bluuebunny/crossref_metadata_2025 huggingface dataset:
Fine tuning a logical model of cancer cells to predict drug synergies: combining manual curation and automated parameterization
Authors: Flobak Åsmund , Zobolas John , Vazquez Miguel , Steigedal Tonje S. , Thommesen Liv , Grislingås Asle , Niederdorfer Barbara , Folkesson Evelina , Kuiper Martin
Published: November 2023

Treatment with combinations of drugs carries great promise for personalized therapy for a variety of diseases. We have previously shown that synergistic combinations of cancer signaling inhibitors can be identified based on a logical framework, by manual model definition. We now demonstrate how automated adjustments of model topology and logic equations both can greatly reduce the workload traditionally associated with logical model optimization. Our methodology allows the exploration of larger model ensembles that all obey a set of observations, while being less restrained for parts of the model where parameterization is not guided by biological data. We benchmark the synergy prediction performance of our logical models in a dataset of 153 targeted drug combinations. We show that well-performing manual models faithfully represent measured biomarker data and that their performance can be outmatched by automated parameterization using a genetic algorithm. Whereas the predictive performance of a curated model is strongly affected by simulated curation errors, data-guided deletion of a small subset of regulatory model edges can significantly improve prediction quality. With correct topology we find evidence of some tolerance to simulated errors in the biomarker calibration data, yet performance decreases with reduced data quality. Moreover, we show that predictive logical models are valuable for proposing mechanisms underpinning observed synergies. With our framework we predict the synergy of joint inhibition of PI3K and TAK1, and further substantiate this prediction with observations in cancer cell cultures and in xenograft experiments.
Binary mixtures of imidacloprid and thiamethoxam do not appear to cause additive toxicity in fathead minnow larvae (Pimephales promelas)
Authors: Jeninga Anya J. , Kooij Nicole , Harrahy Elisabeth , King-Heiden Tisha C.
Published: November 2023

Introduction: Considerable use of neonicotinoid insecticides has resulted in their detection in surface waters globally, with imidacloprid (IM) and thiamethoxam (TM) frequently found together. Neonicotinoids are selective agonists for invertebrate nicotinic acetylcholine receptors (nAChR) leading to paralysis and death. While not overtly toxic to vertebrates, growing evidence suggests that chronic exposure to individual neonicotinoids can cause adverse health effects in fish. This work examined whether chronic exposure to binary mixtures of imidacloprid (IM) and thiamethoxam (TM) would be more toxic to fathead minnow (Pimephales promelas) larvae than either insecticide alone.

Materials and Methods: Embryos were exposed to a 1:1 mixture of IM and TM (0.2, 2, 20, 200 or 2,000 μg/L of each pesticide) or a 1:5, 1:10, or 1:20 mixture of IM and TM (0.02 μg/L of IM with 0.1, 0.2, or 0.4 μg/L of TM) for a total of 8 days. Survival, developmental toxicity, embryonic motor activity, and startle escape responses were quantified.

Results: Survival and growth were reduced, and hatching induced by exposure to a 1:1 mixture containing > 2 μg/L of each insecticide, but not following exposure to mixtures containing environmentally-relevant concentrations. Acute exposure to a 1:1 mixture did not alter embryonic motor activity; however, chronic exposure to these mixtures resulted in a slight but significant decrease in embryonic movements. Only 1:1 mixtures of high concentrations of IM and TM altered the startle escape response by increasing latency of response; however, a significant proportion of fish exposed to 1:1 mixtures had altered latency and burst speed. Taken together, these behavioral indicators of nAChR activation suggest that in mixtures, neonicotinoids could interfere with nAChR signaling despite their low affinity for the nAChR.

Conclusion: Our findings suggest that toxicity of binary mixtures of IM and TM is primarily driven by IM, and that mixtures of IM with TM do not appear to cause significant additive toxicity when compared with our previous studies evaluating each neonicotinoid alone. Given the limited toxicological data available for mixtures of neonicotinoid insecticides in fish, further study is required to better understand the ecological risks these insecticides may pose to aquatic ecosystems.
Modeling and Disturbance Analysis of Spinning Satellites with Inflatable Protective Structures
Authors: Shang Yuting , Deng Yifan , Cai Yuanli , Chen Yu , He Sirui , Liao Xuanchong , Jiang Haonan
Published: November 2023

The escalating proliferation of space debris poses an increasing risk to spinning satellites, elevating the probability of hazardous collisions that can result in severe damage or total loss of functionality. To address this concern, a pioneering inflatable protective structure is employed to ensure the optimal functionality of spinning satellites. Additionally, a multi-body dynamic modeling method based on spring hinge unfolding/spring expansion is proposed to tackle the complex dynamics of spinning satellites with inflatable protective structures during flight. This method enables analysis of the motion parameters of spinning satellites. First, the structural composition of a spinning satellite with inflatable protective structures is introduced and its flight process is analyzed. Then, an articulated spring hinge unfolding model or a spring expansion model using the Newton–Euler method is established to describe the unfolding or expansion of the spinning satellite with inflatable protective structures during flight. Finally, the effects on the motion parameters of a spinning satellite are analyzed through simulation under various working conditions.
Performance Analysis of Inter-Satellite and Satellite-Ground Communication: A Report on Flight Data for a Low Earth Orbit CubeSat
Authors: Limón-González Miguel , García-Sánchez Enrique Rafael , Vargas-Martínez Héctor Simón , Quiroz-Hernández Nicolás , Maya-Rueda Selene Edith
Published: November 2023

