bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrooxidation of Phenol on Polyelectrolyte Modified Carbon Electrodes for Use in Insulin Pump Infusion Sets
Authors: Zhou Lingyun , Huber David E. , van Antwerp Bill , Pennathur Sumita
Published: September 2022

Background:

Many type 1 diabetes patients using continuous subcutaneous insulin infusion (CSII) suffer from the phenomenon of unexplained hypoglycemia or “site loss.” Site loss is hypothesized to be caused by toxic excipients, for example, phenolic compounds within insulin formulations that are used as preservatives and stabilizers. Here, we develop a bioinspired polyelectrolyte-modified carbon electrode for effective electrooxidative removal of phenol from insulin and eventual incorporations into an infusion set of a CSII device.

Methods:

We modified a carbon screen printed electrode (SPE) with poly-L-lysine (PLL) to avoid passivation due to polyphenol deposition while still removing phenolic compounds from insulin injections. We characterized these electrodes using scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) and compared their data with data from bare SPEs. Furthermore, we performed electrochemical measurements to determine the extent of passivation, and high-performance liquid chromatography (HPLC) measurements to confirm both the removal of phenol and the integrity of insulin after phenol removal.

Results:

Voltammetry measurements show that electrode passivation due to polyphenol deposition is reduced by a factor of 2X. HPLC measurements confirm a 10x greater removal of phenol by our modified electrodes relative to bare electrodes.

Conclusion:

Using bioinspired polyelectrolytes to modify a carbon electrode surface aids in the electrooxidation of phenolic compounds from insulin and is a step toward integration within an infusion set for mitigating site loss.
Comparison of the triglyceride glucose (TyG) index, triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, and metabolic score for insulin resistance (METS-IR) associated with periodontitis in Korean adults
Authors: Lee Yea-Chan , Lee Ji-Won , Kwon Yu-Jin
Published: September 2022

Background:

Periodontitis is one of the most common diseases associated with the oral cavity. Previous studies have suggested that there is an association between periodontitis and metabolic dysfunction. Recently, the triglyceride glucose (TyG) index, high-density lipoprotein cholesterol (TG/HDL-C) ratio, and metabolic score for insulin resistance (METS-IR) index have been identified as useful markers for assessing insulin resistance.

Objective:

This study aimed to evaluate the relationship between periodontitis and non-insulin-based insulin resistance (IR) indices and compare the predictive values of these indices in the Korean population.

Design:

This is a cross-sectional study.

Methods:

A total of 13,584 participants were included in the 2013–2015 Korean National Health and Nutrition Examination Survey data. A community periodontal index score⩾3 was used to define periodontitis. Participants were divided into quartiles according to each index. Odds ratios (ORs) and 95% confidence intervals (CIs) for the prevalence of periodontitis and the TyG index, TG/HDL-C ratio, and METS-IR index quartiles were calculated using multiple logistic regression analysis. We estimated the areas under the receiver operating characteristic curves (AUCs) of the indices to compare the predictive values of the three indices.

Results:

Compared with quartile 1, the fourth quartile ORs (95% CIs) for periodontitis were 1.23 (1.01–1.49) for the TyG index, 1.23 (1.02–1.48) for the TG/HDL-C ratio, and 1.53 (1.25–1.88) for the METS-IR index after adjustment for confounders. The AUC (95% CIs) was 0.608 (0.598–0.618) for the TyG index, 0.600 (0.590–0.610) for the TG/HDL-C ratio, and 0.617 (0.608–0.627) for the METS-IR index to identify periodontitis. The predictive power of METS-IR was significantly higher than that of the TyG index and TG/HDL-C.

Conclusion:

Higher TG/HDL-C ratio, TyG, and METS-IR indices are associated with a higher prevalence of periodontitis. The METS-IR index is a more powerful predictor of periodontitis prevalence than the TyG index and TG/HDL-C ratio.
The Self-Censoring Majority: How Political Identity and Ideology Impacts Willingness to Self-Censor and Fear of Isolation in the United States
Authors: Burnett Alycia , Knighton Devin , Wilson Christopher
Published: September 2022

The spiral of silence theory suggests that those who hold a contrary opinion to the majority tend to remain silent; however, social media may be flipping this upside down. The majority may remain silent to the hardcore vocal minority, implying a self-censoring majority. This study examines the spiral of silence theory, and the effect of political identity and ideology has on the willingness to self-censor and the fear of isolation with social media use. Through a survey distributed through a Qualtrics panel to participants that mirror the US census ( N = 1,047), this study investigates political identity and ideology by examining self-censorship and fear of isolation of social media users. Results identify significant differences with self-censorship and identity politics between strong conservatives and liberals in comparison to the majority in the middle. Differing political ideologies seem to have an impact on fear of isolation between democrats and conservatives.
The third way of global Internet governance: A dialogue with Terry Flew
Authors: Flew Terry , Lin Fen
Published: September 2022

