bluuebunny/crossref_metadata_2025 huggingface dataset:
Gluing GAP to RAS Mutants: A New Approach to an Old Problem in Cancer Drug Development
Authors: Ranđelović Ivan , Nyíri Kinga , Koppány Gergely , Baranyi Marcell , Tóvári József , Kigyós Attila , Tímár József , Vértessy Beáta G. , Grolmusz Vince
Published: February 2024

Mutated genes may lead to cancer development in numerous tissues. While more than 600 cancer-causing genes are known today, some of the most widespread mutations are connected to the RAS gene; RAS mutations are found in approximately 25% of all human tumors. Specifically, KRAS mutations are involved in the three most lethal cancers in the U.S., namely pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and lung adenocarcinoma. These cancers are among the most difficult to treat, and they are frequently excluded from chemotherapeutic attacks as hopeless cases. The mutated KRAS proteins have specific three-dimensional conformations, which perturb functional interaction with the GAP protein on the GAP–RAS complex surface, leading to a signaling cascade and uncontrolled cell growth. Here, we describe a gluing docking method for finding small molecules that bind to both the GAP and the mutated KRAS molecules. These small molecules glue together the GAP and the mutated KRAS molecules and may serve as new cancer drugs for the most lethal, most difficult-to-treat, carcinomas. As a proof of concept, we identify two new, drug-like small molecules with the new method; these compounds specifically inhibit the growth of the PANC-1 cell line with KRAS mutation G12D in vitro and in vivo. Importantly, the two new compounds show significantly lower IC50 and higher specificity against the G12D KRAS mutant human pancreatic cancer cell line PANC-1, as compared to the recently described selective G12D KRAS inhibitor MRTX-1133.
Miniature Ultrasound Transducer Incorporating Sm-PMN-PT 1-3 Composite
Authors: Zhang Jia-Ming , Bao Guo-Cui , Gao Wen , Lin Ri-Qiang , Yang Fan , Lam Kwok-Ho
Published: February 2024

Piezoelectric 1-3 composite materials have become extensively utilized in diagnostic ultrasound transducers owing to their high electromechanical coupling coefficient, low acoustic impedance, and low dielectric loss. In this study, Sm-doped PMN-PT ceramic/epoxy 1-3 composite with a ceramic volume fraction of 60% is fabricated by the dice-and-fill method, resulting in a high piezoelectric constant (650 pC/N) and clamped dielectric constant (2350). Utilizing the exceptionally high clamped dielectric constant, a low-frequency (12.4 MHz) ultrasound transducer is developed with a miniature aperture size (0.84 mm × 0.84 mm), exhibiting a −6 dB bandwidth of 70% and an insertion loss of −20.5 dB. The imaging capability of the miniature composite transducer is validated through both phantom and ex vivo imaging. The satisfactory results indicate that Sm-doped ceramic/epoxy composites possess significant potential for miniature devices in biomedical imaging applications.
Diversity of Rock-Inhabiting Fungi in Tarragona Province, Spain
Authors: Sastoque Angie Paola , Cano-Lira José Francisco , Stchigel Alberto Miguel
Published: February 2024

Rock-inhabiting fungi (RIF) are usually extremely tolerant or extremophilic, as they can survive on natural and artificial rocks despite being exposed to stressful conditions. RIF have serious negative effects on the appearance and cohesion of rocky substrates, causing the alteration and decomposition of building materials, but also on human and animal health, as they can act as opportunistic pathogens. Their identification is therefore of great importance, especially in urban areas. In the present study, culturing techniques for isolating fungi, and a polyphasic taxonomic approach to their identification, were used to assess the diversity of micromycetes that darken the surfaces of buildings in various villages and cities in Tarragona Province (Spain). Sixty-four species of RIF belonging to forty-one genera were identified, including a new genus (Coccodomyces) and the following six new fungal species: Coccodomyces pleiosporus, Exophiala caementiphila, Exophiala multiformis, Neocatenulostroma spinulosum, Neodevriesia longicatenispora, and Paradevriesia holothallica. Thus, we have established that building materials are ecological niches where a high biodiversity of RIF can develop.
The Value of Reentry Housing, Zoning, and “Not in My Back Yard” (NIMBY) Obstacles, and How to Overcome Them
Authors: García Ivis
Published: February 2024

Given the housing issues that people who have been in prison face, this article examines the permitting process to operate a vocational and life skills training program for the formerly incarcerated in Salt Lake City, UT, called The Other Side Academy (TOSA). This article employs participant observation, personal and public meeting conversations, planning division staff reports, public comments, and newspaper articles to answer the following question: How was TOSA described in the public input process for a conditional use permit? The author examines how TOSA neighbors first opposed the project and then came to support it. But even with community support, planning staff struggled to find a zoning code that would allow TOSA operations. In the end, the final decision to approve the conditional use permit came to the hearing officer, who sided in favor of TOSA. In this case, planners can learn about the zoning obstacles that reentry housing faces and how those obstacles can be overcome. Finally, academia and planning divisions need to better educate planners involved in administrative process into understanding the intent of the code to achieve just outcomes.
Discounting the Distant Future: What Do Historical Bond Prices Imply about the Long-Term Discount Rate?
Authors: Farmer J. Doyne , Geanakoplos John , Richiardi Matteo G. , Montero Miquel , Perelló Josep , Masoliver Jaume
Published: February 2024

