bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bone mineral density in women with deep infiltrating endometriosis who have undergone early bilateral oophorectomy
Authors: Gosset Anna , Escanes Claire , Pouilles Jean-Michel , Vidal Fabien , Tanguy Le Gac Yann , Plu-Bureau Geneviève , Trémollieres Florence A. 
Published: November 2020

Abstract

Objective:
To study bone mineral density (BMD) in women with and without pelvic deep infiltrating endometriosis (DIE) who underwent early bilateral oophorectomy (BO).

Methods:
A case-control study was performed in 83 women who underwent early BO before the age of 45 years, 31 for DIE and 52 for another clinical condition. All the women answered a standardized computer-assisted questionnaire to record their clinical and historical data and were medically examined. Lumbar spine and femoral neck BMDs were measured by dual-energy X-ray absorptiometry after early BO. Simultaneously, serum calcium, intact parathyroid, 25-hydroxyvitamin D, and cross-linked C-telopeptide were also measured. Unadjusted and adjusted odds ratios (with 95% confidence intervals [CI]) for endometriosis were calculated using logistic regression.

Results:
The mean lumbar spine and femoral neck BMDs were significantly higher in women who underwent early BO for DIE than in those who underwent early BO for another clinical condition. After adjusting for age at BMD measurement, years since menopause, age at menarche and body mass index, odds ratio for endometriosis associated with a 1-SD increase in lumbar spine and femoral neck BMD was 2.59 (95% CI: 1.45-4.62) and 2.16 (95% CI: 1.23-3.81), respectively.

Conclusion:
Higher lumbar spine and femoral neck BMDs are associated with an increase in the likelihood of pelvic DIE in women who underwent early BO. This might be expected to the extent that endometriosis is itself associated with enhanced estrogen status, although further studies are needed to confirm such a hypothesis. These findings suggest that BMD measurement could contribute to the hormonal management of surgical menopause in women with DIE.
Military transgender care
Authors: Seibert Diane C. , Keller Nathan , Zapor Logan , Archer Holly 
Published: November 2020

ABSTRACT
Transgender individuals have a long-standing history of honorable service in the United States Military. However, politics have had an impact on their ability to openly serve in uniform as policies continually change rapidly with each new administration. This article describes the shifting political landscape of policies related to whether (or not) transgender individuals can serve in the military, and how this has affected the health care experiences of transgender individuals and the ability for nurse practitioners to provide quality health care to the transgender population serving on active duty.
Barotraumatic Blow-out Fracture of the Medial Orbital Wall by Nose Blowing
Authors: Kim Dong Hwi , Kim Na Rim , Ko Hyo Sun , Lee Jung Ho 
Published: November 2020

Abstract
Blow-out fracture is one of the most common facial bone fractures and mainly caused by blunt trauma, whereas barotraumatic causes are relatively rare. In this report, we present the case of a patient with an orbital medial wall blow out fracture caused by nose blowing. This case is unique in that the barotraumatic blow out fracture occurred in a patient without previous known risk factors, except that she had previously been operated on for orbital floor blow-out fracture. It is possible that barotraumatic orbital medial wall fracture occurred due to postoperative changes in the aerodynamics or shock-absorbing capacity of the paranasal sinuses. To prevent barotraumatic trauma in the orbital wall, patients undergoing surgery for orbital fractures should consider avoiding excessive nose blowing not only in the weeks after surgery, but for a sufficient period of time.
Botulinum Toxin Type-A for Lip Augmentation: “Lip Flip”
Authors: Teixeira Jeffrey C. , Ostrom Jonnae Y. , Hohman Marc H. , Nuara Michael J. 
Published: November 2020

