bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteomic Biomarkers to Guide Stratification for Covid‐19 Treatment: Exemplifying a Path Forward Toward Implementation?
Authors: Jankowski Joachim 
Published: November 2020

AbstractProteins and peptides serve as biomarkers in the context of multiple pathologies. The hypothesis that protein or peptide biomarkers may also be of value in the context of the Covid‐19 pandemic appears self‐evident. Proteome based biomarkers are not expected to display significant added value in the detection of viral infection but appear well suited to address a major unmet need: the prognosis of the course of disease, to guide appropriate, timely intervention. Based on similar approaches in the context of other diseases and using a CE–MS platform, urinary peptides are investigated for their value as biomarkers to assess disease progression after SARS‐CoV‐2 infection. The manuscript presented in this issue of Proteomics reports first results, indicating that urine peptides may be of substantial value in the assessment and prediction of severity of the Covid‐19 disease course on an individual level. While the findings are not entirely surprising, the report does stand out from all others by a well‐defined context‐of‐use, and, what is more, by presenting an already initiated validation study that may, if successful, result in immediate implementation of this proteomics‐based diagnostic test. This approach should serve as positive example for the planning and execution of clinical proteomics studies.
TMPRSS2‐ERG fusion impacts anterior tumor location in men with prostate cancer
Authors: Yamoah Kosj , Lal Priti , Awasthi Shivanshu , Naghavi Arash O. , Rounbehler Robert J. , Gerke Travis , Berglund Anders E. , Pow‐Sang Julio M. , Schaeffer Edward M. , Dhillon Jasreman , Park Jong Y. , Rebbeck Timothy R. 
Published: November 2020

AbstractBackgroundIn prostate cancer (PCa), lack of androgen receptor (AR) regulated TMPRSS2‐ETS‐related gene (ERG) gene fusion (ERGnegative) status has been associated with African American race; however, the implications of ERG status for the location of dominant tumors within the prostate remains understudied.MethodsAn African American‐enriched multiinstitutional cohort of 726 PCa patients consisting of both African American men (AAM; n = 254) and European American men (EAM; n = 472) was used in the analyses. Methods of categorical analysis were used. Messenger RNA (mRNA) expression differences between anterior and posterior tumor lesions were analyzed using Wilcoxon rank‐sum tests with multiple comparison corrections.ResultsAnti‐ERG immunohistochemistry staining showed that the association between ERG status and anterior tumors is independent of race and is consistently robust for both AAM (ERGnegative 81.4% vs. ERGpositive 18.6%; p = .005) and EAM (ERGnegative 60.4% vs. ERGpositive 39.6%; p < .001). In a multivariable model, anterior tumors were more likely to be IHC‐ERGnegative (odds ratio [OR]: 3.20; 95% confidence interval [CI]: 2.14–4.78; p < .001). IHC‐ERGnegative were also more likely to have high‐grade tumors (OR: 1.73; 95% CI: 1.06–2.82; p = .02). In the exploratory genomic analysis, mRNA expression of location‐dependent genes is highly influenced by ERG status and African American race. However, tumor location did not impact the expression of AR or the major canonical AR‐target genes (KLK3, AMACR, and MYC).ConclusionsERGnegative tumor status is the strongest predictor of anterior prostate tumors, regardless of race. Furthermore, AR expression and canonical AR signaling do not impact tumor location.
Simplified geometric representations of protein structures identify complementary interaction interfaces
Authors: McCafferty Caitlyn L. , Marcotte Edward M. , Taylor David W. 
Published: November 2020