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. From the viewpoint of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long-term discount rate to estimate the rate when taking historical US and UK data, and to further contribute to the discussion about the urgency of climate action in the context of environmental economics and stochastic methods. Century-long historical records of 3-month bonds, 10-year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond-pricing models, which are designed for nominal rates that are assumed to be positive. We, therefore, use the Ornstein–Uhlenbeck model, which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long-term discount rate is 1.7% for the UK and 2.2% for the US. The value of 1.4% used by Stern is less than a standard deviation from our estimated long-run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the need for immediate and substantial spending to combat climate change.
The Peptide LLTRAGL Derived from Rapana venosa Exerts Protective Effect against Inflammatory Bowel Disease in Zebrafish Model by Regulating Multi-Pathways
Authors: Cao Yongna , Xu Fenghua , Xia Qing , Liu Kechun , Lin Houwen , Zhang Shanshan , Zhang Yun
Published: February 2024

Inflammatory bowel disease (IBD) is a chronic inflammatory bowel disease with unknown pathogenesis which has been gradually considered a public health challenge worldwide. Peptides derived from Rapana venosa have been shown to have an anti-inflammatory effect. In this study, peptide LLTRAGL derived from Rapana venosa was prepared by a solid phase synthesis technique. The protective effects of LLTRAGL were studied in a 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced zebrafish colitis model. The underlying mechanisms of LLTRAGL were predicted and validated by transcriptome, real-time quantitative PCR assays and molecular docking. The results showed that LLTRAGL reduced the number of macrophages migrating to the intestine, enhanced the frequency and rate of intestinal peristalsis and improved intestinal inflammatory damage. Furthermore, transcriptome analysis indicated the key pathways (NOD-like receptor signal pathway and necroptosis pathway) that link the underlying protective effects of LLTRAGL’s molecular mechanisms. In addition, the related genes in these pathways exhibited different expressions after TNBS treatment. Finally, molecular docking techniques further verified the RNA-sequencing results. In summary, LLTRAGL exerted protective effects in the model of TNBS-induced colitis zebrafish. Our findings provide valuable information for the future application of LLTRAGL in IBD.
Divergent Fungal Community Dynamics of Thuja sutchuenensis in Arid Environments
Authors: Zuo Youwei , Yang Lingxiang , Wang Qian , Zhu Benchao , Xia Changying , Zhang Huan , Li Wenqiao , Zhang Zhe , Deng Hongping
Published: February 2024

Thuja sutchuenensis Franch., an endangered species sparsely distributed in the mountainous and arid regions of southwest China, faces the critical challenge of adapting to these harsh conditions. Understanding the plant’s strategies for survival and the precise roles played by soil fungal communities in this adaptation remains an area of limited knowledge. Our investigation centers on the fungal communities associated with T. sutchuenensis and their interactions with soil water content. Notably, we identified unique fungal communities in the low soil moisture group, and these communities exhibited lower coverage but higher phylogenetic diversity (PD), Chao1, and Shannon indices compared to other groups. Network analysis revealed a modular structure within the fungal communities, with key hub nodes identified, particularly in the arid group. This group demonstrated higher levels of soil saprotrophs and ectomycorrhizal fungi and a reduced presence of plant pathogens. Linear discriminant analysis highlighted the significance of genera such as Russula, Myxotrichaceae, and Sebacina, emphasizing their roles in supporting the plant in arid environments. Random forest analysis indicated that soil moisture content emerged as the primary driver in determining fungal composition and diversity and contributed to the variables of several fungal genera. Collectively, this study provides valuable insights into the fungal communities associated with T. sutchuenensis, shedding light on their adaptation to extreme arid conditions.
Demethyleneberberine Alleviates Pulmonary Fibrosis through Disruption of USP11 Deubiquitinating GREM1
Authors: Ge Chuang , Huang Mengsheng , Han Yanhong , Shou Chang , Li Dongyin , Zhang Yubin
Published: February 2024

Background: Idiopathic pulmonary fibrosis (IPF) is a fatal and chronic interstitial lung disease. Intricate pathogenesis of pulmonary fibrosis and only two approved medications with side effects and high cost bring us the challenge of fully understanding this lethal disease and urgency to find more safe and low-cost therapeutic alternatives. Purpose: Demethyleneberberine (DMB) has been demonstrated to have various anti-inflammatory, antioxidant, antifibrosis and anti-cancer bioactivities. The objective of this study was to evaluate the effect of DMB on pulmonary fibrosis and investigate the mechanism. Methods: Bleomycin (BLM)-induced pulmonary fibrosis was established in mice to evaluate the antifibrotic effect of DMB in vivo. A549 and MRC5 cells were used to evaluate the effect of DMB on epithelial–mesenchymal transition (EMT) and fibroblast–myofibroblast transition (FMT) in vitro. High throughput sequencing, biotin–avidin system and site-directed mutagenesis were applied to explore the mechanism of DMB in alleviating pulmonary fibrosis. Results: DMB alleviated BLM-induced pulmonary fibrosis in vivo by improving the survival state of mice, significantly reducing pulmonary collagen deposition and oxidative stress and improving lung tissue morphology. Meanwhile, DMB was demonstrated to inhibit epithelial–mesenchymal transition (EMT) and fibroblast–myofibroblast transition (FMT) in vitro. High throughput sequencing analysis indicated that GREM1, a highly upregulated profibrotic mediator in IPF and BLM-induced pulmonary fibrosis, was significantly downregulated by DMB. Furthermore, USP11 was revealed to be involved in the deubiquitination of GREM1 in this study and DMB promoted the ubiquitination and degradation of GREM1 by inhibiting USP11. Remarkably, DMB was demonstrated to selectively bind to the Met776 residue of USP11, leading to disruption of USP11 deubiquitinating GREM1. In addition, DMB presented an equivalent antifibrotic effect at a lower dose compared with pirfenidone and showed no obvious toxicity or side effects. Conclusions: This study revealed that USP11/GREM1 could be a potential target for IPF management and identified that DMB could promote GREM1 degradation by inhibiting USP11, thereby alleviating pulmonary fibrosis.
When Unsuspected Crystallinity Ruins Biological Testing in Early Discovery: A Case Study
Authors: de Rocafiguera Claudi , Belsa Blanca , Font-Bardia Mercè , Puigjaner Cristina , Serra Eduard , Cuartero-Albesa Ana M. , Puig de la Bellacasa Raimon , Borrell José I.
Published: February 2024

