bluuebunny/crossref_metadata_2025 huggingface dataset:
EB1 decoration of microtubule lattice facilitates spindle-kinetochore lateral attachment in Plasmodium male gametogenesis
Authors: Yang Shuzhen , Cai Mengya , Huang Junjie , Zhang Shengnan , Mo Xiaoli , Jiang Kai , Cui Huiting , Yuan Jing
Published: May 2023

Faithful chromosome segregation of 8 duplicated haploid genomes into 8 daughter gametes is essential for male gametogenesis and mosquito transmission of Plasmodium. Plasmodium undergoes endomitosis in this multinucleated cell division, which is highly reliant on proper spindle-kinetochore attachment. However, the mechanisms underlying the spindle-kinetochore attachment remain elusive. End-binding proteins (EBs) are conserved microtubule (MT) plus-end binding proteins and play an important role in regulating MT plus-end dynamics. Here, we report that the Plasmodium EB1 is an orthologue distinct from the canonical eukaryotic EB1. Both in vitro and in vivo assays reveal that the Plasmodium EB1 losses MT plus-end tracking but possesses MT-lattice affinity. This MT-binding feature of Plasmodium EB1 is contributed by both CH domain and linker region. EB1-deficient parasites produce male gametocytes that develop to the anucleated male gametes, leading to defective mosquito transmission. EB1 is localized at the nucleoplasm of male gametocytes. During the gametogenesis, EB1 decorates the full-length of spindle MTs and regulates spindle structure. The kinetochores attach to spindle MTs laterally throughout endomitosis and this attachment is EB1-dependent. Consequently, impaired spindle-kinetochore attachment is observed in EB1-deficient parasites. These results indicate that a parasite-specific EB1 with MT-lattice binding affinity fulfills the spindle-kinetochore lateral attachment in male gametogenesis.
Ultrabroadband sound control with deep-subwavelength plasmacoustic metalayers
Authors: Sergeev Stanislav , Fleury Romain , Lissek Hervé
Published: May 2023

Controlling audible sound requires inherently broadband and subwavelength acoustic solutions, which are to date, crucially missing. This includes current noise absorption methods, such as porous materials or acoustic resonators, which are typically inefficient below 1 kHz, or fundamentally narrowband. Here, we solve this vexing issue by introducing the concept of plasmacoustic metalayers. We demonstrate that the dynamics of small layers of air plasma can be controlled to interact with sound in an ultrabroadband way and over deep-subwavelength distances. Exploiting the unique physics of plasmacoustic metalayers, we experimentally demonstrate perfect sound absorption and tunable acoustic reflection over two frequency decades, from several Hz to the kHz range, with transparent plasma layers of thicknesses down to λ/1000. Such bandwidth and compactness are required in a variety of applications, including noise control, audio-engineering, room acoustics, imaging and metamaterial design.
Joule spectroscopy of hybrid superconductor–semiconductor nanodevices
Authors: Ibabe A. , Gómez M. , Steffensen G. O. , Kanne T. , Nygård J. , Yeyati A. Levy , Lee E. J. H.
Published: May 2023

Hybrid superconductor-semiconductor devices offer highly tunable platforms, potentially suitable for quantum technology applications, that have been intensively studied in the past decade. Here we establish that measurements of the superconductor-to-normal transition originating from Joule heating provide a powerful spectroscopical tool to characterize such hybrid devices. Concretely, we apply this technique to junctions in full-shell Al-InAs nanowires in the Little-Parks regime and obtain detailed information of each lead independently and in a single measurement, including differences in the superconducting coherence lengths of the leads, inhomogeneous covering of the epitaxial shell, and the inverse superconducting proximity effect; all-in-all constituting a unique fingerprint of each device with applications in the interpretation of low-bias data, the optimization of device geometries, and the uncovering of disorder in these systems. Besides the practical uses, our work also underscores the importance of heating in hybrid devices, an effect that is often overlooked.
Characterisation of IL-23 receptor antagonists and disease relevant mutants using fluorescent probes
Authors: Lay Charles S. , Isidro-Llobet Albert , Kilpatrick Laura E. , Craggs Peter D. , Hill Stephen J.
Published: May 2023

Association of single nucleotide polymorphisms in the IL-23 receptor with several auto-inflammatory diseases, led to the heterodimeric receptor and its cytokine-ligand IL-23, becoming important drug targets. Successful antibody-based therapies directed against the cytokine have been licenced and a class of small peptide antagonists of the receptor have entered clinical trials. These peptide antagonists may offer therapeutic advantages over existing anti-IL-23 therapies, but little is known about their molecular pharmacology. In this study, we use a fluorescent version of IL-23 to characterise antagonists of the full-length receptor expressed by living cells using a NanoBRET competition assay. We then develop a cyclic peptide fluorescent probe, specific to the IL23p19:IL23R interface and use this molecule to characterise further receptor antagonists. Finally, we use the assays to study the immunocompromising C115Y IL23R mutation, demonstrating that the mechanism of action is a disruption of the binding epitope for IL23p19.
The NuRD complex cooperates with SALL4 to orchestrate reprogramming
Authors: Wang Bo , Li Chen , Ming Jin , Wu Linlin , Fang Shicai , Huang Yi , Lin Lihui , Liu He , Kuang Junqi , Zhao Chengchen , Huang Xingnan , Feng Huijian , Guo Jing , Yang Xuejie , Guo Liman , Zhang Xiaofei , Chen Jiekai , Liu Jing , Zhu Ping , Pei Duanqing
Published: May 2023