AbstractProtein‐protein interactions are critical to protein function, but three‐dimensional (3D) arrangements of interacting proteins have proven hard to predict, even given the identities and 3D structures of the interacting partners. Specifically, identifying the relevant pairwise interaction surfaces remains difficult, often relying on shape complementarity with molecular docking while accounting for molecular motions to optimize rigid 3D translations and rotations. However, such approaches can be computationally expensive, and faster, less accurate approximations may prove useful for large‐scale prediction and assembly of 3D structures of multi‐protein complexes. We asked if a reduced representation of protein geometry retains enough information about molecular properties to predict pairwise protein interaction interfaces that are tolerant of limited structural rearrangements. Here, we describe a reduced representation of 3D protein accessible surfaces on which molecular properties such as charge, hydrophobicity, and evolutionary rate can be easily mapped, implemented in the MorphProt package. Pairs of surfaces are compared to rapidly assess partner‐specific potential surface complementarity. On two available benchmarks of 185 overall known protein complexes, we observe predictions comparable to other structure‐based tools at correctly identifying protein interaction surfaces. Furthermore, we examined the effect of molecular motion through normal mode simulation on a benchmark receptor‐ligand pair and observed no marked loss of predictive accuracy for distortions of up to 6 Å Cα‐RMSD. Thus, a shape reduction of protein surfaces retains considerable information about surface complementarity, offers enhanced speed of comparison relative to more complex geometric representations, and exhibits tolerance to conformational changes.
Formation of positive product ions from substances with low proton affinity in high kinetic energy ion mobility spectrometry
Authors: Allers Maria , Kirk Ansgar T. , Schaefer Christoph , Schlottmann Florian , Zimmermann Stefan 
Published: November 2020

RationaleIon mobility spectrometry (IMS) instruments are typically equipped with atmospheric pressure chemical ionization (APCI) sources operated at ambient pressure. However, classical APCI‐IMS suffers from a limited ionization yield for nonpolar substances with low proton affinity (PA). This is mainly due to ion clustering processes, especially those that involve water molecules, inhibiting the ionization of these substances.MethodsHigh Kinetic Energy (HiKE)‐IMS instruments are operated at decreased pressures and high reduced electric field strengths. As most clustering reactions are inhibited under these conditions, the ionization yield for nonpolar substances with low PA in HiKE‐IMS should differ from that in classical APCI‐IMS. To gain first insights into the ionization capabilities and limitations of HiKE‐IMS, we investigated the ionization of four model substances with low PA in HiKE‐IMS using HiKE‐IMS‐MS as a function of the reduced electric field strength.ResultsThe four model substances all have proton affinities between those of H2O and (H2O)2 but exhibit different ionization energies, dipole moments, and polarizabilities. As expected, the results show that the ionization yield for these substances differs considerably at low reduced electric field strengths due to ion cluster formation. In contrast, at high reduced electric field strengths, all substances can be ionized via charge and/or proton transfer in HiKE‐IMS.ConclusionsConsidering the detection of polar substances with high PAs, classical ambient pressure IMS should reach better detection limits than HiKE‐IMS. However, considering the detection of nonpolar substances with low PA that are not detected, or only difficult to detect, at ambient pressure, HiKE‐IMS would be beneficial.
Screening for illegal addition of glucocorticoids in adulterated cosmetic products using ultra‐performance liquid chromatography/tandem mass spectrometry with precursor ion scanning
Authors: Jian Longhai , Yuan Xiaoqian , Han Jing , Zheng Rong , Peng Xingsheng , Wang Ke 
Published: November 2020

RationaleThe screening for illegal adulteration of glucocorticoids (GCs) in cosmetics is challenging due to the vast variety of potential GCs that are present to improve the declared effects. An effective analytical method to screen illegally added GCs in cosmetics is vital to protect consumers.MethodsAn ultra‐performance liquid chromatography/tandem mass spectrometry (UPLC/MS/MS) method using precursor ion scanning (PIS) acquisition mode was developed to screen GCs in cosmetics. Forty‐seven GCs were investigated to identify their common product ions formed by collision‐induced dissociation. Cosmetic samples spiked with GCs were extracted using solid‐phase extraction.ResultsFour common positive product ions, m/z 121, 135, 147, and 171, were selected for PIS analysis. Limits of detection (LODs) were established for all 47 GCs. The method was validated on spiked samples to ensure its effectiveness in terms of sensitivity and selectivity. Sixty samples were analyzed. Seven GCs were detected in six samples.ConclusionsAn effective screening method using UPLC/MS/MS with PIS acquisition mode was developed and successfully applied to screen for targeted and untargeted GCs in cosmetic samples.
Selective Fabrication of Single‐Molecule Junctions by Interface Engineering
Authors: Zeng Biao‐Feng , Wang Gan , Qian Qiao‐Zan , Chen Zhi‐Xin , Zhang Xia‐Guang , Lu Zhi‐Xing , Zhao Shi‐Qiang , Feng An‐Ni , Shi Jia , Yang Yang , Hong Wenjing 
Published: November 2020

