bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hybrid Deep Learning‐Based Forecasting Model for the Peak Height of Ionospheric F2 Layer
Authors: Shi Ya‐fei , Yang Cheng , Wang Jian , Zheng Yu , Meng Fan‐yi , Chernogor Leonid F.
Published: October 2023

To achieve accurate forecasting of the peak height of the ionospheric F2 layer (hmF2), we propose a hybrid deep learning model of improved seagull optimization algorithm (ISOA) optimized long short‐term memory (LSTM) model based on a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) theory. The hybrid model decomposes the hmF2 time data into multiple subsequences through CEEMDAN and reconstructs the subsequences by sample entropy and correlation coefficient into high and low‐frequency sequences, which effectively shortens the calculation time of the model. Then, we determine the optimal hyperparameters of the LSTM models through ISOA, achieving high‐precision forecasting of the hmF2. In single‐step forecasting, the forecasting values of the hybrid model in diurnal and seasonal changes are highly consistent with the observation, which can better capture the severe changes in the hmF2. The model's RMSE, MAE, MAPE, and CC evaluation metrics are 15.86, 11.03 km, 4.76%, and 0.93 in the test set. Compared to IRI, GRU, and LSTM models, taking RMSE as an example, the forecasting accuracy of the models increased by 65.24%, 29.89%, and 29.60%, respectively. In multi‐step forecasting, the proposed model is better at forecasting the changing trend of hmF2, and the forecasting accuracies are significantly better than the IRI model. The data from multiple stations also verified the applicability of the proposed model for hmF2 forecasting. The above results indicate that the hybrid model has high accuracy in hmF2 short‐term forecasting and good applicability in multiple multi‐step forecasting, which can further improve the accurate forecasting of space weather.
Exhuming an Accretionary Prism: A Case Study of the Kodiak Accretionary Complex, Alaska, USA
Authors: Rajič Kristijan , Raimbourg Hugues , Famin Vincent , Moris‐Muttoni Benjamin , Fisher Donald M. , Morell Kristin D. , Canizarés Aurélien
Published: October 2023

We have carried a structural study across Kodiak accretionary complex in Alaska, USA, in order to describe its thermal structure and decipher the processes of exhumation. The accretionary complex consists of a stack of tectonic mélanges and coherent units. Mélanges are characterized by simple shear deformation with a pervasive network of top‐to‐the‐trench shear zones, whereas coherent units are affected principally by horizontal shortening, except for spatially limited outcrops in Kodiak Central Belt. Peak temperatures estimated using Raman spectroscopy of carbonaceous material range from 220 to 400°C through most of the complex. These temperatures coincide with estimates from metamorphic parageneses and are interpreted as temperatures of deformation achieved under a high gradient due to contemporaneous ridge subduction. The highest temperatures are recorded in the central part of the complex, pointing to a dome‐like structure. Lower temperatures (∼120°C) are recorded along the southeastern border of the complex, in slope sediments unconformably overlying accreted units. Based on the combination of structural and thermal data, we conclude that the rocks constituting the Kodiak complex experienced at least two stages of burial and then exhumation, with vertical motions reaching up to ∼13 km from the Paleocene to the present. Given the pervasive horizontal shortening within the wedge, exhumation resulted from prism thickening contemporaneous with surficial erosion. Recorded subsidence episodes may be local phenomena associated with thrusting or large‐scale processes associated with basal erosion. The rates of vertical motion range from 0.2 to 1.3 mm/yr, comparable with estimates in modern margins.
Genomic findings in schizophrenia and their implications
Authors: Owen Michael J. , Legge Sophie E. , Rees Elliott , Walters James T. R. , O’Donovan Michael C.
Published: October 2023

There has been substantial progress in understanding the genetics of schizophrenia over the past 15 years. This has revealed a highly polygenic condition with the majority of the currently explained heritability coming from common alleles of small effect but with additional contributions from rare copy number and coding variants. Many specific genes and loci have been implicated that provide a firm basis upon which mechanistic research can proceed. These point to disturbances in neuronal, and particularly synaptic, functions that are not confined to a small number of brain regions and circuits. Genetic findings have also revealed the nature of schizophrenia’s close relationship to other conditions, particularly bipolar disorder and childhood neurodevelopmental disorders, and provided an explanation for how common risk alleles persist in the population in the face of reduced fecundity. Current genomic approaches only potentially explain around 40% of heritability, but only a small proportion of this is attributable to robustly identified loci. The extreme polygenicity poses challenges for understanding biological mechanisms. The high degree of pleiotropy points to the need for more transdiagnostic research and the shortcomings of current diagnostic criteria as means of delineating biologically distinct strata. It also poses challenges for inferring causality in observational and experimental studies in both humans and model systems. Finally, the Eurocentric bias of genomic studies needs to be rectified to maximise benefits and ensure these are felt across diverse communities. Further advances are likely to come through the application of new and emerging technologies, such as whole-genome and long-read sequencing, to large and diverse samples. Substantive progress in biological understanding will require parallel advances in functional genomics and proteomics applied to the brain across developmental stages. For these efforts to succeed in identifying disease mechanisms and defining novel strata they will need to be combined with sufficiently granular phenotypic data.
The m6A reader IGF2BP3 preserves NOTCH3 mRNA stability to sustain Notch3 signaling and promote tumor metastasis in nasopharyngeal carcinoma
Authors: Chen Boyu , Huang Runda , Xia Tianliang , Wang Chunyang , Xiao Xiao , Lu Shunzhen , Chen Xiangfu , Ouyang Ying , Deng Xiaowu , Miao Jingjing , Zhao Chong , Wang Lin
Published: October 2023