Communication between a nanosatellite located in Low Earth Orbit (LEO) and a ground station is limited in regions far from the poles, occurring for only a few minutes on different days and at different times. By utilizing satellite-to-satellite communication, it is possible to transmit and receive information more efficiently, circumventing the restrictions inherent in satellite-ground station links. The objective of this study is to present a comparative report on the results of data transmission through inter-satellite and satellite-to-ground station communication, focusing on a 1U CubeSat nanosatellite (AztechSat-1). This paper discusses the use of the GlobalStar network and a nanosatellite for inter-satellite communication. This paper also discusses the use of proprietary and open-source ground stations for satellite-ground communication. We provide an overview of the GlobalStar network and the associated ground stations involved in this research, along with the results and their subsequent analysis.
Effectiveness of Critical-Strain-Based Methodology Considering Elastic Mode Vibration of Mechanical Housing of Electronics
Authors: Park Jae-Hyeon , Jeong Seong-Keun , Oh Hyun-Ung
Published: November 2023

A critical-strain-based methodology was proposed to overcome the theoretical limitations of Steinberg’s method, and its effectiveness was experimentally verified through fatigue tests of ball grid arrays, column grid arrays, and lead-type specimens on printed circuit boards (PCBs) with various boundary conditions. These verifications were performed only on PCB units with a single electronic package mounted. However, in actual industrial fields, electronics with various types of electronic packages mounted comprehensively are mainly applied to electronics combined in a mechanical housing structure. Therefore, the verification of the corresponding methodology for the above actual conditions is essential. This study aimed to validate the theoretical feasibility of the design technique under the condition that the elastic mode vibration of a mechanical housing structure acts complexly on PCBs. The proposed methodology was validated analytically and experimentally through a vibration test on a comprehensive PCB specimen with various types of electronic packages mounted on electronic mechanical housing structures.
Analysis of Farm Data License Agreements: Do Data Agreements Adequately Reflect on Farm Data Practices and Farmers’ Data Rights?
Authors: Kaur Jasmin , Dara Rozita
Published: November 2023

Farm data license agreements are legal documents that play an important role in informing farmers about farm data processing practices such as collection, use, safeguarding, and sharing. These legal documents govern the exchange, access, and dissemination of farm data and are expected to provide legal protection against misuse of data. Despite their significant influence on farm data processing and governance, there is limited understanding of the content of farm data license agreements and standards for drafting them. Although online privacy policy content has been extensively studied, farm data agreements’ evaluation and analysis have been overlooked. This study aims to investigate the structure, content, and transparency of farm data licenses. We collected 141 agricultural terms of use agreements and used natural language processing methods such as keyword and keyphrase analysis to perform text feature analysis, Flesch Readability Ease Score and Flesch Grade Level readability analysis, transparency analysis, and content analysis to gain insight into common data practices adopted by the agriculture technology providers. We also manually reviewed these agreements to validate the results and strengthen the observations. The findings show that data agreements are long, complex, and difficult to read and comprehend. The results suggest that 95% of the agreements fall under the difficult-to-read category and close to 75% of the policies require university-level education to understand the content. Furthermore, it is noted that some of the data management practices are not given adequate attention and are not as frequently mentioned in the agreements as expected. Finally, our analysis enabled us to provide recommendations on the content of farm data license agreements and strategies to improve them.
What Do Cross-Range Germination, Growth, and Interaction Studies Reveal about the Behaviour of an Expansive Plant Species?
Authors: Kaushik Krishan , Pal Robert W. , Somfalvi-Tóth Katalin , Riyazuddin Riyazuddin , Rudolf Kinga , Morschhauser Tamás
Published: November 2023

Understanding the invasion potential of any plant species is crucial for early detection in habitat conservation, particularly when observing their expansion within their native region. As a test species, we utilised Allium ursinum L., a dominant clonal species in early spring forest floors. We compared the species’ germination capacity in native (Hungarian) and non-native (North American) soils, its seedling growth, and competing performances with two co-occurring dominant species, Melica uniflora Retz. and Carex pilosa Scop., in ten soil types and three soil compositions, respectively. Additionally, the competitive interactions of A. ursinum with Convallaria majalis L., a species already introduced in North America, were assessed under three moisture conditions. The results revealed that A. ursinum exhibited enhanced germination in non-native soils, while its shoot growth was most vigorous in control soil. When grown in soils with different co-dominant species, A. ursinum seedlings exhibited varying growth rates, significantly influenced by solar radiation intensity. A. ursinum shoots displayed superior growth in soil collected from C. pilosa stands compared to soil originating from its own stands. Notably, A. ursinum effectively competed against C. majalis in moderate soil moisture conditions. Furthermore, increasing sand content improved the competitive ability of A. ursinum against C. pilosa and M. uniflora. Based on our findings, A. ursinum possesses an invasion potential for particular North American habitats. However, the extent of its potential is dependent upon soil and climatic conditions. Under medium moisture regime, A. ursinum might outcompete the already established C. majalis from its habitats. Additionally, it can potentially displace native species with comparable ecological characteristics, such as C. pilosa and M. uniflora, especially in loose soils. Similar cross-range seed germination, growth, and paired competition experiments with potential competitor species are highly recommended as these can not only elucidate its native range expansion but also various growth scenarios for its agricultural cultivation.
Long-Term Maize Intercropping with Peanut and Phosphorus Application Maintains Sustainable Farmland Productivity by Improving Soil Aggregate Stability and P Availability
Authors: Zan Zhiman , Jiao Nianyuan , Ma Rentian , Wang Jiangtao , Wang Yun , Ning Tangyuan , Zheng Bin , Liu Ling , Zhao Xupeng , Cong Wenfeng
Published: November 2023

