bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advances in navigating to the nodule and targeting
Authors: Graham Jeffrey , Basist Madeleine , Frye Laura , Agrawal Abhinav , Nasim Faria 
Published: November 2023

Purpose of review
The multitude of available platforms and imaging modalities for navigational bronchoscopy, in combination with the various sampling tools that can be used intra-procedurally, is complex. This review seeks to describe the recent developments in peripheral bronchoscopy in regards to navigation, imaging, and sampling target lesions in the pulmonary parenchyma.

Recent findings
Robotic assisted bronchoscopy has improved navigation to the peripheral airways for sampling of peripheral parenchymal lesions. These navigational platforms use innovative technology utilizing electromagnetic navigation and shape-sensing technology for guidance. The greatest improvement has been the stabilization of the robotic scope in the periphery to allow for accurate sampling. Despite improvements in these platforms, limitations of CT to body divergence continue to impact navigation to the lesion and therefore diagnostic yield of the procedure. Advanced intraprocedural imaging with cone beam CT or augmented fluoroscopy has been a recent focus to improve this area. Further, the adoption of newer sampling tools, such as cryobiopsy, offers the possibility of increased diagnostic yield.

Summary
The developments in advanced bronchoscopy will impact the role of biopsy in the diagnosis of peripheral pulmonary parenchymal lesions.
Reducing Metabolic Bone Disease Burden in Intestinal Failure Children on Home Parenteral Nutrition
Authors: Tridimas Andreas , Padidela Raja , Bassett John , Wood Rachel , Lawson Maureen , Fagbemi Andrew , Morris Timothy J. 
Published: November 2023

Objective:
To determine the prevalence of secondary hyperparathyroidism in a cohort of pediatric patients receiving home parenteral nutrition.

Methods:
For a service review, a population-based cohort of 37 pediatric intestinal failure patients receiving long-term parenteral nutrition that underwent serial biochemical monitoring during a study period of approximately 4 years were examined. Following the production of an algorithm, a follow-up audit was carried out (n = 33) after approximately 6 months.

Results:
Of the 37 patients examined in the initial service review, 22 (59%) were found to have an elevated parathyroid hormone (PTH) during the period of monitoring and 5 (14%) had a persistently elevated PTH. In the follow-up audit following the implementation of an algorithm, the number with elevated PTH reduced to 6 (18%) and no patients had persistently high levels.

Conclusion:
Elevated PTH is a common biochemical finding in pediatric intestinal failure patients receiving home parenteral nutrition and its presence should alert clinicians to the need to optimize nutritional parameters such as calcium to phosphate molar ratio and vitamin D status; failure to do so may increase the future burden of metabolic bone disease in such patients. We propose that an algorithm may help in this endeavor.
A biophysically constrained brain connectivity model based on stimulation-evoked potentials
Authors: Schmid William , Danstrom Isabel A. , Echevarria Maria Crespo , Adkinson Joshua , Mattar Layth , Banks Garrett P. , Sheth Sameer A. , Watrous Andrew J. , Heilbronner Sarah R. , Bijanki Kelly R. , Alabastri Alessandro , Bartoli Eleonora 
Published: November 2023

AbstractBackgroundSingle-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies.New MethodUsing intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features.ResultsThe proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures.Comparison with existing methodsExisting methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences.ConclusionsThese results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
Attention and interoception alter perceptual and neural pain signatures
Authors: Niedernhuber Maria , Streicher Joaquim , Lenggenhager Bigna , Bekinschtein Tristan A. 
Published: November 2023

