bluuebunny/crossref_metadata_2025_split huggingface dataset:
FIRM: Flexible integration of single-cell RNA-sequencing data for large-scale multi-tissue cell atlas datasets
Authors: Ming Jingsi , Lin Zhixiang , Zhao Jia , Wan Xiang ,   The Tabula Microcebus Consortium, Consortium T T M , Ezran C , Liu S , Yang Can , Wu Angela Ruohao 
Published: April 2022

AbstractSingle-cell RNA-sequencing (scRNA-seq) is being used extensively to measure the mRNA expression of individual cells from deconstructed tissues, organs and even entire organisms to generate cell atlas references, leading to discoveries of novel cell types and deeper insight into biological trajectories. These massive datasets are usually collected from many samples using different scRNA-seq technology platforms, including the popular SMART-Seq2 (SS2) and 10X platforms. Inherent heterogeneities between platforms, tissues and other batch effects make scRNA-seq data difficult to compare and integrate, especially in large-scale cell atlas efforts; yet, accurate integration is essential for gaining deeper insights into cell biology. We present FIRM, a re-scaling algorithm which accounts for the effects of cell type compositions, and achieve accurate integration of scRNA-seq datasets across multiple tissue types, platforms and experimental batches. Compared with existing state-of-the-art integration methods, FIRM provides accurate mixing of shared cell type identities and superior preservation of original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis. FIRM is also a facile way to transfer cell type labels and annotations from one dataset to another, making it a reliable and versatile tool for scRNA-seq analysis, especially for cell atlas data integration.
Clinical outcomes of surgical and imatinib treatment for rectal gastrointestinal stromal tumours: retrospective cohort study
Authors: Tsukamoto Shunsuke , Honma Yoshitaka , Shoji Hirokazu , Hirano Hidekazu , Inoue Manabu , Takamizawa Yasuyuki , Moritani Konosuke , Imaizumi Jun , Kanemitsu Yukihide 
Published: April 2022

Abstract

Background
Rectal gastrointestinal stromal tumours (GISTs) are rare and treated mainly by radical surgery. Although the importance of perioperative imatinib has been recognized, there are few reports on its outcomes.

Method
Consecutive patients diagnosed with rectal GISTs between July 2008 and February 2021 were identified from a prospective database. Effects of perioperative imatinib were investigated, and surgical and survival outcomes were compared between neoadjuvant imatinib and upfront surgery.

Results
34 patients meeting the inclusion criteria were identified. Compared with upfront surgery (n = 11), the neoadjuvant imatinib group (n = 23) had significantly larger tumours (median size 8.3 versus 2.5 cm; P = 0.01) and included a significantly greater proportion of high-risk patients according to the modified Fletcher classification (20/23 (87.0%) versus 6/11 (54.5%); P = 0.02). Comparing the operation planned based on imaging before neoadjuvant imatinib and the operation performed, there was an increase in sphincter-preserving surgery (4/23 (17.4%) to 11/23 (47.8%); P = 0.02), abdominoperineal resection 11/23 (47.8%) reduced to 7/23 (30.4%); P = 0.13) and total pelvic exenteration reduced from 8/23 (34.8%) to 5/23 (21.7%); P = 0.01). Tumours were downsized by a median of 30 per cent (range 0 per cent to −56 per cent; P =  0.01). During follow-up (median 42, range 5–131 months), there was no postoperative recurrence in 29 patients who received perioperative imatinib. One of the five patients who underwent surgery without neoadjuvant or adjuvant imatinib developed local recurrence.

Conclusion
Treatment with imatinib for rectal GISTs seems to improve outcomes, and neoadjuvant imatinib increases the rate of sphincter-preserving surgery.
A novel edible packaging film based on chitosan incorporated with persimmon peel extract for the postharvest preservation of banana
Authors: Hu Dongsheng , Liu Xiaogang , Qin Yuyue , Yan Jiatong , Li Jiang , Yang Qiliang 
Published: April 2022