Abstract
Over the last 10 years there has been an explosion in the number of minimally invasive procedures that patients undertake with increasing uses of botulinum neurotoxin type A for off label indications. One area of expansion over the past several years is the “Lip Flip” which involves injection of botulinum neurotoxin type A along the vermillion border to improve lip contour, eversion and fullness. While techniques and results for “gummy smile” and perioral vertical rhytids have been previously reported, minimal literature exists on this new trend, including whether such increased interest truly exists. Therefore, the authors aim to explore whether there is a rising trend regarding “lip flip” and report on clinical results from patients treated in our practice.
An Explainable Multi-Modal Neural Network Architecture for Predicting Epilepsy Comorbidities Based on Administrative Claims Data
Authors: Linden Thomas , de Jong Johann , Lu Chao , Kiri Victor , Haeffs Kathrin , Fröhlich Holger 
Published: November 2020

1AbstractEpilepsy is a complex brain disorder characterized by repetitive seizure events. Epilepsy patients often suffer from various and severe physical and psychological co-morbidities (e.g. anxiety, migraine, stroke, etc.). While general comorbidity prevalences and incidences can be estimated from epidemiological data, such an approach does not take into account that actual patient specific risks can depend on various individual factors, including medication. This motivates to develop a machine learning approach for predicting risks of future comorbidities for the individual epilepsy patient.In this work we use inpatient and outpatient administrative health claims data of around 19,500 US epilepsy patients. We suggest a dedicated multi-modal neural network architecture (Deep personalized LOngitudinal convolutional RIsk model - DeepLORI) to predict the time dependent risk of six common comorbidities of epilepsy patients. We demonstrate superior performance of DeepLORI in a comparison with several existing methods Moreover, we show that DeepLORI based predictions can be interpreted on the level of individual patients. Using a game theoretic approach, we identify relevant features in DeepLORI models and demonstrate that model predictions are explainable in the light of existing knowledge about the disease. Finally, we validate the model on independent data from around 97,000 patients, showing good generalization and stable prediction performance over time.
Identifying Cross-Cancer Similar Patients via a Semi-Supervised Deep Clustering Approach
Authors: Ay Duygu , Tastan Oznur 
Published: November 2020

AbstractThe treatment decisions for a cancer patient are typically based on the patient’s diagnosed cancer type. With the characterization of cancer tumors at the molecular level, there have been reports of patients being similar despite being diagnosed with different cancer types. Motivated from these observations, we aim at discoveringcross-cancerpatients, which we define as patients whose tumors are more similar to patient tumors diagnosed with another cancer type. We develop DeepCrossCancer to identify cross-cancer patients that always co-cluster with the other patient from another cancer type. The input to DeepCrossCancer is the transcriptomic profiles of the patient tumors, the age, and sex of the patient. To solve the clustering problem, we use a semi-supervised deep learning-based clustering method in which the clustering task is supervised by cancer type labels and the survival times of the patients. Applying the method to patient data from nine different cancers, we discover 20 cross-cancer patients that consistently co-cluster. By analyzing the predictive genes of the cross-cancer patients and other genomic information available for the patient such as somatic mutations and copy number variations, we identify striking genomic similarities across these patients providing support. The detection of cross-cancer patients opens up possibilities for transferring clinical decisions across patients at a single patient level. The source code is available atgithub.com/tastanlab/DeepCrossCancer
Vasopressin acts as a synapse organizer in limbic regions by boosting PSD95 and GluA1 expression
Authors: Zhang Limei , Padilla-Flores Teresa , Hernández Vito S. , Zetter Mario A. , Campos-Lira Elba , Escobar Laura I. , Millar Robert P. , Eiden Lee E. 
Published: November 2020

