bluuebunny/crossref_metadata_2025 huggingface dataset:
An axonemal intron splicing program sustains Plasmodium male development
Authors: Guan Jiepeng , Wu Peijia , Mo Xiaoli , Zhang Xiaolong , Liang Wenqi , Zhang Xiaoming , Jiang Lubin , Li Jian , Cui Huiting , Yuan Jing
Published: June 2024

Differentiation of male gametocytes into flagellated fertile male gametes relies on the assembly of axoneme, a major component of male development for mosquito transmission of the malaria parasite. RNA-binding protein (RBP)-mediated post-transcriptional regulation of mRNA plays important roles in eukaryotic sexual development, including the development of female Plasmodium. However, the role of RBP in defining the Plasmodium male transcriptome and its function in male gametogenesis remains incompletely understood. Here, we performed genome-wide screening for gender-specific RBPs and identified an undescribed male-specific RBP gene Rbpm1 in the Plasmodium. RBPm1 is localized in the nucleus of male gametocytes. RBPm1-deficient parasites fail to assemble the axoneme for male gametogenesis and thus mosquito transmission. RBPm1 interacts with the spliceosome E complex and regulates the splicing initiation of certain introns in a group of 26 axonemal genes. RBPm1 deficiency results in intron retention and protein loss of these axonemal genes. Intron deletion restores axonemal protein expression and partially rectifies axonemal defects in RBPm1-null gametocytes. Further splicing assays in both reporter and endogenous genes exhibit stringent recognition of the axonemal introns by RBPm1. The splicing activator RBPm1 and its target introns constitute an axonemal intron splicing program in the post-transcriptional regulation essential for Plasmodium male development.
Machine intelligence accelerated design of conductive MXene aerogels with programmable properties
Authors: Shrestha Snehi , Barvenik Kieran James , Chen Tianle , Yang Haochen , Li Yang , Kesavan Meera Muthachi , Little Joshua M. , Whitley Hayden C. , Teng Zi , Luo Yaguang , Tubaldi Eleonora , Chen Po-Yen
Published: June 2024

Designing ultralight conductive aerogels with tailored electrical and mechanical properties is critical for various applications. Conventional approaches rely on iterative, time-consuming experiments across a vast parameter space. Herein, an integrated workflow is developed to combine collaborative robotics with machine learning to accelerate the design of conductive aerogels with programmable properties. An automated pipetting robot is operated to prepare 264 mixtures of Ti3C2Tx MXene, cellulose, gelatin, and glutaraldehyde at different ratios/loadings. After freeze-drying, the aerogels’ structural integrity is evaluated to train a support vector machine classifier. Through 8 active learning cycles with data augmentation, 162 unique conductive aerogels are fabricated/characterized via robotics-automated platforms, enabling the construction of an artificial neural network prediction model. The prediction model conducts two-way design tasks: (1) predicting the aerogels’ physicochemical properties from fabrication parameters and (2) automating the inverse design of aerogels for specific property requirements. The combined use of model interpretation and finite element simulations validates a pronounced correlation between aerogel density and compressive strength. The model-suggested aerogels with high conductivity, customized strength, and pressure insensitivity allow for compression-stable Joule heating for wearable thermal management.
Co-aggregation with Apolipoprotein E modulates the function of Amyloid-β in Alzheimer’s disease
Authors: Xia Zengjie , Prescott Emily E. , Urbanek Agnieszka , Wareing Hollie E. , King Marianne C. , Olerinyova Anna , Dakin Helen , Leah Tom , Barnes Katy A. , Matuszyk Martyna M. , Dimou Eleni , Hidari Eric , Zhang Yu P. , Lam Jeff Y. L. , Danial John S. H. , Strickland Michael R. , Jiang Hong , Thornton Peter , Crowther Damian C. , Ohtonen Sohvi , Gómez-Budia Mireia , Bell Simon M. , Ferraiuolo Laura , Mortiboys Heather , Higginbottom Adrian , Wharton Stephen B. , Holtzman David M. , Malm Tarja , Ranasinghe Rohan T. , Klenerman David , De Suman
Published: June 2024

Which isoforms of apolipoprotein E (apoE) we inherit determine our risk of developing late-onset Alzheimer’s Disease (AD), but the mechanism underlying this link is poorly understood. In particular, the relevance of direct interactions between apoE and amyloid-β (Aβ) remains controversial. Here, single-molecule imaging shows that all isoforms of apoE associate with Aβ in the early stages of aggregation and then fall away as fibrillation happens. ApoE-Aβ co-aggregates account for ~50% of the mass of diffusible Aβ aggregates detected in the frontal cortices of homozygotes with the higher-risk APOE4 gene. We show how dynamic interactions between apoE and Aβ tune disease-related functions of Aβ aggregates throughout the course of aggregation. Our results connect inherited APOE genotype with the risk of developing AD by demonstrating how, in an isoform- and lipidation-specific way, apoE modulates the aggregation, clearance and toxicity of Aβ. Selectively removing non-lipidated apoE4-Aβ co-aggregates enhances clearance of toxic Aβ by glial cells, and reduces secretion of inflammatory markers and membrane damage, demonstrating a clear path to AD therapeutics.
Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling
Authors: Ruan Zhepu , Chen Kai , Cao Weimiao , Meng Lei , Yang Bingang , Xu Mengjun , Xing Youwen , Li Pengfa , Freilich Shiri , Chen Chen , Gao Yanzheng , Jiang Jiandong , Xu Xihui
Published: June 2024

Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.
Diffusion-based deep learning method for augmenting ultrastructural imaging and volume electron microscopy
Authors: Lu Chixiang , Chen Kai , Qiu Heng , Chen Xiaojun , Chen Gu , Qi Xiaojuan , Jiang Haibo
Published: June 2024

Electron microscopy (EM) revolutionized the way to visualize cellular ultrastructure. Volume EM (vEM) has further broadened its three-dimensional nanoscale imaging capacity. However, intrinsic trade-offs between imaging speed and quality of EM restrict the attainable imaging area and volume. Isotropic imaging with vEM for large biological volumes remains unachievable. Here, we developed EMDiffuse, a suite of algorithms designed to enhance EM and vEM capabilities, leveraging the cutting-edge image generation diffusion model. EMDiffuse generates realistic predictions with high resolution ultrastructural details and exhibits robust transferability by taking only one pair of images of 3 megapixels to fine-tune in denoising and super-resolution tasks. EMDiffuse also demonstrated proficiency in the isotropic vEM reconstruction task, generating isotropic volume even in the absence of isotropic training data. We demonstrated the robustness of EMDiffuse by generating isotropic volumes from seven public datasets obtained from different vEM techniques and instruments. The generated isotropic volume enables accurate three-dimensional nanoscale ultrastructure analysis. EMDiffuse also features self-assessment functionalities on predictions’ reliability. We envision EMDiffuse to pave the way for investigations of the intricate subcellular nanoscale ultrastructure within large volumes of biological systems.
Redox dynamics and surface structures of an active palladium catalyst during methane oxidation
Authors: Yue Shengnan , Praveen C. S. , Klyushin Alexander , Fedorov Alexey , Hashimoto Masahiro , Li Qian , Jones Travis , Liu Panpan , Yu Wenqian , Willinger Marc-Georg , Huang Xing
Published: June 2024

Catalysts based on palladium are among the most effective in the complete oxidation of methane. Despite extensive studies and notable advances, the nature of their catalytically active species and conceivable structural dynamics remains only partially understood. Here, we combine operando transmission electron microscopy (TEM) with near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) and density functional theory (DFT) calculations to investigate the active state and catalytic function of Pd nanoparticles (NPs) under methane oxidation conditions. We show that the particle size, phase composition and dynamics respond appreciably to changes in the gas-phase chemical potential. In combination with mass spectrometry (MS) conducted simultaneously with in situ observations, we uncover that the catalytically active state exhibits phase coexistence and oscillatory phase transitions between Pd and PdO. Aided by DFT calculations, we provide a rationale for the observed redox dynamics and demonstrate that the emergence of catalytic activity is related to the dynamic interplay between coexisting phases, with the resulting strained PdO having more favorable energetics for methane oxidation.
Insight into selectivity of photocatalytic methane oxidation to formaldehyde on tungsten trioxide
Authors: Fan Yingying , Jiang Yuheng , Lin Haiting , Li Jianan , Xie Yuanjiang , Chen Anyi , Li Siyang , Han Dongxue , Niu Li , Tang Zhiyong
Published: June 2024

Tungsten trioxide (WO3) has been recognized as the most promising photocatalyst for highly selective oxidation of methane (CH4) to formaldehyde (HCHO), but the origin of catalytic activity and the reaction manner remain controversial. Here, we take {001} and {110} facets dominated WO3 as the model photocatalysts. Distinctly, {001} facet can readily achieve 100% selectivity of HCHO via the active site mechanism whereas {110} facet hardly guarantees a high selectivity of HCHO along with many intermediate products via the radical way. In situ diffuse reflectance infrared Fourier transform spectroscopy, electron paramagnetic resonance and theoretical calculations confirm that the competitive chemical adsorption between CH4 and H2O and the different CH4 activation routes on WO3 surface are responsible for diverse CH4 oxidation pathways. The microscopic mechanism elucidation provides the guidance for designing high performance photocatalysts for selective CH4 oxidation.
Nutrient levels control root growth responses to high ambient temperature in plants
Authors: Lee Sanghwa , Showalter Julia , Zhang Ling , Cassin-Ross Gaëlle , Rouached Hatem , Busch Wolfgang
Published: June 2024

