bluuebunny/crossref_metadata_2025 huggingface dataset:
Online Model Error Correction With Neural Networks in the Incremental 4D‐Var Framework
Authors: Farchi Alban , Chrust Marcin , Bocquet Marc , Laloyaux Patrick , Bonavita Massimo
Published: August 2023

Recent studies have demonstrated that it is possible to combine machine learning with data assimilation to reconstruct the dynamics of a physical model partially and imperfectly observed. The surrogate model can be defined as an hybrid combination where a physical model based on prior knowledge is enhanced with a statistical model estimated by a neural network (NN). The training of the NN is typically done offline, once a large enough data set of model state estimates is available. By contrast, with online approaches the surrogate model is improved each time a new system state estimate is computed. Online approaches naturally fit the sequential framework encountered in geosciences where new observations become available with time. In a recent methodology paper, we have developed a new weak‐constraint 4D‐Var formulation which can be used to train a NN for online model error correction. In the present article, we develop a simplified version of that method, in the incremental 4D‐Var framework adopted by most operational weather centers. The simplified method is implemented in the European Center for Medium‐Range Weather Forecasts (ECMWF) Object‐Oriented Prediction System, with the help of a newly developed Fortran NN library, and tested with a two‐layer two‐dimensional quasi geostrophic model. The results confirm that online learning is effective and yields a more accurate model error correction than offline learning. Finally, the simplified method is compatible with future applications to state‐of‐the‐art models such as the ECMWF Integrated Forecasting System.
Geohealth Policy Benefits Are Mediated by Interacting Natural, Engineered, and Social Processes
Authors: Calder Ryan S. D. , Schartup Amina T.
Published: August 2023

Interest in health implications of Earth science research has significantly increased. Articles frequently dispense policy advice, for example, to reduce human contaminant exposures. Recommendations such as fish consumption advisories rarely reflect causal reasoning around tradeoffs or anticipate how scientific information will be received and processed by the media or vulnerable communities. Health is the product of interacting social and physical processes, yet predictable responses are often overlooked. Analysis of physical and social mechanisms, and health and non‐health tradeoffs, is needed to achieve policy benefits rather than “policy impact.” Dedicated funding mechanisms would improve the quality and availability of these analyses.
Modeling and Prediction of Large‐Scale Climate Variability by Inferring Causal Structure
Authors: He Shan , Yang Song , Chen Dake
Published: August 2023

This study addresses how to model and predict large‐scale climate variability, such as the El Niño–Southern Oscillation (ENSO). We introduce a framework for inferring the macroscale causal structure of the climate system using a spatial‐dimension reduction and high‐dimensional variable selection. The framework encodes the causal structure into a structural causal model, which captures the mechanisms and diversity of ENSO. It thus has a potential to reveal other physical processes within the climate system. The model predicts ENSO at a 1‐month lead time with high accuracy, and the recursive predictions at multi‐month leads are still reliable, even in a different climate state. The stand‐alone oceanic experiments capture the observed oceanic response, proving the model's capability to predict large‐scale climate variability using fragmentary information. This study demonstrates the potential for inferring causal structures to explain, model, and predict large‐scale climate variability such as ENSO.
Excitation and Propagation of Magnetosonic Waves in the Earth's Dipole Magnetic Field: 3D PIC Simulation
Authors: Sun Jicheng , Wang Xueyi , Lu Quanming , Zhang Beichen , Hu Zejun , Liu Jianjun , Hu Hongqiao , Yang Huigen
Published: August 2023

Magnetosonic (MS) waves are common plasma waves in the Earth's magnetosphere. The self‐consistent excitation of MS waves has been studied by 2D particle‐in‐cell simulations in the meridian and equatorial planes of a dipole magnetic field. However, the direction of wave propagation is artificially limited in the previous 2D simulations. Therefore, the 3D simulation of MS waves needs to be investigated. In this paper, we investigate the excitation and evolution of MS waves in the Earth's dipole magnetic field based on a 3D general curvilinear particle‐in‐cell simulation. We find that the MS waves are excited primarily within 3° of the equator when the thermal velocity of the ring distribution is much less than the ring velocity of the ring distribution. These waves propagate along both the radial and azimuthal directions nearly perpendicular to the background magnetic field. In the linear stage, the growth rates of MS waves are almost equal in the radial and azimuthal directions. Compared with the waves propagating along the radial direction, the waves propagating along the azimuthal direction can grow for a longer time, resulting in a larger wave amplification in this direction after saturation. The simulation results provide a valuable insight to understand the self‐consistent evolution of MS waves in the Earth's dipole magnetic field, and the findings are useful for understanding the plasma wave‐particle interaction in the Earth's radiation belts.
Elucidating Hidden and Enduring Weaknesses in Dust Emission Modeling
Authors: Chappell Adrian , Webb Nicholas P. , Hennen Mark , Zender Charles S. , Ciais Philippe , Schepanski Kerstin , Edwards Brandon L. , Ziegler Nancy P. , Balkanski Yves , Tong Daniel , Leys John F. , Heidenreich Stephan , Hynes Robert , Fuchs David , Zeng Zhenzhong , Baddock Matthew C. , Lee Jeffrey A. , Kandakji Tarek
Published: August 2023

