bluuebunny/crossref_metadata_2025_split huggingface dataset:
The development of depressive symptoms in older adults from a network perspective in the English Longitudinal Study of Ageing
Authors: Schlechter Pascal , Ford Tamsin J. , Neufeld Sharon A. S. 
Published: November 2023

AbstractAn increased understanding of the interrelations between depressive symptoms among older populations could help improve interventions. However, studies often use sum scores to understand depression in older populations, neglecting important symptom dynamics that can be elucidated in evolving depressive symptom networks. We computed Cross-Lagged Panel Network Models (CLPN) of depression symptoms in 11,391 adults from the English Longitudinal Study of Ageing. Adults aged 50 and above (mean age 65) were followed over 16 years throughout this nine-wave representative population study. Using the eight-item Center for Epidemiological Studies Depression Scale, we computed eight CLPNs covering each consecutive wave. Across waves, networks were consistent with respect to the strength of lagged associations (edge weights) and the degree of interrelationships among symptoms (centrality indices). Everything was an effort and could not get going displayed the strongest reciprocal cross-lagged associations across waves. These two symptoms and loneliness were core symptoms as reflected in strong incoming and outgoing connections. Feeling depressed was strongly predicted by other symptoms only (incoming but not strong outgoing connections were observed) and thus was not related to new symptom onset. Restless sleep had outgoing connections only and thus was a precursor to other depression symptoms. Being happy and enjoying life were the least central symptoms. This research underscores the relevance of somatic symptoms in evolving depression networks among older populations. Findings suggest the central symptoms from the present study (everything was an effort, could not get going, loneliness) may be potential key intervention targets to mitigate depression in older adults.
Sulforaphane alleviates psoriasis by enhancing antioxidant defense through KEAP1-NRF2 Pathway activation and attenuating inflammatory signaling
Authors: Ma Chujun , Gu Chaode , Lian Panpan , Wazir Junaid , Lu Renwei , Ruan Binjia , Wei Lulu , Li Li , Pu Wenyuan , Peng Ziqi , Wang Wentong , Zong Yangyongyi , Huang Zhiqiang , Wang Hongwei , Lu Yan , Su Zhonglan 
Published: November 2023

AbstractPsoriasis is a chronic inflammatory skin disease that affects millions of people worldwide. Sulforaphane (SFN) has been shown to have anti-inflammatory and antioxidant properties. In this study, we investigated the effects of SFN on a mouse model of psoriasis induced by imiquimod (IMQ) and its underlying molecular mechanism. Mice treated with SFN showed significant improvement in psoriatic symptoms, including reduced erythema, scales, and cutaneous thickness. Histopathological analysis and immunohistochemical staining revealed decreased expression of K16, K17, and Ki67 in SFN-treated mice, indicating reduced abnormal differentiation of keratinocytes and cutaneous inflammation. SFN treatment also reduced the activation of STAT3 and NF-κB pathways and downregulated pro-inflammatory cytokines IL-1β, IL-6, and CCL2. In vitro experiments using HaCaT cells demonstrated that SFN inhibited IL-22 and TNF-α-induced activation of inflammatory pathways and keratinocyte proliferation. Network pharmacology analysis suggested that the KEAP1-NRF2 pathway might be involved in the protective effects of SFN on psoriasis. We observed reduced NRF2 expression in human psoriatic lesions, and subsequent experiments showed that SFN activated KEAP1-NRF2 pathway in vivo and in vitro. Importantly, NRF2-deficient mice exhibited aggravated psoriasis-like symptoms and reduced response to SFN treatment. Our findings indicate that SFN ameliorates psoriasis symptoms and inflammation through the KEAP1-NRF2 pathway, suggesting a potential therapeutic role for SFN in the treatment of psoriasis.
DNA methylation-activated full-length EMX1 facilitates metastasis through EMX1-EGFR-ERK axis in hepatocellular carcinoma
Authors: Wen Dong-sheng , Huang Li-chang , Bu Xiao-yun , He Min-ke , Lai Zhi-cheng , Du Ze-feng , Huang Ye-xing , Kan Anna , Shi Ming 
Published: November 2023

