bluuebunny/crossref_metadata_2025_split huggingface dataset:
NONO-TFE3 Fusion Promotes Aerobic Glycolysis and Angiogenesis by Targeting HIF1A in NONO-TFE3 Translocation Renal Cell Carcinoma
Authors: Chen Yi , Yang Lei , Liu Ning , Shi Qiancheng , Yin Xiaoqin , Han Xiaodong , Gan Weidong , Li Dongmei 
Published: April 2021

Background:
NONO-TFE3 translocation renal cell carcinoma (tRCC), one of the RCCs
that are associated with Xp11.2 translocation/TFE3 gene fusion (Xp11.2 tRCCs), involves an X
chromosome inversion between NONO and TFE3 with the characteristics of endonuclear aggregation
of NONO-TFE3 fusion protein. The oncogenic mechanisms of NONO-TFE3 fusion have not
yet been fully elucidated.

Objective:
This study aimed at investigating the mechanism of NONO-TFE3 fusion regulating
HIF1A as well as the role of HIF-1α in the progression of NONO-TFE3 tRCC under hypoxia.

Methods:
Immunohistochemistry and Western Blotting assays were performed to profile HIF-1α
expression in renal clear cell carcinoma (ccRCC) or in Xp11.2 tRCC. Chromatin immunoprecipitation
(ChIP), a luciferase reporter assay, and real-time quantitative PCR (RT-qPCR) were used to
evaluate the regulation of HIF1A expression by NONO-TFE3 fusion. Then, the flow cytometry
analysis, tube formation assays, and cell migration assays were used as well as glucose or lactic
acid levels were measured to establish the impact of HIF-1α on the progression of NONO-TFE3 tRCC.
Besides, the effect of HIF-1α inhibitor (PX-478) on UOK109 cells was analyzed.

Results:
We found that HIF1A was the target gene of NONO-TFE3 fusion. In UOK109 cells,
which were isolated from NONO-TFE3 tRCC samples, NONO-TFE3 fusion promoted aerobic glycolysis
and angiogenesis by up-regulating the expression of HIF-1α under hypoxia. Furthermore,
the inhibition of HIF-1α mediated by PX-478 suppressed the development of NONO-TFE3 tRCC
under hypoxia.

Conclusion:
HIF-1α is a potential target for therapy of NONO-TFE3 tRCC under hypoxia.
Diagnostic Tools, Biomarkers, and Treatments in Diabetic polyneuropathy
and Cardiovascular Autonomic Neuropathy
Authors: Bönhof Gidon J. , Herder Christian , Ziegler Dan 
Published: April 2021

:
The various manifestations of diabetic neuropathy, including distal symmetric sensorimotor
polyneuropathy (DSPN) and cardiovascular autonomic neuropathy (CAN), are among the
most prevalent chronic complications of diabetes. Major clinical complications of diabetic neuropathies,
such as neuropathic pain, chronic foot ulcers, and orthostatic hypotension, are associated
with considerable morbidity, increased mortality, and diminished quality of life. Despite the substantial
individual and socioeconomic burden, the strategies to diagnose and treat diabetic neuropathies
remain insufficient. This review provides an overview of the current clinical aspects and recent
advances in exploring local and systemic biomarkers of both DSPN and CAN assessed in human
studies (such as biomarkers of inflammation and oxidative stress) for better understanding of
the underlying pathophysiology and for improving early detection. Current therapeutic options for
DSPN are (I) causal treatment, including lifestyle modification, optimal glycemic control, and multifactorial
risk intervention, (II) pharmacotherapy derived from pathogenetic concepts, and (III)
analgesic treatment against neuropathic pain. Recent advances in each category are discussed, including
non-pharmacological approaches, such as electrical stimulation. Finally, the current therapeutic
options for cardiovascular autonomic complications are provided. These insights should contribute
to a broader understanding of the various manifestations of diabetic neuropathies from both
the research and clinical perspectives.
Silicon Quantum Dots: Chemical, Physical Synthesis, and Applications in
Fluorescence Detection, Solar Cell, Photocatalyst, and Composite
Authors: Tong Wanzhe , Yin Qinhong , Fang Dong , Zeng Taofang , Yi Jianhong 
Published: April 2021