Large‐scale classical dust cycle models, developed more than two decades ago, assume for simplicity that the Earth's land surface is devoid of vegetation, reduce dust emission estimates using a vegetation cover complement, and calibrate estimates to observed atmospheric dust optical depth (DOD). Consequently, these models are expected to be valid for use with dust‐climate projections in Earth System Models. We reveal little spatial relation between DOD frequency and satellite observed dust emission from point sources (DPS) and a difference of up to 2 orders of magnitude. We compared DPS data to an exemplar traditional dust emission model (TEM) and the albedo‐based dust emission model (AEM) which represents aerodynamic roughness over space and time. Both models overestimated dust emission probability but showed strong spatial relations to DPS, suitable for calibration. Relative to the AEM calibrated to the DPS, the TEM overestimated large dust emission over vast vegetated areas and produced considerable false change in dust emission. It is difficult to avoid the conclusion that calibrating dust cycle models to DOD has hidden for more than two decades, these TEM modeling weaknesses. The AEM overcomes these weaknesses without using masks or vegetation cover data. Considerable potential therefore exists for ESMs driven by prognostic albedo, to reveal new insights of aerosol effects on, and responses to, contemporary and environmental change projections.
Improving Global Subseasonal to Seasonal Precipitation Forecasts Using a Support Vector Machine‐Based Method
Authors: Yin Gaohong , Yoshikane Takao , Kaneko Ryo , Yoshimura Kei
Published: August 2023

Subseasonal to seasonal (S2s) precipitation forecasts provide great potential for hydrological forecasting at an extended range. The study proposed a support vector machine (SVM) regression‐based method to improve S2s precipitation forecasts from the European Center for Medium‐Range Weather Forecasts (ECMWF) across the globe (60°N to 60°S). Results suggested that the SVM‐based method significantly improved ECMWF daily precipitation forecasts in representing the spatiotemporal variation of precipitation with higher consistency and reduced errors when compared against observations. Furthermore, the SVM‐based method enhanced the probabilistic skill of ECMWF forecasts, providing improved ranked probability skill score (RPSS) for real‐time forecasts in 2020 (e.g., RPSSECMWF = −0.03 and RPSSrg3 = 0.08 for lead week 1). The most substantial improvement from the SVM‐based method is witnessed in regions with complex terrains where ECMWF yielded the worst skill, such as the Andes mountain range, Congo River Basin, and the Tibet Plateau. However, the SVM‐based post‐processing method did not alter the characteristics of precipitation forecasts regarding climate zone and lead time. Both ECMWF and post‐processed forecasts showed higher skill in the temperate and continental climate zones when the lead time is shorter than 2 weeks. In comparison, low‐latitude regions exhibited higher predictability when the lead time is longer than 5 weeks, which is attributed to the slow variation of boundary conditions such as the El Niño‐Southern Oscillation (ENSO).
The Linkage Between Methane Fluxes and Gross Primary Productivity at Diurnal and Seasonal Scales on a Rice Paddy Field in Eastern China
Authors: Zhu Tingting , Zhou Yanlian , Ju Weimin , Li Jing , Hu Lu , Yuan Shu , Xing Xiuli
Published: August 2023

Carbon dioxide (CO2) and methane (CH4) are the most important two greenhouse gases in the atmosphere which were closely coupled between terrestrial ecosystems and the atmosphere. However, the relationship between CO2 and CH4 fluxes of rice paddy at different temporal scales is still unclear. Based on 6 years of eddy covariance measurements on a flooded rice paddy field in Eastern China, the relationship between gross primary productivity (GPP) and CH4 fluxes and the effects of biophysical and environmental factors on daily CH4/GPP were investigated. CH4 fluxes and GPP were tightly linked at diurnal and seasonal scales. On average, half‐hourly CH4 fluxes lagged GPP by 1.5 hr while daily GPP lagged CH4 fluxes by 19 days over the growing season. Leaf area index, water table depth (WTD), air temperature, vapor pressure deficit, and canopy conductance significantly affect daily CH4/GPP. A semi‐empirical multiplicative model was able to capture 77% and 84% seasonal variability of daily CH4/GPP for the training data set and testing data set, respectively. WTD is a crucial input affecting the performance of the model. Without WTD included, the agreement between estimated and observed daily CH4/GPP was weakened. Under the condition without WTD data available, separate calibration of the semi‐empirical multiplicative model before and after panicle initiation could improve the estimation of daily CH4/GPP to some extent. The findings in this study enhance our understanding regarding the complex interactions between CH4 fluxes and GPP in the rice paddy and are helpful for better estimation of CH4 fluxes from GPP.
High-speed electro-optic modulation in topological interface states of a one-dimensional lattice
Authors: Zhang Yong , Shen Jian , Li Jingchi , Wang Hongwei , Feng Chenglong , Zhang Lei , Sun Lu , Xu Jian , Liu Ming , Wang Ying , Tian Yonghui , Dong Jianwen , Su Yikai
Published: August 2023