In this dialogue, Terry Flew first outlines “a synoptic history” of the dominant discourses on Internet regulation. By exploring the global experiences over the past decades, Flew then articulates “the third way” of global Internet governance. Differing from both the “Silicon Valley” model of the United States and the state-led Chinese model, “the third way” is proposed to be built on trust and regulation. The typology of Internet governance addresses the tension between the nation-state and global market and emphasizes the balance between communication technology and law. Flew further elaborates on the importance of the multi-stakeholder approach in the future of global Internet governance and the challenges such an approach is facing. In addition, Flew offers advice on further research in Internet governance and platform regulation.
Testing Content Validity of Nursing Stress Scales: Do They Reflect Current Practice?
Authors: Pavek Katie U. , Steege Linsey M. , Kwekkeboom Kristine
Published: September 2022

Nurses are subject to considerable stress, arising from the physical, psychological, and social aspects of their work. Widely used nursing occupational stress measures were developed decades ago and may not adequately capture contemporary sources of stress. The study purpose was to evaluate the content validity of items from existing measures and newly developed items to identify a nursing stress scale that can be used to measure occupational stress in current practice. A three-phase approach for development and evaluation of occupational stress items was conducted. Phase 1: item generation; Phase 2: ( N = 11) content expert evaluation of content validity of occupational stress items; Phase 3: subsample ( n = 4) of experts reviewing select items. The total item pool was reduced from 73 to 66 items. Expert reviews indicated acceptable content validity of the Revised Nursing Stress Scale. The Revised Nursing Stress Scale is an updated measure of occupational stress in contemporary nursing practice.
Collective wisdom in polarized groups
Authors: Bak-Coleman Joseph B , Tokita Christopher K , Morris Dylan H , Rubenstein Daniel I , Couzin Iain D
Published: September 2022

The potential for groups to outperform the cognitive capabilities of even highly skilled individuals, known as the “wisdom of the crowd”, is crucial to the functioning of democratic institutions. In recent years, increasing polarization has led to concern about its effects on the accuracy of electorates, juries, courts, and congress. While there is empirical evidence of collective wisdom in partisan crowds, a general theory has remained elusive. Central to the challenge is the difficulty of disentangling the effect of limited interaction between opposing groups (homophily) from their tendency to hold opposing viewpoints (partisanship). To overcome this challenge, we develop an agent-based model of collective wisdom parameterized by the experimentally-measured behaviour of participants across the political spectrum. In doing so, we reveal that differences across the political spectrum in how individuals express and respond to knowledge interact with the structure of the network to either promote or undermine wisdom. We verify these findings experimentally and construct a more general theoretical framework. Finally, we provide evidence that incidental, context-specific differences across the political spectrum likely determine the impact of polarization. Overall, our results show that whether polarized groups benefit from collective wisdom is generally predictable but highly context-specific.
A descriptive analysis of collective intelligence publications since 2000, and the emerging influence of artificial intelligence
Authors: Berditchevskaia Aleks , Maliaraki Eirini , Stathoulopoulos Konstantinos
Published: September 2022

Collective intelligence (CI) is an interdisciplinary field that draws on a wide range of academic disciplines but has struggled to capitalise on cross-pollination between fields, particularly ones which do not self-identify with the collective intelligence label. Past studies have largely undertaken a qualitative and manual approach to classifying different trends in the CI literature. This method risks missing a significant proportion of publications in the field. To this end, we present the first attempt to reflect the field to itself through an automated and quantitative descriptive approach using Microsoft Academic Graph (MAG) to collect and analyse 39,334 CI papers. We further focus our investigation on a subset of the CI literature, at the intersection of artificial intelligence (AI) and CI to understand how these two fields are interacting. We show that while the annual number of CI-only publications has remained steady since 2015, AI+CI research has continued to increase. Publications in the crossover of AI+CI are growing at a faster rate than CI-only papers but show less topical and disciplinary breadth. This may be having a spillover effect on the topical focus of non-AI collective intelligence research. We hope this analysis sheds more light on the dynamics of the CI ecosystem.
Collective intelligence for deep learning: A survey of recent developments
Authors: Ha David , Tang Yujin
Published: September 2022

In the past decade, we have witnessed the rise of deep learning to dominate the field of artificial intelligence. Advances in artificial neural networks alongside corresponding advances in hardware accelerators with large memory capacity, together with the availability of large datasets enabled practitioners to train and deploy sophisticated neural network models that achieve state-of-the-art performance on tasks across several fields spanning computer vision, natural language processing, and reinforcement learning. However, as these neural networks become bigger, more complex, and more widely used, fundamental problems with current deep learning models become more apparent. State-of-the-art deep learning models are known to suffer from issues that range from poor robustness, inability to adapt to novel task settings, to requiring rigid and inflexible configuration assumptions. Collective behavior, commonly observed in nature, tends to produce systems that are robust, adaptable, and have less rigid assumptions about the environment configuration. Collective intelligence, as a field, studies the group intelligence that emerges from the interactions of many individuals. Within this field, ideas such as self-organization, emergent behavior, swarm optimization, and cellular automata were developed to model and explain complex systems. It is therefore natural to see these ideas incorporated into newer deep learning methods. In this review, we will provide a historical context of neural network research’s involvement with complex systems, and highlight several active areas in modern deep learning research that incorporate the principles of collective intelligence to advance its capabilities. We hope this review can serve as a bridge between the complex systems and deep learning communities.
Need and baseline for harmonising nursing education in respiratory care: preliminary results of a global survey
Authors: Šajnić Andreja , Kelly Carol , Smith Sheree , Heslop-Marshall Karen , Axelsson Malin , Padilha José Miguel , Roberts Nicola , Hernández Carmen , Murray Bridget , Poot Betty , Narsavage Georgia
Published: September 2022

Background

The COVID-19 pandemic confirmed that respiratory nurses are critical healthcare providers. Limited knowledge is available about appropriate education to prepare nurses to deliver high-quality respiratory care. A survey was developed by the International Coalition for Respiratory Nursing (ICRN) group to identify the need for a respiratory nursing core curriculum.

