bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experience of Saudi Dental Practitioners with Intraoral Scanners
Authors: Al-Ibrahim Ibrahim K. , Alotaibi Anfal H. , Alshammari Alanoud S. , Madfa Ahmed A. 
Published: July 2022

AbstractBackgroundThe objective of this study was to investigate the experience of Saudi dental practitioners with intraoral scanners, investigate the current knowledge and improve the practice accordingly.MethodsAt random, electronic surveys were distributed to Saudi dental practitioners. The study received 400 questionnaires, with 310 judged valid for the study. The questionnaire was divided into the following sections: (i) Practitioners’ demographic information such as gender, practice level, and practice experience. (ii) Experience and benefits of intraoral scanners. (iii) Require skills and training of IOS. (iv) Knowledge of IOS usage. Descriptive statistics such as numbers and percentages were used to analyze the collected data. The Chi-square and Fisher’s Exact tests were used to assess the results.ResultsThere were 161 women (51.8%) and 149 men among the participants (47.9%). General practitioners (198, or 63.7%) had the most subjects, followed by specialists (80, or 25.7%) and consultants (32, or 10.3%). In terms of IOS use in dental practice, most participants (70.6%) do not use it, while less than one-third do. The majority of participants (52.3%) intend to purchase IOS with significant variations based on gender, experience, and level of practice (p<0.05). Compared to traditional, most participants believe that IOS will eventually replace it, improve quality, and be more aesthetically pleasing. Most dentists believe that using IOS requires special skills and training. More than half of dentists believe IOSs have the same level of accuracy as conventional in producing three units FPDs, implant prosthesis, and complete denture.ConclusionIt can be concluded that dentists have a high level of satisfaction and a favorable attitude toward using IOS technology in clinical dentistry practice.
Obtaining polygenic transcriptome risk scores (PTRS) directly from GWAS summary statistics
Authors: Liang Yanyu 
Published: July 2022

AbstractPolygenic Transcriptome Risk Scores (PTRS) are variations of Polygenic Risk Scores (PRS) that use genetically predicted transcriptome as features for prediction instead of directly using genetic variants. We have shown that when PTRS is combined with PRS, they can yield improved prediction performance and portability across populations (Liang et al., 2022). Given the difficulty of training PTRS using large scale individual-level data (due to both computational burden and the lack of data access), we developed a user friendly software that infers PTRS using GWAS summary results and reference LD. We tested three summary statistics-based PTRS approaches: i) Clumping and thresholding (clump-PTRS), keeping trait associated genes while removing highly correlated ones; ii) Summary statistics-based elastic net PTRS (S-EN-PTRS), an extension of lassosum (Mak et al., 2017) to predicted transcriptome; iii) Naive-PTRS, the sum of predicted expressions of significantly associated genes weighted by PrediXcan-estimated effect sizes (Gamazon et al., 2015). Despite reports that individual-level trained elastic net PTRS outperformed clump-PTRS in (Liang et al., 2022), for most of the 11 traits used in the comparison, clump-PTRS outperformed S-EN-PTRS, which outperformed naive-PTRS.
Valence-dependent self-agency is disturbed in depression and anxiety
Authors: Mehta Marishka M , Na Soojung , Gu Xiaosi , Murrough James W , Morris Laurel S 
Published: July 2022

