bluuebunny/crossref_metadata_2025_split huggingface dataset:
ZNF384–ZEB1 feedback loop regulates breast cancer metastasis
Authors: Meng Qing-Xiang , Wang Ke-Nie , Li Jun-Hui , Zhang Hui , Chen Zhao-Hui , Zhou Xue-Jie , Cao Xu-Chen , Wang Ping , Yu Yue 
Published: September 2022

Abstract
Background
Breast cancer has become the most frequently diagnosed cancer worldwide. Increasing evidence indicated that zinc finger proteins (ZNFs), the largest family of transcription factors, contribute to cancer development and progression. Although ZNF384 is overexpressed in several types of human cancer, the role of ZNF384 in breast cancer remains unknown. Therefore, our research focused on ZNF384 regulation of the malignant phenotype of breast cancer and the underlying molecular mechanisms.

Methods
CCK-8 and colony formation assays were used to evaluate cell proliferation. Transwell and scratch assays were used to evaluate the cell migration and invasion. Chromatin immunoprecipitation (ChIP)-qPCR and luciferase reporter assays were used to confirm the target relationship between ZNF384 and zinc finger E-box binding homeobox 1 (ZEB1). Xenografts were used to monitor the targets in vivo effects.

Results
We noted that ZNF384 was significantly overexpressed in breast cancer and highlighted the oncogenic mechanism of ZNF384. ZNF384 transactivated ZEB1 expression and induced an epithelial and mesenchymal-like phenotype, resulting in breast cancer metastasis. Furthermore, ZNF384 may be a target of miR-485-5p, and ZEB1 can up-regulate ZNF384 expression by repressing miR-485-5p expression. Together, we unveiled a feedback loop of ZNF384–ZEB1 in breast cancer metastasis.

Conclusions
The findings suggest that ZNF384 can serve as a prognostic factor and a therapeutic target for breast cancer patients.
Insights into the combined toxic impacts of phoxim and deltamethrin on the embryo-larval stage of zebrafish (Danio rerio)
Authors: Lv Lu , Gao Zhongwen , Mao Liangang , Liu Xinju , Wang Qiang , Shen Weifeng , Wang Yanhua 
Published: September 2022

Abstract
Background
Pesticides are usually applied as mixtures, and their joint impacts can generate substantial toxicity to organisms. Although exposures to chemical pesticide mixtures make up most occurrences of pesticide exposures, minimal concern has been given to their combined toxicity and interplays to date. In the present study, endpoints of multiple levels were determined to examine the combined toxic impacts of phoxim and deltamethrin on zebrafish (Danio rerio).

Results
Our study showed that the LC50 values of phoxim obtained over a 96-h exposure period for D. rerio during different life stages ranged from 0.24 (0.12–0.33) to 3.39 (2.58–4.86) µM, and those of deltamethrin ranged from 0.0041 (0.0031–0.0060) to 2.97 (1.56–4.69) µM. Combinations of phoxim and deltamethrin displayed synergistic effects on zebrafish embryos. The activities of T-SOD, Cu/Zn-SOD, POD, and CarE varied dramatically under most administrations of phoxim, deltamethrin, and phoxim + deltamethrin combinations relative to the baseline value. Nine genes, namely, Mn-sod, Cu/Zn-sod, cas3, dio1, tsh, ERα, vtg1, cyp17, and crh, related to antioxidation, cell apoptosis, immunity, and the endocrine system were altered to a greater degree under the mixture administration compared with the individual administrations.

Conclusions
In summary, our current data offered a detailed insight into the combined toxic impacts of pesticide mixtures at various endpoints and over a wide range of concentrations. The results emphasized the necessity to consider the administration mixtures during the ecological risk assessment of pesticides.
Transforming L1000 profiles to RNA-seq-like profiles with deep learning
Authors: Jeon Minji , Xie Zhuorui , Evangelista John E. , Wojciechowicz Megan L. , Clarke Daniel J. B. , Ma’ayan Avi 
Published: September 2022