Method

A 39-item survey was distributed to 33 respiratory nursing experts in 27 countries. Questions asked about current roles, perception of need, expectations for a core curriculum project and respiratory content in nursing education in their countries.

Results

30 responses from 25 countries were analysed; participants predominantly worked in academia (53.3%, 16/30) and clinical practice (40%, 12/30). In total, 97% (29/30) confirmed a need for a core respiratory nursing curriculum. Post-registration nursing programmes at bachelor (83.3%, 25/30) and masters (63.3%, 19/30) levels include internal/medical nursing care; less than half identified separate respiratory nursing content. The core educational programme developed should include knowledge (70%, 21/30), skills (60%, 18/30), and competencies (50%, 15/30), with separate paediatric and adult content.

Conclusion

Survey results confirm a wide variation in nursing education and respiratory nursing education across the world, with many countries lacking any formal educational programmes to prepare nurses capable of providing enhanced quality respiratory care. These findings support the need for a core respiratory curriculum. To advance this significant work the ICRN group plans to conduct a Delphi study to identify core curriculum requirements for respiratory nursing education at pre-registration and advanced educational levels to flexibly meet each country's specific educational requirements for recognition of respiratory nursing speciality practice.
Initiatives and challenges in using gamification in transportation: a systematic mapping
Authors: Wang Wenjing , Gan Hongcheng , Wang Xinyu , Lu Huan , Huang Yue
Published: September 2022

Gamification is a new theme that has been applied in different fields and has contributed to different types of behavioural change. This paper aims to describe how gamification is adopted in the context of transportation.

Methods

We performed a systematic mapping of the scientific literature of Web of Science and retrieved 211 studies. After the inclusion and exclusion criteria were applied, 66 studies were selected. After the full texts were read, 30 studies remained to be analysed.

Findings

The results show that the most commonly used gamification elements are goals/challenges and points. Gamification provides support for outcomes such as changing travel behaviour, improving driving behaviour and encouraging bicycle commuting. The use of gamification has changed the behavior of travelers, promoted sustainable travel modes, encouraged safe driving, reduced carbon dioxide emissions and reduced energy consumption. Although gamification has achieved many positive results related to transportation, there are still many difficulties and challenges.
Utilization of abortion services from an unsafe provider and associated factors among women with history of induced abortion in Ghana
Authors: Klu Desmond , Yeboah Isaac , Kayi Esinam Afi , Okyere Joshua , Essiaw Mary Naana
Published: September 2022

Background

In sub-Saharan Africa (SSA), numerous studies have examined women’s choice of abortion methods and services using hospital-based data, community-based surveys and nationally representative data. Little research focuses on the factors influencing a woman’s choice of abortion provider. This study sought to identify factors that are associated with why a woman seeks abortion care services from an unsafe provider in Ghana.

Methods

We used nationally representative data of women from the 2017 Ghana Maternal Health Survey (GMHS). Data analysis was restricted to women aged 15–49 with a recent history of induced abortion. Analyses focused on a weighted sample of 1,880. Descriptive analysis and the chi-square test were used to examine the proportion of women utilizing abortion services from unsafe providers. Factors hypothesized to affect the utilization of abortion services from unsafe providers were examined using both bivariable and multivariable logistic regression analyses.

Results

The proportion of survey respondents who reported that they utilize abortion service from unsafe providers were 57.5%. After adjusting for confounders, those who have knowledge of abortion legality [aOR: 0.381 (0.271–0.541)] and those who have attained secondary or higher education [aOR: 0.613 (0.411–0.914)] were less likely to use abortion services from unsafe providers. On the other hand, women belonging to the Ewe ethnic group [aOR: 0.696 (0.508–0.953)], those residing in the middle belt zone [aOR: 1.743 (1.113–2.728)], younger women aged 15–29 years [aOR: 2.037 (1.234–3.362)] were more likely to use abortion services from unsafe abortion providers.

Conclusions

This research suggests that increasing the knowledge of women on the legal status of abortion through public education and encouraging more women to pursue secondary or higher education can contribute to reducing the use of abortion services from unsafe providers. These interventions should be targeted among younger women and those who reside in the middle belt zones of Ghana.
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma
Authors: Kim Hyung Min , Byun Seok-Soo , Kim Jung Kwon , Jeong Chang Wook , Kwak Cheol , Hwang Eu Chang , Kang Seok Ho , Chung Jinsoo , Kim Yong-June , Ha Yun-Sok , Hong Sung-Hoo
Published: September 2022

Background

Renal cell carcinoma is characterized by a late recurrence that occurs 5 years after surgery; hence, continuous monitoring and follow-up is necessary. Prognosis of late recurrence of renal cell carcinoma can only be improved if it is detected early and treated appropriately. Therefore, tools for rapid and accurate renal cell carcinoma prediction are essential.