Cell fate decision involves rewiring of the genome, but remains poorly understood at the chromatin level. Here, we report that chromatin remodeling complex NuRD participates in closing open chromatin in the early phase of somatic reprogramming. Sall4, Jdp2, Glis1 and Esrrb can reprogram MEFs to iPSCs efficiently, but only Sall4 is indispensable capable of recruiting endogenous components of NuRD. Yet knocking down NuRD components only reduces reprogramming modestly, in contrast to disrupting the known Sall4-NuRD interaction by mutating or deleting the NuRD interacting motif at its N-terminus that renders Sall4 inept to reprogram. Remarkably, these defects can be partially rescured by grafting NuRD interacting motif onto Jdp2. Further analysis of chromatin accessibility dynamics demonstrates that the Sall4-NuRD axis plays a critical role in closing the open chromatin in the early phase of reprogramming. Among the chromatin loci closed by Sall4-NuRD encode genes resistant to reprogramming. These results identify a previously unrecognized role of NuRD in reprogramming, and may further illuminate chromatin closing as a critical step in cell fate control.
Approaching enzymatic catalysis with zeolites or how to select one reaction mechanism competing with others
Authors: Ferri Pau , Li Chengeng , Schwalbe-Koda Daniel , Xie Mingrou , Moliner Manuel , Gómez-Bombarelli Rafael , Boronat Mercedes , Corma Avelino
Published: May 2023

Approaching the level of molecular recognition of enzymes with solid catalysts is a challenging goal, achieved in this work for the competing transalkylation and disproportionation of diethylbenzene catalyzed by acid zeolites. The key diaryl intermediates for the two competing reactions only differ in the number of ethyl substituents in the aromatic rings, and therefore finding a selective zeolite able to recognize this subtle difference requires an accurate balance of the stabilization of reaction intermediates and transition states inside the zeolite microporous voids. In this work we present a computational methodology that, by combining a fast high-throughput screeening of all zeolite structures able to stabilize the key intermediates with a more computationally demanding mechanistic study only on the most promising candidates, guides the selection of the zeolite structures to be synthesized. The methodology presented is validated experimentally and allows to go beyond the conventional criteria of zeolite shape-selectivity.
ADAR1-mediated RNA editing of SCD1 drives drug resistance and self-renewal in gastric cancer
Authors: Wong Tin-Lok , Loh Jia-Jian , Lu Shixun , Yan Helen H. N. , Siu Hoi Cheong , Xi Ren , Chan Dessy , Kam Max J. F. , Zhou Lei , Tong Man , Copland John A. , Chen Leilei , Yun Jing-Ping , Leung Suet Yi , Ma Stephanie
Published: May 2023

Targetable drivers governing 5-fluorouracil and cisplatin (5FU + CDDP) resistance remain elusive due to the paucity of physiologically and therapeutically relevant models. Here, we establish 5FU + CDDP resistant intestinal subtype GC patient-derived organoid lines. JAK/STAT signaling and its downstream, adenosine deaminases acting on RNA 1 (ADAR1), are shown to be concomitantly upregulated in the resistant lines. ADAR1 confers chemoresistance and self-renewal in an RNA editing-dependent manner. WES coupled with RNA-seq identify enrichment of hyper-edited lipid metabolism genes in the resistant lines. Mechanistically, ADAR1-mediated A-to-I editing on 3’UTR of stearoyl-CoA desaturase (SCD1) increases binding of KH domain-containing, RNA-binding, signal transduction-associated 1 (KHDRBS1), thereby augmenting SCD1 mRNA stability. Consequently, SCD1 facilitates lipid droplet formation to alleviate chemotherapy-induced ER stress and enhances self-renewal through increasing β-catenin expression. Pharmacological inhibition of SCD1 abrogates chemoresistance and tumor-initiating cell frequency. Clinically, high proteomic level of ADAR1 and SCD1, or high SCD1 editing/ADAR1 mRNA signature score predicts a worse prognosis. Together, we unveil a potential target to circumvent chemoresistance.
Efficient electrosynthesis of formamide from carbon monoxide and nitrite on a Ru-dispersed Cu nanocluster catalyst
Authors: Lan Jiao , Wei Zengxi , Lu Ying-Rui , Chen DeChao , Zhao Shuangliang , Chan Ting-Shan , Tan Yongwen
Published: May 2023

Conversion into high-value-added organic nitrogen compounds through electrochemical C-N coupling reactions under ambient conditions is regarded as a sustainable development strategy to achieve carbon neutrality and high-value utilization of harmful substances. Herein, we report an electrochemical process for selective synthesis of high-valued formamide from carbon monoxide and nitrite with a Ru1Cu single-atom alloy under ambient conditions, which achieves a high formamide selectivity with Faradaic efficiency of 45.65 ± 0.76% at −0.5 V vs. RHE. In situ X-ray absorption spectroscopy, coupled with in situ Raman spectroscopy and density functional theory calculations results reveal that the adjacent Ru-Cu dual active sites can spontaneously couple *CO and *NH2 intermediates to realize a critical C-N coupling reaction, enabling high-performance electrosynthesis of formamide. This work offers insight into the high-value formamide electrocatalysis through coupling CO and NO2− under ambient conditions, paving the way for the synthesis of more-sustainable and high-value chemical products.
Durable superhydrophobic coatings for prevention of rain attenuation of 5G/weather radomes
Authors: Wei Jinfei , Zhang Jiaojiao , Cao Xiaojun , Huo Jinhui , Huang Xiaopeng , Zhang Junping
Published: May 2023

