bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nuclear compartmentalization of TERT mRNA and TUG1 lncRNA is driven by intron retention
Authors: Dumbović Gabrijela , Braunschweig Ulrich , Langner Heera K. , Smallegan Michael , Biayna Josep , Hass Evan P. , Jastrzebska Katarzyna , Blencowe Benjamin , Cech Thomas R. , Caruthers Marvin H. , Rinn John L. 
Published: June 2021

AbstractThe spatial partitioning of the transcriptome in the cell is an important form of gene-expression regulation. Here, we address how intron retention influences the spatio-temporal dynamics of transcripts from two clinically relevant genes: TERT (Telomerase Reverse Transcriptase) pre-mRNA and TUG1 (Taurine-Upregulated Gene 1) lncRNA. Single molecule RNA FISH reveals that nuclear TERT transcripts uniformly and robustly retain specific introns. Our data suggest that the splicing of TERT retained introns occurs during mitosis. In contrast, TUG1 has a bimodal distribution of fully spliced cytoplasmic and intron-retained nuclear transcripts. We further test the functionality of intron-retention events using RNA-targeting thiomorpholino antisense oligonucleotides to block intron excision. We show that intron retention is the driving force for the nuclear compartmentalization of these RNAs. For both RNAs, altering this splicing-driven subcellular distribution has significant effects on cell viability. Together, these findings show that stable retention of specific introns can orchestrate spatial compartmentalization of these RNAs within the cell. This process reveals that modulating RNA localization via targeted intron retention can be utilized for RNA-based therapies.
Photocatalyzed cycloaromatization of vinylsilanes with arylsulfonylazides
Authors: Chen Fengjuan , Shao Youxiang , Li Mengke , Yang Can , Su Shi-Jian , Jiang Huanfeng , Ke Zhuofeng , Zeng Wei 
Published: June 2021

AbstractSila-molecules have recently attracted attention due to their promising applications in medical and industrial fields. Compared with all-carbon parent compounds, the different covalent radius and electronegativity of silicon from carbon generally endow the corresponding sila-analogs with unique biological activity and physicochemical properties. Vinylsilanes feature both silyl-hyperconjugation effect and versatile reactivities, developing vinylsilane-based Smiles rearrangement will therefore provide an efficient platform to assemble complex silacycles. Here we report a practical Ir(III)-catalyzed cycloaromatization ofortho-alkynylaryl vinylsilanes with arylsulfonyl azides for delivering naphthyl-fused benzosiloles under visible-light photoredox conditions. The combination of experiments and density functional theory (DFT) energy profiles reveals the reaction mechanism involving α-silyl radical Smiles rearrangement.
Perilipin 5 links mitochondrial uncoupled respiration in brown fat to healthy white fat remodeling and systemic glucose tolerance
Authors: Gallardo-Montejano Violeta I. , Yang Chaofeng , Hahner Lisa , McAfee John L. , Johnson Joshua A. , Holland William L. , Fernandez-Valdivia Rodrigo , Bickel Perry E. 
Published: June 2021

AbstractExposure of mice or humans to cold promotes significant changes in brown adipose tissue (BAT) with respect to histology, lipid content, gene expression, and mitochondrial mass and function. Herein we report that the lipid droplet coat protein Perilipin 5 (PLIN5) increases markedly in BAT during exposure of mice to cold. To understand the functional significance of cold-induced PLIN5, we created and characterized gain- and loss-of-function mouse models. Enforcing PLIN5 expression in mouse BAT mimics the effects of cold with respect to mitochondrial cristae packing and uncoupled substrate-driven respiration. PLIN5 is necessary for the maintenance of mitochondrial cristae structure and respiratory function during cold stress. We further show that promoting PLIN5 function in BAT is associated with healthy remodeling of subcutaneous white adipose tissue and improvements in systemic glucose tolerance and diet-induced hepatic steatosis. These observations will inform future strategies that seek to exploit thermogenic adipose tissue as a therapeutic target for type 2 diabetes, obesity, and nonalcoholic fatty liver disease.
Saving superconducting quantum processors from decay and correlated errors generated by gamma and cosmic rays
Authors: Martinis John M. 
Published: June 2021

