bluuebunny/crossref_metadata_2025_split huggingface dataset:
Significance of mitochondrial fatty acid β-oxidation for the survivability of Aurantiochytrium limacinum ATCC MYA-1381 during sugar starvation
Authors: Nyunoya Hayato , Ishibashi Yohei , Ito Makoto , Okino Nozomu 
Published: August 2022

ABSTRACT
Thraustochytrids are marine protists that accumulate large amounts of palmitic acid and docosahexaenoic acid in lipid droplets. Random insertional mutagenesis was adopted for Aurantiochytrium limacinum ATCC MYA-1381 to search for genes that regulate lipid metabolism in thraustochytrids. A mutant strain, M17, was selected because of its significant decrease in myristic acid, palmitic acid, and triacylglycerol contents and cell growth defect. Genome analysis revealed that the gene encoding for mitochondrial electron-transfer flavoprotein ubiquinone oxidoreductase (ETFQO) was lacking in the M17 strain. This mutant strain exhibited a growth defect at the stationary phase, possibly due to stagnation of mitochondrial fatty acid β-oxidation and branched-chain amino acid degradation, both of which were caused by lack of ETFQO. This study shows the usability of random insertional mutagenesis to obtain mutants of lipid metabolism in A. limacinum and clarifies that ETFQO is integral for survival under sugar starvation in A. limacinum.
The impact of type 2 diabetes on long-term gastrointestinal sequelae after colorectal cancer surgery: national population-based study
Authors: Laurberg Tinne , Frandsen Sara , Larsen Helene M , Lehrskov Louise L , Graversen Susanne B , Drewes Asbjørn M , Emmertsen Katrine J , Krogh Klaus 
Published: August 2022

AbstractBackgroundLong-term gastrointestinal sequelae are common after colorectal cancer surgery, but the impact of type 2 diabetes (T2D) is unknown.MethodsIn a cross-sectional design, questionnaires regarding bowel function and quality of life (QoL) were sent to all Danish colorectal cancer survivors, who had undergone surgery between 2001 and 2014 and had more than 2 years follow-up without relapse. The prevalence of long-term gastrointestinal sequelae among colorectal cancer survivors with and without T2D were compared while stratifying for type of surgical resection and adjusting for age, sex, and time since surgery.ResultsA total of 8747 out of 14 488 colorectal cancer survivors answered the questionnaire (response rate 60 per cent), consisting of 3116 right-sided colonic, 2861 sigmoid, and 2770 rectal resections. Of these, 690 (7.9 per cent) had a diagnosis of T2D before surgery. Survivors with T2D following rectal resection had a 15 per cent (95 per cent c.i. 7.8 to 22) higher absolute risk of major low anterior resection syndrome, whereas survivors with T2D following right-sided and sigmoid resection had an 8 per cent higher risk of constipation (P &lt; 0.001) but otherwise nearly the same long-term risk of bowel symptoms as those without T2D. For all types of colorectal cancer resections, T2D was associated with a 6–10 per cent higher risk of severe pain (P &lt; 0.035) and a 4–8 per cent higher risk of impaired QoL.ConclusionT2D at time of surgery was associated with a higher risk of long-term bowel dysfunction after rectal resection, but not after colon resection excluding a higher risk of constipation. T2D was associated with a slightly higher frequency of severe pain and inferior QoL after both rectal and colonic cancer resection.
Retrieval of olfactory fear memory alters cell proliferation and expression of pCREB and pMAPK in the corticomedial amygdala and piriform cortex
Authors: Hakim Marziah , Beecher Kate , Jacques Angela , Chaaya Nicholas , Belmer Arnauld , Battle Andrew R , Johnson Luke R , Bartlett Selena E , Chehrehasa Fatemeh 
Published: August 2022