AbstractFluctuations of chronic pain levels are determined by a complex interplay of cognitive, emotional and perceptual variables. We introduce a pain tracking platform composed of wearable neurotechnology and a smartphone application to measure and predict chronic pain levels. Our method measures, dynamically, pain strength, phenomenal and neural time series collected with an online tool and low-density EEG. Here we used data from a single participant who performed an attention task at home for a period of 20 days to investigate the role of attention to different bodily systems in chronic pain. Our results show a relationship between emotions and pain strength while allocating attention to the heartbeat, the breathing, the affected or the unaffected limb. We found that pain was maximal when attending to the affected limb, and decreased when the participant focused on his breathing or his heartbeat. These results provide interesting insights regarding the role of attention to interoceptive signals in chronic pain. We found power changes in the delta, theta, alpha and beta (but not in the gamma) band between the four attention conditions. However, there was no reliable association of these changes to pain intensity ratings. Theta power was higher when attention was directed to the unaffected limb compared to the others. Further, the pain ratings, when attending to unaffected limb, were associated with alpha and theta power band changes. Overall, we demonstrate that our neurophysiology and experience tracking platform can capture how body attention allocation alters the dynamics of subjective measures and its neural correlates. This research approach is proof of concept for the development of personalized clinical assessment tools and a testbed for behavioural, subjective and biomarkers characterization.
Transcriptomics and chromatin accessibility in multiple African population samples
Authors: DeGorter Marianne K , Goddard Page C , Karakoc Emre , Kundu Soumya , Yan Stephanie M , Nachun Daniel , Abell Nathan , Aguirre Matthew , Carstensen Tommy , Chen Ziwei , Durrant Matthew , Dwaracherla Vikranth R , Feng Karen , Gloudemans Michael J , Hunter Naiomi , Moorthy Mohana P S , Pomilla Cristina , Rodrigues Kameron B , Smith Courtney J , Smith Kevin S , Ungar Rachel A , Balliu Brunilda , Fellay Jacques , Flicek Paul , McLaren Paul J , Henn Brenna , McCoy Rajiv C , Sugden Lauren , Kundaje Anshul , Sandhu Manjinder S , Gurdasani Deepti , Montgomery Stephen B 
Published: November 2023

AbstractMapping the functional human genome and impact of genetic variants is often limited to European-descendent population samples. To aid in overcoming this limitation, we measured gene expression using RNA sequencing in lymphoblastoid cell lines (LCLs) from 599 individuals from six African populations to identify novel transcripts including those not represented in the hg38 reference genome. We used whole genomes from the 1000 Genomes Project and 164 Maasai individuals to identify 8,881 expression and 6,949 splicing quantitative trait loci (eQTLs/sQTLs), and 2,611 structural variants associated with gene expression (SV-eQTLs). We further profiled chromatin accessibility using ATAC-Seq in a subset of 100 representative individuals, to identity chromatin accessibility quantitative trait loci (caQTLs) and allele-specific chromatin accessibility, and provide predictions for the functional effect of 78.9 million variants on chromatin accessibility. Using this map of eQTLs and caQTLs we fine-mapped GWAS signals for a range of complex diseases. Combined, this work expands global functional genomic data to identify novel transcripts, functional elements and variants, understand population genetic history of molecular quantitative trait loci, and further resolve the genetic basis of multiple human traits and disease.
One gecko’s pain is another gecko’s gain: is the Moorish geckoTarentola mauritanicabecoming invasive in France?
Authors: Renet Julien , Dokhelar Théo , Dubos Nicolas 
Published: November 2023

AbstractThe Moorish geckoTarentola mauritanicais currently expanding around the Mediterranean basin as a result of natural dispersal and anthropogenic spread. The species is observed at several sites in sympatry with other gecko species. To date, no impact has been observed on the native species andT. mauritanicais not considered invasive. We present an eight-year survey in southern France, where it lives in sympatry with the European leaf-toed geckoEuleptes europaea. The survey started when the Moorish gecko was rare which enabled us to observe an important increase in abundance. This increase was strongly correlated with a notable decline ofE. europaea, explaining 49% of transect-specific temporal variation in abundance. We suspect that the increase inT. mauritanicadensity is causally related to this decline and recommend intensive monitoring of the species throughout the Mediterranean Basin to determine whether or not the species should be classified as invasive.
Rapid in-EPON CLEM for everyone: Combining fast and efficient labeling of self-labeling enzyme tags with EM-resistant Janelia Fluor dyes
Authors: Franzkoch Rico , Wilkening Sabrina , Liss Viktoria , Holtmannspötter Michael , Kurre Rainer , Psathaki Olympia E. , Hensel Michael 
Published: November 2023