The intercropping of maize (Zea mays L.) and peanuts (Arachis hypogaea L.) (M||P) significantly enhances crop yield. In a long-term M||P field experiment with two P fertilizer levels, we examined how long-term M||P affects topsoil aggregate fractions and stability, organic carbon (SOC), available phosphorus (AP), and total phosphorus (TP) in each aggregate fraction, along with crop yields. Compared to their respective monocultures, long-term M||P substantially increased the proportion of topsoil mechanical macroaggregates (7.6–16.3%) and water-stable macroaggregates (>1 mm) (13.8–36.1%), while reducing the unstable aggregate index (ELT) and the percentage of aggregation destruction (PAD). M||P significantly boosted the concentration (12.9–39.9%) and contribution rate (4.1–47.9%) of SOC in macroaggregates compared to single crops. Moreover, the concentration of TP in macroaggregates (>1 mm) and AP in each aggregate fraction of M||P exceeded that of the respective single crops (p < 0.05). Furthermore, M||P significantly increased the Ca2-P, Ca8-P, Al-P, and Fe-P concentrations of intercropped maize (IM) and the Ca8-P, O-P, and Ca10-P concentrations of intercropped peanuts (IP). The land equivalent ratio (LER) of M||P was higher than one, and M||P stubble improved the yield of subsequent winter wheat (Triticum aestivum L.) compared with sole-crop maize stubble. P application augmented the concentration of SOC, TP, and AP in macroaggregates, resulting in improved crop yields. In conclusion, our findings suggest that long-term M||P combined with P application sustains farmland productivity in the North China Plain by increasing SOC and macroaggregate fractions, improving aggregate stability, and enhancing soil P availability.
Adaptability of Millets and Landscapes: Ancient Cultivation in North-Central Asia
Authors: Ventresca-Miller Alicia R. , Wilkin Shevan , Smithers Rachel , Larson Kara , Spengler Robert , Haruda Ashleigh , Kradin Nikolay , Bazarov Bilikto , Miyagashev Denis , Odbaatar Tserendorj , Turbat Tsagaan , Zhambaltarova Elena , Konovalov Prokopii , Bayarsaikhan Jamsranjav , Hein Anke , Hommel Peter , Nash Brendan , Nayak Ayushi , Vanwezer Nils , Miller Bryan , Fernandes Ricardo , Boivin Nicole , Roberts Patrick
Published: November 2023

Millet is a highly adaptable plant whose cultivation dramatically altered ancient economies in northern Asia. The adoption of millet is associated with increased subsistence reliability in semi-arid settings and perceived as a cultigen compatible with pastoralism. Here, we examine the pace of millet’s transmission and locales of adoption by compiling stable carbon isotope data from humans and fauna, then comparing them to environmental variables. The Bayesian modelling of isotope data allows for the assessment of changes in dietary intake over time and space. Our results suggest variability in the pace of adoption and intensification of millet production across northern Asia.
Soil Moisture Contribution to Winter Wheat Water Consumption from Different Soil Layers under Straw Returning
Authors: Wang Lishu , Zhou Xiaoxiang , Cui Yumiao , Zhou Ke , Zhu Changjun , Luan Qinghua
Published: November 2023

To study the contribution of moisture from different straw-treated and irrigated soil layers to the water consumption of winter wheat in dry farming, a 2-year straw treatment and regulated deficit irrigation experiment was implemented. The field experiment was carried out with 0% (S0), 1% (S1), and 2% (S2) straw returning amounts, and 75 mm (V3), 60 mm (V2), and 45 mm (V1) irrigation volumes. This experiment involved nine treatments, used to quantitatively analyze the ratio and variation of soil water use from different soil layers via the direct contrast method (DCM) and the multiple linear mixed model (MLMM). The results show the following: (1) The distribution of precipitation isotope compositions displayed a repeated trend of first decreasing and then increasing during the study period. Regression analysis showed that the local meteoric water line (LMWL): δD = 6.37δ18O − 3.77 (R2 = 0.832). (2) With increasing soil depth, the δ18O value decreased gradually, and the maximum δ18O value of the soil water within each growth period was distributed at 10 cm. (3) Under the same irrigation amount, δ 18O increased with increasing straw return at 0–20 cm and decreased with increasing straw return at 20–80 cm. (4) The comparison results of the DCM and MLMM were consistent. During the jointing and flowering stages, 0–30 cm soil water was the main source of water for winter wheat. The contribution of soil water below 30 cm had a decreasing trend from the jointing stage to the flowering stage. The average contribution rates of the 0–30 cm soil layer during the jointing and flowering stages were 23.07% and 23.15%, respectively. These findings have important implications for studying the soil water cycle in the context of farming.
Enhancing Tuta absoluta Detection on Tomato Plants: Ensemble Techniques and Deep Learning
Authors: Giakoumoglou Nikolaos , Pechlivani Eleftheria-Maria , Frangakis Nikolaos , Tzovaras Dimitrios
Published: November 2023