AbstractThe L1000 technology, a cost-effective high-throughput transcriptomics technology, has been applied to profile a collection of human cell lines for their gene expression response to > 30,000 chemical and genetic perturbations. In total, there are currently over 3 million available L1000 profiles. Such a dataset is invaluable for the discovery of drug and target candidates and for inferring mechanisms of action for small molecules. The L1000 assay only measures the mRNA expression of 978 landmark genes while 11,350 additional genes are computationally reliably inferred. The lack of full genome coverage limits knowledge discovery for half of the human protein coding genes, and the potential for integration with other transcriptomics profiling data. Here we present a Deep Learning two-step model that transforms L1000 profiles to RNA-seq-like profiles. The input to the model are the measured 978 landmark genes while the output is a vector of 23,614 RNA-seq-like gene expression profiles. The model first transforms the landmark genes into RNA-seq-like 978 gene profiles using a modified CycleGAN model applied to unpaired data. The transformed 978 RNA-seq-like landmark genes are then extrapolated into the full genome space with a fully connected neural network model. The two-step model achieves 0.914 Pearson’s correlation coefficients and 1.167 root mean square errors when tested on a published paired L1000/RNA-seq dataset produced by the LINCS and GTEx programs. The processed RNA-seq-like profiles are made available for download, signature search, and gene centric reverse search with unique case studies.
Transcriptome analysis and identification of abscisic acid and gibberellin-related genes during seed development of alfalfa (Medicago sativa L.)
Authors: Zhao Lu , Li Mingyu , Ma Xiaomei , Luo Dong , Zhou Qiang , Liu Wenxian , Liu Zhipeng 
Published: September 2022

Abstract
Background
Alfalfa (Medicago sativa) is a widely cultivated plant. Unlike many crops, the main goal of breeding alfalfa is to increase its aboveground biomass rather than the biomass of its seeds. However, the low yield of alfalfa seeds limits alfalfa production. Many studies have explored the factors affecting seed development, in which phytohormones, especially ABA and GAs, play an important role in seed development.

Results
Here, we performed a transcriptome analysis of alfalfa seeds at five development stages. A total of 16,899 differentially expressed genes (DEGs) were identified and classified into 10 clusters, and the enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were determined. The contents of ABA, GA1, GA3, GA4 and GA7 in alfalfa seeds at five development stages were determined. In addition, 14 ABA-related DEGs and 20 GA-related DEGs were identified and analysed. These DEGs are involved in plant hormone pathways and play an important role in seed development. Moreover, morphological and physiological analyses revealed the dynamic changes during the development of alfalfa seeds.

Conclusion
Overall, our study is the first to analyse the transcriptome across various stages of seed development in alfalfa. The results of our study could be used to improve alfalfa seed yield. The key ABA and GA related-genes are potential targets for improving alfalfa seed yield via genetic engineering in the future.
Transcriptional regulation of proanthocyanidin biosynthesis pathway genes and transcription factors in Indigofera stachyodes Lindl. roots
Authors: Wang Chongmin , Li Jun , Zhou Tao , Zhang Yongping , Jin Haijun , Liu Xiaoqing 
Published: September 2022

Abstract
Background
Proanthocyanidins (PAs) have always been considered as important medicinal value component. In order to gain insights into the PA biosynthesis regulatory network in I. stachyodes roots, we analyzed the transcriptome of the I. stachyodes in Leaf, Stem, RootI (one-year-old root), and RootII (two-year-old root).

Results
In this study, a total of 110,779 non-redundant unigenes were obtained, of which 63,863 could be functionally annotated. Simultaneously, 75 structural genes that regulate PA biosynthesis were identified, of these 6 structural genes (IsF3′H1, IsANR2, IsLAR2, IsUGT72L1-3, IsMATE2, IsMATE3) may play an important role in the synthesis of PAs in I. stachyodes roots. Furthermore, co-expression network analysis revealed that 34 IsMYBs, 18 IsbHLHs, 15 IsWRKYs, 9 IsMADSs, and 3 IsWIPs hub TFs are potential regulators for PA accumulation. Among them, IsMYB24 and IsMYB79 may be closely involved in the PA biosynthesis in I. stachyodes roots.