Metastasis remains the major cause of treatment failure in patients with nasopharyngeal carcinoma (NPC), in which sustained activation of the Notch signaling plays a critical role. N6-Methyladenosine (m6A)-mediated post-transcriptional regulation is involved in fine-tuning the Notch signaling output; however, the post-transcriptional mechanisms underlying NPC metastasis remain poorly understood. In the present study, we report that insulin-like growth factor 2 mRNA-binding proteins 3 (IGF2BP3) serves as a key m6A reader in NPC. IGF2BP3 expression was significantly upregulated in metastatic NPC and correlated with poor prognosis in patients with NPC. IGF2BP3 overexpression promoted, while IGF2BP3 downregulation inhibited tumor metastasis and the stemness phenotype of NPC cells in vitro and in vivo. Mechanistically, IGF2BP3 maintains NOTCH3 mRNA stability via suppression of CCR4-NOT complex-mediated deadenylation in an m6A-dependent manner, which sustains Notch3 signaling activation and increases the transcription of stemness-associated downstream genes, eventually promoting tumor metastasis. Our findings highlight the pro-metastatic function of the IGF2BP3/Notch3 axis and revealed the precise role of IGF2BP3 in post-transcriptional regulation of NOTCH3, suggesting IGF2BP3 as a novel prognostic biomarker and potential therapeutic target in NPC metastasis.
Neo-intline: integrated pipeline enables neoantigen design through the in-silico presentation of T-cell epitope
Authors: Li Bingyu , Jing Ping , Zheng Genhui , Pi Chenyu , Zhang Lu , Yin Zuojing , Xu Lijun , Qiu Jingxuan , Gu Hua , Qiu Tianyi , Fang Jianmin
Published: October 2023

Neoantigen vaccines are one of the most effective immunotherapies for personalized tumour treatment. The current immunogen design of neoantigen vaccines is usually based on whole-genome sequencing (WGS) and bioinformatics prediction that focuses on the prediction of binding affinity between peptide and MHC molecules, ignoring other peptide-presenting related steps. This may result in a gap between high prediction accuracy and relatively low clinical effectiveness. In this study, we designed an integrated in-silico pipeline, Neo-intline, which started from the SNPs and indels of the tumour samples to simulate the presentation process of peptides in-vivo through an integrated calculation model. Validation on the benchmark dataset of TESLA and clinically validated neoantigens illustrated that neo-intline could outperform current state-of-the-art tools on both sample level and melanoma level. Furthermore, by taking the mouse melanoma model as an example, we verified the effectiveness of 20 neoantigens, including 10 MHC-I and 10 MHC-II peptides. The in-vitro and in-vivo experiments showed that both peptides predicted by Neo-intline could recruit corresponding CD4+ T cells and CD8+ T cells to induce a T-cell-mediated cellular immune response. Moreover, although the therapeutic effect of neoantigen vaccines alone is not sufficient, combinations with other specific therapies, such as broad-spectrum immune-enhanced adjuvants of granulocyte-macrophage colony-stimulating factor (GM-CSF) and polyinosinic-polycytidylic acid (poly(I:C)), or immune checkpoint inhibitors, such as PD-1/PD-L1 antibodies, can illustrate significant anticancer effects on melanoma. Neo-intline can be used as a benchmark process for the design and screening of immunogenic targets for neoantigen vaccines.
Community composition and physiological plasticity control microbial carbon storage across natural and experimental soil fertility gradients
Authors: Butler Orpheus M , Manzoni Stefano , Warren Charles R
Published: October 2023

Many microorganisms synthesise carbon (C)-rich compounds under resource deprivation. Such compounds likely serve as intracellular C-storage pools that sustain the activities of microorganisms growing on stoichiometrically imbalanced substrates, making them potentially vital to the function of ecosystems on infertile soils. We examined the dynamics and drivers of three putative C-storage compounds (neutral lipid fatty acids [NLFAs], polyhydroxybutyrate [PHB], and trehalose) across a natural gradient of soil fertility in eastern Australia. Together, NLFAs, PHB, and trehalose corresponded to 8.5–40% of microbial C and 0.06–0.6% of soil organic C. When scaled to “structural” microbial biomass (indexed by polar lipid fatty acids; PLFAs), NLFA and PHB allocation was 2–3-times greater in infertile soils derived from ironstone and sandstone than in comparatively fertile basalt- and shale-derived soils. PHB allocation was positively correlated with belowground biological phosphorus (P)-demand, while NLFA allocation was positively correlated with fungal PLFA : bacterial PLFA ratios. A complementary incubation revealed positive responses of respiration, storage, and fungal PLFAs to glucose, while bacterial PLFAs responded positively to PO43-. By comparing these results to a model of microbial C-allocation, we reason that NLFA primarily served the “reserve” storage mode for C-limited taxa (i.e., fungi), while the variable portion of PHB likely served as “surplus” C-storage for P-limited bacteria. Thus, our findings reveal a convergence of community-level processes (i.e., changes in taxonomic composition that underpin reserve-mode storage dynamics) and intracellular mechanisms (e.g., physiological plasticity of surplus-mode storage) that drives strong, predictable community-level microbial C-storage dynamics across gradients of soil fertility and substrate stoichiometry.
Ongoing diversification of the global fish pathogenPiscirickettsia salmonisthrough genetic isolation and transposition bursts
Authors: Schober Isabel , Bunk Boyke , Carril Gabriela , Freese Heike M , Ojeda Nicolás , Riedel Thomas , Meier-Kolthoff Jan P , Göker Markus , Spröer Cathrin , Flores-Herrera Patricio A , Nourdin-Galindo Guillermo , Gómez Fernando , Cárdenas Constanza , Vásquez-Ponce Felipe , Labra Alvaro , Figueroa Jaime , Olivares-Pacheco Jorge , Nübel Ulrich , Sikorski Johannes , Marshall Sergio H , Overmann Jörg
Published: October 2023