:
Silicon quantum dots (Si QDs) with the unique properties in light, electricity, magnetism and heat possess the advantages of non-toxic, environmental protection and abundant reserves. They are widely used in various fields and have great potential for development. Till now, numerous researchers have reported the research progress of Si QDs, or elaborated the behavior mechanism. However, there are few summarization and comparison on the properties of quantum dot properties in different fields and different preparation methods. Besides, the parameters of Si QDs vary greatly in different application fields, which is worthy of comparison and summary. During the current work, we review the research progress and synthesis methods in recent years. The main influencing factors of Si QDs of different preparation methods (physical and chemical) and different application properties (fluorescence detection, solar cell, photocatalyst and composite) are compared and discussed in detail. Therefore, this paper aims to find promising preparation methods for different application fields, and to provide a clear direction for researchers to study Si QDs in different directions.
Thioacetamide-Induced Norepinephrine Production by Hepatocytes is Associated
with Hepatic Stellate Cell Activation and Liver Fibrosis
Authors: Tang Wei-Chien , Chang Ya-Wen , Che Mingtian , Wang Mei-Hui , Lai Keith K. , Fueger Patrick T. , Huang Wendong , Lin Shwu-Bin , Lai Keane K. Y. 
Published: April 2021

Background:
Collagen production by activated hepatic stellate cells (HSCs) to encapsulate
injury is part of the natural wound-healing response in injured liver. However, persistent activation
of HSCs can lead to pathological fibrogenesis. Such persistent HSC activation could be mediated
by norepinephrine (NE), a reaction product of dopamine beta-hydroxylase (DBH).

Objective:
To investigate the potential paracrine role of NE in hepatotoxin thioacetamide (TAA)-induced
liver fibrosis.

Methods:
In TAA-treated mice, fibrotic liver tissue showed significant increases in the mRNA expression
of DBH up to 14-fold and collagen up to 7-fold. Immunohistochemical staining showed increased
DBH protein expression in fibrotic liver tissue. Parenchymal hepatocyte cell line HepG2
expressed DBH and secreted NE, and the conditioned medium of HepG2 cells promoted collagenesis
in nonparenchymal HSC cell line LX-2. TAA treatment increased DBH expression by 170% in
HepG2 cells, as well as increased NE by 120% in the conditioned medium of HepG2 cells. The
conditioned medium of TAA-treated HepG2 cells was used to culture LX-2 cells, and was found to
increase collagen expression by 80% in LX-2 cells. Collagen expression was reduced by pre-treating
HepG2 cells with siRNA targeting DBH or by adding NE antagonists to the conditioned medium.

Results:
Finally, TAA-induced oxidative stress in HepG2 cells was associated with induction of
DBH expression. Collectively, our results suggest a potential role for DBH/NE-mediated crosstalk
between hepatocytes and HSCs in fibrogenesis.

Conclusion:
From a therapeutic standpoint, antagonism of DBH/NE induction in hepatocytes
might be a useful strategy to suppress pathological fibrogenesis.
Study of Thermal Conductivity in Two-dimensional Bi2Te3 from Micro- Raman Spectroscopy
Authors: Singh Manavendra P. , Ryntathiang Sumarlang , Krishnan Sivarama , Nayak Pramoda K. 
Published: April 2021

Background:
Topological insulator (TI), Bi2Te3 is a new class of quantum materials.
Having ultralow dissipation surface states, TIs hold great promise toward different potential applications.
Micro-Raman spectroscopy is a conventional and non-destructive technique, which has been
widely used to characterize the structural and electronic properties of thermoelectric materials.

Objective:
The objective of this study is to review power dependent and temperature dependent
Raman spectra of B2Te3 nanoflakes on SiO2/Si substrate to estimate the temperature coefficient and
thermal conductivity of these flakes for possible application of this material in thermoelectrics.

Methods:
Bi2Te3 flakes of different thicknesses were mechanically exfoliated from high-quality
bulk Bi2Te3 crystal using scotch tape on 300 nm SiO2/ Si substrates. The power dependent and temperature
dependent Raman spectra were acquired with the help of HORIBA LabRAM confocal micro-
Raman system in a backscattering geometry.

