bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bioactive VEGF-C from E. coli
Authors: Rauniyar Khushbu , Akhondzadeh Soheila , Gąciarz Anna , Künnapuu Jaana , Jeltsch Michael 
Published: October 2022

AbstractVascular endothelial growth factor-C (VEGF-C) stimulates lymphatic vessel growth in transgenic models, via viral gene delivery, and as a recombinant protein. Expressing eukaryotic proteins like VEGF-C in bacterial cells has limitations, as these cells lack specific posttranslational modifications and provisions for disulfide bond formation. However, given the cost and time savings associated with bacterial expression systems, there is considerable value in expressing VEGF-C using bacterial cells. We identified two approaches that result in biologically active Escherichia coli-derived VEGF-C. Expectedly, VEGF-C expressed from a truncated cDNA became bioactive after in vitro folding from inclusion bodies. Given that VEGF-C is one of the cysteine-richest growth factors in humans, it was unclear whether known methods to facilitate correct cysteine bond formation allow for the direct expression of bioactive VEGF-C in the cytoplasm. By fusing VEGF-C to maltose-binding protein and expressing these fusions in the redox-modified cytoplasm of the Origami (DE3) strain, we could recover biological activity for deletion mutants lacking the propeptides of VEGF-C. This is the first report of a bioactive VEGF growth factor obtained from E. coli cells circumventing in-vitro folding.
Investigating the associations between cognitive appraisals, emotion regulation and symptoms of posttraumatic stress disorder among Asian American and European American trauma survivors
Authors: Jobson Laura , Willoughby Casey , Specker Philippa , Wong Joshua , Draganidis Adriana , Lau Winnie , Liddell Belinda 
Published: October 2022

AbstractThis study investigated whether the associations between emotion regulation and cognitive appraisals and symptoms of posttraumatic stress disorder (PTSD) differ between Asian American and European American trauma survivors. Asian American (n = 103) and European American (n = 104) trauma survivors were recruited through mTurk and completed an on-line questionnaire assessing cognitive appraisals, emotion regulation and PTSD symptomatology. The European American group reported greater trauma-specific rumination, psychological inflexibility, seeking out others for comfort, and negative self-appraisals than the Asian American group. The Asian American group reported greater secondary control appraisals and cultural beliefs about adversity than the European American group. Second, cultural group moderated the associations between (a) brooding rumination, (b) fatalism, (c) self-blame, and (d) negative communal self-appraisals and PTSD symptoms. These associations were larger for the European American group than the Asian American group. Third, there was an indirect pathway from self-construal (independent and interdependent) to PTSD symptoms through certain emotion regulation approaches and cognitive appraisals. Additionally, cultural group was found to moderate several of these indirect effects. These findings highlight the importance of considering cultural background and cultural values in understanding the processes involved in PTSD. Further research in this area is needed.
A neural network for the detection of soccer headers from wearable sensor data
Authors: Kern Jan , Lober Thomas , Hermsdörfer Joachim , Endo Satoshi 
Published: October 2022

AbstractTo investigate the proposed association between soccer heading and deleterious brain changes, an accurate quantification of heading exposure is crucial. While wearable sensors constitute a popular means for this task, available systems typically overestimate the number of headers by poorly discriminating true impacts from spurious recordings. This study investigated the utility of a neural network for automatically detecting soccer headers from kinematic time series data obtained by wearable sensors. During 26 matches, 27 female soccer players wore head impacts sensors to register on-field impact events (> 8 g), which were labelled as valid headers (VH) or non-headers (NH) upon video review. Of these ground truth data, subsets of 49% and 21% each were used to train and validate a Long Short-Term Memory (LSTM) neural network in order to classify sensor recordings as either VH or NH based on their characteristic linear acceleration features. When tested on a balanced dataset comprising 271 VHs and NHs (which corresponds to 30% and 1.4% of ground truth VHs and NHs, respectively), the network showed very good overall classification performance by reaching scores of more than 90% across all metrics. When testing was performed on an unbalanced dataset comprising 271 VHs and 5743 NHs (i.e., 30% of ground truth VHs and NHs, respectively), as typically obtained in real-life settings, the model still achieved over 90% sensitivity and specificity, but only 42% precision, which would result in an overestimation of soccer players’ true heading exposure. Although classification performance suffered from the considerable class imbalance between actual headers and non-headers, this study demonstrates the general ability of a data-driven deep learning network to automatically classify soccer headers based on their linear acceleration profiles.
Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks
Authors: Jiang Min-Zhi , Zhu Hai-Zhen , Zhou Nan , Liu Chang , Jiang Cheng-Ying , Wang Yulin , Liu Shuang-Jiang 
Published: October 2022