AbstractHypothalamic arginine vasopressin (AVP)-containing magnocellular neurosecretory neurons (AVPMNN) emit collaterals to synaptically innervate limbic regions influencing learning, motivational behaviour, and fear responses. Here, we characterize the dynamics of expression changes of two key determinants for synaptic strength, the postsynaptic density (PSD) proteins AMPAR subunit GluA1 and PSD scaffolding protein 95 (PSD95), in response toin vivomanipulations of AVPMNN neuronal activation state, or exposure to exogenous AVPex vivo. Both long term water deprivationin vivo, which powerfully upregulates AVPMNN metabolic activity, and exogenous AVP applicationex vivo, in brain slices, significantly increased GluA1 and PSD95 expression measured by western blot, in brain regions reportedly receiving direct ascending innervations from AVPMNN (i.e., ventral hippocampus, amygdala and lateral habenula). In contrast, the visual cortex, a region not observed to receive AVPMNN projections, showed no such changes. Ex vivo application of V1a and V1b antagonists to ventral hippocampal slices ablated the AVP stimulated increase in postsynaptic protein expression measured by western blot. Using a modified expansion microscopy technique, we were able to quantitatively assess the significant augmentation of PSD95 and GLUA1 densities in subcellular compartments inlocus coeruleus’ tyrosine hydroxylase immunopositive fibres, adjacent to AVP axon terminals. Our data strongly suggest that the AVPMNN ascending system plays a role in the regulation of the excitability of targeted neuronal circuits through upregulation of key post-synaptic density proteins corresponding to excitatory synapse.Supported by grantsUNAM-DGAPA-PAPIIT-IN200121 & CONACYT-CB-238744 (LZ); CONACYT A1-S-8731 (LIE); MH002386, NIMH, NIH, USA (LEE)
Comparative analysis of the clinical presentations, cardiovascular and laboratory findings and treatment of heart failure with preserved and reduced ejection fractions in Cameroon: a multicenter cross-sectional study
Authors: Boombhi Jérôme , Bele Antoin , Temgoua Mazou N , Hamadou Ba , Tochie Joel Noutakdie , Tchapmi Donald , Nganou Chris-Nadège , Mfeukeu-Kuaté Liliane , Menanga Alain , Kingue Samuel 
Published: November 2020

AbstractBackgroundContrarily to past concepts, heart failure with preserved ejection fraction (HFpEF) has become more prevalent than heart failure with reduced ejection fraction (HFrEF). Our objective was to study the clinical, cardiovascular and laboratory findings and therapeutic aspects of HFpEF, compared with those of HFrEF in Yaounde, Cameroon.MethodThis was an analytical cross-sectional study carried-out at the Central Hospital, General Hospital and Military Hospital of Yaounde, from January to April 2018 (4 months). 201 patients aged at least 18 years old with an echocardiography confirmed diagnosis of heart failure were been enrolled. We excluded 12 patients because they had a congenital ventricular septal defect (2), chronic cor pulmonale (4), mitral stenosis (5), and pericarditis (1).ResultsWe found that 45.5% of our patients had HFpEF whereas 37.5% had HFrEF. Patients with HFpEF were older and had a significantly higher incidence of hypertension and obesity. HFrEF was significantly more associated with congestive symptoms than HFpEF. The S3 gallop was significantly more present in patients with HFrEF. Patients with HfpEF had significantly higher rate of atrial fibrillation. Furosemide, spironolactone and digoxin were significantly used more frequently in patients with HFrEF.ConclusionHFpEF is the most frequent form of heart failure in the hospital setting in Yaoundé, Cameroon. Patients with HFpEF were significantly older and more affected by hypertension and obesity than those with HFrEF. Cardiac ultrasound is indispensable to differentiate between the two entities for better management.
Alternative splicing liberates a cryptic cytoplasmic isoform of mitochondrial MECR that antagonizes influenza virus
Authors: Baker Steven F. , Meistermann Helene , Tzouros Manuel , Baker Aaron , Golling Sabrina , Polster Juliane Siebourg , Ledwith Mitchell P. , Gitter Anthony , Augustin Angelique , Javanbakht Hassan , Mehle Andrew 
Published: November 2020