AbstractError-corrected quantum computers can only work if errors are small and uncorrelated. Here, I show how cosmic rays or stray background radiation affects superconducting qubits by modeling the phonon to electron/quasiparticle down-conversion physics. For present designs, the model predicts about 57% of the radiation energy breaks Cooper pairs into quasiparticles, which then vigorously suppress the qubit energy relaxation time (T1 ~ 600 ns) over a large area (cm) and for a long time (ms). Such large and correlated decay kills error correction. Using this quantitative model, I show how this energy can be channeled away from the qubit so that this error mechanism can be reduced by many orders of magnitude. I also comment on how this affects other solid-state qubits.
Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: a software engineering perspective
Authors: Schölzel Christopher , Blesius Valeria , Ernst Gernot , Dominik Andreas 
Published: June 2021

AbstractReuse of mathematical models becomes increasingly important in systems biology as research moves toward large, multi-scale models composed of heterogeneous subcomponents. Currently, many models are not easily reusable due to inflexible or confusing code, inappropriate languages, or insufficient documentation. Best practice suggestions rarely cover such low-level design aspects. This gap could be filled by software engineering, which addresses those same issues for software reuse. We show that languages can facilitate reusability by being modular, human-readable, hybrid (i.e., supporting multiple formalisms), open, declarative, and by supporting the graphical representation of models. Modelers should not only use such a language, but be aware of the features that make it desirable and know how to apply them effectively. For this reason, we compare existing suitable languages in detail and demonstrate their benefits for a modular model of the human cardiac conduction system written in Modelica.
High FIB4 index is an independent risk factor of diabetic kidney disease in type 2 diabetes
Authors: Saito Haruka , Tanabe Hayato , Kudo Akihiro , Machii Noritaka , Higa Moritake , Yamaguchi Satoshi , Maimaituxun Gulinu , Abe Kazumichi , Takahashi Atsushi , Tanaka Kenichi , Asahi Koichi , Masuzaki Hiroaki , Ohira Hiromasa , Kazama Junichiro J. , Shimabukuro Michio 
Published: June 2021

AbstractNonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) may be linked to development of chronic kidney diseases (CKD). The FIB4 index, a noninvasive liver fibrosis score, has been reported to predict CKD in non-diabetic patients, but there are no reports yet in diabetic cases. Therefore, we evaluated the prognostic impact of FIB4 index on the risk of developing diabetic kidney disease (DKD) in Japanese patients with type 2 diabetes in a retrospective cohort study. We assessed patients with type 2 diabetes with an eGFR ≥ 60 mL/min/1.73 m2 and without dipstick positive proteinuria (≥ 1 +) at their first visit to our department. Participants were divided into two groups based on the FIB4 index at their first visit: FIB4 index > 1.3 and FIB4 index ≤ 1.3. The primary endpoint was defined as a decrease in eGFR < 60 mL/min/1.73 m2 or the onset of proteinuria during the course of treatment. The average age of all 584 type 2 diabetic participants (360 [61.6%] men) was 55 ± 11 years. There were 187 patients in the FIB4 index group > 1.3 (32.0%) and the median observation period was 6.0 (3.8–11.0) years. Kaplan–Meier survival analysis indicated that the risks of developing DKD, eGFR < 60 and proteinuria were all higher in FIB4 index > 1.3 patients than in FIB4 ≤ 1.3 patients. In the Cox regression analysis, an FIB4 index > 1.3 was a significant predictor for onset of DKD (HR 1.54, 95% CI 1.15–2.08) and proteinuria (HR 1.55, 95% CI 1.08–2.23), but not for an eGFR < 60 (HR 1.14, 95% CI 0.79–1.99). To the best of our knowledge, this is the first study to demonstrate that an FIB4 index > 1.3 has a prognostic impact on the development of CKD and proteinuria in type 2 diabetic patients. This warrants further investigation of the prognostic impact of the development of DKD or proteinuria.
Responses to chemical cross-talk between the Mycobacterium ulcerans toxin, mycolactone, and Staphylococcus aureus
Authors: Dhungel Laxmi , Burcham Lindsey , Park Joo Youn , Sampathkumar Harshini Devi , Cudjoe Albert , Seo Keun Seok , Jordan Heather 
Published: June 2021

