bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiology and Clinical Characteristics of Bloodstream Infection in Patients Under Extracorporeal Membranous Oxygenation
Authors: Yun Ji Hyun , Hong Sang-Bum , Jung Sung-Ho , Kang Pil Je , Sung Heungsup , Kim Mi-Na , Kim Sung-Han , Lee Sang-Oh , Choi Sang-Ho , Woo Jun Hee , Kim Yang-Soo , Chong Yong Pil 
Published: December 2020

Background: Bloodstream infection (BSI) is an important complication of extracorporeal membranous oxygenation (ECMO) and a major cause of mortality. This study evaluated the epidemiological and clinical characteristics of BSI that occur during ECMO application according to microbial etiology. Methods: Adult patients who underwent ECMO from January 2009 to December 2016 were retrospectively analyzed for BSI episodes at a 2,700-bed, tertiary center. Epidemiological and clinical characteristics and outcomes of BSI were evaluated and were compared for etiologic groups (gram-positive cocci, gram-negative rods, and fungi groups). Risk factors for 14-day mortality were analyzed. Results: A total of 1,100 patients underwent ECMO during the study period, and 65 BSI episodes occurred in 61 patients. The BSI incidence was 8.3 episodes/1,000 ECMO days, which significantly decreased over time ( P = 0.03), primarily in gram-positive cocci BSI. Gram-positive cocci, gram-negative rods, and fungi accounted for 38%, 40%, and 22% of the 73 blood isolates, respectively. Baseline characteristics were comparable between groups. Catheter-related infection (CRI) and pneumonia were the most common sources of BSI; 52% of gram-positive cocci BSIs and 79% of fungi BSIs were caused by CRI, and 75% of gram-negative BSIs by pneumonia. Patients with gram-negative rods BSI died more frequently and earlier than those with other BSIs. Independent risk factors for 14-day mortality were older age and gram-negative rods BSI. Conclusions: The decreased BSI incidence during ECMO was mainly because of the decrease of gram-positive cocci BSI. The high early mortality of gram-negative rods BSI makes prevention and adequate treatment necessary.
Maternal Country of Birth and Exclusive Breastfeeding During the First In-Hospital Day in Portugal: The Influence of the Baby-Friendly Hospital Initiative
Authors: Lisi Cosima , De Freitas Cláudia , Barros Henrique 
Published: December 2020

Background Early breastfeeding practices are important determinants of later breastfeeding behaviors and can be influenced by multiple factors. Despite the Baby-Friendly Hospital Initiative reported positive influence on breastfeeding initiation, its influence on the association between maternal country of birth and first day in-hospital breastfeeding has not been examined. Research aims To determine (1) if association between maternal country of birth and first day in-hospital exclusive breastfeeding exists in Portugal and (2) if any association is affected by giving birth in a Baby-Friendly Hospital. Methods Data were drawn from baMBINO—a longitudinal, 2017–2019 nationwide study designed to assess the perinatal health and healthcare experiences of migrant and native Portuguese women. Data from participants ( N = 5,340) were collected during their hospital stay from 32 maternity units. Missing data were handled through multiple imputation. After stratifying by Baby-Friendly Hospital Initiative accreditation, a multivariate logistic regression was performed. Results First day in-hospital exclusive breastfeeding rates were high among both migrant and native participants (89.2% vs. 87.4%). Migrants were more likely to exclusively breastfeed when compared to natives ( OR = 1.19, 95% CI [1.00, 1.41]). In non-Baby-Friendly Hospitals, a positive association was found between participants from Eastern European countries (a OR = 2.46, 95% CI [1.27, 4.78]) and first day in-hospital exclusive breastfeeding. In accredited hospitals, maternal country of birth did not influence exclusive breastfeeding during the first 24 hr. Conclusions The Baby-Friendly Hospital Initiative attenuates differences between migrant and native participants, promoting optimal breastfeeding practices among natives.
Impact of obesity on safety outcomes and treatment modifications with ado-trastuzumab emtansine in breast cancer patients
Authors: Lee Anna , Larck Chris , Moore Donald C 
Published: December 2020