Global warming will lead to significantly increased temperatures on earth. Plants respond to high ambient temperature with altered developmental and growth programs, termed thermomorphogenesis. Here we show that thermomorphogenesis is conserved in Arabidopsis, soybean, and rice and that it is linked to a decrease in the levels of the two macronutrients nitrogen and phosphorus. We also find that low external levels of these nutrients abolish root growth responses to high ambient temperature. We show that in Arabidopsis, this suppression is due to the function of the transcription factor ELONGATED HYPOCOTYL 5 (HY5) and its transcriptional regulation of the transceptor NITRATE TRANSPORTER 1.1 (NRT1.1). Soybean and Rice homologs of these genes are expressed consistently with a conserved role in regulating temperature responses in a nitrogen and phosphorus level dependent manner. Overall, our data show that root thermomorphogenesis is a conserved feature in species of the two major groups of angiosperms, monocots and dicots, that it leads to a reduction of nutrient levels in the plant, and that it is dependent on environmental nitrogen and phosphorus supply, a regulatory process mediated by the HY5-NRT1.1 module.
Electrochemical characteristics and damage mechanism in scrubber washing water of UNS N08367 with plasma ion nitriding and electropolishing
Authors: Hwang Hyun-Kyu , Kim Seong-Jong
Published: June 2024

In this investigation, electropolishing and plasma ion nitriding are applied to super austenitic stainless steel for the purpose of improving its corrosion and pitting resistance. Electrochemical experiments are conducted with washing water collected directly from the ship’s scrubber. After electropolishing, the surface roughness is improved by about 73.6% compared to mechanical polishing. After plasma ion nitriding, CrN (precipitate), Fe4N (compound), and γN (solid solution) are observed on the surface. The thickness of the layer formed on the surface is measured to be about 10 μm. A hysteresis loop is observed in the cyclic potentiodynamic polarization curves of mechanical polishing and electropolishing, and the areas are calculated as 23.33 mW cm−2 and 0.17 mW cm−2, respectively. The polarization curve of plasma ion nitriding presents perfect passivation characteristics. Accordingly, mechanical polishing and electropolishing reveal local corrosion, whereas plasma ion nitriding presents a tendency towards general corrosion. In the mechanical polishing, electropolishing, and plasma ion nitriding, the corrosion current densities are 0.665 μA cm−2, 0.093 μA cm−2, and 16.47 μA cm−2, respectively, and the maximum damage depth is observed to grow progressively smaller from plasma ion nitriding to electropolishing and then mechanical polishing.
Atomic-scale visualization of a cascade of magnetic orders in the layered antiferromagnet GdTe3
Authors: Raghavan Arjun , Romanelli Marisa , May-Mann Julian , Aishwarya Anuva , Aggarwal Leena , Singh Anisha G. , Bachmann Maja D. , Schoop Leslie M. , Fradkin Eduardo , Fisher Ian R. , Madhavan Vidya
Published: June 2024

GdTe3 is a layered antiferromagnet which has attracted attention due to its exceptionally high mobility, distinctive unidirectional incommensurate charge density wave (CDW), superconductivity under pressure, and a cascade of magnetic transitions between 7 and 12 K, with as yet unknown order parameters. Here, we use spin-polarized scanning tunneling microscopy to directly image the charge and magnetic orders in GdTe3. Below 7 K, we find a striped antiferromagnetic phase with twice the periodicity of the Gd lattice and perpendicular to the CDW. As we heat the sample, we discover a spin density wave with the same periodicity as the CDW between 7 and 12 K; the viability of this phase is supported by our Landau free energy model. Our work reveals the order parameters of the magnetic phases in GdTe3 and shows how the interplay between charge and spin can generate a cascade of magnetic orders.
On the role of surface morphology in impacting-freezing dynamics of supercooled droplets
Authors: Hosseini S. R. , Moghimi M. , Nouri N. M.
Published: June 2024

A thorough understanding of droplet impact and freezing is vital in preventing ice accretion on many outdoor devices. This simulation-based study investigated the effect of surface morphology on the impacting-freezing process of a supercooled droplet. Also, the variations of Weber number and supercooling temperature were studied numerically. The droplet impact and freezing process were simulated with the volume of fluid method and freezing model. A more accurate simulation was achieved by modeling the supercooled droplet and the dynamic contact angle. At the given ranges of the input parameters, the main factors that guaranteed droplet rebounding after collision were determined. The supercooling temperature and the groove width should be above 266 K and less than 0.21 mm, respectively. The droplet should also maintain its cohesion and integrity during impact. Creating grooves on a surface is novel and paves a new way to understand the impact and solidification of water droplets in supercooled conditions.
Little evidence of inbreeding depression for birth mass, survival and growth in Antarctic fur seal pups
Authors: Paijmans A. J. , Berthelsen A. L. , Nagel R. , Christaller F. , Kröcker N. , Forcada J. , Hoffman J. I.
Published: June 2024

