bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of multiple access mode for large-scale constellation networking communication
Authors: GUO Xiaoxu , XU Zhaobin , XU Kedi , ZHU Yaowei , JIN Zhonghe
Published: December 2023

In the large-scale satellite constellation technology, the establishment of satellite internal network is the top priority. As the network capacity of the constellation continues to expand and the number of satellite nodes continues to increase, the previous multiple access technology can no longer meet the network capacity requirements of large-scale constellations. In order to meet the requirements of massive connections of satellite nodes in large-scale constellation for new networking communication methods, this paper establishes a sparse spread spectrum inter-satellite communication system with sparse code multiple access (SCMA) as the core. At the same time, the channel characteristics of large-scale constellation are analyzed and the corresponding inter satellite channel model is established in MATLAB. Based on this channel model, the performance of the system is simulated. The simulation results show that under the same signal energy to noise ratio, the sparse spread spectrum inter-satellite communication system established in this paper has better BER characteristics compared with orthogonal frequency division multiple access (OFDMA) and code division multiple access (CDMA). In addition, the threshold signal energy to noise ratio of the system is more than 2 dB better than that of CDMA technology, and the utilization rate of time-frequency resources is 50% higher than that of OFDMA technology.
Dactylogyrids (Platyhelminthes, Monogenea) from the gill lamellae of doradids (Siluriformes) with description of five new species of Cosmetocleithrum and new geographical distribution for known species from the Neotropical Region, Brazil
Authors: Silva Augusto Leandro de Sousa , de Meneses Yuri Costa , Martins Williane Maria de Oliveira , Cohen Simone Chinicz , da Costa Andréa Pereira , Justo Marcia Cristina Nascimento
Published: December 2023

Five new species of Cosmetocleithrum were described parasitizing the gill filaments of neotropical doradid fishes. Cosmetocleithrum undulatum n. sp., Cosmetocleithrum brachylecis n. sp. and Cosmetocleithrum ludovicense n. sp. are described from Platydoras brachylecis from a market-place of São Luís, State of Maranhão, Brazil. Cosmetocleithrum sacciforme n. sp. and Cosmetocleithrum basicomplexum n. sp. are described from Oxydoras niger from Juruá River, State of Acre, Brazil. Cosmetocleithrum undulatum and Cosmetocleithrum brachylecis resemble Cosmetocleithrum falsunilatum Feronato, Razzolini, Morey & Boeger, 2022 mainly by the unique male copulatory organ (MCO) morphology but differ from these and all congeneric species mainly by the morphology of the MCO, accessory piece and hooks pairs. Cosmetocleithrum ludovicense is closer to Cosmetocleithrum confusus Kritsky, Thatcher & Boeger, 1986 and to Cosmetocleithrum akuanduba Soares, Santos Neto & Domingues, 2018 but differs from those mainly by the morphology of the accessory piece. Cosmetocleithrum sacciforme differs from all congeneric species mainly by the morphology of the accessory piece formed by a single plate of saccular appearance. Cosmetocleithrum basicomplexum also shares morphological characters with Cosmetocleithrum gigas Morey, Cachique & Babilonia, 2019 considering the size of the body and shape of the anchors, but differs mainly in the morphology of the bars and hooks. Besides the new species, new data are presented for Cosmetocleithrum leandroi Soares, Neto & Domingues, 2018, C. akuanduba and C. confusus regarding morphological characteristics and biogeography.
Barriers and drivers of positive COVID-19 vaccination behaviours among healthcare workers in Europe and Central Asia: a qualitative cross-country synthesis
Authors: Jackson Cath , Smith Sian , Aghasaryan Anastas , Andreasyan Diana , Aregay Aron Kassahun , Habersaat Katrine Bach , Hovhannisyan Lusine , Bogdan Ignat V. , Chistyakova Darya P. , Cilović-Lagarija Šeila , Colonescu Silviu , Hajiyev Jeyhun , Ilves Anna , Isahakyan Anna , Isahakyan Shushanik , Jusupov Nursultan , Kachkachishvili Iago , Kender Elisa , Kjosevska Elena , Nielsen Siff Malue , Mazhnaia Alyona , Oona Marje , Păunescu Bogdan , Šabanović Haris , Săndulescu Anca-Irina , Vasilevska Ana , Warsi Sahil , Yusifli Elvin , Zamfirescu Raisa-Gabriela , Craig Brett
Published: December 2023

