bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interregional flows of virtual cropland within China
Authors: Wu Hanfei , Liu Ao , Jin Ruochen , Chai Li 
Published: July 2022

Abstract
Cropland is an essential resource for agricultural system and greatly impacts agricultural sustainability. Cropland can be embodied in the goods and transferred among regions. Managing cropland as a virtual resource, similar with virtual water strategy, is an effective measure to achieve sustainability. Therefore, it is of significance for policymakers to understand how virtual cropland transfers in the economic society. This study employed a Multi-Regional Input-Output model with high resolution in the agriculture sectors (nine categories of crops) to examine the interregional flows of virtual cropland within China in 2015. The results show that Heilongjiang, Inner Mongolia, and Jilin contributed the most virtual cropland, while Guangdong, Zhejiang, and Shandong were the largest receivers. The largest flow was from Heilongjiang to Guangdong embodied in cereals. Most of virtual flows were embodied in cereals, followed by sugar crops, other crops, legumes, and vegetables. Heilongjiang, Xinjiang, and Guangxi dominated the virtual outflows embodied in legumes, fruits, and oilseeds, respectively. This study is informative and implicative for policymakers to understand the spatial transfer pattern of virtual cropland, identify the key nodes, and design the effective measures to achieve sustainability.
StabilitySort: assessment of protein stability changes on a genome-wide scale to prioritize potentially pathogenic genetic variation
Authors: Chuah Aaron , Li Sean , Do Andrea , Field Matt , Andrews Dan 
Published: July 2022

AbstractSummaryMissense mutations that change protein stability are strongly associated with human genetic disease. With the recent availability of predicted structures for all human proteins generated using the AlphaFold2 prediction model, genome-wide assessment of the stability effects of genetic variation can, for the first time, be easily performed. This facilitates the interrogation of personal genetic variation for potentially pathogenic effects through the application of stability metrics. Here, we present a novel tool to prioritize variants predicted to cause strong instability in essential proteins. We show that by filtering by ΔΔG values and then prioritizing by StabilitySort Z-scores, we are able to more accurately discriminate pathogenic, protein-destabilizing mutations from population variation, compared with other mutation effect predictors.Availability and implementationStabilitySort is available as a web service (https://www.stabilitysort.org), as a data download for integration with other tools (https://www.stabilitysort.org/download) or can be deployed as a standalone system from source code (https://gitlab.com/baaron/StabilitySort).Supplementary informationSupplementary data are available at Bioinformatics online.
TogoID: an exploratory ID converter to bridge biological datasets
Authors: Ikeda Shuya , Ono Hiromasa , Ohta Tazro , Chiba Hirokazu , Naito Yuki , Moriya Yuki , Kawashima Shuichi , Yamamoto Yasunori , Okamoto Shinobu , Goto Susumu , Katayama Toshiaki 
Published: July 2022

AbstractMotivationUnderstanding life cannot be accomplished without making full use of biological data, which are scattered across databases of diverse categories in life sciences. To connect such data seamlessly, identifier (ID) conversion plays a key role. However, existing ID conversion services have disadvantages, such as covering only a limited range of biological categories of databases, not keeping up with the updates of the original databases and outputs being hard to interpret in the context of biological relations, especially when converting IDs in multiple steps.ResultsTogoID is an ID conversion service implementing unique features with an intuitive web interface and an application programming interface (API) for programmatic access. TogoID currently supports 65 datasets covering various biological categories. TogoID users can perform exploratory multistep conversions to find a path among IDs. To guide the interpretation of biological meanings in the conversions, we crafted an ontology that defines the semantics of the dataset relations.Availability and implementationThe TogoID service is freely available on the TogoID website (https://togoid.dbcls.jp/) and the API is also provided to allow programmatic access. To encourage developers to add new dataset pairs, the system stores the configurations of pairs at the GitHub repository (https://github.com/togoid/togoid-config) and accepts the request of additional pairs.Supplementary informationSupplementary data are available at Bioinformatics online.
Needle: a fast and space-efficient prefilter for estimating the quantification of very large collections of expression experiments
Authors: Darvish Mitra , Seiler Enrico , Mehringer Svenja , Rahn René , Reinert Knut 
Published: July 2022

