bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of different helmet types in head injuries: a case–control study in northern Ghana
Authors: Baffour Appiah Anthony , Akweongo Patricia , Sackey Samuel Oko , Morna Martin Tangnaa , Kenu Ernest , Buunaaim Alexis Dun Bo-ib , Debrah Samual Akobour Yaw , Ojo Thomas K , Donkor Peter , Mock Charles N
Published: October 2022

Background

Motorcycle helmet use is low in Ghana and many helmets are non-standard. There are limited data on the effectiveness of the different helmet types in use in the real-world circumstances of low-income and middle-income countries. This study assessed the effect of different helmet types on risk of head injury among motorcycle crash victims in northern Ghana.

Methods

A prospective unmatched case–control study was conducted at the Tamale Teaching Hospital (TTH). All persons who had injuries from a motorcycle crash within 2 weeks of presentation to TTH were consecutively sampled. A total of 349 cases, persons who sustained minor to severe head injury, and 363 controls, persons without head injury, were enrolled. A semistructured questionnaire was used to interview patients and review their medical records. Multivariable logistic regression was used to estimate odds for head injury.

Results

After adjusting for confounders, the odds of head injuries were 93% less in motorcyclists with full-face helmet (FFH) (adjusted OR, AOR 0.07, 95% CI 0.04 to 0.15) or open-face helmet (OFH) (AOR 0.07, 95% CI 0.04, 0.13), compared with unhelmeted motorcyclists. Half-coverage helmets (HCH) were less effective (AOR 0.41, 95% CI 0.18 to 0.92). With exception of HCH, the AORs of head injury for the different types of helmets were lower in riders (FFH=0.06, OFH=0.05 and HCH=0.47) than in pillion riders (FFH=0.11, OFH=0.12 and HCH=0.35).

Conclusion

Even in this environment where there is a high proportion of non-standard helmets, the available helmets provided significant protection against head injury, but with considerably less protection provided by HCHs.
PreferentialMGMThypermethylation in SDH-deficient wild-type GIST
Authors: Giger Olivier T , ten Hoopen Rogier , Shorthouse David , Abdullahi Shukri , Bulusu Venkata Ramesh , Jadhav Saili , Maher Eamonn R , Casey Ruth T
Published: October 2022

Aims

Wild-type gastrointestinal stromal tumours (wtGIST) are frequently caused by inherited pathogenic variants, or somatic alterations in the succinate dehydrogenase subunit genes (SDHx). Succinate dehydrogenase is a key enzyme in the citric acid cycle. SDH deficiency caused bySDHxinactivation leads to an accumulation of succinate, which inhibits DNA and histone demethylase enzymes, resulting in global hypermethylation. Epigenetic silencing of the DNA repair gene MGMT has proven utility as a positive predictor of the therapeutic efficacy of the alklyating drug temozolomide (TMZ) in tumours such as glioblastoma multiforme. The aim of this study was to examine MGMT promoter methylation status in a large cohort of GIST.

Methods

MGMT methylation analysis was performed on 65 tumour samples including 47 wtGIST (33 SDH-deficient wtGIST and 11 SDH preserved wtGIST) and 21 tyrosine kinase (TK) mutant GIST.

Results

MGMTpromoter methylation was detected in 8 cases of SDH-deficient (dSDH) GIST but in none of the 14 SDH preserved wild-type GIST or 21 TK mutant GIST samples analysed. Mean MGMT methylation was significantly higher (p 0.0449) and MGMT expression significantly lower (p<0.0001) in dSDH wtGIST compared with TK mutant or SDH preserved GIST. No correlation was identified betweenSDHxsubunit gene mutations or SDHC epimutation status and mean MGMT methylation levels.