Vaccination uptake is essential to controlling the ongoing COVID-19 pandemic. Healthcare workers (HCWs) play a critical role in receiving, recommending and delivering COVID-19 vaccination. Understanding the specific influences on each behaviour enables the development of targeted and tailored interventions to improve vaccination uptake. This paper presents a qualitative synthesis of HCWs’ individual and context barriers and drivers to these three vaccination behaviours across 10 countries in Europe and Central Asia. Qualitative data from interviews and focus group discussions with 378 HCWs between December 2020 and March 2022 were synthesised and organised by four COM (capability, physical and social opportunity, motivation) factors. Differences by stage of COVID-19 vaccine roll-out (in preparation, early and late delivery) were explored. Receiving vaccination related to all four factors. Recommending vaccination mostly related to capability and motivation. HCWs were generally well-informed by official sources and viewed vaccination as the way to end the pandemic, acknowledging their important role in this. Colleagues, family and friends were positive influences on personal vaccination decisions. However, knowledge gaps were evident, particularly amongst nurses who relied on (social) media. Concerns about safety and effectiveness, often connected to knowledge gaps, were heightened by the accelerated timeline for COVID-19 vaccine development and approval. This impeded some HCWs’ motivation to receive and recommend vaccination even in the later roll-out countries. Delivering vaccination was facilitated by support from public health organisations, teamwork and service re-organisation, more evident amongst later roll-out countries. Ongoing high workloads, stress and burnout hindered delivery. Complex and inter-related factors affecting HCWs’ vaccination behaviours were identified. These insights should inform the design of multifaceted interventions (e.g., communication skills training, management support for HCWs’ mental health, and engaging them in decision-making for service redesign); not only for COVID-19 vaccination as it is integrated into routine services but for routine immunization as a whole.
Terahertz spin currents resolved with nanometer spatial resolution
Authors: Cai Jiahua , Dai Mingcong , Chen Sai , Chen Peng , Wang Jiaqi , Xiong Hongting , Ren Zejun , Liu Shaojie , Liu Zhongkai , Wan Caihua , Bai Ming , Wu Xiaojun
Published: December 2023

The development of coherent terahertz (THz) spin currents with femtosecond temporal resolution has been extensively studied due to its significant implications for advancing high-speed information processing devices. However, the precise spatial resolution of THz spin currents, which is crucial for increasing storage density, is still unknown. In this study, we employ spintronic THz emission nanoscopy (STEN) to achieve efficient injection and accurate detection of femtosecond THz spin currents with nanoscale lateral spatial resolution (∼60 nm). The occurrence of emission signals at the fifth harmonic order indicates a substantial signal-to-noise ratio. Additionally, STEN proves to be an effective method for characterizing and etching nanoscale spintronic heterostructures. The integration of nanophotonics, nanospintronics, and THz-nanotechnology into a unified platform is poised to enable the characterization of spin states at micro-to-nanoscale densities, accelerate the development of high-frequency spintronic optoelectronic nanodevices, and catalyze other revolutionary technical applications.
Deep learning-based field-guided optimization method
Authors: Jin Liang , Guo Shaonan , Song Juheng , Liu Lu
Published: December 2023

TEAM Problem 35, a benchmark problem in the optimization of electrical equipment, is a multi-objective, multi-variable optimization problem involving uniform field optimization. This paper proposes a novel guided optimization algorithm to address this problem and achieve optimal magnetic field regulation. First, the deep learning method is used to predict the magnetic field of the solenoid; second, the generated magnetic field cloud map is screened to extract the magnetic field information of the more optimal solution with uniform magnetic field distribution by calculating the variance of the generated magnetic field map; finally, the magnetic field features are combined with the particle swarm optimization algorithm; specifically, the variance of the calculated magnetic field map is added to the objective function of the optimization algorithm to strengthen the optimization process. This integration improves the convergence speed of the optimization process and ensures the continuity and stability of the obtained Pareto solutions. To optimize the solenoid, this paper considers the uniformity of magnetic field distribution and power loss as the primary optimization objectives. The radius of the coil is chosen as the design variable. The optimization results are compared with those obtained by conventional optimization algorithms, demonstrating superior optimization performance.
Shivalik Plasma Device-I, a glow discharge device to study the collective dynamics of dusty plasma
Authors: Sharma Sachin , Sharma Meenakshee , Prakash G. Veda , Srivastav Prabhakar , Saxena Yogesh , Bose Sayak , Tiwari Sanat
Published: December 2023

Using a uniquely configured glow discharge-based Shivalik Plasma Device-I, we demonstrate a variety of collective phenomena in dusty plasma away from the glow discharge region. The cylindrical glass device produces plasma using parallel disc-shaped electrodes with a smaller anode size than the cathode. The dust microparticles are initially sprinkled over the grounded cathode. These particles acquire a significant negative charge upon plasma formation, resulting in their levitation due to the balance between the Coulomb force and gravity. The new device supports the levitation of a big-sized (10 × 8 × 5 cm3) three-dimensional dust cloud over the glass surface. It contrasts the dusty plasma formations in-between electrodes reported earlier. As the discharge voltage varies from high to low, the dust cloud travels from over the glass surface to between the electrodes. A complex interplay of dust void over the cathode, a sharp density gradient, and gravity lead to self-excitation of collective dust phenomena. It includes dust density waves (phase velocity, vph ∼ 4 cm/s), dust cloud oscillation (frequency, f = 5 Hz), sheared flow (flow velocity, vf ∼ 1 cm/s), and multiple-sized dust vortices. These dust vortices provided an excellent platform for studying turbulent mixing phenomena. The power spectrum analysis agreed with two-dimensional Kolmogorov power-law scaling. This is an ideal dusty plasma apparatus where we can create or move the dust cloud to a location of choice from the glass surface to in-between the electrodes and excite one among many collective dust dynamics.
Distinct mouse models of Stargardt disease display differences in pharmacological targeting of ceramides and inflammatory responses
Authors: Engfer Zachary J. , Lewandowski Dominik , Dong Zhiqian , Palczewska Grazyna , Zhang Jianye , Kordecka Katarzyna , Płaczkiewicz Jagoda , Panas Damian , Foik Andrzej T. , Tabaka Marcin , Palczewski Krzysztof
Published: December 2023