Early detection and efficient management practices to control Tuta absoluta (Meyrick) infestation is crucial for safeguarding tomato production yield and minimizing economic losses. This study investigates the detection of T. absoluta infestation on tomato plants using object detection models combined with ensemble techniques. Additionally, this study highlights the importance of utilizing a dataset captured in real settings in open-field and greenhouse environments to address the complexity of real-life challenges in object detection of plant health scenarios. The effectiveness of deep-learning-based models, including Faster R-CNN and RetinaNet, was evaluated in terms of detecting T. absoluta damage. The initial model evaluations revealed diminishing performance levels across various model configurations, including different backbones and heads. To enhance detection predictions and improve mean Average Precision (mAP) scores, ensemble techniques were applied such as Non-Maximum Suppression (NMS), Soft Non-Maximum Suppression (Soft NMS), Non-Maximum Weighted (NMW), and Weighted Boxes Fusion (WBF). The outcomes shown that the WBF technique significantly improved the mAP scores, resulting in a 20% improvement from 0.58 (max mAP from individual models) to 0.70. The results of this study contribute to the field of agricultural pest detection by emphasizing the potential of deep learning and ensemble techniques in improving the accuracy and reliability of object detection models.
Beyond Canine Adipose Tissue-Derived Mesenchymal Stem/Stromal Cells Transplantation: An Update on Their Secretome Characterization and Applications
Authors: Merlo Barbara , Iacono Eleonora
Published: November 2023

A dog is a valuable animal model and concomitantly a pet for which advanced therapies are increasingly in demand. The characteristics of mesenchymal stem/stromal cells (MSCs) have made cell therapy more clinically attractive. During the last decade, research on the MSC therapeutic effectiveness has demonstrated that tissue regeneration is primarily mediated by paracrine factors, which are included under the name of secretome. Secretome is a mixture of soluble factors and a variety of extracellular vesicles. The use of secretome for therapeutic purposes could have some advantages compared to cell-based therapies, such as lower immunogenicity and easy manufacturing, manipulation, and storage. The conditioned medium and extracellular vesicles derived from MSCs have the potential to be employed as new treatments in veterinary medicine. This review provides an update on the state-of-the-art characterization and applications of canine adipose tissue-derived MSC secretome.
Artificial Pasture Grazing System Attenuates Lipopolysaccharide-Induced Gut Barrier Dysfunction, Liver Inflammation, and Metabolic Syndrome by Activating ALP-Dependent Keap1-Nrf2 Pathway
Authors: Ali Qasim , Ma Sen , Liu Boshuai , Mustafa Ahsan , Wang Zhichang , Sun Hao , Cui Yalei , Li Defeng , Shi Yinghua
Published: November 2023

Introduction. Geese can naturally obtain dietary fiber from pasture, which has anti-inflammatory and antioxidant properties. This study aimed to investigate the inhibitory impacts of pasture on ameliorating LPS-ROS-induced gut barrier dysfunction and liver inflammation in geese. Materials and methods. The lipopolysaccharides (LPS), alkaline phosphatase (ALP), reactive oxygen species (ROS), tight junction proteins, antioxidant enzymes, immunoglobulins, and metabolic syndrome were determined using ELISA kits. The Kelch-like-ECH-associated protein 1-Nuclear factor erythroid 2-related factor 2 (Keap1-Nrf2) and inflammatory cytokines were determined using the quantitative reverse transcription PCR (RT-qPCR) method. The intestinal morphology was examined using the Hematoxylin and Eosin (H&E) staining method in ileal tissues. Results. Pasture significantly influences nutrient absorption (p < 0.001) by ameliorating LPS and ROS-facilitated ileal permeability (p < 0.05) and systemic inflammation (p < 0.01). Herein, the gut permeability was paralleled by liver inflammation, which was significantly mimicked by ALP-dependent Nrf2 (p < 0.0001) and antioxidant enzyme activation (p < 0.05). Indeed, the correlation analysis of host markers signifies the importance of pasture in augmenting geese’s health and production by averting gut and liver inflammation. Conclusions. Our results provide new insight into the mechanism of the pasture-induced ALP-dependent Nrf2 signaling pathway in limiting systemic inflammation in geese.
Phylogenetic Analyses of Lizards from the Chilean Humboldt Archipelago Reveal a New Species for the Chañaral Island (Squamata: Liolaemidae)
Authors: Campos-Soto Ricardo , Rodríguez-Valenzuela Evelyn , Bruna Yareta , Díaz-Campusano Gabriel , Cianferoni Franco , Boric-Bargetto Dusan , Torres-Pérez Fernando
Published: November 2023

