bluuebunny/crossref_metadata_2025_split huggingface dataset:
Informative community structure revealed using Arabidopsis time series transcriptome data via partitioned local depth
Authors: Khoury Maleana G , Berenhaut Kenneth S , Moore Katherine E , Allen Edward E , Harkey Alexandria F , Mühlemann Joëlle K , Craven Courtney N , Xu Jiayi , Jain Suchi S , John David J , Norris James L , Muday Gloria K 
Published: November 2023

Abstract
Transcriptome studies that provide temporal information about transcript abundance facilitate identification of gene regulatory networks (GRNs). Inferring GRNs from time series data using computational modeling remains a central challenge in systems biology. Commonly employed clustering algorithms identify modules of like-responding genes but do not provide information on how these modules are interconnected. These methods also require users to specify parameters such as cluster number and size, adding complexity to the analysis. To address these challenges, we used a recently developed algorithm, partitioned local depth (PaLD), to generate cohesive networks for 4 time series transcriptome datasets (3 hormone and 1 abiotic stress dataset) from the model plant Arabidopsis thaliana. PaLD provided a cohesive network representation of the data, revealing networks with distinct structures and varying numbers of connections between transcripts. We utilized the networks to make predictions about GRNs by examining local neighborhoods of transcripts with highly similar temporal responses. We also partitioned the networks into groups of like-responding transcripts and identified enriched functional and regulatory features in them. Comparison of groups to clusters generated by commonly used approaches indicated that these methods identified modules of transcripts that have similar temporal and biological features, but also identified unique groups, suggesting that a PaLD-based approach (supplemented with a community detection algorithm) can complement existing methods. These results revealed that PaLD could sort like-responding transcripts into biologically meaningful neighborhoods and groups while requiring minimal user input and producing cohesive network structure, offering an additional tool to the systems biology community to predict GRNs.
A comparison of empirical and mechanistic models for wheat yield prediction at field level in Moroccan rainfed areas
Authors: Mamassi Achraf , Lang Marie , Tychon Bernard , Lahlou Mouanis , Wellens Joost , El Gharous Mohamed , Marrou Hélène 
Published: November 2023

Abstract
In the context of climate change, in-season and longer-term yield predictions are needed to anticipate local and regional food crises and propose adaptations to farmers’ practices. Mechanistic models and machine learning are two modelling options to consider from this perspective. In this study, multiple regression (MR) and random forest (RF) models were calibrated for wheat yield prediction in Morocco, using data collected from 125 farmers’ wheat fields. Additionally, MR and RF models were calibrated both with or without remotely sensed leaf area index (LAI), while considering all farmers’ fields, or specifically to agroecological zoning in Morocco. The same farmers’ fields were simulated using a mechanistic model (APSIM-wheat). We compared the predictive performances of the empirical models and APSIM-wheat. Results showed that both MR and RF showed rather good predictive quality (normalized root mean square errors (NRMSEs) below 35 %), but were always outperformed by the APSIM model. Both RF and MR selected remotely sensed LAI at heading, climate variables (maximal temperatures at emergence and tillering), and fertilization practices (amount of nitrogen applied at heading) as major yield predictors. Integration of remotely sensed LAI in the calibration process reduced NRMSE by 4.5 % and 1.8 % on average for MR and RF models, respectively. Calibration of region-specific models did not significantly improve the predictive. These findings lead to the conclusion that mechanistic models are better at capturing the impacts of in-season climate variability and would be preferred to support short-term tactical adjustments to farmers’ practices, while machine learning models are easier to use in the perspective of mid-term regional prediction.
Reverse Flow Injection Spectrophotometric Determination of Total Acidity in Beverages Using Butterfly Pea Flower Extract
Authors: Deecharoenchaiyakul Patpitcha , Tangtreamjitmun Napa 
Published: November 2023

Abstract

Background
Monitoring total acidity during beverage production is crucial for quality control (QC). The standard acid–base titration, though widely used, is slow and generates hazardous waste through the use of acid–base indicators.