Electro-optic modulators are key components in data communication, microwave photonics, and quantum photonics. Modulation bandwidth, energy efficiency, and device dimension are crucial metrics of modulators. Here, we provide an important direction for the miniaturization of electro-optic modulators by reporting on ultracompact topological modulators. A topological interface state in a one-dimensional lattice is implemented on a thin-film lithium-niobate integrated platform. Due to the strong optical confinement of the interface state and the peaking enhancement of the electro-optic response, a topological cavity with a size of 1.6 × 140 μm2 enables a large modulation bandwidth of 104 GHz. The first topological modulator exhibits the most compact device size compared to reported LN modulators with bandwidths above 28 GHz, to the best of our knowledge. 100 Gb/s non-return-to-zero and 100 Gb/s four-level pulse amplitude modulation signals are generated. The switching energy is 5.4 fJ/bit, owing to the small electro-optic mode volume and low capacitance. The topological modulator accelerates the response time of topological photonic devices from the microsecond order to the picosecond order and provides an essential foundation for the implementation of large-scale lithium-niobate photonic integrated circuits.
Harnessing metabolism of hepatic macrophages to aid liver regeneration
Authors: Liu Rui , Scimeca Manuel , Sun Qiang , Melino Gerry , Mauriello Alessandro , Shao Changshun ,   TOR Centre, Francesca Bernassola , Pierluigi Bove , Eleonora Candi , Valentina Rovella , Giuseppe Sica , Ying Wang , Shi Yufang , Piacentini Mauro , Tisone Giuseppe , Agostini Massimiliano
Published: August 2023

Liver regeneration is a dynamic and regulated process that involves inflammation, granulation, and tissue remodeling. Hepatic macrophages, abundantly distributed in the liver, are essential components that actively participate in each step to orchestrate liver regeneration. In the homeostatic liver, resident macrophages (Kupffer cells) acquire a tolerogenic phenotype and contribute to immunological tolerance. Following toxicity-induced damage or physical resection, Kupffer cells as well as monocyte-derived macrophages can be activated and promote an inflammatory process that supports the survival and activation of hepatic myofibroblasts and thus promotes scar tissue formation. Subsequently, these macrophages, in turn, exhibit the anti-inflammatory effects critical to extracellular matrix remodeling during the resolution stage. However, continuous damage-induced chronic inflammation generally leads to hepatic macrophage dysfunction, which exacerbates hepatocellular injury and triggers further liver fibrosis and even cirrhosis. Emerging macrophage-targeting strategies have shown efficacy in both preclinical and clinical studies. Increasing evidence indicates that metabolic rewiring provides substrates for epigenetic modification, which endows monocytes/macrophages with prolonged “innate immune memory”. Therefore, it is reasonable to conceive novel therapeutic strategies for metabolically reprogramming macrophages and thus mediate a homeostatic or reparative process for hepatic inflammation management and liver regeneration.
Neonatal and maternal outcomes following SARS-CoV-2 infection and COVID-19 vaccination: a population-based matched cohort study
Authors: Lindsay Laura , Calvert Clara , Shi Ting , Carruthers Jade , Denny Cheryl , Donaghy Jack , Hopcroft Lisa E. M. , Hopkins Leanne , Goulding Anna , McLaughlin Terry , Moore Emily , Taylor Bob , Bhaskaran Krishnan , Katikireddi Srinivasa Vittal , McCabe Ronan , McCowan Colin , Simpson Colin R. , Robertson Chris , Sheikh Aziz , Wood Rachael , Stock Sarah J.
Published: August 2023

Understanding the impact of SARS-CoV-2 infection and COVID-19 vaccination in pregnancy on neonatal and maternal outcomes informs clinical decision-making. Here we report a national, population-based, matched cohort study to investigate associations between SARS-CoV-2 infection and, separately, COVID-19 vaccination just before or during pregnancy and the risk of adverse neonatal and maternal outcomes among women in Scotland with a singleton pregnancy ending at ≥20 weeks gestation. Neonatal outcomes are stillbirth, neonatal death, extended perinatal mortality, preterm birth (overall, spontaneous, and provider-initiated), small-for-gestational age, and low Apgar score. Maternal outcomes are admission to critical care or death, venous thromboembolism, hypertensive disorders of pregnancy, and pregnancy-related bleeding. We use conditional logistic regression to derive odds ratios adjusted for socio-demographic and clinical characteristics (aORs). We find that infection is associated with an increased risk of preterm (aOR=1.36, 95% Confidence Interval [CI] = 1.16–1.59) and very preterm birth (aOR = 1.90, 95% CI 1.20–3.02), maternal admission to critical care or death (aOR=1.72, 95% CI = 1.39–2.12), and venous thromboembolism (aOR = 2.53, 95% CI = 1.47–4.35). We find no evidence of increased risk for any of our outcomes following vaccination. These data suggest SARS-CoV-2 infection during pregnancy is associated with adverse neonatal and maternal outcomes, and COVID-19 vaccination remains a safe way for pregnant women to protect themselves and their babies against infection.
Investigation with able-bodied subjects suggests Myosuit may potentially serve as a stair ascent training robot
Authors: Kim Jaewook , Kim Yekwang , Kang Seonghyun , Kim Seung-Jong
Published: August 2023