AbstractMotivationThe ever-growing size of sequencing data is a major bottleneck in bioinformatics as the advances of hardware development cannot keep up with the data growth. Therefore, an enormous amount of data is collected but rarely ever reused, because it is nearly impossible to find meaningful experiments in the stream of raw data.ResultsAs a solution, we propose Needle, a fast and space-efficient index which can be built for thousands of experiments in &lt;2 h and can estimate the quantification of a transcript in these experiments in seconds, thereby outperforming its competitors. The basic idea of the Needle index is to create multiple interleaved Bloom filters that each store a set of representative k-mers depending on their multiplicity in the raw data. This is then used to quantify the query.Availability and implementationhttps://github.com/seqan/needle.Supplementary informationSupplementary data are available at Bioinformatics online.
Acidic Cannabinoids Suppress Proinflammatory Cytokine Release by Blocking Store-operated Calcium Entry
Authors: Faouzi Malika , Wakano Clay , Monteilh-Zoller Mahealani K , Neupane Ram P , Starkus John G , Neupane Jayanti Bhandari , Cullen Aaron J , Johnson Brandon E , Fleig Andrea , Penner Reinhold 
Published: July 2022

AbstractCannabis sativa has long been known to affect numerous biological activities. Although plant extracts, purified cannabinoids, or synthetic cannabinoid analogs have shown therapeutic potential in pain, inflammation, seizure disorders, appetite stimulation, muscle spasticity, and treatment of nausea/vomiting, the underlying mechanisms of action remain ill-defined. In this study we provide the first comprehensive overview of the effects of whole-plant Cannabis extracts and various pure cannabinoids on store-operated calcium (Ca2+) entry (SOCE) in several different immune cell lines. Store-operated Ca2+ entry is one of the most significant Ca2+ influx mechanisms in immune cells, and it is critical for the activation of T lymphocytes, leading to the release of proinflammatory cytokines and mediating inflammation and T cell proliferation, key mechanisms for maintaining chronic pain. While the two major cannabinoids cannabidiol and trans-Δ9-tetrahydrocannabinol were largely ineffective in inhibiting SOCE, we report for the first time that several minor cannabinoids, mainly the carboxylic acid derivatives and particularly cannabigerolic acid, demonstrated high potency against SOCE by blocking calcium release-activated calcium currents. Moreover, we show that this inhibition of SOCE resulted in a decrease of nuclear factor of activated T-cells activation and Interleukin 2 production in human T lymphocytes. Taken together, these results indicate that cannabinoid-mediated inhibition of a proinflammatory target such as SOCE may at least partially explain the anti-inflammatory and analgesic effects of Cannabis.
Local health systems resilience in managing the COVID-19 pandemic: lessons from Mexico
Authors: Juárez-Ramírez Clara , Reyes-Morales Hortensia , Gutiérrez-Alba Gaudencio , Reartes-Peñafiel Diana L , Flores-Hernández Sergio , Muños-Hernández José Alberto , Escalante-Castañón André , Malo Miguel 
Published: July 2022

AbstractThe concept of resilience was applied to the public health field to investigate the way health systems are impacted by health crises, what conditions allow them to mitigate the blow and how they reorganize once the crisis is over. In 2020, the COVID-19 pandemic caused by the SARS-CoV-2 virus represented a global challenge demanding immediate response to an unprecedented health crisis. Various voices drew attention to the intensity of the crisis in countries with greater inequalities, where the pandemic converged with other social emergencies. We documented the experiences of health personnel who faced the pandemic at the primary care level while simultaneously maintaining the functioning of other areas of medical care. Our results derived from a qualitative study comprising 103 participants from five states of Mexico. We aimed to show through inferential analysis their perspective on what we call ‘the resilience of local health systems’. We observed three stages of experience during the crisis: (a) Preparation (official guidelines received to organize care, training and planning of epidemiological surveillance); (b) Adaptation (performance of community-based prevention activities, infrastructure modifications, telehealth); and (c) Learning (participatory governance with city councils, business sector and organized population). The study suggests that the local health systems analysed benefited from the initiatives of health personnel that in some cases positively exceeded their duties. In terms of the resilience analysis, they were able to handle the impact of the crisis and cope with it. Their transformative capacity came from the strategies implemented to adapt health services by managing institutional resources. Their experience represents a lesson on the strengthening of the essential functions of health systems and shows a way to address successfully the increasingly complex health challenges of the present and future times.
A CROSS-CULTURAL INVESTIGATION OF SELF-COMPASSION IN ADOLESCENTS ACROSS GENDER
Authors: Cheung H N , Ho W S , Chan S W Y , Williams J 
Published: July 2022

