bluuebunny/crossref_metadata_2025 huggingface dataset:
Ipidacrine (Axamon), A Reversible Cholinesterase Inhibitor, Improves Erectile Function in Male Rats With Diabetes Mellitus-Induced Erectile Dysfunction
Authors: Bykov Vladimir , Gushchina Evgenia , Morozov Sergey , Zhuravskaya Natalia , Kryshen Kirill , Makarov Valery , Matichin Aleksandr , Zueva Alena
Published: January 2022

ABSTRACTS

Background

Management of diabetes mellitus-induced erectile dysfunction (DMED) is challenging because of its insufficient responses to phosphodiesterase type 5 inhibitors.

Aim

To compare the effects of ipidacrine, a reversible cholinesterase inhibitor, and sildenafil on DMED in a rat model of streptozotocin (STZ)-induced diabetes.

Methods

Erectile dysfunction (ED) caused by STZ-induced diabetes mellitus was modeled in adult male Wistar rats, which were randomized to 4 groups: untreated diabetic rats, sildenafil (5 mg/kg), ipidacrine (3.6 mg/kg) and ipidacrine (6.7 mg/kg). The test drug (ipidacrine), comparator (sildenafil) or control substance (1% starch solution) were administered orally for 5 days or 14 days. Erectile function was assessed by the change in the maximum intracavernous pressure (ICPmax) following cavernous nerve electrical stimulation. The mean arterial pressure (MAP) was recorded, and the ICPmax/MAP ratio was calculated. Sexual behavior, cholinesterase activity and blood testosterone level tests assessed.

Main Outcome Measure

The quantitative value of ICPmax/MAP 14 days after the start of administration of the test drug and the comparison drug.

Results

Animals with STZ-induced diabetes mellitus showed a significant decrease in ICPmax and ICPmax/MAP ratio compared to the intact control group. When ipidacrine was administered to rats with DMED for 14 days, an increase in these indicators was noted. It was proved that ipidacrine at a dose of 6.7 mg/kg has noninferiority compared to sildenafil on the DMED model. Significant increase in ICPmax compared to STZ-control after electrostimulation of the cavernous nerve was recorded following administration of ipidacrine at a dose of 6.7 mg/kg (P < .05) and sildenafil at a dose 5 mg/kg (P < .05). Neither the test drug, nor the comparator were associated with increase in testosterone levels in blood; as well both drugs did not promote activation of sexual behavior.

Clinical Implications

Ipidacrine may be considered as an effective therapy for DMED but needs to be verified in human investigations.

Strengths & Limitations

The role of ipidacrine, was firstly demonstrated in rats with DMED. However, the results were obtained in animal experiments, and will be further tested in the study of receptor interactions and the determination of cellular targets.

Conclusion

This is the first study to show that administration of ipidacrine, the reversible cholinesterase inhibitor, improved erectile function in diabetic rats and these results may be beneficial in further studies using ipidacrine for treatment of DMED, particularly in non-responders to PDE5 inhibitors.
Quantitative Proteomics Using Isobaric Labeling: A Practical Guide
Authors: Chen Xiulan , Sun Yaping , Zhang Tingting , Shu Lian , Roepstorff Peter , Yang Fuquan
Published: January 2022

In the past decade, relative proteomic quantification using isobaric labeling technology has developed into a key tool for comparing the expression of proteins in biological samples. Although its multiplexing capacity and flexibility make this a valuable technology for addressing various biological questions, its quantitative accuracy and precision still pose significant challenges to the reliability of its quantification results. Here, we give a detailed overview of the different kinds of isobaric mass tags and the advantages and disadvantages of the isobaric labeling method. We also discuss which precautions should be taken at each step of the isobaric labeling workflow, to obtain reliable quantification results in large-scale quantitative proteomics experiments. In the last section, we discuss the broad applications of the isobaric labeling technology in biological and clinical studies, with an emphasis on thermal proteome profiling and proteogenomics.
A Sampling‐Based Path Planning Algorithm for Improving Observations in Tropical Cyclones
Authors: Darko Justice , Folsom Larkin , Park Hyoshin , Minamide Masashi , Ono Masahiro , Su Hui
Published: January 2022

Lack of high‐resolution observations in the inner‐core of tropical cyclones remains a key issue when constructing an accurate initial state of the storm structure. The major implication of an improper initial state is the poor predictability of the future state of the storm. The size and associated hazard from strong winds at the inner‐core make it impossible to sample this region entirely. However, targeting regions of the inner‐core where forecasted atmospheric measurements have high uncertainty can significantly improve the accuracy of measurements for the initial state of the storm. This study provides a scheme for targeted high‐resolution observations for small Unmanned Aircraft Systems (sUAS) platforms (e.g., Coyote sUAS) to improve the estimates of the atmospheric measurement in the inner‐core structure. The benefit of observation is calculated based on the high‐fidelity state‐of‐the‐art hurricane ensemble data assimilation system. Potential locations with the most informative measurements are identified through exploration of various simulation‐based solutions depending on the state variables (e.g., pressure, temperature, wind speed, relative humidity) and a combined representation of those variables. A sampling‐based sUAS path planning algorithm considers energy usage when locating the regions of highly uncertain prediction of measurements, allowing sUAS to maximize the benefit of observation. Robustness analysis of our algorithm for multiple scenarios of sUAS drop and goal locations shows satisfactory performance against benchmark similar to current NOAA field campaign. With optimized sUAS observations, a data assimilation analysis shows significant improvements of up to 4% in the tropical cyclone structure estimates after resolving uncertainties at targeted locations.
Partitioning the Export of Distinct Biogenic Carbon Pools in the Northeast Pacific Ocean Using a Biogeochemical Profiling Float
Authors: Huang Yibin , Fassbender Andrea J. , Long Jacqueline S. , Johannessen Sophia , Bernardi Bif Mariana
Published: January 2022