Objective
To develop an analysis method for beverage samples to determine total acidity using a natural reagent from butterfly pea flower as the colorimetric reagent.

Methods
The determination of total acidity in beverages was based on the reaction of citric acid with anthocyanin extracted from butterfly pea flowers. The decreased absorbance of anthocyanin was measured at 620 nm. A two-line reverse flow injection manifold was used to perform online dilution of samples.

Results
Under optimal conditions, the calibration curve equation 1/A = 0.03782C + 0.00241 (A = absorbance and C = concentration) was linear over a range of 0.050–0.25% (w/v) citric acid. The LOD and LOQ were 0.0123 and 0.0409% (w/v), respectively. The system achieved a throughput of 120 samples per hour with comparable accuracy and precision to the standard titrimetric method.

Conclusion
The injection of butterfly pea flower extract into beverage samples with online dilution in a reverse flow injection system (FIS) was reported for the first time for the determination of total acidity.

Highlights
Use of a green reagent in the method reflects its alignment with the principles of green analytical chemistry, providing a rapid and straightforward solution.
Novel synthetic biological study on intracellular distribution of human GlcNAc-1-phosphotransferase expressed in insect cells
Authors: Kiriyama Kei , Fujioka Keisuke , Kawai Kaito , Mizuno Teru , Shinohara Yasuo , Itoh Kohji 
Published: November 2023

Abstract
Many lysosomal enzymes contain N-glycans carrying mannose 6-phosphate (M6P) residues. Modifying lysosomal enzymes by M6P residues requires a two-step process in the Golgi apparatus. Then the lysosomal enzymes with M6P residues are transported from the trans-Golgi network to endosomes and lysosomes by M6P receptors. In insect cells, M6P residues are not added to N-glycans. Therefore, many insect lysosomal enzymes are transported to lysosomes by the M6P-independent pathway. The expression and subcellular distribution of M6P-modifying enzymes were examined by amplifying DNA fragments of M6P-modifying enzymes, generating the corresponding plasmid constructs, and transfection each construct into Sf9 cells, an insect cell line. The human GlcNac-1-phosphotransferase α/β subunit, one of the M6P-modifying enzymes, was found to differ in maturation and localization between mammalian and insect cells. In mammalian cells, newly biosynthesized α/β subunit localized in the cis-Golgi. In Sf9 cells, most of the α/β subunit was localized in the endoplasmic reticulum, and few mature forms of α/β subunit were observed. However, by the co-expression of the human site-1 protease, the mature forms were observed significantly and co-localization with each protein. Our study indicates new insights into regulating the intracellular distribution of the human GlcNac-1-phosphotransferase α/β subunit in insect cells.
Exploratory comparison of flower visiting behavior and pollination ability of mason bees, bumble bees, and honey bees
Authors: Lyu Zhaoyun , Zhou Ting , Sun Meng , Feng Min , Guo Wenxiu , Nie Lei , Song Yingying , Men Xingyuan , Li Lili , Yu Yi 
Published: November 2023

Abstract
This study explored the flower visiting behaviors and pollination abilities of mason bees (Osmia excavata Alfken (Hymenoptera: Megachilidae)), bumble bees (Bombus terrestris (Linnaeus, 1758) (Hymenoptera: Apidae)), and Italian honey bees (Apis mellifera ligustica Spinola (Hymenoptera: Apidae)) in apple orchards in early spring in Jinan (located in the central region of Shandong) and Yantai (located in the Peninsula of Shandong). We compared the pollen collection patterns, flower visiting behavior, flying speed, and effects on apple pollination of the 3 types of bees. The frequencies of flower visits were significantly higher for mason bees (12.89/min in Jinan and 10.63/min in Yantai) than bumble bees and Italian honey bees in the 2 regions. The single flower residence times were significantly higher for Italian honey bees (8.22 s in Jinan and 9.43 s in Yantai), but Italian honey bees were most affected by the climate. The 3 bees differed significantly in terms of the amount of apple pollen collected and their effects on the fruit setting rate in apples (mason bees &gt; bumble bees &gt; Italian honey bees). The results showed that the mason bee was the most suitable pollinating species for spring apple orchards; Bumble bees were more suitable as alternative pollinators during cloudy and low temperatures; Italian honey bees were able to take advantage of their large number of worker bees in sunny and warm weather. Compared to individual bee species, a combination of 2 or 3 species of bees might be more advantageous in dealing with complex and variable weather conditions.
Rock physics characteristics and their control factors of carbonate in different sedimentary microfacies of the Yingshan Formation, Gucheng Area, Tarim Basin
Authors: Wang Jiaqing , Deng Jixin , Xia Hui , Yan Longlong 
Published: November 2023