Abstract

Background
Self-compassion encourages one to accept oneself, reduce self-criticism and self-judgment, and see one’s shortcomings and setbacks in a balanced view. Adolescent self-compassion is a crucial protective factor against mental illness. It is, however, affected by gender. Given the scarcity of self-compassion scales for adolescents, the current study evaluates the Self-Compassion Scale for Youth (SCS-Y) in a large cross-cultural sample and investigates how the subscales of SCS-Y relate to the dimensions of depressive symptoms across gender.

Subjects and Methods
Through the internet-based Qualtrics, a total of 2881 teenagers aged 12 to 18 years were recruited from Hong Kong (HK), China, and the United Kingdom. A Multiple Indicator Multiple Cause (MIMIC) model was used to evaluate measurement invariance of the SCS-Y, and differential item functioning (DIF) was checked across gender. Upon the establishment of the best model, a multigroup structural equation model (SEM) was built between factors of SCS-Y and Multidimensional depression assessment scale (MDAS) which assesses four dimensions of depressive symptoms (emotional, cognitive, somatic and interpersonal).

Results
The SCS-Y was shown to have good reliability and validity. The MIMIC model produced a good model fit for a hypothetical six-factor model (CFI = 0.980; TLI = 0.974; RMSEA = 0.038) and no item was flagged for DIF across gender. A gender difference was observed between SCS-Y factors and depression dimensions.

Conclusions
The SCS-Y exhibits good psychometric characteristics, including measurement invariance across gender. The study also highlights the gender difference between self-compassion factors and depression dimensions.

Acknowledgements
Supported by a project grant from Hong Kong Metropolitan University Research and Development Scheme (PACRD/R6423).
SUPPRESSOR EFFECT OF FACEBOOK USAGES ON OBSESSIVE BELIEFS
Authors: Lee Soon Li 
Published: July 2022

Abstract

Background
This research aimed to demonstrate a significant suppressor effect between Facebook usages (Facebook intensity and Facebook addiction) on obsessive beliefs (threat, perfectionism, inflated responsibility, control of thoughts).

Subjects and Methods
Participants were 204 university students who completed self-reported measures of Facebook intensity, Facebook addiction, and obsessive beliefs. To examine the significance of the suppressor effect, the conceptual models were analyzed using GSCA Pro.

Results
Results indicated that the suppressor effect was not significant. Facebook intensity, which refers to regular Facebook use, did not significantly predict the facets of obsessive beliefs. Facebook addiction, which represents the maladaptive use of Facebook, significantly predicted these facets.

Conclusions
Results indicated that Facebook intensity did not increase the relationship between Facebook addiction and obsessive beliefs. Facebook addiction increases the saliency of obsessive beliefs, which possibly increases the risk of OCD.

Acknowledgements
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
An alert tool to promote lung protective ventilation for possible acute respiratory distress syndrome
Authors: Knighton Andrew J , Kuttler Kathryn G , Ranade-Kharkar Pallavi , Allen Lauren , Throne Taylor , Jacobs Jason R , Carpenter Lori , Winberg Carrie , Johnson Kyle , Shrestha Neer , Ferraro Jeffrey P , Wolfe Doug , Peltan Ithan D , Srivastava Rajendu , Grissom Colin K 
Published: July 2022

Abstract

Objective
Computer-aided decision tools may speed recognition of acute respiratory distress syndrome (ARDS) and promote consistent, timely treatment using lung-protective ventilation (LPV). This study evaluated implementation and service (process) outcomes with deployment and use of a clinical decision support (CDS) synchronous alert tool associated with existing computerized ventilator protocols and targeted patients with possible ARDS not receiving LPV.

Materials and Methods
We performed an explanatory mixed methods study from December 2019 to November 2020 to evaluate CDS alert implementation outcomes across 13 intensive care units (ICU) in an integrated healthcare system with &gt;4000 mechanically ventilated patients annually. We utilized quantitative methods to measure service outcomes including CDS alert tool utilization, accuracy, and implementation effectiveness. Attitudes regarding the appropriateness and acceptability of the CDS tool were assessed via an electronic field survey of physicians and advanced practice providers.