AbstractAltered DNA methylation is a crucial epigenetic event in hepatocellular carcinoma (HCC) development and progression. Through methylation-transcriptomic analysis, we identified a set of sixty potential DNA methylation-based epidriver genes. In this set of genes, we focused on the hypermethylation of EMX1, which is frequently observed in hepatobiliary tumors. Despite of its frequent occurrence, the function of EMX1 remains largely unknown. By utilizing bisulfite-next-generation sequencing, we have detected EMX1 DNA hypermethylation on the gene body, which is positively correlated with EMX1 mRNA expression. Further analysis revealed that EMX1 mRNA terminal exon splicing in HCC generated two protein isoforms: EMX1 full length (EMX1-FL) and alternative terminal exon splicing isoform (EMX1-X1). Cellular functional assays demonstrated that gain-of-function EMX1-FL, but not EMX1-X1, induced HCC cells migration and invasion while silencing EMX1-FL inhibited HCC cells motility. This result was further validated by in vivo tumor metastasis models. Mechanistically, EMX1-FL bound to EGFR promoter, promoting EGFR transcription and activating EGFR-ERK signaling to trigger tumor metastasis. Therefore, EGFR may be a potential therapeutic target for EMX1-high expression HCC. Our work illuminated the crucial role of gene body hypermethylation-activated EMX1-FL in promoting tumorigenesis and metastasis in HCC. These findings pave the way for targeting the EMX1-EGFR axis in HCC tumorigenicity and metastasis.
Vascular dysfunction caused by loss of Brn-3b/POU4F2 transcription factor in aortic vascular smooth muscle cells is linked to deregulation of calcium signalling pathways
Authors: Yogendran Vaishaali , Mele Laura , Prysyazhna Oleksandra , Budhram-Mahadeo Vishwanie S. 
Published: November 2023

AbstractPhenotypic and functional changes in vascular smooth muscle cells (VSMCs) contribute significantly to cardiovascular diseases (CVD) but factors driving early adverse vascular changes are poorly understood. We report on novel and important roles for the Brn-3b/POU4F2 (Brn-3b) transcription factor (TF) in controlling VSMC integrity and function. Brn-3b protein is expressed in mouse aorta with localisation to VSMCs. Male Brn-3b knock-out (KO) aortas displayed extensive remodelling with increased extracellular matrix (ECM) deposition, elastin fibre disruption and small but consistent narrowing/coarctation in the descending aortas. RNA sequencing analysis showed that these effects were linked to deregulation of genes required for calcium (Ca2+) signalling, vascular contractility, sarco-endoplasmic reticulum (S/ER) stress responses and immune function in Brn-3b KO aortas and validation studies confirmed changes in Ca2+ signalling genes linked to increased intracellular Ca2+ and S/ER Ca2+ depletion [e.g. increased, Cacna1d Ca2+ channels; ryanodine receptor 2, (RyR2) and phospholamban (PLN) but reduced ATP2a1, encoding SERCA1 pump] and chaperone proteins, Hspb1, HspA8, DnaJa1 linked to increased S/ER stress, which also contributes to contractile dysfunction. Accordingly, vascular rings from Brn-3b KO aortas displayed attenuated contractility in response to KCl or phenylephrine (PE) while Brn-3b KO-derived VSMC displayed abnormal Ca2+ signalling following ATP stimulation. This data suggests that Brn-3b target genes are necessary to maintain vascular integrity /contractile function and deregulation upon loss of Brn-3b will contribute to contractile dysfunction linked to CVD.
Loss of p53 function promotes DNA damage-induced formation of nuclear actin filaments
Authors: Torii Takeru , Sugimoto Wataru , Itoh Katsuhiko , Kinoshita Natsuki , Gessho Masaya , Goto Toshiyuki , Uehara Ikuno , Nakajima Wataru , Budirahardja Yemima , Miyoshi Daisuke , Nishikata Takahito , Tanaka Nobuyuki , Hirata Hiroaki , Kawauchi Keiko 
Published: November 2023