Result:
The observed power dependent and temperature dependent Raman spectra of Bi2Te3
nanoflakes follow the same trend as discussed in various pieces of literature. From temperature coefficient
and power coefficient values, the in-plane thermal conductivity has been estimated, which
is found to be in the order of 102 W/m-K. The enhancement in the thermal conductivity suggests that
the underlying substrate significantly affects the heat dissipation of the Bi2Te3 flake based on the
coupling strength with Bi2Te3.

Conclusion:
This work provides a good platform to understand the role of the substrate on the thermal
conductivity of exfoliated Bi2Te3 nanoflakes and this study can be extended to other substrates.
Analysis of Mental Health Disease Trends Using BeGraph Software in Spanish Health Care Centers: Case Study
Authors: Góngora Alonso Susel , de Bustos Molina Andrés , Sainz-De-Abajo Beatriz , Franco-Martín Manuel , De la Torre Díez Isabel 
Published: April 2021

Background
In the era of big data, networks are becoming a popular factor in the field of data analysis. Networks are part of the main structure of BeGraph software, which is a 3D visualization application dedicated to the analysis of complex networks.

Objective
The main objective of this research was to visually analyze tendencies of mental health diseases in a region of Spain, using the BeGraph software, in order to make the most appropriate health-related decisions in each case.

Methods
For the study, a database was used with 13,531 records of patients with mental health disorders in three acute medical units from different health care complexes in a region of Spain. For the analysis, BeGraph software was applied. It is a web-based 3D visualization tool that allows the exploration and analysis of data through complex networks.

Results
The results obtained with the BeGraph software allowed us to determine the main disease in each of the health care complexes evaluated. We noted 6.50% (463/7118) of admissions involving unspecified paranoid schizophrenia at the University Clinic of Valladolid, 9.62% (397/4128) of admissions involving chronic paranoid schizophrenia with acute exacerbation at the Zamora Hospital, and 8.84% (202/2285) of admissions involving dysthymic disorder at the Rio Hortega Hospital in Valladolid.

Conclusions
The data analysis allowed us to focus on the main diseases detected in the health care complexes evaluated in order to analyze the behavior of disorders and help in diagnosis and treatment.
Effectiveness of eHealth Nutritional Interventions for Middle-Aged and Older Adults: Systematic Review and Meta-analysis
Authors: Robert Caroline , Erdt Mojisola , Lee James , Cao Yuanyuan , Naharudin Nurhazimah Binte , Theng Yin-Leng 
Published: April 2021

Background
The risk of development of chronic diseases related to poor nutrition increases with age. In the face of an aging population, it is important for health care sectors to find solutions in delivering health services efficiently and effectively to middle-aged and older adults.

Objective
The aim of this systematic review and meta-analysis was to consolidate the literature that reported the effectiveness of eHealth apps in delivering nutritional interventions for middle-aged and older adults.

Methods
A literature search from five databases (PubMed, CINAHL, Cochrane, Web of Science, and Global Health) from the past 5 years was performed. Studies were selected for inclusion that used eHealth to deliver nutritional interventions to adults aged 40 years and above, and reported health and behavioral outcomes. Two independent reviewers searched for research articles and assessed the eligibility of studies to be included in the review. A third reviewer resolved disagreements on study inclusion. We also assessed the quality of the included studies using the CONSORT 2010 checklist.

Results
A total of 70 studies were included for analysis. The study quality ranged from 44% to 85%. The most commonly used eHealth intervention type was mobile apps (22/70, 31%). The majority of studies (62/70, 89%) provided multicomponent health interventions, which aimed to improve nutrition and other health behaviors (eg, exercise, smoking cessation, medication adherence). Meta-analysis results indicated high and significant heterogeneity; hence, conclusions based on these results should be considered with caution. Nonetheless, the results generally showed that eHealth interventions improved anthropometric and clinical outcomes, but not behavioral outcomes such as fruit and vegetable consumption.

