we demonstrate how this system can be utilized to identify interventions that lower LDL-C and abrogate plaque formation.
Assessing the Efficacy of PLGA-Loaded Antimicrobial Peptide OH-CATH30 Microspheres for the Treatment of Bacterial Keratitis: A Promising Approach
Authors: Jiao Xiaoqian , Dong Xufeng , Shan Hu , Qin Zhihua
Published: August 2023

Bacterial keratitis in animals presents challenges due to ocular structural barriers, hindering effective drug delivery. In this study, we used biocompatible and biodegradable poly(lactic-co-glycolic acid) (PLGA) to encapsulate the naturally occurring antimicrobial peptide OH-CATH30, an alternative to conventional antibiotics, for the treatment of bacterial keratitis in animals. Microspheres (MS) were prepared using a modified water-in-oil-in-water (W/O/W) double-emulsion method with optimized osmotic pressure. We conducted comprehensive evaluations, including in vitro characterization, encapsulation efficiency determination, in vitro release kinetics, and in vivo/vitro assessments of irritation and bacterial inhibition. The optimized method yielded microspheres with impressive encapsulation efficiency of 75.2 ± 3.62% and a loading capacity of 18.25 ± 5.73%, exhibiting a well-defined particle size distribution (200–1000 nm) and a ζ-potential of −17.3 ± 1.91 mV. The microspheres demonstrated initial burst release followed by sustained and controlled release in vitro. Both in vitro and in vivo tolerance tests confirmed the biocompatibility of the drug-loaded microspheres, as they did not elicit significant irritation in ocular tissues. Remarkable antibacterial effects were observed in both in vitro and in vivo experiments. Our developed PLGA microspheres show promise as an alternative therapeutic option for topical administration in managing keratitis, offering exceptional drug delivery capabilities, improved bioavailability, and potent antibacterial efficacy.
Hyperthermia Influences the Secretion Signature of Tumor Cells and Affects Endothelial Cell Sprouting
Authors: Maduabuchi Wisdom O. , Tansi Felista L. , Heller Regine , Hilger Ingrid
Published: August 2023

Tumors are a highly heterogeneous mass of tissue showing distinct therapy responses. In particular, the therapeutic outcome of tumor hyperthermia treatments has been inconsistent, presumably due to tumor versus endothelial cell cross-talks related to the treatment temperature and the tumor tissue environment. Here, we investigated the impact of the average or strong hyperthermic treatment (43 °C or 47 °C for 1 h) of the human pancreatic adenocarcinoma cell line (PANC-1 and BxPC-3) on endothelial cells (HUVECs) under post-treatment normoxic or hypoxic conditions. Immediately after the hyperthermia treatment, the distinct repression of secreted pro-angiogenic factors (e.g., VEGF, PDGF-AA, PDGF-BB, M-CSF), intracellular HIF-1α and the enhanced phosphorylation of ERK1/2 in tumor cells were detectable (particularly for strong hyperthermia, 2D cell monolayers). Notably, there was a significant increase in endothelial sprouting when 3D self-organized pancreatic cancer cells were treated with strong hyperthermia and the post-treatment conditions were hypoxic. Interestingly, for the used treatment temperatures, the intracellular HIF-1α accumulation in tumor cells seems to play a role in MAPK/ERK activation and mediator secretion (e.g., VEGF, PDGF-AA, Angiopoietin-2), as shown by inhibition experiments. Taken together, the hyperthermia of pancreatic adenocarcinoma cells in vitro impacts endothelial cells under defined environmental conditions (cell-to-cell contact, oxygen status, treatment temperature), whereby HIF-1α and VEGF secretion play a role in a complex context. Our observations could be exploited for the hyperthermic treatment of pancreatic cancer in the future.
Role of Syndecan-4 in the Inhibition of Articular Cartilage Degeneration in Osteoarthritis
Authors: Hattori Yoshio , Hasegawa Masahiro , Iino Takahiro , Imanaka-Yoshida Kyoko , Sudo Akihiro
Published: August 2023