Introduction Ado-trastuzumab emtansine (T-DM1) is an antibody-drug conjugate indicated for the treatment of HER2-positive breast cancer. The 2012 American Society of Clinical Oncology guidelines on chemotherapy dosing in obesity recommend using full weight-based cytotoxic chemotherapy doses to treat obese patients with cancer. These guidelines were published prior to the advent of anticancer antibody-drug conjugates. There is a need to investigate the safety of T-DM1 in obese patients. Methods This retrospective chart review included adult patients with breast cancer receiving T-DM1. The primary endpoint was a composite of the incidence of T-DM1 treatment modifications secondary to an adverse event. Secondary outcomes included the incidence of dose reductions, dose delays, treatment discontinuations, and adverse events. Results A total of 119 patients with HER2-positive breast cancer who received T-DM1 therapy were included in this study: 44 obese patients and 75 non-obese patients. The composite outcome of treatment modifications due to toxicity was significantly higher in obese patients compared to non-obese patients (45% vs 25%, p = 0.024). Treatment delays were significantly higher in obese patients (36% vs 16%, p = 0.011). All-grade adverse events with a higher incidence in obese patients included left ventricular ejection fraction decrease (11% vs 5%), bilirubin increase (32% vs 12%), thrombocytopenia (61% vs 55%), and peripheral neuropathy (34% vs 27%). Conclusions This study suggests obese patients receiving T-DM1 may require more treatment modifications secondary to adverse events compared to non-obese patients. Larger studies are needed to determine if obese patients are at higher risk for specific T-DM1-induced adverse events.
Optimal Design of Paired Built Environment Interventions for Control of MDROs in Acute Care and Community Hospitals
Authors: Squire Marietta M. , Sessel Gareth K. , Lin Gary , Squire Edward N. , Igusa Takeru 
Published: December 2020

Objectives: Our goal was to optimize infection control of paired environmental control interventions within hospitals to reduce methicillin-resistant Staphylococcus aureus (MRSA), carbapenem-resistant Enterobacteriaceae (CRE), and vancomycin-resistant Enterococci (VRE). Background: The most widely used infection control interventions are deployment of handwashing (HW) stations, control of relative humidity (RH), and negative pressure (NP) treatment rooms. Direct costs of multidrug-resistant organism (MDRO) infections are typically not included in the design of such interventions. Methods: We examined the effectiveness of pairing HW with RH and HW with NP. We used the following three data sets: A meta-analysis of progression rates from uncolonized to colonized to infected, 6 years of MDRO treatment costs from 400 hospitals, and 8 years of MDRO incidence rates at nine army hospitals. We used these data as inputs into an Infection De-Escalation Model with varying budgets to obtain optimal intervention designs. We then computed the infection and prevention rates and cost savings resulting from these designs. Results: The average direct cost of an MDRO infection was $3,289, $1,535, and $1,067 for MRSA, CRE, and VRE. The mean annual incidence rates per facility were 0.39%, 0.034%, and 0.011% for MRSA, CRE, and VRE. After applying the cost-minimizing intervention pair to each scenario, the percentage reductions in infections (and annual direct cost savings) in large, community, and small acute care hospitals were 69% ($1.5 million), 73% ($631K), 60% ($118K) for MRSA, 52% ($460.5K), 58% ($203K), 50% ($37K) for CRE, and 0%, 0%, and 50% ($12.8K) for VRE. Conclusion: The application of this Infection De-Escalation Model can guide cost-effective decision making in hospital built environment design to improve control of MDRO infections.
Serum C-reactive protein and WBC count in conservatively and operatively managed bacterial spondylodiscitis
Authors: van Gerven Christina , Eid Kevin , Krüger Tobias , Fell Michael , Kendoff Daniel , Friedrich Michael , Kraft Clayton N 
Published: December 2020

Purpose: C-reactive protein (CRP) and white blood cell (WBC) count are routine blood chemistry parameters in monitoring infection. Little is known about the natural history of their serum levels in conservative and operative spondylodiscitis treatment. Methods: Pre- and postoperative serum levels of CRP and WBC count in 145 patients with spondylodiscitis were retrospectively assessed. One hundred and four patients were treated by debridement, spondylodesis, and an antibiotic regime, 41 only with a brace and antibiotics. The results of the surgical group were compared to 156 patients fused for degenerative disc disease (DDD). Results: Surgery had a significant effect on peak postoperative CRP levels. In surgically managed patients, CRP peaked at 2–3 days after surgery (spondylodiscitis: pre-OP: 90 mg/dl vs. post-OP days 2–3: 146 mg/dl; DDD: 9 mg/dl vs. 141 mg/dl; p < 0.001), followed by a sharp decline. Although values were higher for spondylodiscitis patients, dynamics of CRP values were similar in both groups. Nonoperative treatment showed a slower decline. Surgically managed spondylodiscitis showed a higher success rate in identifying bacteria. Specific antibiotic treatment led to a more predictable decline of CRP values. WBC did not show an interpretable profile. Conclusion: CRP is a predictable serum parameter in patients with spondylodiscitis. WBC count is unspecific. Initial CRP increase after surgery is of little value in monitoring infection. A preoperative CRP value, and control once during the first 3 days after surgery is sufficient. Closer monitoring should then be continued. Should a decline not be observed, therapy needs to be scrutinized, antibiotic treatment reassessed, and concomitant infection contemplated.
Evolution of drug resistance in HIV protease
Authors: Shah Dhara , Freas Christopher , Weber Irene T. , Harrison Robert W. 
Published: December 2020