The management of bacterial pathogens remains a key challenge of aquaculture. The marine gammaproteobacterium Piscirickettsia salmonis is the etiological agent of piscirickettsiosis and causes multi-systemic infections in different salmon species, resulting in considerable mortality and substantial commercial losses. Here, we elucidate its global diversity, evolution, and selection during human interventions. Our comprehensive analysis of 73 closed, high quality genome sequences covered strains from major outbreaks and was supplemented by an analysis of all P. salmonis 16S rRNA gene sequences and metagenomic reads available in public databases. Genome comparison showed that Piscirickettsia comprises at least three distinct, genetically isolated species of which two showed evidence for continuing speciation. However, at least twice the number of species exist in marine fish or seawater. A hallmark of Piscirickettsia diversification is the unprecedented amount and diversity of transposases which are particularly active in subgroups undergoing rapid speciation and are key to the acquisition of novel genes and to pseudogenization. Several group-specific genes are involved in surface antigen synthesis and may explain the differences in virulence between strains. However, the frequent failure of antibiotic treatment of piscirickettsiosis outbreaks cannot be explained by horizontal acquisition of resistance genes which so far occurred only very rarely. Besides revealing a dynamic diversification of an important pathogen, our study also provides the data for improving its surveillance, predicting the emergence of novel lineages, and adapting aquaculture management, and thereby contributes towards the sustainability of salmon farming.
Migrasome: a new functional extracellular vesicle
Authors: Zhang Xide , Yao Liuhuan , Meng Yuanyuan , Li Bailong , Yang Yanyong , Gao Fu
Published: October 2023

Migrasome is a novel cellular organelle produced during cell migration, and its biogenesis depends on the migration process. It is generated in a variety of cells such as immune cells, metastatic tumor cells, other special functional cells like podocytes and cells in developing organisms. It plays important roles in various fields especially in the information exchange between cells. The discovery of migrasome, as an important supplement to the extracellular vesicle system, provides new mechanisms and targets for comprehending various biological or pathological processes. In this article, we will review the discovery, structure, distribution, detection, biogenesis, and removal of migrasomes and mainly focus on summarizing its biological functions in cell-to-cell communication, homeostatic maintenance, embryonic development and multiple diseases. This review also creates prospects for the possible research directions and clinical applications of migrasomes in the future.
Travel time to cataract surgical services in Kenya, Malawi and Rwanda: demonstrating a standardised indicator of physical access to cataract surgery
Authors: McCormick Ian , Nesemann John M. , Zhao Jinfeng , Mdala Shaffi , Kitema Gatera Fiston , Mwangi Nyawira , Gichangi Michael , Tang Kevin , Burton Matthew J. , Ramke Jacqueline
Published: October 2023

Background

Travel time can be used to assess health services accessibility by reflecting the proximity of services to the people they serve. We aimed to demonstrate an indicator of physical access to cataract surgery and identify subnational locations where people were more at risk of not accessing cataract surgery.

Methods

We used an open-access inventory of public health facilities plus key informants in Kenya, Malawi and Rwanda to compile a geocoded inventory of cataract facilities. For each country, gridded estimates of the population aged ≥ 50 years and a travel-time friction surface were combined and a least-cost-path algorithm applied to estimate the shortest travel time between each grid and the nearest cataract facility. We categorised continuous travel time by 1-, 2- and 3 h thresholds and calculated the proportion of the population in each category.

Results

At the national level, the proportion of the population aged ≥ 50 years within 2 h travel time to permanent cataract surgical services was 97.2% in Rwanda (n = 10 facilities), 93.5% in Kenya (n = 74 facilities) and 92.0% in Malawi (n = 6 facilities); this reduced to 77.5%, 84.1% and 52.4% within 1 h, respectively. The least densely populated subnational regions had the poorest access to cataract facilities in Malawi (0.0%) and Kenya (1.9%).