Despite its widespread existence, there are relatively few drugs that can inhibit the progression of osteoarthritis (OA). Syndecan-4 (SDC4) is a transmembrane heparan sulfate proteoglycan that modulates cellular interactions with the extracellular matrix. Upregulated SDC4 expression in articular cartilage chondrocytes correlates with OA progression. In the present study, we treated osteoarthritic cartilage with SDC4 to elucidate its role in the disease’s pathology. In this in vitro study, we used real-time polymerase chain reaction (PCR) to investigate the effects of SDC4 on anabolic and catabolic factors in cultured chondrocytes. In the in vivo study, we investigated the effect of intra-articular injection of SDC4 into the knee joints of an OA mouse model. In vitro, SDC4 upregulated the expression of tissue inhibitor of metalloproteinase (TIMP)-3 and downregulated the expression of matrix metalloproteinase (MMP)-13 and disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)-5 in chondrocytes. Injection of SDC4 into the knee joints of OA model mice prevented articular cartilage degeneration 6 and 8 weeks postoperatively. Immunohistochemical analysis 8 weeks after SDC4 injection into the knee joint revealed decreased ADAMTS-5 expression and increased TIMP-3 expression. The results of this study suggest that the treatment of osteoarthritic articular cartilage with SDC4 inhibits cartilage degeneration.
Mast Cell Deficiency in Mice Attenuates Insulin Phenolic Preservative-Induced Inflammation
Authors: Kesserwan Shereen , Sadagurski Marianna , Mao Li , Klueh Ulrike
Published: August 2023

One major obstacle that limits the lifespan of insulin infusion pumps is surmounting the tissue site reaction at the device implantation site. All commercial insulin formulations contain insulin phenolic preservatives (IPPs) designed to ensure insulin protein stability and prolong shelf-life. However, our laboratory demonstrated that these preservatives are cytotoxic and induce inflammation. Mature mast cells (MCs) reside in cutaneous tissue and are one of the first responders to an epidermal breach. Upon activation, MCs release proinflammatory and immunomodulatory prepacked mediators that exacerbate these inflammatory reactions. Thus, we hypothesized that once the epidermis is breached, cutaneous MCs are triggered inciting the inflammatory response to IPP-induced inflammation. This hypothesis was pursued utilizing our modified in vivo mouse air pouch model, including a c-kit dependent (C57BL/6J-kitW-sh/W-sh) and a c-kit independent (Cpa3-Cre; Mcl-1fl/fl) MC-deficient mouse model. Leukocytes were quantified in the mouse air pouch lavage fluid following flow cytometry analysis for IPP infusion under three different states, insulin-containing phenolic preservatives (Humalog®), insulin preservatives alone, and normal saline as a control. The air pouch wall was assessed using histopathological evaluations. Flow cytometry analysis demonstrated a statistically significant difference in inflammatory cell recruitment for both MC-deficient mouse models when compared to the control strain including infused control saline. Significantly less inflammation was observed at the site of infusion for the MC-deficient strains compared to the control strain. Overall, concordant results were obtained in both mouse types, C57Bl6-kitW-sh/W-sh and Cpa3-Cre; Mcl-1fl/fl. These findings in multiple model systems support the conclusion that MCs have important or possible unique roles in IPP-induced inflammation.
A Protective Effect of Pirfenidone in Lung Fibroblast–Endothelial Cell Network via Inhibition of Rho-Kinase Activity
Authors: Nakamura Yusuke , Shimizu Yasuo , Fujimaki-Shiraishi Mio , Uchida Nobuhiko , Takemasa Akihiro , Niho Seiji
Published: August 2023

Pulmonary fibrosis is a life-threatening disease that has been attributed to several causes. Specifically, vascular injury is thought to be involved in the pathogenesis of fibrosis. The effects of the antifibrotic drug pirfenidone on angiogenesis have not been fully elucidated. This study aimed to investigate the effects of pirfenidone in human lung fibroblast–endothelial cell co-culture network formation and to analyze the underlying molecular mechanisms. Human lung fibroblasts were co-cultured with human umbilical vein endothelial cells to establish a co-culture network cell sheet. The influence of pirfenidone was evaluated for protective effect on the endothelial network in cell sheets stimulated with transforming growth factor β (TGF-β). Results indicated that TGF-β disrupted the network formation. Pirfenidone and Y27632 (Rho-associated coiled-coil containing protein kinase [Rho-kinase or ROCK] inhibitor) protected against the TGF-β–induced endothelial network disruption. TGF-β activated Rho-kinase signaling in cells composing the co-culture cell sheet, whereas pirfenidone and Y27632 inhibited these effects. In conclusion, TGF-β–induced Rho-kinase activation and disrupted endothelial network formation. Pirfenidone suppressed TGF-β–induced Rho-kinase activity in cell sheets, thereby enabling vascular endothelial cells networks to be preserved in the cell sheets. These findings suggest that pirfenidone has potential vascular network–preserving effect via inhibiting Rho-kinase activity in vascular injury, which is a precursor to pulmonary fibrosis.
Examining the Interaction between Exercise, Gut Microbiota, and Neurodegeneration: Future Research Directions
Authors: Rojas-Valverde Daniel , Bonilla Diego A. , Gómez-Miranda Luis M. , Calleja-Núñez Juan J. , Arias Natalia , Martínez-Guardado Ismael
Published: August 2023