Methods

This study aimed to develop a prediction model for late recurrence after surgery in patients with renal cell carcinoma that can be used as a clinical decision support system for the early detection of late recurrence. We used the KOrean Renal Cell Carcinoma database that contains large-scale cohort data of patients with renal cell carcinoma in Korea. From the collected data, we constructed a dataset of 2956 patients for the analysis. Late recurrence and non-recurrence were classified by applying eight machine learning models, and model performance was evaluated using the area under the receiver operating characteristic curve.

Results

Of the eight models, the AdaBoost model showed the highest performance. The developed algorithm showed a sensitivity of 0.673, specificity of 0.807, accuracy of 0.799, area under the receiver operating characteristic curve of 0.740, and F1-score of 0.609.

Conclusions

To the best of our knowledge, we developed the first algorithm to predict the probability of a late recurrence 5 years after surgery. This algorithm may be used by clinicians to identify patients at high risk of late recurrence that require long-term follow-up and to establish patient-specific treatment strategies.
Time course of the triglyceride glucose index accumulation with the risk of cardiovascular disease and all-cause mortality
Authors: Tian Xue , Chen Shuohua , Zhang Yijun , Zhang Xiaoli , Xu Qin , Wang Penglian , Wu Shouling , Wang Anxin , Luo Yanxia
Published: September 2022

Background

Future risk of cardiovascular disease (CVD) and mortality is associated with cumulative amount TyG index (cumTyG) exposure, while whether time course of TyG accumulation modulates the risk remains unclear. This study sought to examine the associations of cumTyG index accumulation time course with the risk of CVD and all-cause mortality.

Methods

We enrolled 51,734 participants free of CVD and underwent three examinations at year 2006, 2008, and 2010. CumTyG from baseline to the third examination was calculated. Time course of cumTyG accumulation was calculated as the slope of TyG versus time from 2006 to 2010, or as splinting the overall TyG index accumulation into early (cumTyG06 − 08) and late accumulation (cumTyG08 − 10). Participants were categorized by the combination of cumTyG < or ≥ median (34.44 × years) and a negative or positive TyG slope.

Results

During a median follow-up of 9.04 years, we identified 3,602 incident CVD cases and 3,165 deaths. The risk of CVD and all-cause mortality increased with decreased TyG slope, the corresponding adjusted hazard ratio (aHR) with 95% confidence interval (CI) was 1.11 (1.04–1.19) and 1.18 (1.10–1.26) for patients with a negative TyG slope, respectively. Consistently, a later accumulation of TyG index was not associated with the risk of CVD and all-cause mortality after adjustment for an early accumulation. When considering the combination of cumTyG index and time course, participants with a cumTyG ≥ median and a negative TyG slope had elevated risk of CVD (aHR, 1.37; 95% CI, 1.24–1.51) and all-cause mortality (aHR, 1.28; 95% CI, 1.15–1.43). Additionally, the association was more prominent in young adults.

Conclusion

Early TyG index accumulation resulted in a greater risk of CVD and all-cause mortality than later TyG later accumulation with the same overall cumulative exposure, emphasizing the importance of optimal TyG index control earlier in life.
Risk prediction models for incident type 2 diabetes in Chinese people with intermediate hyperglycemia: a systematic literature review and external validation study
Authors: Xu Shishi , Coleman Ruth L. , Wan Qin , Gu Yeqing , Meng Ge , Song Kun , Shi Zumin , Xie Qian , Tuomilehto Jaakko , Holman Rury R. , Niu Kaijun , Tong Nanwei
Published: September 2022

Background

People with intermediate hyperglycemia (IH), including impaired fasting glucose and/or impaired glucose tolerance, are at higher risk of developing type 2 diabetes (T2D) than those with normoglycemia. We aimed to evaluate the performance of published T2D risk prediction models in Chinese people with IH to inform them about the choice of primary diabetes prevention measures.

Methods

A systematic literature search was conducted to identify Asian-derived T2D risk prediction models, which were eligible if they were built on a prospective cohort of Asian adults without diabetes at baseline and utilized routinely-available variables to predict future risk of T2D. These Asian-derived and five prespecified non-Asian derived T2D risk prediction models were divided into BASIC (clinical variables only) and EXTENDED (plus laboratory variables) versions, with validation performed on them in three prospective Chinese IH cohorts: ACE (n = 3241), Luzhou (n = 1333), and TCLSIH (n = 1702). Model performance was assessed in terms of discrimination (C-statistic) and calibration (Hosmer–Lemeshow test).

Results

Forty-four Asian and five non-Asian studies comprising 21 BASIC and 46 EXTENDED T2D risk prediction models for validation were identified. The majority were at high (n = 43, 87.8%) or unclear (n = 3, 6.1%) risk of bias, while only three studies (6.1%) were scored at low risk of bias. BASIC models showed poor-to-moderate discrimination with C-statistics 0.52–0.60, 0.50–0.59, and 0.50–0.64 in the ACE, Luzhou, and TCLSIH cohorts respectively. EXTENDED models showed poor-to-acceptable discrimination with C-statistics 0.54–0.73, 0.52–0.67, and 0.59–0.78 respectively. Fifteen BASIC and 40 EXTENDED models showed poor calibration (P < 0.05), overpredicting or underestimating the observed diabetes risk. Most recalibrated models showed improved calibration but modestly-to-severely overestimated diabetes risk in the three cohorts. The NAVIGATOR model showed the best discrimination in the three cohorts but had poor calibration (P < 0.05).

