bluuebunny/crossref_metadata_2025_split huggingface dataset:
GOLEM: A tool for visualizing the distribution of Gene regulatOry eLEMents within the plant promoters with a focus on male gametophyte
Authors: Nevosád Lukáš , Klodová Božena , Raček Tomáš , Přerovská Tereza , Kusová Alžbeta , Svobodová Radka , Honys David , Schrumpfová Petra Procházková 
Published: August 2024

AbstractBackgroundThe regulation of gene expression during tissue development is very complex. A key mechanism of gene regulation is the recognition of regulatory motifs, also known as cis-regulatory elements (CREs), by various proteins in gene promoter regions. Localization of these motifs near the transcription start site (TSS) or translation start site (ATG) is crucial for transcription initiation and rate. Transcription levels of individual genes, regulated by these motifs, can vary significantly across tissues and developmental stages, especially in processes like sexual reproduction. However, the precise localization and visualization of regulatory motifs in relation to gene expression in specific tissues can be challenging.ResultsHere, we introduce a program called GOLEM (Gene regulatOry eLEMents) which enables users to precisely locate any motif of interest with respect to TSS or ATG within the relevant plant genomes across the plant Tree of Life (Marchantia, Physcomitrium, Amborella, Oryza, Zea, SolanumandArabidopsis). The visualization of the motifs is performed with respect to the transcript levels of particular genes in leaves and male reproductive tissues and can be compared with genome-wide distribution regardless of the transcription level. Additionally, genes with specific CREs at defined positions and high expression in selected tissues can be exported for further analysis. GOLEM’s functionality is illustrated by its application to conserved motifs (e.g. TATA-box, ABRE, I-box, and TC-element), as well as to male gametophyte-related motifs (e.g. LAT52, MEF2, ARR10_core, and DOF_core).ConclusionGOLEM is a freely available tool (https://golem.ncbr.muni.cz) for tracking the precise localization and distribution of any CREs of interest in plant gene promoters.Graphical abstract
Slow-wave sleep and REM sleep differentially contribute to memory representational transformation
Authors: Liu Jing , Chen Danni , Xia Tao , Zeng Shengzi , Xue Gui , Hu Xiaoqing 
Published: August 2024

AbstractMemory transforms over time, gradually becoming less idiosyncratic and more gist-like. While sleep contributes to memory transformation, how different sleep stages and EEG activity influence memory transformation is far from clear. Applying representational similarity analysis to electroencephalogram (EEG) recordings, we examined memory representational transformation at both the idiosyncratic “item-level” and the generic “category-level”. Our findings revealed that after an overnight sleep, item-level neural representations for post-sleep remembered items were abolished. In contrast, category-level representations remained prominent, but they became distinctive from pre-sleep. Across participants, more rapid eye movement (REM) sleep relative to slow-wave sleep (SWS) was associated with reduced item-level neural representational strength, increased category-level representational strength, as well as the decreased item-level representational similarity between pre-sleep learning and post-sleep retrieval sessions. Moreover, the theta and beta EEG power during REM sleep, and delta power during SWS differentially supported these representational transformations. These findings suggest that post-learning REM sleep and SWS play differential roles in supporting overnight memory transformation.
Gene Expression Prediction from Histology Images via Hypergraph Neural Networks
Authors: Li Bo , Zhang Yong , Wang Qing , Zhang Chengyang , Li Mengran , Wang Guangyu , Song Qianqian 
Published: August 2024

ABSTRACTSpatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing crucial insights into biological processes, disease mechanisms, and drug development. The prediction of gene expression based on cost-effective histology images is a promising yet challenging field of research. Existing methods for gene prediction from histology images exhibit two major limitations. First, they ignore the intricate relationship between cell morphological information and gene expression. Second, these methods do not fully utilize the different latent stages of features extracted from the images. To address these limitations, we propose a novel hypergraph neural network model, HGGEP, to predict gene expressions from histology images. HGGEP includes a gradient enhancement module to enhance the model’s perception of cell morphological information. A lightweight backbone network extracts multiple latent stage features from the image, followed by attention mechanisms to refine the representation of features at each latent stage and capture their relations with nearby features. To explore higher-order associations among multiple latent stage features, we stack them and feed into the hypergraph to establish associations among features at different scales. Experimental results on multiple datasets from disease samples including cancers and tumor disease, demonstrate the superior performance of our HGGEP model than existing methods.Key PointsWe develop a novel histology image-based gene prediction model named HGGEP, which demonstrates high accuracy and robust performance.To reveal the intricate relationship between cell morphology and gene expression in images, we propose a gradient enhancement module, which effectively improves the model’s capability in perceiving cell morphology in images.HGGEP includes a hypergraph module that efficiently models higher-order associations among features across multiple latent stages, resulting in significant performance improvement.
High-grade serous ovarian cancer development and anti-PD-1 resistance is driven by IRE1α activity in neutrophils
Authors: Emmanuelli Alexander , Salvagno Camilla , Min-Hwang Sung , Awasthi Deepika , Sandoval Tito A. , Chae Chang-Suk , Cheong Jin-Gyu , Tan Chen , Iwawaki Takao , Cubillos-Ruiz Juan R. 
Published: August 2024

AbstractHigh-grade serous ovarian cancer (HGSOC) is an aggressive malignancy that remains refractory to current immunotherapies. While advanced stage disease has been extensively studied, the cellular and molecular mechanisms that promote early immune escape in HGSOC remain largely unexplored. Here we report that primary HGSO tumors program neutrophils to inhibit T cell anti-tumor function by activating the endoplasmic reticulum (ER) stress sensor IRE1α. We found that intratumoral neutrophils exhibited overactivation of ER stress response markers compared with their counterparts at non-tumor sites. Selective deletion of IRE1α in neutrophils delayed primary ovarian tumor growth and extended the survival of mice with HGSOC by enabling early T cell-mediated tumor control. Notably, loss of IRE1α in neutrophils sensitized tumor-bearing mice to PD-1 blockade, inducing HGSOC regression and long-term survival in ∼50% of treated hosts. Hence, neutrophil-intrinsic IRE1α facilitates early adaptive immune escape in HGSOC and targeting this ER stress sensor might be used to unleash endogenous and immunotherapy-elicited immunity that controls metastatic disease.
Transcranial focused ultrasound modulates visual thalamus in a nonhuman primate model
Authors: Yu Kai , He Bin 
Published: August 2024

AbstractThe thalamus plays a pivotal role as a neural hub, integrating and distributing visual information to cortical regions responsible for visual processing. Transcranial focused ultrasound (tFUS) has emerged as a promising non-invasive brain stimulation technology, enabling modulation of neural circuits with high spatial precision. This study investigates the tFUS neuromodulation at visual thalamus and characterizes the resultant effects on interconnected visual areas in a nonhuman primate model. Experiments were conducted on a rhesus macaque trained in a visual fixation task, combining tFUS stimulation with simultaneous scalp electroencephalography (EEG) and intracranial recordings from area V4, a region closely linked to the thalamus. Ultrasound was delivered through a 128-element random array ultrasound transducer operating at 700 kHz, with the focus steered onto the pulvinar of the thalamus based on neuroanatomical atlas and individual brain model. EEG source imaging revealed localized tFUS-induced activities in the thalamus, midbrain, and visual cortical regions. Critically, tFUS stimulation of the pulvinar can elicit robust neural responses in V4 without visual input, manifested as significant modulations in local field potentials, elevated alpha and gamma power, corroborating the functional thalamocortical connectivity. Furthermore, the tFUS neuromodulatory effects on visually-evoked V4 activities were region-specific within the thalamus and dependent on ultrasound pulse repetition frequency. This work provides direct electrophysiological evidence demonstrating the capability of tFUS in modulating the visual thalamus and its functional impact on interconnected cortical regions in a large mammalian model, paving the way for potential investigations for tFUS treating visual, sensory, and cognitive impairments.
CqHKT1 and CqSOS1 mediate genotype-dependent Na+exclusion under high salt stress in quinoa
Authors: Kobayashi Yasufumi , Sugita Ryohei , Fujita Miki , Yasui Yasuo , Murata Yoshinori , Ogata Takuya , Nagatoshi Yukari , Fujita Yasunari 
Published: August 2024