AbstractBackgroundThe sense of agency, or the belief in action causality, is an elusive construct that impacts day-to-day experience and decision-making. Despite its relevance in a range of neuropsychiatric disorders, it is widely under-studied and remains difficult to measure objectively in patient populations. We developed and tested a novel cognitive measure of valence-modulated agency perception in an in-person and online cohort.MethodsThe in-person cohort consisted of 52 healthy control subjects and 20 subjects with depression and anxiety disorders (DA), including major depressive disorder and generalized anxiety disorder. The online sample consisted of 254 participants. The task consisted of an effort task for monetary rewards with computerized visual feedback interference and trial-by-trial ratings of self versus other agency.ResultsAll subjects across both cohorts demonstrated higher self-agency after receiving positive-win feedback, compared to negative-loss feedback when the level of computer inference was kept constant. Patients with DA showed reduced positive valence-dependent agency compared to healthy controls. Finally, in both cohorts, lower self-agency following negative-loss feedback was associated with worse anhedonia symptoms.ConclusionTogether this work suggests how positive and negative environmental information impacts the sense of self-agency in healthy subjects, and how it is perturbed in patients with depression and anxiety.
Improved Xerostomia Prediction in Head and Neck Cancer Patients with Dixon Magnetic Resonance Imaging of Glandular Adiposity: Validation of Semi-Quantitative Parotid T1 Signal Intensity Metrics for Biomarker Pre-Qualification
Authors:   Joint Head and Neck Radiotherapy-MRI Development Cooperative,   the MD Anderson Head and Neck Cancer Symptom Working Group, Sanders Keith L. , Mulder Sam , Wahid Kareem A. , McDonald Brigid A. , Ahmed Sara , Salzillo Travis C. , He Renjie , Naser Mohamed A. , Dede Cem , Salama Vivian , Way Ashley , Sharafi Christina Setareh , Mohamed Abdallah S.R. , Rigert Jillian , Chambers Mark , Moreno Amy C. , Hutcheson Katherine A. , Lai Stephen Y. , Fuller Clifton D. , van Dijk Lisanne V. 
Published: July 2022

AbstractPurposeParotid whole-gland magnetic resonance (MR) T1 intensity, thresholded at the 90th percentile (T1 P90), has been previously reported to be a candidate MR imaging biomarker (MR-IBM) for improved prediction of xerostomia development after radiotherapy. Although P90 was previously derived from the parotid glands of T1-weighted MRI, in this study, we aim to validate P90 in an external cohort using fat only images reconstructed from a T1 Dixon MRI sequence, as well as determining alternative T1 intensity thresholds for potential qualification as predictive FDA BEST biomarkers of xerostomia development 6 months after radiotherapy (Xero6m).MethodsMR-IBMs derived from T1 Dixon intensity-normalized scans from 76 head and neck cancer (HNC) patients were extracted from pre-treatment MR images. Scans were normalized to fat tissue, and imaging characteristics were quantified. A reference model and MR-IBM models were created using multivariable logistic regression to predict Xero6m. External validation was performed using the model coefficients described in a previous study. The area under the curve (AUC) of the resulting models were compared. Stepwise forward feature selection was performed to discover additional MR-IBMs for improved predictions of xerostomia.ResultsThe external validation of a previous model coefficients against our cohort showed decreased performance of the P90 MR-IBM model (AUC of 0.73 (CI 0.61-0.85)). The reference model exhibited improved performance when P90 was incorporated (AUC of 0.78 (CI 0.67-0.89)). Feature selection demonstrated the P10 MR-IBM provided performance improvements (AUC of 0.79 (CI: 0.69-0.90)).ConclusionOur findings validated P90 as predictive biomarker for radiation-induced xerostomia and showed MR-IBMs derived from Dixon sequences can improve Xero6m prediction when compared to the reference model. Formal biomarker qualification should be considered for T1 sequences/relaxometry via formalized approaches.
Assessment of concordance between related systematic reviews and between related guideline recommendations: protocol for a methodological survey
Authors: Agarwal Arnav , Albarqouni Loai , Badran Nour , Brax Nina , Gandhi Pooja , Pereira Tiago , Roberts Abigail , Zein Ola El , Akl Elie 
Published: July 2022

AbstractIndependent systematic reviewers may arrive at different conclusions when analyzing evidence addressing the same clinical questions. Similarly, independent expert panels may arrive at different recommendations addressing the same clinical topics. When faced with a multiplicity of reviews or guidelines on a given topic, users are likely to benefit from a structured approach to evaluate concordance, and to explain discordant findings and recommendations. This protocol proposes a methodological survey to evaluate the prevalence of concordance between reviews addressing similar clinical questions, and between clinical practice guidelines addressing similar topics; and to identify methodological frameworks for the evaluation of concordance between related reviews and between related guidelines.
Small gene networks can delineate immune cell states and characterize immunotherapy response in melanoma
Authors: Egan Donagh , Kreileder Martina , Nabhan Myriam , Iglesias-Martinez Luis F. , Dovedi Simon , Valge-Archer Viia , Grover Amit , Wilkinson Robert , Slidel Tim , Bendtsen Claus , Barrett Ian , Brennan Donal , Kolch Walter , Zhernovkov Vadim 
Published: July 2022