AbstractBuruli ulcer is a neglected tropical disease caused by the environmental pathogen, Mycobacterium ulcerans whose major virulence factor is mycolactone, a lipid cytotoxic molecule. Buruli ulcer has high morbidity, particularly in rural West Africa where the disease is endemic. Data have shown that infected lesions of Buruli ulcer patients can be colonized by quorum sensing bacteria such as Staphylococcus aureus, S. epidermidis, and Pseudomonas aeruginosa, but without typical pathology associated with those pathogens’ colonization. M. ulcerans pathogenesis may not only be an individual act but may also be dependent on synergistic or antagonistic mechanisms within a polymicrobial network. Furthermore, co-colonization by these pathogens may promote delayed wound healing, especially after the initiation of antibiotic therapy. Hence, it is important to understand the interaction of M. ulcerans with other bacteria encountered during skin infection. We added mycolactone to S. aureus and incubated for 3, 6 and 24 h. At each timepoint, S. aureus growth and hemolytic activity was measured, and RNA was isolated to measure virulence gene expression through qPCR and RNASeq analyses. Results showed that mycolactone reduced S. aureus hemolytic activity, suppressed hla promoter activity, and attenuated virulence genes, but did not affect S. aureus growth. RNASeq data showed mycolactone greatly impacted S. aureus metabolism. These data are relevant and significant as mycolactone and S. aureus sensing and response at the transcriptional, translational and regulation levels will provide insight into biological mechanisms of interspecific interactions that may play a role in regulation of responses such as effects between M. ulcerans, mycolactone, and S. aureus virulence that will be useful for treatment and prevention.
An electrochemical sensor for nanomolar detection of caffeine based on nicotinic acid hydrazide anchored on graphene oxide (NAHGO)
Authors: Jose Jemini , Subramanian Viswanathan , Shaji Sadasivan , Sreeja P. B. 
Published: June 2021

AbstractA simple modified sensor was developed with nicotinic acid hydrazide anchored on graphene oxide (NAHGO), by ultrasonic-assisted chemical route, using hydroxy benzotriazole as a mediator. Structural and morphologies of NAHGO samples were investigated in detail by Fourier-Transform Infrared spectroscopy (FT-IR), Powder X-ray diffraction (P-XRD), Raman spectroscopy, Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and Thermogravimetric analysis (TGA). The detailed morphological examination and electrochemical studies revealed the delaminated sheet with the tube-like structure of NAHGO provided the route for more electroactive surface which influenced the electrooxidation of caffeine with increased current. The electrochemical behaviour of NAHGO on a glassy carbon electrode (GCE) for caffeine detection was demonstrated by employing voltammetric techniques. The influence of scan rate, pH, and concentration on caffeine's peak current was also studied. The NAHGO sensor was employed for the determination of caffeine in imol plus and energy drinks. The detection limit determined was 8.7 × 10–9 M, and the best value was reported so far. The results show that NAHGO modified electrodes are one of the best preferences to establish new, efficient, and reliable analytical tools for the detection of caffeine.
Multi-photon above threshold ionization of multi-electron atoms and molecules using the R-matrix approach
Authors: Benda Jakub , Mašín Zdeněk 
Published: June 2021

AbstractWe formulate a computationally efficient time-independent method based on the multi-electron molecular R-matrix formalism. This method is used to calculate transition matrix elements for the multi-photon ionization of atoms and molecules under the influence of a perturbative field. The method relies on the partitioning of space which allows us to calculate the infinite-range free-free dipole integrals analytically in the outer region, beyond the range of the initial bound wave function. This approach is valid for an arbitrary order, that is, any number of photons absorbed both in the bound and the continuum part of the spectrum (below- and above-threshold ionization). We calculate generalized multi-photon cross sections and angular distributions of different systems (H, He, $$\hbox {H}_{{2}}$$