SummaryCorrelative light and electron microscopy (CLEM) allows to link light microscopy (LM) of living cells to ultrastructural analyses by electron microscopy (EM). Pre-embedding CLEM often suffers from inaccurate correlation between the LM and EM modalities due to chemical and physical distortions. Post-embedding CLEM enables precise registration of fluorescent structures directly on thin resin sections. However, in-resin CLEM techniques require fluorescent markers withstanding EM sample preparation. Most fluorescent proteins lose their fluorescence during EM sample preparation. Synthetic dyes present an alternative as their photostability and brightness exceed those of fluorescent proteins. Together with self-labeling enzymes (SLE) as protein tags, these fluorophores can be used to precisely label cellular structures of interest. By applying SLE labelling for post-embedding CLEM, we compared Janelia Fluor dyes and TMR to identify most suitable fluorophores. Epithelial cells expressing HaloTag fusion proteins were stained with various ligand-conjugated dyes, and fluorescence preservation was quantified after conventional room temperature sample preparation with embedding in EPON. The results obtained show that only the red dyes TMR, JF549, JFX549 and JFX554 retain their fluorescence in resin, with JFX549 and JFX554 yielding best signal intensity and signal-to-background ratio during in-resin super-resolution microscopy. Since all red dyes possess an oxygen atom within their xanthene structure, our results indicate that this might be a crucial feature making them more tolerant to sample preparation for electron microscopy. Our work reports a rapid in-resin CLEM approach that combines fast and efficient labeling of SLE tags with EM-compatible fluorophores, and serve as benchmarks for experimental planning and future engineering of fluorophores for CLEM.
A minimal sequence motif drives selective tRNA dihydrouridylation by hDUS2
Authors: Ji Jingwei , Yu Nathan J. , Kleiner Ralph E. 
Published: November 2023

ABSTRACTThe post-transcriptional reduction of uridine to dihydrouridine (D) by dihydrouridine synthase (DUS) enzymes is among the most ubiquitous transformations in RNA biology. D is found at multiple sites in tRNAs and studies in yeast have proposed that each of the four eukaryotic DUS enzymes modifies a different site, however the molecular basis for this exquisite selectivity is unknown and human DUS enzymes have remained largely uncharacterized. Here we investigate the substrate specificity of human dihydrouridine synthase 2 (hDUS2) using mechanism-based crosslinking with 5-bromouridine (5-BrUrd)-modified oligonucleotide probes andin vitrodihydrouridylation assays. We find that hDUS2 modifies U20 in the D loop of diverse tRNA substrates and identify a minimal GU motif within the tRNA tertiary fold required for directing its activity. Further, we use our mechanism-based platform to screen small molecule inhibitors of hDUS2, a potential anti-cancer target. Our work elucidates the principles of substrate modification by a conserved DUS and provides a general platform to studying RNA modifying enzymes with sequence-defined activity-based probes.
MiRGraph: A hybrid deep learning approach to identify microRNA-target interactions by integrating heterogeneous regulatory network and genomic sequences
Authors: Liu Pei , Liu Ying , Luo Jiawei , Li Yue 
Published: November 2023

AbstractMicroRNAs (miRNAs) mediates gene expression regulation by targeting specific messenger RNAs (mRNAs) in the cytoplasm. They can function as both tumor suppressors and oncogenes depending on the specific miRNA and its target genes. Detecting miRNA-target interactions (MTIs) is critical for unraveling the complex mechanisms of gene regulation and promising towards RNA therapy for cancer. There is currently a lack of MTIs prediction methods that simultaneously perform feature learning from heterogeneous gene regulatory network (GRN) and genomic sequences. To improve the prediction performance of MTIs, we present a novel transformer-based multiview feature learning method – MiRGraph, which consists of two main modules for learning the sequence-based and GRN-based feature embedding. For the former, we utilize the mature miRNA sequences and the complete 3’UTR sequence of the target mRNAs to encode sequence features using a hybrid transformer and convolutional neural network (CNN) (TransCNN) architecture. For the latter, we utilize a heterogeneous graph transformer (HGT) module to extract the relational and structural information from the GRN consisting of miRNA-miRNA, gene-gene and miRNA-target interactions. The TransCNN and HGT modules can be learned end-to-end to predict experimentally validated MTIs from MiRTarBase. MiRGraph outperforms existing methods in not only recapitulating the true MTIs but also in predicting strength of the MTIs based on thein-vitromeasurements of miRNA transfections. In a case study on breast cancer, we identified plausible target genes of an oncomir.
FICTURE:Scalable segmentation-free analysis of submicron resolution spatial transcriptomics
Authors: Si Yichen , Lee ChangHee , Hwang Yongha , Yun Jeong H. , Cheng Weiqiu , Cho Chun-Seok , Quiros Miguel , Nusrat Asma , Zhang Weizhou , Jun Goo , Zöllner Sebastian , Lee Jun Hee , Kang Hyun Min 
Published: November 2023