Conclusion

MGMT promoter hypermethylation occurs exclusively in a subset of dSDH wtGIST. Data from this study support testing of tumour MGMT promoter methylation in patients with dSDH wtGIST to identify those patients who may benefit from most from TMZ therapy.
Short-term exposure to ambient air pollution and readmissions for heart failure among 3660 post-discharge patients with hypertension in older Chinese adults
Authors: Xu Ruijun , Tian Qi , Wei Jing , Ye Yunshao , Li Yingxin , Lin Qiaoxuan , Wang Yaqi , Liu Likun , Shi Chunxiang , Xia Wenhao , Liu Yuewei
Published: October 2022

Background

Despite ambient air pollution being associated with various adverse cardiovascular outcomes, the acute effects of ambient air pollution on hospital readmissions for heart failure (HF) among post-discharge patients with hypertension remain less understood.

Methods

We conducted a time-stratified case-crossover study among 3660 subjects 60 years or older who were admitted to hospital for HF after discharge for hypertension in Guangzhou, China during 2016–2019. For each subject, individualised residential exposures to ambient particulate matter with an aerodynamic diameter ≤1 µm (PM1), ≤2.5 µm (PM2.5), ≤10 µm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and ozone were extracted from our validated grid dataset.

Results

An IQR increase of lag 04-day exposure to PM1(IQR: 11.6 μg/m3), PM2.5(IQR 21.9 μg/m3), PM10(IQR 35.0 μg/m3), SO2(IQR 4.4 μg/m3), NO2(IQR 23.3 μg/m3) and CO (IQR 0.25 mg/m3) was significantly associated with a 9.77% (95% CI 2.21% to 17.89%), 8.74% (95% CI 1.05% to 17.00%), 13.93% (95% CI 5.36% to 23.20%), 10.81% (95% CI 1.82% to 20.60%), 14.97% (95% CI 8.05% to 22.34%) and 7.37% (95% CI 0.98% to 14.16%) increase in odds of HF readmissions, respectively. With adjustment for other pollutants, the association for NO2exposure remained stable, while the associations for PM1, PM2.5, PM10, SO2and CO exposures became insignificant. Overall, an estimated 19.86% of HF readmissions were attributable to NO2exposure, while reducing NO2exposure to the WHO and China air quality standards would avoid 12.87% and 0.54% of readmissions, respectively. No susceptible populations were observed by sex, age or season.

Conclusion

Short-term exposure to ambient NO2was significantly associated with an increased odds of HF readmissions among post-discharge patients with hypertension in older Chinese adults.
Frequency of GLP-1 receptor agonists use in diabetic patients diagnosed with delayed gastric emptying and their demographic profile
Authors: Kalas M Ammar , Dang The Q , Galura Gian , Alvarado Luis , Dwivedi Alok Kumar , Deoker Abhizith , McCallum Richard
Published: October 2022

Advances in the management of diabetes mellitus have come a long way in the 21st century. One of the most important developments in diabetes management has been the discovery of glucagon-like peptide-1 (GLP-1) receptor agonists. The most common side effects of GLP-1 receptor (GLP-1R) agonists are nausea and vomiting which have been attributed to delayed gastric emptying. While the effects of GLP-1R agonists on gastric emptying have prompted further research in this field, there are limited studies evaluating their effects on patients with pre-existing gastroparesis. Additionally, the frequency of GLP-1R agonist use among patients with gastroparesis has not been assessed in the past and this study aims to identify that percentage along with evaluating for possible iatrogenic gastroparesis. A retrospective review of all the gastric emptying studies performed at one academic medical center between January 2019 and January 2021 was performed. We found that although patients on GLP-1R agonists were more likely to have delayed gastric emptying, we could not establish a statistical significance. This could be due to the small sample size in the study. However, GLP-1R agonists use was associated with delayed gastric emptying in patients with diabetes for <10 years. Moreover, a significant proportion (24%) of patients with diabetes with delayed gastric emptying were on a GLP-1R agonist. Recently, semaglutide (GLP-1R agonist) gained Food and Drug Administration approval as a weight loss medication in both patients with and without diabetes. This should prompt further research to evaluate the safety profile of these medications in patients with and without pre-existing gastroparesis.
Horizon problem for Bianchi type-V universe model
Authors: Çi̇l B. , Çevi̇k I. , Yildiz G.D. Açan , Kara E. , Güdekli̇ E.
Published: October 2022