Conclusion

We demonstrated an indicator of access that reflects the distribution of the population at risk of age-related cataract and identifies regions that could benefit from more accessible services. This indicator provides additional demand-side context for eye health planning and supports WHO’s goal of advancing integrated people-centred eye care.
Impacts of climate change, population growth, and power sector decarbonization on urban building energy use
Authors: Wang Chenghao , Song Jiyun , Shi Dachuan , Reyna Janet L. , Horsey Henry , Feron Sarah , Zhou Yuyu , Ouyang Zutao , Li Ying , Jackson Robert B.
Published: October 2023

Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.S. urban areas using a bottom-up approach. The projected future climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, particularly under higher warming scenarios, with on average 10.1–37.7% increases in the frequency of peak building electricity EUI but over 110% increases in some cities. For each 1 °C of warming, the mean city-scale space-conditioning EUI experiences an average increase/decrease of ~14%/ ~ 10% for space cooling/heating. Heterogeneous city-scale building source energy use changes are primarily driven by population and power sector changes, on average ranging from –9% to 40% with consistent south–north gradients under different scenarios. Across the scenarios considered here, the changes in city-scale building source energy use, when averaged over all urban areas, are as follows: –2.5% to –2.0% due to climate change, 7.3% to 52.2% due to population growth, and –17.1% to –8.9% due to power sector decarbonization. Our findings underscore the necessity of considering intercity heterogeneity when developing sustainable and resilient urban energy systems.
FSH and ApoE4 contribute to Alzheimer’s disease-like pathogenesis via C/EBPβ/δ-secretase in female mice
Authors: Xiong Jing , Kang Seong Su , Wang Mengmeng , Wang Zhihao , Xia Yiyuan , Liao Jianming , Liu Xia , Yu Shan-Ping , Zhang Zhaohui , Ryu Vitaly , Yuen Tony , Zaidi Mone , Ye Keqiang
Published: October 2023

Alzheimer’s disease (AD) is the most common dementia. It is known that women with one ApoE4 allele display greater risk and earlier onset of AD compared with men. In mice, we previously showed that follicle–stimulating hormone (FSH), a gonadotropin that rises in post–menopausal females, activates its receptor FSHR in the hippocampus, to drive AD–like pathology and cognitive impairment. Here we show in mice that ApoE4 and FSH jointly trigger AD-like pathogenesis by activating C/EBPβ/δ-secretase signaling. ApoE4 and FSH additively activate C/EBPβ/δ-secretase pathway that mediates APP and Tau proteolytic fragmentation, stimulating Aβ and neurofibrillary tangles. Ovariectomy-provoked AD-like pathologies and cognitive defects in female ApoE4-TR mice are ameliorated by anti-FSH antibody treatment. FSH administration facilitates AD-like pathologies in both young male and female ApoE4-TR mice. Furthermore, FSH stimulates AD-like pathologies and cognitive defects in ApoE4-TR mice, but not ApoE3-TR mice. Our findings suggest that in mice, augmented FSH in females with ApoE4 but not ApoE3 genotype increases vulnerability to AD-like process by activating C/EBPβ/δ-secretase signalling.
Direct regulation of the voltage sensor of HCN channels by membrane lipid compartmentalization
Authors: Handlin Lucas J. , Dai Gucan
Published: October 2023

Ion channels function within a membrane environment characterized by dynamic lipid compartmentalization. Limited knowledge exists regarding the response of voltage-gated ion channels to transmembrane potential within distinct membrane compartments. By leveraging fluorescence lifetime imaging microscopy (FLIM) and Förster resonance energy transfer (FRET), we visualized the localization of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in membrane domains. HCN4 exhibits a greater propensity for incorporation into ordered lipid domains compared to HCN1. To investigate the conformational changes of the S4 helix voltage sensor of HCN channels, we used dual stop-codon suppression to incorporate different noncanonical amino acids, orthogonal click chemistry for site-specific fluorescence labeling, and transition metal FLIM-FRET. Remarkably, altered FRET levels were observed between VSD sites within HCN channels upon disruption of membrane domains. We propose that the voltage-sensor rearrangements, directly influenced by membrane lipid domains, can explain the heightened activity of pacemaker HCN channels when localized in cholesterol-poor, disordered lipid domains, leading to membrane hyperexcitability and diseases.
Golden section criterion to achieve droplet trampoline effect on metal-based superhydrophobic surface
Authors: Zhao Shengteng , Ma Zhichao , Song Mingkai , Tan Libo , Zhao Hongwei , Ren Luquan
Published: October 2023

Clarifying the consecutive droplet rebound mechanisms can provide scientific inspirations to regulate dynamic wettability of superhydrophobic surface, which facilitates the practical applications on efficient heat control and active anti-icing. Generally, droplet rebound behaviors are directly affected by surface structure and Weber number. Here, we report a novel “golden section” design criterion to regulate the droplet rebound number determined by the structure spacing, subverting conventional knowledge. Especially, the droplet can continuously rebound for 17 times on the metal-based surface, exhibiting an amazing phenomenon of “droplet trampoline”. The droplet rebound number has been experimentally revealed to be closely related to Weber number. We propose novel quantitative formulas to predict droplet rebound number and clarify the coupling effect of the structure spacing and the Weber number on the rebound mechanisms, which can be utilized to establish the regulation criteria of rebound numbers and develop novel metal-based superhydrophobic materials.
Paternal DNA methylation is remodeled to maternal levels in rice zygote
Authors: Liu Qian , Ma Xuan , Li Xue , Zhang Xinran , Zhou Shaoli , Xiong Lizhong , Zhao Yu , Zhou Dao-Xiu
Published: October 2023