Conclusions

In Chinese people with IH, previously published BASIC models to predict T2D did not exhibit good discrimination or calibration. Several EXTENDED models performed better, but a robust Chinese T2D risk prediction tool in people with IH remains a major unmet need.
Glucose consumption rate-dependent transcriptome profiling of Escherichia coli provides insight on performance as microbial factories
Authors: Fragoso-Jiménez Juan Carlos , Gutierrez-Rios Rosa María , Flores Noemí , Martinez Alfredo , Lara Alvaro R. , Delvigne Frank , Gosset Guillermo
Published: September 2022

Background

The modification of glucose import capacity is an engineering strategy that has been shown to improve the characteristics ofEscherichia colias a microbial factory. A reduction in glucose import capacity can have a positive effect on production strain performance, however, this is not always the case. In this study,E. coliW3110 and a group of four isogenic derivative strains, harboring single or multiple deletions of genes encoding phosphoenolpyruvate:sugar phosphotransferase system (PTS)-dependent transporters as well as non-PTS transporters were characterized by determining their transcriptomic response to reduced glucose import capacity.

Results

These strains were grown in bioreactors with M9 mineral salts medium containing 20 g/L of glucose, where they displayed specific growth rates ranging from 0.67 to 0.27 h−1, and specific glucose consumption rates (qs) ranging from 1.78 to 0.37 g/g h. RNA-seq analysis revealed a transcriptional response consistent with carbon source limitation among all the mutant strains, involving functions related to transport and metabolism of alternate carbon sources and characterized by a decrease in genes encoding glycolytic enzymes and an increase in gluconeogenic functions. A total of 107 and 185 genes displayed positive and negative correlations withqs, respectively. Functions displaying positive correlation included energy generation, amino acid biosynthesis, and sugar import.

Conclusion

Changes in gene expression ofE. colistrains with impaired glucose import capacity could be correlated withqsvalues and this allowed an inference of the physiological state of each mutant. In strains with lowerqsvalues, a gene expression pattern is consistent with energy limitation and entry into the stationary phase. This physiological state could explain why these strains display a lower capacity to produce recombinant protein, even when they show very low rates of acetate production. The comparison of the transcriptomes of the engineered strains employed as microbial factories is an effective approach for identifying favorable phenotypes with the potential to improve the synthesis of biotechnological products.
Emerging role of non-coding RNAs in the regulation of Sonic Hedgehog signaling pathway
Authors: Ghafouri-Fard Soudeh , Khoshbakht Tayyebeh , Hussen Bashdar Mahmud , Taheri Mohammad , Samsami Majid
Published: September 2022

Sonic Hedgehog (Shh) signaling cascade is one of the complex signaling pathways that control the accurately organized developmental processes in multicellular organisms. This pathway has fundamental roles in the tumor formation and induction of resistance to conventional therapies. Numerous non-coding RNAs (ncRNAs) have been found to interact with Shh pathway to induce several pathogenic processes, including malignant and non-malignant disorders. Many of the Shh-interacting ncRNAs are oncogenes whose expressions have been increased in diverse malignancies. A number of Shh-targeting miRNAs such as miR-26a, miR-1471, miR-129-5p, miR-361-3p, miR-26b-5p and miR-361-3p have been found to be down-regulated in tumor tissues. In addition to malignant conditions, Shh-interacting ncRNAs can affect tissue regeneration and development of neurodegenerative disorders. XIST, LOC101930370, lncRNA-Hh, circBCBM1, SNHG6, LINC‐PINT, TUG1 and LINC01426 are among long non-coding RNAs/circular RNAs that interact with Shh pathway. Moreover, miR-424, miR-26a, miR-1471, miR-125a, miR-210, miR-130a-5p, miR-199b, miR-155, let-7, miR-30c, miR-326, miR-26b-5p, miR-9, miR-132, miR-146a and miR-425-5p are among Shh-interacting miRNAs. The current review summarizes the interactions between ncRNAs and Shh in these contexts.
Beta amyloid deposition and cognitive decline in Parkinson’s disease: a study of the PPMI cohort
Authors: Mihaescu Alexander S. , Valli Mikaeel , Uribe Carme , Diez-Cirarda Maria , Masellis Mario , Graff-Guerrero Ariel , Strafella Antonio P.
Published: September 2022