AbstractCo-occurrence networks inferred from the abundance data of microbial communities are widely applied to predict microbial interactions. However, the high workloads of bacterial isolation and the complexity of the networks themselves constrained experimental demonstrations of the predicted microbial associations and interactions. Here, we integrate droplet microfluidics and bar-coding logistics for high-throughput bacterial isolation and cultivation from environmental samples, and experimentally investigate the relationships between taxon pairs inferred from microbial co-occurrence networks. We collected Potamogeton perfoliatus plants (including roots) and associated sediments from Beijing Olympic Park wetland. Droplets of series diluted homogenates of wetland samples were inoculated into 126 96-well plates containing R2A and TSB media. After 10 days of cultivation, 65 plates with > 30% wells showed microbial growth were selected for the inference of microbial co-occurrence networks. We cultivated 129 bacterial isolates belonging to 15 species that could represent the zero-level OTUs (Zotus) in the inferred co-occurrence networks. The co-cultivations of bacterial isolates corresponding to the prevalent Zotus pairs in networks were performed on agar plates and in broth. Results suggested that positively associated Zotu pairs in the co-occurrence network implied complicated relations including neutralism, competition, and mutualism, depending on bacterial isolate combination and cultivation time.
Viral metagenomics reveals persistent as well as dietary acquired viruses in Antarctic fur seals
Authors: Martínez-Puchol Sandra , Cardona Luis , Drago Massimiliano , Gazo Manel , Bofill-Mas Sílvia 
Published: October 2022

AbstractViruses linked to animals inhabiting Antarctic latitudes remain poorly studied. Remote environments hosting large pinniped populations may be prone to exposure of immunologically naïve animals to new infectious agents due to increasing human presence or introduction of new animal species. Antarctic fur seals (Arctocephalus gazella)inhabiting the Western Antarctic Peninsula and the South Shetland Islands are challenged because of climate change and increased anthropogenic activity. In the present study, the fecal and serum virome ofA. gazellawas characterized by applying target enrichment next generation sequencing. The resulting viromes were dominated by CRESS-DNA sequences. Viruses known to infect vertebrate and invertebrate hosts were also observed in fecal samples. Fur seal picornavirus was present in all the fecal pools studied suggesting it is a prevalent virus in these species. Six different viruses presenting similarities with previously describedA. gazellaviruses or other otariids and mammal viruses were identified as potential newA. gazellaviruses. Also, diet-derived viruses such as crustacean viruses were present in fecal content. Penguin viruses, but not fish viruses, were also detected. Obtained results contribute to a better understanding of the viral community present in these species, which is relevant for its conservation.
Shared mechanisms and crosstalk of COVID-19 and osteoporosis via vitamin D
Authors: Liu Fei , Song Chao , Cai Weiye , Chen Jingwen , Cheng Kang , Guo Daru , Duan Dayue Darrel , Liu Zongchao 
Published: October 2022