Inbreeding depression, the loss of offspring fitness due to consanguineous mating, is generally detrimental for individual performance and population viability. We investigated inbreeding effects in a declining population of Antarctic fur seals (Arctocephalus gazella) at Bird Island, South Georgia. Here, localised warming has reduced the availability of the seal’s staple diet, Antarctic krill, leading to a temporal increase in the strength of selection against inbred offspring, which are increasingly failing to recruit into the adult breeding population. However, it remains unclear whether selection operates before or after nutritional independence at weaning. We therefore used microsatellite data from 885 pups and their mothers, and SNP array data from 98 mother–offspring pairs, to quantify the effects of individual and maternal inbreeding on three important neonatal fitness traits: birth mass, survival and growth. We did not find any clear or consistent effects of offspring or maternal inbreeding on any of these traits. This suggests that selection filters inbred individuals out of the population as juveniles during the time window between weaning and recruitment. Our study brings into focus a poorly understood life-history stage and emphasises the importance of understanding the ecology and threats facing juvenile pinnipeds.
The lymphedema patient experience within the healthcare system: a cross-sectional epidemiologic assessment
Authors: Bowman Catharine , Rockson Stanley G.
Published: June 2024

Lymphedema is a progressive lymphatic disease that potentiates physical and psychosocial distress. Despite its impact, patients reportedly encounter lymphatic ignorance throughout the healthcare system. This cross-sectional study aims to summarize clinical characteristics and interactions of lymphedema patients within the healthcare system. Two lymphedema patient cohorts were included: The Global Registry Analysis Cohort included lymphedema patients who contributed to an international digital lymphatic registry and the Interactions Cohort included patients who initiated a questionnaire about interactions with the medical system. The global registry was used to obtain demographic and clinical characteristics from affiliated lymphedema patients. A 23-item online questionnaire on healthcare experiences and satisfaction with lymphatic healthcare was then distributed to the Interactions Cohort. Complete responses were obtained from 2474 participants. Participants were a mean age of 57.5 ± 16.1 years and 51.4% had a cancer history. Participants reported substantial delays in diagnosis and treatment. Cancer-related and non-cancer-related lymphedema patients reported similar levels of perceived physician disinterest in their lymphedema; however, non-cancer-related lymphedema patients reported more care dissatisfaction. Ultimately, patients continue to face delays in lymphedema diagnosis and treatment. We developed an evidence-based model highlighting areas of reform needed to improve lymphatic education and healthcare.
Optimal control strategies for toxoplasmosis disease transmission dynamics via harmonic mean-type incident rate
Authors: Khan Usman , Ali Farhad , Alqasem Ohud A. , Elwahab Maysaa E. A. , Khan Ilyas , Rahimzai Ariana Abdul
Published: June 2024

Toxoplasma infection in humans is considered due to direct contact with infected cats. Toxoplasma infection (an endemic disease) has the potential to affect various organs and systems (brain, eyes, heart, lungs, liver, and lymph nodes). Bilinear incidence rate and constant population (birth rate is equal to death rate) are used in the literature to explain the dynamics of Toxoplasmosis disease transmission in humans and cats. The goal of this study is to consider the mathematical model of Toxoplasma disease with harmonic mean type incident rate and also consider that the population of humans and cats is not equal (birth rate and the death rate are not equal). In examining Toxoplasma transmission dynamics in humans and cats, harmonic mean incidence rates are better than bilinear incidence rates. The disease dynamics are first schematically illustrated, and then the law of mass action is applied to obtain nonlinear ordinary differential equations (ODEs). Analysis of the boundedness, positivity, and equilibrium points of the system has been analyzed. The reproduction number is calculated using the next-generation matrix technique. The stability of disease-free and endemic equilibrium are analyzed. Sensitivity analysis is also done for reproduction number. Numerical simulation shows that the infection is spread in the population when the contact rate $$\beta_{h}$$

β
h

and $$\beta_{c}$$

β
c

increases while the infection is reduced when the recovery rate $$\delta_{h}$$

δ
h

increases. This study investigates the impact of various optimal control strategies, such as vaccinations for the control of disease and the awareness of disease awareness, on the management of disease.
Prevalence and genetic diversity of Anaplasma and Ehrlichia in ticks and domesticated animals in Suizhou County, Hubei Province, China
Authors: Tang Ju , Xu Jiao , Liu Xiao-hui , Lv Fang-zhi , Yao Qiu-ju , Zhou Xiao-Fan , Lu Hui-ya , Yu Tian-mei , Jiang Ze-zheng , Jin Xiao-zhou , Guo Fang , Yu Xue-jie
Published: June 2024

