bluuebunny/crossref_metadata_2025 huggingface dataset:
A Decision Support System for Crop Recommendation Using Machine Learning Classification Algorithms
Authors: Senapaty Murali Krishna , Ray Abhishek , Padhy Neelamadhab
Published: July 2024

Today, crop suggestions and necessary guidance have become a regular need for a farmer. Farmers generally depend on their local agriculture officers regarding this, and it may be difficult to obtain the right guidance at the right time. Nowadays, crop datasets are available on different websites in the agriculture sector, and they play a crucial role in suggesting suitable crops. So, a decision support system that analyzes the crop dataset using machine learning techniques can assist farmers in making better choices regarding crop selections. The main objective of this research is to provide quick guidance to farmers with more accurate and effective crop recommendations by utilizing machine learning methods, global positioning system coordinates, and crop cloud data. Here, the recommendation can be more personalized, which enables the farmers to predict crops in their specific geographical context, taking into account factors like climate, soil composition, water availability, and local conditions. In this regard, an existing historical crop dataset that contains the state, district, year, area-wise production rate, crop name, and season was collected for 246,091 sample records from the Dataworld website, which holds data on 37 different crops from different areas of India. Also, for better analysis, a dataset was collected from the agriculture offices of the Rayagada, Koraput, and Gajapati districts in Odisha state, India. Both of these datasets were combined and stored using a Firebase cloud service. Thirteen different machine learning algorithms have been applied to the dataset to identify dependencies within the data. To facilitate this process, an Android application was developed using Android Studio (Electric Eel | 2023.1.1) Emulator (Version 32.1.14), Software Development Kit (SDK, Android SDK 33), and Tools. A model has been proposed that implements the SMOTE (Synthetic Minority Oversampling Technique) to balance the dataset, and then it allows for the implementation of 13 different classifiers, such as logistic regression, decision tree (DT), K-Nearest Neighbor (KNN), SVC (Support Vector Classifier), random forest (RF), Gradient Boost (GB), Bagged Tree, extreme gradient boosting (XGB classifier), Ada Boost Classifier, Cat Boost, HGB (Histogram-based Gradient Boosting), SGDC (Stochastic Gradient Descent), and MNB (Multinomial Naive Bayes) on the cloud dataset. It is observed that the performance of the SGDC method is 1.00 in accuracy, precision, recall, F1-score, and ROC AUC (Receiver Operating Characteristics–Area Under the Curve) and is 0.91 in sensitivity and 0.54 in specificity after applying the SMOTE. Overall, SGDC has a better performance compared to all other classifiers implemented in the predictions.
Research on the Maturity Detection Method of Korla Pears Based on Hyperspectral Technology
Authors: Liu Jiale , Meng Hongbing
Published: July 2024

In this study, hyperspectral imaging technology with a wavelength range of 450 to 1000 nanometers was used to collect spectral data from 160 Korla pear samples at various maturity stages (immature, semimature, mature, and overripe). To ensure high-quality data, multiple preprocessing techniques such as multiplicative scatter correction (MSC), standard normal variate (SNV), and normalization were employed. Based on these preprocessed data, a custom convolutional neural network model (CNN-S) was constructed and trained to achieve precise classification and identification of the maturity stages of Korla pears. Additionally, a BP neural network model was used to determine the characteristic wavelengths for maturity assessment based on the sugar content feature wavelengths. The results demonstrated that the BP model, based on sugar content feature wavelengths, effectively discriminated the maturity stages of the pears. Specifically, the comprehensive recognition rates for the training, testing, and validation sets were 98.5%, 93.5%, and 90.5%, respectively. Furthermore, the combination of hyperspectral imaging technology and the custom CNN-S model significantly enhanced the detection performance of pear maturity. Compared to traditional CNN models, the CNN-S model improved the accuracy of the test set by nearly 10%. Moreover, the CNN-S model outperformed existing techniques based on partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) in capturing hyperspectral data features, showing superior generalization capability and detection efficiency. The superior performance of this method in practical applications further supports its potential in smart agriculture technology, providing a more efficient and accurate solution for agricultural product quality detection. Additionally, it plays a crucial role in the development of smart agricultural technology.
Accelerated Iron Evolution in Quaternary Red Soils through Anthropogenic Land Use Activities
Authors: Zhang Cheng-Cheng , Sun Zhong-Xiu , Jiang Ying-Ying , Duan Si-Yi
Published: July 2024