Superhydrophobic coatings are expected to solve the rain attenuation issue of 5G radomes. However, it is very challenging to design and construct such superhydrophobic coatings with good impalement resistance, mechanical robustness, and weather resistance, which remains as one of the main bottlenecks hindering their practical applications. Here, we report the design of superhydrophobic coatings with all these merits mentioned above by spray-coating a suspension of adhesive/fluorinated silica core/shell microspheres onto substrates. The core/shell microspheres are formed by phase separation of the adhesive and adhesion between the adhesive and fluorinated silica nanoparticles. The coatings have an approximately isotropic three-tier hierarchical micro-/micro-/nanostructure, a dense but rough surface at the nanoscale, and chemically inert composition with low surface energy. Consequently, the coatings show excellent impalement resistance, mechanical robustness and weather resistance compared with previous studies, and the mechanisms are revealed. Furthermore, we realize large-scale preparation, extension, and practical application of the coatings for efficiently preventing rain attenuation of 5G/weather radomes. By taking these advantages, we believe that the superhydrophobic coatings have great application potential and market prospect. The findings here will boost preparation and real-world applications of superhydrophobic coatings.
VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation
Authors: Madec Simon , Irfan Kamran , Velumani Kaaviya , Baret Frederic , David Etienne , Daubige Gaetan , Samatan Lucas Bernigaud , Serouart Mario , Smith Daniel , James Chrisbin , Camacho Fernando , Guo Wei , De Solan Benoit , Chapman Scott C. , Weiss Marie
Published: May 2023

Applying deep learning to images of cropping systems provides new knowledge and insights in research and commercial applications. Semantic segmentation or pixel-wise classification, of RGB images acquired at the ground level, into vegetation and background is a critical step in the estimation of several canopy traits. Current state of the art methodologies based on convolutional neural networks (CNNs) are trained on datasets acquired under controlled or indoor environments. These models are unable to generalize to real-world images and hence need to be fine-tuned using new labelled datasets. This motivated the creation of the VegAnn - Vegetation Annotation - dataset, a collection of 3775 multi-crop RGB images acquired for different phenological stages using different systems and platforms in diverse illumination conditions. We anticipate that VegAnn will help improving segmentation algorithm performances, facilitate benchmarking and promote large-scale crop vegetation segmentation research.
67 million natural product-like compound database generated via molecular language processing
Authors: Tay Dillon W. P. , Yeo Naythan Z. X. , Adaikkappan Krishnan , Lim Yee Hwee , Ang Shi Jun
Published: May 2023

Natural products are a rich resource of bioactive compounds for valuable applications across multiple fields such as food, agriculture, and medicine. For natural product discovery, high throughput in silico screening offers a cost-effective alternative to traditional resource-heavy assay-guided exploration of structurally novel chemical space. In this data descriptor, we report a characterized database of 67,064,204 natural product-like molecules generated using a recurrent neural network trained on known natural products, demonstrating a significant 165-fold expansion in library size over the approximately 400,000 known natural products. This study highlights the potential of using deep generative models to explore novel natural product chemical space for high throughput in silico discovery.
Ten years of morphodynamic data at a micro-tidal urban beach: Cala Millor (Western Mediterranean Sea)
Authors: Fernández-Mora Angels , Criado-Sudau Francisco Fabian , Gómez-Pujol Lluís , Tintoré Joaquín , Orfila Alejandro
Published: May 2023

Systematic and sustained high quality measurements of nearshore waves and beach morphology are crucial to understand morphodynamic processes that determine beach evolution, to unravel the effects of global warming on sandy coasts and thus improve forecasting models. In 2011 a comprehensive beach monitoring program, the first in the Mediterranean Sea, started at Cala Millor Beach on the island of Mallorca (Spain). The aim was to provide long-term datasets of near-shore morphodynamics in a carbonate sandy micro-tidal and semi-embayed beach fronted by a Posidonia oceanica seagrass meadow. We present our morphological and hydrodynamical dataset of Cala Millor covering more than a decade. The dataset includes topobathymetries, shoreline positions obtained from video cameras, meteorological parameters from a weather station, currents, as well as waves and sea level from ADCP measurements and sediment size. This free and unrestricted archived dataset can be used to support the modelling of erosion-deposition patterns, calibrate beach evolution models, and as a result to propose adaptation and mitigation actions under different global change scenarios.
FOPPA: an open database of French public procurement award notices from 2010–2020
Authors: Potin Lucas , Labatut Vincent , Morand Pierre-Henri , Largeron Christine
Published: May 2023