Epigenetic reprogramming occurs during reproduction to reset the genome for early development. In flowering plants, mechanistic details of parental methylation remodeling in zygote remain elusive. Here we analyze allele-specific DNA methylation in rice hybrid zygotes and during early embryo development and show that paternal DNA methylation is predominantly remodeled to match maternal allelic levels upon fertilization, which persists after the first zygotic division. The DNA methylation remodeling pattern supports the predominantly maternal-biased gene expression during zygotic genome activation (ZGA) in rice. However, parental allelic-specific methylations are reestablished at the globular embryo stage and associate with allelic-specific histone modification patterns in hybrids. These results reveal that paternal DNA methylation is remodeled to match the maternal pattern during zygotic genome reprogramming and suggest existence of a chromatin memory allowing parental allelic-specific methylation to be maintained in the hybrid.
Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors
Authors: Berenson Anna , Lane Ryan , Soto-Ugaldi Luis F. , Patel Mahir , Ciausu Cosmin , Li Zhaorong , Chen Yilin , Shah Sakshi , Santoso Clarissa , Liu Xing , Spirohn Kerstin , Hao Tong , Hill David E. , Vidal Marc , Fuxman Bass Juan I.
Published: October 2023

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V
Authors: Cao Zhuohan , Liu Qian , Liu Qianchu , Yu Xiaobo , Kruzic Jamie J. , Li Xiaopeng
Published: October 2023

Abstracts

Quantitatively defining the relationship between laser powder bed fusion (LPBF) process parameters and the resultant microstructures for LPBF fabricated alloys is one of main research challenges. To date, achieving the desired microstructures and mechanical properties for LPBF alloys is generally done by time-consuming and costly trial-and-error experiments that are guided by human experience. Here, we develop an approach whereby an image-driven conditional generative adversarial network (cGAN) machine learning model is used to reconstruct and quantitatively predict the key microstructural features (e.g., the morphology of martensite and the size of primary and secondary martensite) for LPBF fabricated Ti-6Al-4V. The results demonstrate that the developed image-driven machine learning model can effectively and efficiently reconstruct micrographs of the microstructures within the training dataset and predict the microstructural features beyond the training dataset fabricated by different LPBF parameters (i.e., laser power and laser scan speed). This study opens an opportunity to establish and quantify the relationship between processing parameters and microstructure in LPBF Ti-6Al-4V using a GAN machine learning-based model, which can be readily extended to other metal alloy systems, thus offering great potential in applications related to process optimisation, material design, and microstructure control in the additive manufacturing field.
Bacteriophages suppress CRISPR–Cas immunity using RNA-based anti-CRISPRs
Authors: Camara-Wilpert Sarah , Mayo-Muñoz David , Russel Jakob , Fagerlund Robert D. , Madsen Jonas S. , Fineran Peter C. , Sørensen Søren J. , Pinilla-Redondo Rafael
Published: October 2023

Many bacteria use CRISPR–Cas systems to combat mobile genetic elements, such as bacteriophages and plasmids1. In turn, these invasive elements have evolved anti-CRISPR proteins to block host immunity2,3. Here we unveil a distinct type of CRISPR–Cas Inhibition strategy that is based on small non-coding RNA anti-CRISPRs (Racrs). Racrs mimic the repeats found in CRISPR arrays and are encoded in viral genomes as solitary repeat units4. We show that a prophage-encoded Racr strongly inhibits the type I-F CRISPR–Cas system by interacting specifically with Cas6f and Cas7f, resulting in the formation of an aberrant Cas subcomplex. We identified Racr candidates for almost all CRISPR–Cas types encoded by a diverse range of viruses and plasmids, often in the genetic context of other anti-CRISPR genes5. Functional testing of nine candidates spanning the two CRISPR–Cas classes confirmed their strong immune inhibitory function. Our results demonstrate that molecular mimicry of CRISPR repeats is a widespread anti-CRISPR strategy, which opens the door to potential biotechnological applications6.
Two long read-based genome assembly and annotation of polyploidy woody plants, Hibiscus syriacus L. using PacBio and Nanopore platforms
Authors: Koo Hyunjin , Lee Gir-Won , Ko Seo-Rin , Go Sangjin , Kwon Suk-Yoon , Kim Yong-Min , Shin Ah-Young
Published: October 2023

Improvements in long read DNA sequencing and related techniques facilitated the generation of complex eukaryotic genomes. Despite these advances, the quality of constructed plant reference genomes remains relatively poor due to the large size of genomes, high content of repetitive sequences, and wide variety of ploidy. Here, we developed the de novo sequencing and assembly of high polyploid plant genome, Hibiscus syriacus, a flowering plant species of the Malvaceae family, using the Oxford Nanopore Technologies and Pacific Biosciences Sequel sequencing platforms. We investigated an efficient combination of high-quality and high-molecular-weight DNA isolation procedure and suitable assembler to achieve optimal results using long read sequencing data. We found that abundant ultra-long reads allow for large and complex polyploid plant genome assemblies with great recovery of repetitive sequences and error correction even at relatively low depth Nanopore sequencing data and polishing compared to previous studies. Collectively, our combination provides cost effective methods to improve genome continuity and quality compared to the previously reported reference genome by accessing highly repetitive regions. The application of this combination may enable genetic research and breeding of polyploid crops, thus leading to improvements in crop production.
One-year dataset of hourly air quality parameters from 100 air purifiers used in China residential buildings
Authors: Wei Jiaze , Wang Yan , Mo Jinhan , Fan Cheng
Published: October 2023