Abstract
The brain forms robust associations between odors and emotionally salient memories, making odors especially effective at triggering fearful or traumatic memories. Using Pavlovian olfactory fear conditioning (OFC), a variant of the traditional tone-shock paradigm, this study explored the changes involved in its processing. We assessed the expression of neuronal plasticity markers phosphorylated cyclic adenosine monophosphate response element binding protein (pCREB) and phosphorylated mitogen-activated protein kinase (pMAPK) 24 h and 14 days following OFC, in newborn neurons (EdU+) and in brain regions associated with olfactory memory processing; the olfactory bulb, piriform cortex, amygdale, and hippocampus. Here, we show that all proliferating neurons in the dentate gyrus of the hippocampus and glomerular layer of the olfactory bulb were colocalized with pCREB at 24 h and 14 days post-conditioning, and the number of proliferating neurons at both time points were statistically similar. This suggests the occurrence of long-term potentiation within the neurons of this pathway. Finally, OFC significantly increased the density of pCREB- and pMAPK-positive immunoreactive neurons in the medial and cortical subnuclei of the amygdala and the posterior piriform cortex, suggesting their key involvement in its processing. Together, our investigation identifies changes in neuroplasticity within critical neural circuits responsible for olfactory fear memory.
The Disproportionate Impact of Coronavirus Disease 2019 (COVID-19) Pandemic on Healthcare-Associated Infections in Community Hospitals: Need for Expanding the Infectious Disease Workforce
Authors: Advani Sonali D , Sickbert-Bennett Emily , Moehring Rebekah , Cromer Andrea , Lokhnygina Yuliya , Dodds-Ashley Elizabeth , Kalu Ibukunoluwa C , DiBiase Lauren , Weber David J , Anderson Deverick J ,   for the CDC Prevention Epicenters Program
Published: August 2022

Abstract

Background
The coronavirus disease 2019 (COVID-19) pandemic had a considerable impact on US healthcare systems, straining hospital resources, staff, and operations. However, a comprehensive assessment of the impact on healthcare-associated infections (HAIs) across different hospitals with varying level of infectious disease (ID) physician expertise, resources, and infrastructure is lacking.

Methods
This retrospective longitudinal multicenter cohort study included central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), Clostridioides difficile infections (CDIs), and ventilator-associated events (VAEs) from 53 hospitals (academic and community) in Southeastern United States from 1 January 2018 to 31 March 2021. Segmented negative binomial regression generalized estimating equations models estimated changes in monthly incidence rates in the baseline (01/2018–02/2020) compared to the pandemic period (03/2020–03/2021, further divided into three pandemic phases).

Results
CLABSIs and VAEs increased by 24% and 34%, respectively, during the pandemic period. VAEs increased in all phases of the pandemic, while CLABSIs increased in later phases of the pandemic. CDI trend increased by 4.2% per month in the pandemic period. On stratifying the analysis by hospital characteristics, the impact of the pandemic on healthcare-associated infections was more significant in smaller sized and community hospitals. CAUTIs did not change significantly during the pandemic across all hospital types.

Conclusions
CLABSIs, VAEs, and CDIs increased significantly during the pandemic, especially in smaller community hospitals, most of which lack ID physician expertise. Future efforts should focus on better understanding challenges faced by community hospitals, strengthening the infection prevention infrastructure, and expanding the ID workforce, particularly to community hospitals.
Task reformulation and data-centric approach for Twitter medication name extraction
Authors: Zhang Yu , Lee Jong Kang , Han Jen-Chieh , Tsai Richard Tzong-Han 
Published: August 2022