Public Procurement refers to governments’ purchasing activities of goods, services, and construction of public works. In the European Union (EU), it is an essential sector, corresponding to 15% of the GDP. EU public procurement generates large amounts of data, because award notices related to contracts exceeding a predefined threshold must be published on the TED (EU’s official journal). Under the framework of the DeCoMaP project, which aims at leveraging such data in order to predict fraud in public procurement, we constitute the FOPPA (French Open Public Procurement Award notices) database. It contains the description of 1,380,965 lots obtained from the TED, covering the 2010–2020 period for France. We detect a number of substantial issues in these data, and propose a set of automated and semi-automated methods to solve them and produce a usable database. It can be leveraged to study public procurement in an academic setting, but also to facilitate the monitoring of public policies, and to improve the quality of the data offered to buyers and suppliers.
Biophotonic sensor for swift detection of malignant brain tissues by using nanocomposite YBa2Cu3O7/dielectric material as a 1D defective photonic crystal
Authors: Malek C. , Abdallah Suhad Ali Osman , Awasthi S. K. , Ismail M. A. , Sabra W. , Aly Arafa H.
Published: May 2023

In the present research work we have theoretically examined the biosensing capabilities of proposed one dimensional defective photonic crystal for swift detection of malignant brain tissues. The transfer matrix formulation and MATLAB computational tool have been used to examine the transmission properties of proposed structure. The identical buffer layers of nanocomposite superconducting material have been used either side of cavity region to enhance the interaction between incident light and different brain tissue samples poured into the cavity region. All the investigations have been carried out under normal incidence to suppress the experimental liabilities involved. We have investigated the biosensing performance of the proposed design by changing the values of two internal parameters (1) the cavity layer thickness (d4) and (2) volume fraction (η) of nanocomposite buffer layers one by one to get the optimum biosensing performance from the structure. It has been found that the sensitivity of the proposed design becomes 1.42607 μm/RIU when the cavity region of thickness 15dd is loaded with lymphoma brain tissue. This value of sensitivity can be further increased to 2.66136 μm/RIU with η = 0.8. The findings of this work are very beneficial for designing of various bio-sensing structures composed of nanocomposite materials of diversified biomedical applications.
Self-modulation of rectus femoris reflex excitability in humans
Authors: Kim Kyoungsoon , Akbas Tunc , Lee Robert , Manella Kathleen , Sulzer James
Published: May 2023

Hyperreflexia is common after neurological injury such as stroke, yet clinical interventions have had mixed success. Our previous research has shown that hyperreflexia of the rectus femoris (RF) during pre-swing is closely associated with reduced swing phase knee flexion in those with post-stroke Stiff-Knee gait (SKG). Thus, reduction of RF hyperreflexia may improve walking function in those with post-stroke SKG. A non-pharmacological procedure for reducing hyperreflexia has emerged based on operant conditioning of H-reflex, an electrical analog of the spinal stretch reflex. It is currently unknown whether operant conditioning can be applied to the RF. This feasibility study trained 7 participants (5 neurologically intact, 2 post-stroke) to down-condition the RF H-reflex using visual feedback. We found an overall decrease in average RF H-reflex amplitude among all 7 participants (44% drop, p < 0.001, paired t-test), of which the post-stroke individuals contributed (49% drop). We observed a generalized training effect across quadriceps muscles. Post-stroke individuals exhibited improvements in peak knee-flexion velocity, reflex excitability during walking, and clinical measures of spasticity. These outcomes provide promising initial results that operant RF H-reflex conditioning is feasible, encouraging expansion to post-stroke individuals. This procedure could provide a targeted alternative in spasticity management.
Ivermectin metabolites reduce Anopheles survival
Authors: Kobylinski Kevin C. , Tipthara Phornpimon , Wamaket Narenrit , Chainarin Sittinont , Kullasakboonsri Rattawan , Sriwichai Patchara , Phasomkusolsil Siriporn , Hanboonkunupakarn Borimas , Jittamala Podjanee , Gemmell Renia , Boyle John , Wrigley Stephen , Steele Jonathan , White Nicholas J. , Tarning Joel
Published: May 2023

Ivermectin mass drug administration to humans or livestock is a potential vector control tool for malaria elimination. The mosquito-lethal effect of ivermectin in clinical trials exceeds that predicted from in vitro laboratory experiments, suggesting that ivermectin metabolites have mosquito-lethal effect. The three primary ivermectin metabolites in humans (i.e., M1 (3″-O-demethyl ivermectin), M3 (4-hydroxymethyl ivermectin), and M6 (3″-O-demethyl, 4-hydroxymethyl ivermectin) were obtained by chemical synthesis or bacterial modification/metabolism. Ivermectin and its metabolites were mixed in human blood at various concentrations, blood-fed to Anopheles dirus and Anopheles minimus mosquitoes, and mortality was observed daily for fourteen days. Ivermectin and metabolite concentrations were quantified by liquid chromatography linked with tandem mass spectrometry to confirm the concentrations in the blood matrix. Results revealed that neither the LC50 nor LC90 values differed between ivermectin and its major metabolites for An. dirus or An. minimus., Additionally, there was no substantial differences in the time to median mosquito mortality when comparing ivermectin and its metabolites, demonstrating an equal rate of mosquito killing between the compounds evaluated. These results demonstrate that ivermectin metabolites have a mosquito-lethal effect equal to the parent compound, contributing to Anopheles mortality after treatment of humans.
Earthquake-induced soil landslides: volume estimates and uncertainties with the existing scaling exponents
Authors: Yunus Ali P. , Xinyu Chen , Catani Filippo , Subramaniam Srikrishnan Siva , Fan Xuanmei , Jie Dou , Sajinkumar K. S. , Gupta Ankita , Avtar Ram
Published: May 2023