H
2

, $$\hbox {CO}_{{2}}$$

CO
2

) and validate our approach by comparison with data from the literature.
Robust diagnostic classification via Q-learning
Authors: Ardulov Victor , Martinez Victor R. , Somandepalli Krishna , Zheng Shuting , Salzman Emma , Lord Catherine , Bishop Somer , Narayanan Shrikanth 
Published: June 2021

AbstractMachine learning (ML) models have demonstrated the power of utilizing clinical instruments to provide tools for domain experts in gaining additional insights toward complex clinical diagnoses. In this context these tools desire two additional properties: interpretability, being able to audit and understand the decision function, and robustness, being able to assign the correct label in spite of missing or noisy inputs. This work formulates diagnostic classification as a decision-making process and utilizes Q-learning to build classifiers that meet the aforementioned desired criteria. As an exemplary task, we simulate the process of differentiating Autism Spectrum Disorder from Attention Deficit-Hyperactivity Disorder in verbal school aged children. This application highlights how reinforcement learning frameworks can be utilized to train more robust classifiers by jointly learning to maximize diagnostic accuracy while minimizing the amount of information required.
Endothelial-derived cardiovascular disease-related microRNAs elevated with prolonged sitting pattern among postmenopausal women
Authors: Chang Ya-Ju , Tuz-Zahra Fatima , Godbole Suneeta , Avitia Yesenia , Bellettiere John , Rock Cheryl L. , Jankowska Marta M. , Allison Matthew A. , Dunstan David W. , Rana Brinda , Natarajan Loki , Sears Dorothy D. 
Published: June 2021

AbstractTime spent sitting is positively correlated with endothelial dysfunction and cardiovascular disease risk. The underlying molecular mechanisms are unknown. MicroRNAs contained in extracellular vesicles (EVs) reflect cell/tissue status and mediate intercellular communication. We explored the association between sitting patterns and microRNAs isolated from endothelial cell (EC)-derived EVs. Using extant actigraphy based sitting behavior data on a cohort of 518 postmenopausal overweight/obese women, we grouped the woman as Interrupted Sitters (IS; N = 18) or Super Sitters (SS; N = 53) if they were in the shortest or longest sitting pattern quartile, respectively. The cargo microRNA in EC-EVs from the IS and SS women were compared. MicroRNA data were weighted by age, physical functioning, MVPA, device wear days, device wear time, waist circumference, and body mass index. Screening of CVD-related microRNAs demonstrated that miR-199a-5p, let-7d-5p, miR-140-5p, miR-142-3p, miR-133b level were significantly elevated in SS compared to IS groups. Group differences in let-7d-5p, miR-133b, and miR-142-3p were validated in expanded groups. Pathway enrichment analyses show that mucin-type O-glycan biosynthesis and cardiomyocyte adrenergic signaling (P < 0.001) are downstream of the three validated microRNAs. This proof-of-concept study supports the possibility that CVD-related microRNAs in EC-EVs may be molecular transducers of sitting pattern-associated CVD risk in overweight postmenopausal women.
Nitrogen fixation and denitrification activity differ between coral- and algae-dominated Red Sea reefs
Authors: El-Khaled Yusuf C. , Roth Florian , Rädecker Nils , Tilstra Arjen , Karcher Denis B. , Kürten Benjamin , Jones Burton H. , Voolstra Christian R. , Wild Christian 
Published: June 2021