AbstractAutomatically extracting medication names from tweets is challenging in the real world. There are many tweets; however, only a small proportion mentions medications. Thus, datasets are usually highly imbalanced. Moreover, the length of tweets is very short, which makes it hard to recognize medication names from the limited context. This paper proposes a data-centric approach for extracting medications in the BioCreative VII Track 3 (Automatic Extraction of Medication Names in Tweets). Our approach formulates the sequence labeling problem as text entailment and question–answer tasks. As a result, without using the dictionary and ensemble method, our single model achieved a Strict F1 of 0.77 (the official baseline system is 0.758, and the average performance of participants is 0.696). Moreover, combining the dictionary filtering and ensemble method achieved a Strict F1 of 0.804 and had the highest performance for all participants. Furthermore, domain-specific and task-specific pretrained language models, as well as data-centric approaches, are proposed for further improvements.Database URL https://competitions.codalab.org/competitions/23925 and https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-3/
Asymmetric septal thickening is observed in hypertrophic cardiomyopathy mutation carriers without left ventricular hypertrophy: insights from AI analysis
Authors: Shiwani H , Hughes R K , Camaioni C , Augusto J B , Knott K , Rosmini S , Burke L , Pierce I , Moon J C , Davies R H 
Published: August 2022

Abstract

Funding Acknowledgements
Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Dr Hughes is supported by the British Heart Foundation (grant number FS/17/82/33222).

Background
Hypertrophic cardiomyopathy (HCM) is a common inherited cardiac disease characterised by left ventricular hypertrophy (LVH), often, with asymmetric septal thickening. Despite the prevalence of inherited mutations present in &gt;50% of cases, there is variable phenotypic expression in those with abnormal sarcomere protein genes. In individuals with abnormal genes but without LVH, we hypothesised that there is subtle asymmetric septal hypertrophy, detectable by the increased precision offered by an artificial intelligence (AI) tool for measuring wall thickness.

Purpose
We explored the septal-lateral ratio measured by AI in individuals with an identified genotype but no left ventricular hypertrophy as a component of sub-clinical HCM.

Methods
43 individuals with identified genotype, but no left ventricular hypertrophy (G+LVH-) and 97 age-, sex- and disease-matched controls underwent CMR. Patients were excluded if they had a maximum wall thickness (MWT) of ≥13mm. A clinically validated AI tool was used to measure the MWT, for each segment in the 16-segment AHA model. The septal-lateral ratio was calculated using the septal segment with the largest MWT and the lateral segment with the largest MWT.

Results
The mean septal-lateral ratio of the G+LVH- patients was 1.22 (SD 0.22) and the mean septal-lateral ratio of the matched controls was 1.14 (SD 0.15) with a statistically significant mean difference of 0.08 (p=0.01). There was no significant difference between the MWT of the G+LVH- patients at 10.3mm (SD 2.2) and healthy volunteers at 10.1mm (SD 1.8) (p = 0.61).

Conclusion
G+LVH- patients have a 7% increase in their septal-lateral ratio compared with age-matched controls despite the lack of difference in the MWT. Using increased precision offered by AI, early features of HCM can be observed in patients without overt LVH.
Fully automated machine learning-based selection of optimal bSSFP frequency offset for artifact reduction in cardiac MRI
Authors: Yoon S , Gadjimuradov F , Schmidt M , Wetzl J , Maier A 
Published: August 2022

Abstract

Funding Acknowledgements
Type of funding sources: Private company. Main funding source(s): Research Support from Siemens Healthineers GmbH.

Background
In bSSFP sequences commonly used for cardiac MRI, signal modulation (e.g. banding artifacts) due to B0 inhomogeneity is often observed, especially at higher field strengths. The spatial position of these artifacts can be shifted by a frequency offset to reduce artifacts in a region of interest (ROI), e.g. the heart. To this end, frequency scout (FS) scans are acquired to visually select the optimal frequency offset [1,2]. In this work, we propose a fully automated image-based system for selecting the optimal frequency offset on FS images based on machine learning.

