bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling drug combination effects via latent tensor reconstruction
Authors: Wang Tianduanyi , Szedmak Sandor , Wang Haishan , Aittokallio Tero , Pahikkala Tapio , Cichonska Anna , Rousu Juho 
Published: April 2021

Abstract

Motivation
Combination therapies have emerged as a powerful treatment modality to overcome drug resistance and improve treatment efficacy. However, the number of possible drug combinations increases very rapidly with the number of individual drugs in consideration, which makes the comprehensive experimental screening infeasible in practice. Machine-learning models offer time- and cost-efficient means to aid this process by prioritizing the most effective drug combinations for further pre-clinical and clinical validation. However, the complexity of the underlying interaction patterns across multiple drug doses and in different cellular contexts poses challenges to the predictive modeling of drug combination effects.

Results
We introduce comboLTR, highly time-efficient method for learning complex, non-linear target functions for describing the responses of therapeutic agent combinations in various doses and cancer cell-contexts. The method is based on a polynomial regression via powerful latent tensor reconstruction. It uses a combination of recommender system-style features indexing the data tensor of response values in different contexts, and chemical and multi-omics features as inputs. We demonstrate that comboLTR outperforms state-of-the-art methods in terms of predictive performance and running time, and produces highly accurate results even in the challenging and practical inference scenario where full dose–response matrices are predicted for completely new drug combinations with no available combination and monotherapy response measurements in any training cell line.

Availability and implementation
comboLTR code is available at https://github.com/aalto-ics-kepaco/ComboLTR.

Supplementary information
Supplementary data are available at Bioinformatics online.
On the feasibility of deep learning applications using raw mass spectrometry data
Authors: Cadow Joris , Manica Matteo , Mathis Roland , Reddel Roger R , Robinson Phillip J , Wild Peter J , Hains Peter G , Lucas Natasha , Zhong Qing , Guo Tiannan , Aebersold Ruedi , Rodríguez Martínez María 
Published: April 2021

Abstract

Summary
In recent years, SWATH-MS has become the proteomic method of choice for data-independent–acquisition, as it enables high proteome coverage, accuracy and reproducibility. However, data analysis is convoluted and requires prior information and expert curation. Furthermore, as quantification is limited to a small set of peptides, potentially important biological information may be discarded. Here we demonstrate that deep learning can be used to learn discriminative features directly from raw MS data, eliminating hence the need of elaborate data processing pipelines. Using transfer learning to overcome sample sparsity, we exploit a collection of publicly available deep learning models already trained for the task of natural image classification. These models are used to produce feature vectors from each mass spectrometry (MS) raw image, which are later used as input for a classifier trained to distinguish tumor from normal prostate biopsies. Although the deep learning models were originally trained for a completely different classification task and no additional fine-tuning is performed on them, we achieve a highly remarkable classification performance of 0.876 AUC. We investigate different types of image preprocessing and encoding. We also investigate whether the inclusion of the secondary MS2 spectra improves the classification performance. Throughout all tested models, we use standard protein expression vectors as gold standards. Even with our naïve implementation, our results suggest that the application of deep learning and transfer learning techniques might pave the way to the broader usage of raw mass spectrometry data in real-time diagnosis.

Availability and implementation
The open source code used to generate the results from MS images is available on GitHub: https://ibm.biz/mstransc. The data, including the MS images, their encodings, classification labels and results, can be accessed at the following link: https://ibm.ent.box.com/v/mstc-supplementary

Supplementary information
Supplementary data are available at Bioinformatics online.
SeRenDIP-CE: sequence-based interface prediction for conformational epitopes
Authors: Hou Qingzhen , Stringer Bas , Waury Katharina , Capel Henriette , Haydarlou Reza , Xue Fuzhong , Abeln Sanne , Heringa Jaap , Feenstra K Anton 
Published: April 2021

Abstract

Motivation
Antibodies play an important role in clinical research and biotechnology, with their specificity determined by the interaction with the antigen’s epitope region, as a special type of protein–protein interaction (PPI) interface. The ubiquitous availability of sequence data, allows us to predict epitopes from sequence in order to focus time-consuming wet-lab experiments toward the most promising epitope regions. Here, we extend our previously developed sequence-based predictors for homodimer and heterodimer PPI interfaces to predict epitope residues that have the potential to bind an antibody.