The Humboldt Archipelago, situated on Chile’s north-central coast, is renowned for its exceptional biodiversity. However, lizards of the Liolaemus genus are a particularly understudied group in this archipelago. Liolaemus genus is divided into two clades: chiliensis and nigromaculatus. Within the nigromaculatus clade the zapallarensis group is restricted to the semi-arid and arid coastal habitats of the Atacama Desert in north-central Chile. While it has been reported that lizards from the zapallarensis group inhabit various islands within the Humboldt Archipelago, there has been limited knowledge regarding their specific species identification. To identify the lizard species inhabiting these islands, we conducted phylogenetic analyses using a mitochondrial gene and examined morphological characteristics. Our findings reveal that lizards from the Damas, Choros, and Gaviota islands belong to Liolaemus silvai. In contrast, the lizards on Chañaral Island form a distinct and previously unrecognised group, clearly distinguishable from Liolaemus silvai. In conclusion, our study not only confirms the presence of L. silvai on the Damas, Choros, and Gaviota islands but also describes a new lizard species on Chañaral Island named Liolaemus carezzae sp. nov. These findings contribute valuable insights into the biodiversity of these islands and introduce a newly discovered endemic taxon to the region, enriching our understanding of Chile’s unique island ecosystems.
Environmental Impacts of High-Quality Brazilian Beef Production: A Comparative Life Cycle Assessment of Premium and Super-Premium Beef
Authors: Morais Henrique Biasotto , Chardulo Luis Artur Loyola , Baldassini Welder Angelo , Lippi Isabella Cristina de Castro , Orsi Gabriela Belinassi , Ruviaro Clandio Favarini
Published: November 2023

When individual purchasing power increases in society, there is a trend toward a quantitative and qualitative increase in the consumption of products. Considering the magnitude of beef production in Brazil, environmental impacts are important factors for the domestic and international markets. This study assessed a Brazilian feedlot system characterized by high animal welfare standards that produces high-quality beef that is more marbled than that produced in grass-fed systems. We assessed the environmental impacts and compared premium and super-premium beef produced in a feedlot system using a partial Life Cycle Assessment (LCA). Data were collected directly on the property analyzed, considering environmental inputs and outputs and economic factors associated with the production stages of each line (premium versus super-premium). The results show that high-quality beef has, beyond a greater financial cost, an environmental cost, with the super-premium line producing a 286% higher carbon footprint, 297% more eutrophication, and three times higher acidification potential and land use than the premium line. The results of the environmental impacts agree with the results of production costs, reflecting a 282.82% higher production cost in super-premium than in premium animals. Footprints of 5.0323 kg, 4.7746 kg, and 8.8858 kg CO2 eq./kg live weight gain at the feedlot were found in the three lines.
Rapid Minimum Inhibitory Concentration (MIC) Analysis Using Lyophilized Reagent Beads in a Novel Multiphase, Single-Vessel Assay
Authors: Khire Tejas Suresh , Gao Wei , Bales Brian , Hsieh Kuangwen , Grossmann Greg , Park Dong Jin M. , O’Keefe Christine , Brown-Countess Arnyah , Peterson Sara , Chen Fan-En , Lenigk Ralf , Trick Alex , Wang Tza-Huei , Puleo Christopher
Published: November 2023

Antimicrobial resistance (AMR) is a global threat fueled by incorrect (and overuse) of antibiotic drugs, giving rise to the evolution of multi- and extreme drug-resistant bacterial strains. The longer time to antibiotic administration (TTA) associated with the gold standard bacterial culture method has been responsible for the empirical usage of antibiotics and is a key factor in the rise of AMR. While polymerase chain reaction (PCR) and other nucleic acid amplification methods are rapidly replacing traditional culture methods, their scope has been restricted mainly to detect genotypic determinants of resistance and provide little to no information on phenotypic susceptibility to antibiotics. The work presented here aims to provide phenotypic antimicrobial susceptibility testing (AST) information by pairing short growth periods (~3–4 h) with downstream PCR assays to ultimately predict minimum inhibitory concentration (MIC) values of antibiotic treatment. To further simplify the dual workflows of the AST and PCR assays, these reactions are carried out in a single-vessel format (PCR tube) using novel lyophilized reagent beads (LRBs), which store dried PCR reagents along with primers and enzymes, and antibiotic drugs separately. The two reactions are separated in space and time using a melting paraffin wax seal, thus eliminating the need to transfer reagents across different consumables and minimizing user interactions. Finally, these two-step single-vessel reactions are multiplexed by using a microfluidic manifold that allows simultaneous testing of an unknown bacterial sample against different antibiotics at varying concentrations. The LRBs used in the microfluidic system showed no interference with the bacterial growth and PCR assays and provided an innovative platform for rapid point-of-care diagnostics (POC-Dx).
Whole-Genome Sequencing Analysis of Non-Typhoidal Salmonella Isolated from Breeder Poultry Farm Sources in China, 2020–2021
Authors: Ju Zijing , Cui Lulu , Lei Changwei , Song Mengze , Chen Xuan , Liao Ziwei , Zhang Tiejun , Wang Hongning
Published: November 2023