Methods
The proposed prototype system consists of four main steps (Fig.1). First, a pre-trained deep-learning-based whole heart segmentation network is applied on a four chamber-view FS image to localize the ROI where artifacts should be reduced. Second, high frequency components within the ROI (for each frequency offset in the FS series) are extracted by successive processing of Fourier transformation, high-pass filtering, inverse Fourier transformation and subtraction over series. and N images with the lowest high-frequency content are selected. Third, an adaptive weighting map for each FS image is generated which penalizes signal deviations from a pixel-wise median that is calculated based on the selected images [3]. By averaging the maps and selecting the frame with maximum percentage, the optimal frequency offset is selected.
A total of 38 datasets, acquired on multiple clinical 3T MRI scanners (MAGNETOM Skyra, Vida, Prisma, Lumina; Siemens Healthcare, Erlangen, Germany), were used to evaluate the proposed system. All FS series were annotated manually and used to compare with the system output. The experts were allowed to select multiple possible optimal FS images within a FS series. In case of multiple annotations, the system output was labelled as correct when it selected one of the offsets chosen by the expert. Further, the generated weighting maps were visually evaluated.

Results
The proposed system achieved an accuracy of 92.1% compared to experts’ ground truth annotations. From the failed cases (n=3), the maximum difference was off by 2 frames. Based on the generated weighting maps, a reasonable decision on the selection of the optimal frequency offset is made. The algorithm successfully selects an FS image with minimized banding and flow artifacts within the ROI (Fig. 2a). Further, it reveals that the generated weighting map correctly suppress areas containing artifacts (Fig. 2b).

Conclusions
Initial results demonstrate the feasibility of the proposed system to automatically select the optimal frequency offset on FS scans. Therefore, it can improve the automation of a cardiac MRI workflow. An example of the result of each step
Surface wave dispersion inversion using an energy likelihood function
Authors: Zhang Xin , Zheng York , Curtis Andrew 
Published: August 2022

SUMMARY
Seismic surface wave dispersion inversion is used widely to study the subsurface structure of the Earth. The dispersion property is usually measured by using frequency–phase velocity (f–c) analysis of data recorded on a local array of receivers. The apparent phase velocity at each frequency of the surface waves travelling across the array is that at which the f–c spectrum has maximum amplitude. However, because of potential contamination by other wave arrivals or due to complexities in the velocity structure the f–c spectrum often has multiple maxima at each frequency for each mode. These introduce errors and ambiguity in the picked phase velocities, and consequently the estimated shear velocity structure can be biased, or may not account for the full uncertainty in the data. To overcome this issue we introduce a new method which directly uses the spectrum as the data to be inverted. We achieve this by solving the inverse problem in a Bayesian framework and define a new likelihood function, the energy likelihood function, which uses the spectrum energy to define data fit. We apply the new method to a land data set recorded by a dense receiver array, and compare the results to those obtained using the traditional method. The results show that the new method produces more accurate results since they better match independent data from refraction tomography. This real-data application also shows that it can be applied with relatively little adjustment to current practice since it uses standard f–c panels to define the likelihood, and efficiently since it removes the need to pick phase velocities. We therefore conclude that the energy likelihood function can be a valuable tool for surface wave dispersion inversion in practice.
Separating GIA signal from surface mass change using GPS and GRACE data
Authors: Vishwakarma Bramha Dutt , Ziegler Yann , Bamber Jonathan L , Royston Sam 
Published: August 2022

SUMMARY
The visco-elastic response of the solid Earth to the past glacial cycles and the present-day surface mass change (PDSMC) are detected by the geodetic observation systems such as global navigation satellite system and satellite gravimetry. Majority of the contemporary PDSMC is driven by climate change and in order to better understand them using the aforementioned geodetic observations, glacial isostatic adjustment (GIA) signal should be accounted first. The default approach is to use forward GIA models that use uncertain ice-load history and approximate Earth rheology to predict GIA, yielding large uncertainties. The proliferation of contemporary, global, geodetic observations and their coverage have therefore enabled estimation of data-driven GIA solutions. A novel framework is presented that uses geophysical relations between the vertical land motion (VLM) and geopotential anomaly due to GIA and PDSMC to express GPS VLM trends and GRACE geopotential trends as a function of either GIA or PDSMC, which can be easily solved using least-squares regression. The GIA estimates are data-driven and differ significantly from forward models over Alaska and Greenland.
Expression and subcellular localization ofUSH1C/harmonin in human retina provides insights into pathomechanisms and therapy
Authors: Nagel-Wolfrum Kerstin , Fadl Benjamin R , Becker Mirjana M , Wunderlich Kirsten A , Schäfer Jessica , Sturm Daniel , Fritze Jacques , Gür Burcu , Kaplan Lew , Andreani Tommaso , Goldmann Tobias , Brooks Matthew , Starostik Margaret R , Lokhande Anagha , Apel Melissa , Fath Karl R , Stingl Katarina , Kohl Susanne , DeAngelis Margaret M , Schlötzer-Schrehardt Ursula , Kim Ivana K , Owen Leah A , Vetter Jan M , Pfeiffer Norbert , Andrade-Navarro Miguel A , Grosche Antje , Swaroop Anand , Wolfrum Uwe 
Published: August 2022