AbstractTumor suppressor p53 plays a central role in response to DNA damage. DNA-damaging agents modulate nuclear actin dynamics, influencing cell behaviors; however, whether p53 affects the formation of nuclear actin filaments remains unclear. In this study, we found that p53 depletion promoted the formation of nuclear actin filaments in response to DNA-damaging agents, such as doxorubicin (DOXO) and etoposide (VP16). Even though the genetic probes used for the detection of nuclear actin filaments exerted a promotive effect on actin polymerization, the detected formation of nuclear actin filaments was highly dependent on both p53 depletion and DNA damage. Whilst active p53 is known to promote caspase-1 expression, the overexpression of caspase-1 reduced DNA damage-induced formation of nuclear actin filaments in p53-depleted cells. In contrast, co-treatment with DOXO and the pan-caspase inhibitor Q-VD-OPh or the caspase-1 inhibitor Z-YVAD-FMK induced the formation of nuclear actin filament formation even in cells bearing wild-typep53. These results suggest that the p53-caspase-1 axis suppresses DNA damage-induced formation of nuclear actin filaments. In addition, we found that the expression of nLifeact-GFP, the filamentous-actin-binding peptide Lifeact fused with the nuclear localization signal (NLS) and GFP, modulated the structure of nuclear actin filaments to be phalloidin-stainable in p53-depleted cells treated with the DNA-damaging agent, altering the chromatin structure and reducing the transcriptional activity. The level of phosphorylated H2AX (γH2AX), a marker of DNA damage, in these cells also reduced upon nLifeact-GFP expression, whilst details of the functional relationship between the formation of nLifeact-GFP-decorated nuclear actin filaments and DNA repair remained to be elucidated. Considering that the loss of p53 is associated with cancer progression, the results of this study raise a possibility that the artificial reinforcement of nuclear actin filaments by nLifeact-GFP may enhance the cytotoxic effect of DNA-damaging agents in aggressive cancer cells through a reduction in gene transcription.
LINC01133 can induce acquired ferroptosis resistance by enhancing the FSP1 mRNA stability through forming the LINC01133-FUS-FSP1 complex
Authors: Wang Shaowen , Chen Jionghuang , Li Pengping , Chen Yangchao 
Published: November 2023

AbstractDue to a lack of research on the critical non-coding RNAs in regulating ferroptosis, our study aimed to uncover the crucial ones involved in the process. We found that LINC01133 could make pancreatic cancer cells more resistant to ferroptosis. A higher expression of LINC01133 was associated with a higher IC50 of sorafenib in clinical samples. Furthermore, we discovered that LINC01133 induced this process through enhancing the mRNA stability of FSP1. CEBPB was the transcription factor to increase the expression of LINC01133. A higher CEBPB could also indicate a higher IC50 of sorafenib in patients with cancer. Moreover, we confirmed that LINC01133 could form a triple complex with FUS and FSP1 to increase the mRNA stability of FSP1.
Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues
Authors: Pham Duy , Tan Xiao , Balderson Brad , Xu Jun , Grice Laura F. , Yoon Sohye , Willis Emily F. , Tran Minh , Lam Pui Yeng , Raghubar Arti , Kalita-de Croft Priyakshi , Lakhani Sunil , Vukovic Jana , Ruitenberg Marc J. , Nguyen Quan H. 
Published: November 2023

AbstractSpatial transcriptomics (ST) technologies generate multiple data types from biological samples, namely gene expression, physical distance between data points, and/or tissue morphology. Here we developed three computational-statistical algorithms that integrate all three data types to advance understanding of cellular processes. First, we present a spatial graph-based method, pseudo-time-space (PSTS), to model and uncover relationships between transcriptional states of cells across tissues undergoing dynamic change (e.g. neurodevelopment, brain injury and/or microglia activation, and cancer progression). We further developed a spatially-constrained two-level permutation (SCTP) test to study cell-cell interaction, finding highly interactive tissue regions across thousands of ligand-receptor pairs with markedly reduced false discovery rates. Finally, we present a spatial graph-based imputation method with neural network (stSME), to correct for technical noise/dropout and increase ST data coverage. Together, the algorithms that we developed, implemented in the comprehensive and fast stLearn software, allow for robust interrogation of biological processes within healthy and diseased tissues.
Real-data-driven real-time reconfigurable microwave reflective surface
Authors: Wen Erda , Yang Xiaozhen , Sievenpiper Daniel F. 
Published: November 2023

AbstractManipulating the electromagnetic (EM) scattering behavior from an arbitrary surface dynamically on arbitrary design goals is an ultimate ambition for many EM stealth and communication problems, yet it is nearly impossible to accomplish with conventional analysis and optimization techniques. Here we present a reconfigurable conformal metasurface prototype as well as a workflow that enables it to respond to multiple design targets on the reflection pattern with extremely low on-site computing power and time. The metasurface is driven by a sequential tandem neural network which is pre-trained using actual experimental data, avoiding any possible errors that may arise from calculation, simulation, or manufacturing tolerances. This platform empowers the surface to operate accurately in a complex environment including varying incident angle and operating frequency, or even with other scatterers present close to the surface. The proposed data-driven approach requires minimum amount of prior knowledge and human effort yet provides maximized versatility on the reflection control, stepping towards the end form of intelligent tunable EM surfaces.
Three-dimensional surface motion capture of multiple freely moving pigs using MAMMAL
Authors: An Liang , Ren Jilong , Yu Tao , Hai Tang , Jia Yichang , Liu Yebin 
Published: November 2023