Quantifying landslide volumes in earthquake affected areas is critical to understand the orogenic processes and their surface effects at different spatio-temporal scales. Here, we build an accurate scaling relationship to estimate the volume of shallow soil landslides based on 1 m pre- and post-event LiDAR elevation models. On compiling an inventory of 1719 landslides for 2018 Mw 6.6 Hokkaido-Iburi earthquake epicentral region, we find that the volume of soil landslides can be estimated by γ = 1.15. The total volume of eroded debris from Hokkaido-Iburi catchments based on this new scaling relationship is estimated as 64–72 million m3. Based on the GNSS data approximation, we noticed that the co-seismic uplift volume is smaller than the eroded volume, suggesting that frequent large earthquakes (and rainfall extremes) may be counterbalancing the topographic uplift through erosion by landslides, especially in humid landscapes such as Japan, where soil properties are rather weak.
Intra-pulse difference frequency generation in ZnGeP2 for high-frequency terahertz radiation generation
Authors: Carnio B. N. , Zhang M. , Zawilski K. T. , Schunemann P. G. , Moutanabbir O. , Elezzabi A. Y.
Published: May 2023

The highly-nonlinear chalcopyrite crystal family has experienced remarkable success as source crystals in the mid-infrared spectral range, such that these crystals are primary candidates for producing high terahertz frequency (i.e., $$\gtrsim$$
≳
10 THz) electric fields. A phase-resolved terahertz electric field pulse is produced via intra-pulse difference frequency generation in a chalcopyrite (110) ZnGeP2 crystal, with phase-matching being satisfied by the excitation electric field pulse having polarizations along both the ordinary and extraordinary crystal axes. While maximum spectral power is observed at the frequency of 24.5 THz (in agreement with intra-pulse phase-matching calculations), generation nonetheless occurs across the wide spectral range of 23–30 THz. To our knowledge, this is the first time a chalcopyrite ZnGeP2 crystal has been used for the generation of phase-resolved high-frequency terahertz electric fields.
Bayesian forecasting of disease spread with little or no local data
Authors: Cook Jonathan D. , Williams David M. , Walsh Daniel P. , Hefley Trevor J.
Published: May 2023

Rapid and targeted management actions are a prerequisite to efficiently mitigate disease outbreaks. Targeted actions, however, require accurate spatial information on disease occurrence and spread. Frequently, targeted management actions are guided by non-statistical approaches that define the affected area by a pre-determined distance surrounding a small number of disease detections. As an alternative, we present a long-recognized but underutilized Bayesian technique that uses limited local data and informative priors to make statistically valid predictions and forecasts about disease occurrence and spread. As a case study, we use limited local data that were available after the detection of chronic wasting disease in Michigan, U.S. along with information rich priors obtained from a previous study in a neighboring state. Using these limited local data and informative priors, we generate statistically valid predictions of disease occurrence and spread for the Michigan study area. This Bayesian technique is conceptually and computationally simple, relies on little to no local data, and is competitive with non-statistical distance-based metrics in all performance evaluations. Bayesian modeling has added benefits because it allows practitioners to generate immediate forecasts of future disease conditions and provides a principled framework to incorporate new data as they accumulate. We contend that the Bayesian technique offers broad-scale benefits and opportunities to make statistical inference across a diversity of data-deficient systems, not limited to disease.
Discovery of andrographolide hit analog as a potent cyclooxygenase-2 inhibitor through consensus MD-simulation, electrostatic potential energy simulation and ligand efficiency metrics
Authors: Jain Priyanka , Satija Jitendra , Sudandiradoss C.
Published: May 2023

Cyclooxygenase-2 (COX-2) is the key enzyme responsible for the conversion of arachidonic acid to prostaglandins that display pro-inflammatory properties and thus, it is a potential target protein to develop anti-inflammatory drugs. In this study, chemical and bio-informatics approaches have been employed to find a novel potent andrographolide (AGP) analog as a COX-2 inhibitor having better pharmacological properties than aspirin and rofecoxib (controls). The full amino acid sequenced human Alpha fold (AF) COX-2 protein (604AA) was selected and validated for its accuracy against the reported COX-2 protein structures (PDB ID: 5F19, 5KIR, 5F1A, 5IKQ and 1V0X) followed by multiple sequence alignment analysis to establish the sequence conservation. The systematic virtual screening of 237 AGP analogs against AF-COX-2 protein yielded 22 lead compounds based on the binding energy score (< − 8.0 kcal/mol). These were further screened out to 7 analogs by molecular docking analysis and investigated further for ADMET prediction, ligand efficiency metrics calculations, quantum mechanical analysis, MD simulation, electrostatic potential energy (EPE) docking simulation, and MM/GBSA. In-depth analysis revealed that AGP analog A3 (3-[2-[(1R,4aR,5R,6R,8aR)-6-hydroxy-5,6,8a-trimethyl-2-methylidene-3,4,4a,5,7,8-hexahydro-1H-naphthalen-1-yl]ethylidene]-4-hydroxyoxolan-2-one) forms the most stable complex with the AF-COX-2 showing the least RMSD value (0.37 ± 0.03 nm), a good number of hydrogen bonds (protein–ligand H-bond = 11, and protein H-bond = 525), minimum EPE score (− 53.81 kcal/mol), and lowest MM-GBSA before and after simulation (− 55.37 and − 56.25 kcal/mol, respectively) value compared to other analogs and controls. Thus, we suggest that the identified A3 AGP analog could be developed as a promising plant-based anti-inflammatory drug by inhibiting COX-2.
Prosaposin PS18 reduces dopaminergic neurodegeneration in a 6-hydroxydopamine rat model of Parkinson’s disease
Authors: Wu Kuo-Jen , Hung Tsai-Wei , Wang Yu-Syuan , Chen Yun-Hsiang , Bae Eun-Kyung , Yu Seong-Jin
Published: May 2023

