bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tail-tape-fused virion and non-virion RNA polymerases of a thermophilic virus with an extremely long tail
Authors: Chaban Anastasiia , Minakhin Leonid , Goldobina Ekaterina , Bae Brain , Hao Yue , Borukhov Sergei , Putzeys Leena , Boon Maarten , Kabinger Florian , Lavigne Rob , Makarova Kira S. , Koonin Eugene V. , Nair Satish K. , Tagami Shunsuke , Severinov Konstantin , Sokolova Maria L. 
Published: January 2024

AbstractThermus thermophilus bacteriophage P23-45 encodes a giant 5,002-residue tail tape measure protein (TMP) that defines the length of its extraordinarily long tail. Here, we show that the N-terminal portion of P23-45 TMP is an unusual RNA polymerase (RNAP) homologous to cellular RNAPs. The TMP-fused virion RNAP transcribes pre-early phage genes, including a gene that encodes another, non-virion RNAP, that transcribes early and some middle phage genes. We report the crystal structures of both P23-45 RNAPs. The non-virion RNAP has a crab-claw-like architecture. By contrast, the virion RNAP adopts a unique flat structure without a clamp. Structure and sequence comparisons of the P23-45 RNAPs with other RNAPs suggest that, despite the extensive functional differences, the two P23-45 RNAPs originate from an ancient gene duplication in an ancestral phage. Our findings demonstrate striking adaptability of RNAPs that can be attained within a single virus species.
Molecular and circuit mechanisms underlying avoidance of rapid cooling stimuli in C. elegans
Authors: Lin Chenxi , Shan Yuxin , Wang Zhongyi , Peng Hui , Li Rong , Wang Pingzhou , He Junyan , Shen Weiwei , Wu Zhengxing , Guo Min 
Published: January 2024

AbstractThe mechanisms by which animals respond to rapid changes in temperature are largely unknown. Here, we found that polymodal ASH sensory neurons mediate rapid cooling-evoked avoidance behavior within the physiological temperature range in C. elegans. ASH employs multiple parallel circuits that consist of stimulatory circuits (AIZ, RIA, AVA) and disinhibitory circuits (AIB, RIM) to respond to rapid cooling. In the stimulatory circuit, AIZ, which is activated by ASH, releases glutamate to act on both GLR-3 and GLR-6 receptors in RIA neurons to promote reversal, and ASH also directly or indirectly stimulates AVA to promote reversal. In the disinhibitory circuit, AIB is stimulated by ASH through the GLR-1 receptor, releasing glutamate to act on AVR-14 to suppress RIM activity. RIM, an inter/motor neuron, inhibits rapid cooling-evoked reversal, and the loop activities thus equally stimulate reversal. Our findings elucidate the molecular and circuit mechanisms underlying the acute temperature stimuli-evoked avoidance behavior.
Circulating tumour mutation detection in triple-negative breast cancer as an adjunct to tissue response assessment
Authors: Zaikova Elena , Cheng Brian Y. C. , Cerda Viviana , Kong Esther , Lai Daniel , Lum Amy , Bates Cherie , den Brok Wendie , Kono Takako , Bourque Sylvie , Chan Angela , Feng Xioalan , Fenton David , Gurjal Anagha , Levasseur Nathalie , Lohrisch Caroline , Roberts Sarah , Shenkier Tamara , Simmons Christine , Taylor Sara , Villa Diego , Miller Ruth , Aguirre-Hernandez Rosalia , Aparicio Samuel , Gelmon Karen 
Published: January 2024

AbstractCirculating tumour DNA (ctDNA) detection via liquid biopsy is an emerging alternative to tissue biopsy, but its potential in treatment response monitoring and prognosis in triple negative breast cancer (TNBC) is not yet well understood. Here we determined the prevalence of actionable mutations detectable in ctDNA using a clinically validated cancer gene panel assay in patients with TNBC, without recurrence at the time of study entry. Sequencing of plasma DNA and validation of variants from 130 TNBC patients collected within 7 months of primary treatment completion revealed that 7.7% had detectable residual disease with a hotspot panel. Among neoadjuvant treated patients, we observed a trend where patients with incomplete pathologic response and positive ctDNA within 7 months of treatment completion were at much higher risk of reduced progression free survival. We propose that a high risk subset of early TNBC patients treated in neoadjuvant therapy protocols may be identifiable by combining tissue response and sensitive ctDNA detection.
Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing
Authors: Jiang Runbo , Smith John , Yi Yu-Tsen , Sun Tao , Simonds Brian J. , Rollett Anthony D. 
Published: January 2024