Iron in soil exists in various valence states and is prone to changes with alterations in soil environmental conditions. Its migration and transformation are crucial for soil formation and understanding soil evolution. This study focuses on Quaternary red soils found in woodland, sparse forest grassland, grassland, and cultivated land located in the semi-humid region of the middle temperate zone. For comparison, buried Quaternary red soil was also examined. A soil reconstruction model was used to quantitatively calculate the variation of different forms of iron in order to analyze various forms of iron composition, migration, and transformation within the soil profile, as well as the evolutionary traits of Quaternary red soils influenced by diverse land use activities. This study found that after exposure and use, iron from the topsoil of buried Quaternary red soil migrated to the subsoil, altering the iron distribution. Free iron and crystalline oxides decreased in the topsoil but increased in specific subsoil layers, with woodland and grassland showing the most significant changes. Silicate-bound iron pooled in the soil weathered to form free iron under different land uses, and poorly crystalline iron oxides transformed into crystalline oxides, with grassland exhibiting the highest transformation intensity. Conversion processes predominated over iron migration in the Quaternary red soils. The evolution of Quaternary red soils can be divided into three stages, marked by changes in iron composition and crystallization due to anthropogenic land use activities. Initially, during 140−94 ka BP, iron composition was stable. Then, between 94–24 ka BP, plant decomposition formed iron–metal complexes, releasing and crystallizing poorly crystalline iron oxides. Finally, from 24 ka BP to the present, anthropogenic activities intensified, increasing the formation and conversion rates of these oxides. This study quantifies iron migration and transformation in Quaternary red soils, providing insights for sustainable soil management, especially in regions where human activities have accelerated iron evolution. Based on these findings, the following policy recommendations are proposed: implement sustainable land use practices, encourage land management strategies that preserve natural vegetation, promote research on soil management techniques, develop and implement regulatory policies, and support educational programs to maintain the health and stability of Quaternary red soils, particularly in regions prone to accelerated iron evolution due to anthropogenic activities.
Effects of Irrigation Amount and Nitrogen Rate on Cotton Yield, Nitrogen Use Efficiency, and Soil Nitrogen Balance under Drip Irrigation
Authors: Liao Huan , Liu Kai , Hao Haibo , Yong Yanrong , Zhang Weibao , Hou Zhenan
Published: July 2024

Water and nitrogen (N) are major constraints for cotton growth and yield formation in arid regions. Irrigation and N application have been widely investigated to improve crop yield and water and N use efficiency (NUE). However, further optimization of water and N management is needed because the effects of N application on soil N balance and N loss under different irrigation levels remain unclear. In this study, a field experiment was conducted in 2020 and 2021 to investigate the effects of different irrigation amounts (full irrigation (100% ETc), moderate irrigation (80% ETc), low irrigation (60% ETc)) and N application rates (control (without N application, N0), low N (150 kg ha−1, N150), medium N (225 kg ha−1 and 300 kg ha−1, N225 and N300), and high N (375 kg ha−1, N375)) on cotton yield, NUE, and soil N balance. The 2-year results showed that under the 60% ETc treatment, cotton dry matter accumulation, N uptake, and yield were significantly enhanced by increasing N application. Under the 80% and 100% ETc treatments, these parameters peaked with the N300 treatment; the N375 treatment showed no significant difference or decrease compared to the N300 treatment. The 80% ETc N300 treatment had the highest cotton yield and NUE, which increased by 17.49–106.57% and 12.28–88.78% compared with other treatments, respectively. Residual soil N accumulation (RSNmin), apparent N loss (ANL), and apparent N surplus (ANS) increased as the N application rate increased under the 60% and 100% ETc treatments. While under the 80% ETc treatment, the ANS did not significantly differ between the N225 and N300 treatments, ANL significantly decreased by 43.51–88.56% when the N application rate increased from 150 to 225 and 300 kg ha−1. The ANL of the 80% ETc N300 treatment was the lowest, but ANS did not significantly increase. The regression analysis and spatial analysis results showed that under irrigation of 336–348 mm and N application of 254–327 kg ha−1, cotton yield, NUE, and WPI reached more than 80% of the maximum value, with less apparent N loss, thus maintaining the soil N balance in drip-irrigated cotton fields. This study helps to improve the utilization of water and N resources in cotton production. Future research on optimizing water and N management needs to more fully consider environmental pollution to achieve sustainable development of agricultural ecosystems.
Effect of Composted Organic Waste on Miscanthus sinensis Andersson Yield, Morphological Characteristics and Chlorophyll Fluorescence and Content
Authors: Zając Mariola , Skrajna Teresa
Published: July 2024

The aim of this research was to determine the impact of composted mushroom substrate and composted municipal waste on the quality and yield of Miscanthus sinensis Andersson biomass. The plant was grown on anthropogenic soil, cultured earth type and hortisol subtype, with a pH of 6.81. Before planting rhizomes, experimental plots were treated with composted mushroom substrate and composted municipal waste, applied separately or in combination, each dose introducing 170 N kg·ha−1 to the soil. During the experiment, observations of plant development and growth were carried out, and the yield was determined. Each growing season’s measurements were taken of the grass height, the number and diameter of stems and the number of leaf blades and of nodes per stem. In order to determine the level of plant stress, relative chlorophyll content and chlorophyll fluorescence parameters were determined. The measurements were carried out in a non-invasive way, using the SPAD-502 chlorophyll meter and OS30p+ plant stress meter. For the research hypothesis, it was assumed that the one-time addition of composted mushroom substrate and composted municipal waste to the soil would increase yields. The experiment also aimed to assess the impact of both types of compost on the yield and morphological characteristics of Miscanthus sinensis. Its yields increased steadily, and, in the third year of cultivation, were higher by 52%. The highest average yields were noted on plots fertilized only with composted mushroom substrate (KPP100%), with 8.44 Mg·ha−1 DM, and with compost from municipal waste (KOM100%), with 7.91 Mg·ha−1 DM. The experience presents a solution to the problem of increasing amounts of organic waste and represents an improvement in cultivation techniques to increase crop yields, improve their quality and increase resistance to biotic and abiotic stress. This paper highlights the possibility of applying environmentally friendly organic waste materials to energy crops used as a sustainable energy source.
Metagenomics Analysis of the Impact of Protein-Degrading Functional Microbial Agents on Composting of Chicken Manure from Cereal Hulls
Authors: Zhao Jinfeng , Wang Xinyu , Liu Zhuangzhuang , He Liuqin , Jiang Hongmei , Yao Hao , Fang Jun , Liu Gang
Published: July 2024