Abstract
Understanding the influence of geological characteristics on rock physics properties is crucial for accurately recognizing the relationship between rock physics variation and reservoir characteristics. Unlike the conventional rock species, the rock physics properties of the deep carbonate rocks in the third member of Yingshan Formation (Ying-III Member) in Gucheng area, Tarim Basin are relatively more complex. To address this problem, we investigated the rock physics characteristics and controlling factors of different sedimentary microfacies samples, combined with sedimentological analysis and rock physics experiments. The results show that the sedimentary environment affects the lithology and pore structure by controlling the properties of the primitive rock and early diagenesis. Dolomitized shoal microfacies and shoal top dolomitic flat microfacies primarily form crystalline dolomite and siliceous dolomite, with pores consisting of inter-crystalline pores, dissolution pores, and cracks. Inter-shoal dolomitic flat microfacies develops silty dolomite, with only a few inter-crystalline pores and cracks. Middle- to high-energy shoal microfacies and inter-shoal sea microfacies develop tight calcarenite and micritic limestone. Samples with similar mineral composition have relatively consistent density values and acoustic properties. Soft pores, such as micro-cracks, have a significant impact on the effective pressure and acoustic wave velocity, velocity and velocity ratio, and velocity and porosity relationships. The research shows a new approach for the rock physics characteristics of deep carbonate reservoirs under geological background constraints, as well as the rock physics basis for seismic prediction of the Ying-III Member reservoir.
Electron holography observation of electron spin polarization around charged insulating wire
Authors: Sato Takafumi , Shimada Keiko , Akase Zentaro , Magara Hideyuki , Tomita Takeshi , Shindo Daisuke 
Published: November 2023

Abstract
We report direct observation by electron holography of the spin polarization of electrons in a vacuum region around a charged SiO2 wire coated with Pt–Pd. Irradiating the SiO2 wire with 300 keV electrons caused the wire to become positively charged due to the emission of secondary electrons. The spin polarization of these electrons interacting with the charged wire was observed in situ using a phase reconstruction process under an external magnetic field. The magnetic field of the spin-polarized electrons was simulated taking into account the distribution of secondary electrons and the effect of the external magnetic field.
Loss of Respiratory Syncytial Virus Antibody Functions During the Peak of the COVID-19 Pandemic Mitigation Measures
Authors: Abu-Raya Bahaa , Reicherz Frederic , Michalski Christina , Viñeta Paramo Marina , Majdoubi Abdelilah , Golding Liam , Granoski Madison , Stojic Aleksandra , Marchant David J , Lavoie Pascal M 
Published: November 2023

Abstract
Studies have linked respiratory syncytial virus (RSV) antibody-mediated phagocytosis and complement deposition to severe RSV infection in humans. This study shows waning of these antibody functions in women of childbearing age in 2020-2021 during the implementation of COVID-19 mitigation measures, in absence of RSV circulation. These functions could be explored as correlates of protection against severe RSV disease.
Bayesian design with sampling windows for complex spatial processes
Authors: Buchhorn Katie , Mengersen Kerrie , Santos-Fernandez Edgar , Peterson Erin E , McGree James M 
Published: November 2023