AbstractUnderstandings of the three-dimensional social behaviors of freely moving large-size mammals are valuable for both agriculture and life science, yet challenging due to occlusions in close interactions. Although existing animal pose estimation methods captured keypoint trajectories, they ignored deformable surfaces which contained geometric information essential for social interaction prediction and for dealing with the occlusions. In this study, we develop a Multi-Animal Mesh Model Alignment (MAMMAL) system based on an articulated surface mesh model. Our self-designed MAMMAL algorithms automatically enable us to align multi-view images into our mesh model and to capture 3D surface motions of multiple animals, which display better performance upon severe occlusions compared to traditional triangulation and allow complex social analysis. By utilizing MAMMAL, we are able to quantitatively analyze the locomotion, postures, animal-scene interactions, social interactions, as well as detailed tail motions of pigs. Furthermore, experiments on mouse and Beagle dogs demonstrate the generalizability of MAMMAL across different environments and mammal species.
Core-dependent post-translational modifications guide the biosynthesis of a new class of hypermodified peptides
Authors: Pei Zeng-Fei , Zhu Lingyang , Nair Satish K. 
Published: November 2023

AbstractThe ribosomally synthesized and post-translationally modified peptide (RiPPs) class of natural products has undergone significant expansion due to the rapid growth in genome sequencing data. Using a bioinformatics approach, we identify the dehydrazoles, a novel class of hypermodified RiPPs that contain both side chain dehydration of Ser residues, and backbone heterocyclization at Ser, Thr, and Cys residues to the corresponding azol(in)es. Structure elucidation of the hypermodified peptide carnazolamide, a representative class member, shows that 18 post-translational modifications are installed by just five enzymes. Complete biosynthetic reconstitution demonstrates that dehydration is carried out by an unusual DUF4135 dehydration domain fused to a zinc-independent cyclase domain (CcaM). We demonstrate that CcaM only modifies Ser residues that precede an azole in the core peptide. As heterocyclization removes the carbonyl following the Ser residue, CcaM likely catalyzes dehydration without generating an enolate intermediate. Additionally, CcaM does not require the leader peptide, and this core-dependence effectively sets the order for the biosynthetic reactions. Biophysical studies demonstrate direct binding of azoles to CcaM consistent with this azole moiety-dependent dehydration. Bioinformatic analysis reveals more than 50 related biosynthetic gene clusters that contain additional catalysts that may produce structurally diverse scaffolds.
Chromosome-level genome assembly of Przevalski’s partridge (Alectoris magna)
Authors: Wang Xumin , Xia Wenhao , Teng Xindong , Lin Wanying , Xing Zhikai , Wang Shuang , Liu Xiumei , Qu Jiangyong , Zhao Wei , Wang Lijun 
Published: November 2023

AbstractPrzevalski’s partridge (Alectoris magna) is one of the birds in the genus Alectoris endemic to China. The distribution of A. magna was narrow, and it was only found in parts of the Qinghai, Gansu, and Ningxia provinces. A. magna was considered a monotypic species until it was distinguished into two subspecies. However, external morphological characteristics, rather than genetic differences or evolutionary relationships, are now commonly used as evidence of subspecies differentiation. In this study, a chromosome-level reference genome of A. magna has been constructed by combining Illumina, PacBio and Hi-C sequencing data. The 1135.01 Mb A. magna genome was ultimately assembled. The genome showed 96.9% completeness (BUSCO), with a contig N50 length of 23.34 Mb. The contigs were clustered and oriented on 20 chromosomes, covering approximately 99.96% of the genome assembly. Additionally, altogether 19,103 protein-coding genes were predicted, of which 95.10% were functionally annotated. This high-quality genome assembly could serve as a valuable genomic resource for future research on the functional genomics, genetic protection, and interspecific hybridization of A. magna.
FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling
Authors: Chen Xianda , Zhu Meixin , Chen Kehua , Wang Pengqin , Lu Hongliang , Zhong Hui , Han Xu , Wang Xuesong , Wang Yinhai 
Published: November 2023

