bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pore‐Scale MultiResolution Rock‐Typing of Layered Sandstones via Minkowski Maps
Authors: Jiang Han , Arns C. H. 
Published: February 2021

AbstractA challenge in utilizing pore‐scale information in subsurface transport calculations is the small field‐of‐view of tomographic imaging methods resolving pore‐scale features. While low‐resolution tomography provides a larger field‐of‐view, critical connectivity information may not be resolved, or lost in the upscaling process. In this study, we present a multiscale upscaling approach utilizing regional morphological measures—Minkowski maps—at two different resolutions. The workflow consists of the definition of high‐resolution rock‐types and their characterization, followed by an image registration process to lower resolution tomograms, a projection of the high‐resolution rock‐types to low‐resolution Minkowski maps via support vector machines, and application of high‐resolution transport characteristics to the low‐resolution rock‐types, followed by upscaling. The method is applied to a complex thinly laminated reservoir sandstone. Upscaled permeability and electrical conductivity agree well with full‐resolution calculations.
ZRSR2 overexpression is a frequent and early event in castration-resistant prostate cancer development
Authors: He Haiqing , Hao Jun , Dong Xin , Wang Yu , Xue Hui , Qu Sifeng , Choi Stephen Yiu Chuen , Ci Xinpei , Wang Yong , Wu Rebecca , Shi Mingchen , Zhao Xiaokun , Collins Colin , Lin Dong , Wang Yuzhuo 
Published: February 2021

Abstract
Background
Androgen deprivation therapy (ADT) remains the leading systemic therapy for locally advanced and metastatic prostate cancers (PCa). While a majority of PCa patients initially respond to ADT, the durability of response is variable and most patients will eventually develop incurable castration-resistant prostate cancer (CRPC). Our research objective is to identify potential early driver genes responsible for CRPC development.

Methods
We have developed a unique panel of hormone-naïve PCa (HNPC) patient-derived xenograft (PDX) models at the Living Tumor Laboratory. The PDXs provide a unique platform for driver gene discovery as they allow for the analysis of differentially expressed genes via transcriptomic profiling at various time points after mouse host castration. In the present study, we focused on genes with expression changes shortly after castration but before CRPC has fully developed. These are likely to be potential early drivers of CRPC development. Such genes were further validated for their clinical relevance using data from PCa patient databases. ZRSR2 was identified as a top gene candidate and selected for further functional studies.

Results
ZRSR2 is significantly upregulated in our PDX models during the early phases of CRPC development after mouse host castration and remains consistently high in fully developed CRPC PDX models. Moreover, high ZRSR2 expression is also observed in clinical CRPC samples. Importantly, elevated ZRSR2 in PCa samples is correlated with poor patient treatment outcomes. ZRSR2 knockdown reduced PCa cell proliferation and delayed cell cycle progression at least partially through inhibition of the Cyclin D1 (CCND1) pathway.

Conclusion
Using our unique HNPC PDX models that develop into CRPC after host castration, we identified ZRSR2 as a potential early driver of CRPC development.
Symbiotic bacteria mediate volatile chemical signal synthesis in a large solitary mammal species
Authors: Zhou Wenliang , Qi Dunwu , Swaisgood Ronald R , Wang Le , Jin Yipeng , Wu Qi , Wei Fuwen , Nie Yonggang 
Published: February 2021

Abstract
Mammalian chemosignals—or scent marks—are characterized by astounding chemical diversity, reflecting both complex biochemical pathways that produce them and rich information exchange with conspecifics. The microbiome of scent glands was thought to play prominent role in the chemical signal synthesis, with diverse microbiota metabolizing glandular products to produce odorants that may be used as chemosignals. Here, we use gas chromatography–mass spectrometry and metagenomic shotgun sequencing to explore this phenomenon in the anogenital gland secretions (AGS) of the giant panda (Ailuropoda melanoleuca). We find that this gland contains a diverse community of fermentative bacteria with enzymes that support metabolic pathways (e.g., lipid degradation) for the productions of volatile odorants specialized for chemical communication. We found quantitative and qualitative differences in the microbiota between AGS and digestive tract, a finding which was mirrored by differences among chemical compounds that could be used for olfactory communication. Volatile chemical compounds were more diverse and abundant in AGS than fecal samples, and our evidence suggests that metabolic pathways have been specialized for the synthesis of chemosignals for communication. The panda’s microbiome is rich with genes coding for enzymes that participate in the fermentation pathways producing chemical compounds commonly deployed in mammalian chemosignals. These findings illuminate the poorly understood phenomena involved in the role of symbiotic bacteria in the production of chemosignals.
StressNet - Deep learning to predict stress with fracture propagation in brittle materials
Authors: Wang Yinan , Oyen Diane , Guo Weihong , Mehta Anishi , Scott Cory Braker , Panda Nishant , Fernández-Godino M. Giselle , Srinivasan Gowri , Yue Xiaowei 
Published: February 2021

AbstractCatastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal stress is critical to predicting time to failure and improving the fracture resistance and reliability of materials. Existing high-fidelity methods, such as the Finite-Discrete Element Model (FDEM), are limited by their high computational cost. Therefore, to reduce computational cost while preserving accuracy, a deep learning model, StressNet, is proposed to predict the entire sequence of maximum internal stress based on fracture propagation and the initial stress data. More specifically, the Temporal Independent Convolutional Neural Network (TI-CNN) is designed to capture the spatial features of fractures like fracture path and spall regions, and the Bidirectional Long Short-term Memory (Bi-LSTM) Network is adapted to capture the temporal features. By fusing these features, the evolution in time of the maximum internal stress can be accurately predicted. Moreover, an adaptive loss function is designed by dynamically integrating the Mean Squared Error (MSE) and the Mean Absolute Percentage Error (MAPE), to reflect the fluctuations in maximum internal stress. After training, the proposed model is able to compute accurate multi-step predictions of maximum internal stress in approximately 20 seconds, as compared to the FDEM run time of 4 h, with an average MAPE of 2% relative to test data.
Unprotected sidewalls of implantable silicon-based neural probes and conformal coating as a solution
Authors: Ghelich Pejman , Nolta Nicholas F. , Han Martin 
Published: February 2021

AbstractSilicon-based implantable neural devices have great translational potential as a means to deliver various treatments for neurological disorders. However, they are currently held back by uncertain longevity following chronic exposure to body fluids. Conventional deposition techniques cover only the horizontal surfaces which contain active electronics, electrode sites, and conducting traces. As a result, a vast majority of today’s silicon devices leave their vertical sidewalls exposed without protection. In this work, we investigated two batch-process silicon dioxide deposition methods separately and in combination: atomic layer deposition and inductively-coupled plasma chemical vapor deposition. We then utilized a rapid soak test involving potassium hydroxide to evaluate the coverage quality of each protection strategy. Focused ion beam cross sectioning, scanning electron microscopy, and 3D extrapolation enabled us to characterize and quantify the effectiveness of the deposition methods. Results showed that bare silicon sidewalls suffered the most dissolution whereas ALD silicon dioxide provided the best protection, demonstrating its effectiveness as a promising batch process technique to mitigate silicon sidewall corrosion in chronic applications.
Small molecule inhibitor of OGG1 blocks oxidative DNA damage repair at telomeres and potentiates methotrexate anticancer effects
Authors: Baquero Juan Miguel , Benítez-Buelga Carlos , Rajagopal Varshni , Zhenjun Zhao , Torres-Ruiz Raúl , Müller Sarah , Hanna Bishoy M. F. , Loseva Olga , Wallner Olov , Michel Maurice , Rodríguez-Perales Sandra , Gad Helge , Visnes Torkild , Helleday Thomas , Benítez Javier , Osorio Ana 
Published: February 2021