AbstractRecent progress in addressing electrically driven single‐molecule behaviors has opened up a path toward the controllable fabrication of molecular devices. Herein, the selective fabrication of single‐molecule junctions is achieved by employing the external electric field. For molecular junctions with methylthio (–SMe), thioacetate (–SAc), amine (–NH2), and pyridyl (–PY), the evolution of their formation probabilities along with the electric field is extracted from the plateau analysis of individual single‐molecule break junction traces. With the increase of the electric field, the SMe‐anchored molecules show a different trend in the formation probability compared to the other molecular junctions, which is consistent with the density functional theory calculations. Furthermore, switching from an SMe‐anchored junction to an SAc‐anchored junction is realized by altering the electric field in a mixed solution. The results in this work provide a new approach to the controllable fabrication and modulation of single‐molecule junctions and other bottom‐up nanodevices at molecular scales.
A square lattice topology coordination network that exhibits highly selective C2H2/CO2 separation performance
Authors: Kumar Naveen , Mukherjee Soumya , Bezrukov Andrey A. , Vandichel Matthias , Shivanna Mohana , Sensharma Debobroto , Bajpai Alankriti , Gascón Victoria , Otake Ken‐ichi , Kitagawa Susumu , Zaworotko Michael J. 
Published: November 2020

AbstractC2H2/CO2 separation is an industrially important process that remains challenging because of the similar physicochemical properties of C2H2 and CO2. We herein report that the new square lattice (sql) coordination network [Cu(bipy‐xylene)2(NO3)2]n, sql‐16‐Cu‐NO3, 16 = bipy‐xylene = 4,4′‐(2,5‐dimethyl‐1,4‐phenylene)dipyridine, exists in at least three forms, as‐synthesised (α), activated (α′) and hydrated (β). The activated phase, sql‐16‐Cu‐NO3‐α′, is an ultramicroporous material that exhibits high selectivity towards C2H2 over CO2 as revealed by dynamic gas breakthrough experiments (1:1, C2H2/CO2) that afforded 99.87% pure CO2 in the effluent stream. The separation selectivity at 298 K and 1 bar, 78, is the third best value yet reported for C2H2 selective physisorbents whereas the mid‐loading performance sets a new benchmark. The performance of sql‐16‐Cu‐NO3‐α′ is attributed to a new type of C2H2 binding site in which CH···ONO2 interactions enable moderately strong sorbent‐sorbate binding (Qst (C2H2) = 38.6 kJ/mol) at low loading. Conversely, weak CO2 binding (Qst (CO2) = 25.6 kJ/mol) at low loading means that (ΔQst)AC [Qst (C2H2)–Qst (CO2)] is 13 kJ/mol at low coverage and 11.4 kJ/mol at mid‐loading. Analysis of in situ powder X‐ray diffraction and modelling experiments provide insight into the sorption properties and high C2H2/CO2 separation performance of sql‐16‐Cu‐NO3‐α′.
Engineering faster sorters for small sets of items
Authors: Bingmann Timo , Marianczuk Jasper , Sanders Peter 
Published: November 2020