AbstractThe quantification of absorbed light is essential for understanding laser-material interactions and melt pool dynamics in order to minimize defects in additively manufactured metal components. The geometry of a vapor depression formed during laser melting is closely related to laser energy absorption. This relationship has been observed by the state-of-the-art in situ high-speed synchrotron X-ray visualization and integrating sphere radiometry. These two techniques create a temporally resolved dataset consisting of vapor depression images and corresponding laser absorptance. In this work, we propose two different approaches to predict instantaneous laser absorptance. The end-to-end approach uses deep convolutional neural networks to learn implicit features of X-ray images automatically and predict the laser energy absorptance. The two-stage approach uses a semantic segmentation model to engineer geometric features and predict absorptance using classical regression models. While having distinct advantages, both approaches achieved a consistently low mean absolute error of less than 3.3%.
Constant inner potential DFT for modelling electrochemical systems under constant potential and bias
Authors: Melander Marko M. , Wu Tongwei , Weckman Timo , Honkala Karoliina 
Published: January 2024

AbstractElectrochemical systems play a decisive role in, e.g. clean energy conversion but understanding their complex chemistry remains an outstanding challenge. Constant potential and grand canonical ensemble (GCE) simulations are indispensable for unraveling the properties of electrochemical processes as a function of the electrode potential. Currently, GCE calculations performed at the density functional theory (DFT) level require fixing the Fermi level within the simulation cell. Here, we illustrate that this method is inadequate when modeling outer sphere reactions and a biased two-electrode cell. For these systems, the Fermi level obtained from DFT calculations does not accurately present the experimentally controlled electrode potential or describe the thermodynamic independent variable in GCE-DFT. To address this limitation, we developed and implemented a constant inner potential (CIP) method offering a more robust and general approach to conducting GCE-DFT simulations of electrochemical systems under constant potential or bias conditions. The primary advantage of CIP is that it uses the local electrode inner potential as the thermodynamic parameter for the electrode potential, as opposed to the global Fermi level. Through numerical and analytical studies, we demonstrate that the CIP and Fermi level GCE-DFT approaches are equivalent for metallic electrodes and inner-sphere reactions. However, CIP proves to be more versatile, as it can be applied to outer-sphere and two-electrode systems, addressing the limitations of the constant Fermi-level approach in these scenarios. Altogether, the CIP approach stands out as a general and efficient GCE-DFT method simulating electrochemical interfaces from first principles.
Pure-water-fed, electrocatalytic CO2 reduction to ethylene beyond 1,000 h stability at 10 A
Authors: She Xiaojie , Zhai Lingling , Wang Yifei , Xiong Pei , Li Molly Meng-Jung , Wu Tai-Sing , Wong Man Chung , Guo Xuyun , Xu Zhihang , Li Huaming , Xu Hui , Zhu Ye , Tsang Shik Chi Edman , Lau Shu Ping 
Published: January 2024

AbstractElectrocatalytic CO2 reduction at near-ambient temperatures requires a complex inventory of protons, hydroxyls, carbonate ions and alkali-metal ions at the cathode and anode to be managed, necessitating the use of ion-selective membranes to regulate pH. Anion-exchange membranes provide an alkaline environment, allowing CO2 reduction at low cell voltages and suppression of hydrogen evolution while maintaining high conversion efficiencies. However, the local alkaline conditions and the presence of alkali cations lead to problematic carbonate formation and even precipitation. Here we report a pure-water-fed (alkali-cation-free) membrane–electrode–assembly system for CO2 reduction to ethylene by integrating an anion-exchange membrane and a proton-exchange membrane at the cathode and anode side, respectively, under forward bias. This system effectively suppresses carbonate formation and prevents salt precipitation. A scaled-up electrolyser stack achieved over 1,000 h stability without CO2 and electrolyte losses and with 50% Faradaic efficiency towards ethylene at a total current of 10 A.
Optimized spatial information for 1990, 2000, and 2010 U.S. census microdata
Authors: Fowler Christopher S. , Gaboardi James D. , Schroeder Jonathan P. , Van Riper David C. 
Published: January 2024