Real world settings are seldomly just composed of level surfaces and stairs are frequently encountered in daily life. Unfortunately, ~ 90% of the elderly population use some sort of compensation pattern in order to negotiate stairs. Because the biomechanics required to successfully ascend stairs is significantly different from level walking, an independent training protocol is warranted. Here, we present as a preliminary investigation with 11 able-bodied subjects, prior to clinical trials, whether Myosuit could potentially serve as a stair ascent training robot. Myosuit is a soft wearable exosuit that was designed to assist the user via hip and knee extension during the early stance phase. We hypothesized that clinical studies could be carried out if the lower limb kinematics, sensory feedback via plantar force, and electromyography (EMG) patterns do not deviate from the user’s physiological stair ascent patterns while reducing hip and knee extensor demand. Our results suggest that Myosuit conserves the user’s physiological kinematic and plantar force patterns. Moreover, we observe approximately 20% and 30% decrease in gluteus maximus and vastus medialis EMG levels in the pull up phase, respectively. Collectively, Myosuit reduces the hip and knee extensor demand during stair ascent without any introduction of significant compensation patterns.
MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration
Authors: Ji Zhengran , Hu Mike , Xin Huolin L.
Published: August 2023

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn3O4, MnO, Mn2O3, and MnO2. The accurate decomposition of Mn3O4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.
Trimming flow, plasticity, and mechanical properties by cubic silsesquioxane chemistry
Authors: Sztorch Bogna , Brząkalski Dariusz , Głowacka Julia , Pakuła Daria , Frydrych Miłosz , Przekop Robert E.
Published: August 2023

In this work, the possibility of managing the rheological and mechanical parameters of composites based on PLA with the use of cubic structures of organofunctional spherosilicates was verified. To accurately observe the effect of various organosilicon modifier substitutions on changes in composites’ properties, we synthesized and used monofunctional octasubstituted derivatives as reference systems. The OSS/PLA systems were tested with concentrations of 0.1–2.5% (w/w) using extrusion to obtain a filament with a diameter of 1.75 mm. The printed samples underwent comprehensive tests including microscopic (SEM–EDS, optical microscope), rheological, thermal (TG, DSC, HDT), mechanical (impact and strength) as well as water contact angle tests. The work is interdisciplinary in nature and combines elements of organosilicon synthesis, materials engineering, and materials processing and characterization technology.
Identification of the novel potential pathogen Trueperella pecoris with interspecies significance by LAMP diagnostics
Authors: Kreitlow Antonia , Ningrum Siti Gusti , Lämmler Christoph , Erhard Marcel , Hoffmann Christiane , Plötz Madeleine , Abdulmawjood Amir
Published: August 2023

Trueperella pecoris was described as a new species of the genus Trueperella in 2021 and might be pathogenic to various animal species. However, the lack of a suitable diagnostic test system stands in the way of epidemiological surveys to clarify possible causalities. In this study, a Loop-mediated Isothermal Amplification (LAMP) assay was developed and validated that was highly specific for T. pecoris. The assay provided an analytical sensitivity of 0.5 pg/25 µL and showed 100% inclusivity and exclusivity for 11 target and 33 non-target strains, respectively. Three different DNA extraction methods were evaluated to select the most LAMP-compatible method for cell disruption in pure and complex samples. Using an on-site applicable single-buffer DNA extraction with additional heating, the cell-based detection limit was 2.3 CFU/reaction. Finally, the LAMP assay was validated by means of artificially contaminated porcine lung tissue samples in which minimal microbial loads between 6.54 and 8.37 × 103 CFU per swab sample were detectable. The LAMP assay established in this study represents a suitable diagnostic procedure for identifying T. pecoris in clinical specimens and will help to collect epidemiological data on the pathogenicity of this species.
Low-light image enhancement via adaptive frequency decomposition network
Authors: Liang Xiwen , Chen Xiaoyan , Ren Keying , Miao Xia , Chen Zhihui , Jin Yutao
Published: August 2023

Images captured in low light conditions suffer from low visibility, blurred details and strong noise, resulting in unpleasant visual appearance and poor performance of high level visual tasks. To address these problems, existing approaches have attempted to enhance the visibility of low-light images using convolutional neural networks (CNN). However, due to the insufficient consideration of the characteristics of the information of different frequency layers in the image, most of them yield blurry details and amplified noise. In this work, to fully extract and utilize these information, we proposed a novel Adaptive Frequency Decomposition Network (AFDNet) for low-light image enhancement. An Adaptive Frequency Decomposition (AFD) module is designed to adaptively extract low and high frequency information of different granularities. Specifically, the low-frequency information is employed for contrast enhancement and noise suppression in low-scale space and high-frequency information is for detail restoration in high-scale space. Meanwhile, a new frequency loss function are proposed to guarantee AFDNet’s recovery capability for different frequency information. Extensive experiments on various publicly available datasets show that AFDNet outperforms the existing state-of-the-art methods both quantitatively and visually. In addition, our results showed that the performance of the face detection can be effectively improved by using AFDNet as pre-processing.
Mycobacterial DNA-binding protein 1 is critical for BCG survival in stressful environments and simultaneously regulates gene expression
Authors: Shaban Amina K. , Gebretsadik Gebremichal , Hakamata Mariko , Takihara Hayato , Inouchi Erina , Nishiyama Akihito , Ozeki Yuriko , Tateishi Yoshitaka , Nishiuchi Yukiko , Yamaguchi Takehiro , Ohara Naoya , Okuda Shujiro , Matsumoto Sohkichi
Published: August 2023