AbstractSorting a set of items is a task that can be useful by itself or as a building block for more complex operations. That is why a lot of effort has been put into finding sorting algorithms that sort large sets as efficiently as possible. But the more sophisticated and complex the algorithms become, the less efficient they are for small sets of items due to large constant factors. A relatively simple sorting algorithm that is often used as a base case sorter is insertion sort, because it has small code size and small constant factors influencing its execution time. We aim to determine if there is a faster way to sort small sets of items to provide an efficient base case sorter. We looked at sorting networks, at how they can improve the speed of sorting few elements, and how to implement them in an efficient manner using conditional moves. Since sorting networks need to be implemented explicitly for each set size, providing networks for larger sizes becomes less efficient due to increased code sizes. To also enable the sorting of slightly larger base cases, we adapted sample sort to Register Sample Sort, to break down those larger sets into sizes that can in turn be sorted by sorting networks. From our experiments we found that when sorting only small sets of integers, the sorting networks outperform insertion sort by a factor of at least 1.76 for any array size between six and 16, and by a factor of 2.72 on average across all machines and array sizes. When integrating sorting networks as a base case sorter into Quicksort, we achieved far less performance improvements over using insertion sort, which is probably due to the networks having a larger code size and cluttering the L1 instruction cache. The same effect occurs when including Register Sample Sort as a base case sorter for IPSo. But for x86 machines that have a larger L1 instruction cache of 64 KiB or more, we obtained speedups of 12.7% when using sorting networks as a base case sorter in std::sort, and of 5%–6% when integrating Register Sample Sort as a base case sorter into IPSo, each in comparison to using insertion sort as the base case sorter. In conclusion, the desired improvement in speed could only be achieved under special circumstances, but the results clearly show the potential of using conditional moves in the field of sorting algorithms.
Optical coherence tomography: From technology to applications in ophthalmology
Authors: Everett Matthew , Magazzeni Stephanie , Schmoll Tilman , Kempe Michael 
Published: November 2020

AbstractThe relatively fast translation of optical coherence tomography (OCT) from an optical measurement technology to a standard of care in ophthalmology was driven by its ability to address clear unmet diagnostic needs. OCT's further technological developments have expanded its clinical use by extending the imaging range (wider, deeper) and the imaging contrast (from morphology to blood flow). The translation of technical advances into clinical value is an ongoing process involving both the potential substitution of established diagnostics (such as fundus angiography) and the identification of novel feature‐disease correlations. This review looks into the development, the status and the prospects of OCT with regard to translation to clinical routine in ophthalmology.
Molecule‐Based Transistors: From Macroscale to Single Molecule.
Authors: Li Peihui , Jia Chuancheng , Guo Xuefeng 
Published: November 2020

AbstractMolecule‐based field‐effect transistors (FETs) are of great significance as they have a wide range of application prospects, such as logic operations, information storage and sensor monitoring. This account mainly introduces and reviews our recent work in molecular FETs. Specifically, through molecular and device design, we have systematically investigated the construction and performance of FETs from macroscale to nanoscale and even single molecule. In particular, we have proposed the broad concept of molecular FETs, whose functions can be achieved through various external controls, such as light stimulation, and other physical, chemical or biological interactions. In the end, we tend to focus the discussion on the development challenges of single‐molecule FETs, and propose prospects for further breakthroughs in this field.
Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: comparison with expert subjective assessment
Authors: Christiansen F. , Epstein E. L. , Smedberg E. , Åkerlund M. , Smith K. , Epstein E. 
Published: November 2020

AbstractObjectivesTo develop and test the performance of computerized ultrasound image analysis using deep neural networks (DNNs) in discriminating between benign and malignant ovarian tumors and to compare its diagnostic accuracy with that of subjective assessment (SA) by an ultrasound expert.MethodsWe included 3077 (grayscale, n = 1927; power Doppler, n = 1150) ultrasound images from 758 women with ovarian tumors, who were classified prospectively by expert ultrasound examiners according to IOTA (International Ovarian Tumor Analysis) terms and definitions. Histological outcome from surgery (n = 634) or long‐term (≥ 3 years) follow‐up (n = 124) served as the gold standard. The dataset was split into a training set (n = 508; 314 benign and 194 malignant), a validation set (n = 100; 60 benign and 40 malignant) and a test set (n = 150; 75 benign and 75 malignant). We used transfer learning on three pre‐trained DNNs: VGG16, ResNet50 and MobileNet. Each model was trained, and the outputs calibrated, using temperature scaling. An ensemble of the three models was then used to estimate the probability of malignancy based on all images from a given case. The DNN ensemble classified the tumors as benign or malignant (Ovry‐Dx1 model); or as benign, inconclusive or malignant (Ovry‐Dx2 model). The diagnostic performance of the DNN models, in terms of sensitivity and specificity, was compared to that of SA for classifying ovarian tumors in the test set.ResultsAt a sensitivity of 96.0%, Ovry‐Dx1 had a specificity similar to that of SA (86.7% vs 88.0%; P = 1.0). Ovry‐Dx2 had a sensitivity of 97.1% and a specificity of 93.7%, when designating 12.7% of the lesions as inconclusive. By complimenting Ovry‐Dx2 with SA in inconclusive cases, the overall sensitivity (96.0%) and specificity (89.3%) were not significantly different from using SA in all cases (P = 1.0).ConclusionUltrasound image analysis using DNNs can predict ovarian malignancy with a diagnostic accuracy comparable to that of human expert examiners, indicating that these models may have a role in the triage of women with an ovarian tumor. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
Fun30 chromatin remodeler helps in dealing with torsional stress and camptothecin‐induced DNA damage
Authors: Al‐Natour Zeina , Chalissery Jisha , Hassan Ahmed H. 
Published: November 2020