The accumulation of beta amyloid in the brain has a complex and poorly understood impact on the progression of Parkinson’s disease pathology and much controversy remains regarding its role, specifically in cognitive decline symptoms. Some studies have found increased beta amyloid burden is associated with worsening cognitive impairment in Parkinson’s disease, especially in cases where dementia occurs, while other studies failed to replicate this finding. To better understand this relationship, we examined a cohort of 25 idiopathic Parkinson’s disease patients and 30 healthy controls from the Parkinson’s Progression Marker Initiative database. These participants underwent [18F]Florbetaben positron emission tomography scans to quantify beta amyloid deposition in 20 cortical regions. We then analyzed this beta amyloid data alongside the longitudinal Montreal Cognitive Assessment scores across 3 years to see how participant’s baseline beta amyloid levels affected their cognitive scores prospectively. The first analysis we performed with these data was a hierarchical cluster analysis to help identify brain regions that shared similarity. We found that beta amyloid clusters differently in Parkinson’s disease patients compared to healthy controls. In the Parkinson’s disease group, increased beta amyloid burden in cluster 2 was associated with worse cognitive ability, compared to deposition in clusters 1 or 3. We also performed a stepwise linear regression where we found an adjusted R2 of 0.495 (49.5%) in a model explaining the Parkinson’s disease group’s Montreal Cognitive Assessment score 1-year post-scan, encompassing the left gyrus rectus, the left anterior cingulate cortex, and the right parietal cortex. Taken together, these results suggest regional beta amyloid deposition alone has a moderate effect on predicting future cognitive decline in Parkinson’s disease patients. The patchwork effect of beta amyloid deposition on cognitive ability may be part of what separates cognitive impairment from cognitive sparing in Parkinson’s disease. Thus, we suggest it would be more useful to measure beta amyloid burden in specific brain regions rather than using a whole-brain global beta amyloid composite score and use this information as a tool for determining which Parkinson’s disease patients are most at risk for future cognitive decline.
Combined alteration of lamin and nuclear morphology influences the localization of the tumor-associated factor AKTIP
Authors: La Torre Mattia , Merigliano Chiara , Maccaroni Klizia , Chojnowski Alexandre , Goh Wah Ing , Giubettini Maria , Vernì Fiammetta , Capanni Cristina , Rhodes Daniela , Wright Graham , Burke Brian , Soddu Silvia , Burla Romina , Saggio Isabella
Published: September 2022

Background

Lamins, key nuclear lamina components, have been proposed as candidate risk biomarkers in different types of cancer but their accuracy is still debated. AKTIP is a telomeric protein with the property of being enriched at the nuclear lamina. AKTIP has similarity with the tumor susceptibility gene TSG101. AKTIP deficiency generates genome instability and, in p53−/−mice, the reduction of the mouse counterpart of AKTIP induces the exacerbation of lymphomas. Here, we asked whether the distribution of AKTIP is altered in cancer cells and whether this is associated with alterations of lamins.

Methods

We performed super-resolution imaging, quantification of lamin expression and nuclear morphology on HeLa, MCF7, and A549 tumor cells, and on non-transformed fibroblasts from healthy donor and HGPS (LMNA c.1824C > T p.Gly608Gly) and EDMD2 (LMNA c.775 T > G) patients. As proof of principle model combining a defined lamin alteration with a tumor cell setting, we produced HeLa cells exogenously expressing the HGPS lamin mutant progerin that alters nuclear morphology.

Results

In HeLa cells, AKTIP locates at less than 0.5 µm from the nuclear rim and co-localizes with lamin A/C. As compared to HeLa, there is a reduced co-localization of AKTIP with lamin A/C in both MCF7 and A549. Additionally, MCF7 display lower amounts of AKTIP at the rim. The analyses in non-transformed fibroblasts show that AKTIP mislocalizes in HGPS cells but not in EDMD2. The integrated analysis of lamin expression, nuclear morphology, and AKTIP topology shows that positioning of AKTIP is influenced not only by lamin expression, but also by nuclear morphology. This conclusion is validated by progerin-expressing HeLa cells in which nuclei are morphologically altered and AKTIP is mislocalized.

Conclusions

Our data show that the combined alteration of lamin and nuclear morphology influences the localization of the tumor-associated factor AKTIP. The results also point to the fact that lamin alterations per se are not predictive of AKTIP mislocalization, in both non-transformed and tumor cells. In more general terms, this study supports the thesis that a combined analytical approach should be preferred to predict lamin-associated changes in tumor cells. This paves the way of next translational evaluation to validate the use of this combined analytical approach as risk biomarker.
Immune-mediated diseases are associated with a higher incidence of dementia: a prospective cohort study of 375,894 individuals
Authors: Zhang Ya-Ru , Yang Liu , Wang Hui-Fu , Wu Bang-Sheng , Huang Shu-Yi , Cheng Wei , Feng Jian-Feng , Yu Jin-Tai
Published: September 2022

Background

Immune system dysregulation plays a vital role in the pathogenesis of neurodegenerative diseases, even considered to be as important as classical pathological protein aggregation assumption. However, the associations of immune-mediated diseases with incident dementia are unclear and need to be clarified in prospective studies with a large population and long follow-up time.

Methods

We investigated the relationship between any or individual immune-mediated diseases and incident dementia based on a prospective cohort UK Biobank. The risk for dementia was assessed with multivariable hazard ratio (HR) and 95% confidence interval (CI) after adjusting for various potential confounders using time-varying Cox proportional hazards regression. We also performed the subgroup Cox analysis stratified by time since immune-mediated diseases and gender. Causal mediation analyses with 1000 bootstrapped iterations were conducted to explore the mediation effects of peripheral immune cells on the associations of immune-mediated diseases with dementia.