The impact of the crystalline or amorphous structure of a solid on the solubility and pharmacokinetic properties of a drug candidate is always considered by the pharmaceutical industry during the development of a new drug; however, it is not so frequently considered during the early drug discovery process by organic and medicinal chemists, particularly those working in academia. We want to share, as an example, the false negative obtained in the biological testing of a solid sample of a tyrosine kinase inhibitor due to its unexpected crystallinity and lower solubility with respect to a solid amorphous batch of the same compound and the experimentation carried out to establish the origin of such a discrepancy.
Preparation of PVA/SA-FMB Microspheres and Their Adsorption of Cr(VI) in Aqueous Solution
Authors: Zuo Jinlong , Ren Jin , Jiang Liming , Tan Chong , Li Junsheng , Xia Zhi , Wang Wei
Published: February 2024

Biochar, a carbon-dense material known for its substantial specific surface area, remarkable porosity, diversity of functional groups, and cost-effective production, has garnered widespread acclaim as a premier adsorbent for the elimination of heavy metal ions and organic contaminants. Nevertheless, the application of powdered biochar is hindered by the challenges associated with its separation from aqueous solutions, and without appropriate management, it risks becoming hazardous waste. To facilitate its use as an immobilization medium, biochar necessitates modification. In this investigation, sodium alginate, celebrated for its superior gelation capabilities, was amalgamated with polyvinyl alcohol to bolster mechanical robustness, thereby embedding biochar to formulate sodium alginate biochar microspheres (PVA/SA-FMB). A meticulously designed response surface methodology experiment was employed to ascertain the optimal synthesis conditions for PVA/SA-FMB. Characterization outcomes unveiled a highly developed surface abundant in functional groups and confirmed the successful incorporation of iron ions. Adsorption trials revealed that at a temperature of 25 °C and a pH of 2, the adsorption capacity of PVA/SA-FMB for Cr(VI) was 13.7 mg/g within the initial 30 min, reaching an equilibrium capacity of 26.03 mg/g after 1440 min. Notably, the material sustained a Cr(VI) removal efficiency exceeding 90% across five cycles, underscoring its rapid and effective Cr(VI) eradication performance. Kinetic and isothermal adsorption analyses suggested that the adsorption of Cr(VI) adheres to a pseudo-second-order kinetic model and the Freundlich isotherm, indicative of monolayer adsorption dominated by reaction mechanisms. X-ray photoelectron spectroscopy (XPS) analysis inferred that the adsorption mechanism predominantly encompasses electrostatic attraction, redox processes, and complex formation.
A Numerical Study on the Process of the H2 Shaft Furnace Equipped with a Center Gas Distributor
Authors: Yu Shan , Shao Lei , Zou Zongshu
Published: February 2024

In order to explore technically feasible options for improving the performance of the H2 shaft furnace (HSF), a previously built and validated computational fluid dynamics (CFD) model was employed in the current work to assess the potential of the operation based on a center gas distributor (CGD). A set of simulations was performed to mimic scenarios where different amounts of feed gas (0–30% of 1400 Nm3/t-pellet) are injected via the CGD located at the bottom of the HSF. The results showed that a relatively large stagnant zone (approximately 8.0-m in height and 0.3-m in diameter) exists in the furnace center where the gas flows are weak owing to an overly shortened penetration depth of the H2 stream solely injected from the circumferentially installed bustle-pipe. When adopting the CGD operation, however, the center gas flows can be effectively enhanced, consequently squeezing the stagnant zone and thus leading to a better overall performance of the HSF. In particular, the uniformity of the final reduction degree (mean values ranging from 0.8846 to 0.8896) of the solid phase (i.e., pellets) is well improved under the investigated condition where the total gas feed rate is fixed at 1400 Nm3/t-pellet. As for the final mean reduction degree of solid and top gas utilization degree, the two performance indicators rise to maximal values when the CGD feed ratio is increased to 20% and then slightly drop with a further increase in the ratio.
A Transfer Learning-Enhanced Generative Adversarial Network for Downscaling Sea Surface Height through Heterogeneous Data Fusion
Authors: Zhang Qi , Sun Wenjin , Guo Huaihai , Dong Changming , Zheng Hong
Published: February 2024

