bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of host promiscuity in the invasion process of a seaweed holobiont
Authors: Bonthond Guido , Bayer Till , Krueger-Hadfield Stacy A , Stärck Nadja , Wang Gaoge , Nakaoka Masahiro , Künzel Sven , Weinberger Florian 
Published: January 2021

Abstract
Invasive species are co-introduced with microbiota from their native range and also interact with microbiota found in the novel environment to which they are introduced. Host flexibility toward microbiota, or host promiscuity, is an important trait underlying terrestrial plant invasions. To test whether host promiscuity may be important in macroalgal invasions, we experimentally simulated an invasion in a common garden setting, using the widespread invasive macroalga Agarophyton vermiculophyllum as a model invasive seaweed holobiont. After disturbing the microbiota of individuals from native and non-native populations with antibiotics, we monitored the microbial succession trajectories in the presence of a new source of microbes. Microbial communities were strongly impacted by the treatment and changed compositionally and in terms of diversity but recovered functionally by the end of the experiment in most respects. Beta-diversity in disturbed holobionts strongly decreased, indicating that different populations configure more similar –or more common– microbial communities when exposed to the same conditions. This decline in beta-diversity occurred not only more rapidly, but was also more pronounced in non-native populations, while individuals from native populations retained communities more similar to those observed in the field. This study demonstrates that microbial communities of non-native A. vermiculophyllum are more flexibly adjusted to the environment and suggests that an intraspecific increase in host promiscuity has promoted the invasion process of A. vermiculophyllum. This phenomenon may be important among invasive macroalgal holobionts in general.
Integrative analysis of genome-wide association studies identifies novel loci associated with neuropsychiatric disorders
Authors: Yao Xueming , Glessner Joseph T. , Li Junyi , Qi Xiaohui , Hou Xiaoyuan , Zhu Chonggui , Li Xiaoge , March Michael E. , Yang Liu , Mentch Frank D. , Hain Heather S. , Meng Xinyi , Xia Qianghua , Hakonarson Hakon , Li Jin 
Published: January 2021

AbstractNeuropsychiatric disorders, such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), bipolar disorder (BIP), and major depressive disorder (MDD) share common clinical presentations, suggesting etiologic overlap. A substantial proportion of SNP-based heritability for neuropsychiatric disorders is attributable to genetic components, and genome-wide association studies (GWASs) focusing on individual diseases have identified multiple genetic loci shared between these diseases. Here, we aimed at identifying novel genetic loci associated with individual neuropsychiatric diseases and genetic loci shared by neuropsychiatric diseases. We performed multi-trait joint analyses and meta-analysis across five neuropsychiatric disorders based on their summary statistics from the Psychiatric Genomics Consortium (PGC), and further carried out a replication study of ADHD among 2726 cases and 16299 controls in an independent pediatric cohort. In the multi-trait joint analyses, we found five novel genome-wide significant loci for ADHD, one novel locus for BIP, and ten novel loci for MDD. We further achieved modest replication in our independent pediatric dataset. We conducted fine-mapping and functional annotation through an integrative multi-omics approach and identified causal variants and potential target genes at each novel locus. Gene expression profile and gene-set enrichment analysis further suggested early developmental stage expression pattern and postsynaptic membrane compartment enrichment of candidate genes at the genome-wide significant loci of these neuropsychiatric disorders. Therefore, through a multi-omics approach, we identified novel genetic loci associated with the five neuropsychiatric disorders which may help to better understand the underlying molecular mechanism of neuropsychiatric diseases.
Long-term risk of subsequent cancer incidence among hereditary and nonhereditary retinoblastoma survivors
Authors: Schonfeld Sara J. , Kleinerman Ruth A. , Abramson David H. , Seddon Johanna M. , Tucker Margaret A. , Morton Lindsay M. 
Published: January 2021

Abstract
Background
Increased sarcoma and melanoma risks after hereditary retinoblastoma are well established, whereas less is known about epithelial subsequent malignant neoplasms (SMNs) and risks for multiple (≥2) SMNs.

Methods
Leveraging long-term follow-up and detailed histologic information, we quantified incident SMN risk among 1128 hereditary and 924 nonhereditary retinoblastoma survivors (diagnosed 1914–2006; follow-up through 2016). Standardised incidence ratios (SIRs) compared cancer risk after retinoblastoma relative to the general population. We estimated cumulative incidence accounting for competing risk of death.