Results
We collected and curated a high quality epitope dataset from the SAbDab database. Our generic PPI heterodimer predictor obtained an AUC-ROC of 0.666 when evaluated on the epitope test set. We then trained a random forest model specifically on the epitope dataset, reaching AUC 0.694. Further training on the combined heterodimer and epitope datasets, improves our final predictor to AUC 0.703 on the epitope test set. This is better than the best state-of-the-art sequence-based epitope predictor BepiPred-2.0. On one solved antibody–antigen structure of the COVID19 virus spike receptor binding domain, our predictor reaches AUC 0.778. We added the SeRenDIP-CE Conformational Epitope predictors to our webserver, which is simple to use and only requires a single antigen sequence as input, which will help make the method immediately applicable in a wide range of biomedical and biomolecular research.

Availability and implementation
Webserver, source code and datasets at www.ibi.vu.nl/programs/serendipwww/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Functional roles of the chromatin remodeler SMARCA5 in mouse and bovine preimplantation embryos†
Authors: Shi Yan , Zhao Panpan , Dang Yanna , Li Shuang , Luo Lei , Hu Bingjie , Wang Shaohua , Wang Huanan , Zhang Kun 
Published: April 2021

Abstract
Upon fertilization, extensive chromatin reprogramming occurs during preimplantation development. Growing evidence reveals species-dependent regulations of this process in mammals. ATP-dependent chromatin remodeling factor SMARCA5 (also known as SNF2H) is required for peri-implantation development in mice. However, the specific functional role of SMARCA5 in preimplantation development and if it is conserved among species remain unclear. Herein, comparative analysis of public RNA-seq datasets reveals that SMARCA5 is universally expressed during oocyte maturation and preimplantation development in mice, cattle, humans, and pigs with species-specific patterns. Immunostaining analysis further describes the temporal and spatial changes of SMARCA5 in both mouse and bovine models. siRNA-mediated SMARCA5 depletion reduces the developmental capability and compromises the specification and differentiation of inner cell mass in mouse preimplantation embryos. Indeed, OCT4 is not restricted into the inner cell mass and the formation of epiblast and primitive endoderm disturbed with reduced NANOG and SOX17 in SMARCA5-deficient blastocysts. RNA-seq analysis shows SMARCA5 depletion causes limited effects on the transcriptomics at the morula stage, however, dysregulates 402 genes, including genes involved in transcription regulation and cell proliferation at the blastocyst stage in mice. By comparison, SMARCA5 depletion does not affect the development through the blastocyst stage but significantly compromises the blastocyst quality in cattle. Primitive endoderm formation is greatly disrupted with reduced GATA6 in bovine blastocysts. Overall, our studies demonstrate the importance of SMARCA5 in fostering the preimplantation development in mice and cattle while there are species-specific effects.
On the power of Chatterjee’s rank correlation
Authors: Shi H , Drton M , Han F 
Published: April 2021