Conclusions
The use of eHealth apps to deliver health interventions has been increasing in recent years, and these apps have the potential to deliver health services to a larger group of people. Our findings showed that the effectiveness of eHealth apps to deliver health interventions for middle-aged to older adults was supported by the improvement of anthropometric and clinical outcomes. Future work could aim to develop research frameworks in administering eHealth interventions to address heterogeneity in this field of research.
Neural Network–Based Retinal Nerve Fiber Layer Profile Compensation for Glaucoma Diagnosis in Myopia: Model Development and Validation
Authors: Li Lei , Zhu Haogang , Zhang Zhenyu , Zhao Liang , Xu Liang , Jonas Rahul A , Garway-Heath David F , Jonas Jost B , Wang Ya Xing 
Published: April 2021

Background
Due to the axial elongation–associated changes in the optic nerve and retina in high myopia, traditional methods like optic disc evaluation and visual field are not able to correctly differentiate glaucomatous lesions. It has been clinically challenging to detect glaucoma in highly myopic eyes.

Objective
This study aimed to develop a neural network to adjust for the dependence of the peripapillary retinal nerve fiber layer (RNFL) thickness (RNFLT) profile on age, gender, and ocular biometric parameters and to evaluate the network’s performance for glaucoma diagnosis, especially in high myopia.

Methods
RNFLT with 768 points on the circumferential 3.4-mm scan was measured using spectral-domain optical coherence tomography. A fully connected network and a radial basis function network were trained for vertical (scaling) and horizontal (shift) transformation of the RNFLT profile with adjustment for age, axial length (AL), disc-fovea angle, and distance in a test group of 2223 nonglaucomatous eyes. The performance of RNFLT compensation was evaluated in an independent group of 254 glaucoma patients and 254 nonglaucomatous participants.

Results
By applying the RNFL compensation algorithm, the area under the receiver operating characteristic curve for detecting glaucoma increased from 0.70 to 0.84, from 0.75 to 0.89, from 0.77 to 0.89, and from 0.78 to 0.87 for eyes in the highest 10% percentile subgroup of the AL distribution (mean 26.0, SD 0.9 mm), highest 20% percentile subgroup of the AL distribution (mean 25.3, SD 1.0 mm), highest 30% percentile subgroup of the AL distribution (mean 24.9, SD 1.0 mm), and any AL (mean 23.5, SD 1.2 mm), respectively, in comparison with unadjusted RNFLT. The difference between uncompensated and compensated RNFLT values increased with longer axial length, with enlargement of 19.8%, 18.9%, 16.2%, and 11.3% in the highest 10% percentile subgroup, highest 20% percentile subgroup, highest 30% percentile subgroup, and all eyes, respectively.

Conclusions
In a population-based study sample, an algorithm-based adjustment for age, gender, and ocular biometric parameters improved the diagnostic precision of the RNFLT profile for glaucoma detection particularly in myopic and highly myopic eyes.
Introducing an Integrated Model of Adults’ Wearable Activity Tracker Use and Obesity Information–Seeking Behaviors From a National Quota Sample Survey
Authors: Kim Bokyung , Hong Seoyeon , Kim Sungwook 
Published: April 2021

Background
Research from multiple perspectives to investigate adults’ use of wearable activity-tracking devices is limited. We offer a multiperspective model and provide empirical evidence of what leads to frequent usage of wearable health technologies from a large, nationally representative survey sample.

Objective
This study aims to explore factors affecting the use of wearable activity-tracking devices among health consumers from the perspectives of individual health beliefs (perceived severity, perceived susceptibility, perceived benefits, and self-efficacy) and information-seeking behaviors.

Methods
Our Integrated Model of Wearable Activity Tracker (IMWAT) use and proposed hypotheses were validated and tested with data collected from a telephone survey with a national quota sample. The data were analyzed using a variety of statistical techniques, including structural equation analysis.

Results
The sample comprised 2006 participants. Our results showed that the perceived benefits of physical activity, perceived susceptibility, and self-efficacy toward obesity were significant predictors of information-seeking behaviors, which, in turn, mediated their effects on the use of wearable activity trackers. Perceptions of obesity severity directly promoted wearable device usage.