In this study, four highly efficient protein-degrading bacteria (Siccibactercolletis, Bacillus thuringiensis, Bacillus cereus, and Bacillus sp. (in: Firmicutes)) were screened from soil and fermentation beds and prepared into a mixed microbial agent in a ratio of 1:1:1:1. The effects of inoculation with protein-degrading functional bacteria on nitrogen transformation rate, microbial community, and functional genes during chicken manure–rice husk composting were studied. With the addition of functional agents, the nitrogen loss in chicken manure composting was reduced to 17.05%, and ammonia emissions were also reduced. Firmicutes, Proteobacteria, Bacteroidetes, Cocci, and Actinobacteria became the dominant bacterial communities, accounting for 85.41%~98.52% of the overall bacterial community in the compost; it promoted the growth of microorganisms such as Pseudogracilibacillus and Lachnospiraceae in the compost. Metagenomic analysis revealed that the addition of functional bacterial agents enhanced the expression of nitrogen fixation genes (nifK, nifH, and glnA) during the high-temperature phase, increased the diversity of bacteria associated with the nitrogen cycle in the compost, and improved the absorption and fixation of nitrogen source elements by microorganisms. Additionally, it strengthened the correlation between microbial communities, the composting environment, and functional genes. This study provides a theoretical basis for the efficient application of microbial agents and the reduction of pollution in chicken manure hull composting.
The Expression of Genes Involved in Synthesis of Bitter Acids and Xanthohumol and the Content of These Compounds in Aroma and Bitter Hop under Reduced Nitrogen Fertilisation
Authors: Czubacka Anna , Skomra Urszula , Agacka-Mołdoch Monika , Koziara-Ciupa Marta
Published: July 2024

Hop (Humulus lupulus) is cultivated for industrial purposes, primarily for brewing, but also for pharmaceutical and cosmetic applications. The hop cones are valued for their secondary metabolites, including bitter acids and prenylflavonoids. The objective of the presented study was to investigate the impact of reducing nitrogen fertilisation on the activity of genes involved in the production of bitter acids and xanthohumol in cultivars Lubelski (aroma) and Magnat (bitter) grown in the field. Furthermore, the content of these compounds was determined. The results demonstrated that the majority of studied genes were expressed at a similar level despite the reduction in the nitrogen dose by 25–30%. Nitrogen dose influenced the activity of genes BCAT2, HS1, and PAL. Moreover, the differences in gene expression were observed between cultivars and developmental stages. The reduction in nitrogen dose did not result in a reduction in secondary metabolite content. The content of alpha and beta acids in Magnat was approximately 14.8% and 3.2%, respectively, while in Lubelski it was approximately 7.7% and 5.8%, respectively. The content of xanthohumol in both cultivars was approximately 0.7%.
How Can Soil Quality Be Accurately and Quickly Studied? A Review
Authors: El Behairy Radwa A. , El Arwash Hasnaa M. , El Baroudy Ahmed A. , Ibrahim Mahmoud M. , Mohamed Elsayed Said , Kucher Dmitry E. , Shokr Mohamed S.
Published: July 2024

Evaluating soil quality is crucial for ensuring the sustainable use of agricultural lands. This review examines the definition, evaluation methods, indicator selection, and relevant case studies. The concept of soil quality supplements soil science research by deepening our understanding of soils and aiding in the allocation of resources as agriculture intensifies to meet rising global demand. Soil quality provides a framework for educating stakeholders about the essential functions of soils and offers a tool for assessing and comparing different management techniques. Regular evaluation of soil quality is vital for maintaining high crop yields and addressing the gap between production and consumption. Nowadays, many researchers have explored machine learning (ML) and deep learning (DL) techniques and various algorithms to model and predict soil quality with satisfactory results. These chosen indicators can be influenced by chemical, biological, or physical features. This paper compares ML and DL with traditional methods, examining their features, limitations, different categories of machine learning, and their applications in soil quality assessment. Finally, we show that predicting soil quality has the potential to be extremely accurate and efficient with ML and DL. This distinguishes the application of DL and ML from other approaches since they can anticipate the soil quality index without the need for more intricate computations. Our suggestion for future studies is to evaluate soil quality over broader regions and predict it by using more accurate, modern, and faster methods, using a variety of activation functions and algorithms.
A Critical Functional Missense Mutation (T117M) in Sheep MC4R Gene Significantly Leads to Gain-of-Function
Authors: Zhao Ziyi , Yang Yuta , Liu Peiyao , Yan Taotao , Li Ran , Pan Chuanying , Li Yang , Lan Xianyong
Published: July 2024