ABSTRACTBackgroundSingle-cell sequencing studies have elucidated some of the underlying mechanisms responsible for immune checkpoint inhibitor (ICI) response, but are difficult to implement as a general strategy or in a clinical diagnostic setting. In contrast, bulk RNAseq is now routine for both research and clinical applications. Therefore, our analysis extracts small transcription factor-directed co-expression networks (regulons) from single-cell RNA-seq data and uses them to deconvolute immune functional states from bulk RNA-seq data to characterize patient responses.MethodsRegulons were inferred in pre-treatment CD45+ cells from metastatic melanoma samples (n=19) treated with first-line ICI therapy (discovery dataset). A logistic regression-based classifier identified immune cell states associated with response, which were characterized according to differentially active, cell-state specific regulons. The complexity of these regulons was reduced and scored in bulk RNAseq melanoma samples from four independent studies (n=209, validation dataset). Patients were clustered according to their regulon scores, and the associations between cluster assignment, response, and survival were determined. Intercellular communication analysis of cell states was performed, and the resulting effector genes were analyzed by trajectory inference.ResultsRegulons preserved the information of gene expression data and accurately delineated immune cell phenotypes, despite reducing dimensionality by > 100-fold. Four cell states, termed exhausted T cells, monocyte lineage cells, memory T cells, and B cells, were associated with therapeutic responses in the discovery dataset. The cell states were characterized by seven differentially active and specific regulons that showed low specificity in non-immune cells. Four clusters with significantly different response outcomes (P <0.001) were identified in the bulk RNAseq validation cohort. An intercellular link between exhausted T cells and monocyte lineage cells was established, whereby their cell numbers were correlated, and exhausted T cells predicted prognosis as a function of monocyte lineage cell number. Analysis of ligand – receptor expression suggested that monocyte lineage cells drive exhausted T cells into terminal exhaustion through programs that regulate antigen presentation, chronic inflammation, and negative co-stimulation.ConclusionsRegulon-based characterization of cell states provides robust and functionally informative markers that can deconvolve bulk RNA-seq data to identify ICI responders.
Perturbations of a causal synaptic molecular network in autism and schizophrenia revealed with multiplexed imaging
Authors: Falkovich Reuven , Danielson Eric W. , Perez de-Arce Karen , Wamhoff Eike C. , Cottrell Jeffrey , Sheng Morgan , Bathe Mark 
Published: July 2022

ABSTRACTThe complex functions of neuronal synapses in the central nervous system depend on their tightly interacting, compartmentalized molecular network of hundreds of proteins spanning the pre- and post-synaptic sites. This biochemical system is implicated in the pathogenesis of autism spectrum disorders and schizophrenia, with identified common synaptopathologies and numerous risk genes associated with synaptic function. However, it remains unclear how the synaptic molecular network is altered in these disorders, and whether effects are common to distinct genetic perturbations. Here, we applied PRISM, a quantitative single-synapse multiplexed imaging technique, to systematically probe the effects of RNAi knockdown of 16 autism- and schizophrenia-associated genes on the simultaneous distribution of 10 synaptic proteins. This enabled the identification of novel phenotypes in synapse compositions and distributions. We applied Bayesian network inference to construct and validate a predictive model of causal hierarchical dependencies among eight proteins of the excitatory synapse. The resulting conditional dependence relationships could only be accessed via measurement which is both single-synapse and multiprotein, unique to PRISM. Finally, we show that central features of the network are similarly affected across distinct gene knockdowns. These results offer insight into the convergent molecular etiology of these debilitating, hereditary and highly polygenic disorders, as well as offering a novel, general framework for probing subcellular molecular networks.
Nonenzymatic template-directed replication using 2′-3′ cyclic nucleotides under wet-dry cycles
Authors: Dagar Shikha , Sarkar Susovan , Rajamani Sudha 
Published: July 2022