AbstractSalinity threatens crop production worldwide, and salinized areas are steadily increasing. As most crops are sensitive to salt, there is a need to improve the salt tolerance of major crops and promote the cultivation of under-utilized salt-tolerant crops. Quinoa, a pseudocereal and leafy vegetable from the Andean region of South America, is highly salt-tolerant, thrives in marginal environments, and has excellent nutritional properties. Research has often focused on epidermal bladder cells, a feature of quinoa thought to contribute to salt tolerance; however recent evidence suggests that these cells are not directly involved. The salt tolerance mechanism in quinoa remains unclear. Here, we show genotype-dependent differences in Na+and K+accumulation mechanisms using representative 18 lines of three genotypes by focusing on young quinoa seedlings at a stage without epidermal bladder cells. High salinity (600 mM NaCl) did not affect the early growth of all three quinoa genotypes. Under high salinity, lowland quinoa lines accumulated the most Na+in the aerial parts, whereas southern highland lines accumulated the least. By contrast, K+accumulation was slightly reduced in the aerial parts but significantly decreased in roots of all the genotypes. Resequencing of 18 quinoa lines supports the notion that genotype determines aboveground Na+uptake and gene expression in response to salt stress. Using virus-induced gene silencing, we further demonstrated that CqHKT1 and CqSOS1 mediate Na+exclusion in quinoa. These findings provide insight into salt tolerance mechanisms, serving as a basis for improving crop production under salt stress.
Models of microbiome evolution incorporating host resource provisioning
Authors: Xiao Yao , Li Teng , Rodrigo Allen 
Published: August 2024

AbstractMulticellular hosts and their associated microbial partners (i.e., microbiomes) often interact in mutually beneficial ways. Consequently, hosts may choose to allocate resources to regulate and recruit appropriate microbes. In doing so, hosts may incur an energetic cost, and in turn, these costs can affect host fitness. It remains unclear how hosts have evolved to balance the costs of expending resources to manage their microbiomes against the benefits that might accrue by doing so. We extended a previously-developed agent-based computational model of hostmicrobiome evolution by incorporating a resource provisioning process, whereby hosts provide resources to support beneficial microbes and suppress harmful microbes, with attendant fitness costs. Our results indicate that the ways and sources from which a host acquires microbes are crucial factors influencing the host’s willingness to provide resources, to regulate microbiome composition. The intensity of resource provisioning will depend, in part, on how much of their microbiome hosts contribute to, and obtain from, their environment: when hosts that engage in resource provisioning contribute a high percentage of their microbiome to the environment, then there is less evolutionary imperative for other hosts to also provide resources. Since resource provisioning incurs a fitness cost to the host, over evolutionary time, resource provisioning will not be favored. Additionally, if selection at the microbial level is not sufficiently strong, and the host obtains a high proportion of microbes from the environment, then the higher the proportion of beneficial microbes in the environment, the less the host is willing to provide resources.
A COVID-19 Rapid Antigen Test Employing Upconversion Nanoparticles
Authors: Zhang Le , Zhou Jiajia , Shimoni Olga , Wen Shihui , Alghalayini Amani , Liu Yuan , Rezaeishahmirzadi Meysam , Liao Jiayan , Maddahfar Mahnaz , Hunt Roger , Black Murdo , Johansen Matt D. , Hansbro Phil M. , Zhang Lin , Stenzel Martina , Warkiani Majid , Valenzuela Stella M , Jin Dayong 
Published: August 2024