Household air purifiers have been widely used as an effective approach to improving indoor air quality. Air purifiers can automatically record indoor air quality parameters, providing valuable data resources for in-depth data-driven analysis. This work presents a one-year hourly indoor air quality dataset collected by household air purifiers in 100 residential homes in 18 provinces across 4 different climate zones in China. The data were collected from July 1, 2021, to July 1, 2022. The concentrations of formaldehyde, PM2.5, TVOC, temperature, relative humidity, on/off status and the airflow rate of air purifiers during operations were recorded hourly. The data were carefully screened with possibly missing values imputed using chained equation-based methods if any. The dataset provides a comprehensive and detailed picture of the indoor air quality in residential buildings, enabling evaluations on the cleaning effect of air purifiers, the impact of outdoor climate change on indoor air quality, and the future trends in indoor human behavior.
High-resolution lithostratigraphy and reconnaissance sedimentology of Changotaung structure, Chittagong Tripura fold belt, Bengal Basin, Bangladesh
Authors: Sharmili Noshin , Apu Saiful Islam , Gazi Md. Yousuf , Bhuiyan Md. Anwar Hossain , Lupin Janifar Hakim
Published: October 2023

Unlike other structures in the vicinity of the Chittagong Tripura Fold Belt, the Changotaung anticline is one of Bangladesh's least explored structures. An attempt has been made for the first time to understand and document sedimentary deposits, environments, structure, and tectonic activity based on the high-resolution outcrop and reconnaissance study with the knowledge of broad-brush geology. We found that Changotaung is a symmetrical box-folded structure with an extensive western flank where the amount of dip varies between 11° and 45°. The exposed Cenozoic succession was categorized into three separate sedimentary sequences and correlated with the conventional stratigraphic unit. A first-order simple Markovian approach was presented for the exposed litho-section in an effort to illustrate vertical facies variations in the Upper Surma group. We quantified that heterolithic bed mostly overlies both trough cross-bedding ($${P}_{ij}U$$

P

ij

U

= 0.706) and parallel laminated bed ($${P}_{ij}U=0.955)$$

P

ij

U
=
0.955
)

according to the facies transition probability matrix. According to the results of the stationary distribution, there is a 40% chance of coming across heterolithic beds within the Upper Surma group during any given event that is completely random whereas trough cross-bedding, parallel laminated bed, cumulative sandstone facies, and cumulative shale facies shows around 10.8%, 15.2%, 20.6%, 13.4% probability. We hypothesized, based on the interpretive facies analysis, that the Chittagong Tripura fold belt region's Upper Surma Group underwent three interrelated depositional settings (wave-dominated shallow marine, tide-dominated shallow marine, and fluvio-deltaic distributary).
The impact of participation in agricultural industry organizational models on crop yields: evidence from Chinese wheat growers
Authors: Zhang Xinde , Wan Xiaoyu , Liu Pengling
Published: October 2023

Increasing income for grain farmers is crucial to mobilise farmers’ incentive for grain cultivation. This article, based on the survey data of 2032 wheat growers in Anhui Province, China, employs the Logit model, multinomial Logit model, and entropy balance-OLS regression method to empirically analyze the factors influencing wheat growers’ participation in agricultural industrial organization models and the impact of their participation decisions on planting returns. The research found that: (1) Wheat growers with richer resource endowments are more likely to participate in agricultural industrial organization models. Factors such as household head’s education level, training experience, quality of arable land, scale of operation, and labor endowment are crucial determinants of wheat growers’ decisions to participate in industrial organization models. (2) Participation in agricultural industrial organizations significantly enhances the net income of wheat growers. Comparatively, the income-boosting effect is more pronounced for those participating in the “household + farmer cooperatives/agricultural enterprises” model. (3) The mechanisms through which wheat growers’ participation in different agricultural industrial organization models affects their crop yields vary. The income-enhancing effects of wheat growers' participation in the “household + farmer cooperatives/agricultural enterprises” model of industrial organization primarily stem from the improvement in land productivity and market bargaining power. On the other hand, the income-enhancing effects of participation in the “household + village collective + farmer cooperatives/agricultural enterprises” model are mainly attributed to the improvement in market bargaining power. The policy implication is that priority should be given to cultivating and developing industrial organisations based on the model of “household + farmers’ co-operatives/agribusinesses” in regions where farmers are richly endowed with resources, and at the same time, the development of industrial organisations based on the model of “household + village collectives + farmers’ co-operatives/agribusinesses” should be supplemented in accordance with local conditions. At the same time, the development of “household + village collectives + farmers’ cooperatives/agribusinesses” mode is supplemented according to local conditions.
EEG-based epileptic seizure detection using binary dragonfly algorithm and deep neural network
Authors: Yogarajan G. , Alsubaie Najah , Rajasekaran G. , Revathi T. , Alqahtani Mohammed S. , Abbas Mohamed , Alshahrani Madshush M. , Soufiene Ben Othman
Published: October 2023