Abstract
This study aimed to develop a novel edible packaging film for the postharvest preservation of banana based on chitosan (CS) and persimmon peel extract (PPE). Scanning electron microscopy analysis showed that PPE was evenly distributed in the CS matrix and Fourier transform infrared spectroscopy analysis showed that CS and PPE interacted to form hydrogen bonds, demonstrating good compatibility. Simultaneously, the addition of PPE also significantly improved the physical properties and antioxidant activity of the CS film. Among them, the CS film containing 10% PPE (CS-PPE 10) showed the optimal mechanical properties, water vapor barrier properties and oxygen barrier properties. The CS film containing 15% PPE (CS-PPE 15) exhibited the best thermal stability, UV-Vis barrier properties and antioxidant activity. In the experiment on banana preservation, CS-PPE 10 film obtained optimal performance on decreasing senescence spots, weight loss, fruit softening, and cell wall degradation, inhibiting the activities of polyphenol oxidase and cell wall-degrading enzymes and maintaining the content of total soluble sugar and ascorbic acid during the storage period. Consequently, CS-PPE 10 film was expected to be a novel edible packaging material to maintain banana quality and prolong shelf life.
A natural genetic variation screen identifies insulin signaling, neuronal communication, and innate immunity as modifiers of hyperglycemia in the absence of Sirt1
Authors: Palu Rebecca A S , Owings Katie G , Garces John G , Nicol Audrey 
Published: April 2022

Abstract
Variation in the onset, progression, and severity of symptoms associated with metabolic disorders such as diabetes impairs the diagnosis and treatment of at-risk patients. Diabetes symptoms, and patient variation in these symptoms, are attributed to a combination of genetic and environmental factors, but identifying the genes and pathways that modify diabetes in humans has proven difficult. A greater understanding of genetic modifiers and the ways in which they interact with metabolic pathways could improve the ability to predict a patient’s risk for severe symptoms, as well as enhance the development of individualized therapeutic approaches. In this study, we use the Drosophila Genetic Reference Panel to identify genetic variation influencing hyperglycemia associated with loss of Sirt1 function. Through analysis of individual candidate functions, physical interaction networks, and gene set enrichment analysis, we identify not only modifiers involved in canonical glucose metabolism and insulin signaling, but also genes important for neuronal signaling and the innate immune response. Furthermore, reducing the expression of several of these candidates suppressed hyperglycemia, making them potential candidate therapeutic targets. These analyses showcase the diverse processes contributing to glucose homeostasis and open up several avenues of future investigation.
A Systematic Review on Navigation Programs for Persons Living With Dementia and Their Caregivers
Authors: Kokorelias Kristina M , Shiers-Hanley Jessica E , Li Zoe , Hitzig Sander L 
Published: April 2022

Abstract

Background and Objectives
System navigation programs are becoming more available to meet the needs of patients with complex care needs. The aim of this review was to systematically assess the outcomes of navigation programs for persons with dementia and their family caregivers.

Research Design and Methods
A systematic review methodology was employed. Ten databases were searched for all relevant articles published until October 30, 2021. English-language full-text articles were included if they focused on implemented navigation program(s) that primarily supported persons with dementia who were aged 50 or older. Methodological quality was assessed by 2 independent raters using the Physiotherapy Evidence Database Scale, the STrengthening the Reporting of OBservational studies in Epidemiology checklist, and the Mixed Methods Appraisal Tool.

Results
Fourteen articles were included in the review. There was Level 1 evidence for the benefits of system navigation programs on delaying institutionalization, wherein benefits appeared to be specific to interventions that had an in-person component. There was Level 1 (n = 4) and Level 3 (n = 1) evidence on service use from time of diagnosis to continued management of dementia. Finally, Level 1 to Level 5 evidence indicated a number of benefits on caregiver outcomes.