AbstractThe COVID-19 pandemic has underscored the critical need for rapid and accurate diagnostic tools. Current methods, including PCR and rapid antigen tests (RAT), have limitations in speed, sensitivity, and the requirement for specialized equipment and trained personnel. Nanotechnology, particularly upconversion nanoparticles (UCNPs), offer a promising alternative due to their unique optical properties. UCNPs can convert low-energy near-infrared (NIR) light into higher-energy visible light, making them ideal for use as optical probes in single molecule detection and point of care applications. This study, initiated in early 2020, explores the opportunity of using highly doped UCNPs (40%Yb3+/4%Er3+) in lateral flow assay (LFA) for the early diagnosis of COVID-19. The UCNPs-based LFA testing demonstrated a minimum detection concentration of 100 pg/mL for SARS-CoV-2 antigen and 105CCID50/mL for inactivated virus. Clinical trials, conducted in Malaysia and Western Australia independently, showed that the technique was at least 100 times more sensitive than commercial RAT kits, with a sensitivity of 100% and specificity of 91.34%. The development process involved multidisciplinary collaborations, resulting in the Virulizer device, an automated strip reader for point-of-care testing. This work sets a reference for future development of highly sensitive and quantitative rapid antigen tests, aiming for the Limits of Detection (LoD) in the range of sub-ng/mL.
Evaluation of High-Affinity Monoclonal Antibodies and Antibody-Drug Conjugates by Homogenous Time-Resolved FRET
Authors: Greenway Harmon , Wang Jin 
Published: August 2024

ABSTRACTThe rapid growth of therapeutic monoclonal antibodies demands greater accessibility to scalable methods of evaluating antigen binding. Homogenous TR-FRET is ideal for preliminary screening but has not been reported to assay these interactions due to their high-affinity and complex solution-phase kinetics. Here we report the development of a competition assay to rank-order the relative affinities of these drugs for a common antigen. The assay is compatible with automation, requires no modification of the analytes, and measures affinities as low as single-digit picomolar. We further demonstrate applications to inform the development of antibody-drug conjugates. The assay may aid discovery and manufacturing of therapeutic antibodies as a low-cost, high-throughput alternative to existing technologies.
PCL-seq: enhanced high-resolution transcriptomic profiling of region of interest in fresh frozen and FFPE tissues
Authors: Dong Xue , Cui Xiaonan , Hu Mengzhu , Zhou Wenjian , Shi Weiyang 
Published: August 2024

AbstractThe spatial heterogeneity of gene expression has propelled the development of multiple spatial transcriptomics technologies. Here, we presentphotocleavage andligation sequencing (PCL-seq), an method for spatial indexing using a light-controlled DNA labeling strategy on tissue section. PCL-seq uses photocleavable oligonucleotides and ligation adapters to construct transcription profiles of region of interest (ROI), selected by microscopically controlled photo illumination apparatus in tissue sections. Applied to mouse embryos, PCL-seq obtains gene expression matrices that align with spatial locations and competitive data quality, featuring around 1.7×105UMIs and 8,600 genes (irradiation diameter=100µm). PCL-seq can also apply to formalin fixation and paraffin embedding (FFPE) mouse embryo sections, whereas obtained competitive data output and recovered thousands of differentially enriched transcripts from limb and skeleton. Additionally, PCL-seq can achieve subcellular resolution, which was demonstrated for differential expression between nuclear and cytoplasmic. Thus, PCL-seq provides an accessible workflow for spatial transcriptomic analysis in frozen and FFPE tissue at subcellular resolution.
Barriers to Access to Care Evaluation Scale - Proxy Report (BACE-PR): evidence of reliability and validity for caregivers reporting on children and adolescents with mental health concerns in Greece
Authors: Kotsis Konstantinos , Thornicroft Graham , Schafer Julia Luiza , Serdari Aspasia , Basta Maria , Casella Caio Borba , Marchionatti Lauro Estivalete , Hoffmann Mauricio Scopel , Tzotzi Alexandra , Mitropoulou Andromachi , Simioni André Rafael , Papanikolaou Katerina , Koumoula Anastasia , Salum Giovanni Abrahão 
Published: August 2024