AbstractSpatial transcriptomics (ST) technologies have advanced to enable transcriptome-wide gene expression analysis at submicron resolution over large areas. Analysis of high-resolution ST data relies heavily on image-based cell segmentation or gridding, which often fails in complex tissues due to diversity and irregularity of cell size and shape. Existing segmentation-free analysis methods scale only to small regions and a small number of genes, limiting their utility in high-throughput studies. Here we present FICTURE, a segmentation-free spatial factorization method that can handle transcriptome-wide data labeled with billions of submicron resolution spatial coordinates. FICTURE is orders of magnitude more efficient than existing methods and it is compatible with both sequencing- and imaging-based ST data. FICTURE reveals the microscopic ST architecture for challenging tissues, such as vascular, fibrotic, muscular, and lipid-laden areas in real data where previous methods failed. FICTURE’s cross-platform generality, scalability, and precision make it a powerful tool for exploring high-resolution ST.
Expression of mitochondrial oxidative stress response genes in muscle is associated with mitochondrial respiration, physical performance, and muscle mass in the Study of Muscle, Mobility and Aging (SOMMA)
Authors: Tranah Gregory J , Barnes Haley N , Cawthon Peggy M , Coen Paul M , Esser Karyn A , Hepple Russell T , Huo Zhiguang , Kramer Philip A , Toledo Frederico G. S. , Evans Daniel S , Cummings Steven R 
Published: November 2023

AbstractGene expression in skeletal muscle of older individuals may reflect compensatory adaptations in response to oxidative damage that preserve tissue integrity and maintain function. Identifying associations between oxidative stress response gene expression patterns and mitochondrial function, physical performance, and muscle mass in older individuals would further our knowledge of mechanisms related to managing molecular damage that may be targeted to preserve physical resilience. To characterize expression patterns of genes responsible for the oxidative stress response, RNA was extracted and sequenced from skeletal muscle biopsies collected from 575 participants (≥70 years old) from the Study of Muscle, Mobility and Aging. Expression levels of twenty-one protein coding RNAs related to the oxidative stress response were analyzed in relation to six phenotypic measures, including: maximal mitochondrial respiration from muscle biopsies (Max OXPHOS), physical performance (VO2peak, 400m walking speed, and leg strength), and muscle size (thigh muscle volume and whole-body D3Cr muscle mass). The mRNA level of the oxidative stress response genes most consistently associated across outcomes are preferentially expressed within the mitochondria. Higher expression of mRNAs that encode generally mitochondria located proteinsSOD2,TRX2,PRX3,PRX5, andGRX2were associated with higher levels of mitochondrial respiration and VO2peak. In addition, greaterSOD2, PRX3,andGRX2expression was associated with higher physical performance and muscle size. Identifying specific mechanisms associated with high functioning across multiple performance and physical domains may lead to targeted antioxidant interventions with greater impacts on mobility and independence.
Machine Learning Model to Predict Allocation of Patients with Chronic Back Pain for Integrated Practice Units in a System of Value-based Health Care
Authors: Barbosa Vitor Pereira , Said dos Reis João Lucas Maehara , von Zuben de Valega Negrão Cyro , Barboza Victor Rossetto , Simoes Marcondes Keli Cristina Betto , Rezende Elton Pereira , Neto Pereira Cerize Natália , de Paula Guirado Vinicius Monteiro 
Published: November 2023

AbstractChronic pain incurs substantial global healthcare costs, requiring long-term specialized care. However, the variability in treatment approaches hampers the feasibility of value-based healthcare. To advance management and prevention efforts, data science tools like supervised and unsupervised machine learning algorithms offer promising solutions. This study employed data from six questionnaires to evaluate pain conditions in patients. Correlation techniques were applied to determine the questions most strongly correlated with low back pain, back pain, and leg pain. Five machine learning algorithms predicted the presence or absence of pain in the low back region. Seven variables were identified as input for the prediction models, with the XBoost Classifier demonstrating the highest accuracy, precision, recall, and F1-Score (0.8 accuracy, precision, recall; 0.78 F1-Score). By incorporating the machine learning model, it predicts the allocation of chronic back pain patients to integrated practice in a value-based healthcare system. Finally, our findings show that data science methods, such as machine learning, improve chronic pain management, expedite surveys, and improve value-based healthcare through efficient allocation.Graphical abstractHighlightsCorrelation analysis identified pain-related questions (back, leg, chronic low back).7 characteristics used by ML algorithms to forecast chronic low back pain occurrence.XBoost algorithm and neural network achieved best performance (Precision, Recall ∼0.8).Outcomes aid patient allocation, screening, and reducing costs in value-based healthcare.Streamlining surveys boosts response rates and enables larger datasets for improved modeling.