Mutations in many visual cycle enzymes in photoreceptors and retinal pigment epithelium (RPE) cells can lead to the chronic accumulation of toxic retinoid byproducts, which poison photoreceptors and the underlying RPE if left unchecked. Without a functional ATP-binding cassette, sub-family A, member 4 (ABCA4), there is an elevation of all-
trans
-retinal and prolonged buildup of all-
trans
-retinal adducts, resulting in a retinal degenerative disease known as Stargardt-1 disease. Even in this monogenic disorder, there is significant heterogeneity in the time to onset of symptoms among patients. Using a combination of molecular techniques, we studied
Abca4
knockout (simulating human noncoding disease variants) and
Abca4
knock-in mice (simulating human misfolded, catalytically inactive protein variants), which serve as models for Stargardt-1 disease. We compared the two strains to ascertain whether they exhibit differential responses to agents that affect cytokine signaling and/or ceramide metabolism, as alterations in either of these pathways can exacerbate retinal degenerative phenotypes. We found different degrees of responsiveness to maraviroc, a known immunomodulatory CCR5 antagonist, and to the ceramide-lowering agent AdipoRon, an agonist of the ADIPOR1 and ADIPOR2 receptors. The two strains also display different degrees of transcriptional deviation from matched WT controls. Our phenotypic comparison of the two distinct
Abca4
mutant-mouse models sheds light on potential therapeutic avenues previously unexplored in the treatment of Stargardt disease and provides a surrogate assay for assessing the effectiveness for genome editing.
Radiation properties of the accretion disk around a black hole in Einstein-Maxwell-scalar theory*
Authors: Alloqulov Mirzabek , Shaymatov Sanjar , Ahmedov Bobomurat , Jawad Abdul
Published: December 2023

In this study, we explore the properties of a non-rotating black hole in the Einstein-Maxwell-scalar (EMS) theory and investigate the luminosity of the accretion disk surrounding it. We determine all the orbital parameters of particles in the accretion disk, including the radius of the innermost stable circular orbit (ISCO) with angular velocity, angular momentum, and energy. Further, we study the radiative efficiency for different values of black hole parameters. Finally, we analyze the flux, differential luminosity, and temperature of the accretion disk.
Low Harmonics Plug-in Home Charging Electric Vehicle Battery Charger BMS State of Charge Balancing using Priority and Sequencing Technique
Authors: Arof Saharul , Mawby Philip , Arof Hamzah , Noorsal Emilia
Published: December 2023

Poor battery state of health (SOH) or unit cell replacement of a damaged battery may cause an imbalance in the state of charge (SOC) or battery voltage terminal of electric vehicle (EV) batteries, which can negatively impact EV performance and EV batteries when charging. Battery Management System (BMS) monitor charges safely and efficiently. BMS can maximize battery life, can estimate SOC and State of health (SOH). EV Charger charge batteries individually in sequence (parallel) or, at once while in series connection. BMS cell balance controls battery charging in series or parallel using macro charging circuits. This study discusses series motor DC drive Electric Car (EC) Battery Management System (BMS) utilizing macro charging circuit and cell balancing control method. The MATLAB/Simulink software used to test the control algorithm shows that the proposed BMS cell balancing algorithm works effectively and meets our expectations.
Analysis of nanostructured anti reflection coating for various perovskite layer thicknesses in perovskite silicon tandem solar cells
Authors: Kumar B Kranthi , Gupta Nikhil Deep
Published: December 2023

The anti-reflection coating (ARC) plays an important role in the design of every kind of solar cell. The suitable optimization of the ARC layer can make a lot of difference in the final output of the cell, by reducing the reflections at the surface. In this regard, the present paper highlights and analyses numerically the effect of nanostructured ARC for different top perovskite layer thicknesses in perovskite-silicon tandem solar cells. In the present case, the nanostructures for ARC are considered to be made up of SiO2 nanoparticles (NP) embedded in ITO. To evaluate the effect of nanostructure for this proposed cell, the nanostructured tandem cell is compared with its planar ARC-based reference cell. The top perovskite active thickness is varied from 100 nm to 800 nm. It has been found that the effect of nanostructured ARC is more pronounced for thinner perovskite layer-based cells than for thicker layers. To reduce reflections at the front surface, the SiO2 NP diameter and inter-particle spacing are optimized. With the nanostructured ARC at the top, the cell achieved the current density rise of 11.3% as compared to the reference cell for a 100 nm thick perovskite-based tandem cell design. As both the sub-cells are in series in tandem design, the top cell current is matched to the bottom silicon layer current by optimizing the bottom cell too. The proposed ARC design has the added advantage that it can simply be done with sol–gel processes.
Multi-layered micro-patterns co-printed with Ag@CuO nano-ink for flexible devices
Authors: Yu Zhiheng , Zhang Tiancheng , Zhou Shipeng , Pan Taiyao , Yao Haoyang , Huang Fengli
Published: December 2023