AbstractWe report on the successful completion of a project to upgrade the positional accuracy of every response to the 1990, 2000, and 2010 U.S. decennial censuses. The resulting data set, called Optimized Spatial Census Information Linked Across Time (OSCILAT), resides within the restricted-access data warehouse of the Federal Statistical Research Data Center (FSRDC) system where it is available for use with approval from the U.S. Census Bureau. OSCILAT greatly improves the accuracy and completeness of spatial information for older censuses conducted prior to major quality improvements undertaken by the Bureau. Our work enables more precise spatial and longitudinal analysis of census data and supports exact tabulations of census responses for arbitrary spatial units, including tabulating responses from 1990, 2000, and 2010 within 2020 block boundaries for precise measures of change over time for small geographic areas.
Chromosomal-scale genome assembly and annotation of the land slug (Meghimatium bilineatum)
Authors: Sun Shaolei , Han Xiaolu , Han Zhiqiang , Liu Qi 
Published: January 2024

AbstractMeghimatium bilineatum is a notorious pest land slug used as a medicinal resource to treat ailments in China. Although this no-model species is unique in terms of their ecological security and medicinal value, the genome resource of this slug is lacking to date. Here, we used the Illumina, PacBio, and Hi-C sequencing techniques to construct a chromosomal-level genome of M. bilineatum. With the Hi-C correction, the sequencing data from PacBio system generated a 1.61 Gb assembly with a scaffold N50 of 68.08 Mb, and anchored to 25 chromosomes. The estimated assembly completeness at 91.70% was obtained using BUSCO methods. The repeat sequence content in the assembled genome was 72.51%, which mainly comprises 34.08% long interspersed elements. We further identified 18631 protein-coding genes in the assembled genome. A total of 15569 protein-coding genes were successfully annotated. This genome assembly becomes an important resource for studying the ecological adaptation and potential medicinal molecular basis of M. bilineatum.
Diabetic foot ulcers risk prediction in patients with type 2 diabetes using classifier based on associations rule mining
Authors: Piran Nasrin , Farhadian Maryam , Soltanian Ali Reza , Borzouei Shiva 
Published: January 2024

AbstractIdentifying diabetic patients at risk of developing foot ulcers, as one of the most significant complications of diabetes, is a crucial healthcare concern. This study aimed to develop an associative classification model (CBA) using the Apriori algorithm to predict diabetic foot ulcers (DFU). This retrospective cohort study included 666 patients with type 2 diabetes referred to Shahid Beheshti Hospital in Iran between April 2020 and August 2022, of which 279 (42%) had DFU. Data on 29 specific baseline features were collected, which were preprocessed by discretizing numerical variables based on medical cutoffs. The target variable was the occurrence of DFU, and the minimum support, confidence, and lift thresholds were set to 0.01, 0.7, and 1, respectively. After data preparation and cleaning, a CBA model was created using the Apriori algorithm, with 80% of the data used as a training set and 20% as a testing set. The accuracy and AUC (area under the roc curve) measure were used to evaluate the performance of the model. The CBA model discovered a total of 146 rules for two patient groups. Several factors, such as longer duration of diabetes over 10 years, insulin therapy, male sex, older age, smoking, addiction to other drugs, family history of diabetes, higher body mass index, physical inactivity, and diabetes complications such as proliferative and non-proliferative retinopathy and nephropathy, were identified as major risk factors contributing to the development of DFU. The CBA model achieved an overall accuracy of 96%. Also, the AUC value was 0.962 (95%CI 0.924, 1.000). The developed model has a high accuracy in predicting the risk of DFU in patients with type 2 diabetes. The creation of accurate predictive models for DFU has the potential to significantly reduce the burden of managing recurring ulcers and the need for amputation, which are significant health concerns associated with diabetes.
Peri-implantitis increases the risk of medication-related osteonecrosis of the jaws associated with osseointegrated implants in rats treated with zoledronate
Authors: Quintão Manhanini Souza Eduardo , Felipe Toro Luan , Franzão Ganzaroli Vinícius , de Oliveira Alvarenga Freire Jéssica , Matsumoto Mariza Akemi , Casatti Cláudio Aparecido , Tavares Ângelo Cintra Luciano , Leone Buchaim Rogério , Mardegan Issa João Paulo , Gouveia Garcia Valdir , Theodoro Leticia Helena , Ervolino Edilson 
Published: January 2024