SummaryChatterjee (2021) introduced a simple new rank correlation coefficient that has attracted much attention recently. The coefficient has the unusual appeal that it not only estimates a population quantity first proposed by Dette et al. (2013) that is zero if and only if the underlying pair of random variables is independent, but also is asymptotically normal under independence. This paper compares Chatterjee’s new correlation coefficient with three established rank correlations that also facilitate consistent tests of independence, namely Hoeffding’s $D$, Blum–Kiefer–Rosenblatt’s $R$, and Bergsma–Dassios–Yanagimoto’s $\tau^*$. We compare the computational efficiency of these rank correlation coefficients in light of recent advances, and investigate their power against local rotation and mixture alternatives. Our main results show that Chatterjee’s coefficient is unfortunately rate-suboptimal compared to $D$, $R$ and $\tau^*$. The situation is more subtle for a related earlier estimator of Dette et al. (2013). These results favour $D$, $R$ and $\tau^*$ over Chatterjee’s new correlation coefficient for the purpose of testing independence.
PTEN somatic mutations contribute to spectrum of cerebral overgrowth
Authors: Koboldt Daniel C , Miller Katherine E , Miller Anthony R , Bush Jocelyn M , McGrath Sean , Leraas Kristen , Crist Erin , Fair Summer , Schwind Wesley , Wijeratne Saranga , Fitch James , Leonard Jeffrey , Shaikhouni Ammar , Hester Mark E , Magrini Vincent , Ho Mai-Lan , Pierson Christopher R , Wilson Richard K , Ostendorf Adam P , Mardis Elaine R , Bedrosian Tracy A 
Published: April 2021

Abstract
Phosphatase and tensin homologue (PTEN) regulates cell growth and survival through inhibition of the mammalian target of rapamycin (MTOR) signalling pathway. Germline genetic variation of PTEN is associated with autism, macrocephaly and PTEN hamartoma tumour syndromes. The effect of developmental PTEN somatic mutations on nervous system phenotypes is not well understood, although brain somatic mosaicism of MTOR pathway genes is an emerging cause of cortical dysplasia and epilepsy in the paediatric population.
Here we report two somatic variants of PTEN affecting a single patient presenting with intractable epilepsy and hemimegalencephaly that varied in clinical severity throughout the left cerebral hemisphere. High-throughput sequencing analysis of affected brain tissue identified two somatic variants in PTEN. The first variant was present in multiple cell lineages throughout the entire hemisphere and associated with mild cerebral overgrowth. The second variant was restricted to posterior brain regions and affected the opposite PTEN allele, resulting in a segmental region of more severe malformation, and the only neurons in which it was found by single-nuclei RNA-sequencing had a unique disease-related expression profile.
This study reveals brain mosaicism of PTEN as a disease mechanism of hemimegalencephaly and furthermore demonstrates the varying effects of single- or bi-allelic disruption of PTEN on cortical phenotypes.
Signs of congestion in patients with perioperative atrial fibrillation in major noncardiac surgery
Authors: Dzhioeva O , Shvartz VA , Drapkina OM 
Published: April 2021

Abstract

Funding Acknowledgements
Type of funding sources: None.

Purpose
to evaluate the frequency of perioperative atrial fibrillation in patients with postoperative signs of systemic congestion.

Methods
we examined 102 patients who underwent cardiac monitoring in the perioperative period to detect episodes of atrial fibrillation and focused echocardiography to detect signs of systemic congestion. All patients underwent abdominal surgery lasting more than 180 minutes.Clinical, laboratory, and echocardiographic criteria were used to verify systemic stagnation in the postoperative period in patients after non-cardiac surgery.

Results
we determined the number of patients with perioperative AF who had acute decompensation of HF in the early postoperative period, determined by signs of systemic stagnation. When assessing the number of patients with preoperative anamnestic AF, which was initially 16 people, in 100% of cases in the postoperative period, decompensation of HF was noted. When evaluating the number of patients with intraoperative AF, which was detected in 24 patients, decompensation of HF in the first 24 hours after abdominal surgery was observed in 23 patients (95.8%) (OR: 25.4; 95% CI: 3.27-198.14; p &lt;0.001). When assessing the number of patients with postoperative AF, which was detected in 36 patients, decompensation of HF in the first 24 hours after abdominal surgery was observed in 35 patients (97.2%) (OR:57.4;95% CI:7.39-435.45; p &lt;0.001).

Conclusion
in major non-cardiac operations, most patients with perioperative atrial fibrillation show signs of systemic stagnation in the postoperative period with FOCUS.
Prognostic role of the Rockwood Clinical Frailty Scale in patients with acute heart failure:results from a single-centre retrospective cohort study
Authors: Todd F , Wong C , Hewitson L , Mohamed A , Doolub J , Gogola L , Skyrme-Jones A , Aziz S , Sammut E , Dastidar A 
Published: April 2021

Abstract

Funding Acknowledgements
Type of funding sources: None.