Silver (Ag) nano-ink is widely used to fabricate the micro-patterns of flexible electronic devices owing to its excellent conductivity and stability. However, the cost of micro-patterns prepared with silver nano-ink is high. Here, multi-layered, multi-inked (silver@copper oxide) micro-patterns were co-printed layer by layer using an in-house silver nano-ink and commercial copper oxide (CuO) nano-ink. The prepared micro-patterns were solidified by laser sintering. Among the co-printed micro-patterns, the micro-pattern with a top layer of copper (1CuO@2Ag) had the lowest resistance, which was 13.1 Ω cm–1. Additionally, 1CuO@2Ag had the smoothest topography and lowest porosity, which was attributed to effective sintering at the optimal laser power (3 W) for all co-printed micropatterns owing to the high absorptivity and low reflectivity of copper. Moreover, after 500, 1000, and 1500 cycles of fatigue testing, the resistance of 1CuO@2Ag increased by 1.5%, 8.4%, and 13.7%, respectively, indicating good reliability. The proposed method lays the foundation for further studies on Ag@CuO composites for micro-pattern preparation.
Physics-enhanced neural networks for equation-of-state calculations
Authors: Callow Timothy J , Nikl Jan , Kraisler Eli , Cangi Attila
Published: December 2023

Rapid access to accurate equation-of-state (EOS) data is crucial in the warm-dense matter (WDM) regime, as it is employed in various applications, such as providing input for hydrodynamic codes to model inertial confinement fusion processes. In this study, we develop neural network models for predicting the EOS based on first-principles data. The first model utilises basic physical properties, while the second model incorporates more sophisticated physical information, using output from average-atom (AA) calculations as features. AA models are often noted for providing a reasonable balance of accuracy and speed; however, our comparison of AA models and higher-fidelity calculations shows that more accurate models are required in the WDM regime. Both the neural network models we propose, particularly the physics-enhanced one, demonstrate significant potential as accurate and efficient methods for computing EOS data in WDM.
Optimizing building solutions in a changing climate: parameter-based analysis of embodied and operational environmental impacts
Authors: Ramon Delphine , Allacker Karen
Published: December 2023

Buildings contribute significantly to global energy consumption and carbon dioxide emissions. Climate change affects building performance, particularly heating and cooling demands. While current policies focus on improving energy performance and reducing operational emissions, the embodied emissions from building materials become more significant in energy-efficient buildings. This study aims to investigate optimal building solutions considering both operational and embodied environmental impact in the context of climate change in the Belgian context. The research questions address the influence of building characteristics on environmental impact and the contribution of embodied and operational emissions to optimal design. The study employs parametric life cycle assessment and dynamic building energy simulation to explore design strategies for a medium-sized office building. The results reveal the trade-offs between operational and embodied impacts. Buildings with better energy performance exhibit higher embodied emissions, highlighting the importance of considering both aspects. Pareto optimal buildings are identified, minimizing total life cycle environmental cost and operational environmental cost. Insulation levels, solar shading, and orientation are key factors in achieving optimal design. HVAC systems and electricity mixes also significantly influence optimal solutions. Lightweight and heavyweight buildings have distinct characteristics affecting heating and cooling demands. Variations in electricity mixes impact energy consumption and environmental costs of different HVAC system scenarios. The study emphasizes the need for a holistic life cycle approach and considering both operational and embodied impacts in building design. It underscores the importance of optimizing building characteristics while addressing climate change challenges. Further research should explore additional factors such as night cooling, HVAC system performance under climate change, and the inclusion of financial costs and visual comfort in the analysis.
Bibliometric analysis of neuroscience publications quantifies the impact of data sharing
Authors: Emissah Herve , Ljungquist Bengt , Ascoli Giorgio A
Published: December 2023

Neural morphology, the branching geometry of brain cells, is an essential cellular substrate of nervous system function and pathology. Despite the accelerating production of digital reconstructions of neural morphology, the public accessibility of data remains a core issue in neuroscience. Deficiencies in the availability of existing data create redundancy of research efforts and limit synergy. We carried out a comprehensive bibliometric analysis of neural morphology publications to quantify the impact of data sharing in the neuroscience community. Our findings demonstrate that sharing digital reconstructions of neural morphology via NeuroMorpho.Org leads to a significant increase of citations to the original article, thus directly benefiting authors. The rate of data reusage remains constant for at least 16 years after sharing (the whole period analyzed), altogether nearly doubling the peer-reviewed discoveries in the field. Furthermore, the recent availability of larger and more numerous datasets fostered integrative applications, which accrue on average twice the citations of re-analyses of individual datasets. We also released an open-source citation tracking web-service allowing researchers to monitor reusage of their datasets in independent peer-reviewed reports. These results and tools can facilitate the recognition of shared data reuse for merit evaluations and funding decisions.

Availability and implementation

The application is available at: http://cng-nmo-dev3.orc.gmu.edu:8181/. The source code at https://github.com/HerveEmissah/nmo-authors-app and https://github.com/HerveEmissah/nmo-bibliometric-analysis.
Drug repositioning with adaptive graph convolutional networks
Authors: Sun Xinliang , Jia Xiao , Lu Zhangli , Tang Jing , Li Min
Published: December 2023

Motivation

Drug repositioning is an effective strategy to identify new indications for existing drugs, providing the quickest possible transition from bench to bedside. With the rapid development of deep learning, graph convolutional networks (GCNs) have been widely adopted for drug repositioning tasks. However, prior GCNs based methods exist limitations in deeply integrating node features and topological structures, which may hinder the capability of GCNs.