Survival of the live attenuated Bacillus Calmette-Guérin (BCG) vaccine amidst harsh host environments is key for BCG effectiveness as it allows continuous immune response induction and protection against tuberculosis. Mycobacterial DNA binding protein 1 (MDP1), a nucleoid associated protein, is essential in BCG. However, there is limited knowledge on the extent of MDP1 gene regulation and how this influences BCG survival. Here, we demonstrate that MDP1 conditional knockdown (cKD) BCG grows slower than vector control in vitro, and dies faster upon exposure to antibiotics (bedaquiline) and oxidative stress (H2O2 and menadione). MDP1-cKD BCG also exhibited low infectivity and survival in THP-1 macrophages and mice indicating possible susceptibility to host mediated stress. Consequently, low in vivo survival resulted in reduced cytokine (IFN-gamma and TNF-alpha) production by splenocytes. Temporal transcriptome profiling showed more upregulated (81–240) than downregulated (5–175) genes in response to MDP1 suppression. Pathway analysis showed suppression of biosynthetic pathways that coincide with low in vitro growth. Notable was the deferential expression of genes involved in stress response (sigI), maintenance of DNA integrity (mutT1), REDOX balance (WhiB3), and host interactions (PE/PE_PGRS). Thus, this study shows MDP1’s importance in BCG survival and highlights MDP1-dependent gene regulation suggesting its role in growth and stress adaptation.
Quantifying agonistic interactions between group-housed animals to derive social hierarchies using computer vision: a case study with commercially group-housed rabbits
Authors: Ipek Nusret , Van Damme Liesbeth G. W. , Tuyttens Frank A. M. , Verwaeren Jan
Published: August 2023

In recent years, computer vision has contributed significantly to the study of farm animal behavior. In complex environments such as commercial farms, however, the automated detection of social behavior and specific interactions between animals can be improved. The present study addresses the automated detection of agonistic interactions between caged animals in a complex environment, relying solely on computer vision. An automated pipeline including group-level temporal action segmentation, object detection, object tracking and rule-based action classification for the detection of agonistic interactions was developed and extensively validated at a level unique in the field. Comparing with observations made by human observers, our pipeline reaches 77% precision and 85% recall using a 5-min tolerance interval for the detection of agonistic interactions. Results obtained using this pipeline allow to construct time-dependent socio-matrices of a group of animals and derive metrics on the dominance hierarchy in a semi-automated manner. Group-housed breeding rabbits (does) with their litters in commercial farms are the main use-case in this work, but the idea is probably also applicable to other social farm animals.
Optimal transfer learning based nutrient deficiency classification model in ridge gourd (Luffa acutangula)
Authors: Shadrach Finney Daniel , Kandasamy Gunavathi , Neelakandan S. , Lingaiah T. Bheema
Published: August 2023

The efficient detection of nutrient deficiency and proper fertilizer for that deficiency becomes the critical challenges various farmers face. The family Cucurbitaceae includes members cultivated globally as a source of indigenous medicines, food, and fiber. Luffa acutangula (L.) Roxb, generally called Ridge gourd, belongs to the Cucurbitaceae family and is an annual herb originating in several areas of India, particularly in the coastal regions. Nutrient deficiency detection in ridge gourd is essential to improve crop productivity. In agricultural practises, the early identification and categorization of nutrient deficiencies in crops is essential for sustaining optimal growth and production. Addressing these nutrient deficiencies, we applied the Ring Toss Game Optimization with a Deep Transfer Learning-based Nutrient Deficiency Classification (RTGODTL-NDC) to Ridge Gourd (Luffa acutangula). This research proposes a new ring toss game optimization with a deep transfer learning-based nutrient deficiency classification (RTGODTL-NDC) method. The RTGODTL-NDC technique uses pre-processing, segmentation, feature extraction, hyperparameter tuning, and classification. The Gabor filter (GF) is mainly used for image pre-processing, and the Adam optimizer with SqueezeNet model is utilized for feature extraction. Finally, the RTGO algorithm with the deep hybrid learning (HDL) model is applied to classify nutrient deficiencies. The suggested framework has the potential to improve crop management practises by allowing for proactive and targeted interventions, which will result in improved agricultural health, production, and resource utilisation. The outcomes represented by the RTGODTL-NDC method have resulted in improved performance. For example, based on accuracy and specificity, the RTGODTL-NDC methodology rendered maximum $$acc{u}_{y}$$

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of 97.16% and specificity of 98.29%. The outcomes show how effective the transfer learning-based model is in identifying nutrient deficits in ridge gourd plants, as seen by its high level of accuracy.
Improving quantitation accuracy in isobaric-labeling mass spectrometry experiments with spectral library searching and feature-based peptide-spectrum match filter
Authors: Kuo Tzu-Yun , Wang Jen-Hung , Huang Yung-Wen , Sung Ting-Yi , Chen Ching-Tai
Published: August 2023