Conclusions
This study provided a new and powerful theoretical model that combined the health beliefs and information-seeking behaviors behind the use of wearable activity trackers in the adult population. The findings provide meaningful implications for developers and designers of wearable health technology products and will assist health informatics practitioners and obesity prevention communicators.
Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis
Authors: Luo Gang , Nau Claudia L , Crawford William W , Schatz Michael , Zeiger Robert S , Koebnick Corinna 
Published: April 2021

BackgroundAsthma exerts a substantial burden on patients and health care systems. To facilitate preventive care for asthma management and improve patient outcomes, we recently developed two machine learning models, one on Intermountain Healthcare data and the other on Kaiser Permanente Southern California (KPSC) data, to forecast asthma-related hospital visits, including emergency department visits and hospitalizations, in the succeeding 12 months among patients with asthma. As is typical for machine learning approaches, these two models do not explain their forecasting results. To address the interpretability issue of black-box models, we designed an automatic method to offer rule format explanations for the forecasting results of any machine learning model on imbalanced tabular data and to suggest customized interventions with no accuracy loss. Our method worked well for explaining the forecasting results of our Intermountain Healthcare model, but its generalizability to other health care systems remains unknown.ObjectiveThe objective of this study is to evaluate the generalizability of our automatic explanation method to KPSC for forecasting asthma-related hospital visits.MethodsThrough a secondary analysis of 987,506 data instances from 2012 to 2017 at KPSC, we used our method to explain the forecasting results of our KPSC model and to suggest customized interventions. The patient cohort covered a random sample of 70% of patients with asthma who had a KPSC health plan for any period between 2015 and 2018.ResultsOur method explained the forecasting results for 97.57% (2204/2259) of the patients with asthma who were correctly forecasted to undergo asthma-related hospital visits in the succeeding 12 months.ConclusionsFor forecasting asthma-related hospital visits, our automatic explanation method exhibited an acceptable generalizability to KPSC.International Registered Report Identifier (IRRID)RR2-10.2196/resprot.5039
Retention of the Aboriginal Health, Ageing, and Disability Workforce: Protocol for a Mixed Methods Study
Authors: Gilroy John , Bulkeley Kim , Talbot Folau , Gwynn Josephine , Gwynne Kylie , Henningham Mandy , Alcorso Caroline , Rambaldini Boe , Lincoln Michelle 
Published: April 2021

Background
Despite a plethora of research into Aboriginal employment and recruitment, the extent and nature of the retention of frontline Aboriginal people in health, ageing, and disability workforces are currently unknown. In this application, frontline service delivery is defined as Aboriginal people who are paid employees in the health, ageing, and disability service sectors in roles that involve direct client, participant, or patient contact. There is a need to identify the factors that inhibit (push) and promote (pull) staff retention or departure of this workforce from the sectors. This study will provide additional insight about this topic.

Objective
The objective of this project is to uncover the factors that influence the retention of frontline Aboriginal workers in the health, ageing, and disability workforces in New South Wales (NSW) who do not have university qualifications. The aim of the proposed project aims to discover the push and pull factors for the retention of the frontline Aboriginal workforce in the health, ageing, and disability sectors in NSW in relation to their role, employment, and community and design evidence-based strategies for retaining the Aboriginal frontline workforce in the health, ageing, and disability sectors in NSW.

Methods
The proposed research will use a mixed methods approach, collecting both quantitative and qualitative data via surveys and interviews to capture and represent the voices and perspectives of Aboriginal people in a way that the participants chose.

Results
Indigenous research methodologies are a growing field in Aboriginal health research in Australia. A key strength of this study is that it is led by Aboriginal scholars and Aboriginal controlled organizations that apply an Indigenous methodological framework throughout the research process.

Conclusions
This study uses a mixed methods design. The survey and interview questions and model were developed in partnership with Aboriginal health, ageing, and disability service workers rather than relying only on research publications on the workforce, government policies, and human resources strategies. This design places a strong emphasis on generalizable findings together with an inductive approach that explores employers and workers’ lived experience of the Aboriginal health workforce in NSW. Excluding workers who have graduated from university places a strong focus on the workforce who have obtained either school or Technical and Further Education or registered training organizations qualifications. Data collection was conducted during the COVID-19 pandemic, and results will include the unique experiences of Aboriginal workers and employers delivering services in an extremely challenging organizational, community, and personal context.

International Registered Report Identifier (IRRID)
PRR1-10.2196/25261