We leverage observations from chemical and bio‐optical sensors mounted on a biogeochemical profiling float in the Northeast Pacific Ocean to quantify the cycling and export potential of distinct biogenic carbon pools, including particulate inorganic carbon (PIC), particulate organic carbon (POC), and dissolved organic carbon (DOC). Year‐round observations reveal complex carbon cycle dynamics among these carbon pools. Net DOC production peaked during bloom initiation, about 3 months prior to the summer peak in POC production. We validate the float estimates of DOC cycling with seasonal accumulation and removal rates derived from ship‐board DOC observations over the same period. By combining chemical and bio‐optical tracers of POC cycling, we estimate the instantaneous POC sinking flux (). The cooccurrence of DOC consumption and POC production and sinking during fall and winter resolves the regional conundrum of a persistent particle sinking flux observed by sediment traps during a season that is known to be heterotrophic. PIC production is small, and uncertainties are large. By combining float‐based estimates of instantaneous net primary production (NPP) and , we quantify a real‐time carbon export ratio ([/NPP] × 100%) for the euphotic zone. Elevated export ratios during summer are associated with an increase in the fraction of particles larger than 100 μm in size. Elevated export ratios during winter are associated with the physical redistribution of particles through seasonal deep mixing. Our study demonstrates how the combined use of multiple sensors on biogeochemical profiling floats can provide more nuanced information about upper ocean carbon cycle dynamics.
Volcanism‐Triggered Climatic Control on Late Cretaceous Oceans
Authors: Sun Ruiyang , Yao Hanwei , Deng Changzhou , Grasby Stephen E. , Wang Chengshan , Chen Xi , Yin Runsheng
Published: January 2022

During the Late Cretaceous, Earth's climate oscillated between warm and cool states, and global oceans changed between anoxic and oxic conditions, resulting in black/gray shales and oceanic red beds (ORBs) deposition, respectively. To understand such climate/ocean dynamics, this study investigated bulk Hg and Hg isotopes, as well as Fe3+/Fe2+ in Upper Cretaceous sediments deposited in southern Tibet and the North Atlantic. In both areas, black/gray shales show much higher Hg concentrations than ORBs, indicating enhanced Hg flux to global oceans during time of black/gray shale deposition. Black/gray shales show lower Fe3+/Fe2+ and positive Δ199Hg, suggesting a significant input of Hg into the anoxic/dysoxic ocean via atmospheric deposition. The isotope values are consistent with a volcanic source for this excess Hg. ORBs show high Fe3+/Fe2+ and negative shifts of Δ199Hg, suggesting that the dominant source of Hg into the oxic oceans was via terrestrial runoff. This study suggests that volcanism was an important driver of the climate/ocean dynamics during the Late Cretaceous.
The Source of Auroral Omegas
Authors: Weygand J. M. , El‐Alaoui M. , Nykyri H. K.
Published: January 2022

The auroral wave‐like structures called “omega bands” appear within the post‐midnight sector auroral oval with shapes resembling the Greek letter omega, and are typically associated with the recovery phase of substorms. Prior work and MHD simulations suggest both high speed earthward flows and post‐midnight flow shears are possible omega band source mechanisms. However, what produces omega bands is not well understood. It is most likely that the paucity of concurrent magnetospheric data has limited our ability to understand fully the mechanism responsible for the generation of the omega bands. We have identified about 263 auroral omegas in seven different THEMIS all sky cameras (ASCs) over a 10 year period. A fraction appear to form from north‐south streamers, but some appear to form from east‐west auroral arcs. Fifty‐one of the 263 Ω also have conjugate or near conjugate THEMIS and GOES spacecraft data. There is evidence in about 80% of these events that high speed earthward flows have occurred prior to or at about the same time as the auroral omega observation. This evidence consists of high speed earthward flows, magnetic field dipolarizations, particle injections into the inner magnetosphere, and auroral streamers. 11 events also show plasma flow data azimuthally along the inner magnetosphere, but for six of these events the Vy component is inconsistent with the auroral omega direction of motion. Of the remaining five events, four have Vy flow shear events but also show evidence of magnetic field dipolarizations, particle injections into the inner magnetosphere, and auroral streamers. Our observations suggest high speed earthward flows are more likely to be the source of auroral omega bands.
The Effect of Fault Roughness and Earthquake Ruptures on the Evolution and Scaling of Fault Damage Zones
Authors: Tal Yuval , Faulkner Daniel
Published: January 2022