Abstract‘RNA World Hypothesis’ is centred around the idea of a period in the early history of life’s origin, wherein nonenzymatic oligomerization and replication of RNA resulted in functional ribozymes. Previous studies in this endeavour have demonstrated template-directed replication using chemically modified nucleotides and primers. Nonetheless, similar studies that used non-activated nucleotides led to the formation of RNA only with abasic sites. In this study, we report template-directed replication with prebiotically relevant cyclic nucleotides, under dehydration-rehydration (DH-RH) cycles occurring at high temperature (90°C) and alkaline conditions (pH 8). 2′–3′ cyclic nucleoside monophosphates (cNMP) resulted in primer extension, while 3′–5′ cNMP failed to do so. Intact extension of up to two nucleotide additions was observed with both canonical hydroxy-terminated (OH-primer) and activated amino-terminated (NH2-primer) primers. We demonstrate primer extension reactions using both purine and pyrimidine 2′–3′ cNMPs, with higher product yield observed during cAMP additions. Further, the presence of lipid was observed to significantly enhance the extended product in cCMP reactions. In all, our study provides a proof-of-concept for nonenzymatic replication of RNA, using intrinsically activated prebiotically relevant cyclic nucleotides as monomers.
Correspondence between the layered structure of deep language models and temporal structure of natural language processing in the human brain
Authors: Goldstein Ariel , Ham Eric , Nastase Samuel A. , Zada Zaid , Grinstein-Dabus Avigail , Aubrey Bobbi , Schain Mariano , Gazula Harshvardhan , Feder Amir , Doyle Werner , Devore Sasha , Dugan Patricia , Friedman Daniel , Brenner Michael , Hassidim Avinatan , Devinsky Orrin , Flinker Adeen , Levy Omer , Hasson Uri 
Published: July 2022

AbstractDeep language models (DLMs) provide a novel computational paradigm for how the brain processes natural language. Unlike symbolic, rule-based models described in psycholinguistics, DLMs encode words and their context as continuous numerical vectors. These “embeddings” are constructed by a sequence of computations organized in “layers” to ultimately capture surprisingly sophisticated representations of linguistic structures. How does this layered hierarchy map onto the human brain during natural language comprehension? In this study, we used electrocorticography (ECoG) to record neural activity in language areas along the superior temporal gyrus and inferior frontal gyrus while human participants listened to a 30-minute spoken narrative. We supplied this same narrative to a high-performing DLM (GPT2-XL) and extracted the contextual embeddings for each word in the story across all 48 layers of the model. We next trained a set of linear encoding models to predict the temporally-evolving neural activity from the embeddings at each layer. We found a striking correspondence between the layer-by-layer sequence of embeddings from GPT2-XL and the temporal sequence of neural activity in language areas. In addition, we found evidence for the gradual accumulation of recurrent information along the linguistic processing hierarchy. However, we also noticed additional neural processes in the brain, but not in DLMs, during the processing of surprising (unpredictable) words. These findings point to a connection between human language processing and DLMs where the layer-by-layer accumulation of contextual information in DLM embeddings matches the temporal dynamics of neural activity in high-order language areas.
Evidence for absence of links between striatal dopamine synthesis capacity and working memory capacity, spontaneous eye-blink rate, and trait impulsivity
Authors: van den Bosch Ruben , Hezemans Frank H. , Määttä Jessica I. , Hofmans Lieke , Papadopetraki Danae , Verkes Robbert-Jan , Marquand Andre F. , Booij Jan , Cools Roshan 
Published: July 2022

AbstractIndividual differences in striatal dopamine synthesis capacity have been associated with working memory capacity, trait impulsivity and spontaneous eye-blink rate (sEBR), as measured with readily available and easily administered, ‘off-the-shelf’ tests. Such findings have raised the suggestion that individual variation in dopamine synthesis capacity, estimated with expensive and invasive brain positron emission tomography (PET) scans, can be approximated with simple, more pragmatic tests. However, direct evidence for the relationship between these simple trait measures and striatal dopamine synthesis capacity has been limited and inconclusive. We measured striatal dopamine synthesis capacity using [18F]-FDOPA PET in a large sample of healthy volunteers (N=94) and assessed the correlation with simple, short tests of working memory capacity, trait impulsivity, and sEBR. We additionally explored the relationship with an index of subjective reward sensitivity. None of these trait measures correlated significantly with striatal dopamine synthesis capacity, nor did they have out-of-sample predictive power. Bayes Factor analyses indicated the evidence was in favour of absence of correlations for all but subjective reward sensitivity. These results warrant caution for using these off-the-shelf trait measures as proxies of striatal dopamine synthesis capacity.
Interrogating the effect of enzyme kinetics on metabolism using differentiable constraint-based models
Authors: Wilken St. Elmo , Besançon Mathieu , Kratochvíl Miroslav , Foko Kuate Chilperic Armel , Trefois Christophe , Gu Wei , Ebenhöh Oliver 
Published: July 2022