Abstract
Optimal design facilitates intelligent data collection. In this paper, we introduce a fully Bayesian design approach for spatial processes with complex covariance structures, like those typically exhibited in natural ecosystems. Coordinate exchange algorithms are commonly used to find optimal design points. However, collecting data at specific points is often infeasible in practice. Currently, there is no provision to allow for flexibility in the choice of design. Accordingly, we also propose an approach to find Bayesian sampling windows, rather than points, via Gaussian process emulation to identify regions of high design efficiency across a multi-dimensional space. These developments are motivated by two ecological case studies: monitoring water temperature in a river network system in the northwestern United States and monitoring submerged coral reefs off the north-west coast of Australia.
CEP hormones at the nexus of nutrient acquisition and allocation, root development, and plant–microbe interactions
Authors: Taleski Michael , Jin Marvin , Chapman Kelly , Taylor Katia , Winning Courtney , Frank Manuel , Imin Nijat , Djordjevic Michael A 
Published: November 2023

Abstract
A growing understanding is emerging of the roles of peptide hormones in local and long-distance signalling that coordinates plant growth and development as well as responses to the environment. C-TERMINALLY ENCODED PEPTIDE (CEP) signalling triggered by its interaction with CEP RECEPTOR 1 (CEPR1) is known to play roles in systemic nitrogen (N) demand signalling, legume nodulation, and root system architecture. Recent research provides further insight into how CEP signalling operates, which involves diverse downstream targets and interactions with other hormone pathways. Additionally, there is emerging evidence of CEP signalling playing roles in N allocation, root responses to carbon levels, the uptake of other soil nutrients such as phosphorus and sulfur, root responses to arbuscular mycorrhizal fungi, plant immunity, and reproductive development. These findings suggest that CEP signalling more broadly coordinates growth across the whole plant in response to diverse environmental cues. Moreover, CEP signalling and function appear to be conserved in angiosperms. We review recent advances in CEP biology with a focus on soil nutrient uptake, root system architecture and organogenesis, and roles in plant–microbe interactions. Furthermore, we address knowledge gaps and future directions in this research field.
Evaluation of Detection and Efficacy of Decontamination of Respiratory Pathogens Including SARS-CoV-2 on Basic Military Trainee Gas Masks
Authors: Foushee Ann Marie DiGeorge , Casey Theresa M , Strickland Amanda , Ochoa Anna , Asin Susana , Lott Lisa , Burdette Alexander J 
Published: November 2023

ABSTRACT

Introduction
Basic military trainee (BMT) gas mask training poses a potential mechanism of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission. After training, gas masks are decontaminated. Insufficient decontamination can lead to viral transmission in the next training class. To our knowledge, the decontamination process has not been validated for efficacy in removing respiratory pathogens such as SARS-CoV-2.

Materials and Methods
Inactivated strains of SARS-CoV-2, influenza A and B, and Bordetella pertussis were separately inoculated onto gas masks in the emitter area (n = 5). Pathogen detection in swabs collected from gas masks was performed by real-time polymerase chain reaction (RT-PCR) using the BioFire® RP2.1 panel and Biomeme Franklin system. For decontamination efficacy experiments, pathogens were inoculated onto gas masks, and contaminated areas were swabbed before and after decontamination, with detection using both PCR platforms. Lastly, 65 gas masks were swabbed after gas mask training, and again after the trainees and guardians decontaminated the masks, to identify the presence of any respiratory pathogen exhaled onto the gas masks.

Results
All four pathogens were detected by both PCR platforms. The BioFire® FilmArray® was more sensitive than the Biomeme platform. Decontamination resulted in undetectable levels of all three viruses. B. pertussis was detected on one mask after decontamination. Experiments with live B. pertussis validated that decontamination eliminated all viable bacteria from gas masks. For BMT sampling, all masks were negative for SARS-CoV-2. One mask tested positive for coronavirus 229E. Once decontaminated, all masks tested negative.

Conclusions
BMT gas masks can be monitored for the presence of respiratory pathogens using RT-PCR. The decontamination process removed all viable respiratory pathogens tested from the gas masks. This study demonstrates that RT-PCR can be used to conduct pathogen surveillance on BMT gas masks after training and that the current decontamination process is effective to eliminate respiratory viruses including SARS-CoV-2.
Predictors of Sustained Response to Functional Restoration in a Military Population
Authors: Flynn Diane M , Burke Larisa A , Ransom Jeffrey C , McQuinn Honor M , Steffen Alana D , Snow Tyler J , Doorenbos Ardith Z 
Published: November 2023

ABSTRACT

Introduction
The purpose of this study was to determine if improvement in pain impact and functional performance following a functional restoration (FR) program was sustained up to 6 months posttreatment and to identify predictors of sustained improvement.