The melanocortin 4 receptor (MC4R) gene plays a central role in regulating energy homeostasis and food intake in livestock, thereby affecting their economic worth and growth. In a previous study, the p.T117M mutation in the sheep MC4R gene, which leads to the transition of threonine to methionine, was found to affect the body weight at six months and the average daily gain in Hu sheep. However, there are still limited studies on the frequency of the sheep p.T117M missense mutation globally, and the underlying cellular mechanism remains elusive. Therefore, this study first used WGS to investigate the distribution of the MC4R gene p.T117M mutation in 652 individuals across 22 breeds worldwide. The results showed that the mutation frequency was higher in European breeds compared with Chinese sheep breeds, particularly in Poll Dorset sheep (mutation frequency > 0.5). The p.T117M mutation occurs in the first extracellular loop of MC4R. Mechanistically, the basal activity of the mutated receptor is significantly increased. Specifically, upon treatment with α-MSH and ACTH ligands, the cAMP and MAPK/ERK signaling activation of M117 MC4R is enhanced. These results indicate that the T117M mutation may change the function of the gene by increasing the constitutive activity and signaling activation of cAMP and MAPK/ERK, and, thus, may regulate the growth traits of sheep. In conclusion, this study delved into the global distribution and underlying cellular mechanisms of the T117M mutation of the MC4R gene, establishing a scientific foundation for breeding sheep with superior growth, thereby contributing to the advancement of the sheep industry.
Use of Hair as Matrix for Trace Elements Biomonitoring in Cattle and Roe Deer Sharing Pastures in Northern Italy
Authors: Draghi Susanna , Fehri Nour Elhouda , Ateş Fatma , Özsobacı Nural Pastacı , Tarhan Duygu , Bilgiç Bengü , Dokuzeylül Banu , Yaramış Çağla Parkan , Ercan Alev Meltem , Or Mehmet Erman , Cagnardi Petra , Brecchia Gabriele , Curone Giulio , Di Cesare Federica
Published: July 2024

Intensive cattle breeding’s environmental challenges are prompting shifts to extensive, pasture-based systems, influencing nutrient and pollutant uptake. PTEs are essential and non-essential elements, regularly found in the environment and organisms, and in which unbalances lead to health issues. Hair analysis, a non-invasive method, provides retrospective PTE exposure evaluation. This study aims to understand exposure and species-specific accumulation patterns of PTEs in cattle and roe deer sharing pastures in Northern Italy using the hair analysis. Aluminum, As, Cd, Cr, Ni, Pb, Cu, Mg, Fe, and Zn were quantified through the use of ICP-OES. Findings show As levels significantly higher in roe deer due to their selective feeding, while Cd and Pb levels align with other studies. Essential elements like Cu, Fe, and Zn are lower in cattle, possibly due to diet differences. Higher Cr and Ni levels in cattle suggest contamination or physiological differences in accumulation patterns. In conclusion, hair analysis is valuable for monitoring environmental PTE exposure, highlighting significant interspecies differences and the potential of both animals as bioindicators in shared grazing areas.
Resveratrol Enhances Antioxidant and Anti-Apoptotic Capacities in Chicken Primordial Germ Cells through m6A Methylation: A Preliminary Investigation
Authors: Qiao Yanzhao , Xiao Gengsheng , Zhu Xiaohua , Wen Jun , Bu Yonghui , Zhang Xinheng , Kong Jie , Bai Yinshan , Xie Qingmei
Published: July 2024

Avian primordial germ cells (PGCs) are essential in avian transgenic research, germplasm conservation, and disease resistance breeding. However, cultured PGCs are prone to fragmentation and apoptosis, regulated at transcriptional and translational levels, with N6-methyladenosine (m6A) being the most common mRNA modification. Resveratrol (RSV) is known for its antioxidant and anti-apoptotic properties, but its effects on PGCs and the underlying mechanisms are not well understood. This study shows that RSV supplementation in cultured PGCs improves cell morphology, significantly enhances total antioxidant capacity (p < 0.01), reduces malondialdehyde levels (p < 0.05), increases anti-apoptotic BCL2 expression, and decreases Caspase-9 expression (p < 0.05). Additionally, RSV upregulates the expression of m6A reader proteins YTHDF1 and YTHDF3 (p < 0.05). m6A methylation sequencing revealed changes in mRNA m6A levels after RSV treatment, identifying 6245 methylation sites, with 1223 unique to the control group and 798 unique to the RSV group. Combined analysis of m6A peaks and mRNA expression identified 65 mRNAs with significantly altered methylation and expression levels. Sixteen candidate genes were selected, and four were randomly chosen for RT-qPCR validation, showing results consistent with the transcriptome data. Notably, FAM129A and SFRP1 are closely related to apoptosis, indicating potential research value. Overall, our study reveals the protective effects and potential mechanisms of RSV on chicken PGCs, providing new insight into its use as a supplement in reproductive stem cell culture.
Local Antimicrobial Therapy with Combined Aminoglycoside and Vancomycin Compared to Aminoglycoside Monotherapy in the Surgical Management of Osteomyelitis and Fracture-Related Infection
Authors: Unsworth Annalise , Young Bernadette , Ferguson Jamie , Scarborough Matthew , McNally Martin
Published: July 2024