Results

A total of 375,894 participants were included in the study, among which 5291 developed dementia during a median follow-up of 9.08 years. Immune-mediated diseases were associated with an increased risk of dementia (HR, 1.10; 95% CI, 1.00–1.21), and the risk was highest between 1 and 2 years after immune-mediated diseases onset (HR, 2.74; 95% CI, 1.86–4.04). Females who suffered from immune-mediated diseases were more prone to AD, while males were more susceptible to VD. Four of the individual immune-mediated diseases including type I diabetes mellitus (HR, 2.49; 95% CI, 1.97–3.15), rheumatic fever or rheumatic heart diseases (HR, 1.36; 95% CI, 1.05–1.77), multiple sclerosis (HR, 2.87; 95% CI, 1.92–4.30), and necrotizing vasculopathies (HR, 1.71; 95%CI, 1.03–2.85) were significantly related to higher dementia incidence. The relationship between immune-mediated diseases and dementia was partially mediated by peripheral immune cells including neutrophils and lymphocytes.

Conclusions

In this large cohort study, immune-mediated diseases were proven to be significantly associated with an increased risk of incident dementia, especially for type I diabetes mellitus which was observed to be related to the higher incidence of all types of dementia. Our findings could provide new sights on dementia pathogenesis and intervention from the perspective of systemic immunology and immune-mediated diseases.
Improved CTAB method for RNA extraction of thick waxy leaf tissues from sago palm (Metroxylon sagu Rottb.)
Authors: Yan Wei-Jie , Pendi Fifi Hafizzah , Hussain Hasnain
Published: September 2022

Background

There is a growing interest in transcriptomics studies parallel to the advancement of transcriptome databases and bioinformatics, which provided the opportunity to study responses to growths, stimuli and stresses. There is an increase in demand for excellent RNA extraction techniques. General RNA extraction protocols can be used in RNA extraction, but the quality and quantity vary in different types of tissues from different organisms. Hence, a specific RNA extraction method for each organism’s tissue type is required to obtain the desired RNA quality and quantity.

Results

The improved CTAB RNA extraction method is superior to the PCI method and MRIP method for thick waxy leaves that were applied for mature sago palm (Metroxylon saguRottb.) leaf tissue and produce total RNA extract with good purity (OD 260/280 ≥ 1.8, OD 260/230 ≥ 2.0) and integrity (RIN ~ 7). RNA sequencing was conducted with the extracted samples and showed good assembly results (Q20 ≥ 97, Q30 ≥ 91%, assembly mean length ≥ 700 bp).

Conclusion

The improved CTAB RNA extraction method enables rapid, cost-effective, and relatively simple RNA extraction from waxy, fibrous and high-in-polyphenol sago palm (M. saguRottb.) leaf tissue with next-generation RNA sequencing recommended quality.

Graphical Abstract
Integrating arts with STEM and leading with STEAM to increase science learning with equity for emerging bilingual learners in the United States
Authors: Hughes Bradley S. , Corrigan Michael W. , Grove Douglas , Andersen Sage B. , Wong Joseph T.
Published: September 2022

Background

To inform STEM education for benefiting emerging bilingual (EB) and English fluent (EF) students, the present study evaluated the order effects of integrating science and arts within a large-scale, ongoing effort investigating the efficacies of Next Generation Science Standards (NGSS)-aligned Science Technology, Engineering, and Math (STEM) methodologies to provide more equitable opportunities to students to learn science through Arts integration (STEAM). The experiment examines the curriculum integrating order of implementing combinations of STEM and STEAM approaches in fifth grade life and physical science instruction, comparing (STEM → STEAM) vs (STEAM → STEM).

Results

Ttests and a three-way between-groups analysis of covariance examined the impact of instructional order, language fluency, and teachers’ implementation fidelity. Findings indicate similar results in life and physical sciences, in which the STEAM first approach produced significantly higher science learning gains for both EF and EB students, revealing some higher learning gains for EF students, but with greater STEAM first order effect advantages for EB students overall. While EF students show higher learning gain scores in the high fidelity classrooms, the advantage of the STEAM first order is greater for EB students in all classroom fidelity levels and even within low to moderate implementation fidelity classrooms, as may commonly occur, such that the integration order of STEAM before STEM strategy is particularly advantageous to EB learners.

Conclusions

The integration pattern of leading with STEAM and following with STEM offers an important opportunity to learn for EB students, and increases equity in opportunities to learn among EB and EF learners of science. Both EB and EF students benefit similarly and significantly in high fidelity implementation classrooms. However, the gains for EF students are not significant in low fidelity implementation classrooms, while in such low fidelity implementation classrooms, the EB students still benefited significantly despite the poor implementation. These results suggest that a strong compensating STEAM first order effect advantage is possibly involved in the implementation system for the EB population of learners. Teaching science through the arts with STEAM lessons is an effective approach that can be significantly improved through introducing STEM units with the STEAM first order effect advantage.
Machine learning-based calibration of the GOCE satellite platform magnetometers
Authors: Styp-Rekowski Kevin , Michaelis Ingo , Stolle Claudia , Baerenzung Julien , Korte Monika , Kao Odej
Published: September 2022