AbstractBackgroundDrug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to identify protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies. Few studies, however, have assessed the evolution of resistance from genotype–phenotype data.ResultsThe machine learning produced highly accurate and robust classification of resistance to HIV protease inhibitors. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Estimates of evolutionary relationships, based on this encoding, and using Minimum Spanning Trees, showed clusters of mutations that closely resemble the wild type. These clusters appear to evolve uniquely to more resistant phenotypes.ConclusionsUsing the triangulation metric and spanning trees results in paths that are consistent with evolutionary theory. The majority of the paths show bifurcation, namely they switch once from non-resistant to resistant or from resistant to non-resistant. Paths that lose resistance almost uniformly have far lower levels of resistance than those which either gain resistance or are stable. This strongly suggests that selection for stability in the face of a rapid rate of mutation is as important as selection for resistance in retroviral systems.
Automated Isoform Diversity Detector (AIDD): a pipeline for investigating transcriptome diversity of RNA-seq data
Authors: Plonski Noel-Marie , Johnson Emily , Frederick Madeline , Mercer Heather , Fraizer Gail , Meindl Richard , Casadesus Gemma , Piontkivska Helen 
Published: December 2020

Abstract
Background
As the number of RNA-seq datasets that become available to explore transcriptome diversity increases, so does the need for easy-to-use comprehensive computational workflows. Many available tools facilitate analyses of one of the two major mechanisms of transcriptome diversity, namely, differential expression of isoforms due to alternative splicing, while the second major mechanism—RNA editing due to post-transcriptional changes of individual nucleotides—remains under-appreciated. Both these mechanisms play an essential role in physiological and diseases processes, including cancer and neurological disorders. However, elucidation of RNA editing events at transcriptome-wide level requires increasingly complex computational tools, in turn resulting in a steep entrance barrier for labs who are interested in high-throughput variant calling applications on a large scale but lack the manpower and/or computational expertise.

Results
Here we present an easy-to-use, fully automated, computational pipeline (Automated Isoform Diversity Detector, AIDD) that contains open source tools for various tasks needed to map transcriptome diversity, including RNA editing events. To facilitate reproducibility and avoid system dependencies, the pipeline is contained within a pre-configured VirtualBox environment. The analytical tasks and format conversions are accomplished via a set of automated scripts that enable the user to go from a set of raw data, such as fastq files, to publication-ready results and figures in one step. A publicly available dataset of Zika virus-infected neural progenitor cells is used to illustrate AIDD’s capabilities.

Conclusions
AIDD pipeline offers a user-friendly interface for comprehensive and reproducible RNA-seq analyses. Among unique features of AIDD are its ability to infer RNA editing patterns, including ADAR editing, and inclusion of Guttman scale patterns for time series analysis of such editing landscapes. AIDD-based results show importance of diversity of ADAR isoforms, key RNA editing enzymes linked with the innate immune system and viral infections. These findings offer insights into the potential role of ADAR editing dysregulation in the disease mechanisms, including those of congenital Zika syndrome. Because of its automated all-inclusive features, AIDD pipeline enables even a novice user to easily explore common mechanisms of transcriptome diversity, including RNA editing landscapes.
Utilizing deep learning and graph mining to identify drug use on Twitter data
Authors: Tassone Joseph , Yan Peizhi , Simpson Mackenzie , Mendhe Chetan , Mago Vijay , Choudhury Salimur 
Published: December 2020

AbstractBackgroundThe collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of a collected set of Twitter data, a model will be developed for predicting positively referenced, drug-related tweets. From this, trends and correlations can be determined.MethodsSocial media data (tweets and attributes) were collected and processed using topic pertaining keywords, such as drug slang and use-conditions (methods of drug consumption). Potential candidates were preprocessed resulting in a dataset of 3,696,150 rows. The predictive classification power of multiple methods was compared including SVM, XGBoost, BERT and CNN-based classifiers. For the latter, a deep learning approach was implemented to screen and analyze the semantic meaning of the tweets.ResultsTo test the predictive capability of the model, SVM and XGBoost were first employed. The results calculated from the models respectively displayed an accuracy of 59.33% and 54.90%, with AUC’s of 0.87 and 0.71. The values show a low predictive capability with little discrimination. Conversely, the CNN-based classifiers presented a significant improvement, between the two models tested. The first was trained with 2661 manually labeled samples, while the other included synthetically generated tweets culminating in 12,142 samples. The accuracy scores were 76.35% and 82.31%, with an AUC of 0.90 and 0.91. Using association rule mining in conjunction with the CNN-based classifier showed a high likelihood for keywords such as “smoke”, “cocaine”, and “marijuana” triggering a drug-positive classification.ConclusionPredictive analysis with a CNN is promising, whereas attribute-based models presented little predictive capability and were not suitable for analyzing text of data. This research found that the commonly mentioned drugs had a level of correspondence with frequently used illicit substances, proving the practical usefulness of this system. Lastly, the synthetically generated set provided increased accuracy scores and improves the predictive capability.
Presence of the weak ferromagnetism in pure antiferromagnetic systems with octahedral structure: Effective field theory analysis
Authors: Jurčišinová E. , Jurčišin M. 
Published: December 2020