In this study, we examined the horizon problem in the Bianchi type-V cosmological model. Our investigation showed that we could not obtain the solution to the horizon problem without neglecting the strong energy condition. As a result, we have shown no horizon problem in our model with figures and calculations.
Does United Kingdom parliamentary attention follow social media posts?
Authors: Bollenbacher John , Loynes Niklas , Bryden John
Published: October 2022

News and social media play an important role in public political discourse. It is not clear what quantifiable relationships public discussions of politics have with official discourse within legislative bodies. In this study we present an analysis of how language used by Members of Parliament (MPs) in the United Kingdom (UK) changes after social media posts and online reactions to those posts. We consider three domains: news articles posted on Facebook in the UK, speeches in the questions-debates in the UK House of Commons, and Tweets by UK MPs. Our method works by quantifying how the words used in one domain become more common in another domain after an event such as a social media post. Our results show that words used in one domain later appear more commonly in other domains. For instance after each article on Facebook, we estimate that on average 4 in 100,000 words in Commons speeches had changed, becoming more similar to the language in the article. We also find that the extent of this language change positively correlates with the number of comments and emotional interactions on Facebook. The observed language change differs between political parties; in particular, changes in word use by Labour MPs are more strongly related to social media content than that of Conservative MPs. We argue that the magnitude of this word flow is quite substantial given the large volume of news articles shared on Facebook. Our method and results quantify how parliamentary attention follows public interest as expressed on Facebook and also indicate how this effect may be stronger for posts which evoke reactions on Facebook associated with laughter or anger.
On a theorem of Friedl and Vidussi
Authors: Morifuji Takayuki , Suzuki Masaaki
Published: October 2022

A theorem of Friedl and Vidussi says that any 3-manifold [Formula: see text] and any non-fibered class in [Formula: see text] there exists a representation such that the corresponding twisted Alexander polynomial is zero. However, it seems that no concrete example of such a representation is known so far. In this paper, we provide several explicit examples of non-fibered knots and their representations with zero twisted Alexander polynomial.
Recent advances in charm mixing and CP violation at LHCb
Authors: Pajero Tommaso
Published: October 2022

After playing a pivotal role in the birth of the Standard Model in the 70s, the study of charm physics has undergone a revival during the last decade, triggered by a wealth of precision measurements from the charm and B factories, and from the CDF and especially the LHCb experiments. In this paper, we sum up how the unique phenomenology of charmed hadrons can be used to test the Standard Model and we review the latest measurements performed in this field by the LHCb experiment. These include the historic first observations of CP violation and of a nonzero mass difference between the charmed neutral-meson mass eigenstates, the most precise determination of their decay-width difference to date, and a search for time-dependent CP violation reaching the unprecedented precision of [Formula: see text]. These results challenge our comprehension of nonperturbative strong interactions, and their interpretation calls for further studies on both the theoretical and experimental sides. The upcoming upgrades of the LHCb experiment will play a leading role in this quest.
Rheology of tangent-hyperbolic (T-H) nanoliquid configured by stretchable stratified surface considering transpiration effects
Authors: Nasir Muhammad , Waqas Muhammad , Zamri Nurnadiah , Jameel Mohammed , Guedri Kamel , Galal Ahmed M.
Published: October 2022

This research reports the thermo-solutal mixed convective non-Newtonian (tangent-hyperbolic) fluid flow from a stretchable surface under the effect of viscous dissipation. Impermeable surface with stratifications (thermal and solutal) creates the flow. The Buongiorno nanoliquid model capturing Brownian diffusion and thermophoresis is opted for analysis. Energy expression modeling is based on heat source/sink and thermal radiation. Consideration of chemical reaction accounts for species concentration. Via relevant transformations, the flow model of nonlinear governing partial differential conservation equations and free-stream boundary conditions are extracted into coupled nonlinear ordinary differential equations which are solved analytically using homotopy technique. Comparative results ensuring the soundness of the employed technique are included. Analytical results are presented graphically for the influence of pertinent parameters on velocity, temperature, skin-friction coefficient, local Nusselt and Sherwood numbers. The obtained outcomes witness that the concentration of nanoparticles is increased with stronger values of thermophoresis and concentration Biot number while it declines with increasing values of solutal stratification variable, Brownian motion and Schmidt number.
A Multi-Input File Data Symmetry Placement Method Considering Job Execution Frequency for MapReduce Join Operation
Authors: Wu Jia-Xuan , Zhang Yu-Zhu , Jiang Yue-Qiu , Zhang Xin
Published: October 2022