In recent decades, satellites have played a pivotal role in observing ocean dynamics, providing diverse datasets with varying spatial resolutions. Notably, within these datasets, sea surface height (SSH) data typically exhibit low resolution, while sea surface temperature (SST) data have significantly higher resolution. This study introduces a Transfer Learning-enhanced Generative Adversarial Network (TLGAN) for reconstructing high-resolution SSH fields through the fusion of heterogeneous SST data. In contrast to alternative deep learning approaches that involve directly stacking SSH and SST data as input channels in neural networks, our methodology utilizes bifurcated blocks comprising Residual Dense Module and Residual Feature Distillation Module to extract features from SSH and SST data, respectively. A pixelshuffle module-based upscaling block is then concatenated to map these features into a common latent space. Employing a hybrid strategy involving adversarial training and transfer learning, we overcome the limitation that SST and SSH data should share the same time dimension and achieve significant resolution enhancement in SSH reconstruction. Experimental results demonstrate that, when compared to interpolation method, TLGAN effectively reduces reconstruction errors and fusing SST data could significantly enhance in generating more realistic and physically plausible results.
Urban Green Connectivity Assessment: A Comparative Study of Datasets in European Cities
Authors: Aleixo Cristiana , Branquinho Cristina , Laanisto Lauri , Tryjanowski Piotr , Niinemets Ülo , Moretti Marco , Samson Roeland , Pinho Pedro
Published: February 2024

Urban biodiversity and ecosystem services depend on the quality, quantity, and connectivity of urban green areas (UGAs), which are crucial for enhancing urban livability and resilience. However, assessing these connectivity metrics in urban landscapes often suffers from outdated land cover classifications and insufficient spatial resolution. Spectral data from Earth Observation, though promising, remains underutilized in analyzing UGAs’ connectivity. This study tests the impact of dataset choices on UGAs’ connectivity assessment, comparing land cover classification (Urban Atlas) and spectral data (Normalized Difference Vegetation Index, NDVI). Conducted in seven European cities, the analysis included 219 UGAs of varying sizes and connectivity levels, using three connectivity metrics (size, proximity index, and surrounding green area) at different spatial scales. The results showed substantial disparities in connectivity metrics, especially at finer scales and shorter distances. These differences are more pronounced in cities with contiguous UGAs, where Urban Atlas faces challenges related to typology issues and minimum mapping units. Overall, spectral data provides a more comprehensive and standardized evaluation of UGAs’ connectivity, reducing reliance on local typology classifications. Consequently, we advocate for integrating spectral data into UGAs’ connectivity analysis to advance urban biodiversity and ecosystem services research. This integration offers a comprehensive and standardized framework for guiding urban planning and management practices.
Attention Mechanism and LSTM Network for Fingerprint-Based Indoor Location System
Authors: Wu Zhen , Hu Peng , Liu Shuangyue , Pang Tao
Published: February 2024

The demand for precise indoor localization services is steadily increasing. Among various methods, fingerprint-based indoor localization has become a popular choice due to its exceptional accuracy, cost-effectiveness, and ease of implementation. However, its performance degrades significantly as a result of multipath signal attenuation and environmental changes. In this paper, we propose an indoor localization method based on fingerprints using self-attention and long short-term memory (LSTM). By integrating a self-attention mechanism and LSTM network, the proposed method exhibits outstanding positioning accuracy and robustness in diverse experimental environments. The performance of the proposed method is evaluated under two different experimental scenarios, which involve 2D and 3D moving trajectories, respectively. The experimental results demonstrate that our approach achieves an average localization error of 1.76 m and 2.83 m in the respective scenarios, outperforming the existing state-of-the-art methods by 42.67% and 31.64%.
Acceleration of Hyperspectral Skin Cancer Image Classification through Parallel Machine-Learning Methods
Authors: Petracchi Bernardo , Torti Emanuele , Marenzi Elisa , Leporati Francesco
Published: February 2024

Hyperspectral imaging (HSI) has become a very compelling technique in different scientific areas; indeed, many researchers use it in the fields of remote sensing, agriculture, forensics, and medicine. In the latter, HSI plays a crucial role as a diagnostic support and for surgery guidance. However, the computational effort in elaborating hyperspectral data is not trivial. Furthermore, the demand for detecting diseases in a short time is undeniable. In this paper, we take up this challenge by parallelizing three machine-learning methods among those that are the most intensively used: Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGB) algorithms using the Compute Unified Device Architecture (CUDA) to accelerate the classification of hyperspectral skin cancer images. They all showed a good performance in HS image classification, in particular when the size of the dataset is limited, as demonstrated in the literature. We illustrate the parallelization techniques adopted for each approach, highlighting the suitability of Graphical Processing Units (GPUs) to this aim. Experimental results show that parallel SVM and XGB algorithms significantly improve the classification times in comparison with their serial counterparts.
Editorial for the Special Issue “Sensing-Based Biomedical Communication and Intelligent Identification for Healthcare”
Authors: Jia Wenyan , Gao Yi , Mao Zhi-Hong , Sun Mingui
Published: February 2024

The integration of sensor technology in healthcare has become crucial for disease diagnosis and treatment [...]
Faces in Event Streams (FES): An Annotated Face Dataset for Event Cameras
Authors: Bissarinova Ulzhan , Rakhimzhanova Tomiris , Kenzhebalin Daulet , Varol Huseyin Atakan
Published: February 2024

