bluuebunny/crossref_metadata_2025_split huggingface dataset:
Positive scores on the 4AT delirium assessment tool at hospital admission are linked to mortality, length of stay and home time: two-centre study of 82,770 emergency admissions
Authors: Anand Atul , Cheng Michael , Ibitoye Temi , Maclullich Alasdair M J , Vardy Emma R L C 
Published: February 2022

AbstractBackgroundStudies investigating outcomes of delirium using large-scale routine data are rare. We performed a two-centre study using the 4 ‘A’s Test (4AT) delirium detection tool to analyse relationships between delirium and 30-day mortality, length of stay and home time (days at home in the year following admission).MethodsThe 4AT was performed as part of usual care. Data from emergency admissions in patients ≥65 years in Lothian, UK (n = 43,946) and Salford, UK (n = 38,824) over a period of $\sim$3 years were analysed using logistic regression models adjusted for age and sex.Results4AT completion rates were 77% in Lothian and 49% in Salford. 4AT scores indicating delirium (≥4/12) were present in 18% of patients in Lothian, and 25% of patients in Salford. Thirty-day mortality with 4AT ≥4 was 5.5-fold greater than the 4AT 0/12 group in Lothian (adjusted odds ratio (aOR) 5.53, 95% confidence interval [CI] 4.99–6.13) and 3.4-fold greater in Salford (aOR 3.39, 95% CI 2.98–3.87). Length of stay was more than double in patients with 4AT scores of 1–3/12 (indicating cognitive impairment) or ≥ 4/12 compared with 4AT 0/12. Median home time at 1 year was reduced by 112 days (Lothian) and 61 days (Salford) in the 4AT ≥4 group (P &lt; 0.001).ConclusionsScores on the 4AT used at scale in practice are strongly linked with 30-day mortality, length of hospital stay and home time. The findings highlight the need for better understanding of why delirium is linked with poor outcomes and also the need to improve delirium detection and treatment.
MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification
Authors: Moon Sehwan , Lee Hyunju 
Published: February 2022

Abstract

Motivation
Accurate diagnostic classification and biological interpretation are important in biology and medicine, which are data-rich sciences. Thus, integration of different data types is necessary for the high predictive accuracy of clinical phenotypes, and more comprehensive analyses for predicting the prognosis of complex diseases are required.

Results
Here, we propose a novel multi-task attention learning algorithm for multi-omics data, termed MOMA, which captures important biological processes for high diagnostic performance and interpretability. MOMA vectorizes features and modules using a geometric approach and focuses on important modules in multi-omics data via an attention mechanism. Experiments using public data on Alzheimer’s disease and cancer with various classification tasks demonstrated the superior performance of this approach. The utility of MOMA was also verified using a comparison experiment with an attention mechanism that was turned on or off and biological analysis.

Availability and implementation
The source codes are available at https://github.com/dmcb-gist/MOMA.

Supplementary information
Supplementary materials are available at Bioinformatics online.
Optimal transport improves cell–cell similarity inference in single-cell omics data
Authors: Huizing Geert-Jan , Peyré Gabriel , Cantini Laura 
Published: February 2022

Abstract

Motivation
High-throughput single-cell molecular profiling is revolutionizing biology and medicine by unveiling the diversity of cell types and states contributing to development and disease. The identification and characterization of cellular heterogeneity are typically achieved through unsupervised clustering, which crucially relies on a similarity metric.

Results
We here propose the use of Optimal Transport (OT) as a cell–cell similarity metric for single-cell omics data. OT defines distances to compare high-dimensional data represented as probability distributions. To speed up computations and cope with the high dimensionality of single-cell data, we consider the entropic regularization of the classical OT distance. We then extensively benchmark OT against state-of-the-art metrics over 13 independent datasets, including simulated, scRNA-seq, scATAC-seq and single-cell DNA methylation data. First, we test the ability of the metrics to detect the similarity between cells belonging to the same groups (e.g. cell types, cell lines of origin). Then, we apply unsupervised clustering and test the quality of the resulting clusters. OT is found to improve cell–cell similarity inference and cell clustering in all simulated and real scRNA-seq data, as well as in scATAC-seq and single-cell DNA methylation data.