Anaplasma and Ehrlichia are tick-borne bacterial pathogens that cause anaplasmoses and ehrlichioses in humans and animals. In this study, we examined the prevalence of Anaplasma and Ehrlichia species in ticks and domesticated animals in Suizhou County, Hubei Province in the central China. We used PCR amplification and DNA sequencing of the 16S rRNA, groEL, and gltA genes to analyze. We collected 1900 ticks, including 1981 Haemaphysalis longicornis and 9 Rhipicephalus microplus, 159 blood samples of goats (n = 152), cattle (n = 4), and dogs (n = 3) from May to August of 2023. PCR products demonstrated that Anaplasma bovis, Anaplasma capra, and an Ehrlichia species were detected in the H. longicornis with the minimum infection rates (MIR) of 1.11%, 1.32%, and 0.05%, respectively; A. bovis, A. capra, and unnamed Anaplasma sp. were detected in goats with an infection rate of 26.31%, 1.31% and 1.97%, respectively. Anaplasma and Ehrlichia species were not detected from cattle, dogs and R. microplus ticks. The genetic differences in the groEL gene sequences of the Anaplasma in the current study were large, whereas the 16S rRNA and gltA gene sequences were less disparate. This study shows that ticks and goats in Suizhou County, Hubei Province carry multiple Anaplasma species and an Ehrlichia species, with relatively higher infection rate of A. bovis in goats. Our study indicates that multiple Anaplasma and Ehrlichia species exist in ticks and goats in the central China with potential to cause human infection.
A study on deep learning model based on global–local structure for crowd flow prediction
Authors: Go HeounMo , Park SangHyun
Published: June 2024

Crowd flow prediction has been studied for a variety of purposes, ranging from the private sector such as location selection of stores according to the characteristics of commercial districts and customer-tailored marketing to the public sector for social infrastructure design such as transportation networks. Its importance is even greater in light of the spread of contagious diseases such as COVID-19. In many cases, crowd flow can be divided into subgroups by common characteristics such as gender, age, location type, etc. If we use such hierarchical structure of the data effectively, we can improve prediction accuracy of crowd flow for subgroups. But the existing prediction models do not consider such hierarchical structure of the data. In this study, we propose a deep learning model based on global–local structure of the crowd flow data, which utilizes the overall(global) and subdivided by the types of sites(local) crowd flow data simultaneously to predict the crowd flow of each subgroup. The experiment result shows that the proposed model improves the prediction accuracy of each sub-divided subgroup by 5.2% (Table 5 Cat #9)—45.95% (Table 11 Cat #5), depending on the data set. This result comes from the comparison with the related works under the same condition that use target category data to predict each subgroup. In addition, when we refine the global data composition by considering the correlation between subgroups and excluding low correlated subgroups, the prediction accuracy is further improved by 5.6–48.65%.
Measuring global cerebrovascular pulsatility transmission using 4D flow MRI
Authors: Dempsey Sergio , Safaei Soroush , Holdsworth Samantha J. , Maso Talou Gonzalo D.
Published: June 2024

Pulse wave encephalopathy (PWE) is hypothesised to initiate many forms of dementia, motivating its identification and risk assessment. As candidate pulsatility based biomarkers for PWE, pulsatility index and pulsatility damping have been studied and, currently, do not adequately stratify risk due to variability in pulsatility and spatial bias. Here, we propose a locus-independent pulsatility transmission coefficient computed by spatially tracking pulsatility along vessels to characterise the brain pulse dynamics at a whole-organ level. Our preliminary analyses in a cohort of 20 subjects indicate that this measurement agrees with clinical observations relating blood pulsatility with age, heart rate, and sex, making it a suitable candidate to study the risk of PWE. We identified transmission differences between vascular regions perfused by the basilar and internal carotid arteries attributed to the identified dependence on cerebral blood flow, and some participants presented differences between the internal carotid perfused regions that were not related to flow or pulsatility burden, suggesting underlying mechanical differences. Large populational studies would benefit from retrospective pulsatility transmission analyses, providing a new comprehensive arterial description of the hemodynamic state in the brain. We provide a publicly available implementation of our tools to derive this coefficient, built into pre-existing open-source software.
Structural, dynamic behaviour, in-vitro and computational investigations of Schiff’s bases of 1,3-diphenyl urea derivatives against SARS-CoV-2 spike protein
Authors: Ullah Saeed , Ullah Atta , Waqas Muhammad , Halim Sobia Ahsan , Pasha Anam Rubbab , Shafiq Zahid , Mali Suraj N. , Jawarkar Rahul D. , Khan Ajmal , Khalid Asaad , Abdalla Ashraf N. , Kashtoh Hamdy , Al-Harrasi Ahmed
Published: June 2024