Saposin and its precursor prosaposin are endogenous proteins with neurotrophic and anti-apoptotic properties. Prosaposin or its analog prosaposin-derived 18-mer peptide (PS18) reduced neuronal damage in hippocampus and apoptosis in stroke brain. Its role in Parkinson’s disease (PD) has not been well characterized. This study aimed to examine the physiological role of PS18 in 6-hydroxydopamine (6-OHDA) cellular and animal models of PD. We found that PS18 significantly antagonized 6-OHDA -mediated dopaminergic neuronal loss and TUNEL in rat primary dopaminergic neuronal culture. In SH-SY5Y cells overexpressing the secreted ER calcium—monitoring proteins, we found that PS18 significantly reduced thapsigargin and 6-OHDA-mediated ER stress. The expression of prosaposin and the protective effect of PS18 were next examined in hemiparkinsonian rats. 6-OHDA was unilaterally administered to striatum. The expression of prosaposin was transiently upregulated in striatum on D3 (day 3) after lesioning and returned below the basal level on D29. The 6-OHDA-lesioned rats developed bradykinesia and an increase in methamphetamine-mediated rotation, which was antagonized by PS18. Brain tissues were collected for Western blot, immunohistochemistry, and qRTPCR analysis. Tyrosine hydroxylase immunoreactivity was significantly reduced while the expressions of PERK, ATF6, CHOP, and BiP were upregulated in the lesioned nigra; these responses were significantly antagonized by PS18. Taken together, our data support that PS18 is neuroprotective in cellular and animal models of PD. The mechanisms of protection may involve anti-ER stress.
The perception of COVID-19, the Light Triad, harmony and ethical sensitivity in late adolescents: The role of meaning-making and stress
Authors: Krok Dariusz , Zarzycka Beata , Telka Ewa
Published: May 2023

The experiences of inner harmony and ethical sensitivity among late adolescents during the COVID-19 pandemic depend on the interplay of perceptive factors, personal resources and cognitive and stress mechanisms. Using a sample from Poland, the present study examined the relationships between the perceptions of COVID-19 and the Light Triad and the characteristics of inner harmony and ethical sensitivity from the mediational perspective of meaning-making and perceived stress. Three hundred and sixteen late adolescents were recruited in the cross-sectional study. They filled in questionnaires measuring the perception of COVID-19, the Light Triad, meaning-making, stress, inner harmony and ethical sensitivity, from April to September 2020. The perception of COVID-19 was negatively related to ethical sensitivity, whereas the Light Triad was positively related to inner harmony and ethical sensitivity. Perceived stress and meaning-making mediated the relationships between the perceptions of COVID-19, the Light Triad and the characteristic of inner harmony. Perception processes and the Light Triad dimensions directly influence ethical sensitivity, as well as indirectly affect inner harmony through meaning-making processes and perceived stress. This noticeably highlights the vital role played by meaning structures and emotional reactions in the experience of inner peace and calmness.
Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system
Authors: Mu Qianqian , Long Fei , Li Bin
Published: May 2023

This paper investigates the adaptive neural network prescribed performance control problem for a class of dual switching nonlinear systems with time-delay. By using the approximation of neural networks (NNs), an adaptive controller is designed to achieve tracking performance. Another research point of this paper is tracking performance constraints which can solve the performance degradation in practical systems. Therefore, an adaptive NNs output feedback tracking scheme is studied by combining the prescribed performance control (PPC) and backstepping method. With the designed controller and the switching rule, all signals of the closed-loop system are bounded, and the tracking performance satisfies the prescribed performance.
Development, fabrication and mechanical characterisation of auxetic bicycle handlebar grip
Authors: Novak Nejc , Plesec Vasja , Harih Gregor , Cupar Andrej , Kaljun Jasmin , Vesenjak Matej
Published: May 2023

The auxetic cellular structures are one of the most promising metamaterials for vibration damping and crash absorption applications. Therefore, their use in the bicycle handlebar grip was studied in this work. A preliminary computational design study was performed using various auxetic and non-auxetic geometries under four load cases, which can typically appear. The most representative geometries were then selected and fabricated using additive manufacturing. These geometries were then experimentally tested to validate the discrete and homogenised computational models. The homogenised computational model was then used to analyse the biomechanical behaviour of the handlebar grip. It was observed that handle grip made from auxetic cellular metamaterials reduce the high contact pressures, provide similar stability and hereby improve the handlebar ergonomics.
Comparative analysis of productive performance and fattening efficiency of commercial pigs in China for two consecutive years
Authors: Guan Ran , Wu Junqiang , Wang Yunzhou , Cai Qian , Li Xiaowen
Published: May 2023