Fault damage zones dominate the mechanical, hydraulic and seismological properties of faults yet the relative contributions from processes leading to their development and growth is obscure. In this study, we investigate the damage development related to slip on rough faults and passage of earthquake ruptures. We compare the cumulative damage with slip and damage distribution from numerical models against field data from exhumed faults with slip less than 3.5 m within the Atacama Fault Zone in northern Chile. Models are constrained by experimentally determined mechanical properties of the host rock. We perform simulations of damage accumulation during quasistatic slip on rough faults and during sequences of earthquakes on planar and rough faults governed by rate and state friction laws. Both sets of simulations include Drucker–Prager rheology of the bulk to identify off‐fault damage where the yield stress is exceeded. Our results indicate that the extent and distribution of damage depend on the characteristics of fault roughness, amount of slip, and, when present, the intensity and variability of dynamic ruptures. When typical values for fault roughness are used, the scaling of damage zone width versus slip during quasistatic slip is comparable to that observed in the field data. Earthquake rupture on smooth faults by itself does not explain the field data. Simulations of earthquake sequences on rough faults leads to significantly larger damage zone widths with slip than that observed in the field data, suggesting the development of damage for small displacement is dominated by quasistatic slip on rough faults.
On the Groupiness and Intermittency of Oceanic Whitecaps
Authors: Malila M. P. , Thomson J. , Breivik Ø. , Benetazzo A. , Scanlon B. , Ward B.
Published: January 2022

The enhancement of wave breaking activity during wave group passage is investigated using coherent field observations of the instantaneous sea surface elevation and whitecap coverage from platform‐based stereo video measurements in the central North Sea. Passing wave groups are shown to be associated with a two to threefold enhancement in the probability distribution of total whitecap coverage W whereas the enhancement of active whitecap coverage WA is approximately fivefold. Breaking time scales and intermittency characteristics are also investigated with the inclusion of a secondary data set of W and WA observations collected during a research cruise in the North Pacific. The time scale analysis suggests a universal periodicity in wave breaking activity within a representative sea‐surface area encompassing approximately one dominant wave crest. The breaking periodicity is shown to be closely linked to the peak period of the dominant wave components, suggesting that long‐wave modulation of wave breaking is a predominant mechanism controlling the intermittency of wave breaking across scales.
Depthwise Soil CO2 Production Is Controlled by Freeze‐Thaw Processes in a Tibetan Alpine Steppe
Authors: Zhang Jianxin , Wei Da , Hong Jiangtao , Wang Xiaodan
Published: January 2022

Cold ecosystems in regions of high‐latitude and altitude with vast stores of soil organic carbon suffer strong freeze‐thaw cycles, which can greatly affect soil CO2 release. However, on the Tibetan Plateau, where altitude is >4,000 m, it remains unknown how freeze‐thaw processes regulate CO2 production across the soil profile. In this study, we used the gradient method to explore impacts of freeze‐thaw processes on depthwise soil CO2 production in an alpine steppe. We found almost all soil CO2 was produced in the root‐zone layer (<30 cm), while the root‐free layer (>30 cm) frequently alternated between being a source and sink of CO2 and thus acted largely as a buffer. The surface layer (0–15 cm) and subsurface layer (15–30 cm) had a similar CO2 production rate in the thawed period. However, during the freezing‐frozen‐thawing period, the subsurface layer consistently functioned as a weak CO2 source, although parts were trapped in frozen soil, resulting in a weaker CO2 sink in the surface layer. Soil CO2 production in subsurface layer is thus more sensitive to temperature variability compared with surface layer. Furthermore, our results suggest water content plays a more important role than temperature in regulating soil CO2 production. For the first time, our data set reveals the vertical production of CO2 within the seasonally frozen soils on the Tibetan Plateau, which will benefit understanding of belowground carbon processes and modeling of soil CO2 release in the region.
Influences of 3D Sub‐Grid Terrain Radiative Effect on the Performance of CoLM Over Heihe River Basin, Tibetan Plateau
Authors: Zhang Xindan , Huang Anning , Dai Yongjiu , Li Weiping , Gu Chunlei , Yuan Hua , Wei Nan , Zhang Yanlin , Qiu Bo , Cai Shuxin
Published: January 2022

Surface solar radiation (SSR), as a primary component of heat budget between land and atmosphere, controls both water and energy exchanges. However, the sub‐grid terrain radiative effect (STRE) which exerts critical influences on SSR simulation is usually extremely simplified or even ignored in most current land surface models (LSMs) due to the heavy computational burden. In this study, we developed a physically realistic and computationally efficient three dimensional (3D) STRE scheme and implemented it into the Common Land Model (CoLM) to indicate its quantitative influences on surface energy budget, land surface temperature (LST), soil temperature, and moisture simulations over the Heihe River Basin, Tibetan Plateau. Results show that the CoLM coupled with 3D‐STRE scheme shows more realistic description of SSR and improves the simulation of soil thermal and moist features at both single‐point and regional scales. Compared to the results without 3D‐STRE, the inclusion of 3D‐STRE scheme efficiently diminishes the overestimation of SSR, which leads to the root mean square error (RMSE) of LST simulation reduced by 17.1% due to significant improvements in valley areas. Adopting 3D‐STRE scheme also improves the pattern and amplitude of temporal variability of simulated soil temperature (moisture) at 37 sites with the mean Taylor score increased by 3.6–3.7% (14.0–14.3%). These results emphasize the importance of considering the 3D‐STRE scheme in LSMs and are significantly helpful to deepen our understanding of surface heat exchanges and improve the representations of land surface processes over complex terrain.
Hydrothermal Microbes Can Be Green Energy Producers
Authors: Derouin Sarah
Published: January 2022