Electroencephalogram (EEG) is one of the most common methods used for seizure detection as it records the electrical activity of the brain. Symmetry and asymmetry of EEG signals can be used as indicators of epileptic seizures. Normally, EEG signals are symmetrical in nature, with similar patterns on both sides of the brain. However, during a seizure, there may be a sudden increase in the electrical activity in one hemisphere of the brain, causing asymmetry in the EEG signal. In patients with epilepsy, interictal EEG may show asymmetric spikes or sharp waves, indicating the presence of epileptic activity. Therefore, the detection of symmetry/asymmetry in EEG signals can be used as a useful tool in the diagnosis and management of epilepsy. However, it should be noted that EEG findings should always be interpreted in conjunction with the patient's clinical history and other diagnostic tests. In this paper, we propose an EEG-based improved automatic seizure detection system using a Deep neural network (DNN) and Binary dragonfly algorithm (BDFA). The DNN model learns the characteristics of the EEG signals through nine different statistical and Hjorth parameters extracted from various levels of decomposed signals obtained by using the Stationary Wavelet Transform. Next, the extracted features were reduced using the BDFA which helps to train DNN faster and improve its performance. The results show that the extracted features help to differentiate the normal, interictal, and ictal signals effectively with 100% accuracy, sensitivity, specificity, and F1 score with a 13% selected feature subset when compared to the existing approaches.
Oral manifestations in patients with coronavirus disease 2019 (COVID-19) identified using text mining: an observational study
Authors: Guauque-Olarte Sandra , Cifuentes-C Laura , Fong Cristian
Published: October 2023

Text mining enables search, extraction, categorisation and information visualisation. This study aimed to identify oral manifestations in patients with COVID-19 using text mining to facilitate extracting relevant clinical information from a large set of publications. A list of publications from the open-access COVID-19 Open Research Dataset was downloaded using keywords related to oral health and dentistry. A total of 694,366 documents were retrieved. Filtering the articles using text mining yielded 1,554 oral health/dentistry papers. The list of articles was classified into five topics after applying a Latent Dirichlet Allocation (LDA) model. This classification was compared to the author's classification which yielded 17 categories. After a full-text review of articles in the category “Oral manifestations in patients with COVID-19”, eight papers were selected to extract data. The most frequent oral manifestations were xerostomia (n = 405, 17.8%) and mouth pain or swelling (n = 289, 12.7%). These oral manifestations in patients with COVID-19 must be considered with other symptoms to diminish the risk of dentist-patient infection.
Deep learning-based sleep stage classification with cardiorespiratory and body movement activities in individuals with suspected sleep disorders
Authors: Morokuma Seiichi , Hayashi Toshinari , Kanegae Masatomo , Mizukami Yoshihiko , Asano Shinji , Kimura Ichiro , Tateizumi Yuji , Ueno Hitoshi , Ikeda Subaru , Niizeki Kyuichi
Published: October 2023

Deep learning methods have gained significant attention in sleep science. This study aimed to assess the performance of a deep learning-based sleep stage classification model constructed using fewer physiological parameters derived from cardiorespiratory and body movement data. Overnight polysomnography (PSG) data from 123 participants (age: 19–82 years) with suspected sleep disorders were analyzed. Multivariate time series data, including heart rate, respiratory rate, cardiorespiratory coupling, and body movement frequency, were input into a bidirectional long short-term memory (biLSTM) network model to train and predict five-class sleep stages. The trained model's performance was evaluated using balanced accuracy, Cohen's κ coefficient, and F1 scores on an epoch-per-epoch basis and compared with the ground truth using the leave-one-out cross-validation scheme. The model achieved an accuracy of 71.2 ± 5.8%, Cohen's κ of 0.425 ± 0.115, and an F1 score of 0.650 ± 0.083 across all sleep stages, and all metrics were negatively correlated with the apnea–hypopnea index, as well as age, but positively correlated with sleep efficiency. Moreover, the model performance varied for each sleep stage, with the highest F1 score observed for N2 and the lowest for N3. Regression and Bland–Altman analyses between sleep parameters of interest derived from deep learning and PSG showed substantial correlations (r = 0.33–0.60) with low bias. The findings demonstrate the efficacy of the biLSTM deep learning model in accurately classifying sleep stages and in estimating sleep parameters for sleep structure analysis using a reduced set of physiological parameters. The current model without using EEG information may expand the application of unobtrusive in-home monitoring to clinically assess the prevalence of sleep disorders outside of a sleep laboratory.
Risk Assessment of Large-scale Nanoparticle Uses
Authors: Akdogan Ozan , Bagci Canan , Akdogan Nilay Gunduz , Ozunlu Sedef
Published: October 2023

As the size of high-tech devices is becoming smaller day by day, the main field of science that feeds this demand is nanotechnology. Getting smaller is not only an issue of size reduction but, on the other hand, novel and unorthodox phenomena are uncovered. Nanotechnology is a scientific field in which nature has been familiar for a very long time and the lead role of this field is reserved for nanoparticles. For the past 60 years, the demand for nanoparticles has been increasing exponentially. To meet the demands of the industry, large-scale production routes have been developed. From one point of view, nanoparticles are now an integral part of our life and revolutionized technology but, on the other hand, large-scale production and use of nanoparticles impose many risks on humans, the environment, and different organisms by means of different exposure routes. In this book chapter, the most used nanoparticle properties, characterization methods and large-scale production routes are reviewed extensively. In addition, an elaborative discussion is presented about the risk assessment approaches for these nanoparticles. Besides the proposed validation steps for these assessments, in vitro and in vivo study results are reviewed together with the effects of engineered nanoparticles on different organisms and the environment. The worldwide regulations and legislations about large-scale engineered nanoparticles and the future perspectives are also mentioned in the context of this chapter.
Multiplexing potential of NIR resonant and non-resonant Raman reporters for bio-imaging applications
Authors: Eremina Olga E. , Schaefer Sarah , Czaja Alexander T. , Awad Samer , Lim Matthew A. , Zavaleta Cristina
Published: October 2023