Background
Acute decompensated heart failure carries a poor prognosis and places a significant burden on healthcare resources. Our ability to predict patients at high risk of deterioration is limited. The Rockwood Clinical Frailty Scale (CFS) is an established frailty screening tool that stratifies patients on a nine-point scale ranging from 1 (very well) to 9 (terminally ill) providing a useful measure of physiological reserve. CFS is used extensively for general prognostication in geriatric populations, yet its impact on mortality specifically in patients admitted with acute heart failure remains sparsely investigated.

Purpose
We performed a retrospective cohort study to investigate the prognostic role for CFS for short term mortality in patients admitted with acute heart failure.

Methods
Over a period of 16 weeks (7th January – 27th April 2020), 283 consecutive patients presenting to our hospital with signs and symptoms of acute heart failure were identified. Discharge summaries, electronic notes and shared care networks were manually searched for each patient to determine frailty score, baseline demographics, admission bloods and co-morbidity indices. Short term mortality at 30 days was recorded from electronic hospital and GP records. Univariate and multivariate Cox regression analysis was performed to identify clinical and biochemical predictors of mortality.

Results
In total, 283 patients were admitted with acute heart failure over the study period (mean age 81+/-10 years, 46% female. The mean CFS score was 5+/-1 and mean Charlson Comorbidity Index score 8+/-3. 15% of patients died within 30 days. On univariate analysis age, creatinine, Charlson Comorbidity Index and CFS were associated with prognosis. On multivariate analysis, only CFS was found to be an independent predictor of mortality (hazard ratio 1.36, p = 0.029).

Conclusion
This study demonstrates a clear relationship between increasing frailty score and short-term mortality in acute heart failure. The CFS is a rapid and easily accessible screening tool used widely throughout the UK. This work highlights its potential for use alongside other parameters in prognostication of patients presenting with acute decompensated heart failure. Further work is needed to explore the impact on longer term mortality and to determine practical implementation in this setting. Abstract Figure.
Renin-angiotensin-aldosterone system blockers could contribute to the gender-related disparities in STEMI outcomes
Authors: Scridon A , Hadadi L , Sus I , Lakatos EK , Demjen Z , Ceamburu A , Fisca PC , Somkereki C , Serban RC 
Published: April 2021

Abstract

Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Romanian Ministry of Education and Research, CNCS - UEFISCDI

BACKGROUND
Women with ST-segment elevation myocardial infarction (STEMI) have been shown to present higher in-hospital mortality compared to their male counterparts. However, most of these data were obtained in the pre-percutaneous coronary intervention (PCI) or even in the pre-thrombolytic era.

PURPOSE
We aimed to investigate the contribution of female gender to the occurrence of in-hospital complications in STEMI patients treated by primary PCI.

METHODS
Data regarding in-hospital outcomes (i.e., mortality, inotropic and diuretic drugs usage, occurrence of cardiogenic shock, cardiac arrest) were evaluated in 848 consecutive patients treated by primary PCI for STEMI. Occurrence of new-onset kidney dysfunction and length of hospital stay were also analysed. The relationship between gender and the occurrence of STEMI-related complications was evaluated.

RESULTS
Out of the 848 patients included in the study, 254 (29.9%) were women. Compared to their male counterparts, female STEMI patients were older (65.7 ± 11.3 vs. 60.1 ± 11.8 years; p&lt; 0.0001), had more often pre-existing heart failure, hypertension, diabetes mellitus, and chronic kidney disease (all p&lt; 0.05), longer symptom onset-to-cardiac catheterization laboratory time intervals (7.9 ± 6.7 vs. 6.4 ± 5.0 h; p&lt; 0.001), and higher Killip class on admission (p = 0.02). Cardiogenic shock, inotropic and diuretic drugs usage, kidney dysfunction, and cardiac arrest occurred more often in female than in male patients (all p&lt; 0.01). The length of hospital stay (p&lt; 0.01) and in-hospital death (RR 1.89 [95%CI 1.43-2.50], p&lt; 0.001) were also higher in female compared to male patients, whereas renin-angiotensin-aldosterone system (RAAS) blockers were used more rarely in female patients (p = 0.01). When corrected for potential confounders, female gender remained an independent predictor of in-hospital mortality (p = 0.01). However, when in-hospital RAAS blockers usage was included in the model, female gender was no longer associated with increased in-hospital mortality (p = 0.15).