In ultramafic, reducing environments, forming microbial proteins can actually release energy.
Application of deep learning algorithm on whole genome sequencing data uncovers structural variants associated with multiple mental disorders in African American patients
Authors: Liu Yichuan , Qu Hui-Qi , Mentch Frank D. , Qu Jingchun , Chang Xiao , Nguyen Kenny , Tian Lifeng , Glessner Joseph , Sleiman Patrick M. A. , Hakonarson Hakon
Published: January 2022

Mental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patients who have more than one type of mental disorder, especially for young toddlers who are not able to complete questionnaires or standardized rating scales for diagnosis. In the past decade, multiple genomic association signals have been reported for mental disorders, some of which present attractive drug targets. Concurrently, machine learning algorithms, especially deep learning algorithms, have been successful in the diagnosis and/or labeling of complex diseases, such as attention deficit hyperactivity disorder (ADHD) or cancer. In this study, we focused on eight common mental disorders, including ADHD, depression, anxiety, autism, intellectual disabilities, speech/language disorder, delays in developments, and oppositional defiant disorder in the ethnic minority of African Americans. Blood-derived whole genome sequencing data from 4179 individuals were generated, including 1384 patients with the diagnosis of at least one mental disorder. The burden of genomic variants in coding/non-coding regions was applied as feature vectors in the deep learning algorithm. Our model showed ~65% accuracy in differentiating patients from controls. Ability to label patients with multiple disorders was similarly successful, with a hamming loss score less than 0.3, while exact diagnostic matches are around 10%. Genes in genomic regions with the highest weights showed enrichment of biological pathways involved in immune responses, antigen/nucleic acid binding, chemokine signaling pathway, and G-protein receptor activities. A noticeable fact is that variants in non-coding regions (e.g., ncRNA, intronic, and intergenic) performed equally well as variants in coding regions; however, unlike coding region variants, variants in non-coding regions do not express genomic hotspots whereas they carry much more narrow standard deviations, indicating they probably serve as alternative markers.
Electrochemically controlled ON/OFF switching of NaBH4 hydrolysis based on NiMoN@NC for on-demand hydrogen production
Authors: He Baoying , Zhuang Shuxian , Tai Xuefeng , Xie Ao , Lou Weihao , Tang Yang , Chen Yongmei , Wan Pingyu
Published: January 2022

A novel electrochemical strategy to conveniently control the hydrolysis of sodium borohydride is proposed for on-demand hydrogen generation through modulating the surface state of the NiMoN@NC electrode by applying selected potentials.
Synthesis of methyl glycolate by hydrogenation of dimethyl oxalate with a P modified Co/SiO2 catalyst
Authors: Zhuang Zailang , Li Yihui , Chen Fang , Chen Xingkun , Li Zheng , Wang Shiyi , Wang Xuepeng , Zhu Hejun , Tan Yuan , Ding Yunjie
Published: January 2022

A P-modified Co/SiO2 catalyst exhibited excellent performance in selective hydrogenation of dimethyl oxalate to methyl glycolate.
Nano-scale insights regarding coke formation in zeolite SSZ-13 subject to the methanol-to-hydrocarbons reaction
Authors: van Vreeswijk S. H. , Monai M. , Oord R. , Schmidt J. E. , Vogt E. T. C. , Poplawsky J. D. , Weckhuysen B. M.
Published: January 2022

A correlation between the micro- and nano-scale coking behavior of SSZ-13 was discovered within situ/operandospectroscopy and atom probe tomography (APT), which allows for spatial reconstruction and analysis of relations between framework elements and carbon atoms.
High-k dielectric screen-printed inks for mechanical energy harvesting devices
Authors: Leese Hannah S. , Tejkl Miroslav , Vilar Laia , Georgi Leopold , Yau Hin Chun , Rubio Noelia , Reixach Elisenda , Buk Jan , Jiang Qixiang , Bismarck Alexander , Hahn Robert , Shaffer Milo S. P.
Published: January 2022

Mechanical energy harvesting devices can scavenge low-frequency energy from regular biomotion. Here, the harvester exploits printed nanocomposite dielectric inks in combination with commercial conductive elastomers to produce a low-cost, high-performance embodiment of a variable capacitance mechanism device.
Reusable citric acid modified V/AC catalyst prepared by dielectric barrier discharge for hydroxylation of benzene to phenol
Authors: Li Xiuying , Li Siyu , Jia Wenting , Sun Qi , Zhang Yue
Published: January 2022