Conclusions
The biosynthesis of PAs in I. stachyodes roots is mainly produced by the subsequent pathway of cyanidin. Our work provides new insights into the molecular pathways underlying PA accumulation and enhances our global understanding of transcriptome dynamics throughout different tissues.
Physical performance reference values for Japanese oldest old: a SONIC study
Authors: Matsumoto Kiyoaki , Gondo Yasuyuki , Masui Yukie , Yasumoto Saori , Yoshida Yuko , Ikebe Kazunori , Arai Yasumichi , Kabayama Mai , Kamide Kei , Akasaka Hiroshi , Ishizaki Tatsuro 
Published: September 2022

AbstractBackgroundThe oldest old, defined as those aged 90 or over, is now the fastest-growing population sector. This study aimed to determine reference values for several physical performance measures (PPMs) among 90-year-olds using internationally standardized measurements and to clarify the characteristics of these indices by comparing their results for 90-year-olds with those for older people 70 and 80.MethodsWe used the Septuagenarians, Octogenarians, and Nonagenarians Investigation with Centenarians (SONIC) study data from 2010 to 2018. The study subjects were 70, 80, and 90-year-olds in the target area eligible to participate in the venue. Excluding those certified for long-term care, the final number of eligible persons is 70s cohort 1000 (2010), 80s cohort 973 (2011), and 90s cohort 690. 90s cohort only consisted of three survey waves: 2012, 2015, and 2018. We used hand grip strength and score on the Short Physical Performance Battery (SPPB) for our physical performance measurements. In addition, we statistically analyzed sex and age differences.ResultThe simple mean ± standard deviation (SD) for the 90-year-old respondents were in men, 24.1 ± 5.4 kg in hand grip strength, 0.80 ± 0.22 m/s in usual gait speed, 17.2 ± 6.73 s in 5times chair stand, 5.89 ± 4.42 s in tandem balance, and 8.3 ± 2.2 in SPPB respectively and in women, 14.4 ± 4.0 kg in hand grip strength, 0.72 ± 0.20 m/s in usual gait speed, 17.8 ± 7.89 s in 5times chair stand, 4.72 ± 4.35 s in tandem balance, and 7.5 ± 2.4 in SPPB, respectively. For all PPMs, the age 90 cohort was statistically significantly different from the age 70 and 80 cohorts (all trendsP <  0.001). Hand grip strength decreased with a similar gradient with age cohort increase of 10 years for both sexes. In contrast, SPPB lower limb score showed a larger drop between the age 80 and 90 cohorts than between the age 70 and 80 cohorts. We also constructed sex-specific appraisal standards according to quintiles.ConclusionsOur study yielded inclusive sex-specific reference values and appraisal standards for major physical performance measures not certified as requiring long-term care, community-dwelling, oldest old Japanese. The characteristics of age-related decline in physical performance differed between the upper and lower extremity assessments.
Absence of long-term changes in urine biomarkers after AKI: findings from the CRIC study
Authors: McCoy Ian E. , Hsu Jesse Y. , Bonventre Joseph V. , Parikh Chirag R. , Go Alan S. , Liu Kathleen D. , Ricardo Ana C. , Srivastava Anand , Cohen Debbie L. , He Jiang , Chen Jing , Rao Panduranga S. , Muiru Anthony N. , Hsu Chi-yuan 
Published: September 2022

Abstract
Background
Mechanisms by which AKI leads to CKD progression remain unclear. Several urine biomarkers have been identified as independent predictors of progressive CKD. It is unknown whether AKI may result in long-term changes in these urine biomarkers, which may mediate the effect of AKI on CKD progression.

Methods
We selected 198 episodes of hospitalized AKI (defined as peak/nadir inpatient serum creatinine values ≥ 1.5) among adult participants in the Chronic Renal Insufficiency Cohort (CRIC) Study. We matched the best non-AKI hospitalization (unique patients) for each AKI hospitalization using pre-hospitalization characteristics including eGFR and urine protein/creatinine ratio. Biomarkers were measured in banked urine samples collected at annual CRIC study visits.

Results
Urine biomarker measurements occurred a median of 7 months before and 5 months after hospitalization. There were no significant differences in the change in urine biomarker-to-creatinine ratio between the AKI and non-AKI groups: KIM-1/Cr + 9% vs + 7%, MCP-1/Cr + 4% vs + 1%, YKL-40/Cr + 7% vs -20%, EGF/Cr -11% vs -8%, UMOD/Cr -2% vs -7% and albumin/Cr + 17% vs + 13% (all p > 0.05).

Conclusion
In this cohort of adults with CKD, AKI did not associate with long-term changes in urine biomarkers.
Optimal therapeutic conditions for the neural stem cell-based management of ischemic stroke: a systematic review and network meta-analysis based on animal studies
Authors: Yang Yongna , Hu Xurui , Qin Qijie , Kong Fanling , Peng Xiaolan , Zhao Jing , Si Jianghua , Yang Zhilong , Xie Shoupin 
Published: September 2022

Abstract
Background
In order to promote the clinical translation of preclinical findings, it is imperative to identify the most optimal therapeutic conditions and adopt them for further animal and human studies. This study aimed to fully
explore the optimal conditions for neural stem cell (NSC)-based ischemic stroke treatment based on animal studies.