AbstractThe most common oxidative DNA lesion is 8-oxoguanine which is mainly recognized and excised by the 8-oxoG DNA glycosylase 1 (OGG1), initiating the base excision repair (BER) pathway. Telomeres are particularly sensitive to oxidative stress (OS) which disrupts telomere homeostasis triggering genome instability. In the present study, we have investigated the effects of inactivating BER in OS conditions, by using a specific inhibitor of OGG1 (TH5487). We have found that in OS conditions, TH5487 blocks BER initiation at telomeres causing an accumulation of oxidized bases, that is correlated with telomere losses, micronuclei formation and mild proliferation defects. Moreover, the antimetabolite methotrexate synergizes with TH5487 through induction of intracellular reactive oxygen species (ROS) formation, which potentiates TH5487-mediated telomere and genome instability. Our findings demonstrate that OGG1 is required to protect telomeres from OS and present OGG1 inhibitors as a tool to induce oxidative DNA damage at telomeres, with the potential for developing new combination therapies for cancer treatment.
Prevalence of obesity and an interrogation of the correlation between anthropometric indices and blood pressures in urban Lagos, Nigeria
Authors: Adegoke Oluseyi , Ozoh Obianuju B. , Odeniyi Ifedayo A. , Bello Babawale T. , Akinkugbe Ayesha O. , Ojo Oluwadamilola O. , Agabi Osigwe P. , Okubadejo Njideka U. 
Published: February 2021

AbstractAdverse cardiovascular outcomes are linked to higher burden of obesity and hypertension. We conducted a secondary analysis of data for 5135 participants aged ≥ 16 years from our community-based hypertension prevalence study to determine the prevalence of obesity and association between multiple anthropometric indices and blood pressure (BP). The indices were waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), a body shape index(ABSI), abdominal volume index (AVI), body adiposity index (BAI), body roundness index (BRI), visceral adiposity index (VAI) and conicity index (CI). We performed statistical analyses to determine the association, predictive ability, cutoff values and independent determinants of hypertension. Crude prevalence of obesity was 136 per 1000 (95% confidence interval 126–146). BMI had the strongest correlation with systolic and diastolic BP (rs = 0.260 and 0.264, respectively). Indices of central adiposity (AVI, WC, WHtR, BRI) were the strongest predictors of hypertension (≥ 140/90 mmHg), and their cut-off values were generally higher in females than males. WHR, age, BMI and CI were independent determinants of hypertension ≥ 140 mmHg (p < 0.05). We conclude that, based on this novel study, measures of central adiposity are the strongest predictors and independent determinants of hypertension in our population, and cut-off values vary from previously recommended standards.
Origami paper analytical assay based on metal complex sensor for rapid determination of blood cyanide concentration in fire survivors
Authors: Sheini Azarmidokht , Aseman Marzieh Dadkhah , Bordbar Mohammad Mahdi 
Published: February 2021

AbstractCyanide-based blood poisoning can seriously damage fire victims and cause death if not detected quickly. Previous conventional methods require laboratory equipment, which are expensive and increase the duration of the analysis. Here, a simple origami based microfluidic device was introduced for point of need detection of blood cyanide concentration in people involved in fire. The device is made of four layers of paper. Each layer was in the size of 1 × 1 cm folded on each other. In this work, the blood sample was acidified by trichloroacetic acid to separate cyanide from methaemoglobin in the form of HCN gas. The produced gas released into borate buffer to recover free cyanide ions which interacted with the Pt complex ([Pt(p-MeC6H4)2(phen)]) used as a receptor in this study. Optimized conditions were applied to have a suitable interaction causing the color of the receptor to change from yellow to colorless. The color changes were recorded by a smartphone, and the sensor response was calculated by the routine image analysis software. The assay was capable of determining cyanide ions at different concentrations in the range of 1.0 to 100.0 µmol L−1. The detection limit of these determination was equal to 0.4 µmol L−1. The assay responses were not affected by the interfering species. As a practical analysis, the proposed sensor was applied to determine cyanide ions in the blood sample of 20 studied fire survivors and 10 controls with high accuracy.
Doppler imaging detects bacterial infection of living tissue
Authors: Choi Honggu , Li Zhe , Hua Zhen , Zuponcic Jessica , Ximenes Eduardo , Turek John J. , Ladisch Michael R. , Nolte David D. 
Published: February 2021