AbstractCar-following is a control process in which a following vehicle adjusts its acceleration to keep a safe distance from the lead vehicle. Recently, there has been a booming of data-driven models that enable more accurate modeling of car-following through real-world driving datasets. Although there are several public datasets available, their formats are not always consistent, making it challenging to determine the state-of-the-art models and how well a new model performs compared to existing ones. To address this gap and promote the development of microscopic traffic flow modeling, we establish the first public benchmark dataset for car-following behavior modeling. This benchmark consists of more than 80 K car-following events extracted from five public driving datasets under the same criteria. To give an overview of current progress in car-following modeling, we implemented and tested representative baseline models within the benchmark. The established benchmark provides researchers with consistent data formats and metrics for cross-comparing different car-following models, coming with open datasets and codes.
Coming in handy: CeTI-Age — A comprehensive database of kinematic hand movements across the lifespan
Authors: Muschter Evelyn , Schulz Jonas , Tömösközi Máté , Herbst Leonie , Küssel Lena , Sefunç Merve , Holtzhausen Stefan , Speidel Stefanie , Fitzek Frank H. P. , Li Shu-Chen 
Published: November 2023

AbstractThe Tactile Internet aims to advance human-human and human-machine interactions that also utilize hand movements in real, digitized, and remote environments. Attention to elderly generations is necessary to make the Tactile Internet age inclusive. We present the first age-representative kinematic database consisting of various hand gesturing and grasping movements at individualized paces, thus capturing naturalistic movements. We make this comprehensive database of kinematic hand movements across the adult lifespan (CeTI-Age-Kinematic-Hand) publicly available to facilitate a deeper understanding of intra-individual–focusing especially on age-related differences–and inter-individual variability in hand kinematics. The core of the database contains participants’ hand kinematics recorded with wearable resistive bend sensors, individual static 3D hand models, and all instructional videos used during the data acquisition. Sixty-three participants ranging from age 20 to 80 years performed six repetitions of 40 different naturalistic hand movements at individual paces. This unique database with data recorded from an adult lifespan sample can be used to advance machine-learning approaches in hand kinematic modeling and movement prediction for age-inclusive applications.
Structured dataset of human-machine interactions enabling adaptive user interfaces
Authors: Carrera-Rivera Angela , Reguera-Bakhache Daniel , Larrinaga Felix , Lasa Ganix , Garitano Iñaki 
Published: November 2023

AbstractThis article introduces a dataset of human-machine interactions collected in a controlled and structured manner. The aim of this dataset is to provide insights into user behavior and support the development of adaptive Human-Machine Interfaces (HMIs). The dataset was generated using a custom-built application that leverages formally defined User Interfaces (UIs). The resulting interactions underwent processing and analysis to create a suitable dataset for professionals and data analysts interested in user interface adaptations. The data processing stage involved cleaning the data, ensuring its consistency and completeness. A data profiling analysis was conducted for checking the consistency of elements in the interaction sequences. Furthermore, for the benefit of researchers, the code used for data collection, data profiling, and usage notes on creating adaptive user interfaces are made available. These resources offer valuable support to those interested in exploring and utilizing the dataset for their research and development efforts in the field of human-machine interfaces.
Plasma metabolomics profiling of 580 patients from an Early Detection Research Network prostate cancer cohort
Authors: Benedetti Elisa , Chetnik Kelsey , Flynn Thomas , Barbieri Christopher E. , Scherr Douglas S. , Loda Massimo , Krumsiek Jan 
Published: November 2023

AbstractProstate cancer is the second most common cancer in men and affects 1 in 9 men in the United States. Early screening for prostate cancer often involves monitoring levels of prostate-specific antigen (PSA) and performing digital rectal exams. However, a prostate biopsy is always required for definitive cancer diagnosis. The Early Detection Research Network (EDRN) is a consortium within the National Cancer Institute aimed at improving screening approaches and early detection of cancers. As part of this effort, the Weill Cornell EDRN Prostate Cancer has collected and biobanked specimens from men undergoing a prostate biopsy between 2008 and 2017. In this report, we describe blood metabolomics measurements for a subset of this population. The dataset includes detailed clinical and prospective records for 580 patients who underwent prostate biopsy, 287 of which were subsequentially diagnosed with prostate cancer, combined with profiling of 1,482 metabolites from plasma samples collected at the time of biopsy. We expect this dataset to provide a valuable resource for scientists investigating prostate cancer metabolism.