Results

In this study, we propose an adaptive GCNs approach, termed AdaDR, for drug repositioning by deeply integrating node features and topological structures. Distinct from conventional graph convolution networks, AdaDR models interactive information between them with adaptive graph convolution operation, which enhances the expression of model. Concretely, AdaDR simultaneously extracts embeddings from node features and topological structures and then uses the attention mechanism to learn adaptive importance weights of the embeddings. Experimental results show that AdaDR achieves better performance than multiple baselines for drug repositioning. Moreover, in the case study, exploratory analyses are offered for finding novel drug–disease associations.

Availability and implementation

The soure code of AdaDR is available at: https://github.com/xinliangSun/AdaDR.
Nephrology Partnership for Advancing Technology in Healthcare (N-PATH) program: the teachers’ perspective
Authors: Lomonte Carlo , Rossini Michele , Ibeas Jose , Forcella Mauro , Ponikvar Jadranka Buturovic , Gallieni Maurizio , Russo Roberto , Goumenos Dimitrios , Tesar Vladimir , Hruskova Zdenka , Roelofs Joris , Florquin Sandrine , Snoeijs Maarten , Giusto Antonio , Shemesh David , Rotmans Joris , Torra Roser , Wanner Christoph , Gesualdo Loreto
Published: December 2023

The N-PATH (Nephrology Partnership for Advancing Technology in Healthcare) program concluded with the 60th European Renal Association 2023 Congress in Milan, Italy. This collaborative initiative aimed to provide advanced training in interventional nephrology to young European nephrologists. Funded by Erasmus+ Knowledge Alliance, N-PATH addressed the global burden of chronic kidney disease (CKD) and the shortage of nephrologists. CKD affects >850 million people worldwide, yet nephrology struggles to attract medical talent, leading to unfilled positions in residency programs. To address this, N-PATH focused on enhancing nephrology education through four specialized modules: renal expert in renal pathology (ReMAP), renal expert in vascular access (ReVAC), renal expert in medical ultrasound (ReMUS) and renal expert in peritoneal dialysis (RePED). ReMAP emphasized the importance of kidney biopsy in nephrology diagnosis and treatment, providing theoretical knowledge and hands-on training. ReVAC centred on vascular access in haemodialysis, teaching trainees about different access types, placement techniques and managing complications. ReMUS recognized the significance of ultrasound in nephrology, promoting interdisciplinary collaboration and preparing nephrologists for comprehensive patient care. RePED addressed chronic peritoneal dialysis, offering comprehensive training in patient selection, prescription, monitoring, complications and surgical techniques for catheter insertion. Overall, N-PATH's strategy involved collaborative networks, hands-on training, mentorship, an interdisciplinary approach and the integration of emerging technologies. By bridging the gap between theoretical knowledge and practical skills, N-PATH aimed to revitalize interest in nephrology and prepare proficient nephrologists to tackle the challenges of kidney diseases. In conclusion, the N-PATH program aimed to address the shortage of nephrologists and improve the quality of nephrology care in Europe. By providing specialized training, fostering collaboration and promoting patient-centred care, N-PATH aimed to inspire future nephrology professionals to meet the growing healthcare demands related to kidney diseases and elevate the specialty's status within the medical community.
A scalable pipeline to create synthetic datasets from functional–structural plant models for deep learning
Authors: Baker Dirk Norbert , Bauer Felix Maximilian , Giraud Mona , Schnepf Andrea , Göbbert Jens Henrik , Scharr Hanno , Hvannberg Ebba Þora , Riedel Morris
Published: December 2023

In plant science, it is an established method to obtain structural parameters of crops using image analysis. In recent years, deep learning techniques have improved the underlying processes significantly. However, since data acquisition is time and resource consuming, reliable training data are currently limited. To overcome this bottleneck, synthetic data are a promising option for not only enabling a higher order of correctness by offering more training data but also for validation of results. However, the creation of synthetic data is complex and requires extensive knowledge in Computer Graphics, Visualization and High-Performance Computing. We address this by introducing Synavis, a framework that allows users to train networks on real-time generated data. We created a pipeline that integrates realistic plant structures, simulated by the functional–structural plant model framework CPlantBox, into the game engine Unreal Engine. For this purpose, we needed to extend CPlantBox by introducing a new leaf geometrization that results in realistic leafs. All parameterized geometries of the plant are directly provided by the plant model. In the Unreal Engine, it is possible to alter the environment. WebRTC enables the streaming of the final image composition, which, in turn, can then be directly used to train deep neural networks to increase parameter robustness, for further plant trait detection and validation of original parameters. We enable user-friendly ready-to-use pipelines, providing virtual plant experiment and field visualizations, a python-binding library to access synthetic data and a ready-to-run example to train models.
Simultaneous Quantification of Two Neonicotinoids Using QuEChERS–LC–MS/MS in Moroccan Spearmint (Mentha Spicata.L): Qualimetry of the Method by Uncertainty Estimation Using Generalized Pivotal Quantities Approach and Monte Carlo Simulation
Authors: Aaziz Hicham , Saffaj Taoufiq , Benchekroun Yassine Hameda , Ihssane Bouchaib
Published: December 2023

Background

Neonicotinoids (NEOs) are used for the phytosanitary treatment of Mentha Spicata.L crops, and this practice requires precise control of these harmful substances at very low concentrations.