Isobaric labeling relative quantitation is one of the dominating proteomic quantitation technologies. Traditional quantitation pipelines for isobaric-labeled mass spectrometry data are based on sequence database searching. In this study, we present a novel quantitation pipeline that integrates sequence database searching, spectral library searching, and a feature-based peptide-spectrum-match (PSM) filter using various spectral features for filtering. The combined database and spectral library searching results in larger quantitation coverage, and the filter removes PSMs with larger quantitation errors, retaining those with higher quantitation accuracy. Quantitation results show that the proposed pipeline can improve the overall quantitation accuracy at the PSM and protein levels. To our knowledge, this is the first study that utilizes spectral library searching to improve isobaric labeling-based quantitation. For users to conveniently perform the proposed pipeline, we have implemented the feature-based filter being executable on both Windows and Linux platforms; its executable files, user manual, and sample data sets are freely available at https://ms.iis.sinica.edu.tw/comics/Software_FPF.html. Furthermore, with the developed filter, the proposed pipeline is fully compatible with the Trans-Proteomic Pipeline.
Effects of emotional content on social inhibition of gaze in live social and non-social situations
Authors: Pasqualette Laura , Kulke Louisa
Published: August 2023

In real-life interactions, it is crucial that humans adequately respond to others’ emotional expressions. Emotion perception so far has mainly been studied in highly controlled laboratory tasks. However, recent research suggests that attention and gaze behaviour significantly differ between watching a person on a controlled laboratory screen compared to in real world interactions. Therefore, the current study aimed to investigate effects of emotional expression on participants’ gaze in social and non-social situations. We compared looking behaviour towards a confederate showing positive, neutral or negative facial expressions between live social and non-social waiting room situations. Participants looked more often and longer to the confederate on the screen, than when physically present in the room. Expressions displayed by the confederate and individual traits (social anxiety and autistic traits) of participants did not reliably relate to gaze behaviour. Indications of covert attention also occurred more often and longer during the non-social, than during the social condition. Findings indicate that social norm is a strong factor modulating gaze behaviour in social contexts.

Protocol registration

The stage 1 protocol for this Registered Report was accepted in principle on September 13, 2021. The protocol, as accepted by the journal, can be found at:https://doi.org/10.6084/m9.figshare.16628290.
Effects of mixed application of avermectin, imidacloprid and carbendazim on soil degradation and toxicity toward earthworms
Authors: Liang Xiaoyu , Li Yufei , Zheng Zhao , Tian Fang , Du Yannan , Yang Ye , Wang Meng , Zhang Yu
Published: August 2023

The application of pesticides in mixtures often exerts multiple pressures on agricultural soils in the short term. Therefore, it is necessary to assess the effects of mixed application on the environmental behavior and ecotoxicity of pesticides in soil. In this study, we assessed the effects of three common pesticides through mixed application on soil degradation and toxicity toward the earthworm Eisenia fetida. Compared with the degradation half-lives (DT50) the single pesticide, the DT50 values of avermectin, imidacloprid and carbendazim in the binary mixtures were similar. However, their DT50 values in the ternary mixtures were approximately 1.5 times longer than those in the individual applications, enhancing their stable in soil after two or three applications. The ternary mixtures of the pesticides showed significantly synergistic toxicity toward E. fetida, while their binary mixtures exhibited a changing interaction throughout the entire effect level range. The ternary mixtures activated higher SOD and CAT activities in E. fetida than the individual treatments, confirming their synergistic effects. By conducting avoidance tests with E. fetida, ternary toxic interactions were effectively assessed within a relatively short testing period. In summary, the three pesticides in ternary mixtures exhibited longer degradation half-lives and synergistic toxicity toward earthworms compared to individual or binary mixtures.
Improving physio-mechanical and biological properties of 3D-printed PLA scaffolds via in-situ argon cold plasma treatment
Authors: Zarei Masoud , Sayedain Sayed Shahab , Askarinya Amirhossein , Sabbaghi Mobina , Alizadeh Reza
Published: August 2023

As a bone tissue engineering material, polylactic acid (PLA) has received significant attention and interest due to its ease of processing and biocompatibility. However, its insufficient mechanical properties and poor wettability are two major drawbacks that limit its extensive use. For this purpose, the present study uses in-situ cold argon plasma treatment coupled with a fused deposition modeling printer to enhance the physio-mechanical and biological behavior of 3D-printed PLA scaffolds. Following plasma treatment, field emission scanning electron microscopy images indicated that the surface of the modified scaffold became rough, and the interlayer bonding was enhanced. This resulted in an improvement in the tensile properties of samples printed in the X, Y, and Z directions, with the enhancement being more significant in the Z direction. Additionally, the root mean square value of PLA scaffolds increased (up to 70-fold) after plasma treatment. X-ray photoelectron spectroscopy analysis demonstrated that the plasma technique increased the intensity of oxygen-containing bonds, thereby reducing the water contact angle from 92.5° to 42.1°. The in-vitro degradation study also demonstrated that argon plasma treatment resulted in a 77% increase in PLA scaffold degradation rate. Furthermore, the modified scaffold improved the viability, attachment, and proliferation of human adipose-derived stem cells. These findings suggest that in-situ argon plasma treatment may be a facile and effective method for improving the properties of 3D-printed parts for bone tissue engineering and other applications.
Investigation of kinetics, isotherms, thermodynamics and photocatalytic regeneration of exfoliated graphitic carbon nitride/zeolite as dye adsorbent
Authors: Farhadi Hajar , Keramati Narjes
Published: August 2023