Discussion and Implications
There is strong evidence on the benefits of system navigation for people with dementia on delaying institutionalization and caregiver outcomes, but outcomes across other domains (i.e., functional independence) are less clear, which may be due to the varied approaches within system navigation models of care.
A stochastic Gauss–Newton algorithm for regularized semi-discrete optimal transport
Authors: Bercu Bernard , Bigot Jérémie , Gadat Sébastien , Siviero Emilia 
Published: April 2022

Abstract
We introduce a new second order stochastic algorithm to estimate the entropically regularized optimal transport (OT) cost between two probability measures. The source measure can be arbitrary chosen, either absolutely continuous or discrete, whereas the target measure is assumed to be discrete. To solve the semi-dual formulation of such a regularized and semi-discrete optimal transportation problem, we propose to consider a stochastic Gauss–Newton (SGN) algorithm that uses a sequence of data sampled from the source measure. This algorithm is shown to be adaptive to the geometry of the underlying convex optimization problem with no important hyperparameter to be accurately tuned. We establish the almost sure convergence and the asymptotic normality of various estimators of interest that are constructed from this SGN algorithm. We also analyze their non-asymptotic rates of convergence for the expected quadratic risk in the absence of strong convexity of the underlying objective function. The results of numerical experiments from simulated data are also reported to illustrate the finite sample properties of this Gauss–Newton algorithm for stochastic regularized OT and to show its advantages over the use of the stochastic gradient descent, stochastic Newton and ADAM algorithms.
Association between maternal exposure to chemical fertilizer and the risk of birth defects in a rural population in northern China: a population-based study
Authors: Li Jiajia , Lin Shiqi , Wu Jilei , Pei Lijun , Shang Xuejun 
Published: April 2022

Abstract

Background
Maternal exposure to pesticides during early pregnancy is associated with increased risks of birth defects, while the association between maternal exposure to chemical fertilizer during pregnancy and the risk of birth defects remains unknown.

Methods
Data were from a population-based birth defects surveillance system between 2007 and 2012 in Pingding County, Shanxi Province, northern China. A total of 14 074 births with 235 birth defects were used to estimate spatial clustering and correlations at the village level. A population-based case–control study of 157 cases with birth defects and 204 controls was performed to investigate the association between maternal chemical fertilizer exposure and the risk of birth defects by a two-level logistic model.

Results
The total prevalence of birth defects between 2007 and 2012 was 167.0/10 000 births. The spatial analysis indicated a remarkable high-risk area of birth defects in the southeast of Pingding County and the use of chemical fertilizer was associated with the risk of birth defects at the village level. After adjusting for confounders at the individual level, mothers who live in villages with chemical fertilizer application ≥65 tons/y had an increased risk of birth defects (adjusted odds ratio 2.06 [95% confidence interval 1.23 to 3.46]) compared with those of &lt;65 tons/y.

Conclusions
Our findings suggest that the risk of birth defects may be associated with the use of chemical fertilizer in rural northern China. The findings must be cautiously interpreted and need to be investigated on larger samples.
Implementation approaches and barriers for rule-based and machine learning-based sepsis risk prediction tools: a qualitative study
Authors: Joshi Mugdha , Mecklai Keizra , Rozenblum Ronen , Samal Lipika 
Published: April 2022

Abstract

Objective
Many options are currently available for sepsis surveillance clinical decision support (CDS) from electronic medical record (EMR) vendors, third party, and homegrown models drawing on rule-based (RB) and machine learning (ML) algorithms. This study explores sepsis CDS implementation from the perspective of implementation leads by describing the motivations, tool choices, and implementation experiences of a diverse group of implementers.

Materials and Methods
Semi-structured interviews were conducted with and a questionnaire was administered to 21 hospital leaders overseeing CDS implementation at 15 US medical centers. Participants were recruited via convenience sampling. Responses were coded by 2 coders with consensus approach and inductively analyzed for themes.

Results
Use of sepsis CDS is motivated in part by quality metrics for sepsis patients. Choice of tool is driven by ease of integration, customization capability, and perceived predictive potential. Implementation processes for these CDS tools are complex, time-consuming, interdisciplinary undertakings resulting in heterogeneous choice of tools and workflow integration. To improve clinician acceptance, implementers addressed both optimization of the alerts as well as clinician understanding and buy in. More distrust and confusion was reported for ML models, as compared to RB models. Respondents described a variety of approaches to overcome implementation barriers; these approaches related to alert firing, content, integration, and buy-in.

Discussion
While there are shared socio-technical challenges of implementing CDS for both RB and ML models, attention to user education, support, expectation management, and dissemination of effective practices may improve feasibility and effectiveness of ML models in quality improvement efforts.