AbstractUsher syndrome (USH) is the most common form of hereditary deaf-blindness in humans. USH is a complex genetic disorder, assigned to three clinical subtypes differing in onset, course and severity, with USH1 being the most severe. Rodent USH1 models do not reflect the ocular phenotype observed in human patients to date; hence, little is known about the pathophysiology of USH1 in the human eye. One of the USH1 genes, USH1C, exhibits extensive alternative splicing and encodes numerous harmonin protein isoforms that function as scaffolds for organizing the USH interactome. RNA-seq analysis of human retinae uncovered harmonin_a1 as the most abundant transcript of USH1C. Bulk RNA-seq analysis and immunoblotting showed abundant expression of harmonin in Müller glia cells (MGCs) and retinal neurons. Furthermore, harmonin was localized in the terminal endfeet and apical microvilli of MGCs, presynaptic region (pedicle) of cones and outer segments (OS) of rods as well as at adhesive junctions between MGCs and photoreceptor cells (PRCs) in the outer limiting membrane (OLM). Our data provide evidence for the interaction of harmonin with OLM molecules in PRCs and MGCs and rhodopsin in PRCs. Subcellular expression and colocalization of harmonin correlate with the clinical phenotype observed in USH1C patients. We also demonstrate that primary cilia defects in USH1C patient-derived fibroblasts could be reverted by the delivery of harmonin_a1 transcript isoform. Our studies thus provide novel insights into PRC cell biology, USH1C pathophysiology and development of gene therapy treatment(s).
Investment Funds, Monetary Policy, and the Global Financial Cycle
Authors: Kaufmann Christoph 
Published: August 2022

AbstractThis paper examines the role of international investment funds in the transmission of global financial conditions to the euro area using structural Bayesian vector auto regressions. While cross-border banking sector capital flows receded significantly in the aftermath of the global financial crisis, portfolio flows from investors actively searching for yield on financial markets worldwide gained importance during the post-crisis “second phase of global liquidity”. The analysis presented in this paper shows that a loosening of US monetary policy leads to higher investment fund inflows to equities and debt globally. Focussing on the euro area, these inflows not only imply elevated asset prices but also coincide with increased debt and equity issuance. The findings demonstrate the growing importance of non-bank financial intermediation over the past decade and hold important policy implications for monetary and financial stability.
Firms and Collective Reputation: a Study of the Volkswagen Emissions Scandal
Authors: Bachmann Rüdiger , Ehrlich Gabriel , Fan Ying , Ruzic Dimitrije , Leard Benjamin 
Published: August 2022

AbstractThis paper uses the 2015 Volkswagen (VW) emissions scandal as a natural experiment to provide evidence that collective reputation externalities are economically significant. Using a combination of difference-in-differences and demand estimation approaches, we document a spillover effect from the scandal to the non-VW German auto manufacturers. The spillover amounts to an average drop of $2,057 in consumer valuations of these manufacturers’ vehicles and a 34.6% reduction in their annual sales. We substantiate our interpretation that the estimates reflect a reputation spillover using data on internet search behavior and direct measures of consumer sentiment from Twitter.