A novel exfoliated graphitic carbon nitride and clinoptilolite nanocomposites (Ex.g-C3N4/CP and g-C3N4/CP with a various ratios of g-C3N4 to CP) were prepared by facile method. This study evaluates the adsorption of methylene blue (MB) on the surface of synthesized adsorbents. The as-prepared composites were characterized by XRD, FT-IR, FESEM, BET and DRS. Batch experiments were carried out under various conditions, such as the amount of adsorbent and solution pH. The optimum batch experimental conditions were found under the response surface methodology. The Ex.g-C3N4/CP presented maximum removal of MB as compared to others. The removal efficiency of the as-prepared nanocomposite was significantly elevated owing to the synergistic effects. The adsorption capacities of MB (10 ppm) on Ex.g-C3N4/CP was 54.3 mg/g. The adsorption process by both composites (g-C3N4/CP and Ex.g-C3N4/CP) showed well-fitting with the Elovich kinetic model, and Langmuir isotherm. The thermodynamic study suggested that the adsorption of MB was a spontaneous and endothermic process. The reusability of g-C3N4/CP1:2 and Ex. g-C3N4/CP in removing of MB (10 ppm, pH = 9) was studied by photocatalytic regeneration under visible irradiation for three consecutive cycles. The results obtained from the experimental analyses showed that the removal of MB was easy treatment, eco-friendly, and high yield.
Prophylactic use amphotericin B use in patients with hematologic disorders complicated by neutropenia: a systematic review and meta-analysis
Authors: Chen Zhaoyan , Feng Qiyi , Wang Xiaoxing , Tian Fangyuan
Published: August 2023

The purpose of this study is to evaluate the efficacy of prophylactic use amphotericin B in patients with hematologic disorders complicated by neutropenia. We searched the PubMed, EMBASE, The Cochrane Library, CBM, CNKI, VIP and WanFang Data database and the China Clinical Trials Registry (www.chictr.org.cn) to collect randomized controlled trials (RCTs) of amphotericin B for patients with hematologic disorders complicated by neutropenia from inception to May 2023. The Cochrane risk-of-bias tool for RCTs was used to assess the bias risk of the included studies. The meta-analysis was performed using RevMan 5.3 software. A total of 6 studies with a total of 1019 patients were included. The results of the meta-analysis showed that the treatment group was superior to the control group in terms of the fungal infection rate, and the differences were statistically significant [RR = 0.47, 95% CI (0.32, 0.69), P < 0.0001]. There was no significant difference between the two groups in terms of the mortality [RR = 0.87, 95% CI (0.61, 1.23), P = 0.43] and the incidence of colonization [OR = 0.51, 95% CI (0.25, 1.03), P = 0.06]. The evidence shows that amphotericin B prophylactic use for patients with hematologic disorders complicated by neutropenia can decrease the fungal infection rate. However, there was no significant difference in reducing mortality or the incidence of colonization. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.
Switching from high-fat diet to normal diet ameliorate BTB integrity and improve fertility potential in obese male mice
Authors: Zhang Wenjing , Tian Zhenhua , Qi Xiangyu , Chen Pengcheng , Yang Qian , Guan Qingbo , Ye Jifeng , Yu Chunxiao
Published: August 2023

Obesity is a prominent risk factor for male infertility, and a high-fat diet is an important cause of obesity. Therefore, diet control can reduce body weight and regulate blood glucose and lipids, but it remains unclear whether it can improve male fertility and its mechanism. This study explores the effects of switching from a high-fat diet (HFD) to a normal diet (ND) on the fertility potential of obese male mice and its related mechanisms. In our study, male mice were separated into three groups: normal diet group (NN), continuous high-fat diet group (HH), and return to normal diet group (HN). The reproductive potential of mice was tested through cohabitation. Enzymatic methods and ELISA assays were used to measure metabolic indicators, follicle-stimulating hormone (FSH) levels and intratesticular testosterone levels. Transmission electron microscopy and immunofluorescence with biotin tracers assessed the integrity of the blood-testis barrier (BTB). Malondialdehyde (MDA), superoxide dismutase (SOD), and reactive oxygen species (ROS) were inspected for the assessment of oxidative stress. The expression and localization of BTB-related proteins were detected through the immunoblot and immunofluorescence. The mice in the high-fat diet group indicated increased body weight and epididymal fat weight, elevated serum TC, HDL, LDL, and glucose, decreased serum FSH, and dramatic lipid deposition in the testicular interstitium. Analysis of fertility potential revealed that the fertility rate of female mice and the number of pups per litter in the HH group were significantly reduced. After the fat intake was controlled by switching to a normal diet, body weight and epididymal fat weight were significantly reduced, serum glucose and lipid levels were lowered, serum FSH level was elevated and the deposition of interstitial lipids in the testicles was also decreased. Most significantly, the number of offspring of male mice returning to a normal diet was significantly increased. Following further mechanistic analysis, the mice in the sustained high-fat diet group had disrupted testicular BTB integrity, elevated levels of oxidative stress, and abnormal expression of BTB-related proteins, whereas the restoration of the normal diet significantly ameliorated the above indicators in the mice. Our study confirms diet control by switching from a high-fat diet to a normal diet can effectively reduce body weight, ameliorate testicular lipotoxicity and BTB integrity in male mice, and improve fertility potential, providing an effective treatment option for obese male infertility.
Regulation and function of adiponectin in the intestinal epithelial cells in response to Trichinella spiralis infection
Authors: Jeerawattanawart Siranart , Hansakon Adithap , Roytrakul Sittiruk , Angkasekwinai Pornpimon
Published: August 2023