Conclusion
Further implementation science research is needed to determine real world efficacy of these tools. Clinician acceptance is a significant barrier to sepsis CDS implementation. Successful implementation of less clinically intuitive ML models may require additional attention to user confusion and distrust.
Machine-learning-based quality-level-estimation system for inspecting steel microstructures
Authors: Nishiura Hiromi , Miyamoto Atsushi , Ito Akira , Harada Minoru , Suzuki Shogo , Fujii Kouhei , Morifuji Hiroshi , Takatsuka Hiroyuki 
Published: April 2022

Abstract
Quality control of special steel is accomplished through visual inspection of its microstructure based on microscopic images. This study proposes an ‘automatic-quality-level-estimation system’ based on machine learning. Visual inspection of this type is sensory-based, so training data may include variations in judgments and training errors due to individual differences between inspectors, which makes it easy for a drop in generalization performance to occur due to overfitting. To deal with this issue, we here propose the preprocessing of inspection images and a data augmentation technique. Preprocessing reduces variation in images by extracting features that are highly related to the level of quality from inspection images. Data augmentation, meanwhile, suppresses the problem of overfitting when training with a small number of images by taking into account information on variation in judgment values obtained from on-site experience. While the correct-answer rate for judging the quality level by an inspector was about 90%, the proposed method achieved a correct-answer rate of 92.5%, which indicates that the method shows promise for practical applications.
Hydroxynitrile lyase defends Arabidopsis againstTetranychus urticae
Authors: Arnaiz Ana , Santamaria M Estrella , Rosa-Diaz Irene , Garcia Irene , Dixit Sameer , Vallejos Saul , Gotor Cecilia , Martinez Manuel , Grbic Vojislava , Diaz Isabel 
Published: April 2022

AbstractPlant–pest interactions involve multifaceted processes encompassing a complex crosstalk of pathways, molecules, and regulators aimed at overcoming defenses developed by each interacting organism. Among plant defensive compounds against phytophagous arthropods, cyanide-derived products are toxic molecules that directly target pest physiology. Here, we identified the Arabidopsis (Arabidopsis thaliana) gene encoding hydroxynitrile lyase (AtHNL, At5g10300) as one gene induced in response to spider mite (Tetranychus urticae) infestation. AtHNL catalyzes the reversible interconversion between cyanohydrins and derived carbonyl compounds with free cyanide. AtHNL loss- and gain-of-function Arabidopsis plants showed that specific activity of AtHNL using mandelonitrile as substrate was higher in the overexpressing lines than in wild-type (WT) and mutant lines. Concomitantly, mandelonitrile accumulated at higher levels in mutant lines than in WT plants and was significantly reduced in the AtHNL overexpressing lines. After mite infestation, mandelonitrile content increased in WT and overexpressing plants but not in mutant lines, while hydrogen cyanide (HCN) accumulated in the three infested Arabidopsis genotypes. Feeding bioassays demonstrated that the AtHNL gene participated in Arabidopsis defense against T. urticae. The reduced leaf damage detected in the AtHNL overexpressing lines reflected the mite’s reduced ability to feed on leaves, which consequently restricted mite fecundity. In turn, mites upregulated TuCAS1 encoding β-cyanoalanine synthase to avoid the respiratory damage produced by HCN. This detoxification effect was functionally demonstrated by reduced mite fecundity observed when dsRNA-TuCAS-treated mites fed on WT plants and hnl1 mutant lines. These findings add more players in the Arabidopsis–T. urticae interplay to overcome mutual defenses.
Minimum complexity drives regulatory logic in Boolean models of living systems
Authors: Subbaroyan Ajay , Martin Olivier C , Samal Areejit 
Published: April 2022