The use of event-based cameras in computer vision is a growing research direction. However, despite the existing research on face detection using the event camera, a substantial gap persists in the availability of a large dataset featuring annotations for faces and facial landmarks on event streams, thus hampering the development of applications in this direction. In this work, we address this issue by publishing the first large and varied dataset (Faces in Event Streams) with a duration of 689 min for face and facial landmark detection in direct event-based camera outputs. In addition, this article presents 12 models trained on our dataset to predict bounding box and facial landmark coordinates with an mAP50 score of more than 90%. We also performed a demonstration of real-time detection with an event-based camera using our models.
Novel Machine Learning Approach for DDoS Cloud Detection: Bayesian-Based CNN and Data Fusion Enhancements
Authors: AlSaleh Ibtihal , Al-Samawi Aida , Nissirat Liyth
Published: February 2024

Cloud computing has revolutionized the information technology landscape, offering businesses the flexibility to adapt to diverse business models without the need for costly on-site servers and network infrastructure. A recent survey reveals that 95% of enterprises have already embraced cloud technology, with 79% of their workloads migrating to cloud environments. However, the deployment of cloud technology introduces significant cybersecurity risks, including network security vulnerabilities, data access control challenges, and the ever-looming threat of cyber-attacks such as Distributed Denial of Service (DDoS) attacks, which pose substantial risks to both cloud and network security. While Intrusion Detection Systems (IDS) have traditionally been employed for DDoS attack detection, prior studies have been constrained by various limitations. In response to these challenges, we present an innovative machine learning approach for DDoS cloud detection, known as the Bayesian-based Convolutional Neural Network (BaysCNN) model. Leveraging the CICDDoS2019 dataset, which encompasses 88 features, we employ Principal Component Analysis (PCA) for dimensionality reduction. Our BaysCNN model comprises 19 layers of analysis, forming the basis for training and validation. Our experimental findings conclusively demonstrate that the BaysCNN model significantly enhances the accuracy of DDoS cloud detection, achieving an impressive average accuracy rate of 99.66% across 13 multi-class attacks. To further elevate the model’s performance, we introduce the Data Fusion BaysFusCNN approach, encompassing 27 layers. By leveraging Bayesian methods to estimate uncertainties and integrating features from multiple sources, this approach attains an even higher average accuracy of 99.79% across the same 13 multi-class attacks. Our proposed methodology not only offers valuable insights for the development of robust machine learning-based intrusion detection systems but also enhances the reliability and scalability of IDS in cloud computing environments. This empowers organizations to proactively mitigate security risks and fortify their defenses against malicious cyber-attacks.
Soil Fauna and Ecosystem Services in Agroecological Cropping Systems: Focus on Experimental Open-Field Market Gardens
Authors: Moulin-Rouyard Coraline , Vaillant Victor , Angeon Valérie , Diman Jean-Louis , Vaillant Jean , Loranger-Merciris Gladys
Published: February 2024

Agroecological practices can be used to optimise ecological functions and improve the health of agroecosystems. The present study aimed to determine the effects of two agroecological systems (AG and AGSPP) on soil biodiversity and ecosystem services in tropical market gardens. The AG (agroecological) cropping system allows the use of organic phytosanitary products, unlike the second one (AGSPP, agroecological without phytosanitary products). The cropping systems were established in the open field and compared in terms of (i) soil fauna, (ii) soil fertility, (iii) soil aggregation, (iv) pest regulation, and (v) crop production. A total of eighteen months after the establishment of the experiment, the macrofaunal communities of the two cropping systems were significantly different. The AGSPP cropping system was characterised by a higher abundance of predators, a better soil structure, a higher tomato fruit set rate, and a lower pest proliferation. The increase in plant diversity and the non-use of phytosanitary products could modify the macrofaunal communities and, consequently, the provision of some ecosystem services. We also observed an effect of repellent and host plants on pest control in both systems, promoting high crop production. Overall, we showed that small changes in agroecological practices can have positive effects on soil biodiversity, pest regulation, and crop production.
The Effectiveness of Protection and Surveillance Zones in Detecting Further African Swine Fever Outbreaks in Domestic Pigs—Experience of the Baltic States
Authors: Lamberga Kristīne , Viltrop Arvo , Nurmoja Imbi , Masiulis Marius , Bušauskas Paulius , Oļševskis Edvīns , Seržants Mārtiņš , Laddomada Alberto , Ardelean Felix , Depner Klaus
Published: February 2024