AbstractFun30 is an ATP‐dependent chromatin remodeler in budding yeast that is involved in cellular processes important for maintaining genomic stability such as gene silencing and DNA damage repair. Cells lacking Fun30 are moderately sensitive to the topoisomerase inhibitor camptothecin and exhibit a delay in cell cycle progression in the presence of camptothecin. Here, we show that Fun30 is required to cope with torsional stress in the absence of Top1. Moreover, we show through genetic studies that Fun30 acts in a parallel pathway to Mus81 endonuclease but is epistatic to Tdp1 phosphodiesterase and Rad1 endonuclease in the repair of camptothecin‐induced DNA damage. More importantly, we show that DNA damage sensitivity of Fun30 deficient cells is enhanced in the absence of RNase H enzymes that remove RNA:DNA hybrids. We believe that chromatin remodeling by Fun30 may be important in dealing with torsional stress and camptothecin‐induced DNA damage.
Prediction of culture-positive sepsis and selection of empiric antibiotics in critically ill patients with complicated intra-abdominal infections: a retrospective study
Authors: Sim Joohyun , Hong Sung Soo , Kwak Jae Young , Jung Yun Tae 
Published: November 2020

Abstract
Purpose
To compare the mortality rates between culture-positive and culture-negative sepsis in complicated intra-abdominal infections (cIAI) and investigate the predictors of culture-positivity and their causative microorganisms.

Materials and methods
The medical records of 1581 adult patients who underwent emergency gastrointestinal surgery between January 2013 and December 2018 were reviewed retrospectively. A total of 239 patients with sepsis or septic shock who were admitted to an emergency department, underwent emergency surgery for cIAI, and needed postoperative intensive care unit care were included and divided into two groups according to their initial blood and peritoneal culture results.

Results
Among the 239 patients, 200 were culture-negative and 39 were culture-positive. The culture-positive group had higher in-hospital (35.9% vs 14.5%; P = .001) and 30-day mortality (30.8% vs 12.0%; P = .003) than the culture-negative group. Colon involvement (OR 4.211; 95% CI 1.909–9.287; P < .001) and higher Sequential Organ Failure Assessment (SOFA) score (OR 1.169; 95% CI 1.065–1.282; P = .001) were shown to be the predictors of culture-positive sepsis for cIAI. Regarding antibiotic sensitivity, 31.6% of the gram-positive bacteria were methicillin-resistant and 42.1% of the gram-negative bacteria were extended spectrum β-lactamase-producing Enterobacteriaceae.

Conclusions
Patients with cIAI had higher mortality rates in culture-positive sepsis than in culture-negative sepsis. High SOFA score and colon involvement were the risk factors associated with culture-positivity. The most common single species grown in the blood or peritoneal cultures was Escherichia coli, and the most common group was Gram-positive cocci.
Spectral Gap in Mean-Field $${\mathcal {O}}(n)$$-Model
Authors: Becker Simon , Menegaki Angeliki 
Published: November 2020

AbstractWe study the dependence of the spectral gap for the generator of the Ginzburg–Landau dynamics for all$$\mathcal O(n)$$O(n)-modelswith mean-field interaction and magnetic field, below and at the critical temperature on the numberNof particles. For our analysis of the Gibbs measure, we use a one-step renormalization approach and semiclassical methods to study the eigenvalue-spacing of an auxiliary Schrödinger operator.