AbstractThis study evaluated the peri-implant tissues under normal conditions and under the influence of experimental peri-implantitis (EPI) in osseointegrated implants installed in the maxillae of rats treated with oncologic dosage of zoledronate. Twenty-eight senescent female rats underwent the extraction of the upper incisor and placement of a titanium dental implant (DI). After eight weeks was installated a transmucosal healing screw on DI. After nine weeks, the following groups were formed: VEH, ZOL, VEH-EPI and ZOL-EPI. From the 9th until the 19th, VEH and VEH-EPI groups received vehicle and ZOL and ZOL-EPI groups received zoledronate. At the 14th week, a cotton ligature was installed around the DI in VEH-EPI and ZOL-EPI groups to induce the EPI. At the 19th week, euthanasia was performed, and the maxillae were processed so that at the implanted sites were analyzed: histological aspects and the percentage of total bone tissue (PTBT) and non-vital bone tissue (PNVBT), along with TNFα, IL-1β, VEGF, OCN and TRAP immunolabeling. ZOL group presented mild persistent peri-implant inflammation, higher PNVBT and TNFα and IL-1β immunolabeling, but lower for VEGF, OCN and TRAP in comparison with VEH group. ZOL-EPI group exhibited exuberant peri-implant inflammation, higher PNVBT and TNFα and IL-1β immunolabeling when compared with ZOL and VEH-EPI groups. Zoledronate disrupted peri-implant environment, causing mild persistent inflammation and increasing the quantity of non-vital bone tissue. Besides, associated with the EPI there were an exacerbated inflammation and even greater increase in the quantity of non-vital bone around the DI, which makes this condition a risk factor for medication-related osteonecrosis of the jaws.
Field evaluation of electrophysiologically-active dung volatiles as chemical lures for trapping of dung beetles
Authors: Perera Nisansala N. , Barrow Russell A. , Weston Paul A. , Weston Leslie A. , Gurr Geoff M. 
Published: January 2024

AbstractDung beetles are economically important beneficial insects that process dung. To locate this source, they use volatile organic compounds (VOCs). The objectives of the study were to evaluate the attractiveness of ten electrophysiologically-active dung volatiles (phenol, skatole, indole, p-cresol, butanone, butyric acid, eucalyptol, dimethyl sulphide, dimethyl disulphide, and toluene) to dung beetles in the field and to investigate how the composition of volatile blends influences efficacy as lures for use in traps. Six combinations of the compounds were compared with field collected cattle dung bait and a negative control, across three seasons. Both dung and synthetic baits captured all exotic dung beetle species present in the study area. A six-compound mix (M1), comprising major dung volatiles, served as an attractive chemical mixture. The addition of dimethyl sulphide, dimethyl disulphide (M2) and toluene (M4) enhanced attractancy of M1 for dung beetles, while eucalyptol (M3) decreased the attractancy. The degree of attraction by various dung beetle species to synthetic baits varied, but baits proved to be effective, especially for summer trapping. The trap design used in this study presented a convenient and practical way to sample dung beetle and other associated scarabs from open pastures. The attraction of introduced dung beetle species to synthetic baits is documented here for the first time in Australia. In addition, necrophagous Omorgus sp. is reported here for the first time to be attracted to synthetic baits. They showed a significant attraction to the mixture containing dimethyl sulphide and dimethyl disulphide (M2). The current study represents a promising first step towards formulating a synthetic chemical lure for dung beetles, offering a consistent, standardised, and bio-secure trapping method compared to use of naturally occurring dung baits, especially as a multi-species lure.
Long-term continuous monitoring of methane emissions at an oil and gas facility using a multi-open-path laser dispersion spectrometer
Authors: IJzermans Rutger , Jones Matthew , Weidmann Damien , van de Kerkhof Bas , Randell David 
Published: January 2024