Results
Thirty-eight percent of study encounters had at least one episode of LPV nonadherence. Addition of LPV treatment detection logic prevented an estimated 1812 alert messages (41%) over use of disease detection logic alone. Forty-eight percent of alert recommendations were implemented within 2 h. Alert accuracy was estimated at 63% when compared to gold standard ARDS adjudication, with sensitivity of 85% and positive predictive value of 62%. Fifty-seven percent of survey respondents observed one or more benefits associated with the alert.

Conclusion
Introduction of a CDS alert tool based upon ARDS risk factors and integrated with computerized ventilator protocol instructions increased visibility to gaps in LPV use and promoted increased adherence to LPV.
Outcomes of COVID-19 Vaccination–Related Incidental Axillary Adenopathy in Women Undergoing Breast MRI
Authors: Zuckerman Samantha P , McDonald Elizabeth S , Weinstein Susan P , Birnbaum Julia A , Tobey Jennifer D , Conant Emily F , Edmonds Christine E 
Published: July 2022

Abstract

Objective
To assess the frequency, management, and early outcomes of COVID-19 vaccine–related adenopathy on breast MRI.

Methods
This IRB-exempt retrospective study reviewed patients who underwent breast MRI following COVID-19 vaccine approval in the U.S. from December 14, 2020, to April 11, 2021 (N = 1912) and compared patients who underwent breast MRI the year prior to the pandemic, March 13, 2019, to March 12, 2020 (N = 5342). Study indication, patient age, date of study, date and type of vaccination(s), time difference between study and vaccinations, lymph node–specific and overall management recommendations, and outcomes of additional examinations were recorded. Differences in the final assessment categories between the subjects scanned pre-pandemic and post-vaccine were compared using the Fisher exact test.

Results
Vaccine-related adenopathy was mentioned in 67 breast MRI reports; only 1 in the pre-pandemic group. There were no clinically relevant differences in patient demographics between groups. There was a statistically significant increase in BI-RADS 0 assessments between the pre-pandemic and post-vaccine approval groups—0.8% (45/5342) versus 1.8% (34/1912) (P = 0.001) and BI-RADS 3 assessments—6.5% (348/5342) versus 9.2% (176/1912) (P &lt; 0.0001). Of the 29 patients who underwent additional imaging (range, 2–94 days following MRI) and the 2 patients who underwent biopsy, 47% (31/66), none were found to have malignant adenopathy.

Conclusion
COVID-19 vaccination is associated with transient axillary adenopathy of variable duration. This leads to additional imaging in women undergoing breast MRI, so far with benign outcomes, and this may affect audits of outcomes of MRI.
Recent progress on the activation of the cGAS–STING pathway and its regulation by biomolecular condensation
Authors: Yu Xiaoyu , Zhao Zhen , Jiang Zhengfan 
Published: July 2022

ABSTRACT
The cyclic guanosine monophosphate (GMP)–adenosine monophosphate (AMP) synthetase (cGAS)–stimulator of interferon genes (STING) pathway, comprising the DNA sensor cGAS, the second messenger cyclic GMP–AMP (cGAMP), and the endoplasmic reticulum (ER) adaptor protein STING, detects cytoplasmic double-stranded DNA (dsDNA) to trigger type I-interferon responses for host defense against pathogens. Previous studies defined a model for the allosteric activation of cGAS by DNA-binding, but recent work reveals other layers of mechanisms to regulate cGAS activation such as the phase condensation and metal ions, especially the discovery of Mn2+ as a cGAS activator. Activation of the 2′3′-cGAMP sensor STING requires translocating from the ER to the Golgi apparatus. The sulfated glycosaminoglycans at the Golgi are found to be the second STING ligand promoting STING oligomerization and activation in addition to 2′3′-cGAMP, while surpassed levels of 2′3′-cGAMP induce ER-located STING to form a highly organized ER membranous condensate named STING phase-separator to restrain STING activation. Here, we summarize recent advances in the regulation of cGAS–STING activation and their implications in physiological or pathological conditions, particularly focusing on the emerging complexity of the regulation.
Leaf litter decomposition characteristics and controlling factors across two contrasting forest types
Authors: Zhao Yuan-Yuan , Li Zhuo-Ting , Xu Ting , Lou An-ru 
Published: July 2022