A reusable and efficient citric acid modified V/AC catalyst for benzene hydroxylation was prepared using an environmentally benign DBD method.
NHC-catalyzed [4 + 2] annulations of allenoates and 2,3-dioxopyrrolidine derivatives
Authors: Song Xue , Chen Yangxu , Lu Fangfang , Zhang Kai , Yu Chenxia , Li Tuanjie , Yao Changsheng
Published: January 2022

A facile NHC-catalyzed [2+4] annulation of allenoates with 2,3-dioxypyrrolidine derivatives was discovered, which paved a new avenue to the construction of highly substituted pyranopyrrole with moderate to good yields.
Transaminases as suitable catalysts for the synthesis of enantiopure β,β-difluoroamines
Authors: García-Ramos Marina , Lavandera Iván
Published: January 2022

Transaminases are able to catalyze the amination of α,α-difluorinated ketones with high stereoselectivity using a small excess of the amine donor to give access to the corresponding enantiopure β,β-difluoroamines.
Fabrication of an amorphous metal oxide/p-BiVO4 photocathode: understanding the role of entropy for reducing nitrate to ammonia
Authors: Wang Fengfeng , Ding Qijia , Bai Yajie , Bai Hongye , Wang Song , Fan Weiqiang
Published: January 2022

Entropy regulation makes an amorphous metal oxide/p-BiVO4 heterostructure a desirable catalyst for the NO3− reduction reaction in a photoelectrochemical system.
Anti-solvatochromic and highly emissive twisted D–A structure with intramolecular hydrogen bond
Authors: Liang Hong-Wen , Jia Tian , Wang Zhen-Zhen , Wang Jia-Qi , Hou Da-Yong , Wang Lei , Gao Xingfa , Sun He-Lue , Wang Hao
Published: January 2022

We construct a D–A type fluorescent dye via modification of its structural engineering, and exhibit almost the same quantum yields with the increase of solvent polarity. Furthermore, it shows good emission efficiency in the solid state.
Multi‐scale attention encoder for street‐to‐aerial image geo‐localization
Authors: Li Songlian , Tu Zhigang , Chen Yujin , Yu Tan
Published: January 2022

The goal of street‐to‐aerial cross‐view image geo‐localization is to determine the location of the query street‐view image by retrieving the aerial‐view image from the same place. The drastic viewpoint and appearance gap between the aerial‐view and the street‐view images brings a huge challenge against this task. In this paper, we propose a novel multiscale attention encoder to capture the multiscale contextual information of the aerial/street‐view images. To bridge the domain gap between these two view images, we first use an inverse polar transform to make the street‐view images approximately aligned with the aerial‐view images. Then, the explored multiscale attention encoder is applied to convert the image into feature representation with the guidance of the learnt multiscale information. Finally, we propose a novel global mining strategy to enable the network to pay more attention to hard negative exemplars. Experiments on standard benchmark datasets show that our approach obtains 81.39% top‐1 recall rate on the CVUSA dataset and 71.52% on the CVACT dataset, achieving the state‐of‐the‐art performance and outperforming most of the existing methods significantly.
A low‐power fast‐switching write‐and‐standby shared assist circuit for low‐voltage SRAMs
Authors: Wang Jinn‐Shyan , Liu Chien‐Tung , Liu Zhi‐Rong , Wang Shao‐Zhi , Kang Jyun‐Jiea
Published: January 2022

Assist circuitry helps the SRAM to lower the supply voltage VDD to reduce power consumption. Separately designed read, write, and standby assists for low voltage (LV) are not area‐ and power‐efficient. This paper proposes a fast‐switching VDD‐lowering circuit without inducing direct current to achieve a single low‐power write‐and‐standby shared assist circuit. Experimental results verify that the proposed assist can achieve significant power reduction no matter in the write or the standby modes.
Semantically guided self‐supervised monocular depth estimation
Authors: Lu Xiao , Sun Haoran , Wang Xiuling , Zhang Zhiguo , Wang Haixia
Published: January 2022

Depth information plays an important role in the vision‐related activities of robots and autonomous vehicles. An effective method to obtain 3D scene information is self‐supervised monocular depth estimation, which utilizes large and diverse monocular video datasets during the training process without the need for ground‐truth data. A novel multi‐task learning strategy that uses semantic information to guide the monocular depth estimation method while maintaining self‐supervision is proposed. An improved differential direct visual odometer (DDVO) combined with Pose‐Net is applied for achieving better pose prediction. Minimum reprojection loss with auto‐masking and semantic masking is used to remove the effects of low‐texture areas and moving dynamic‐class objects within scenes. Concurrently, the semantic masking is introduced into the DDVO pose predictor to filter moving objects and reduce the matching error between monocular sequence frames. In addition, PackNet is employed as the backbone of multi‐task learning to further improve the accuracy of deep prediction. The proposed method produces state‐of‐the‐art results for monocular depth estimation on the KITTI Eigen split benchmark, even outperforming supervised methods that have been trained using ground‐truth depth.
One‐shot learning‐based driver's head movement identification using a millimetre‐wave radar sensor
Authors: Nguyen Hong Nhung , Lee Seongwook , Nguyen Tien‐Tung , Kim Yong‐Hwa
Published: January 2022