Objective

The objective of this study is to apply an approach allowing simultaneously validation and evaluation of measurement uncertainty based on total error methodology, in order to accurately quantify the presence of two NEOs in Mentha Spicata.L utilizing a Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS)–LC–MS/MS methodology.

Methods

 The quantification of imidacloprid and acetamiprid employing a QuEChERS extraction method, coupled with LC–MS/MS, ensuring the accuracy of the analytical method and managing the risks associated with its routine use. A complete and exhaustive validation approach based on the “β-content, γ-confidence” tolerance interval was used for the uncertainty assessment, using the generalized pivot quantity (GPQ) concept and Monte Carlo simulation, which avoids the need for additional data while achieving intermediate precision for each concentration level within predetermined acceptable limits.

Results

The validation procedure is based on the choice of a quadratic model for the two NEOs, allowing the validation of acetamiprid and imidacloprid by LC–MS/MS assay within the range of working concentration. The flexibility of the uncertainty profile intervals was demonstrated with a variation in β-content values (66.7, 80, and 90%) and risk values (10 and 5%), which remained within the acceptability limits of 20%, and the relative expanded uncertainty did not exceed 15 and 11%.

Conclusion

A QuEChERS–LC–MS/MS method for the analysis of two NEOs has been successfully fully validated using the uncertainty profile strategy.

Highlights

Implementation of an overall validation strategy, which involves both the validation and uncertainty assessment known as the uncertainty profile, for the quantification of two important NEOs in Mentha Spicata.L using QuEChERS–LC–MS/MS. This qualimetric approach has been conducted by computing the measurement uncertainty of the method utilizing data from analytical validation under conditions of intermediate precision at each level of concentration without additional effort. After that we have demonstrated the flexibility of this strategy for the LC–MS/MS quantification of acetamiprid and imidacloprid, using a decision tool that enables the choice and modification of β-content and γ-confidence values.
Enfortumab vedotin following platinum-based chemotherapy and immune checkpoint inhibitors for advanced urothelial carcinoma: response, survival and safety analysis from a multicentre real-world Japanese cohort
Authors: Miyake Makito , Nishimura Nobutaka , Oda Yuki , Miyamoto Tatsuki , Ohmori Chihiro , Takamatsu Norimi , Itami Yoshitaka , Tachibana Akira , Matsumoto Yoshihiro , Kiba Keisuke , Tomioka Atsushi , Yamamoto Hiroaki , Okajima Eijiro , Masaomi Kuwata , Sakamoto Keichi , Tomizawa Mitsuru , Shimizu Takuto , Ohnishi Kenta , Hori Shunta , Morizawa Yosuke , Gotoh Daisuke , Nakai Yasushi , Torimoto Kazumasa , Tanaka Nobumichi , Fujimoto Kiyohide ,   the Nara Urological Research and Treatment Group
Published: December 2023

Objective

Real-world evidence regarding enfortumab vedotin for unresectable or metastatic urothelial carcinoma is scarce, particularly in Japan. We investigated real-world data focusing on patient background, previous treatments, response, survival and adverse events in patients receiving enfortumab vedotin.

Methods

A multicentre database was used to register 556 patients diagnosed with metastatic urothelial carcinoma from 2008 to 2023; 34 patients (6.1%) treated with enfortumab vedotin were included. Best radiographic objective responses were evaluated using the Response Evaluation Criteria in Solid Tumors (v1.1) during treatments. Overall survival and progression-free survival were estimated (Kaplan–Meier method). Toxicities were reported according to the Common Terminology Criteria for Adverse Events, version 5.0. The relative dose intensity, which could impact oncological outcomes, was calculated.

Results

The median number of enfortumab vedotin therapy cycles was 5. The best objective response to enfortumab vedotin was partial response, stable disease and progressive disease in 19 (56%), 5 (15%) and 10 (29%) patients, respectively. The median overall survival and progression-free survival after the first enfortumab vedotin dose were 16 and 9 months, respectively. No significant relationship was observed between survival outcomes after enfortumab vedotin initiation and the enfortumab vedotin relative dose intensity. The median overall survival from first-line platinum-based chemotherapy initiation was 42 months. Twenty-six (76%) patients experienced any grade of enfortumab vedotin-related toxicities; eight (24%) experienced Grades 3–4 toxicities, the most common being skin toxicity (any grade, 47%; Grades 3–4, 12%).

Conclusions

Here, we report real-world evidence for enfortumab vedotin therapy in Japan. Tumour responses and safety profiles were comparable with those of clinical trials on this novel treatment.
Phytonutrients and outcomes following breast cancer: a systematic review and meta-analysis of observational studies
Authors: van Die M Diana , Bone Kerry M , Visvanathan Kala , Kyrø Cecile , Aune Dagfinn , Ee Carolyn , Paller Channing J
Published: December 2023

Background

Phytonutrient intakes may improve outcomes following breast cancer, but the impact of postdiagnosis introduction vs established prediagnostic exposure as well as optimum doses has not been established. Evidence from observational studies for key exposures was evaluated, including dosage and intake time frames.