Results
Hereditary survivors had statistically significantly increased SMN risk (N = 239; SIR = 11.9; 95% confidence interval [CI] 10.4–13.5), with SIRs >80-fold for sarcomas, nasal cavity tumours and pineoblastoma. Significantly increased risks were also observed for melanoma and central nervous system, oral cavity and breast SMNs (SIRs = 3.1–17), but not the uterus, kidney, lung, bladder, pancreas or other types. Cumulative incidence 50 years following hereditary retinoblastoma was 33.1% (95% CI 29.0–37.2) for a first SMN and 6.0% (95% CI 3.8–8.2) for a second SMN. SMN risk was not increased after nonhereditary retinoblastoma (N = 25; SIR = 0.8; 95% CI 0.5–1.2).

Conclusion
Beyond the established sarcoma and melanoma risks after hereditary retinoblastoma, we demonstrate increased risk for a more limited number of epithelial malignancies than previously suggested. Cumulative incidence estimates emphasise long-term SMN burden after hereditary retinoblastoma.
Comparative analysis of drug response and gene profiling of HER2-targeted tyrosine kinase inhibitors
Authors: Conlon Neil T. , Kooijman Jeffrey J. , van Gerwen Suzanne J. C. , Mulder Winfried R. , Zaman Guido J. R. , Diala Irmina , Eli Lisa D. , Lalani Alshad S. , Crown John , Collins Denis M. 
Published: January 2021

AbstractBackgroundHuman epidermal growth factor 2 (HER2/ERBB2) is frequently amplified/mutated in cancer. The tyrosine kinase inhibitors (TKIs) lapatinib, neratinib, and tucatinib are FDA-approved for the treatment of HER2-positive breast cancer. Direct comparisons of the preclinical efficacy of the TKIs have been limited to small-scale studies. Novel biomarkers are required to define beneficial patient populations.MethodsIn this study, the anti-proliferative effects of the three TKIs were directly compared using a 115 cancer cell line panel. Novel TKI response/resistance markers were identified through cross-analysis of drug response profiles with mutation, gene copy number and expression data.ResultsAll three TKIs were effective against HER2-amplified breast cancer models; neratinib showing the most potent activity, followed by tucatinib then lapatinib. Neratinib displayed the greatest activity inHER2-mutant andEGFR-mutant cells. High expression ofHER2,VTCN1,CDK12, andRAC1correlated with response to all three TKIs. DNA damage repair genes were associated with TKI resistance.BRCA2mutations were correlated with neratinib and tucatinib response, and high expression ofATM,BRCA2, andBRCA1were associated with neratinib resistance.ConclusionsNeratinib was the most effective HER2-targeted TKI againstHER2-amplified, -mutant, andEGFR-mutant cell lines. This analysis revealed novel resistance mechanisms that may be exploited using combinatorial strategies.
MicroRNA-194: a novel regulator of glucagon-like peptide-1 synthesis in intestinal L cells
Authors: Wang Jiao , Zhao Di , Ding Cheng-Zhi , Guo Feng , Wu Li-Na , Huang Feng-Jiao , Liu Yan-Ling , Zhao Shui-Ying , Xin Ying , Ma Sheng-Nan , Ji Hong-Fei , Wang Xiang , Wei Li-Rui 
Published: January 2021