1AbstractMetabolic models are typically characterized by a large number of parameters. Traditionally, metabolic control analysis is applied to differential equation-based models to investigate the sensitivity of predictions to parameters. A corresponding theory for constraint-based models is lacking, due to their formulation as optimization problems. Here, we show that optimal solutions of optimization problems can be efficiently differentiated using constrained optimization duality and implicit differentiation. We use this to calculate the sensitivities of predicted reaction fluxes and enzyme concentrations to turnover numbers in an enzyme-constrained metabolic model of Escherichia coli. The sensitivities quantitatively identify rate limiting enzymes and are mathematically precise, unlike current finite difference based approaches used for sensitivity analysis. Further, efficient differentiation of constraint-based models unlocks the ability to use gradient information for parameter estimation. We demonstrate this by improving, genome-wide, the state-of-the-art turnover number estimates for E. coli. Finally, we show that this technique can be generalized to arbitrarily complex models. By differentiating the optimal solution of a model incorporating both thermodynamic and kinetic rate equations, the effect of metabolite concentrations on biomass growth can be elucidated. We benchmark these metabolite sensitivities against a large experimental gene knockdown study, and find good alignment between the predicted sensitivities and in vivo metabolome changes. In sum, we demonstrate several applications of differentiating optimal solutions of constraint-based metabolic models, and show how it connects to classic metabolic control analysis.
Autocrine Sfrp1 inhibits lung fibroblast invasion during transition to injury induced myofibroblasts
Authors: Mayr Christoph H. , Sengupta Arunima , Ansari Meshal , Pestoni Jeanine C. , Ogar Paulina , Angelidis Ilias , Liontos Andreas , Rodriguez-Castillo Alberto , Lang Niklas J. , Strunz Maximilian , Asgharpour Sara , Porras-Gonzalez Diana , Gerckens Michael , Oehrle Bettina , Viteri-Alvarez Valeria , Fernandez Isis E. , Tallquist Michelle , Irmler Martin , Beckers Johannes , Eickelberg Oliver , Stoleriu Gabriel Mircea , Behr Jürgen , Kneidinger Nikolaus , Yildirim Ali Önder , Ahlbrecht Katrin , Morty Rory E. , Samakovlis Christos , Theis Fabian J. , Burgstaller Gerald , Schiller Herbert B. 
Published: July 2022

AbstractFibroblast to myofibroblast conversion is a major driver of tissue remodeling in organ fibrosis. Several distinct lineages of fibroblasts support homeostatic tissue niche functions, yet, specific activation states and phenotypic trajectories of fibroblasts during injury and repair have remained unclear. Here, we combined spatial transcriptomics, longitudinal single-cell RNA-seq and genetic lineage tracing to study fibroblast fates during mouse lung regeneration. We discovered a transitional fibroblast state characterized by high Sfrp1 expression, derived from both Tcf21-Cre lineage positive and negative cells. Sfrp1+ cells appeared early after injury in peribronchiolar, adventitial and alveolar locations and preceded the emergence of myofibroblasts. We identified lineage specific paracrine signals and inferred converging transcriptional trajectories towards Sfrp1+ transitional fibroblasts and Cthrc1+ myofibroblasts. Tgfβ1 downregulated Sfrp1 in non-invasive transitional cells and induced their switch to an invasive Cthrc1+ myofibroblast identity. Finally, using loss of function studies we showed that autocrine Sfrp1 directly inhibits fibroblast invasion by regulating the RhoA pathway. In summary, our study reveals the convergence of spatially and transcriptionally distinct fibroblast lineages into transcriptionally uniform myofibroblasts and identifies Sfrp1 as an autocrine inhibitor of fibroblast invasion during early stages of fibrogenesis.