CONCLUSIONS
Female patients with STEMI continue to display significantly higher in-hospital mortality rates compared to their male peers including in the primary PCI era. The difference in in-hospital mortality between female and male patients with STEMI could be at least partially due to the significantly lower usage of RAAS blockers in women. Increasing in-hospital RAAS blockers usage in female patients with STEMI may improve survival in this high-risk population.
Admission biomarkers among patients with acute myocardial-infarction related cardiogenic shock with or without out-of-hospital cardiac arrest
Authors: Thoegersen M , Frydland M , Helgestad O , Jensen LO , Josiassen J , Goetze JP , Moeller JE , Hassager C 
Published: April 2021

Abstract

Funding Acknowledgements
Type of funding sources: Foundation. Main funding source(s): Lundbeck Foundation

OnBehalf
Critical Cardiac Care Research Group

Background
Approximately half of all patients with acute myocardial infarction complicated by cardiogenic shock (AMICS) present with out-of-hospital cardiac arrest (OHCA). Cardiogenic shock due to OHCA is caused by abrupt cessation of circulation, whereas AMICS without OHCA is due to cardiac failure with low cardiac output. Thus, there may also be differences between the two conditions in terms of blood borne biomarkers.

Purpose
To explore the potential differences in the admission plasma concentrations of biomarkers reflecting tissue perfusion (lactate), neuroendocrine response (mid-regional proadrenomedullin [MRproADM], Copeptin, pro-atrial natriuretic peptide [proANP]), endothelial damage (Syndecan-1, soluble thrombomodulin [sTM]), inflammation (soluble suppression of tumorigenicity 2 [sST2]) and kidney injury (neutrophil gelatinase-associated lipocalin [NGAL]), in patients with AMICS presenting with or without OHCA.

Method
Consecutive patients admitted for acute coronary angiography due to suspected ST-elevation myocardial infarction (STEMI) were enrolled during a 1-year period. A total of 2,713 patients were screened. In the present study 86 patients with confirmed STEMI and CS at admission were included.

Results
Patients with OHCA (had significantly higher median admission concentrations of Lactate (6,9 mmol/L vs. 3.4 mmol/L p &lt;0.001), NGAL (220 ng/ml vs 150 ng/ml p = 0.046), sTM (10 ng/ml vs. 8.0 ng/ml p = 0.026) and Syndecan-1 (160 ng/ml vs. 120 ng/ml p= 0.015) and significantly lower concentrations of MR-proADM (0.85 nmol/L vs. 1.6 nmol/L p &lt;0.001) and sST2 (39 ng/ml vs. 62 ng/ml p &lt; 0.001). After adjusting for age, sex, and time from symptom onset to coronary angiography, lactate (p = 0.008), NGAL (p = 0.03) and sTM (p = 0.011) were still significantly higher in patients presenting with OHCA while sST2 was still significantly lower (p = 0.029). There was very little difference in 30-day mortality between the OHCA and non-OHCA groups (OHCA 37% vs. non-OHCA 38%).

Conclusion
Patients with STEMI and CS at admission with or without concomitant OHCA had similar 30-day mortality but differed in terms of Lactate, NGAL, sTM and sST2 levels at the time of admission to catheterization laboratory. These findings propose that non-OHCA and OHCA patients with CS could be considered as two individual clinical entities. Abstract Figure. Level of biomarkers OHCA vs. non-OHCA