AbstractIn the status of obesity, the glucagon-like peptide-1 (GLP-1) level usually declines and results in metabolic syndrome. This study aimed to investigate the intracellular mechanism of GLP-1 synthesis in L cells from the perspective of microRNA (miRNA). In the present study, we found that GLP-1 level was down-regulated in the plasma and ileum tissues of obese mice, while the ileac miR-194 expression was up-regulated. In vitro experiments indicated that miR-194 overexpression down-regulated GLP-1 level, mRNA levels of proglucagon gene (gcg) and prohormone convertase 1/3 gene (pcsk1), and the nuclear protein level of beta-catenin (β-catenin). Further investigation confirmed that β-catenin could promote gcg transcription through binding to transcription factor 7-like 2 (TCF7L2). miR-194 suppressed gcg mRNA level via negatively regulating TCF7L2 expression. What’s more, forkhead box a1 (Foxa1) could bind to the promoter of pcsk1 and enhanced its transcription. miR-194 suppressed pcsk1 transcription through targeting Foxa1. Besides, the interference of miR-194 reduced palmitate (PA)-induced cell apoptosis and the anti-apoptosis effect of miR-194 inhibitor was abolished by TCF7L2 knockdown. Finally, in HFD-induced obese mice, the silence of miR-194 significantly elevated GLP-1 level and improved the metabolic symptoms caused by GLP-1 deficiency. To sum up, our study found that miR-194 suppressed GLP-1 synthesis in L cells via inhibiting TCF7L2-mediated gcg transcription and Foxa1-mediated pcsk1 transcription. Meanwhile, miR-194 took part in the PA-induced apoptosis of L cells.
Survival of salivary gland cancer stem cells requires mTOR signaling
Authors: Andrade Nathalia P. , Warner Kristy A. , Zhang Zhaocheng , Pearson Alexander T. , Mantesso Andrea , Guimaraēs Douglas M. , Altemani Albina , Mariano Fernanda V. , Nunes Fabio D. , Nör Jacques E. 
Published: January 2021

AbstractAdvanced salivary gland mucoepidermoid carcinoma (MEC) is a relentless cancer that exhibits resistance to conventional chemotherapy. As such, treatment for patients with advanced MEC is tipically radical surgery and radiotherapy. Facial disfigurement and poor quality of life are frequent treatment challenges, and many patients succumb to loco-regional recurrence and/or metastasis. We know that cancer stem-like cells (CSC) drive MEC tumorigenesis. The current study tests the hypothesis that MEC CSC are sensitive to therapeutic inhibition of mTOR. Here, we report a correlation between the long-term clinical outcomes of 17 MEC patients and the intratumoral expression of p-mTOR (p = 0.00294) and p-S6K1 (p = 0.00357). In vitro, we observed that MEC CSC exhibit constitutive activation of the mTOR signaling pathway (i.e., mTOR, AKT, and S6K1), unveiling a potential strategy for targeted ablation of these cells. Using a panel of inhibitors of the mTOR pathway, i.e., rapamycin and temsirolimus (mTOR inhibitors), buparlisib and LY294002 (AKT inhibitors), and PF4708671 (S6K1 inhibitor), we observed consistently dose-dependent decrease in the fraction of CSC, as well as inhibition of secondary sphere formation and self-renewal in three human MEC cell lines (UM-HMC-1,-3A,-3B). Notably, therapeutic inhibition of mTOR with rapamycin or temsirolimus induced preferential apoptosis of CSC, when compared to bulk tumor cells. In contrast, conventional chemotherapeutic drugs (cisplatin, paclitaxel) induced preferential apoptosis of bulk tumor cells and accumulation of CSC. In vivo, therapeutic inhibition of mTOR with temsirolimus caused ablation of CSC and downregulation of Bmi-1 expression (major inducer of stem cell self-renewal) in MEC xenografts. Transplantation of MEC cells genetically silenced for mTOR into immunodeficient mice corroborated the results obtained with temsirolimus. Collectively, these data demonstrated that mTOR signaling is required for CSC survival, and unveiled the therapeutic potential of targeting the mTOR pathway for elimination of highly tumorigenic cancer stem-like cells in salivary gland mucoepidermoid carcinoma.
Gaussian-preserved, non-volatile shape morphing in three-dimensional microstructures for dual-functional electronic devices
Authors: Tian Ziao , Xu Borui , Wan Guangchao , Han Xiaomin , Di Zengfeng , Chen Zi , Mei Yongfeng 
Published: January 2021

AbstractMotile plant structures such as Mimosa pudica leaves, Impatiens glandulifera seedpods, and Dionaea muscipula leaves exhibit fast nastic movements in a few seconds or less. This motion is stimuli-independent mechanical movement following theorema egregium rules. Artificial analogs of tropistic motion in plants are exemplified by shape-morphing systems, which are characterized by high functional robustness and resilience for creating 3D structures. However, all shape-morphing systems developed so far rely exclusively on continuous external stimuli and result in slow response. Here, we report a Gaussian-preserved shape-morphing system to realize ultrafast shape morphing and non-volatile reconfiguration. Relying on the Gaussian-preserved rules, the transformation can be triggered by mechanical or thermal stimuli within a microsecond. Moreover, as localized energy minima are encountered during shape morphing, non-volatile configuration is preserved by geometrically enhanced rigidity. Using this system, we demonstrate a suite of electronic devices that are reconfigurable, and therefore, expand functional diversification.
The impact of COVID-19 and social distancing on people with Parkinson’s disease: a survey study
Authors: Feeney Megan P. , Xu Yaqian , Surface Matthew , Shah Hiral , Vanegas-Arroyave Nora , Chan Amanda K. , Delaney Elizabeth , Przedborski Serge , Beck James C. , Alcalay Roy N. 
Published: January 2021