Methods
The PubMed, Ovid-Embase, and Web of Science databases were searched in December 2021. The screening of search results, extraction of relevant data, and evaluation of study quality were performed independently by two reviewers.

Results
In total, 52 studies were included for data analysis. Traditional meta-analysis showed that NSCs significantly reduced the modified neurological severity score (mNSS) and volume of cerebral infarct in animal models of ischemic stroke. Network meta-analysis showed that allogeneic embryonic tissue was the best source of NSCs. Further, intracerebral transplantation was the most optimal route of NSC transplantation, and the acute phase was the most suitable stage for intervention. The optimal number of NSCs for transplantation was 1–5×105 in mouse models and 1×106 or 1.8×106 in rat models.

Conclusions
We systematically explored the therapeutic strategy of NSCs in ischemic stroke, but additional research is required to develop optimal therapeutic strategies based on NSCs. Moreover, it is necessary to further improve and standardize the design, implementation, measuring standards, and reporting of animal-based studies to promote the development of better animal experiments and clinical research.
Machine learning for prediction of bronchopulmonary dysplasia-free survival among very preterm infants
Authors: Leigh Rebekah M. , Pham Andrew , Rao Srinandini S. , Vora Farha M. , Hou Gina , Kent Chelsea , Rodriguez Abigail , Narang Arvind , Tan John B. C. , Chou Fu-Sheng 
Published: September 2022

Abstract
Background
Bronchopulmonary dysplasia (BPD) is one of the most common and serious sequelae of prematurity. Prompt diagnosis using prediction tools is crucial for early intervention and prevention of further adverse effects. This study aims to develop a BPD-free survival prediction tool based on the concept of the developmental origin of BPD with machine learning.

Methods
Datasets comprising perinatal factors and early postnatal respiratory support were used for initial model development, followed by combining the two models into a final ensemble model using logistic regression. Simulation of clinical scenarios was performed.

Results
Data from 689 infants were included in the study. We randomly selected data from 80% of infants for model development and used the remaining 20% for validation. The performance of the final model was assessed by receiver operating characteristics which showed 0.921 (95% CI: 0.899–0.943) and 0.899 (95% CI: 0.848–0.949) for the training and the validation datasets, respectively. Simulation data suggests that extubating to CPAP is superior to NIPPV in BPD-free survival. Additionally, successful extubation may be defined as no reintubation for 9 days following initial extubation.

Conclusions
Machine learning-based BPD prediction based on perinatal features and respiratory data may have clinical applicability to promote early targeted intervention in high-risk infants.
The status of depression literacy and its relationship with quality of life among Iranian public population: a cross sectional study
Authors: Tehrani Hadi , Vali Mohebat , Nejatian Mahbobeh , Moshki Mahdi , Charoghchian Khorasani Elham , Jafari Alireza 
Published: September 2022

Abstract
Background
This study was designed and conducted to determine the status of depression literacy (D-Lit) and its relationship with the quality of life across the Iranian population.

Methods
This cross-sectional study was conducted in 2020 among 1382 participating from the general population in Gonabad, Iran. Participants were selected and recruited using a multistage sampling method. Data were collected using three sets of questionnaires (demographic section, D-Lit scale, and quality of life questionnaire). Data were analyzed by SPSS software version 24 and using independent samples t- test, Chi-square test, One-way ANOVA, and Pearson correlation.

Results
Based on the results, the mean (± standard deviation) of D-Lit and quality of life were 44.14 (± 4.69) and 35.81 (± 5.17), respectively. Based on the results of Pearson correlation coefficient, there was a significant positive correlation between D-Lit and quality of life (r = 0.104, p < 0.001). D-Lit was significantly higher in those who reported having consulted with a psychiatrist compared with those who did not (p < 0.001). Participants with a family history of mental illness and those whose family members were referred to a psychologist for psychological issues had significantly higher levels of D-Lit than others (p < 0.001).