Materials and Methods
Secondary analysis of data collected during randomized clinical trial. Study population included 108 US active duty service members who completed an FR program, as well as 3- and/or 6-month follow-up assessments. Primary outcome measure was the NIH Research Task Force (pain) impact score (PIS). Secondary outcome was a composite functional performance measure of treadmill, lifting, and carrying tolerances. Variables analyzed to determine their predictive value included demographics; treatment hours; measures of pain intensity, function, mood, sleep, social satisfaction, pain catastrophizing, kinesiophobia, self-efficacy, pain acceptance, patient activation, functional performance, and neuropathic pain.

Results
Mean PIS and functional performance improved significantly immediately following FR, but after 6 months, only improvement in functional performance sustained. Responder analysis showed that 6 months after FR, 42% of participants reported improvement that exceeded the minimal clinically important difference in PIS or functional performance. Predictors of sustained PIS improvement included younger age, absence of neuropathic pain features, less self-rated disability, better baseline functional performance, and worse baseline PIS. Predictors of sustained functional performance improvement included more treatment hours, lower baseline pain catastrophizing, and lower baseline functional performance.

Conclusions
This study supports the investment of treatment time in FR to yield sustained clinically meaningful improvement, as observed in over 40% of this study’s military participants. Pretreatment predictors of sustained response included lower pain catastrophizing and absence of neuropathic pain. Further research is needed to determine if treatments that improve pain catastrophizing and neuropathic pain will result in sustained improvement in pain impact and functional performance following FR program participation.
Development of the Troop Readiness Evaluation With Augmented Reality Return-to-Duty (Troop READY) Platform to Aid in the Detection and Treatment of Military Mild Traumatic Brain Injury
Authors: Rosenfeldt Anson B , Kaya Ryan D , Owen Kelsey , Hastilow Karissa , Scelina Kathryn , Scelina Logan , Miller Koop Mandy , Zimmerman Eric , Alberts Jay L 
Published: November 2023

ABSTRACT

Introduction
Mild traumatic brain injury (mTBI) is prevalent in service members (SMs); however, there is a lack of consensus on the appropriate approach to return to duty (RTD). Head-mounted augmented reality technology, such as the HoloLens 2, can create immersive, salient environments to more effectively evaluate relevant military task performance. The Troop Readiness Evaluation with Augmented Reality Return-to-Duty (READY) platform was developed to objectively quantify cognitive and motor performance during military-specific activities to create a comprehensive approach to aid in mTBI detection and facilitate appropriate RTD. The aim of this project was to detail the technical development of the Troop READY platform, the outcomes, and its potential role in the aiding detection and RTD decision-making post mTBI. The secondary aim included evaluating the safety, feasibility, and SM usability of the Troop READY platform.

Materials and Methods
The Troop READY platform comprises three assessment modules of progressing complexity: (1) Static and Dynamic Mobility, (2) Rifle Qualification Test, and (3) Small Unit Operations Capacity–Room Breach/Clearing Exercise. The modules were completed by 137 active duty SMs. Safety was assessed through monitoring of adverse events. Feasibility was assessed using the self-directed module completion rate. Usability was measured using the Systems Usability Scale.

Results
No adverse events occurred. Completion rates of the three modules ranged from 98 to 100%. In terms of usability, the mean Systems Usability Scale score of all participants was 83.92 (13.95), placing the Troop READY platform in the good-to-excellent category. Objective motor and cognitive outcomes were generated for each module.

Conclusion
The Troop READY platform delivers self-directed, salient assessment modules to quantify single-task, dual-task, and unit-based performance in SMs. The resultant data provide insight into SM performance through objective outcomes and identify specific areas of executive or motor function that may be slow to recover following mTBI.