The purpose of this study: (1) propose an evaluation indicator of the fattening efficiency of commercial pigs (Yorkshire × Landrace × Duroc)—fattening efficiency index (FEI). (2) Analyze the correlation to find the main productive factors affecting the FEI. (3) Compare and analyze the yearly/monthly/different piglets’ sources of productive performance in 2020 and 2021. The data included 2592 commercial pig batches in 2020 and 3266 in 2021, with a total of 6,134,234 commercial pigs. Descriptive statistics and difference analysis were carried out on 16 productive factors of a whole year and single/multiple sources for two consecutive years. The same period difference between the monthly data and the annual average were also analyzed. The top six productive factors correlated with FEI were average daily gain (ADG) (0.8080), feed conversion rate (FCR) (− 0.7203), survival rate (SR) (0.6968), number of deaths (− 0.4103), feeding days (− 0.3748) and body weight (BW) of marketing pigs (0.3369). The overall productive performance in 2021 was lower than that in 2020, which was reflected in more piglet sources and a lower BW of piglets, more deaths, a lower SR, longer feeding days, a lower ADG, a higher FCR and a lower FEI. The productive performance of a single source was better than that of multiple ones. The contrastive results of monthly data in 2020 and 2021 showed significant differences in most factors except for the number of marketing pigs, the number of piglets and feed consumption. The monthly trend of 15 factors for two consecutive years revealed similar trends only in the month of piglets purchasing, number of piglets sources, number of deaths and ADG. Compared with the annual average, the ADG significantly increased in May. The FEI of multiple sources was markedly lower than that of a single source. FEI may be suitable for evaluating the fattening efficiency of commercial pigs. The annual and monthly productive performance and fattening efficiency in 2021 were significantly lower than those in 2020. Single source was represented better productive performance and fattening efficiency than multiple ones.
Ontologizing health systems data at scale: making translational discovery a reality
Authors: Callahan Tiffany J. , Stefanski Adrianne L. , Wyrwa Jordan M. , Zeng Chenjie , Ostropolets Anna , Banda Juan M. , Baumgartner William A. , Boyce Richard D. , Casiraghi Elena , Coleman Ben D. , Collins Janine H. , Deakyne Davies Sara J. , Feinstein James A. , Lin Asiyah Y. , Martin Blake , Matentzoglu Nicolas A. , Meeker Daniella , Reese Justin , Sinclair Jessica , Taneja Sanya B. , Trinkley Katy E. , Vasilevsky Nicole A. , Williams Andrew E. , Zhang Xingmin A. , Denny Joshua C. , Ryan Patrick B. , Hripcsak George , Bennett Tellen D. , Haendel Melissa A. , Robinson Peter N. , Hunter Lawrence E. , Kahn Michael G.
Published: May 2023

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68–99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.
Predicting 3D soft tissue dynamics from 2D imaging using physics informed neural networks
Authors: Movahhedi Mohammadreza , Liu Xin-Yang , Geng Biao , Elemans Coen , Xue Qian , Wang Jian-Xun , Zheng Xudong
Published: May 2023

Tissue dynamics play critical roles in many physiological functions and provide important metrics for clinical diagnosis. Capturing real-time high-resolution 3D images of tissue dynamics, however, remains a challenge. This study presents a hybrid physics-informed neural network algorithm that infers 3D flow-induced tissue dynamics and other physical quantities from sparse 2D images. The algorithm combines a recurrent neural network model of soft tissue with a differentiable fluid solver, leveraging prior knowledge in solid mechanics to project the governing equation on a discrete eigen space. The algorithm uses a Long-short-term memory-based recurrent encoder-decoder connected with a fully connected neural network to capture the temporal dependence of flow-structure-interaction. The effectiveness and merit of the proposed algorithm is demonstrated on synthetic data from a canine vocal fold model and experimental data from excised pigeon syringes. The results showed that the algorithm accurately reconstructs 3D vocal dynamics, aerodynamics, and acoustics from sparse 2D vibration profiles.
The drivers of plant community composition have shifted from external to internal processes over the past 20,000 years
Authors: Doncaster C. Patrick , Edwards Mary E. , Clarke Charlotte L. , Alsos Inger Greve
Published: May 2023

Internal and external factors regulating the past composition of plant communities are difficult to identify in palaeo-vegetation records. Here, we develop an index of relative entropy of community assembly, which applies to changes in the composition of a community over time, measuring disorder in its assembly relative to disassembly. Historical periods of relatively ordered assembly (negative index values) are characteristic of a community undergoing endogenous self-organisation, in contrast to relatively disordered assembly (positive values) characterising periods of exogenous abiotic forcing. We quantified the relative entropy index for a 22,000-year time-series of tundra vegetation obtained in the Polar Urals, based on sedimentary DNA. We find it most positive during the Late Pleistocene characterized by persistent taxa, and most negative during the post-glacial Holocene characterized by more ephemeral floras. Changes in relative entropy coincide with changes in regional temperature as reconstructed from stable oxygen composition of an Arctic ice-core. Our results suggest that temperature strongly influenced community assembly in the Polar Urals until about 9000 years before present, after which endogenous community self-organization prevailed through to the present. We conclude that time-series of community composition can reveal changes in the balance between internal and external influences on taxonomic turnover and resulting diversity.
Autumn canopy senescence has slowed down with global warming since the 1980s in the Northern Hemisphere
Authors: Zhang Yichen , Hong Songbai , Liu Qiang , Huntingford Chris , Peñuelas Josep , Rossi Sergio , Myneni Ranga B. , Piao Shilong
Published: May 2023