Availability and implementation
All our analyses are reproducible through the OT-scOmics Jupyter notebook available at https://github.com/ComputationalSystemsBiology/OT-scOmics.

Supplementary information
Supplementary data are available at Bioinformatics online.
Effectidor: an automated machine-learning-based web server for the prediction of type-III secretion system effectors
Authors: Wagner Naama , Avram Oren , Gold-Binshtok Dafna , Zerah Ben , Teper Doron , Pupko Tal 
Published: February 2022

Abstract

Motivation
Type-III secretion systems are utilized by many Gram-negative bacteria to inject type-3 effectors (T3Es) to eukaryotic cells. These effectors manipulate host processes for the benefit of the bacteria and thus promote disease. They can also function as host-specificity determinants through their recognition as avirulence proteins that elicit immune response. Identifying the full effector repertoire within a set of bacterial genomes is of great importance to develop appropriate treatments against the associated pathogens.

Results
We present Effectidor, a user-friendly web server that harnesses several machine-learning techniques to predict T3Es within bacterial genomes. We compared the performance of Effectidor to other available tools for the same task on three pathogenic bacteria. Effectidor outperformed these tools in terms of classification accuracy (area under the precision–recall curve above 0.98 in all cases).

Availability and implementation
Effectidor is available at: https://effectidor.tau.ac.il, and the source code is available at: https://github.com/naamawagner/Effectidor.

Supplementary information
Supplementary data are available at Bioinformatics online.
Reconstructing viral haplotypes using long reads
Authors: Cai Dehan , Sun Yanni 
Published: February 2022

AbstractMotivationMost RNA viruses lack strict proofreading during replication. Coupled with a high replication rate, some RNA viruses can form a virus population containing a group of genetically related but different haplotypes. Characterizing the haplotype composition in a virus population is thus important to understand viruses’ evolution. Many attempts have been made to reconstruct viral haplotypes using next-generation sequencing (NGS) reads. However, the short length of NGS reads cannot cover distant single-nucleotide variants, making it difficult to reconstruct complete or near-complete haplotypes. Given the fast developments of third-generation sequencing technologies, a new opportunity has arisen for reconstructing full-length haplotypes with long reads.ResultsIn this work, we developed a new tool, RVHaplo to reconstruct haplotypes for known viruses from long reads. We tested it rigorously on both simulated and real viral sequencing data and compared it against other popular haplotype reconstruction tools. The results demonstrated that RVHaplo outperforms the state-of-the-art tools for viral haplotype reconstruction from long reads. Especially, RVHaplo can reconstruct the rare (1% abundance) haplotypes that other tools usually missed.Availability and implementationThe source code and the documentation of RVHaplo are available at https://github.com/dhcai21/RVHaplo.Supplementary informationSupplementary data are available at Bioinformatics online.
HIV-1 drug resistance profiling using amino acid sequence space cartography
Authors: Pikalyova Karina , Orlov Alexey , Lin Arkadii , Tarasova Olga , Marcou MarcouGilles , Horvath Dragos , Poroikov Vladimir , Varnek Alexandre 
Published: February 2022

Abstract

Motivation
Human immunodeficiency virus (HIV) drug resistance is a global healthcare issue. The emergence of drug resistance influenced the efficacy of treatment regimens, thus stressing the importance of treatment adaptation. Computational methods predicting the drug resistance profile from genomic data of HIV isolates are advantageous for monitoring drug resistance in patients. However, existing computational methods for drug resistance prediction are either not suitable for emerging HIV strains with complex mutational patterns or lack interpretability, which is of paramount importance in clinical practice. The approach reported here overcomes these limitations and combines high accuracy of predictions and interpretability of the models.