We investigated the effect of combination aminoglycoside and vancomycin local antibiotic treatment compared to aminoglycoside alone in the surgical management of bone infection. Data including patient demographics, type of surgery, microbiological characteristics, BACH score, duration of antibiotic treatment and clinical outcomes were collected. Failure of therapy was a composite of recurrence of infection, continued or new antimicrobial therapy, or reoperation with suspected or confirmed infection at one year after index surgery. A total of 266 patients met the inclusion criteria. 252 patients reached the final follow-up and were included in the final analysis. 113 patients had treatment with aminoglycoside alone and 139 patients had combination aminoglycoside and vancomycin. There was no difference in the failure rate between groups; 10/113 (8.8%) in the aminoglycoside alone and 12/139 (8.6%) in the combination group, p = 0.934. Multivariate analysis showed that there was no added benefit of combination therapy (OR 1.54: 95% CI 0.59–4.04, p = 0.38). BACH score and low BMI were associated with increased risk of failure (BACH OR 3.49: 95% CI 1.13–10.76, p = 0.03; Low BMI OR 0.91: 95% CI 0.84–0.99, p = 0.037). The form of the carrier material (pellets or injectable paste) had no effect on failure rate (p = 0.163). The presence of aminoglycoside resistance had no effect on failure rate (OR 0.39: 95% CI 0.05–3.01, p = 0.37). Clinical outcome was not improved by the addition of vancomycin to aminoglycoside alone as local therapy for the management of bone infection.
Matrix Metalloproteinase 9 (MMP-9) and Interleukin-8 (IL-8) in Gingival Crevicular Fluid after Minimally Invasive Periodontal Surgery with or without Er:YAG and Nd:YAG Laser Application
Authors: Dolińska Ewa , Skurska Anna , Dymicka-Piekarska Violetta , Milewski Robert , Pietruska Małgorzata
Published: July 2024

Background: This study aimed to evaluate alterations in the concentrations of matrix metalloproteinase-9 (MMP-9) and interleukin-8 (IL-8) within gingival crevicular fluid (GCF) extracted from the intrabony periodontal defect site before and after minimally invasive regenerative surgery, with or without supplemental laser application. The surgical procedure was performed using the modified minimally invasive surgical technique (M-MIST). Methods: Thirty-eight patients, each presenting with a single vertical defect, were randomly assigned to either the test (M-MIST + Er:YAG + Nd:YAG) or the control group (M-MIST). IL-8 and MMP-9 levels (primary outcomes of the study) were assessed prior to therapy, after 2 and 4 weeks, and 6 months following the surgical procedure by means of dedicated ELISA kits. Results: Both procedures were clinically effective as evidenced by probing depth (PD) reduction and clinical attachment level (CAL) gain at the 6-month follow-up. No statistical differences were observed in the levels of MMP-9 and IL-8 between the groups at any time point assessed. The changes in the level of MMP-9 and IL-8 over time were not statistically significant in any group. IL-8 was positively correlated with MMP-9 in the control group throughout the study and in the test group 2 weeks and 6 months post-op. Conclusions: Within the limitations of this study, the additional application of Er:YAG + Nd:YAG lasers alongside the M-MIST procedure did not enhance the clinical and biochemical treatment outcomes compared to M-MIST alone.
Clinacanthus nutans (Burm. f.) Lindau Extract Inhibits Dengue Virus Infection and Inflammation in the Huh7 Hepatoma Cell Line
Authors: Jantakee Kanyaluck , Panwong Suthida , Sattayawat Pachara , Sumankan Ratchaneewan , Saengmuang Sasithorn , Choowongkomon Kiattawee , Panya Aussara
Published: July 2024

Dengue virus (DENV) infection has emerged as a global health problem, with no specific treatment available presently. Clinacanthus nutans (Burm. f.) Lindau extract has been used in traditional medicine for its anti-inflammatory and antiviral properties. We thus hypothesized C. nutans had a broad-ranged activity to inhibit DENV and the liver inflammation caused by DENV infection. The study showed that treatment using C. nutans extract during DENV infection (co-infection step) showed the highest efficiency in lowering the viral antigen concentration to 22.87 ± 6.49% at 31.25 μg/mL. In addition, the virus–host cell binding assay demonstrated that C. nutans treatment greatly inhibited the virus after its binding to Huh7 cells. Moreover, it could remarkably lower the expression of cytokine and chemokine genes, including TNF-α, CXCL10, IL-6, and IL-8, in addition to inflammatory mediator COX-2 genes. Interestingly, the activation of the NF-κB signaling cascade after C. nutans extract treatment was dramatically decreased, which could be the underlying mechanism of its anti-inflammatory activity. The HPLC profile showed that gallic acid was the bioactive compound of C. nutans extract and might be responsible for the antiviral properties of C. nutans. Taken together, our results revealed the potential of C. nutans extract to inhibit DENV infection and lower inflammation in infected cells.
First Data on WGS-Based Typing and Antimicrobial Resistance of Human Salmonella Enteritidis Isolates in Greece
Authors: Polemis Michalis , Sideroglou Theologia , Chrysostomou Anthi , Mandilara Georgia D.
Published: July 2024