Concentration of drivers on traffic is a vital safety issue; thus, monitoring a driver being on road becomes an essential requirement. The key purpose of supervision is to detect abnormal behaviours of the driver and promptly send warnings to him/her for avoiding incidents related to traffic accidents. In this paper, to meet the requirement, based on radar sensors applications, the authors first use a small‐sized millimetre‐wave radar installed at the steering wheel of the vehicle to collect signals from different head movements of the driver. The received signals consist of the reflection patterns that change in response to the head movements of the driver. Then, in order to distinguish these different movements, a classifier based on the measured signal of the radar sensor is designed. However, since the collected data set is not large, in this paper, the authors propose One‐shot learning to classify four cases of driver's head movements. The experimental results indicate that the proposed method can classify the four types of cases according to the various head movements of the driver with a high accuracy reaching up to 100%. In addition, the classification performance of the proposed method is significantly better than that of the convolutional neural network (CNN) model.
Green Synthesis of Diaryl Selenides from Arylboronic Acids and Arylseleninic Acids
Authors: Redon Sébastien , Vanelle Patrice , Remusat Vincent
Published: January 2022

A new method of deborylative selanylation using arylboronic acids and arylseleninic acids gave diaryl selenoethers and diarylselenoxide. The present approach requires only equimolar arylseleninic acid and led selectively to selenoethers or selenoxides depending on the solvent. The method is metal-free, base- or oxidant-free, efficient, and environmentally friendly.
Moving beyond velocity derivatives; using global positioning system data to extract sequential movement patterns at different levels of rugby league match‐play
Authors: Collins Neil , White Ryan , Palczewska Anna , Weaving Dan , Dalton‐Barron Nicholas , Jones Ben
Published: January 2022

This study aims to (a) quantify the movement patterns during rugby league match‐play and (b) identify if differences exist by levels of competition within the movement patterns and units through the sequential movement pattern (SMP) algorithm. Global Positioning System data were analysed from three competition levels; four Super League regular (regular‐SL), three Super League (semi‐)Finals (final‐SL) and four international rugby league (international) matches. The SMP framework extracted movement pattern data for each athlete within the dataset. Between competition levels, differences were analysed using linear discriminant analysis (LDA). Movement patterns were decomposed into their composite movement units; then Kruskal–Wallis rank‐sum and Dunn post‐hoc were used to show differences. The SMP algorithm found 121 movement patterns comprised mainly of “walk” and “jog” based movement units. The LDA had an accuracy score of 0.81, showing good separation between competition levels. Linear discriminant 1 and 2 explained 86% and 14% of the variance. The Kruskal–Wallis found differences between competition levels for 9 of 17 movement units. Differences were primarily present between regular‐SL and international with other combinations showing less differences. Movement units which showed significant differences between competition levels were mainly composed of low velocities with mixed acceleration and turning angles. The SMP algorithm found 121 movement patterns across all levels of rugby league match‐play, of which, 9 were found to show significant differences between competition levels. Of these nine, all showed significant differences present between international and domestic, whereas only four found differences present within the domestic levels. This study shows the SMP algorithm can be used to differentiate between levels of rugby league and that higher levels of competition may have greater velocity demands.

Highlights

This study shows that movement patterns and movement units can be used to investigate team sports through the application of the SMP framework

One hundred and twenty‐one movement patterns were found to be present within rugby league match‐play, with the walk‐ and jog‐based movement units most prevalent. No movement pattern was unique to a single competition level.

Further analysis revealed that the majority of movement units analysed had significant differences between international and domestic rugby league, whereas only four movement units (i.e. f,m,n,q) had significant differences within the two domestic rugby league levels.

International rugby league had higher occurrences of the movement patterns consisting of higher velocity movement units (ie. T,S,y). This suggests that international rugby league players may need greater high velocity exposure in training.
A hybrid framework to predict ski jumping forces by combining data‐driven pose estimation and model‐based force calculation
Authors: Nam Yunhyoung , Do Youngkyung , Kim Jaehoon , Lee Heonyong , Kim Do‐Nyun
Published: January 2022

The aim of this paper is to propose a hybrid framework that combines a data‐driven pose estimation with model‐based force calculation in order to predict the ski jumping force from a recorded motion video. A skeletal model consisting of five joints (ear, hip, knee, ankle, and toe) and four rigid segments (head/arm/trunk or HAT, thigh, shank, and foot) connecting each joint is developed. The joint forces are calculated from the dynamic equilibrium equations, which requires the time history of joint coordinates. They are estimated from a recorded motion video using a deep neural network for pose estimation trained with human motion data. Joint coordinates can be obtained by the proposed deep neural network directly from images of jumping motion without using any markers. The validity and usefulness of the proposed method are confirmed in lab experiments. Further, our method is practically applicable to the study in a real competition environment because it is not required to attach any sensor or marker to athletes.