AbstractThe properties of random Boolean networks have been investigated extensively as models of regulation in biological systems. However, the Boolean functions (BFs) specifying the associated logical update rules should not be expected to be random. In this contribution, we focus on biologically meaningful types of BFs, and perform a systematic study of their preponderance in a compilation of 2,687 functions extracted from published models. A surprising feature is that most of these BFs have odd “bias”, that is they produce “on” outputs for a total number of input combinations that is odd. Upon further analysis, we are able to explain this observation, along with the enrichment of read-once functions (RoFs) and its nested canalyzing functions (NCFs) subset, in terms of 2 complexity measures: Boolean complexity based on string lengths in formal logic, which is yet unexplored in biological contexts, and the so-called average sensitivity. RoFs minimize Boolean complexity and all such functions have odd bias. Furthermore, NCFs minimize not only the Boolean complexity but also the average sensitivity. These results reveal the importance of minimum complexity in the regulatory logic of biological networks.
Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays
Authors: Thakku Sri Gowtham , Ackerman Cheri M , Myhrvold Cameron , Bhattacharyya Roby P , Livny Jonathan , Ma Peijun , Gomez Giselle Isabella , Sabeti Pardis C , Blainey Paul C , Hung Deborah T 
Published: April 2022

Abstract
Rapid and accurate diagnosis of infections is fundamental to individual patient care and public health management. Nucleic acid detection methods are critical to this effort, but are limited either in the breadth of pathogens targeted or by the expertise and infrastructure required. We present here a high-throughput system that enables rapid identification of bacterial pathogens, bCARMEN, which utilizes: (1) modular CRISPR-Cas13-based nucleic acid detection with enhanced sensitivity and specificity; and (2) a droplet microfluidic system that enables thousands of simultaneous, spatially multiplexed detection reactions at nanoliter volumes; and (3) a novel preamplification strategy that further enhances sensitivity and specificity. We demonstrate bCARMEN is capable of detecting and discriminating 52 clinically relevant bacterial species and several key antibiotic resistance genes. We further develop a simple proof of principle workflow using stabilized reagents and cell phone camera optical readout, opening up the possibility of a rapid point-of-care multiplexed bacterial pathogen identification and antibiotic susceptibility testing.
Artificial light at night: an underappreciated effect on phenology of deciduous woody plants
Authors: Meng Lin , Zhou Yuyu , Román Miguel O , Stokes Eleanor C , Wang Zhuosen , Asrar Ghassem R , Mao Jiafu , Richardson Andrew D , Gu Lianhong , Wang Yiming 
Published: April 2022

Abstract
Artificial light at night (ALAN), an increasing anthropogenic driver, is widespread and shows rapid expansion with potential adverse impact on the terrestrial ecosystem. However, whether and to what extent does ALAN affect plant phenology, a critical factor influencing the timing of terrestrial ecosystem processes, remains unexplored due to limited ALAN observation. Here, we used the Black Marble ALAN product and phenology observations from USA National Phenology Network to investigate the impact of ALAN on deciduous woody plants phenology in the conterminous United States. We found that (1) ALAN significantly advanced the date of breaking leaf buds by 8.9 ± 6.9 days (mean ± SD) and delayed the coloring of leaves by 6.0 ± 11.9 days on average; (2) the magnitude of phenological changes was significantly correlated with the intensity of ALAN (P &lt; 0.001); and (3) there was an interaction between ALAN and temperature on the coloring of leaves, but not on breaking leaf buds. We further showed that under future climate warming scenarios, ALAN will accelerate the advance in breaking leaf buds but exert a more complex effect on the coloring of leaves. This study suggests intensified ALAN may have far-reaching but underappreciated consequences in disrupting key ecosystem functions and services, which requires an interdisciplinary approach to investigate. Developing lighting strategies that minimize the impact of ALAN on ecosystems, especially those embedded and surrounding major cities, is challenging but must be pursued.
Erosion of N = 28 shell closure: Shape coexistence and monopole transition
Authors: Suzuki Y , Horiuchi W , Kimura M 
Published: April 2022

Abstract
In neutron-rich nuclei neighboring 42Si, the quenching of the N = 28 shell gap occurs and is expected to induce shape coexistence in their excitation spectra. We have applied the theoretical framework of antisymmetrized molecular dynamics with the Gogny D1S density functional to describe the shape coexistence in the N = 28 isotones 40Mg, 42Si, and 44S. We show that different nuclear shapes coexist in these nuclei: Rigid shapes with different deformations coexist in 40Mg and 42Si, while 44S exhibits large-amplitude collective motion and does not have any particular shape. These characteristics are reflected well in the monopole transition strengths that can be utilized as a probe for the shape coexistence.