AbstractLiving 3D in vitro tissue cultures, grown from immortalized cell lines, act as living sentinels as pathogenic bacteria invade the tissue. The infection is reported through changes in the intracellular dynamics of the sentinel cells caused by the disruption of normal cellular function by the infecting bacteria. Here, the Doppler imaging of infected sentinels shows the dynamic characteristics of infections. Invasive Salmonella enterica serovar Enteritidis and Listeria monocytogenes penetrate through multicellular tumor spheroids, while non-invasive strains of Escherichia coli and Listeria innocua remain isolated outside the cells, generating different Doppler signatures. Phase distributions caused by intracellular transport display Lévy statistics, introducing a Lévy-alpha spectroscopy of bacterial invasion. Antibiotic treatment of infected spheroids, monitored through time-dependent Doppler shifts, can distinguish drug-resistant relative to non-resistant strains. This use of intracellular Doppler spectroscopy of living tissue sentinels opens a new class of microbial assay with potential importance for studying the emergence of antibiotic resistance.
Systematic auditing is essential to debiasing machine learning in biology
Authors: Eid Fatma-Elzahraa , Elmarakeby Haitham A. , Chan Yujia Alina , Fornelos Nadine , ElHefnawi Mahmoud , Van Allen Eliezer M. , Heath Lenwood S. , Lage Kasper 
Published: February 2021

AbstractBiases in data used to train machine learning (ML) models can inflate their prediction performance and confound our understanding of how and what they learn. Although biases are common in biological data, systematic auditing of ML models to identify and eliminate these biases is not a common practice when applying ML in the life sciences. Here we devise a systematic, principled, and general approach to audit ML models in the life sciences. We use this auditing framework to examine biases in three ML applications of therapeutic interest and identify unrecognized biases that hinder the ML process and result in substantially reduced model performance on new datasets. Ultimately, we show that ML models tend to learn primarily from data biases when there is insufficient signal in the data to learn from. We provide detailed protocols, guidelines, and examples of code to enable tailoring of the auditing framework to other biomedical applications.
Global mapping of protein–metabolite interactions in Saccharomyces cerevisiae reveals that Ser-Leu dipeptide regulates phosphoglycerate kinase activity
Authors: Luzarowski Marcin , Vicente Rubén , Kiselev Andrei , Wagner Mateusz , Schlossarek Dennis , Erban Alexander , de Souza Leonardo Perez , Childs Dorothee , Wojciechowska Izabela , Luzarowska Urszula , Górka Michał , Sokołowska Ewelina M. , Kosmacz Monika , Moreno Juan C. , Brzezińska Aleksandra , Vegesna Bhavana , Kopka Joachim , Fernie Alisdair R. , Willmitzer Lothar , Ewald Jennifer C. , Skirycz Aleksandra 
Published: February 2021

AbstractProtein–metabolite interactions are of crucial importance for all cellular processes but remain understudied. Here, we applied a biochemical approach named PROMIS, to address the complexity of the protein–small molecule interactome in the model yeast Saccharomyces cerevisiae. By doing so, we provide a unique dataset, which can be queried for interactions between 74 small molecules and 3982 proteins using a user-friendly interface available at https://promis.mpimp-golm.mpg.de/yeastpmi/. By interpolating PROMIS with the list of predicted protein–metabolite interactions, we provided experimental validation for 225 binding events. Remarkably, of the 74 small molecules co-eluting with proteins, 36 were proteogenic dipeptides. Targeted analysis of a representative dipeptide, Ser-Leu, revealed numerous protein interactors comprising chaperones, proteasomal subunits, and metabolic enzymes. We could further demonstrate that Ser-Leu binding increases activity of a glycolytic enzyme phosphoglycerate kinase (Pgk1). Consistent with the binding analysis, Ser-Leu supplementation leads to the acute metabolic changes and delays timing of a diauxic shift. Supported by the dipeptide accumulation analysis our work attests to the role of Ser-Leu as a metabolic regulator at the interface of protein degradation and central metabolism.
Scalable reservoir computing on coherent linear photonic processor
Authors: Nakajima Mitsumasa , Tanaka Kenji , Hashimoto Toshikazu 
Published: February 2021