Non-typhoidal salmonellosis is a dangerous foodborne disease that causes enormous economic loss and threatens public health worldwide. The consumption of food, especially poultry or poultry products, contaminated with non-typhoidal Salmonella (NTS) is the main cause of human salmonellosis. To date, no research has identified the molecular epidemiological characteristics of NTS strains isolated from breeder chicken farms in different provinces of China. In our study, we investigated the antimicrobial resistance, phylogenetic relationships, presence of antimicrobial resistance and virulence genes, and plasmids of NTS isolates recovered from breeder chicken farms in five provinces of China between 2020 and 2021 by using a whole-genome sequencing (WGS) approach and phenotypic methods. All sequenced isolates belonged to six serovars with seven sequence types. Nearly half of the isolates (44.87%) showed phenotypic resistance to at least three classes of antimicrobials. Salmonella enterica serotype Kentucky harbored more antimicrobial resistance genes than the others, which was highly consistent with phenotypic resistance. Furthermore, the carried rate of 104 out of 135 detected virulence genes was 100%. Overall, our WGS results highlight the need for the continuous monitoring of, and additional studies on, the antimicrobial resistance of NTS.
Stachys Species: Comparative Evaluation of Phenolic Profile and Antimicrobial and Antioxidant Potential
Authors: Benedec Daniela , Oniga Ilioara , Hanganu Daniela , Tiperciuc Brîndușa , Nistor Adriana , Vlase Ana-Maria , Vlase Laurian , Pușcaș Cristina , Duma Mihaela , Login Cristian Cezar , Niculae Mihaela , Silaghi-Dumitrescu Radu
Published: November 2023

This study aimed to investigate the polyphenolic composition and antioxidant and antimicrobial potential of six Romanian Stachys species: S. officinalis, S. germanica, S. byzantina, S. sylvatica, S. palustris, and S. recta. The LC-MS/MS method was used to analyze the polyphenolic profile, while the phenolic contents were spectrophotometrically determined. The antioxidant activity was evaluated using the following methods: DPPH, FRAP, nitrite-induced autooxidation of hemoglobin, inhibition of cytochrome c-catalyzed lipid peroxidation, and electron paramagnetic resonance spectroscopy. The in vitro antimicrobial properties were assessed using agar-well diffusion, broth microdilution, and antibiofilm assays. Fifteen polyphenols were identified using LC-MS and chlorogenic acid was the major component in all the samples (1131.8–6761.4 μg/g). S. germanica, S. palustris, and S. byzantina extracts each displayed an intense antiradical action in relation to high contents of TPC (6.40 mg GAE/mL), flavonoids (3.90 mg RE/mL), and caffeic acid derivatives (0.89 mg CAE/mL). In vitro antimicrobial and antibiofilm properties were exhibited towards Candida albicans, Gram-positive and Gram-negative strains, with the most intense efficacy recorded for S. germanica and S. byzantina when tested against S. aureus. These results highlighted Stachys extracts as rich sources of bioactive compounds with promising antioxidant and antimicrobial efficacies and important perspectives for developing phytopharmaceuticals.
An Effective Method for Detecting Unknown Types of Attacks Based on Log-Cosh Variational Autoencoder
Authors: Yu Li , Xu Liuquan , Jiang Xuefeng
Published: November 2023

The increasing prevalence of unknown-type attacks on the Internet highlights the importance of developing efficient intrusion detection systems. While machine learning-based techniques can detect unknown types of attacks, the need for innovative approaches becomes evident, as traditional methods may not be sufficient. In this research, we propose a deep learning-based solution called the log-cosh variational autoencoder (LVAE) to address this challenge. The LVAE inherits the strong modeling abilities of the variational autoencoder (VAE), enabling it to understand complex data distributions and generate reconstructed data. To better simulate discrete features of real attacks and generate unknown types of attacks, we introduce an effective reconstruction loss term utilizing the logarithmic hyperbolic cosine (log-cosh) function in the LVAE. Compared to conventional VAEs, the LVAE shows promising potential in generating data that closely resemble unknown attacks, which is a critical capability for improving the detection rate of unknown attacks. In order to classify the generated unknown data, we employed eight feature extraction and classification techniques. Numerous experiments were conducted using the latest CICIDS2017 dataset, training with varying amounts of real and unknown-type attacks. Our optimal experimental results surpassed several state-of-the-art techniques, achieving accuracy and average F1 scores of 99.89% and 99.83%, respectively. The suggested LVAE strategy also demonstrated outstanding performance in generating unknown attack data. Overall, our work establishes a solid foundation for accurately and efficiently identifying unknown types of attacks, contributing to the advancement of intrusion detection techniques.
Through the Forming Process of Femtosecond-Laser Nanotextured Sheets for Production of Complex 3D Parts
Authors: Mincuzzi Girolamo , Bourtereau Alexandra , Gemini Laura , Parareda Sergi , Rzepa Sylwia , Koukolíková Martina , Konopík Pavel , Kling Rainer
Published: November 2023