AbstractAs the COVID-19 pandemic continues to affect the international community, very little is known about its impact on the health and day-to-day activities of people with Parkinson’s disease (PwPD). To better understand the emotional and behavioral consequences of the public health policies implemented to mitigate the spread of SARS-CoV-2 in PwPD, and to explore the factors contributing to accessing alternative health care mechanisms, such as telehealth, we administered an anonymous knowledge, attitude, and practice survey to PwPD and care partners, via the mailing lists of the Parkinson’s Foundation and Columbia University Parkinson’s Disease Center of Excellence with an average response rate of 19.3%. Sufficient information was provided by 1,342 PwPD to be included in the final analysis. Approximately half of respondents reported a negative change in PD symptoms, with 45–66% reporting mood disturbances. Telehealth use increased from 9.7% prior to the pandemic to 63.5% during the pandemic. Higher income and higher education were associated with telehealth use. Services were more often used for doctor’s appointment than physical, occupational, speech, or mental health therapies. Almost half (46%) of PwPD preferred to continue using telehealth always or sometimes after the coronavirus outbreak had ended. Having received support/instruction for telehealth and having a care partner, friend, or family member to help them with the telehealth visit increased the likelihood of continuous use of telehealth after the pandemic ended. Taken together, PD symptoms and management practices were markedly affected by COVID-19. Given the observed demographic limitations of telehealth, expanding its implementation to include additional physical, occupational, psychological, and speech therapies, increasing support for telehealth, as well as reaching underserved (low income) populations is urgently required.
The human O-GlcNAcome database and meta-analysis
Authors: Wulff-Fuentes Eugenia , Berendt Rex R. , Massman Logan , Danner Laura , Malard Florian , Vora Jeet , Kahsay Robel , Olivier-Van Stichelen Stephanie 
Published: January 2021

AbstractOver the past 35 years, ~1700 articles have characterized protein O-GlcNAcylation. Found in almost all living organisms, this post-translational modification of serine and threonine residues is highly conserved and key to biological processes. With half of the primary research articles using human models, the O-GlcNAcome recently reached a milestone of 5000 human proteins identified. Herein, we provide an extensive inventory of human O-GlcNAcylated proteins, their O-GlcNAc sites, identification methods, and corresponding references (www.oglcnac.mcw.edu). In the absence of a comprehensive online resource for O-GlcNAcylated proteins, this list serves as the only database of O-GlcNAcylated proteins. Based on the thorough analysis of the amino acid sequence surrounding 7002 O-GlcNAc sites, we progress toward a more robust semi-consensus sequence for O-GlcNAcylation. Moreover, we offer a comprehensive meta-analysis of human O-GlcNAcylated proteins for protein domains, cellular and tissue distribution, and pathways in health and diseases, reinforcing that O-GlcNAcylation is a master regulator of cell signaling, equal to the widely studied phosphorylation.
AC–DC electropenetrography unmasks fine temporal details of feeding behaviors for two tick species on unsedated hosts
Authors: Reif Kathryn E. , Backus Elaine A. 
Published: January 2021