AbstractRecently accumulated evidence implicates a close association of vitamin D (VitD) insufficiency to the incidence and clinical manifestations of the COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). Populations with insufficient VitD including patients with osteoporosis are more susceptible to SARS-COV-2 infection and patients with COVID-19 worsened or developed osteoporosis. It is currently unknown, however, whether osteoporosis and COVID-19 are linked by VitD insufficiency. In this study, 42 common targets for VitD on both COVID-19 and osteoporosis were identified among a total of 243 VitD targets. Further bioinformatic analysis revealed 8 core targets (EGFR, AR, ESR1, MAPK8, MDM2, EZH2, ERBB2 and MAPT) in the VitD-COVID-19-osteoporosis network. These targets are involved in the ErbB and MAPK signaling pathways critical for lung fibrosis, bone structural integrity, and cytokines through a crosstalk between COVID-19 and osteoporosis via the VitD-mediated conventional immune and osteoimmune mechanisms. Molecular docking confirmed that VitD binds tightly to the predicted targets. These findings support that VitD may target common signaling pathways in the integrated network of lung fibrosis and bone structural integrity as well as the immune systems. Therefore, VitD may serve as a preventive and therapeutic agent for both COVID-19 and osteoporosis.
Prediction of global omicron pandemic using ARIMA, MLR, and Prophet models
Authors: Zhao Daren , Zhang Ruihua , Zhang Huiwu , He Sizhang 
Published: October 2022

AbstractGlobally, since the outbreak of the Omicron variant in November 2021, the number of confirmed cases of COVID-19 has continued to increase, posing a tremendous challenge to the prevention and control of this infectious disease in many countries. The global daily confirmed cases of COVID-19 between November 1, 2021, and February 17, 2022, were used as a database for modeling, and the ARIMA, MLR, and Prophet models were developed and compared. The prediction performance was evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE). The study showed that ARIMA (7, 1, 0) was the optimum model, and the MAE, MAPE, and RMSE values were lower than those of the MLR and Prophet models in terms of fitting performance and forecasting performance. The ARIMA model had superior prediction performance compared to the MLR and Prophet models. In real-world research, an appropriate prediction model should be selected based on the characteristics of the data and the sample size, which is essential for obtaining more accurate predictions of infectious disease incidence.
Artificial intelligence for strengthening healthcare systems in low- and middle-income countries: a systematic scoping review
Authors: Ciecierski-Holmes Tadeusz , Singh Ritvij , Axt Miriam , Brenner Stephan , Barteit Sandra 
Published: October 2022

AbstractIn low- and middle-income countries (LMICs), AI has been promoted as a potential means of strengthening healthcare systems by a growing number of publications. We aimed to evaluate the scope and nature of AI technologies in the specific context of LMICs. In this systematic scoping review, we used a broad variety of AI and healthcare search terms. Our literature search included records published between 1st January 2009 and 30th September 2021 from the Scopus, EMBASE, MEDLINE, Global Health and APA PsycInfo databases, and grey literature from a Google Scholar search. We included studies that reported a quantitative and/or qualitative evaluation of a real-world application of AI in an LMIC health context. A total of 10 references evaluating the application of AI in an LMIC were included. Applications varied widely, including: clinical decision support systems, treatment planning and triage assistants and health chatbots. Only half of the papers reported which algorithms and datasets were used in order to train the AI. A number of challenges of using AI tools were reported, including issues with reliability, mixed impacts on workflows, poor user friendliness and lack of adeptness with local contexts. Many barriers exists that prevent the successful development and adoption of well-performing, context-specific AI tools, such as limited data availability, trust and evidence of cost-effectiveness in LMICs. Additional evaluations of the use of AI in healthcare in LMICs are needed in order to identify their effectiveness and reliability in real-world settings and to generate understanding for best practices for future implementations.
Synchronization induced by directed higher-order interactions
Authors: Gallo Luca , Muolo Riccardo , Gambuzza Lucia Valentina , Latora Vito , Frasca Mattia , Carletti Timoteo 
Published: October 2022

AbstractNon-reciprocal interactions play a crucial role in many social and biological complex systems. While directionality has been thoroughly accounted for in networks with pairwise interactions, its effects in systems with higher-order interactions have not yet been explored as deserved. Here, we introduce the concept ofM-directed hypergraphs, a general class of directed higher-order structures, which allows to investigate dynamical systems coupled through directed group interactions. As an application we study the synchronization of nonlinear oscillators on 1-directed hypergraphs, finding that directed higher-order interactions can destroy synchronization, but also stabilize otherwise unstable synchronized states.
Projected climate variability of internal waves in the Andaman Sea
Authors: Yadidya B. , Rao A. D. 
Published: October 2022