Salmonella enterica subsp. enterica serotype Enteritidis (S. Enteritidis) is one of the major causes of foodborne infections and is responsible for many national and multi-country foodborne outbreaks worldwide. In Greece, human salmonellosis is a mandatory notifiable disease, with laboratory surveillance being on a voluntary basis. This study aims to provide the first insights into the genetic characteristics and antimicrobial resistance profiles of 47 S. Enteritidis human isolates using whole-genome sequencing (WGS) technology. The S. Enteritidis population was mainly resistant to fluoroquinolones due to gyrA point mutations, whereas one isolate presented a multi-resistant plasmid-mediated phenotype. ST11 was the most frequent sequence type, and phylogenetic analysis through the cgMLST and SNP methods revealed considerable genetic diversity. Regarding virulence factors, 8 out of the 24 known SPIs and C63PI were detected. Due to the observed variability between countries, it is of utmost importance to record the circulating S. Enteritidis strains’ structure and genomic epidemiology at the national level. WGS is a valuable tool that is revolutionizing our approach to Salmonella by providing a deeper understanding of these pathogens and their impact on human health.
Clinical Outcomes of Patients with AmpC-Beta-Lactamase-Producing Enterobacterales Bacteremia Treated with Carbapenems versus Non-Carbapenem Regimens: A Single-Center Study
Authors: Shalabi Orjowan , Kashat Livnat , Murik Omer , Zevin Shoshana , Assous Marc V. , Ben-Chetrit Eli
Published: July 2024

Introduction: Bloodstream infections caused by AmpC-producing Enterobacterales pose treatment challenges due to the risk of AmpC overproduction and treatment failure. Current guidelines recommend carbapenems or cefepime as optimal therapy. We aimed to evaluate empiric and definitive non-carbapenem regimens for these infections. Methods: In a retrospective study from June 2014 to March 2023, adult bacteremic patients with Enterobacter cloacae complex strains and Morganella morganii were evaluated. Demographic, clinical and lab data and outcomes were assessed. Results: The cohort comprised 120 bacteremic patients, 17 receiving empiric carbapenem and 103 non-carbapenem regimens. Both groups had similar Charlson and Norton scores and previous antimicrobial exposure. The most common sources of bacteremia were urinary, abdominal and central-line-associated sources. Empiric non-carbapenem regimens (primarily piperacillin–tazobactam and cephalosporins) were not associated with recurrent bacteremia or 30-day mortality. Definitive regimens included mainly carbapenems (n = 41) and ciprofloxacin (n = 46). Beta-lactams were administered to 25 patients. Recurrent bacteremia and 30-day mortality rates were similar among treatment groups. Ciprofloxacin showed comparable outcomes to carbapenems, however, severity of illness among these patients was lower. Conclusions: Empiric and definitive non-carbapenem regimens for bacteremia with AmpC-producing organisms were not associated with treatment failure or increased 30-day mortality. Ciprofloxacin appears promising for selected, stable patients, potentially enabling early discharge.
Synergistic Interactions between Selected β-Lactam Antibiotics and Cinnamic Acid and Its Chosen Derivatives
Authors: Zawiła Tomasz , Swolana Denis , Zawiła Marta , Wojtyczka Robert D.
Published: July 2024

Staphylococcus epidermidis, a component of human microbiota, may also cause life-threatening opportunistic infections. These are becoming increasingly common infections associated with the implantation of various implants. Due to the exhaustion of antibiotic resources, new substances with antimicrobial activity are being sought. The present study examined the antibacterial effect of cinnamic acid and its derivatives and their combinations with β-lactam antibiotics on the growth of Staphylococcus epidermidis strains isolated from vascular infections. The data obtained during the research indicated that cinnamic acid and its derivatives, sinapic acid, ferulic acid, and p-coumaric acid, have weak antibacterial activity (MIC values at the level of 2048 and 4096 mg/L). The combination of cinnamic acid and its derivatives with β-lactam antibiotics increases the effectiveness of their action and may demonstrate various pharmacological effects depending on the established cutoff.
Short-Term Celecoxib Promotes Bone Formation without Compromising Cefazolin Efficacy in an Early Orthopaedic Device-Related Infection: Evidence from a Rat Model
Authors: Mdingi Vuyisa Siphelele , Gens Lena , Mys Karen , Varga Peter , Zeiter Stephan , Marais Leonard Charles , Richards Robert Geoffrey , Moriarty Fintan Thomas , Chittò Marco
Published: July 2024

Non-steroidal anti-inflammatory drugs (NSAIDs) are crucial components of multimodal analgesia for musculoskeletal injuries, targeting cyclooxygenase (COX) enzymes (COX-1 and/or COX-2 isoenzymes). Concerns exist regarding their potential interference with bone healing and orthopaedic device-related infections (ODRI), where data are limited. This study aimed to investigate whether the COX-selectivity of NSAIDs interfered with antibiotic efficacy and bone changes in the setting of an ODRI. In vitro testing demonstrated that combining celecoxib (a COX-2 inhibitor) with cefazolin significantly enhanced antibacterial efficacy compared to cefazolin alone (p < 0.0001). In vivo experiments were performed using Staphylococcus epidermidis in the rat proximal tibia of an ODRI model. Long and short durations of celecoxib treatment in combination with antibiotics were compared to a control group receiving an antibiotic only. The long celecoxib treatment group showed impaired infection clearance, while the short celecoxib treatment showed increased bone formation (day 6, p < 0.0001), lower bone resorption (day 6, p < 0.0001), and lower osteolysis (day 6, BV/TV: p < 0.0001; BIC: p = 0.0005) compared to the control group, without impairing antibiotic efficacy (p > 0.9999). Given the use of NSAIDs as part of multimodal analgesia, and considering these findings, short-term use of COX-2 selective NSAIDs like celecoxib not only aids pain management but also promotes favorable bone changes during ODRI.
Prediction of Concomitant Nosocomial Infection in Patients Previously Colonized Colorectally by Multidrug-Resistant Bacteria in an SDD Setting
Authors: Ruiz-Santana Sergio , Dearriba-Reyes José , Saavedra Pedro , Iglesias-Llorente Laura , Alonso-Acero Laura , Hernández-Socorro Carmen-Rosa , Sánchez-Ramírez Catalina
Published: July 2024