Results
In this work, a new methodology based on generative topographic mapping (GTM) for biological sequence space representation and quantitative genotype–phenotype relationships prediction purposes was introduced. The GTM-based resistance landscapes allowed us to predict the resistance of HIV strains based on sequencing and drug resistance data for three viral proteins [integrase (IN), protease (PR) and reverse transcriptase (RT)] from Stanford HIV drug resistance database. The average balanced accuracy for PR inhibitors was 0.89 ± 0.01, for IN inhibitors 0.85 ± 0.01, for non-nucleoside RT inhibitors 0.73 ± 0.01 and for nucleoside RT inhibitors 0.84 ± 0.01. We have demonstrated in several case studies that GTM-based resistance landscapes are useful for visualization and analysis of sequence space as well as for treatment optimization purposes. Here, GTMs were applied for the in-depth analysis of the relationships between mutation pattern and drug resistance using mutation landscapes. This allowed us to predict retrospectively the importance of the presence of particular mutations (e.g. V32I, L10F and L33F in HIV PR) for the resistance development. This study highlights some perspectives of GTM applications in clinical informatics and particularly in the field of sequence space exploration.

Availability and implementation
https://github.com/karinapikalyova/ISIDASeq.

Supplementary information
Supplementary data are available at Bioinformatics online.
Aberrant motor contagion of emotions in psychopathy and high-functioning autism
Authors: Sun Lihua , Lukkarinen Lasse , Noppari Tuomo , Nazari-Farsani Sanaz , Putkinen Vesa , Seppälä Kerttu , Hudson Matthew , Tani Pekka , Lindberg Nina , Karlsson Henry K , Hirvonen Jussi , Salomaa Marja , Venetjoki Niina , Lauerma Hannu , Tiihonen Jari , Nummenmaa Lauri 
Published: February 2022

Abstract
Psychopathy and autism are both associated with aberrant social skills and empathy, yet only psychopaths are markedly antisocial and violent. Here, we compared the functional neural alterations underlying these two groups that both have aberrant empathetic abilities but distinct behavioral phenotypes. We studied 19 incarcerated male offenders with high psychopathic traits, 20 males with high-functioning autism, and 19 age-matched healthy controls. All groups underwent functional magnetic resonance imaging while they viewed dynamic happy, angry, and disgusted faces or listened to laughter and crying sounds. Psychopathy was associated with reduced somatomotor responses to almost all expressions, while participants with autism demonstrated less marked and emotion-specific alterations in the somatomotor area. These data suggest that psychopathy and autism involve both common and distinct functional alterations in the brain networks involved in the socioemotional processing. The alterations are more profound in psychopathy, possibly reflecting the more severely disturbed socioemotional brain networks in this population.
Distinct cerebral coherence in task-based fMRI hyperscanning: cooperation versus competition
Authors: Wang Le-Si , Cheng Jen-Tang , Hsu I-Jeng , Liou Shyhnan , Kung Chun-Chia , Chen Der-Yow , Weng Ming-Hung 
Published: February 2022

Abstract
This study features an functional magnetic resonance imaging (fMRI) hyperscanning experiment from 2 sites, 305 km apart. The experiment contains 2 conditions: the dyad collaborated to win and then split the reward in the cooperation condition, whereas the winner took all the reward in the competition condition, thereby resulting in dynamic strategic interactions. To calculate the cerebral coherence in such jittered event-related fMRI tasks, we first iteratively estimated the feedback-related blood oxygenation level-dependent responses of each trial, using 8 finite impulse response functions (16 s) and then concatenated the beta volume series. With the right temporal–parietal junction (rTPJ) as the seed, the interpersonal connected brain areas were separately identified: the right superior temporal gyrus (rSTG) (cooperation) and the left precuneus (lPrecuneus) (competition), both peaking at the designated frequency bin (1/16 s = 0.0625 Hz), but not in permuted pairs. In addition, the extended coherence analyses on shorter and longer concatenated volumes verified that only in the optimal trial frequency did the rTPJ–rSTG and rTPJ–lPrecuneus couplings peak. In sum, our approach both showcases a flexible analysis method that widens the applicability of interpersonal coherence in the rapid event-related fMRI hyperscanning and reveals a context-based inter-brain coupling between interacting pairs during cooperation and during competition.
Examining the neural correlates of error awareness in a large fMRI study
Authors: Dali Gezelle , Brosnan Méadhbh , Tiego Jeggan , Johnson Beth P , Fornito Alex , Bellgrove Mark A , Hester Robert 
Published: February 2022