In the event of an outbreak of African swine fever (ASF) in pig farms, the European Union (EU) legislation requires the establishment of a restricted zone, consisting of a protection zone with a radius of at least 3 km and a surveillance zone with a radius of at least 10 km around the outbreak. The main purpose of the restricted zone is to stop the spread of the disease by detecting further outbreaks. We evaluated the effectiveness and necessity of the restricted zone in the Baltic States by looking at how many secondary outbreaks were detected inside and outside the protection and surveillance zones and by what means. Secondary outbreaks are outbreaks with an epidemiological link to a primary outbreak while a primary outbreak is an outbreak that is not epidemiologically linked to any previous outbreak. From 2014 to 2023, a total of 272 outbreaks in domestic pigs were confirmed, where 263 (96.7%) were primary outbreaks and 9 (3.3%) were secondary outbreaks. Eight of the secondary outbreaks were detected by epidemiological enquiry and one by passive surveillance. Epidemiological enquiries are legally required investigations on an outbreak farm to find out when and how the virus entered the farm and to obtain information on contact farms where the ASF virus may have been spread. Of the eight secondary outbreaks detected by epidemiological investigations, six were within the protection zone, one was within the surveillance zone and one outside the restricted zone. Epidemiological investigations were therefore the most effective means of detecting secondary outbreaks, whether inside or outside the restricted zones, while active surveillance was not effective. Active surveillance are legally prescribed activities carried out by the competent authorities in the restricted zones. Furthermore, as ASF is no longer a rare and exotic disease in the EU, it could be listed as a “Category B” disease, which in turn would allow for more flexibility and “tailor-made” control measures, e.g., regarding the size of the restricted zone.
Prognostic Value of D-dimer to Lymphocyte Ratio (DLR) in Hospitalized Coronavirus Disease 2019 (COVID-19) Patients: A Validation Study in a National Cohort
Authors: Oblitas Crhistian-Mario , Demelo-Rodríguez Pablo , Alvarez-Sala-Walther Luis-Antonio , Rubio-Rivas Manuel , Navarro-Romero Francisco , Giner Galvañ Vicente , de Jorge-Huerta Lucía , Fonseca Aizpuru Eva , García García Gema María , Beato Pérez José Luis , Pesqueira Fontan Paula María , Artero Mora Arturo , Vargas Núñez Juan Antonio , Ramírez Perea Nuria , García Bruñén José Miguel , Roy Vallejo Emilia , Perales-Fraile Isabel , Gil Sánchez Ricardo , López Castro José , Martínez González Ángel Luis , Díez García Luis Felipe , Aroza Espinar Marina , Casas-Rojo José-Manuel , Millán Núñez-Cortés Jesús
Published: February 2024

Background: This study aimed to validate the role of the D-dimer to lymphocyte ratio (DLR) for mortality prediction in a large national cohort of hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: A retrospective, multicenter, observational study that included hospitalized patients due to SARS-CoV-2 infection in Spain was conducted from March 2020 to March 2022. All biomarkers and laboratory indices analyzed were measured once at admission. Results: A total of 10,575 COVID-19 patients were included in this study. The mean age of participants was 66.9 (±16) years, and 58.6% (6202 patients) of them were male. The overall mortality rate was 16.3% (n = 1726 patients). Intensive care unit admission was needed in 10.5% (n = 1106 patients), non-invasive mechanical ventilation was required in 8.8% (n = 923 patients), and orotracheal intubation was required in 7.5% (789 patients). DLR presented a c-statistic of 0.69 (95% CI, 0.68–0.71) for in-hospital mortality with an optimal cut-off above 1. Multivariate analysis showed an independent association for in-hospital mortality for DLR > 1 (adjusted OR 2.09, 95% CI 1.09–4.04; p = 0.03); in the same way, survival analysis showed a higher mortality risk for DLR > 1 (HR 2.24; 95% CI 2.03–2.47; p < 0.01). Further, no other laboratory indices showed an independent association for mortality in multivariate analysis. Conclusions: This study confirmed the usefulness of DLR as a prognostic biomarker for mortality associated with SARS-CoV-2 infection, being an accessible, cost-effective, and easy-to-use biomarker in daily clinical practice.
A Specific Pattern of Routine Cerebrospinal Fluid Parameters Might Help to Identify Cases of West Nile Virus Neuroinvasive Disease
Authors: Pelz Johann Otto , Mühlberg Christoph , Friedrich Isabel , Weidhase Lorenz , Zimmermann Silke , Maier Melanie , Pietsch Corinna
Published: February 2024

Background: Viral meningitis/encephalitis (ME) is a rare but potentially harmful disease. The prompt identification of the respective virus is important to guide not only treatment but also potential public health countermeasures. However, in about 40% of cases, no virus is identified despite an extensive diagnostic workup. The aim of the present study was to analyze demographic, seasonal, and routine cerebrospinal fluid (CSF) parameters in cases of viral ME and assess their utility for the prediction of the causative virus. Methods: Demographic data, season, and routine CSF parameters (total leucocytes, CSF cell differentiation, age-adjusted CSF/serum albumin ratio, and total immunoglobulin ratios) were retrospectively assessed in cases of viral ME. Results: In total, 156 cases of acute viral ME (74 female, median age 40.0 years) were treated at a tertiary-care hospital in Germany. Specific viral infections were detected in 93 (59.6%) cases. Of these, 14 (9.0%) cases were caused by herpes simplex virus (HSV), 36 (23.1%) by varicella-zoster virus (VZV), 27 (17.3%) by enteroviruses, 9 (5.8%) by West Nile virus (WNV), and 7 (4.5%) by other specific viruses. Additionally, 64 (41.0%) cases of ME of unknown viral etiology were diagnosed. Cases of WNV ME were older, predominantly male, showed a severe disruption of the blood–CSF–barrier, a high proportion of neutrophils in CSF, and an intrathecal total immunoglobulin M synthesis in the first CSF sample. In a multinominal logistic regression analysis, the accuracy of these CSF parameters together with age and seasonality was best for the prediction of WNV (87.5%), followed by unknown viral etiology (66.7%), VZV (61.8%), and enteroviruses (51.9%). Conclusions: Cases with WNV ME showed a specific pattern of routine CSF parameters and demographic data that allowed for their identification with good accuracy. These findings might help to guide the diagnostic workup in cases with viral ME, in particular allowing the timely identification of cases with ME due to WNV.
Optimization of Electric Vehicle Routes Considering Multi-Temperature Co-Distribution in Cold Chain Logistics with Soft Time Windows
Authors: He Meiling , Yang Mei , Fu Wenqing , Wu Xiaohui , Izui Kazuhiro
Published: February 2024