AbstractThe Andaman Sea, in the northeast Indian Ocean, is renowned for large-amplitude internal waves. Here, we use a global climate model (CanESM5) to investigate the long-term variability of internal waves in the Andaman Sea under a range of shared socioeconomic pathway (SSP) scenarios. SSPs are future societal development pathways related to emissions and land use scenarios. We project that mean values of depth-averaged stratification will increase by approximately 6% (SSP1-2.6), 7% (SSP2-4.5), and 12% (SSP5-8.5) between 1871-1900 and 2081-2100. Simulating changes in internal tides between the present (2015-2024) and the end-century (2091-2100), we find that the increase in stratification will enhance internal tide generation by approximately 4 to 8%. We project that the propagation of internal tides into the Andaman Sea and the Bay of Bengal will increase by 8 to 18% and 4 to 19%, respectively, under different SSP scenarios. Such changes in internal tides under global warming will have implications for primary production and ecosystem health not only in the Andaman Sea but also in the Bay of Bengal.
Presence of algal symbionts affects denitrifying bacterial communities in the sea anemone Aiptasia coral model
Authors: Xiang Nan , Rädecker Nils , Pogoreutz Claudia , Cárdenas Anny , Meibom Anders , Wild Christian , Gärdes Astrid , Voolstra Christian R 
Published: October 2022

Abstract
The coral-algal symbiosis is maintained by a constant and limited nitrogen availability in the holobiont. Denitrifiers, i.e., prokaryotes reducing nitrate/nitrite to dinitrogen, could contribute to maintaining the nitrogen limitation in the coral holobiont, however the effect of host and algal identity on their community is still unknown. Using the coral model Aiptasia, we quantified and characterized the denitrifier community in a full-factorial design combining two hosts (CC7 and H2) and two strains of algal symbionts of the family Symbiodiniaceae (SSA01 and SSB01). Strikingly, relative abundance of denitrifiers increased by up to 22-fold in photosymbiotic Aiptasia compared to their aposymbiotic (i.e., algal-depleted) counterparts. In line with this, while the denitrifier community in aposymbiotic Aiptasia was largely dominated by diet-associated Halomonas, we observed an increasing relative abundance of an unclassified bacterium in photosymbiotic CC7, and Ketobacter in photosymbiotic H2, respectively. Pronounced changes in denitrifier communities of Aiptasia with Symbiodinium linucheae strain SSA01 aligned with the higher photosynthetic carbon availability of these holobionts compared to Aiptasia with Breviolum minutum strain SSB01. Our results reveal that the presence of algal symbionts increases abundance and alters community structure of denitrifiers in Aiptasia. Thereby, patterns in denitrifier community likely reflect the nutritional status of aposymbiotic vs. symbiotic holobionts. Such a passive regulation of denitrifiers may contribute to maintaining the nitrogen limitation required for the functioning of the cnidarian-algal symbiosis.
Spatio-temporal dynamics of three diseases caused by Aedes-borne arboviruses in Mexico
Authors: Dong Bo , Khan Latifur , Smith Madison , Trevino Jesus , Zhao Bingxin , Hamer Gabriel L. , Lopez-Lemus Uriel A. , Molina Aracely Angulo , Lubinda Jailos , Nguyen Uyen-Sa D. T. , Haque Ubydul 
Published: October 2022

Abstract
Background
The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus (CHIKV), Dengue virus (DENV), and Zika virus (ZIKV) clusters in Mexico.

Methods
We present an integrated analysis of Aedes-borne diseases (ABDs), the local climate, and the socio-demographic profiles of 2469 municipalities in Mexico. We used SaTScan to detect spatial clusters and utilize the Pearson correlation coefficient, Randomized Dependence Coefficient, and SHapley Additive exPlanations to analyze the influence of socio-demographic and climatic factors on the prevalence of ABDs. We also compare six machine learning techniques, including XGBoost, decision tree, Support Vector Machine with Radial Basis Function kernel, K nearest neighbors, random forest, and neural network to predict risk factors of ABDs clusters.