AbstractGoal-directed behavior is dependent upon the ability to detect errors and implement appropriate posterror adjustments. Accordingly, several studies have explored the neural activity underlying error-monitoring processes, identifying the insula cortex as crucial for error awareness and reporting mixed findings with respect to the anterior cingulate cortex (ACC). Variable patterns of activation have previously been attributed to insufficient statistical power. We therefore sought to clarify the neural correlates of error awareness in a large event-related functional magnetic resonance imaging (fMRI) study. Four hundred and two healthy participants undertook the error awareness task, a motor Go/No-Go response inhibition paradigm in which participants were required to indicate their awareness of commission errors. Compared to unaware errors, aware errors were accompanied by significantly greater activity in a network of regions, including the insula cortex, supramarginal gyrus (SMG), and midline structures, such as the ACC and supplementary motor area (SMA). Error awareness activity was related to indices of task performance and dimensional measures of psychopathology in selected regions, including the insula, SMG, and SMA. Taken together, we identified a robust and reliable neural network associated with error awareness.
Comparing Coronavirus Disease 2019 (COVID-19) Pandemic Waves in Hospitalized Patients: A Retrospective, Multicenter, Cohort Study
Authors: Niv Yaron , Eliakim-Raz Noa , Bar-Lavi Yaron , Green Manfred , Dreiher Jacob , Hupert Amit , Freedman Laurence , Weiss Yoram , Zetland Riki , Luz Shirli , Menachemi Doron , Kuniavsky Michael , Rahav Gaila , Sagi Ram , Goldschmidt Nethanel , Mahalla Hanna 
Published: February 2022

AbstractBackgroundCoronavirus disease 2019 was first diagnosed in Israel at the end of February 2020. By the end of June 2021, there were 842 536 confirmed cases and 6428 deaths. Our aim in this multicenter, retrospective, cohort study is to describe the demographic and clinical characteristics of hospitalized patients and compare the pandemic waves before immunization.MethodsOf 22 302 patients hospitalized in general medical centers, we randomly selected 6329 for the study. Of these, 3582 and 1106 were eligible for the study in the first period (first and second waves) and in the second period (third wave), respectively.ResultsThirty-day mortality was higher in the second period than in the first period, 25.20% vs 13.68% (P &lt; .001). Invasive mechanical ventilation supported 9.19% and 14.21% of patients in the first period and second period, respectively. Extracorporeal membrane oxygenation (ECMO) was used more than twice as often in the second period.ConclusionsInvasive ventilation, use of ECMO, and mortality rate were 1.5 to 2 times higher in the second period than in the first period. In the second period, patients had a more severe presentation and higher mortality than those in the first period.
Solving the riddle of Aguascalientes nephropathy: nephron number, environmental toxins and family clustering
Authors: Villalvazo Priscila , Carriazo Sol , Martin-Cleary Catalina , Sanchez-Niño Maria Dolores , Ortiz Alberto 
Published: February 2022

ABSTRACTAguascalientes, Mexico, has a high incidence and prevalence of advanced chronic kidney disease (CKD). CKD is especially frequent in young people ages 20–40 years in whom the cause of CKD was unknown, although kidney biopsies frequently showed focal segmental glomerulosclerosis (FSGS) and glomerulomegaly. Macias-Diaz et al. have now pursued this lead by screening teenagers in Calvillo, one of the hardest hit municipalities. They uncovered clinical, laboratory, kidney biopsy and exposure findings that define a new entity, Aguascalientes nephropathy, and are consistent with familial exposure to common environmental toxins, potentially consisting of pesticides. They hypothesize that prenatal exposure to these toxins may decrease nephron number. The young age of persons with FSGS would be consistent with a novel environmental toxin introduced more than 50 years ago but not present in the environment before. Key takeaways from this research are the need to screen teenagers for albuminuria, to provide kidney-protective strategies to patients identified as having CKD and for the research community to support Aguascalientes nephrologists and health authorities to unravel the cause and potential solutions for this CKD hotspot. In this regard, the screening approach and the cohort generated by Macias-Diaz et al. represent a giant step forward. The next steps should be to screen younger children for albuminuria and kidney size and to identify the putative toxins.
Serial passage in an insect host indicates genetic stability of the human probioticEscherichia coliNissle 1917
Authors: Schröder Nicolas C H , Korša Ana , Wami Haleluya , Mantel Olena , Dobrindt Ulrich , Kurtz Joachim 
Published: February 2022