AbstractViruses must balance their reliance on host cell machinery for replication while avoiding host defense. Influenza A viruses are zoonotic agents that frequently switch hosts, causing localized outbreaks with the potential for larger pandemics. The host range of influenza virus is limited by the need for successful interactions between the virus and cellular partners. Here we used immuno-competitive capture-mass spectrometry to identify cellular proteins that interact with human- and avian-style viral polymerases. We focused on the pro-viral activity of heterogenous nuclear ribonuclear protein U-like 1 (hnRNP UL1) and the anti-viral activity of mitochondrial enoyl CoA-reductase (MECR). MECR is localized to mitochondria where it functions in mitochondrial fatty acid synthesis (mtFAS). While a small fraction of the polymerase subunit PB2 localizes to the mitochondria, PB2 did not interact with full-length MECR. By contrast, a minor splice variant produces cytoplasmic MECR (cMECR) that interacts with PB2. cMECR binds the viral polymerase and suppresses viral replication by blocking assembly of viral ribonucleoprotein complexes (RNPs). MECR ablation through genome editing or drug treatment is detrimental for cell health, creating a generic block to virus replication. Using the yeast homolog Etr1 to supply the metabolic functions of MECR in MECR-null cells, we showed that specific antiviral activity is independent of mtFAS and lies solely within cMECR. Thus, alternative splicing produces a cryptic antiviral protein that is embedded within a key metabolic enzyme.
Age-dependent increase in α-tocopherol and phytosterols in maize leaves exposed to elevated ozone pollution
Authors: Wedow Jessica M. , Burroughs Charles H. , Rios Acosta Lorena , Leakey Andrew D.B. , Ainsworth Elizabeth A. 
Published: November 2020

AbstractTropospheric ozone is a major air pollutant that significantly damages crop production around the world. Crop metabolic responses to rising chronic ozone stress have not been well-studied in the field, especially in C4crops. In this study, we investigated the metabolomic profile of leaves from two diverse maize (Zea mays) inbred lines and the hybrid cross during exposure to season-long elevated ozone (~100 nL L−1) in the field using free air concentration enrichment (FACE) to identify key biochemical responses of maize to elevated ozone. Senescence, measured by loss of chlorophyll content, was accelerated in the hybrid line, B73 x Mo17, but not in either inbred line (B73 or Mo17). Untargeted metabolomic profiling further revealed that inbred and hybrid lines of maize differed in metabolic responses to ozone. A significant difference in the metabolite profile of hybrid leaves exposed to elevated ozone occurred as leaves aged, but no age-dependent difference in leaf metabolite profiles between ozone conditions was measured in the inbred lines. Phytosterols and α-tocopherol levels increased in B73 x Mo17 leaves as they aged, and to a significantly greater degree in elevated ozone stress. These metabolites are involved in membrane stabilization and chloroplast reactive oxygen species (ROS) quenching. The hybrid line also showed significant yield loss at elevated ozone, which the inbred lines did not. This suggests that the hybrid maize line was more sensitive to ozone exposure than the inbred lines, and up-regulated metabolic pathways to stabilize membranes and quench ROS in response to chronic ozone stress.
An integrative analysis of genomic and exposomic data for complex traits and phenotypic prediction
Authors: Zhou Xuan , Lee S. Hong 
Published: November 2020

AbstractComplementary to the genome, the concept of exposome has been proposed to capture the totality of human environmental exposures. While there has been some recent progress on the construction of the exposome, few tools exist that can integrate the genome and exposome for complex trait analyses. Here we propose a linear mixed model approach to bridge this gap, which jointly models the random effects of the two omics layers on phenotypes of complex traits. We illustrate our approach using traits from the UK Biobank (e.g., BMI & height for N ∼ 35,000) with a small fraction of the exposome that comprises 28 lifestyle factors. The joint model of the genome and exposome explains substantially more phenotypic variance and significantly improves phenotypic prediction accuracy, compared to the model based on the genome alone. The additional phenotypic variance captured by the exposome includes its additive effects as well as non-additive effects such as genome-exposome (gxe) and exposome-exposome (exe) interactions. For example, 19% of variation in BMI is explained by additive effects of the genome, while additional 7.2% by additive effects of the exposome, 1.9% by exe interactions and 4.5% by gxe interactions. Correspondingly, the prediction accuracy for BMI, computed using Pearson’s correlation between the observed and predicted phenotypes, improves from 0.15 (based on the genome alone) to 0.35 (based on the genome & exposome). We also show, using established theories, integrating genomic and exposomic data is essential to attaining a clinically meaningful level of prediction accuracy for disease traits. In conclusion, the genomic and exposomic effects can contribute to phenotypic variation via their latent relationships, i.e. genome-exposome correlation, and gxe and exe interactions, and modelling these effects has a great potential to improve phenotypic prediction accuracy and thus holds a great promise for future clinical practice.
Evaluating urban greening scenarios for urban heat mitigation: a spatially-explicit approach
Authors: Bosch Martí , Locatelli Maxence , Hamel Perrine , Jaligot Rémi , Chenal Jérôme , Joost Stéphane 
Published: November 2020