Background: Antibiotic resistance is a worldwide concern. This study retrospectively analyzed patients admitted to the ICU of a tertiary hospital over a period of 7 months who were rectally colonized by multidrug-resistant microorganisms. The incidence of concomitant nosocomial infections was estimated, thus providing the risk of a colonizing microorganism producing a nosocomial infection. Methods: Infections with the same microorganism (concomitant) or different microorganisms (non-concomitant) were analyzed in order to adjust the empirical antibiotic treatment. Patients with rectal colonization by at least one multidrug-resistant bacterium (MDRB) on admission or after ICU admission were included. All patients had complete selective digestive decontamination (SDD) prophylaxis. For univariate analysis, categorical variables are expressed as frequencies and percentages and continuous variables as means and standard deviations, or as medians and interquartile ranges. For multivariate analysis, the model is summarized with p-values and hazard ratios with 95% confidence intervals. Survival analysis was conducted using the Kaplan–Meier method, which was performed to evaluate the time elapsed from colonization to infection by the same bacteria. Statistical significance was considered at p < 0.05. Results: Of the 130 patients with MDRB bacterial colonization analyzed, 98 remained free of infection, while 22 developed non-concomitant infections and 10 had infections concomitant to rectal colonizing bacteria. OXA-48-producing bacteria and MDR-Pseudomonas spp. incidences were 18.9% (95% CI: 7.96–35.2) and 44.4% (CI: 13.7–78.8), respectively. Conclusions: OXA-48-producing bacteria and MDR-Pseudomonas spp. were the only bacteria associated with the development of infections concomitant to rectal colonization in an SDD setting. The incidence of MDRB infections was low.
Evaluating Intelligent CPTED Systems to Support Crime Prevention Decision-Making in Municipal Control Centers
Authors: Choi Woochul , Na Joonyeop , Lee Sangkyeong
Published: July 2024

To maximize its synergetic effect across the cycle from prevention to response to post-crime management, crime prevention requires a balanced combination of spatial urban design and advanced crime prevention technologies for crime prediction and real-time response. This study derived intelligent Crime Prevention Through Environmental Design (CPTED) services and suggested a decision model based on the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to implement these services in municipal control centers. The analysis results are summarized as follows. First, this study established a fuzzy TOPSIS-based decision-making support model enabling local government control centers to effectively select intelligent CPTED service elements. Second, overall, operator-led Closed-Circuit Television (CCTV) and platform control technologies were identified as significant components of intelligent CPTED service elements. Third, a comparison by city size revealed that large cities in the Seoul metropolitan area rated system services for control based on advanced crime prevention infrastructure (e.g., the crime monitoring systems and real-time control drones/robots) relatively higher. In contrast, small and medium-sized cities in other provinces rated services that were perceptible to residents and improved crime-prone environments (e.g., artificial intelligence (AI) video analysis for living safety) relatively higher.
A Low-Cost Redundant Attitude System for Small Satellites, Based on Strap-Down Inertial Techniques and Gyro Sensors Linear Clustering
Authors: Mustață Mircea Ștefan , Grigorie Teodor Lucian
Published: July 2024

The significant technological changes related to the manufacturing of the miniaturized sensors produced a higher impact at the level of the detection units equipping the strap-down inertial navigation systems (INSs). Together with miniaturization, many more advantages are brought by these technologies, related to low costs, low necessary energy, high robustness and high potential for adapting the design solutions. However, reducing the dimensions and weight of the sensors is reflected by a decrease in their performance in terms of sensitivity, noise and the possibility of controlling sensitive elements. On the other hand, there is a permanent increase in the need to have in-space applications of miniaturized systems with a high degree of redundancy and to equip miniaturized satellites, miniaturized space robots or space rovers. The paper proposes a new methodology to increase the quality of the signals received from the miniaturized inertial measurement units (IMUs), but also to increase the degree of redundancy, by using low-cost sensors arranged in redundant linear configurations. The presentation is focused on the development of an attitude system based on strap-down inertial techniques which uses a redundant IMU equipped with three linear clusters of miniaturized gyros. For each of the three clusters, a data fusion mechanism based on the maximal ratio combining method is applied. This fusion mechanism reduces the noise power and bias of the signal delivered to the navigation processor. Shown are the theory, software modeling and experimentation results for the attitude algorithm, for the data fusion method, and for the integrated system.
Artificial Intelligence in Biomaterials: A Comprehensive Review
Authors: Gokcekuyu Yasemin , Ekinci Fatih , Guzel Mehmet Serdar , Acici Koray , Aydin Sahin , Asuroglu Tunc
Published: July 2024