Methods

MEDLINE, EMBASE, CINAHL, Cochrane Library, ClinicalTrials.gov, and the ISRCTN registry were searched for prospective and retrospective observational studies investigating the impact of soybean, lignans, cruciferous (cabbage-family) vegetables, green tea, or their phytonutrients on breast cancer survival outcomes. A random-effects model was used to calculate summary hazard ratios (HRs) and 95% confidence intervals (CIs). Nonlinear dose-response analyses were conducted using restricted cubic splines.

Results

Thirty-two articles were included. Soy isoflavones were associated with a 26% reduced risk of recurrence (HR = 0.74, 95% CI = 0.60 to 0.92), particularly among postmenopausal (HR = 0.72, 95% CI = 0.55 to 0.94) and estrogen receptor–positive survivors (HR = 0.82, 95% CI = 0.70 to 0.97), with the greatest risk reduction at 60 mg/day. In mortality outcomes, the reduction was mostly at 20 to 40 mg/day. Soy protein and products were inversely associated with cancer-specific mortality for estrogen receptor–positive disease (HR = 0.75, 95% CI = 0.60 to 0.92). An inverse association was observed for serum or plasma enterolactone, measured prediagnosis and early postdiagnosis, with cancer-specific mortality (HR = 0.72, 95% CI = 0.58 to 0.90) and all-cause mortality (HR = 0.69, 95% CI = 0.57 to 0.83). No effects were observed for cruciferous vegetables. There was a 44% reduced risk of recurrence with prediagnostic green tea for stage I and II breast cancer (HR = 0.56, 95% CI = 0.38 to 0.83).

Conclusions

Soy, enterolactone, and green tea demonstrated significant risk reductions in outcomes following breast cancer. Evidence is needed regarding the impact of postdiagnostic introduction or substantial increase of these exposures.
Predictive Value of Methicillin-Resistant Staphylococcus aureus Nasal Swab PCR Assay for MRSA Infection in Critically Ill Pediatric Patients
Authors: Crawford Lexi , Pertsovskaya Vera , Shanklin Alice , Zhang Anqing , Hamdy Rana F
Published: December 2023

Background

Critically ill pediatric patients are frequently initiated methicillin-resistant Staphylococcus aureus (MRSA) active antibiotics during infection evaluation even though MRSA infections are rare in many patient populations. The MRSA nasal swab polymerase chain reaction assay (MRSA-NS-PCR) is a test that has been shown to have a high negative predictive value (NPV) for MRSA infection in adults. This study evaluated the diagnostic test characteristics of the MRSA-NS-PCR in predicting the presence of MRSA infection in critically ill pediatric patients.

Study Design

A retrospective cohort study was performed in a 44-bed pediatric intensive care unit (PICU) between 2013 and 2017. 3860 pediatric patients (54% male, median age 4 years [IQR 1–11 years]) admitted to the PICU who met pediatric systemic inflammatory response syndrome (pSIRS) criteria, were screened with a MRSA-NS-PCR, and had cultures obtained within seven days of MRSA-NS-PCR collection were included. Predictive values and post-test probabilities of the MRSA-NS-PCR for MRSA infection were calculated.

Results

MRSA-NS-PCR was positive in 8.6% of patients. MRSA infection was identified in 40 patients, equaling an incidence rate of 2 per 1000 patient days. The MRSA-NS-PCR demonstrated a positive predictive value (PPV) of 9.7%, a NPV of 99.8%, and a post-test probability for a negative test of 0.2% for MRSA infection.

Conclusions

The MRSA-NS-PCR has a poor PPV but a high NPV for MRSA infection in PICU patients when the incidence of MRSA infection is low. Creation of protocols to guide antimicrobial selection based on MRSA-NS-PCR results may lead to improved antimicrobial stewardship and significant risk reduction.
Superconducting ternary hydrides: progress and challenges
Authors: Zhao Wendi , Huang Xiaoli , Zhang Zihan , Chen Su , Du Mingyang , Duan Defang , Cui Tian
Published: December 2023

Since the discovery of the high-temperature superconductors H3S and LaH10 under high pressure, compressed hydrides have received extensive attention as promising candidates for room-temperature superconductors. As a result of current high-pressure theoretical and experimental studies, it is now known that almost all the binary hydrides with a high superconducting transition temperature (Tc) require extremely high pressure to remain stable, hindering any practical application. In order to further lower the stable pressure and improve superconductivity, researchers have started exploring ternary hydrides and had many achievements in recent years. Here, we discuss recent progress in ternary hydrides, aiming to deepen the understanding of the key factors regulating the structural stability and superconductivity of ternary hydrides, such as structural motifs, bonding features, electronic structures, electron–phonon coupling, etc. Furthermore, the current issues and challenges of superconducting ternary hydrides are presented, together with the prospects and opportunities for future research.
Modularized viromimetic polymer nanoparticle vaccines (VPNVaxs) to elicit durable and effective humoral immune responses
Authors: Huang Zichao , Zhuang Xinyu , Liu Liping , Zhao Jiayu , Ma Sheng , Si Xinghui , Zhu Zhenyi , Wu Fan , Jin Ningyi , Tian Mingyao , Song Wantong , Chen Xuesi
Published: December 2023