The COVID-19 has had a significant influence on people's lives across the world. The viral genome has undergone numerous unanticipated changes that have given rise to new varieties, raising alarm on a global scale. Bioactive phytochemicals derived from nature and synthetic sources possess lot of potential as pathogenic virus inhibitors. The goal of the recent study is to report new inhibitors of Schiff bases of 1,3-dipheny urea derivatives against SARS COV-2 spike protein through in-vitro and in-silico approach. Total 14 compounds were evaluated, surprisingly, all the compounds showed strong inhibition with inhibitory values between 79.60% and 96.00% inhibition. Here, compounds 3a (96.00%), 3d (89.60%), 3e (84.30%), 3f (86.20%), 3g (88.30%), 3h (86.80%), 3k (82.10%), 3l (90.10%), 3m (93.49%), 3n (85.64%), and 3o (81.79%) exhibited high inhibitory potential against SARS COV-2 spike protein. While 3c also showed significant inhibitory potential with 79.60% inhibition. The molecular docking of these compounds revealed excellent fitting of molecules in the spike protein receptor binding domain (RBD) with good interactions with the key residues of RBD and docking scores ranging from − 4.73 to − 5.60 kcal/mol. Furthermore, molecular dynamics simulation for 150 ns indicated a strong stability of a complex 3a:6MOJ. These findings obtained from the in-vitro and in-silico study reflect higher potency of the Schiff bases of 1,3-diphenyl urea derivatives. Furthermore, also highlight their medicinal importance for the treatment of SARS COV-2 infection. Therefore, these small molecules could be a possible drug candidate.
Diagnostic value of combined ultrasound contrast and elastography for differentiating benign and malignant thyroid nodules: a meta-analysis
Authors: Liu Funing , Wang Yihan , Xiong Yu , Li Xin , yao Jun , Ju Hao , Ren Fu , Zhang Luwei , Wang Hongbo
Published: June 2024

The diagnostic value of contrast-enhanced ultrasound combined with ultrasound elastography for benign and malignant thyroid nodules is still controversial, so we used meta-analysis to seek controversial answers. The PubMed, OVID, and CNKI databases were searched according to the inclusion and exclusion criteria. The literature was selected from the establishment of each database to February 2024. The QUADAS-2 tool assessed diagnostic test accuracy. SROC curves and Spearman's correlation coefficient were made by Review Manager 5.4 software to assess the presence of threshold effects in the literature. Meta-Disc1.4 software was used for Cochrane-Q and χ2 tests, which be used to evaluate heterogeneity, with P-values and I2 indicating heterogeneity levels. The appropriate effect model was selected based on the results of the heterogeneity test. Stata18.0 software was used to evaluate publication bias. The diagnostic accuracy of contrast-enhanced ultrasound combined with ultrasound elastography for benign and malignant thyroid nodules was evaluated by calculating the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the SROC curve. A total of 31 studies included 3811 patients with 4718 nodules were analyzed. There is no heterogeneity caused by the threshold effect, but there is significant non-threshold heterogeneity. Combined diagnostic metrics were: sensitivity = 0.93, specificity = 0.91, DOR = 168.41, positive likelihood ratio = 10.60, and negative likelihood ratio = 0.07. The SROC curve area was 0.97. Contrast-enhanced ultrasound and elastography show high diagnostic accuracy for thyroid nodules, offering a solid foundation for early diagnosis and treatment.

Trial registration. CRD42024509462.
Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study
Authors: Zhou Xingwang , Ling Yuanguo , Cui Junshuan , Wang Xiang , Long Niya , Teng Wei , Liu Jian , Xiang Xin , Yang Hua , Chu Liangzhao
Published: June 2024

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell–cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.
Estimation of rice yield using multivariate analysis techniques based on meteorological parameters
Authors: Sharma Ajay , Kumar Joginder , Redhu Mandeep , Kumar Parveen , Godara Mohit , Ghiyal Pushpa , Fu Pingping , Rahimi Mehdi
Published: June 2024

This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980–81 to 2020–21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices.
Accelerating 3D genomics data analysis with Microcket
Authors: Zhao Yu , Yang Mengqi , Gong Fanglei , Pan Yuqi , Hu Minghui , Peng Qin , Lu Leina , Lyu Xiaowen , Sun Kun
Published: June 2024

The three-dimensional (3D) organization of genome is fundamental to cell biology. To explore 3D genome, emerging high-throughput approaches have produced billions of sequencing reads, which is challenging and time-consuming to analyze. Here we present Microcket, a package for mapping and extracting interacting pairs from 3D genomics data, including Hi-C, Micro-C, and derivant protocols. Microcket utilizes a unique read-stitch strategy that takes advantage of the long read cycles in modern DNA sequencers; benchmark evaluations reveal that Microcket runs much faster than the current tools along with improved mapping efficiency, and thus shows high potential in accelerating and enhancing the biological investigations into 3D genome. Microcket is freely available at https://github.com/hellosunking/Microcket.
Dynamic molecular portraits of ion-conducting pores characterize functional states of TRPV channels
Authors: Trofimov Yury A. , Krylov Nikolay A. , Minakov Alexander S. , Nadezhdin Kirill D. , Neuberger Arthur , Sobolevsky Alexander I. , Efremov Roman G.
Published: June 2024

