bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractAlzheimer’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

AbstractIon 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

AbstractClarifying 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

AbstractEpigenetic 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

AbstractCooperativity 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

AbstractsQuantitatively 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

AbstractMany 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

AbstractImprovements 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

AbstractHousehold 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

AbstractUnlike 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

AbstractIncreasing 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

AbstractElectroencephalogram (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

AbstractText 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

AbstractDeep 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.
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.