The importance of biomaterials lies in their fundamental roles in medical applications such as tissue engineering, drug delivery, implantable devices, and radiological phantoms, with their interactions with biological systems being critically important. In recent years, advancements in deep learning (DL), artificial intelligence (AI), machine learning (ML), supervised learning (SL), unsupervised learning (UL), and reinforcement learning (RL) have significantly transformed the field of biomaterials. These technologies have introduced new possibilities for the design, optimization, and predictive modeling of biomaterials. This review explores the applications of DL and AI in biomaterial development, emphasizing their roles in optimizing material properties, advancing innovative design processes, and accurately predicting material behaviors. We examine the integration of DL in enhancing the performance and functional attributes of biomaterials, explore AI-driven methodologies for the creation of novel biomaterials, and assess the capabilities of ML in predicting biomaterial responses to various environmental stimuli. Our aim is to elucidate the pivotal contributions of DL, AI, and ML to biomaterials science and their potential to drive the innovation and development of superior biomaterials. It is suggested that future research should further deepen these technologies’ contributions to biomaterials science and explore new application areas.
Efficient and Sustainable Cleaning: A Comparative Analysis of Cryogenic Technology
Authors: Vega-Bosch Aina , Santamarina-Campos Virginia , Osete-Cortina Laura , Sánchez-Pons Mercedes , Bosch-Roig Pilar
Published: July 2024

Dry ice blasting is a technology that has been widely studied and applied in different industrial sectors as an alternative to the use of solvent, water, or abrasive spraying methods. It is a CO2 spraying system capable of balancing efficiency and sustainability with a wide variety of equipment available on the market. This study analyses and compares cryo-cleaning equipment manufactured by pioneering companies in the cryogenic industry. Based on data sheets, safety data sheets, and contact with manufacturers, a quantitative comparative study has been carried out. The aim of this study is to identify those with the best performance, efficiency, and adaptability to operational and environmental requirements. The results reflect the strengths and weaknesses of the equipment in terms of occupational safety and operability. These have been discussed and evaluated, recognising improvements of this technology, which is capable of removing surface layers of different natures without altering the underlying substrate.
An Adaptive Multi-Objective Genetic Algorithm for Solving Heterogeneous Green City Vehicle Routing Problem
Authors: Zhao Wanqiu , Bian Xu , Mei Xuesong
Published: July 2024

Intelligent scheduling plays a crucial role in minimizing transportation expenses and enhancing overall efficiency. However, most of the existing scheduling models fail to comprehensively account for the requirements of urban development, as exemplified by the vehicle routing problem with time windows (VRPTW), which merely specifies the minimization of path length. This paper introduces a new model of the heterogeneous green city vehicle routing problem with time windows (HGCVRPTW), addressing challenges in urban logistics. The HGCVRPTW model considers carriers with diverse attributes, recipients with varying tolerance for delays, and fluctuating road congestion levels impacting carbon emissions. To better deal with the HGCVRPTW, an adaptive multi-objective genetic algorithm based on the greedy initialization strategy (AMoGA-GIS) is proposed, which includes the following three advantages. Firstly, considering the impact of initial information on the search process, a greedy initialization strategy (GIS) is proposed to guide the overall evolution during the initialization phase. Secondly, the adaptive multiple mutation operators (AMMO) are introduced to improve the diversity of the population at different evolutionary stages according to their success rate of mutation. Moreover, we built a more tailored testing dataset that better aligns with the challenges faced by the HGCVRPTW. Our extensive experiments affirm the competitive performance of the AMoGA-GIS by comparing it with other state-of-the-art algorithms and prove that the GIS and AMMO play a pivotal role in advancing algorithmic capabilities tailored to the HGCVRPTW.
Multi-Criteria Decision-Making Method for Simple and Fast Dimensioning and Selection of Glass Tube Collector Type Based on the Iterative Thermal Resistance Calculation Algorithm with Experimental Validation
Authors: Nešović Aleksandar , Kowalik Robert , Cvetković Dragan , Janaszek Agata
Published: July 2024

This paper presents an analytical method for the dimensioning and selection of the four glass tube collector types: single-glazed with an air layer, single-glazed with a vacuum layer, double-glazed with an air layer, and double-glazed with a vacuum layer. In the first part of the paper (dimensioning phase), the iterative thermal resistance calculation algorithms were developed for all glass tube collector types, whereby the iterative thermal resistance calculation algorithm of the single-glazed tube collector with an air layer was experimentally tested and validated. The second part of the paper (selection phase) uses a multi-criteria decision-making method to determine the optimal glass tube collector design. Unlike other papers, three indicator groups are taken into account in this case: geometric (mass, surface occupation, total surface occupation, volume occupation), economic (manufacturing and exploitation costs), and ecological (embodied energy and greenhouse gas emission). The proposed method is characterized by simple and fast calculations with satisfactory accuracy, which avoids high investment costs (experimental research), approximation and discretization of physical models (numerical research), and a large number of input parameters with boundary conditions (theoretical research). It should be noted that, with certain additions and changes, it can also be applied to other solar thermal collectors, so the authors believe such tools are handy for the global scientific public.