Highlights

A method to predict the ski jumping force from a recorded motion video is proposed.

It combines a data‐driven pose estimation with a model‐based force calculation.

The proposed method does not require any markers and sensors to be attached to athletes.

In a laboratory environment, the relative error in the maximum jumping force is less than 7%.

The method can be easily applied to a field study in a real competition environment.
Spatiotemporal dynamic of environmental indices of watershed sustainability in connection with land-use change
Authors: Mirchooli Fahimeh , Sadeghi Seyed Hamidreza , Khaledi Darvishan Abdulvahed
Published: January 2022

Exploring spatial and temporal land-use changes is valuable for local governments to address issues of sustainability and planning policy where urbanization and industrialization are taking place. Besides anthropogenic effects, natural driving forces like climate change may also affect sustainability. However, such relationships have not been studied minutely. Hence, this study first investigates the land-use changes and their relationship with land surface temperature (LST) for the Shazand Watershed, Iran, in 1986, 1998, 2008, and 2016 coincided with supplementary industrialization stages. Furthermore, the relations among LST and other biophysical parameters, including Normalized Difference Vegetation Index (NDVI), Normalized Difference Buildup Index (NDBI), and Normalized Difference Water Index (NDWI), were analyzed, and corresponding variations were explored. The results indicated that the mean LST of the study watershed has an increasing trend from 1986 to 2008 due to land-use change and drought intensification. Later, LST decreased in 2016. Lower LST was associated with irrigation farming and orchard, and higher LST was related to sparse oak forest areas. There was also a negative correlation between LST and NDVI. As a result, it was inferred that greenery declined LST. Conversely, a positive correlation was found between LST and NDBI resulting from the built-up areas. Since LST could influence biological, physical, chemical processes, it can therefore be supported as an effective index for environmental sustainability assessment.
In situ quantification of NO synthesis in a warm air glow discharge by WMS-based Mid-IR QCL absorption spectroscopy
Authors: WANG Chuanqi , QIAO Junjie , SONG Yijia , YANG Qi , WANG Dazhi , ZHANG Qingyuan , SHU Zhan , XIONG Qing
Published: January 2022

Nitric oxide (NO) is one of the most crucial products in the plasma-based nitrogen fixation process. In this work, in situ measurements were performed for quantifying the NO synthesis spatially in a warm air glow discharge, through the method of Mid-infrared quantum cascade laser absorption spectroscopy (QCL-AS). Two ro-vibrational transitions at 1900.076 cm−1 and 1900.517 cm−1 of the ground-state NO(X) were probed sensitively by the help of the wavelength modulation spectroscopy (WMS) approach to increase the signal/noise (S/N) level. The results show a decline trend of NO synthesis rate along the discharge channel from the cathode to the anode. However, from the point of energy efficiency, the cathode region is of significantly low energy efficiency of NO production. Severe disproportionality was found for the high energy consumption but low NO production in the region of cathode area, compared to that in the positive column zone. Further analysis demonstrates the high energy cost of NO production in the cathode region, is ascribed to the extremely high reduced electric field

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therein not selectively preferable for the processes of vibrational excitation or dissociation of N2 and O2 molecules. This drags down the overall energy efficiency of NO synthesis by this typical warm air glow discharge, particularly for the ones with short electrode gaps. Limitations of further improving the energy cost of NO synthesis by variations of the discharge operation conditions, such as discharge current or airflow rate, imply other effective manners able to tune the energy delivery selectively to the NO formation process, are sorely needed.
MS-Decipher: a user-friendly proteome database search software with an emphasis on deciphering the spectra of O-linked glycopeptides
Authors: Mao Jiawei , Zhu He , Liu Luyao , Fang Zheng , Dong Mingming , Qin Hongqiang , Ye Mingliang
Published: January 2022

Motivation

The interpretation of mass spectrometry (MS) data is a crucial step in proteomics analysis, and the identification of post-translational modifications (PTMs) is vital for the understanding of the regulation mechanism of the living system. Among various PTMs, glycosylation is one of the most diverse ones. Though many search engines have been developed to decipher proteomic data, some of them are difficult to operate and have poor performance on glycoproteomic datasets compared to advanced glycoproteomic software.

Results

To simplify the analysis of proteomic datasets, especially O-glycoproteomic datasets, here, we present a user-friendly proteomic database search platform, MS-Decipher, for the identification of peptides from MS data. Two scoring schemes can be chosen for peptide-spectra matching. It was found that MS-Decipher had the same sensitivity and confidence in peptide identification compared to traditional database searching software. In addition, a special search mode, O-Search, is integrated into MS-Decipher to identify O-glycopeptides for O-glycoproteomic analysis. Compared with Mascot, MetaMorpheus and MSFragger, MS-Decipher can obtain about 139.9%, 48.8% and 6.9% more O-glycopeptide-spectrum matches. A useful tool is provided in MS-Decipher for the visualization of O-glycopeptide-spectra matches. MS-Decipher has a user-friendly graphical user interface, making it easier to operate. Several file formats are available in the searching and validation steps. MS-Decipher is implemented with Java, and can be used cross-platform.