In recent years, data-parallel computing frameworks such as Hadoop have become increasingly popular among scientists. Data-grouping-aware multiple input file data placement for Hadoop is becoming increasingly popular. However, we note that many data-grouping-aware data placement schemes for multiple input files do not take MapReduce job execution frequency into account. Through the study, such data placement schemes will increase the data transmission between nodes. The starting point of this paper is that if a certain type of MapReduce job has been executed more frequently recently, then it can be assumed that this type of job will also have a higher chance of being executed later. Based on this assumption, we proposed a data-grouping-aware multiple input files data symmetry placement method based on MapReduce jobs execution frequency (DGAMF). Based on the history of MapReduce job executions, this method first creates an inter-block join access correlation model, then divides the correlated blocks into groups according to this model and gives a mathematical model for data placement. The model can be used to guide the placement of data blocks centrally to solve the node load balancing issue caused by data asymmetry. Using the proposed method, correlated blocks from the same groups were placed in the same set of nodes, thereby effectively reducing the amount of data transmitted between nodes. Our data placement method was validated by setting up an experimental Hadoop environment. Experimental results showed that the proposed method effectively processed massive datasets and improved MapReduce’s efficiency significantly.
Learning Student Intents and Named Entities in the Education Domain
Authors: Tran Oanh Thi , Nguyen Thang Van , Nguyen Tu Anh , Bach Ngo Xuan
Published: October 2022

Detecting intents and extracting necessary contextual information (aka named entities) in input utterances are two fundamental tasks in understanding what the users say in chatbot systems. While most work in this field has been dedicated to high-resource languages in popular domains like business and home automation, little research has been done for low-resource languages, especially in a less popular domain like education. To narrow this gap, this paper presents the first study on learning to detect student intents and to recognize named entities in the education domain targeted to the Vietnamese language. Specifically, we first introduce a complete corpus consisting of 3690 utterances of students. It was manually annotated with both named entities and intent information at two levels of granularity: the fine-grained and the coarse-grained levels. We then systematically investigate different approaches to deal with the two tasks using not only independent but also joint learning architectures. The experimental results show that the joint architectures based on pre-trained language models are superior in boosting the performance of both tasks. They outperformed the conventional independent learning architectures which looked at the two tasks separately. Moreover, to further enhance the final performance, this paper proposes a technique to enrich the models with more useful linguistic features. Compared to the standard approaches, we achieve considerably better results for two tasks in both architectures. Overall, for the named entity recognition task, the best model yielded an F1 score of 88.61%. For the intent detection task, it yielded F1 scores of 94.36% and 91.62% at the coarse-grained and fine-grained levels, respectively.
Top-k Learned Clauses for Modern SAT Solvers
Authors: Lonlac Jerry , Nguifo Engelbert Mephu
Published: October 2022

Clause Learning is one of the most important components of a conflict driven clause learning (CDCL) SAT solver that is effective on industrial SAT instances. Since the number of learned clauses is proved to be exponential in the worst case, it is necessary to identify the most relevant clauses to maintain and delete the irrelevant ones. As reported in the literature, several learned clauses deletion strategies have been proposed. However the diversity in both the number of clauses to be removed at each step of reduction and the results obtained with each strategy increase the difficulty to determine which criterion is better. Thus, the problem to select which learned clauses are to be removed during the search step remains very challenging. In this paper, we propose a novel approach to identify the most relevant learned clauses without favoring or excluding any of the proposed measures, but by adopting the notion of dominance relationship among those measures. Our approach bypasses the problem of difference in the results obtained with different measures and reaches a compromise between the measures assessments. Furthermore, the proposed approach also reduces the non-trivial problem of choosing the number of clauses to delete at each reduction of the learned clause database.
Prediction of Incident Solar Radiation Using a Hybrid Kernel Based Extreme Learning Machine
Authors: Preeti  , Bala Rajni , Singh Ram Pal
Published: October 2022