AbstractCoral reefs experience phase shifts from coral- to algae-dominated benthic communities, which could affect the interplay between processes introducing and removing bioavailable nitrogen. However, the magnitude of such processes, i.e., dinitrogen (N2) fixation and denitrification levels, and their responses to phase shifts remain unknown in coral reefs. We assessed both processes for the dominant species of six benthic categories (hard corals, soft corals, turf algae, coral rubble, biogenic rock, and reef sands) accounting for > 98% of the benthic cover of a central Red Sea coral reef. Rates were extrapolated to the relative benthic cover of the studied organisms in co-occurring coral- and algae-dominated areas of the same reef. In general, benthic categories with high N2fixation exhibited low denitrification activity. Extrapolated to the respective reef area, turf algae and coral rubble accounted for > 90% of overall N2fixation, whereas corals contributed to more than half of reef denitrification. Total N2fixation was twice as high in algae- compared to coral-dominated areas, whereas denitrification levels were similar. We conclude that algae-dominated reefs promote new nitrogen input through enhanced N2fixation and comparatively low denitrification. The subsequent increased nitrogen availability could support net productivity, resulting in a positive feedback loop that increases the competitive advantage of algae over corals in reefs that experienced a phase shift.
Temporal coherency of mechanical stimuli modulates tactile form perception
Authors: Nakatani Masashi , Kobayashi Yasuaki , Ohno Kota , Uesaka Masaaki , Mogami Sayako , Zhao Zixia , Sushida Takamichi , Kitahata Hiroyuki , Nagayama Masaharu 
Published: June 2021

AbstractThe human hand can detect both form and texture information of a contact surface. The detection of skin displacement (sustained stimulus) and changes in skin displacement (transient stimulus) are thought to be mediated in different tactile channels; however, tactile form perception may use both types of information. Here, we studied whether both the temporal frequency and the temporal coherency information of tactile stimuli encoded in sensory neurons could be used to recognize the form of contact surfaces. We used the fishbone tactile illusion (FTI), a known tactile phenomenon, as a probe for tactile form perception in humans. This illusion typically occurs with a surface geometry that has a smooth bar and coarse textures in its adjacent areas. When stroking the central bar back and forth with a fingertip, a human observer perceives a hollow surface geometry even though the bar is physically flat. We used a passive high-density pin matrix to extract only the vertical information of the contact surface, suppressing tangential displacement from surface rubbing. Participants in the psychological experiment reported indented surface geometry by tracing over the FTI textures with pin matrices of the different spatial densities (1.0 and 2.0 mm pin intervals). Human participants reported that the relative magnitude of perceived surface indentation steeply decreased when pins in the adjacent areas vibrated in synchrony. To address possible mechanisms for tactile form perception in the FTI, we developed a computational model of sensory neurons to estimate temporal patterns of action potentials from tactile receptive fields. Our computational data suggest that (1) the temporal asynchrony of sensory neuron responses is correlated with the relative magnitude of perceived surface indentation and (2) the spatiotemporal change of displacements in tactile stimuli are correlated with the asynchrony of simulated sensory neuron responses for the fishbone surface patterns. Based on these results, we propose that both the frequency and the asynchrony of temporal activity in sensory neurons could produce tactile form perception.
Ensemble machine learning of factors influencing COVID-19 across US counties
Authors: McCoy David , Mgbara Whitney , Horvitz Nir , Getz Wayne M. , Hubbard Alan 
Published: June 2021

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately impact certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting the early phases (before July, 2020) of per capita COVID-19 transmission and per capita all-cause mortality in US counties. We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze per capita COVID-19 outcomes. Because of the high-dimensionality, multicollinearity, and unknown interactions of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measure. Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest predictors for both per capita COVID-19 incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black- and/or African-American individuals in a county were the most important features for per capita COVID-19 cases within a month after the pandemic started in a county and also at the latest date examined. For per capita all-cause mortality at day 100 and total to date, we find that public transportation use and proportion of Black- and/or African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use, all other factors remaining fixed at the observed values, is associated with increases mortality at day 100 of 2012 individuals (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black- and/or African-American individuals in a county is associated with increases total deaths at end of study of 2067 (95% CI [1189, 2654]). Using data until the end of study, the same metric suggests ethnicity has double the association as the next most important factors, which are location, disease prevalence, and transit factors. Our findings shed light on societal patterns that have been reported and experienced in the U.S. by using robust methods to understand the features most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results provide evidence of the disproportionate impact of the COVID-19 pandemic on minority populations. Our results suggest that mitigation measures, including how vaccines are distributed, could have the greatest impact if they are given with priority to the highest risk communities.