Structural biology is solving an ever-increasing number of snapshots of ion channel conformational ensembles. Deciphering ion channel mechanisms, however, requires understanding the ensemble dynamics beyond the static structures. Here, we present a molecular modeling-based approach characterizing the ion channel structural intermediates, or their “dynamic molecular portraits”, by assessing water and ion conductivity along with the detailed evaluation of pore hydrophobicity and residue packing. We illustrate the power of this approach by analyzing structures of few vanilloid-subfamily transient receptor potential (TRPV) channels. Based on the pore architecture, there are three major states that are common for TRPVs, which we call α-closed, π-closed, and π-open. We show that the pore hydrophobicity and residue packing for the open state is most favorable for the pore conductance. On the contrary, the α-closed state is the most hydrophobic and always non-conducting. Our approach can also be used for structural and functional classification of ion channels.
Amorphous cobalt–nickel borides boost electrocatalytic ethanol oxidation coupled with energy-saving hydrogen production
Authors: Hong Anqi , Du Xiangbowen , Qian Kaicheng , Fang Zheng , Duan Yu , Sui Jing , Wei Tong , Li Renhong
Published: June 2024

We report an amorphous heterogeneous catalyst composed of boride and tungstate, which realizes the upgrading of ethanol oxidation coupled with energy saving hydrogen production.
Low reflective index, highly transparent, and ultra-low dielectric constant materials prepared via effective copolymerization of 4-methyl-1-pentene and a Si-containing α,ω-diolefin
Authors: Wang Yafei , Huang Dong , Gao Xianhang , Wang Fei , Cai Hao , Pan Li , Li Yuesheng
Published: June 2024

A series of ultra-low dielectric constant materials containing C–Si-cyclic units were prepared. The new copolymers showed stable and ultra-low dielectric constants below 2.0, tunable glass transition temperature and mechanical performance.
Reversal of enantioselectivity by tuning the ring size of ProPhenol
Authors: Huang Xu-Yi , Li Na , Miao Yu-Hang , Hua Yuan-Zhao , Wang Min-Can , Xu Li-Ping , Mei Guang-Jian
Published: June 2024

Reported herein is the ligand-ring-size controlled enantiodivergent aza-Friedel–Crafts alkylation reaction of 3-aminophenols with imines.
Automated federated learning‐based adversarial attack and defence in industrial control systems
Authors: Zeng Guo‐Qiang , Shao Jun‐Min , Lu Kang‐Di , Geng Guang‐Gang , Weng Jian
Published: June 2024

With the development of deep learning and federated learning (FL), federated intrusion detection systems (IDSs) based on deep learning have played a significant role in securing industrial control systems (ICSs). However, adversarial attacks on ICSs may compromise the ability of deep learning‐based IDSs to accurately detect cyberattacks, leading to serious consequences. Moreover, in the process of generating adversarial samples, the selection of replacement models lacks an effective method, which may not fully expose the vulnerabilities of the models. The authors first propose an automated FL‐based method to generate adversarial samples in ICSs, called AFL‐GAS, which uses the principle of transfer attack and fully considers the importance of replacement models during the process of adversarial sample generation. In the proposed AFL‐GAS method, a lightweight neural architecture search method is developed to find the optimised replacement model composed of a combination of four lightweight basic blocks. Then, to enhance the adversarial robustness, the authors propose a multi‐objective neural architecture search‐based IDS method against adversarial attacks in ICSs, called MoNAS‐IDSAA, by considering both classification performance on regular samples and adversarial robustness simultaneously. The experimental results on three widely used intrusion detection datasets in ICSs, such as secure water treatment (SWaT), Water Distribution, and Power System Attack, demonstrate that the proposed AFL‐GAS method has obvious advantages in evasion rate and lightweight compared with other four methods. Besides, the proposed MoNAS‐IDSAA method not only has a better classification performance, but also has obvious advantages in model adversarial robustness compared with one manually designed federated adversarial learning‐based IDS method.
Programmable cancer treatments: Engineering biology approaches for living cures
Authors: Biarnes Carrera Marc , Sevko Alexandra , Glanville Nicholas , Deban Livija
Published: June 2024

Living cures are cell‐based, programmable therapies that integrate the latest learnings in immunology and synthetic biology. Although Adoptive Cell Therapies (ACTs) have transformed the treatment landscape of haematological malignancies by harnessing the powerful anti‐tumour properties of immune cells, commercialisation and ensuring access is challenging. Their application in solid tumour treatment has been hindered by the immunosuppressive tumour microenvironment (TME) and its associated physical barriers. Conversely, bacterial immunotherapies offer cost‐effective solutions by utilising tumour‐colonising bacteria that trigger localised inflammatory responses within the TME. The authors briefly examine advancements in ACT and propose bacterial immunotherapies as an alternative or complementary treatment modality with potential use either as standalone therapies or in conjunction with other treatments.
Beyond central-local relations: the introduction of a new perspective on China’s environmental governance model
Authors: Chen Haisong , Feng Li , Sun Xiaoyu
Published: June 2024