Results
DENV is the most prevalent of the three diseases throughout Mexico, with nearly 60.6% of the municipalities reported having DENV cases. For some spatiotemporal clusters, the influence of socio-economic attributes is larger than the influence of climate attributes for predicting the prevalence of ABDs. XGBoost performs the best in terms of precision-measure for ABDs prevalence.

Conclusions
Both socio-demographic and climatic factors influence ABDs transmission in different regions of Mexico. Future studies should build predictive models supporting early warning systems to anticipate the time and location of ABDs outbreaks and determine the stand-alone influence of individual risk factors and establish causal mechanisms.
Speech-Language Pathology Interventions for Children With Executive Function Deficits: A Systematic Literature Review
Authors: Senter Reed , Chow Jason C. , Willis Emma C. 
Published: October 2022

Purpose:
The purpose of this synthesis was to systematically review the research and guidance for school-based speech-language pathologists (SLPs) who provide intervention to children with developmental executive function (EF) deficits, particularly those children with co-occurring developmental language disorder (DLD).

Method:
We conducted a structured search of four major electronic databases, as well as a manual review of references and journals, which yielded 4,571 nonduplicate articles. We screened first titles and abstracts and then full texts to identify peer-reviewed articles, dissertations, and theses containing research or guidance for SLPs' interventions for children with co-occurring DLD and EF deficits; this process yielded 27 articles for analysis. We categorized these studies by type of publication and synthesized their contents to assess the evidence base for EF interventions in children with DLD and to evaluate the guidance for SLP-implemented direct and indirect interventions.

Results:
A small body of research explores the efficacy of SLPs' intervention for children with co-occurring DLD and EF deficits, generally finding modest but inconsistent effects of cognitive interventions and strategy training to improve language outcomes. Meanwhile, nonempirical articles (e.g., tutorials) offer guidance to SLPs to support students with EF deficits through direct and indirect services.

Conclusions:
A growing body of literature equips SLPs with the principles and strategies of EF intervention. Many of these articles are sourced from literature about children with EF deficits or attention-deficit/hyperactivity disorder, but few empirical studies measure the efficacy of these interventions for children with co-occurring DLD.

Supplemental Material:

https://doi.org/10.23641/asha.21401901
A novel spectral peak estimator based on underdetermined equation
Authors: Chen Bingbing , Sun Yufa 
Published: October 2022

AbstractThis letter develops a fast spectral peak estimation method, which is inspired by the theory of compressed sensing (CS). In this work, the measurement procedure of the CS is employed to construct an underdetermined equation, and then a low complexity spectral peak search method is established by using a priori knowledge of signal amplitude. Compared with other frequency estimation methods, the proposed method requires only 10% inner products demanded to obtain the spectral peak positions, and this method can be introduced into any existing discrete Fourier transform (DFT)‐based interpolation methods. Experimental results show that the proposed method yields nearly the same accuracy as other interpolation methods, but with lower computational demands.
Tunable and reconfigurable bandstop filters enabled by optically controlled switching elements
Authors: Li Peizhao , Shi Yu , Deng Yijing , Fay Patrick , Liu Lei 
Published: October 2022

AbstractThe authors report a novel approach for designing tunable and reconfigurable bandstop filters by employing bias‐free optically‐controlled photoconductive radio frequency (RF) switching elements. To verify the effectiveness of the approach, a bandstop filter with two stopbands centred at 4.05 and 4.75 GHz was designed using a split‐ring‐coupled microstrip transmission line on RO3010 substrates. To enable reconfigurability, a micromachined Si chip with a thickness of ∼73 μm was embedded in the gap of each resonator. The tuning and reconfiguring of the filter are accomplished by selectively illuminating the Si chips using fibre‐coupled laser diodes with a wavelength of 808 nm. By turning on and off each laser diode, the filter stop bands can be dynamically reconfigured. In addition, the suppression of each stop band can be continuously and independently tuned by changing the light intensity from 0 to 20 W/cm2. With geometric scaling, this approach is promising for realizing a novel class of compact and high‐performance tunable and/or reconfigurable circuits from the microwave to mmW‐THz region.