AbstractBackgroundTo improve access to mental health care for children and adolescents, it is necessary to identify the barriers faced by their caregivers. The aim of this study is to identify these barriers in Greece and to investigate the reliability and validity of the modified version of the Barriers to Access to Care Evaluation scale (BACE) - the BACE Proxy Report (BACE-PR).MethodsA total of 265 caregivers completed the BACE-PR. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to investigate the factor structure of the instrument. Item parameters were assessed via Item Response Theory. Interpretability was assessed by linking summed scores to IRT-based scores.ResultsCaregivers reported care costs as the major barrier to access. Obsessive compulsive symptoms and self-harm were the conditions for which caregivers reported the highest level of barriers. EFA and CFA suggested that a one-factor solution fit the data well (RMSEA = 0.048, CFI = 0.991, TLI = 0.990). Internal consistency was found to be high (ω=0.96). Average z-scores provided five meaningful levels of caregivers’ perceived barriers compared to the national average.ConclusionsCaregivers face a variety of barriers to access mental health care for their children and this could partly explain the treatment gap in the Greek mental health sector. Our study provides evidence for the reliability and validity of the BACE-PR scale, which can aid to identify caregiver-perceived barriers and to design interventions to improve access to mental health care.
A Balanced Bagging Classifier machine learning model-based web application to predict risk of febrile neutropenia in cancer patients
Authors: Bozcuk HŞ , Yıldız M. 
Published: August 2024

ABSTRACTBackgroundAlthough several models exist to predict risk of febrile neutropenia in cancer patients, there is still need to more accurately quantify this risk to minimize morbidity of and mortality from this treatment toxicity.Material and methodsFrom previous reports of our group, un updated predictive model had emerged. We refined our algorithm even further by using Balanced Bagging Classifier (BBC) machine learning in the previous model derivation cohort, discarding all the missing data. Moreover, we made a web application to make it accessible for experimental clinical use.ResultsWe used clinical data from 3439 cycles of chemotherapy obtained from the periods of 2010-2011 and 2015-2019, with 133 episodes of febrile neutropenia observed (after 4% of chemotherapy cycles). BBC resulted in a more efficient model as reflected by an area under curve (AUC) of 0.97, accuracy of 0.95, sensitivity of 0.93, and specificity of 0.95. Permutation importance analysis revealed previous febrile neutropenia, cancer type and receipt of previous radiotherapy as the most important features for the BBC model. The web app that integrates the BBC model with a user-friendly user interface has been found to be clinically useful.ConclusionsUsing machine learning with our previous data, we are now able to predict the risk of febrile neutropenia more effectively after chemotherapy in cancer patients. The resultant web application is functional and makes use of the developed machine learning model to predict febrile neutropenia.
Elevated Cardiovascular Biomarkers Following Hypertensive Disorder of Pregnancy
Authors: Gabel Austin M. , Cheu Lindsay , Pike Mindy , Olerich Kelsey L , Kachikis Alisa , McCartney Stephen A , Shree Raj 
Published: August 2024

ABSTRACTHypertensive disorder of pregnancy (HDP) is associated with an increased risk for later-life cardiovascular disease (CVD). Whether the HDP pregnancy itself confers risk towards CVD later in life is suggested in several epidemiologic studies. Given this connection and that the HDP exposure itself may play a role, understanding whether markers associated with cardiovascular risk vary based on HDP history in the years following pregnancy may assist with risk stratification and development of targeted interventions. We measured 77 proteins (CVD-associated and inflammatory markers) in n=22 individuals with a history of HDP and n=43 matched controls with no HDP history at a median of 4 years after pregnancy. Several CVD-associated proteins (fibrinogen, fetuin-A, L-selectin, and alpha-1-acid glycoprotein) were significantly elevated, by orders of magnitude, in individuals with a history of HDP compared to normotensive pregnancies (all p<0.0001). In multivariable linear regression models controlling for age, body mass index, chronic hypertension, and diabetes, a history of HDP remained associated with higher levels of CVD-associated proteins (all p<0.0001). We clustered samples based on global patterns of CVD protein expression and found a significant difference in CVD protein expression patterns between post-Normal and post-HDP samples. Conversely, differences in circulating inflammatory markers were largely insignificant or more subtle than that observed with the CVD-associated proteins. Identification of biomarkers associated with CVD in the intervening years after HDP but before evident CVD is critical to understanding post-HDP cardiovascular risk to provide insight for the development of therapeutic interventions that mitigate CVD event risk in this high-risk population.