In recent years, the Chinese government has initiated assertive centralization efforts in its approach to environmental governance. However, the efficacy of these initiatives demonstrates marked variability across different sectors. While the central-local relational framework has traditionally been employed to elucidate these disparities, its explanatory power is showing signs of strain. This paper, through policy analysis and field interviews, investigates regulatory conflicts in land use for ecological and agricultural purposes within China. The findings highlight instances of overlapping jurisdictions and discordant policy objectives among agencies responsible for delineating ecological spaces and agricultural zones. While these conflicts seem to stem from the dynamics between the central and local governments, they more accurately reflect the inherent characteristics of fragmented authoritarianism. This paper aims to expand the theory of fragmented authoritarianism by incorporating the dimension of inter-departmental competition into environmental governance, moving beyond the traditional binary analysis framework of central-local relations. It seeks to understand and critique its limitations from a broader perspective, emphasizing the role of departmental competition within fragmented authoritarianism. By analyzing this internal mechanism, the paper reveals a more nuanced governance landscape, essentially replacing the traditional central-local paradigm with a model that situates departmental competition within the overall context of fragmented authoritarianism. We propose two models for delineating competition among governmental institutions: the bureaucratic model and the charisma model, thereby advancing and deepening the application of fragmented authoritarianism theory in China’s environmental governance. This provides new theoretical insights for understanding the current challenges and developments in China’s environmental governance.
How does the digital transformation of agriculture affect carbon emissions? Evidence from China’s provincial panel data
Authors: Chen Yihui , Li Minjie
Published: June 2024

Agriculture is becoming a substantial contributor to carbon emissions in China, and the efficient reduction of agricultural carbon emissions (ACEs) has become a universal concern. Currently, the digital transformation of agriculture (DTA) provides a new way to reduce carbon emissions. However, questions regarding whether and how DTA suppresses ACEs remain the focus of both academic and practical attention; thus, they serve as the objectives of this study. Based on theoretical analyzes, the carbon emission reduction effect of DTA is empirically analyzed using panel data from 30 Chinese provinces between 2015 and 2021 with a benchmark regression model, mediating effect model and threshold effect model. The results show the following: (1) DTA significantly reduces ACEs. (2) DTA reduces ACEs through three paths: expanding the agricultural production scale, optimizing the agricultural industrial structure, and promoting agricultural technological progress. The agricultural industrial structure has the most considerable mediating effect, while the agricultural production scale expansion has the smallest effect. (3) The inhibitory effect of DTA on ACEs shows very distinct heterogeneity. DTA primarily reduces ACEs in eastern and nongrain production areas yet has an insignificant impact on other areas. In addition, the DTA has a significant inhibitory effect on ACEs from both fertilizers and diesel oil. (4) The inhibitory effect of DTA on ACEs is nonlinear rather than linear. There is a single threshold effect for the effect of DTA on ACEs, which is insignificant below the threshold and significantly negative above the threshold. Therefore, China’s central and local governments need to increase the level of DTA, encourage farmers to moderately expand the scale of their operations, emphasize the agricultural service industry, and enhance agricultural technological innovation to ultimately reduce ACEs.
Comparing clocks by using pulses of light
Authors: Caldwell Emily , Sinclair Laura
Published: June 2024

Microwave atomic clocks can easily be synchronized across long distances using RF methods. Their more precise optical cousins require a subtler approach.
Q&A: Ernest Moniz on the nuclear weapons threat
Authors: Kramer David
Published: June 2024

Nuclear and nonnuclear nations need to act to prevent the growing risk of accidental or deliberate use, says the former US secretary of energy.
Electron microscopy for attosecond science
Authors: Hassan Mohammed
Published: June 2024

Some of the fastest processes in physical and biological systems can be studied by generating ultrashort electron pulses.
Reduced Mn uptake of pleiotropic ZIP8 SNP is caused by its loss of Mn-responsive accumulation on the cell-surface
Authors: Nishito Yukina , Fujishiro Hitomi , Nagamatsu Shino , Kambe Taiho
Published: June 2024

Zrt/Irt-like protein 8 (ZIP8), which is a Zn transporter, plays a pivotal role as a Mn transporter. Recent studies have shown that a ZIP8 SNP (rs13107325 C→T, A391T) is associated with multiple diseases, likely by causing systemic Mn deficiency. However, the underlying molecular mechanisms remain unclear. We attempted to address this issue in cell-based experiments using Madin-Darby canine kidney cells stably expressing ZIP8 WT or the A391T SNP mutant under the control of the Tet-regulatable promoter. We showed that the A391T mutant lost the property of Mn-responsive accumulation on the cell surface, which was observed in WT ZIP8. We also showed that the loss of Mn-responsive accumulation of A391T mutant was associated with its reduced Mn uptake, compared with WT ZIP8, in the Mn uptake assay using the radioisotope 54Mn. Our results potentially explain how the ZIP8 A391T substitution is associated with disease pathogenesis caused by Mn deficiency.