AbstractPhotonic neuromorphic computing is of particular interest due to its significant potential for ultrahigh computing speed and energy efficiency. The advantage of photonic computing hardware lies in its ultrawide bandwidth and parallel processing utilizing inherent parallelism. Here, we demonstrate a scalable on-chip photonic implementation of a simplified recurrent neural network, called a reservoir computer, using an integrated coherent linear photonic processor. In contrast to previous approaches, both the input and recurrent weights are encoded in the spatiotemporal domain by photonic linear processing, which enables scalable and ultrafast computing beyond the input electrical bandwidth. As the device can process multiple wavelength inputs over the telecom C-band simultaneously, we can use ultrawide optical bandwidth (~5 terahertz) as a computational resource. Experiments for the standard benchmarks showed good performance for chaotic time-series forecasting and image classification. The device is considered to be able to perform 21.12 tera multiplication–accumulation operations per second (MAC ∙ s−1) for each wavelength and can reach petascale computation speed on a single photonic chip by using wavelength division multiplexing. Our results are challenging for conventional Turing–von Neumann machines, and they confirm the great potential of photonic neuromorphic processing towards peta-scale neuromorphic super-computing on a photonic chip.
High-efficiency Pd nanoparticles loaded porous organic polymers membrane catalytic reactors
Authors: Chen Yaohan , Li Yonggang , Dai Lei , Qin Guorui , Guo Jing , Zhang Qifeng , Li Shenghai , Sherazi Tauqir A. , Zhang Suobo 
Published: February 2021

Cross-linked porous organic polymer membranes were fabricated via interfacial azo-coupling polymerization and demonstrated to be a high-performance membrane catalytic reactor with a flux of 27.3 t m−2 day−1 for reducing the nitrophenols.
Development of an Oral Care Multidisciplinary Initiative in an Acute Care Community Hospital: Framework, Timeline, and Outcomes
Authors: Wennerholm Laurie , Perez Nilsa Rubin , Abt Suzanne , Fon Karen , Elsabrout Kerri 
Published: February 2021

Purpose
Published literature universally supports the provision of oral care in acute care settings to decrease hospital-acquired aspiration pneumonia (HAAP) events. This evidence-based practice project aimed to implement a comprehensive oral care initiative to reduce a problematic HAAP rate.

Method
Through a comprehensive, multidisciplinary approach, the project scope included an assessment of the current state of oral care delivery, development of an Oral Care Task Force, creation of risk stratification criteria with recommended oral care products, and robust education for the clinical staff. Data were gathered using a small convenience sample of inpatients and hospital-wide HAAP rates.

Results
Over the 1 year of implementation and education associated with this multidisciplinary project, the organization saw an increase in oral care tools being available to patients and staff at the bedside, an increase in patients' awareness of oral care tools in their rooms, and a decrease in the overall HAAP rate.

Conclusions
Creating a multidisciplinary team within an acute care organization with a focus on oral care delivery can be substantially advantageous to patients and hospitals alike. Although this project was limited in its analysis, the demonstrated results are nonetheless interesting and may be applicable to other acute care settings. Ultimately, attention to the importance of oral care and consistent care delivery can provide improved patient outcomes.
Dysphagia Management in Military Service Members With Polytrauma: Overview and Case Report
Authors: Cord Laura L. , Rajpal Veena , Solomon Nancy Pearl 
Published: February 2021

Purpose
At Walter Reed National Military Medical Center, service members (SMs) with polytraumatic injuries, usually resulting from blast explosions, are routinely referred to the Speech Pathology Clinic for evaluation of swallowing function. The purpose of this clinical focus article is to advance the speech-language pathologist's (SLP) knowledge of polytrauma and to improve the care of individuals with traumatic injuries, especially related to nutrition and swallowing within a larger multidisciplinary team approach.

Case Report
Previous research within our center identified common demographic and injury characteristics of SMs with combat-related injuries that led to referrals for swallowing evaluation. An SM with polytraumatic injuries was selected for this case report to illustrate the relevance of the research findings and also the importance of multidisciplinary team support to appropriately manage such complex cases. Evaluations and relevant treatments are described across a 3-month acute care hospitalization, including swallowing and nutritional recommendations at the time of each swallowing evaluation.

Discussion
Comparisons of polytrauma cases at Walter Reed National Military Medical Center with literature from civilian trauma centers revealed somewhat longer hospitalizations and the particular influence of maxillofacial trauma on dysphagia outcomes. The complex case reported in this article illustrates the importance of multidisciplinary care and coordination, with particular emphasis on the intersecting roles of the SLP and registered dietitian. This report can serve as a guide for SLPs working in trauma settings for developing prognostic statements, treatment plans, and multidisciplinary interaction.