Abstract
Plant leaf litter decomposition provides a source of energy and nutrients in forest ecosystems. In addition to traditional environmental factors, the degradation process of litter is also affected by plant functional traits and litter quality. However, at the community level, it is still unclear whether the relative importance of plant traits and litter quality on the litter decomposition rate is consistent. A year-long mixed leaf litter decomposition experiment in a similar environment was implemented by using the litterbag method in seven typical forest types in Dongling Mountain, Beijing, North China, including six monodominant communities dominated by Juglans mandshurica, Populus cathayana, Betula dahurica, Betula platyphylla, Pinus tabuliformis and Larix gmelinii var. principis-rupprechtii and one codominant community dominated by Fraxinus rhynchophylla, Quercus mongolica and Tilia mongolica. The results showed that there were considerable differences in the litter decomposition rate (k-rate) among the different forest types. The community weighted mean (CWM) traits of green leaves and litter quality explained 35.60% and 9.05% of the k-rate variations, respectively, and the interpretation rate of their interaction was 23.37%, indicating that the CWM traits and their interaction with litter quality are the main factors affecting the k-rate variations. In the recommended daily allowance, leaf nitrogen content, leaf dry matter content, leaf tannin content and specific leaf area were the main factors affecting the k-rate variations. Therefore, we suggest that future studies should focus on the effects of the CWM traits of green leaves on litter decomposition at the community level.
A Rare Etiology for Ascending Paralysis in an Infant
Authors: Abe Keisuke , Casamina Chanel , Ching Natascha , Abe Keith K , Melish Marian , Thompson Karen S , Ahmed Asim A , Purohit Prashant J 
Published: July 2022

Abstract
An 11-month-old male infant with ascending paralysis had an unremarkable initial cerebrospinal fluid (CSF) analysis and imaging. Progressive neurological symptoms resulted in repeated CSF sampling, microscopy, and plasma microbial cell-free DNA next-generation sequencing analysis, that in combination with epidemiology, confirmed the diagnosis.
Measuring the thermal and ionization state of the low-z IGM using likelihood free inference
Authors: Hu Teng , Khaire Vikram , Hennawi Joseph F , Walther Michael , Hiss Hector , Alsing Justin , Oñorbe Jose , Lukic Zarija , Davies Frederick 
Published: July 2022

ABSTRACT
We present a new approach to measure the power-law temperature density relationship $T=T_0 (\rho/ \bar{\rho })^{\gamma -1}$ and the UV background photoionization rate $\Gamma _{{{{\rm H\, {\small I}}}}{}}$ of the intergalactic medium (IGM) based on the Voigt profile decomposition of the Ly α forest into a set of discrete absorption lines with Doppler parameter b and the neutral hydrogen column density $N_{\rm H\, {\small I}}$. Previous work demonstrated that the shape of the $b-N_{{{{\rm H\, {\small I}}}}{}}$ distribution is sensitive to the IGM thermal parameters T0 and γ, whereas our new inference algorithm also takes into account the normalization of the distribution, i.e. the line-density dN/dz, and we demonstrate that precise constraints can also be obtained on $\Gamma _{{{{\rm H\, {\small I}}}}{}}$. We use density-estimation likelihood-free inference (DELFI) to emulate the dependence of the $b-N_{{{{\rm H\, {\small I}}}}{}}$ distribution on IGM parameters trained on an ensemble of 624 nyx hydrodynamical simulations at z = 0.1, which we combine with a Gaussian process emulator of the normalization. To demonstrate the efficacy of this approach, we generate hundreds of realizations of realistic mock HST/COS data sets, each comprising 34 quasar sightlines, and forward model the noise and resolution to match the real data. We use this large ensemble of mocks to extensively test our inference and empirically demonstrate that our posterior distributions are robust. Our analysis shows that by applying our new approach to existing Ly α forest spectra at z ≃ 0.1, one can measure the thermal and ionization state of the IGM with very high precision ($\sigma _{\log T_0} \sim 0.08$ dex, σγ ∼ 0.06, and $\sigma _{\log \Gamma _{{{{\rm H\, {\small I}}}}{}}} \sim 0.07$ dex).