AbstractBackground and objectivesThe probiotic Escherichia coli strain Nissle 1917 (EcN) has been shown to effectively prevent and alleviate intestinal diseases. Despite the widespread medical application of EcN, we still lack basic knowledge about persistence and evolution of EcN outside the human body. Such knowledge is important also for public health aspects, as in contrast to abiotic therapeutics, probiotics are living organisms that have the potential to evolve. This study made use of experimental evolution of EcN in an insect host, the red flour beetle Tribolium castaneum, and its flour environment.MethodologyUsing a serial passage approach, we orally introduced EcN to larvae of T.castaneum as a new host, and also propagated it in the flour environment. After eight propagation cycles, we analyzed phenotypic attributes of the passaged replicate EcN lines, their effects on the host in the context of immunity and infection with the entomopathogen Bacillus thuringiensis, and potential genomic changes using WGS of three of the evolved lines.ResultsWe observed weak phenotypic differences between the ancestral EcN and both, beetle and flour passaged EcN lines, in motility and growth at 30°C, but neither any genetic changes, nor the expected increased persistence of the beetle-passaged lines. One of these lines displayed distinct morphological and physiological characteristics.Conclusions and implicationsOur findings suggest that EcN remains rather stable during serial passage in an insect. Weak phenotypic changes in growth and motility combined with a lack of genetic changes indicate a certain degree of phenotypic plasticity of EcN.Lay SummaryFor studying adaptation of the human probiotic Escherichia coli strain Nissle 1917, we introduced it to a novel insect host system and its environment using a serial passage approach. After passage, we observed weak phenotypic changes in growth and motility but no mutations or changes in persistence inside the host.
The correlation of ESC 2016 diastolic guidelines with invasively measured left ventricular filling pressure
Authors: Barakat A , Amar A , Alsaadi A,R 
Published: February 2022

Abstract

Funding Acknowledgements
Type of funding sources: Public hospital(s). Main funding source(s): Al-mouwasat University Hospital, University Heart Surgery Center in Damascus, Syrian Arab Republic.

Background
left ventricular (LV) diastolic function and filling pressure assessment is a challenge. ESC 2016 diastolic guidelines handles with this issue. Validation of and comparing the correlation between this guidelines and invasively measured different waves may add a step forward in the assessment, prognosis and treatment of LV diastolic function by echo.

Purpose
this study validates of the correlation of ESC 2016 left ventricular filling pressure echo guidelines with invasively measured left ventricular end-diastolic pressure and left ventricular pre-a.

Methods
124 patients who accepted to participate for this study underwent transthoracic echocardiography immediately before left heart catheterization. This study obtained echo parameters to assess LV filling pressure according to ESC 2016 algorithms. It also obtained left ventricular end-diastolic pressure (LVEDP) and LV pre-a waves during catheterization. It analyzed the data and compared the results.

Results
Correlations of grading system (normal, abnormal parameters 1,2 and 3 present) with LV pre-a and LVEDP waves were (P= &lt; 0.0001 r = 0.47, P = 0.0027 r = 0.41), respectively. After excluding group of patients with only one abnormal parameter as indeterminate group, pressure assessment guidelines correlations with the presence of LV pre-a and LVEDP waves were (P = 0.0009 OR = 31.76, p= 0.0170 OR = 36.00), respectively. Means difference of LV pre-a and LVEDP waves between pressure guidelines presence and absence two groups were (LV pre-a: 12.72, 7.52, P &lt; 0.0001and LVEDP: 21.03 10.36, P = 0.0043), respectively. All results are summarized in (Table:1 + 2+3 + 4+5).

Conclusion
ESC 2016 guidelines pressure assessment correlated strongly with both LV pre-a and LVEDP waves which means that the higher the number of abnormal echo parameters is resulted by echo guidelines, the higher the LV pre-a or LVEDP is presented invasively. Different approaches had different diagnostic accuracy, the best specific was cutoff≥ 2 abnormal echo parameters and the best sensitive and overall accuracy was still cutoff≥2 but after excluding only one abnormal echo parameter group as indeterminate group. The difference between means between echo guidelines pressure assessment was more significant statistically in LV pre-a wave than in LVEDP. Abstract Figure. Abstract Figure.