AbstractTicks are significant nuisance pests and vectors of pathogens for humans, companion animals, and livestock. Limited information on tick feeding behaviors hampers development and rigorous evaluation of tick and tick-borne pathogen control measures. To address this obstacle, the present study examined the utility of AC–DC electropenetrography (EPG) to monitor feeding behaviors of adult Dermacentor variabilis and Amblyomma americanum in real-time. EPG recording was performed during early stages of slow-phase tick feeding using an awake calf host. Both tick species exhibited discernable and stereotypical waveforms of low-, medium-, and high-frequencies. Similar waveform families and types were observed for both tick species; however, species-specific waveform structural differences were also observed. Tick waveforms were hierarchically categorized into three families containing seven types. Some waveform types were conserved by both species (e.g., Types 1b, 1c, 2b, 2c) while others were variably performed among species and individually recorded ticks (e.g., Types 1a, 2a, 2d). This study provides a proof-of-principle demonstration of the feasibility for using EPG to monitor, evaluate, and compare tick feeding behaviors, providing a foundation for future studies aimed at correlating specific feeding behaviors with waveforms, and ultimately the influence of control measures and pathogens on tick feeding behaviors.
Why do inequality and deprivation produce high crime and low trust?
Authors: De Courson Benoît , Nettle Daniel 
Published: January 2021

AbstractHumans sometimes cooperate to mutual advantage, and sometimes exploit one another. In industrialised societies, the prevalence of exploitation, in the form of crime, is related to the distribution of economic resources: more unequal societies tend to have higher crime, as well as lower social trust. We created a model of cooperation and exploitation to explore why this should be. Distinctively, our model features a desperation threshold, a level of resources below which it is extremely damaging to fall. Agents do not belong to fixed types, but condition their behaviour on their current resource level and the behaviour in the population around them. We show that the optimal action for individuals who are close to the desperation threshold is to exploit others. This remains true even in the presence of severe and probable punishment for exploitation, since successful exploitation is the quickest route out of desperation, whereas being punished does not make already desperate states much worse. Simulated populations with a sufficiently unequal distribution of resources rapidly evolve an equilibrium of low trust and zero cooperation: desperate individuals try to exploit, and non-desperate individuals avoid interaction altogether. Making the distribution of resources more equal or increasing social mobility is generally effective in producing a high cooperation, high trust equilibrium; increasing punishment severity is not.
Asthma-prone areas modeling using a machine learning model
Authors: Razavi-Termeh Seyed Vahid , Sadeghi-Niaraki Abolghasem , Choi Soo-Mi 
Published: January 2021

AbstractNowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the number of asthmatics has significantly increased. Therefore, the purpose of our study was to determine the asthma-prone areas in Tehran, Iran considering environmental, spatial factors. Initially, we built a spatial database using 872 locations of children with asthma and 13 environmental factors affecting the disease—distance to parks and streets, rainfall, temperature, humidity, pressure, wind speed, particulate matter (PM 10 and PM 2.5), ozone (O3), sulfur dioxide (SO2), carbon monoxide (CO), and nitrogen dioxide (NO2). Subsequently, utilizing this spatial database, a random forest (RF) machine learning model, and a geographic information system, we prepared a map of asthma-prone areas. For modeling and validation, we deployed 70% and 30%, respectively, of the locations of children with asthma. The results of spatial autocorrelation and RF model showed that the criteria of distance to parks and streets as well as PM 2.5 and PM 10 had the greatest impact on asthma occurrence in the study area. Spatial autocorrelation analyses indicated that the distribution of asthma cases was not random. According to receiver operating characteristic results, the RF model had good accuracy (the area under the curve was 0.987 and 0.921, respectively, for training and testing data).
Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques
Authors: Marcos-Pasero Helena , Colmenarejo Gonzalo , Aguilar-Aguilar Elena , Ramírez de Molina Ana , Reglero Guillermo , Loria-Kohen Viviana 
Published: January 2021

AbstractThe increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potential risk factors: genetics, dietary and physical activity habits, socio-economic environment, lifestyle, etc. In addition, all these factors are expected to exert their influence through a specific and especially convoluted way during childhood, given the fast growth along this period. Machine Learning methods are the appropriate tools to model this complexity, given their ability to cope with high-dimensional, non-linear data. Here, we have analyzed by Machine Learning a sample of 221 children (6–9 years) from Madrid, Spain. Both Random Forest and Gradient Boosting Machine models have been derived to predict the body mass index from a wide set of 190 multidomain variables (including age, sex, genetic polymorphisms, lifestyle, socio-economic, diet, exercise, and gestation ones). A consensus relative importance of the predictors has been estimated through variable importance measures, implemented robustly through an iterative process that included permutation and multiple imputation. We expect this analysis will help to shed light on the most important variables associated to childhood obesity, in order to choose better treatments for its prevention.