AbstractA method for methane emissions monitoring at industrial facility level was developed based on a high precision multi-open-path laser dispersion spectrometer combined with Bayesian analysis algorithms using Monte Carlo Markov Chain (MCMC) inference. From the methane path-averaged concentrations spatially distributed over the facility under study, together with the wind vector, the analysis allows detection, localization and quantification of fugitive methane emissions. This paper describes the very first long term (3 months), continuous (24 h/7 days) deployment of this monitoring system at an operational gas processing and distribution facility. The continuous monitoring system, made of the combination of the open-path high-precision (<10 ppb) methane concentration analyser and the data analysis method, was evaluated with controlled releases of methane of about 5 kg/h for short periods of time (30–60 min). Quantification was successful, with actual emission rates lying well within the quoted uncertainty ranges. Source localisation was found to lack accuracy, with biases of 30–50 m in the direction of the line of sight of the spectrometer, due to the short duration of the controlled releases, the limited wind vector diversity, and complications from air flows around buildings not accounted for by the transport model. Using longer-term data from the deployment, the MCMC algorithm led to the identification of unexpected low intensity persistent sources (<1 kg/h) at the site. Localisation of persistent sources was mostly successful at equipment level (within ~20 m) as confirmed by a subsequent survey with an optical gas imaging (OGI) camera. Quantification of these individual sources was challenging owing to their low intensity, but a consistent estimate of the total methane emission from the facility could be derived using two different inference approaches. These results represent a stepping stone in the development of continuous monitoring systems for methane emissions, pivotal in driving greenhouse gas reduction from industrial facilities. The demonstrated continuous monitoring system gives promising performance in early detection of unexpected emissions and quantification of potentially time-varying emissions from an entire facility.
Identifying unique spectral fingerprints in cough sounds for diagnosing respiratory ailments
Authors: Ghrabli Syrine , Elgendi Mohamed , Menon Carlo 
Published: January 2024

AbstractCoughing, a prevalent symptom of many illnesses, including COVID-19, has led researchers to explore the potential of cough sound signals for cost-effective disease diagnosis. Traditional diagnostic methods, which can be expensive and require specialized personnel, contrast with the more accessible smartphone analysis of coughs. Typically, coughs are classified as wet or dry based on their phase duration. However, the utilization of acoustic analysis for diagnostic purposes is not widespread. Our study examined cough sounds from 1183 COVID-19-positive patients and compared them with 341 non-COVID-19 cough samples, as well as analyzing distinctions between pneumonia and asthma-related coughs. After rigorous optimization across frequency ranges, specific frequency bands were found to correlate with each respiratory ailment. Statistical separability tests validated these findings, and machine learning algorithms, including linear discriminant analysis and k-nearest neighbors classifiers, were employed to confirm the presence of distinct frequency bands in the cough signal power spectrum associated with particular diseases. The identification of these acoustic signatures in cough sounds holds the potential to transform the classification and diagnosis of respiratory diseases, offering an affordable and widely accessible healthcare tool.
Association between sexual dysfunction and vitamin D in Swedish primary health care patients born in the Middle East and Sweden
Authors: Taloyan Marina , Hjörleifdottir Steiner Kristin , Östenson Claes-Göran , Salminen Helena 
Published: January 2024

AbstractThe present study investigated primary care patients and compared self-reported sexual health in Swedes and Middle Easterners; analysed differences within and between the groups and analysed differences in 25-hydroxyvitamin D [25(OH)D] levels between the groups. 522 patients responded to a health questionnaire that included items on sexual health: 225 Middle Easterners from Iran, Iraq, and Turkey and 297 Swedes. Logistic regression was used to calculate the odds ratio (OR). Middle Easterners reported less sexual dysfunction than Swedes, and 75.8% of them and 18.9% of Swedes presented a 25(OH)D of < 50 nmol/L. The crude OR for reporting sexual dysfunction was 70% higher in Swedes compared to Middle Easterners (OR 1.70, 95% CI 1.15–2.50). This OR remained significant after adjustment for age, gender, waist circumference, and reported sexual desire. However, the significance disappeared after additional adjustment for 25(OH)D. In both groups, more females than males reported insufficient sexual desire. More female Middle Easterners reported sex life dissatisfaction. More female Swedes reported sexual dysfunction. Vitamin D could explain an association between gender and sex life dissatisfaction in Middle Easterners, and age could explain an association between gender and sexual dysfunction in Swedes. Age, waist circumference, and 25(OH)D levels were significant covariates in the logistic regression models. Results from the present study suggest that 25(OH)D variation partly explains differences in sexual dysfunction between the groups and between genders within the groups. Vitamin D therapy should be investigated to determine if these results are clinically useful.