Abstract
The recently reported (Jurčišinová E. and Jurčišin M., J. Magn. & Magn. Mater., 513 (2020) 167085) possibility of the existence of the weak ferromagnetism with small but nonzero spontaneous magnetization in pure antiferromagnetic systems with the octahedral structure is confirmed using the six-site effective-field theory cluster approximation of the antiferromagnetic spin-

Ising model on the octahedral lattice. The sublattice magnetizations, the total spontaneous magnetization, as well as the Néel temperature of the model are found and compared to those obtained in the framework of the recursive lattice approach. The performed analysis allows one to conclude that the existence of the weak ferromagnetism in pure antiferromagnetic systems with the octahedral structure is directly related to their intrinsic geometry. The spontaneous magnetization and the Curie temperature of the ferromagnetic model are also determined and briefly discussed.
The Productivity J-Curve: How Intangibles Complement General Purpose Technologies
Authors: Brynjolfsson Erik , Rock Daniel , Syverson Chad 
Published: December 2020

General purpose technologies (GPTs) like AI enable and require significant complementary investments. These investments are often intangible and poorly measured in national accounts. We develop a model that shows how this can lead to underestimation of productivity growth in a new GPTs early years and, later, when the benefits of intangible investments are harvested, productivity growth overestimation. We call this phenomenon the Productivity J-curve. We apply our method to US data and find that adjusting for intangibles related to computer hardware and software yields a TFP level that is 15.9 percent higher than official measures by the end of 2017. (JEL E22, E23, G31, L63, L86)
Correlation of C-arm CT acquired parenchymal blood volume (PBV) with 99mTc-macroaggregated albumin (MAA) SPECT/CT for radioembolization work-up
Authors: Weissinger Matthias , Vogel Jonas , Kupferschläger Jürgen , Dittmann Helmut , Castaneda Vega Salvador Guillermo , Grosse Ulrich , Artzner Christoph , Nikolaou Konstantin , la Fougere Christian , Grözinger Gerd 
Published: December 2020

ObjectiveSPECT/CT with99mTc-macroaggregated albumin (MAA) is generally used for diagnostic work-up prior to transarterial radioembolization (TARE) to exclude shunts and to provide additional information for treatment stratification and dose calculation. C-arm CT is used for determination of lobular vascular supply and assessment of parenchymal blood volume (PBV). Aim of this study was to correlate MAA-uptake and PBV-maps in hepatocellular carcinoma (HCC) and hepatic metastases of the colorectal carcinoma (CRC).Materials and methods34 patients underwent a PBV C-arm CT immediately followed by99mTc-MAA injection and a SPECT/CT acquisition after 1 h uptake. MAA-uptake and PBV-maps were visually assessed and semi-quantitatively analyzed (MAA-tumor/liver-parenchyma = MAA-TBR or PBV in ml/100ml). In case of a poor match, tumors were additionally correlated with post-TARE90Y-Bremsstrahlung-SPECT/CT as a reference.Results102 HCC or CRC metastases were analyzed. HCC presented with significantly higher MAA-TBR (7.6 vs. 3.9, p<0.05) compared to CRC. Tumors showed strong intra- and inter-individual dissimilarities between TBR and PBV with a weak correlations for capsular HCCs (r = 0.45, p<0.05) and no correlation for CRC. The demarcation of lesions was slightly better for both HCC and CRC in PBV-maps compared to MAA-SPECT/CT (exact match: 52%/50%; same intensity/homogeneity: 38%/39%; insufficient 10%/11%). MAA-SPECT/CT revealed a better visual correlation with post-therapeutic90Y-Bremsstrahlung-SPECT/CT.ConclusionThe acquisition of PBV can improve the detectability of small intrahepatic tumors and correlates with the MAA-Uptake in HCC. The results indicate that99mTc-MAA-SPECT/CT remains to be the superior method for the prediction of post-therapeutic90Y-particle distribution, especially in CRC. However, intra-procedural PBV acquisition has the potential to become an additional factor for TARE planning, in addition to improving the determination of segment and tumor blood supply, which has been demonstrated previously.