The use of ultra-short pulse lasers in the kW range, combined with an appropriate beam engineering approach, enables the achievement of high-throughput production of laser-functionalised surfaces. However, the manufacturing of complex parts still faces various challenges, such as difficulties in accessing regions with high aspect ratio shapes or intricate profiles, which often leads to the necessity of adapting the laser processing workstation to specific geometries. The forming process is a well-established technique for producing parts of any shape from metallic foils by imposing specific constraints. In this study, we aimed to assess the feasibility of producing laser-functionalised 3D complex products by the forming of laser-treated flat thin metallic sheets. Two-hundred micrometre-thick stainless-steel foils were textured with laser-induced periodic surface structures (LIPSS) through a roll-to-roll pilot line. First, we optimized the morphology of LIPSS. Subsequently, we conducted three types of mechanical tests on both laser-treated and untreated foils: standard tensile tests, fatigue tests, and cruciform specimen tests. We measured and compared parameters such as ultimate tensile strength, breaking strength, maximum elongation, and area reduction between specimens with and without LIPSS, all obtained from the same foil. Additionally, we utilized scanning electron microscopy (SEM) to compare the LIPSS morphology of laser-treated samples before and after mechanical tests.
Housing Experimentation and Design Guides: Affordable Housing in Guangzhou since 2006
Authors: Wang Lu , Jacoby Sam
Published: November 2023

This paper examines the recent growth of government-led affordable housing in Guangzhou, addressing a paucity of global housing studies that explore experimental and contextual policy approaches in China. It also addresses the lack of Chinese housing studies recognizing the impact of housing design governance, including regulatory controls and design standards, on housing preferences, supply and lifestyles. Since 1995, the supply of affordable housing has surged, now surpassing that of market housing for the first time. This response to failures in the private housing market and a lack of equitable access to housing signifies a significant shift, acknowledging the need to re-establish a state-led and long-term public housing supply after decades of housing marketization. Employing an architectural design research perspective, this paper investigates the interplay between affordable housing supply and the emergence of housing standards, examining resulting housing design outcomes. It poses the question: What changes in housing policy and interventions in housing markets are necessary to increase public rental housing supply, and how do these changes affect housing outcomes? The paper explores these questions through a discussion of the key moments in affordable housing policy and housing estate development in Guangzhou that facilitated the creation of widely accessible public housing and long-term housing assets. This provides new insights into China’s unique approach to translating central government social welfare and housing policy through contextual design experimentation and pilot housing projects, departing from the conventional top-down policy implementation found in most other countries.
Optimized Self-Similar Borel Summation
Authors: Gluzman Simon , Yukalov Vyacheslav I.
Published: November 2023

The method of Fractional Borel Summation is suggested in conjunction with self-similar factor approximants. The method used for extrapolating asymptotic expansions at small variables to large variables, including the variables tending to infinity, is described. The method is based on the combination of optimized perturbation theory, self-similar approximation theory, and Borel-type transformations. General Borel Fractional transformation of the original series is employed. The transformed series is resummed in order to adhere to the asymptotic power laws. The starting point is the formulation of dynamics in the approximations space by employing the notion of self-similarity. The flow in the approximation space is controlled, and “deep” control is incorporated into the definitions of the self-similar approximants. The class of self-similar approximations, satisfying, by design, the power law behavior, such as the use of self-similar factor approximants, is chosen for the reasons of transparency, explicitness, and convenience. A detailed comparison of different methods is performed on a rather large set of examples, employing self-similar factor approximants, self-similar iterated root approximants, as well as the approximation technique of self-similarly modified Padé–Borel approximations.
Enhancing the Super-Resolution of Medical Images: Introducing the Deep Residual Feature Distillation Channel Attention Network for Optimized Performance and Efficiency
Authors: Umirzakova Sabina , Mardieva Sevara , Muksimova Shakhnoza , Ahmad Shabir , Whangbo Taegkeun
Published: November 2023

In the advancement of medical image super-resolution (SR), the Deep Residual Feature Distillation Channel Attention Network (DRFDCAN) marks a significant step forward. This work presents DRFDCAN, a model that innovates traditional SR approaches by introducing a channel attention block that is tailored for high-frequency features—crucial for the nuanced details in medical diagnostics—while streamlining the network structure for enhanced computational efficiency. DRFDCAN’s architecture adopts a residual-within-residual design to facilitate faster inference and reduce memory demands without compromising the integrity of the image reconstruction. This design strategy, combined with an innovative feature extraction method that emphasizes the utility of the initial layer features, allows for improved image clarity and is particularly effective in optimizing the peak signal-to-noise ratio (PSNR). The proposed work redefines efficiency in SR models, outperforming established frameworks like RFDN by improving model compactness and accelerating inference. The meticulous crafting of a feature extractor that effectively captures edge and texture information exemplifies the model’s capacity to render detailed images, necessary for accurate medical analysis. The implications of this study are two-fold: it presents a viable solution for deploying SR technology in real-time medical applications, and it sets a precedent for future models that address the delicate balance between computational efficiency and high-fidelity image reconstruction. This balance is paramount in medical applications where the clarity of images can significantly influence diagnostic outcomes. The DRFDCAN model thus stands as a transformative contribution to the field of medical image super-resolution.
Diagnostic Validation of the Screening Corneal Objective Risk of Ectasia Analyzer Evaluated by Swept Source Optical Coherence Tomography for Keratoconus in an Asian Population
Authors: Kim Kookyoung , Koh Kyungmin , Lee Seongjun , Lee Yongwoo
Published: November 2023