Conclusion
Based on the results of this study, some D-Lit projects should be improved. Also, the results revealed that D-Lit is a potential factor that can affect people's mental health status and enhance their quality of life. Therefore, it is necessary to develop appropriate educational programs to enhance D-Lit in the community and ultimately improve the quality of life in the community by reducing mental illness.
Smoking-related psychosocial beliefs and justifications among smokers in India: Findings from Tobacco Control Policy (TCP) India Surveys
Authors: Sidhu Anupreet K. , Pednekar Mangesh S. , Fong Geoffrey T. , Gupta Prakash C. , Quah Anne C. K. , Unger Jennifer , Sussman Steve , Sood Neeraj , Wipfli Heather , Valente Thomas 
Published: September 2022

AbstractBackgroundPrevious research in high-income countries (HICs) has shown that smokers reduce their cognitive dissonance through two types of justifications over time: risk minimizing and functional beliefs. To date, however, the relationship between these justifications and smoking behaviors over time has limited evidence from low- and middle-income countries. This study examines these of justifications and their relation to quitting behavior and intentions among smoking tobacco users in India.MethodsThe data are from the Tobacco Control Policy (TCP) India Survey, a prospective cohort of nationally representative sample of tobacco users. The respondents include smoked tobacco (cigarettes and bidi) users (n = 1112) who participated in both Wave 1 (W1; 2010–2011) and Wave 2 (W2; 2012–2013) surveys. Key measures include questions about psychosocial beliefs such as functional beliefs (e.g., smoking calms you down when you are stressed or upset) and risk-minimizing beliefs (e.g., the medical evidence that smoking is harmful is exaggerated) and quitting behavior and intentions at Wave 2.FindingsOf the 1112 smokers at W1, 78 (7.0%) had quit and 86 (7.8%) had intentions to quit at W2. Compared to W1, there was a significant increase in functional beliefs at W2 among smokers who transitioned to mixed use (using both smoking and smokeless tobacco) and a significant decrease among those who quit. At W2, smokers who quit held significantly lower levels of functional beliefs, than continuing smokers, and mixed users ((M = 2.96, 3.30, and 3.93, respectively,p < .05). In contrast, risk-minimizing beliefs did not change significantly between the two waves. Additionally, higher income and lower functional beliefs were significant predictors of quitting behavior at W2.ConclusionThese results suggest that smokers in India exhibit similar patterns of dissonance reduction as reported in studies from HICs: smokers who quit reduced their smoking justifications in the form of functional beliefs, not risk-minimizing beliefs. Smokers’ beliefs change in concordance with their smoking behavior and functional beliefs tend to play a significant role as compared to risk-minimizing beliefs. Tobacco control messaging and interventions can be framed to target these functional beliefs to facilitate quitting.
Motive perception pathways to the release of personal information to healthcare organizations
Authors: Soellner Michaela , Koenigstorfer Joerg 
Published: September 2022

AbstractBackgroundThe goal of the study is to assess the downstream effects of who requests personal information from individuals for artificial intelligence-(AI) based healthcare research purposes—be it a pharmaceutical company (as an example of a for-profit organization) or a university hospital (as an example of a not-for-profit organization)—as well as their boundary conditions on individuals’ likelihood to release personal information about their health. For the latter, the study considers two dimensions: the tendency to self-disclose (which is aimed to be high so that AI applications can reach their full potential) and the tendency to falsify (which is aimed to be low so that AI applications are based on both valid and reliable data).MethodsAcross three experimental studies with Amazon Mechanical Turk workers from the U.S. (n = 204, n = 330, and n = 328, respectively), Covid-19 was used as the healthcare research context.ResultsUniversity hospitals (vs. pharmaceutical companies) score higher on altruism and lower on egoism. Individuals were more willing to disclose data if they perceived that the requesting organization acts based on altruistic motives (i.e., the motives function as gate openers). Individuals were more likely to protect their data by intending to provide false information when they perceived egoistic motives to be the main driver for the organization requesting their data (i.e., the motives function as a privacy protection tool). Two moderators, namely message appeal (Study 2) and message endorser credibility (Study 3) influence the two indirect pathways of the release of personal information.ConclusionThe findings add to Communication Privacy Management Theory as well as Attribution Theory by suggesting motive-based pathways to the release of correct personal health data. Compared to not-for-profit organizations, for-profit organizations are particularly recommended to match their message appeal with the organizations’ purposes (to provide personal benefit) and to use high-credibility endorsers in order to reduce inherent disadvantages in motive perceptions.