Besides metabolic homeostasis regulation, adipokines are recently emerged as important players in regulating immunity and inflammation. Helminth infection has known to modulate circulating adipokine secretion; however, the regulation and function of adipokines in response to helminth infection is still unclear. Here, we investigated the regulation and function of adiponectin during T. spiralis infection. While there was no change in circulating level of adiponectin, we found an increased adiponectin, but not leptin expression in the small intestine. Interestingly, the intestinal adiponectin expression was strongly associated with the expression of epithelial cell-derived cytokines IL-25, IL-33, and TSLP following infection. Indeed, mice deficiency of IL-25 receptor exhibited no intestinal adiponectin induction upon helminth infection. Interestingly, IL-25-induced adiponectin modulated intestinal epithelial cell responses by enhancing occludin and CCL17 expression. Using LPS-induced intestinal epithelial barrier dysfunctions in a Caco-2 cell monolayer model, adiponectin pretreatment enhanced a Transepithelial electrical resistance (TEER) and occludin expression. More importantly, adiponectin pretreatment of Caco2 cells prevented T. spiralis larval invasion in vitro and its administration during infection enhanced intestinal IL-13 secretion and worm expulsion in vivo. Altogether, our data suggest that intestinal adiponectin expression induced by helminth infection through the regulation of IL-25 promotes worm clearance and intestinal barrier function.
A cell-based assay for rapid assessment of ACE2 catalytic function
Authors: Meyers Warren M. , Hong Ryan J. , Sin Wun Chey , Kim Christine S. , Haas Kurt
Published: August 2023

Angiotensin-converting enzyme II (ACE2) is a monocarboxypeptidase expressed throughout multiple tissues and its catalysis of bioactive peptides regulates the renin-angiotensin system mediating blood pressure homeostasis. ACE2 is implicated in a variety of diseases, including obesity, diabetes, and cardiovascular diseases, and is the obligate entry receptor for SARS-CoV-2 infection. Disease-associated genetic variants of ACE2 are increasingly being identified but are poorly characterized. To aid this problem, we introduce a fluorometric cell-based assay for evaluating surface-expressed ACE2 catalytic activity that preserves the native glycosylation of the host environment and is amenable to high-throughput analysis of ACE2 variants in multi-well plates. We demonstrate sensitivity to detecting catalysis of the key ACE2 substrates, Angiotensin II, Apelin-13, and des-Arg9-bradykinin, and impact of a catalytically-deficient ACE2 variant. Normalizing catalytic measures to surface ACE2 expression accounts for variability in ACE2 variant transfection, surface delivery or stability. This assay provides a convenient and powerful approach for investigating the catalytic characteristics of ACE2 variants involved in cardiovascular peptide cascades and homeostasis of multiple organs.
Antibody response in elderly vaccinated four times with an mRNA anti-COVID-19 vaccine
Authors: Rouvinski Alexander , Friedman Ahuva , Kirillov Saveliy , Attal Jordan Hannink , Kumari Sujata , Fahoum Jamal , Wiener Reuven , Magen Sophie , Plotkin Yevgeni , Chemtob Daniel , Bercovier Herve
Published: August 2023

The humoral response after the fourth dose of a mRNA vaccine against COVID-19 has not been adequately described in elderly recipients, particularly those not exposed previously to SARS-CoV-2. Serum anti-RBD IgG levels (Abbott SARS-CoV-2 IgG II Quant assay) and neutralizing capacities (spike SARS-CoV-2 pseudovirus Wuhan and Omicron BA.1 variant) were measured after the third and fourth doses of a COVID-19 mRNA vaccine among 46 elderly residents (median age 85 years [IQR 81; 89]) of an assisted living facility. Among participants never infected by SARS-CoV-2, the mean serum IgG levels against RBD (2025 BAU/ml), 99 days after the fourth vaccine, was as high as 76 days after the third vaccine (1987 BAU/ml), and significantly higher (p = 0.030) when the latter were corrected for elapsed time. Neutralizing antibody levels against the historical Wuhan strain were significantly higher (Mean 1046 vs 1573; p = 0.002) and broader (against Omicron) (Mean 170 vs 375; p = 0.018), following the fourth vaccine. The six individuals with an Omicron breakthrough infection mounted strong immune responses for anti-RBD and neutralizing antibodies against the Omicron variant indicating that the fourth vaccine dose did not prevent a specific adaptation of the immune response. These findings point out the value of continued vaccine boosting in the elderly population