Climate change strongly impact vegetation phenology, with considerable potential to alter land-atmosphere carbon dioxide exchange and terrestrial carbon cycle. In contrast to well-studied spring leaf-out, the timing and magnitude of autumn senescence remains poorly understood. Here, we use monthly decreases in Normalized Difference Vegetation Index satellite retrievals and their trends to surrogate the speed of autumn senescence during 1982–2018 in the Northern Hemisphere (>30°N). We find that climate warming accelerated senescence in July, but this influence usually reversed in later summer and early autumn. Interestingly, summer greening causes canopy senescence to appear later compared to an advancing trend after eliminating the greening effect. This finding suggests that summer canopy greening may counteract the intrinsic changes in autumnal leaf senescence. Our analysis of autumn vegetation behavior provides reliable guidance for developing and parameterizing land surface models that contain an interactive dynamic vegetation module for placement in coupled Earth System Models.
Neural network based prediction of the efficacy of ball milling to separate cable waste materials
Authors: Lu Jiaqi , Han Mengqi , Kumagai Shogo , Li Guanghui , Yoshioka Toshiaki
Published: May 2023

Material recycling technologies are essential for achieving a circular economy while reducing greenhouse gas emissions. However, most of them remain in laboratory development. Machine learning (ML) can promote industrial application while maximising yield and environmental performance. Herein, an asynchronous-parallel recurrent neural network was developed to predict the dynamic behaviour when separating copper and poly(vinyl chloride) components from the cable waste. The model was trained with six datasets (treatment conditions) at 3600 epochs. High accuracy was confirmed based on a mean-square error of 0.0015–0.0145 between the prediction and experimental results. The quantitative relationship between the input features and the separation yield was identified using sensitivity analysis. The charged weight of cables and impact energy were determined as the critical factors affecting the separation efficiency. The ML framework can be widely applied to recycling technologies to reveal the process mechanism and establish a quantitative relationship between process variables and treatment outputs.
Introduction: Biotechnology—An Ever Expanding Toolbox for Medicine
Authors: Marks Lara V.
Published: May 2023

Biotechnology is one of the hottest growth areas in medicine today. It is central to both the diagnosis and treatment of disease. This chapter provides an overview of the application of biotechnology to medicine from the early twentieth century to the present day. It begins by looking at how DNA first became associated with disease in the mid twentieth century and then moves on to explore a number of different biotechnological tools that have become important in medicine. As this chapter shows, this has not always been a straightforward process. Indeed, some of the developments, notably genetic engineering, stem cell therapy and gene therapy, have been dogged by controversy. In addition, a number of the new treatments aided by biotechnology pose significant challenges to traditional modes of production. Furthermore, they have greatly increased the cost of healthcare.
Biopharmaceutical Proteins: The Manufacturing Challenge
Authors: Alldread Richard , Birch John
Published: May 2023

The biopharmaceutical industry is one of global importance and has driven the growth of the pharmaceutical industry over the last 20 years. This industry is responsible for the production of medicinal products manufactured in, extracted from, or semi-synthesised from biological sources. It has supplied innovative medicines to treat some of the most serious and debilitating diseases where conventional pharmaceuticals have proven ineffective. However, the development of the industry has not been easy and has relied on multiple advances in biology, biotechnology, analytical science and engineering. By making use of a broad range of technologies it is now possible to develop and manufacture highly complex biopharmaceuticals in an efficient, robust and economic manner. This chapter focuses on biopharmaceutical proteins, which are a key component in healthcare today. Their success would not have been possible without major developments in technology to manufacture them. Here we look at the manufacturing challenges and the techniques developed to make and purify proteins from a range of different types of organism. Such manufacturing technology, as we shall see, is now facing new hurdles with the increasing need to reduce the costs of healthcare and demand for more lower-priced drugs and more sophisticated and effective treatments with higher quality.
Vaccines: The Recombinant Revolution
Authors: Buckland Barry C.
Published: May 2023

Methods used to develop vaccines have undergone a revolution driven by the emergence of technology to create recombinant DNA. This chapter traces the history of the adoption of recombinant DNA in vaccine development and production and the challenges that were involved. The first time the technology was used was for a vaccine to prevent Hepatitis B infections. Its deployment not only helped improve the safety and efficacy of the vaccine, originally made from the blood of previously infected individuals, but also reduced its cost by enabling large-scale manufacture of the vaccine. Overall the technology helped transform what had started off as a highly specialized and difficult to manufacture product, only given to health practitioners, into a very safe and inexpensive vaccine that could be made available to most infants around the world. Another vaccine examined in this chapter is the one developed against the human papilloma virus, where recombinant DNA facilitated the development of a vaccine based on a virus-like particle. The final vaccine considered is for influenza, now being developed with a particular protein from the virus which is revolutionizing the ability to quickly respond to threatening new strains of the virus instead of having to adapt the virulent virus to safe propagation in cell culture.