We aimed to investigate the diagnostic accuracy of Screening Corneal Objective Risk of Ectasia (SCORE) Analyzer software using ANTERION, a swept-source optical coherence tomography device, for keratoconus diagnosis in an Asian population. A total of 151 eyes of 151 patients were included in this retrospective study as follows: 60, 45, and 46 keratoconus, keratoconus suspects, and normal control eyes, respectively. Parameters in the SCORE calculation, including six indices, were compared for the three groups. The receiver operating characteristic curve analysis and cut-off value were estimated to assess the diagnostic ability to differentiate keratoconus and keratoconus suspect eyes from the normal group. The SCORE value and six indices were significantly correlated—“AntK max” (R = 0.864), “AntK oppoK” (R = 0.866), “Ant inf supK” (R = 0.943), “Ant irre 3mm” (R = 0.741), “post elevation at the thinnest point” (R = 0.943), and “minimum corneal thickness” (R = −0.750). The SCORE value showed high explanatory power (98.1%), sensitivity of 81.9%, and specificity of 78.3% (cut-off value: 0.25) in diagnosing normal eyes from the keratoconus suspect and keratoconus eyes. The SCORE Analyzer was found to be valid and consistent, showing good sensitivity and specificity for keratoconus detection in an Asian population.
The Growth-Inhibitory Effect of Increased Planting Density Can Be Reduced by Abscisic Acid-Degrading Bacteria
Authors: Vysotskaya Lidiya , Martynenko Elena , Ryabova Alena , Kuzmina Ludmila , Starikov Sergey , Chetverikov Sergey , Gaffarova Elvina , Kudoyarova Guzel
Published: November 2023

High-density planting can increase crop productivity per unit area of cultivated land. However, the application of this technology is limited by the inhibition of plant growth in the presence of neighbors, which is not only due to their competition for resources but is also caused by growth regulators. Specifically, the abscisic acid (ABA) accumulated in plants under increased density of planting has been shown to inhibit their growth. The goal of the present study was to test the hypothesis that bacteria capable of degrading ABA can reduce the growth inhibitory effect of competition among plants by reducing concentration of this hormone in plants and their environment. Lettuce plants were grown both individually and three per pot; the rhizosphere was inoculated with a strain of Pseudomonas plecoglossicida 2.4-D capable of degrading ABA. Plant growth was recorded in parallel with immunoassaying ABA concentration in the pots and plants. The presence of neighbors indeed inhibited the growth of non-inoculated lettuce plants. Bacterial inoculation positively affected the growth of grouped plants, reducing the negative effects of competition. The bacteria-induced increase in the mass of competing plants was greater than that in the single ones. ABA concentration was increased by the presence of neighbors both in soil and plant shoots associated with the inhibition of plant growth, but accumulation of this hormone as well as inhibition of the growth of grouped plants was prevented by bacteria. The results confirm the role of ABA in the response of plants to the presence of competitors as well as the possibility of reducing the negative effect of competition on plant productivity with the help of bacteria capable of degrading this hormone.
Selection of Mexican Medicinal Plants by Identification of Potential Phytochemicals with Anti-Aging, Anti-Inflammatory, and Anti-Oxidant Properties through Network Analysis and Chemoinformatic Screening
Authors: Barrera-Vázquez Oscar Salvador , Montenegro-Herrera Sergio Andrés , Martínez-Enríquez María Elena , Escobar-Ramírez Juan Luis , Magos-Guerrero Gil Alfonso
Published: November 2023

Many natural products have been acquired from plants for their helpful properties. Medicinal plants are used for treating a variety of pathologies or symptoms. The axes of many pathological processes are inflammation, oxidative stress, and senescence. This work is focused on identifying Mexican medicinal plants with potential anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects through network analysis and chemoinformatic screening of their phytochemicals. We used computational methods to analyze drug-like phytochemicals in Mexican medicinal plants, multi-target compounds, and signaling pathways related to anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence mechanisms. A total of 1373 phytochemicals are found in 1025 Mexican medicinal plants, and 148 compounds showed no harmful functionalities. These compounds displayed comparable structures with reference molecules. Based on their capacity to interact with pharmacological targets, three clusters of Mexican medicinal plants have been established. Curatella americana, Ximenia americana, Malvastrum coromandelianum, and Manilkara zapota all have anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects. Plumeria rubra, Lonchocarpus yucatanensis, and Salvia polystachya contained phytochemicals with anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence reported activity. Lonchocarpus guatemalensis, Vallesia glabra, Erythrina oaxacana, and Erythrina sousae have drug-like phytochemicals with potential anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects. Between the drug-like phytochemicals, lonchocarpin, vallesine, and erysotrine exhibit potential anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects. For the first time, we conducted an initial virtual screening of selected Mexican medicinal plants, which was subsequently confirmed in vivo, evaluating the anti-inflammatory activity of Lonchocarpus guatemalensis Benth in mice.