Additional datasets from space-based observations of the Earth’s magnetic field are of high value to space physics and geomagnetism. The use of platform magnetometers from non-dedicated satellites has recently successfully provided additional spatial and temporal coverage of the magnetic field. The Gravity and steady-state Ocean Circulation Explorer (GOCE) mission was launched in March 2009 and ended in November 2013 with the purpose of measuring the Earth’s gravity field. It also carried three platform magnetometers onboard. Careful calibration of the platform magnetometers can remove artificial disturbances caused by other satellite payload systems, improving the quality of the measurements. In this work, a machine learning-based approach is presented that uses neural networks to achieve a calibration that can incorporate a variety of collected information about the satellite system. The evaluation has shown that the approach is able to significantly reduce the calibration residual with a mean absolute residual of about 6.47nT for low- and mid-latitudes. In addition, the calibrated platform magnetometer data can be used for reconstructing the lithospheric field, due to the low altitude of the mission, and also observing other magnetic phenomena such as geomagnetic storms. Furthermore, the inclusion of the calibrated platform magnetometer data also allows improvement of geomagnetic field models. The calibrated dataset is published alongside this work.

Graphical Abstract
Successful emergency evacuation from a catastrophic loess landslide reactivated by the torrential rain in October 2021 in Tianshui, Ganusu, NW China
Authors: Zhang Shuai , Sun Ping , Ren Jian , Wang Haojie , Xin Peng , Wang Tao
Published: September 2022

Background

At the beginning of October 2021, the northwest China suffered torrential rainfall and several loess landslides were induced in Northwest China. This work presents a typical case (the Zhongzhai landslide) reactivated during this period in Niangniangba town, Tianshui, Gansu, China. The retrogressive failure was triggered again in the early morning of 5 October 2021 after a succession of torrential rain, and buried 2 houses and damaged another 2 houses. In this work, the geometric feature, soil composition, evolution history and failure process were preliminary described based on field investigation, history satellite images, and unmanned aerial vehicle photogrammetry.

Results

The Zhongzhai landslide is mainly composed of Malan loess and the underlain silty slate, and the sliding surface is localized at their interface. The tensile cracks near the main scarp provide favorable channels for rainfall precipitation and the permeability difference between loess and silty slate enhances the liquefaction occurrence. The counter-tilt silty slate benefits water impoundment and exacerbates the flow-like slope failure. The lag effect is obvious in the Zhongzhai landslide due to the rainfall infiltration process and pore pressure generation.

Conclusions

Although the Zhongzhai landslide is characterized with small scar and shallow sliding surface, it provides a classic case both for evolution history investigation of loess landslide and successful emergency evacuation. Based on our preliminary study, the unstable mass at the source of the Zhongzhai landslide with an area of approximately 3600 m2 that was slightly displaced in this event and has a high possibility to slide in future. Meanwhile, the Zhongzhai landslide is a retrogressive landslide and progressive failure occurred in the 2021 case, further analysis concerning the relationship among rainfall intensity, infiltration rate and pore water generation, as well as motion feature and runout prediction will be conducted.
Exploration of proper heating protocol for injectable horizontal platelet-rich fibrin gel
Authors: Zheng Xijiao , Yan Xiang , Cheng Kai , Feng Mengge , Wang Yulan , Xiao Bing
Published: September 2022

Purpose

Platelet-rich fibrin (PRF) has been proposed as promising biomaterials with the advantages of host accumulation of platelets and leukocytes with entrapment of growth factors and fibrin scaffold. However, limitations including fast resorption rate (~ 2 weeks) restricts its clinical application. Recent studies have demonstrated heating treatment can prolong PRF degradation. Current published articles used the method of 75 °C for 10 min to obtain longer degradation, while few studies investigated the most suitable temperature for heating horizontal PRF. Our present study was to discover and confirm the optimum temperature for heat treatment before obtaining H-PRF gels by investigating their structure, mechanical properties, and bioactivity of the H-PRF gels after heating treatment.

Methods

In the present study, 2-mL upper layer of horizontal PRF was collected and heated at 45 °C, 60 °C, 75 °C, and 90 °C to heat 2-mL upper layer of horizontal PRF for 10 min before mixing with the 2-mL lower layer horizontal PRF. The weight, solidification time and the degradation properties were subsequently recorded. Scanning electron microscopy (SEM) and rheologic tests were carried out to investigate the microstructure and rheologic properties of each H-PRF gel. The biological activity of each H-PRF gel was also evaluated using live/dead staining.

Results

H-PRF gel prepared at 75 °C for 10 min had the fast solidification period (over a tenfold increase than control) as well as the best resistance to degradation. The number of living cells in H-PRF gel is greater than 90%. SEM showed that H-PRF gel becomes denser as the heating temperature increases, and rheologic tests also revealed that the heat treatment improved the mechanical properties of H-PRF gels when compared to non-heated control group. Future clinical studies are needed to further support the clinical application of H-PRF gels in tissue regeneration procedures.

Conclusions

Our results demonstrated that the H-PRF gel obtained at 75 °C for 10 min could produce a uniform, moldable gel with a short time for solidification time, great rheologic behavior and, high percent of live cells in PRF gel. A promising use of the commonly utilized PRF gel was achieved facilitating tissue regeneration and preventing degradation.