AbstractUrban green infrastructure, especially trees, are widely regarded as one of the most effective ways to reducing urban temperatures in extreme heat events, and alleviate its adverse impacts on human health and well-being. Nevertheless, urban planners and decision-makers are still lacking methods and tools to spatially evaluate the cooling effects of urban green spaces and exploit them to assess greening strategies at the urban agglomeration scale. This article introduces a novel spatially-explicit approach to simulate urban greening scenarios by increasing the tree canopy cover in the existing urban fabric, and evaluating their heat mitigation potential. The latter is achieved by applying the InVEST urban cooling model to the synthetic land use/land cover maps generated for the greening scenarios. A case study in the urban agglomeration of Lausanne, Switzerland, illustrates the development of tree canopy scenarios following distinct spatial distribution strategies. The spatial pattern of the tree canopy strongly influences the human exposure to the highest temperatures, and small increases in the abundance of tree canopy cover with the appropriate spatial configuration can have major impacts on human health and well-being. The proposed approach supports urban planning and the design of nature-based solutions to enhance climate resilience.
Predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning
Authors: Quadir Farhan , Roy Raj , Halfmann Randal , Cheng Jianlin 
Published: November 2020

AbstractDeep learning methods that achieved great success in predictingintrachainresidue-residue contacts have been applied to predictinterchaincontacts between proteins. However, these methods require multiple sequence alignments (MSAs) of a pair of interacting proteins (dimers) as input, which are often difficult to obtain because there are not many known protein complexes available to generate MSAs of sufficient depth for a pair of proteins. In recognizing that multiple sequence alignments of a monomer that forms homomultimers contain the co-evolutionary signals of both intrachain and interchain residue pairs in contact, we applied DNCON2 (a deep learning-based protein intrachain residue-residue contact predictor) to predict both intrachain and interchain contacts for homomultimers using multiple sequence alignment (MSA) and other co-evolutionary features of a single monomer followed by discrimination of interchain and intrachain contacts according to the tertiary structure of the monomer. Allowing true-positive predictions within two residue shifts, the best average precision was obtained for the Top-L/10 predictions of DNCON2: 22.9% for homodimers, and 17.0% for higher order homomultimers. In some instances, especially where interchain contact densities are high, the approach predicted interchain contacts with 100% precision. We show that the predicted contacts can be used to accurately construct the structure of some complexes. Our experiment demonstrates that monomeric multiple sequence alignments can be used with deep learning to predict interchain contacts of homomeric proteins.
Characterization of theCannabis sativaglandular trichome proteome
Authors: Conneely Lee J. , Mauleon Ramil , Mieog Jos , Barkla Bronwyn J. , Kretzschmar Tobias 
Published: November 2020

AbstractCannabis sativahas been cultivated since antiquity as a source of fibre, food and medicine. The recent resurgence ofCannabisas a cash crop is mainly driven by the medicinal and therapeutic properties of its resin, which contains compounds that interact with the human endocannabinoid system. Compared to other medicinal crops of similar value, however, little is known about the biology ofC. sativa. Glandular trichomes are small hair-like projections made up of stalk and head tissue and are responsible for the production of the resin inC. sativa.Trichome productivity, as determined byCannabis sativaresin yield and composition, is only beginning to be understood at the molecular level. In this study the proteomes of glandular trichome stalks and heads, were investigated and compared to the proteome of the whole flower tissue, to help elucidateCannabis sativaglandular trichome biochemistry. The data suggested that the floral tissue acts as a major source of carbon and energy to the glandular trichome head sink tissue, supplying sugars which drive secondary metabolite biosynthesis in the glandular trichome head; the location of the secretory cells. The trichome stalk seems to play only a limited role in secondary metabolism and acts as both source and sink.