Non-resonant SERS reporters and NIR-resonant heptamethine cyanine SERRS dyes, which have been routinely used for biomedical imaging, have different levels of multiplexing capabilities for accurate biomarker detection.
A perylenemonoimide-based fluorescent probe: ultrasensitive and selective tracing of endogenous peroxynitrite in living cells
Authors: Khan Aasif , Meena Vinod Kumar , Silswal Akshay , Koner Apurba Lal
Published: October 2023

Red-emitting PMI-BE was synthesized for ultrasensitive nanomolar detection of peroxynitrite. PMI-BE also responds to endogenously generated peroxynitrite in live macrophase cells.
Vanadium-doped graphitic carbon nitride for high performance lithium–sulfur batteries
Authors: Wang Yankang , Wang Yanbo , Huang Chunhong , Zhang Qiang , Liu Zhanghaoran , Zhang Fengxiang
Published: October 2023

High load V@gC3N4-ND catalyst for lithium-sulfur batteries.
Preparation of a Janus copper mesh via nanoparticle interface self-assembly for unidirectional water transportation
Authors: Chen Chaolang , Zhu Linfeng , Jiang Ruisong , Li Xuan
Published: October 2023

A novel colloidal interface self-assembly technology is developed to fabricate Janus meshes for unidirectional water transport. Besides, for the first time, their water transport mechanism was fully revealed using numerical simulation.
Half-substituted fluorocycloparaphenylenes with high symmetry: synthesis, properties and derivatization to densely substituted carbon nanorings
Authors: Shudo Hiroki , Kuwayama Motonobu , Segawa Yasutomo , Yagi Akiko , Itami Kenichiro
Published: October 2023

Synthesis and properties of novel fluorinated cycloparaphenylenes (FCPPs), F16[8]CPP and F12[6]CPP, were reported. Furthermore, the derivatization of F16[8]CPP afforded a new carbon nanoring where sixteen pyrroles are densely substituted.
Influence of Na+ on vaterite formation, content and yield using steamed ammonia liquid waste as a calcium source
Authors: Song Xuewen , Hua Xinrui , Zhang Xiaomin , Tuo Yuxin , Su Yihan , Ma Jianxiang , Mu Sicheng , Chen Tianxing , He Panyang , Ma Lianjing , Weng Cunjian
Published: October 2023

The effect of Na+ concentration on the crystalline phase, morphology, and content of vaterite in a system with different Ca2+ and CO32− ratios using steamed ammonia liquid waste as the calcium source and the effect of Na+ on the yield of vaterite was studied systematically for the first time.
Mechanistic model for quantifying the effect of impact force on mechanochemical reactivity
Authors: Nwoye Emmanuel , Raghuraman Shivaranjan , Costales Maya , Batteas James , Felts Jonathan R.
Published: October 2023

This paper presents methodology to quantitatively link the macroscale ball mill reaction parameters to fundamental drivers of chemical reactivity using a novel ball mill reactor with precise force control and integrated measurement.
Secondary-structure phase formation for semiflexible polymers by bifurcation in hyperphase space
Authors: Aierken Dilimulati , Bachmann Michael
Published: October 2023

The bifurcation of the collapse transition line creates a stable phase of secondary loop and hairpin structures in the hyperphase diagram of semiflexible polymers.
A theoretical study of novel orthorhombic group-IVB nitride halide monolayers for photocatalytic overall water splitting
Authors: Wang Jiali , Lu Jiajun , Zhao Xiuwen , Hu Guichao , Yuan Xiaobo , Qi Siyun , Ren Junfeng
Published: October 2023

It is shown theoretically that the novel orthorhombic Hf2N2Br2, HfZrN2Br2, and Hf2N2ClBr monolayers can spontaneously achieve overall water splitting within wide pH ranges.
Daisy chain architectures: from discrete molecular entities to polymer materials
Authors: Moulin Emilie , Carmona-Vargas Christian C. , Giuseppone Nicolas
Published: October 2023

We review recent progresses in the synthesis and the use of daisy chain architectures as molecular machines and stimuli-responsive materials.
Synthesis of novel solid scale inhibitors based on silver tungstate loaded KIT-6 for scale removal from produced water: static and modeling evaluation
Authors: Salem Heba M. , Mubarak Mahmoud F. , Abdelrahman Asmaa A. , Hosny R.
Published: October 2023

Synthesized solid scale inhibitors based on Ag2WO4 loaded KIT-6 were evaluated for their scaling inhibition properties using a static jar test. The synthesized materials were effective scale inhibitors for calcium carbonate, with an inhibition efficiency of 99%.
Introduction to Dalton Transactions themed issue – New Talent: Asia-Pacific (2023)
Authors: Uemura Takashi , Bera Jitendra K. , Brooker Sally , Zheng Li-Min
Published: October 2023

Takashi Uemura, Jitendra K. Bera, Sally Brooker and Li-Min Zheng introduce the Dalton Transactions themed issue “New Talent: Asia-Pacific (2023)”.