Availability and implementation

MS-Decipher is freely available at https://github.com/DICP-1809/MS-Decipher for academic use. For detailed implementation steps, please see the user guide.

Supplementary information

Supplementary data are available at Bioinformatics online.
ProteinBERT: a universal deep-learning model of protein sequence and function
Authors: Brandes Nadav , Ofer Dan , Peleg Yam , Rappoport Nadav , Linial Michal
Published: January 2022

Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. However, existing models and pretraining methods are designed and optimized for text analysis. We introduce ProteinBERT, a deep language model specifically designed for proteins. Our pretraining scheme combines language modeling with a novel task of Gene Ontology (GO) annotation prediction. We introduce novel architectural elements that make the model highly efficient and flexible to long sequences. The architecture of ProteinBERT consists of both local and global representations, allowing end-to-end processing of these types of inputs and outputs. ProteinBERT obtains near state-of-the-art performance, and sometimes exceeds it, on multiple benchmarks covering diverse protein properties (including protein structure, post-translational modifications and biophysical attributes), despite using a far smaller and faster model than competing deep-learning methods. Overall, ProteinBERT provides an efficient framework for rapidly training protein predictors, even with limited labeled data.

Availability and implementation

Code and pretrained model weights are available at https://github.com/nadavbra/protein_bert.

Supplementary information

Supplementary data are available at Bioinformatics online.
Benchmarking the empirical accuracy of short-read sequencing across theM. tuberculosisgenome
Authors: Marin Maximillian , Vargas Roger , Harris Michael , Jeffrey Brendan , Epperson L Elaine , Durbin David , Strong Michael , Salfinger Max , Iqbal Zamin , Akhundova Irada , Vashakidze Sergo , Crudu Valeriu , Rosenthal Alex , Farhat Maha Reda
Published: January 2022

Motivation

Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content.

Results

Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision (<99%) was tuning the mapping quality filtering threshold, i.e. confidence of the read mapping (recall = 85.8%, precision = 99.1%, MQ ≥ 40). Additional masking of repetitive sequence content is an alternative conservative approach to variant calling that increases precision at cost to recall (recall = 70.2%, precision = 99.6%, MQ ≥ 40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52/168 PE/PPE genes (34.5%). From these results, we present a refined list of low confidence regions across the Mtb genome, which we found to frequently overlap with regions with structural variation, low sequence uniqueness and low sequencing coverage. Our benchmarking results have broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems and more generally for WGS applications in other organisms.

Availability and implementation

All relevant code is available at https://github.com/farhat-lab/mtb-illumina-wgs-evaluation.

Supplementary information

Supplementary data are available at Bioinformatics online.
Sirt1 attenuates astrocyte activation via modulating Dnajb1 and chaperone-mediated autophagy after closed head injury
Authors: Zhang Zhuo , Zhang Xu , Wu Xin , Zhang Yan , Lu Jie , Li Dan
Published: January 2022

Our previous study indicates that Silent information regulator 1 (Sirt1) is involved in macroautophagy by upregulating light chain 3 (LC3) expression in astrocyte to exert a neuroprotective effect. Chaperon-mediated autophagy (CMA), another form of autophagy, is also upregulated after brain injury. However, little is known about the role of Sirt1 in regulation of the CMA. In the present study, an in vivo model of closed head injury (CHI) and an in vitro model of primary cortical astrocyte stimulated with interleukin-1β were employed to mimic the astrocyte activation induced by traumatic brain injury. Lentivirus carrying target complementary DNA (cDNA) or short hairpin RNA (shRNA) sequence was used to overexpress Sirt1 or knockdown DnaJ heat shock protein family member B1 (Dnajb1) (a molecular chaperone). We found that Sirt1 overexpression ameliorated neurological deficits, reduced tissue loss, and attenuated astrocyte activation after CHI, which was reversed by Dnajb1-shRNA administration. The upregulation of CMA activity induced by CHI in vivo and in vitro was inhibited after Dnajb1 knockdown. Sirt1 potently promoted CMA activity via upregulating Dnajb1 expression. Mechanically, Sirt1 could interact with Dnajb1 and modulate the deacetylation and ubiquitination of Dnajb1. These findings collectively suggest that Sirt1 plays a protective role against astrocyte activation, which may be associated with the regulation of the CMA activity via modulating the deacetylation and ubiquitination of Dnajb1 after CHI.
Impact of Biannual Mass Azithromycin Treatment on Enteropathogen Carriage in Children <5 Years Old in Niger
Authors: Platts-Mills James A , Ayoub Elias G , Zhang Jixian , McQuade Elizabeth T Rogawski , Arzika Ahmed M , Maliki Ramatou , Abdou Amza , Keenan Jeremy D , Lietman Thomas M , Liu Jie , Houpt Eric R
Published: January 2022

We analyzed samples obtained at baseline and 24 months in a mass azithromycin administration trial in Niger using quantitative polymerase chain reaction. In villages randomized to azithromycin, Shigella was the only pathogen reduced at 24 months (prevalence ratio, 0.36 [95% confidence interval: .17–.79]; difference in log quantity, −.42 [−.75 to −.10]).