Inspired by the practice of urban distribution of fresh products, we introduce a new electric vehicle routing problem with soft time windows. In this problem, goods with different temperature layers can be distributed in ordinary electric vehicles simultaneously based on the cold storage insulation box. The primary objective is to devise optimized distribution routes for logistics companies to minimize distribution costs, including transportation, refrigeration, and charging costs. To address this, we present a mathematical model for the problem and propose an improved ant colony optimization algorithm combined with a 2-opt algorithm. Based on Solomon dataset, we conduct numerical experiments to verify the effectiveness of the proposed model and algorithm. The numerical results demonstrate that multi-temperature co-distribution can lead to a reduction in distribution cost and an improvement in distribution efficiency.
Study on stability and antifungal activity against Candida albicans of gel containing clotrimazole-loaded nanoparticles
Authors: Ho Hoang Nhan , Ngo Thi Minh Chau , Hoang Ngoc Tuan , Ton Nu Phuong Anh , Nguyen Thi Kieu Nhi
Published: February 2024

Background: Clotrimazole (CLO) is a widely used drug for the treatment of cutaneous and mucosal fungal infections caused by Candida albicans (C. albicans). To improve the topical drug absorption, nano-sized drug delivery systems have gained significant attention, particularly for poorly soluble drugs such as CLO. This research aimed to assess the drug release capability of gel containing clotrimazole-loaded nanoparticles and evaluate its antifungal activity against C. albicans.

Materials and methods: CLO (China), Eudragit RS100 (Germany), Carbopol 934P (China), and other chemicals were utilized in this study. The clotrimazole-loaded nanoparticles were prepared and incorporated into the gel formulation. The in vitro drug release profile of gel was evaluated using Franz diffusion cells. Furthermore, the antifungal efficacy against C. albicans was assessed using Potato Dextrose Agar (PDA) medium.

Results: The prepared gel containing CLO-loaded nanoparticles were stable during 6-week storage, demonstrated prolonged drug release after 24 hours compared to the gel containing free CLO (51.46 ± 1.10% and 71.98 ± 1.40%, respectively), exhibited better antifungal activity against C. albicans than gel containing free CLO (31 points versus 33 points).

Conclusion: The CLO-loaded nanoparticles incorporated into the gel formulation showed promising potential as a topical drug delivery system, enhancing the antifungal activity and prolonging the drug release.

Key words: clotrimazole, Candida albicans, antifungal, gel, nanoparticles
Lower extremity deep vein thrombosis: an ultrasound revisit regarding its diagnostic value
Authors: Nguyen Quoc Bao , Ngo Dac Hong An , Huyen Ton Nu Hong Hanh , Le Minh Tuan , Le Trong Khoan , Le Trong Binh
Published: February 2024

Aim: To determine the diagnostic value of ultrasound in lower extremity deep vein thrombosis (LEDVT).

Methods: Data of 20 patients diagnosed with LEDVT and underwent endovascular treatment at Hue University of Medicine and Pharmacy hospital from 01/2021 - 08/2022 were analyzed. Ultrasound findings were documented and correlated with venography. All patients were initialized with anticoagulation upon the diagnosis of LEDVT. Endovascular treatment included diagnostic venography, inferior vena cava filter insertion, intraclot thrombolysis, manual thromboaspiration with or without venoplasty and stenting.

Results: The mean age was 58.63 ± 16.9 (range, 17 - 85 age). The major risk factors were trauma, surgery, and a history of DVT. LEDVT was found prominently in the left leg and at the femoropopliteal level. Ultrasound had a sensitivity of 93.6%, a specificity of 97.6%, a positive predictive value of 98.6%, a negative predictive value of 89.1% and accuracy of 95% in the diagnosis of LEDVT. The sensitivity and specificity of ultrasound in differentiating between chronic and acute thrombus were 96.5% and 92%. Ultrasound had low sensitivity in evaluating collaterals and venous outflow obstruction (May-Thurner syndrome).

Conclusion: Ultrasound has a high diagnostic value and remains the first line imaging modality in the investigation of LEDVT.

Key words: deep vein thrombosis; ultrasound; venography; thromboaspiration; May-Thurner syndrome
Evaluation of the morphological characteristics of Candida species on chromogenic agar medium and media for chlamydospore production
Authors: Ngo Thi Minh Chau , Nguyen Thi Hong Hanh
Published: February 2024

Background: Candida is a widespread pathogen with various clinical forms. By testing chlamydospore production and culturing on chromogenic agar, C. albicans and some species of C. non-albicans could be identified.

Objectives: 1. To study the morphological characteristics of Candida species on Brilliance Candida agar and chlamydospore production media; 2. To evaluate the Candida species identification value of Brilliance Candida agar and chlamydospore production media.