Forecasting solar radiation for a given region is an emerging field of study. It will help to identify the places for installing large-scale photovoltaic-systems, designing energy-efficient buildings and energy estimation. The different machine learning kernel-based approaches for prediction problems uses either a local or global kernel. These models can provide either strong training capability or good generalization performance. In this paper, a new hybrid kernel is proposed using the combination of a local and global kernel. A novel algorithm Hybrid Kernel-based Extreme Learning Machine is proposed for predictive modelling of Incident Solar Radiation (ISR) time series using new hybrid kernel. The proposed algorithm uses the surface, atmospheric, cloud properties obtained from the MODIS instrument and observed ISR at time t – 1 to predict ISR at time t. This study is conducted for 41 diverse sites of Australia for the period of 2012–2015. Further, the proposed model is experimented with other time series datasets to prove its efficacy. It is shown that the proposed methodology outperforms five other benchmarking methods in terms of MAE and Willmott’s Index (WI). Therefore, the suggested approach can be used for modelling solar energy at a national scale using remotely-sensed satellite footprints.
S, N Co-Doped Graphene Quantum Dots for Novel Quantum Dots Solar Cell
Authors: Majumder Tanmoy , Mondal Suvra Prakash
Published: October 2022

Graphene quantum dots (GQDs) have been extensively studied in recent days due to their excellent optical photo-absorption, low-cost synthesis and nontoxic nature. Furthermore, the optical and electronic properties of GQDs can be modulated by adding various dopant (like N, S, B, F, K, Si etc.) and can be used as a potential candidate for green solar energy material. Here, we have synthesized GQDs, N and N, S co-doped GQDs using low-cost hydrothermal process. Quantum dot sensitized solar cells (QDSSCs) were fabricated by sensitizing doped and undoped GQDs with ZnO nanorods. Current-Voltage characteristics of GQD sensitized ZnO NRs, N-GQD sensitized ZnO NRs and S, N-GQD sensitized ZnO NRs have been studied. The superior photovoltaic performance was obtained using S, N co-doped GQDs sensitized ZnO NRs with conversion efficiency [Formula: see text]%, which was 1.75 times higher than undoped GQD sensitized QDSSC device.
Analysis of new barrow agegraphic dark energy with different diagnostic tools
Authors: Kumar Mukesh , Sharma Umesh Kumar , Dubey Vipin Chandra
Published: October 2022

In this paper, we investigate the recently proposed New Barrow Agegraphic Dark Energy (NBADE) model by taking the distinct values of Barrow parameter [Formula: see text] in the context of Friedmann–Robertson–Walker (FRW) Universe. We have used different diagnostic tools to discriminate NBADE model from [Formula: see text]CDM model, namely statefinder pair [Formula: see text], [Formula: see text], [Formula: see text] pair, jerk parameter and [Formula: see text] diagnostic planes. The trajectories for the evolution of statefinder parameters [Formula: see text], [Formula: see text], [Formula: see text] pair, jerk parameter and [Formula: see text] diagnostic are plotted of NBADE model using distinct values of the Barrow parameter [Formula: see text] at initially [Formula: see text] and [Formula: see text].
Perturbations in the interacting vacuum
Authors: Munyeshyaka Albert , Ntahompagaze Joseph , Mutabazi Tom , Mbonye Manasse R. , Ayirwanda Abraham , Twagirayezu Fidele , Abebe Amare
Published: October 2022