Physical activity has been demonstrated to have a significant impact on gut microbial diversity and function. Emerging research has revealed certain aspects of the complex interactions between the gut, exercise, microbiota, and neurodegenerative diseases, suggesting that changes in gut microbial diversity and metabolic function may have an impact on the onset and progression of neurological conditions. This study aimed to review the current literature from several databases until 1 June 2023 (PubMed/MEDLINE, Web of Science, and Google Scholar) on the interplay between the gut, physical exercise, microbiota, and neurodegeneration. We summarized the roles of exercise and gut microbiota on neurodegeneration and identified the ways in which these are all connected. The gut–brain axis is a complex and multifaceted network that has gained considerable attention in recent years. Research indicates that gut microbiota plays vital roles in metabolic shifts during physiological or pathophysiological conditions in neurodegenerative diseases; therefore, they are closely related to maintaining overall health and well-being. Similarly, exercise has shown positive effects on brain health and cognitive function, which may reduce/delay the onset of severe neurological disorders. Exercise has been associated with various neurochemical changes, including alterations in cortisol levels, increased production of endorphins, endocannabinoids like anandamide, as well as higher levels of serotonin and dopamine. These changes have been linked to mood improvements, enhanced sleep quality, better motor control, and cognitive enhancements resulting from exercise-induced effects. However, further clinical research is necessary to evaluate changes in bacteria taxa along with age- and sex-based differences.
Hydrogel Bioelectronics for Health Monitoring
Authors: Lyu Xinyan , Hu Yan , Shi Shuai , Wang Siyuan , Li Haowen , Wang Yuheng , Zhou Kun
Published: August 2023

Hydrogels are considered an ideal platform for personalized healthcare due to their unique characteristics, such as their outstanding softness, appealing biocompatibility, excellent mechanical properties, etc. Owing to the high similarity between hydrogels and biological tissues, hydrogels have emerged as a promising material candidate for next generation bioelectronic interfaces. In this review, we discuss (i) the introduction of hydrogel and its traditional applications, (ii) the work principles of hydrogel in bioelectronics, (iii) the recent advances in hydrogel bioelectronics for health monitoring, and (iv) the outlook for future hydrogel bioelectronics’ development.
The Efficacy of Psychoeducational Family Intervention for Major Depression: Study Protocol of a Randomized Controlled Trial
Authors: Toni Claudia , Luciano Mario , Arsenio Eleonora , Boiano Alessia , Corvino Emilia , Della Rocca Bianca , Lapadula Maria , Tretola Lucia , Sampogna Gaia , Fiorillo Andrea
Published: August 2023

This study aims to assess the efficacy of a psychoeducational family intervention (PFI) to reduce the severity of depressive symptoms and to improve psychosocial functioning and to increase social contacts in a sample of patients with major depressive disorder (MDD). The degree to which PFI will reduce patients’ relapses, hospitalizations, and self-stigmatization and will improve their quality of life will also be assessed. Other secondary outcomes include the improvement of relatives’ coping strategies, family burden, expressed emotions and quality of life. This non-profit, unfunded, national, multicentric randomized controlled trial with blinded outcome assessments will be carried out in 24 Italian university outpatient units. Families will be assessed at baseline and at 6, 12, and 24 months post-randomization. Our working hypothesis is that the PFIs will reduce the patients’ severity of depressive symptoms, their relapses, and their hospitalizations, and that they will improve their psychosocial functioning and quality of life. We expect these results to be maintained after 12 and 24 months, albeit with a reduction in magnitude. The sample will consist of 384 patients randomized at a 1:1 ratio and stratified according to center, age, gender, and educational level.