Materials and methods: 75 Candida isolates belonging to five species were identified by MALDI-TOF MS and stored. These isolates were cultured on Brilliance Candida agar and chlamydospore production media. Results: On Brilliance Candida agar: 100% of C. albicans isolates grew well and had green colonies after 24 hours, 100% of C. tropicalis isolates grew well and had blue color colonies after 48 hours; isolates of C. krusei, C. parapsilosis, and C. glabrata had different coloured colonies after 12 - 48 hours. In addition, C. krusei colonies were dry and wrinkled, compared to the other species’colonies, which were creamy, soft, and convex. 83-100% of C. albicans isolates produced chlamydospores after 3 days. The specificity of the Brilliance Candida agar culture and chlamydospore production test was 100% in identifying C. albicans. The sensitivity of Chromogenic Agar was 100% for C. albicans identification and 83%-100% for chlamydospore production after 3 days. The specificity and sensitivity of Chromogenic Agar in identifying C. tropicalis was 100% after 48 hours.

Conclusions: Brilliance Candida agar had high specificity and sensitivity in identifying C. albicans after 24 hours and C. tropicalis after 48 hours. Chlamydospore production test had high specificity and sensitivity in identifying C. albicans at 3 days

Key words: Candida, chromogenic agar, chlamydospore
Building an application for automatic identification image result of Kirby-Bauer disk diffusion susceptibility test
Authors: Nguyen Hoang Bach , Phan Thanh Luan , Ung Thi Thuy
Published: February 2024

Objectives: AI (artificial intelligence) technologies have allowed us to automate the analysis, processing, and decision-making based on vast amounts of medical data. As a result, disease diagnosis has become more accurate and faster, saving time and enhancing treatment capabilities. Building upon this, we conducted a study on the application of machine learning in image recognition of Kirby-Bauer diffusion antibiotic susceptibility test results to lay the foundation for further research in the use of artificial intelligence to support healthcare professionals in examination, diagnosis, and decision-making in the medical field.

Material and methods: We utilized 200 images of antibiotic susceptibility test results obtained through Kirby-Bauer diffusion technique, with the number of antibiotic zones ≤ 6. The images were labeled to distinguish the inhibition zone and antibiotic zones. We employed the Single-shot Detection (SSD) MobileNet method to achieve a balance between speed, ease of deployment, and accuracy, especially when working with devices with limited computational power. The results obtained from the model’s detection of antibiotic zone labels were used as input for the result recognition algorithm.

Results and discussion: Out of the 200 images, 160 (80%) were successfully identified with sufficient information regarding the number of antibiotic zones. Among the 40 failed images, 30 (15%) lacked sufficient recognition of both the bacterial inhibition zones and the number of antibiotic zones, while 10 (5%) images were unrecognizable. The application demonstrated accurate identification and classification of antibiotic zone positions and bacterial inhibition circles in images with appropriate brightness and contrast. Conclusion: We have successfully developed an initial tool and algorithm based on a machine learning model to quickly and accurately determine the necessary information of a Kirby-Bauer antibiotic susceptibility test result, including the number of antibiotic zones, bacterial inhibition circles, and diameter of inhibition circles, achieving an accuracy rate of 80%.

Key words: deep learning, disk diffusion susceptibility test, Kirby-Bauer, image recognition, artifical intelligence.
An in vitro scanning electron microscopic study: dentine erosion by chelat activation methods
Authors: Phan Anh Chi , Le Thi Thu Nga
Published: February 2024

Background: The purpose of this study was to evaluate and compare the dentine erosion ability of root canal irrigation methods with chelat solution.

Materials and Methods: 45 premolar roots were selected and randomly divided into 3 groups (n = 15) based on root canal irrigation methods with 17% EDTA solution: (1) Conventional needle irrigation, (2) Ultrasonic activation, (3) Sonic activation. After undergoing sample processing, the half roots were observed and evaluated for the erosion dentine under a scanning electron microscope with a magnification of 1000 times according to Torabinejad (2003).

Results: In cervical, the average dentine erosion score of the 3 study groups was not statistically significant (p > 0.05). In the middle, apical and over the root canal, the average dentine erosion score of the sonic activation method was higher than that of the other groups (p < 0.05).

Conclusion: Sonic irrigation cause higher dentine erosion than conventional needle irrigation and ultrasonic activation.

Key words: dentine erosion, ultrasonic activation, sonic activation
Impacto de las herramientas digitales y la capacitación en los docentes de la Universidad Tamaulipeca durante 2020-2021
Authors: Cruz Héctor Iván García
Published: February 2024

El periodo 2020-2021, marcado por la pandemia por SARS-CoV-2, desencadenó algunas necesidades a resolver en el aspecto educativo, entre las que se encontraba la de capacitación docente en las nuevas tecnologías. Los objetivos de esta investigación fueron la identificación del impacto de las herramientas digitales y el análisis de la capacitación de los docentes de la Universidad Tamaulipeca en Reynosa, Tamaulipas, México. La metodología fue mixta. Se emplearon dos cuestionarios de elaboración propia; y el Cuestionario para Medir la competencia Digital Docente, desarrollado por el grupo de Metodologías Activas y Mastery Learning de Universidad Internacional de La Rioja. Participaron 42 docentes voluntarios con edades entre 21 a 61 años, mismos que asistieron a un taller de capacitación. Como resultado, los docentes de la UT, percibieron un impacto positivo de las herramientas digitales en la enseñanza durante este periodo de pandemia 2020-2021, denotando aspectos positivos como el autoaprendizaje y el desarrollo de actividades interactivas y algunos obstáculos como el poco conocimiento y capacitación en el manejo de las herramientas digitales. Después de la capacitación, los docentes percibieron una mejora significativa en el conocimiento y uso de las herramientas digitales, y su autopercepción de dominio, potenciando las habilidades en el uso de la gamificación en sus clases.