Virus-like particle (VLP) vaccines had shown great potential during the COVID-19 pandemic, and was thought to be the next generation of antiviral vaccine technology due to viromimetic structures. However, the time-consuming and complicated processes in establishing a current recombinant-protein–based VLP vaccine has limited its quick launch to the out-bursting pandemic. To simplify and optimize VLP vaccine design, we herein report a kind of viromimetic polymer nanoparticle vaccine (VPNVax), with subunit receptor-binding domain (RBD) proteins conjugated to the surface of polyethylene glycol-b-polylactic acid (PEG-b-PLA) nanoparticles for vaccination against SARS-CoV-2. The preparation of VPNVax based on synthetic polymer particle and chemical post-conjugation makes it possible to rapidly replace the antigens and construct matched vaccines at the emergence of different viruses. Using this modular preparation system, we identified that VPNVax with surface protein coverage of 20%–25% had the best immunostimulatory activity, which could keep high levels of specific antibody titers over 5 months and induce virus neutralizing activity when combined with an aluminum adjuvant. Moreover, the polymer nano-vectors could be armed with more immune-adjuvant functions by loading immunostimulant agents or chemical chirality design. This VPNVax platform provides a novel kind of rapidly producing and efficient vaccine against different variants of SARS-CoV-2 as well as other viral pandemics.
Toxoplasma gondii infection and ABO blood groups: a systematic review and meta-analysis
Authors: Nayeri Tooran , Moosazadeh Mahmood , Dalimi Asl Abdolhossein , Ghaffarifar Fatemeh , Sarvi Shahabeddin , Daryani Ahmad
Published: December 2023

The current study aimed to determine the prevalence of Toxoplasma gondii in ABO blood groups and assess the relationship between the prevalence of T. gondii and blood groups. A literature search was carried out for epidemiological studies that were published through December 2022. A random effects model was used to determine the OR and the pooled prevalence with a 95% CI. The estimated pooled prevalences of T. gondii infection in the A, B, AB and O blood groups were 38% (95% CI 27 to 48%), 38% (95% CI 29 to 47%), 36% (95% CI 26 to 45%) and 36% (95% CI 27 to 45%), respectively. Also, the pooled ORs of the relationship between the prevalence of T. gondii infection and the A, B, AB and O blood groups were 1.08 (95% CI 0.97 to 1.19), 1.10 (95% CI 0.95 to 1.28), 1.08 (95% CI 0.92 to 1.27) and 0.89 (95% CI 0.80 to 1.00), respectively. This meta-analysis did not show any relationship between the prevalence of T. gondii infection and ABO blood groups.
Lung Ultrasound Score on Postoperative Day 1 Is Predictive of the Occurrence of Pulmonary Complications after Major Abdominal Surgery: A Multicenter Prospective Observational Study
Authors: Boussier Jeremy , Lemasle Aymeric , Hantala Nicolas , Scatton Olivier , Vaillant Jean-Christophe , Paye François , Langeron Olivier , Lescot Thomas , Quesnel Christophe , Verdonk Franck , Eyraud Daniel , Sitbon Alexandre , Delorme Louis , Monsel Antoine
Published: December 2023

Background

Postoperative pulmonary complications after major abdominal surgery are frequent and carry high morbidity and mortality. Early identification of patients at risk of pulmonary complications by lung ultrasound may allow the implementation of preemptive strategies. The authors hypothesized that lung ultrasound score would be associated with pulmonary postoperative complications. The main objective of the study was to evaluate the performance of lung ultrasound score on postoperative day 1 in predicting pulmonary complications after major abdominal surgery. Secondary objectives included the evaluation of other related measures for their potential prediction accuracy.

Methods

A total of 149 patients scheduled for major abdominal surgery were enrolled in a bicenter observational study. Lung ultrasound score was performed before the surgery and on days 1, 4, and 7 after surgery. Pulmonary complications occurring before postoperative day 10 were recorded.

Results

Lung ultrasound score on postoperative day 1 was higher in patients developing pulmonary complications before day 10 (median, 13; interquartile range, 8.25 to 18; vs. median, 10; interquartile range, 6.5 to 12; Mann–Whitney P = 0.002). The area under the curve for predicting postoperative pulmonary complications before day 10 was 0.65 (95% CI, 0.55 to 0.75; P = 0.003). Lung ultrasound score greater than 12 had a sensitivity of 0.54 (95% CI, 0.40 to 0.67), specificity of 0.77 (95% CI, 0.67 to 0.85), and negative predictive value of 0.74 (95% CI, 0.65 to 0.83). Lung ultrasound score greater than 17 had sensitivity of 0.33 (95% CI, 0.21 to 0.47), specificity of 0.95 (95% CI, 0.88 to 0.98), and positive predictive value of 0.78 (95% CI, 0.56 to 0.93). Anterolateral lung ultrasound score and composite scores using lung ultrasound score and other patient characteristics showed similar predictive accuracies.

Conclusions

An elevated lung ultrasound score on postoperative day 1 is associated with the occurrence of pulmonary complications within the first 10 days after major abdominal surgery.

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