In this study, we present the evolution of cosmological perturbations in a universe consisting of standard matter and interacting vacuum. We use the 1 + 3 covariant formalism in perturbation framework and consider two different models for the interacting vacuum; namely, a linear interacting model and interaction with creation pressure model. For both models, we derive the evolution equations governing the growth of linear perturbations for both radiation- and dust-dominated universe. We find numerical solutions in appropriate limits, namely long and short wavelengths. For both models, the perturbations grow with time (decay with redshift), showing that structure formation is possible in an accelerated cosmic background. The perturbation amplitudes — and their relative scalings with those of [Formula: see text]CDM — depend on the values of the interaction parameters considered, and in a way that can be used to constrain the models using existing and future large-scale structure data. In the vanishing limits of the coupling parameters of the interaction, we show that standard [Formula: see text]CDM cosmology, both background and perturbed, is recovered.
Construction of Shikonin-Loaded Mammaglobin-Modified Liposomes for Breast Cancer Targeted Therapy
Authors: Zhang Qianqian , Zhang Mingjie , Wang Wenhui
Published: October 2022

Objective: In this study, we investigated the antitumor advantages of human mammaglobin (MGB) antibody-modified shikonin (SK)-loaded liposomes (MGB-SK-LPs) in the treatment of breast cancer. Methods: MGB-SK-LPs were prepared via the solvent evaporation method, and their encapsulation rate, drug-loading capacity and in vitro release performance were determined after characterization and analysis. Fluorescein isothiocyanate (FITC) was used as a probe to investigate the cell uptake behavior. The MTT method was used to investigate the cytotoxicity and proliferation behavior, whereas flow cytometry was used to detect the effect of MGB-SK-LPs on tumor cell apoptosis. The antitumor activity of the xenograft tumor model in nude mice was also evaluated. Results: MGB-SK-LPs had a particle size of [Formula: see text] nm and a zeta potential of [Formula: see text][Formula: see text]mV. The encapsulation rate of SK and the drug-loading capacity of MGB-liposomes to SK were [Formula: see text] and [Formula: see text], respectively. The MGB-SK-LPs had a sustained-release function with spherical morphology. MGB-SK-LPs, which had low cytotoxicity, can be ingested by breast cancer cells and inhibit proliferation and promote apoptosis. In vivo antitumor activity of SK was significantly enhanced by liposome encapsulation and MGB-targeted modification. Conclusions: MGB-SK-LPs prepared in this study can specifically target breast cancer cells, effectively concentrate drugs on the surface of the tumor cells, and release them slowly. Moreover, they can significantly enhance the antitumor therapeutic effect of SK in vivo, providing a promising solution for targeted treatment of breast cancer.
Influence of Acid on Ring-Opening, Fluorescence, Aggregation, Electrochemical Oxidation, and C–C Bond Coupling of Spiropyran Derivatives
Authors: Kathuria Ishana , Rani Sweety , Srivastava Rajiv K. , Kumar Arvind , Kumar Satish
Published: October 2022

Two benzothiazolinic spiropyran derivatives differently substituted at phenolic segment were synthesized to study the effect of acid on their ring-opening and electrochemical oxidation properties. Upon protonation, conventional spiropyrans undergo Cspiro–O bond breakage, resulting in the formation of their ring-open protonatedcisoidmerocyanine form, which rearranges itself to its stabletransoidmerocyanine. Benzothiazolinic spiropyrans have also displayed pH-controlled photochromism, with the spiro moiety being opened by trifluoroacetic acid and reverted to spiro form on neutralization with triethylamine. It was demonstrated that the increase in the concentration of trifluoroacetic acid (TFA) influences the rate of ring-opening permitting its identification by1H NMR, 2D NMR, UV Visible spectroscopy, and single-crystal X-ray crystallography. The aggregation-induced emission characteristics of benzothiazolinic spiropyrans were also explored using fluorescence and DLS measurements. Moreover, the thia-indoline segment of spiropyran undergoes electrochemical oxidation followed by C–C coupling due to the presence of electron-rich nitrogen and sulfur atoms. The influence of acid on electrochemical oxidation and substituent was also investigated. Further, the density functional theory (DFT) based studies were performed to study the electrochemical oxidation and acidochromism in benzothiazolinic spiropyrans. Time-dependent DFT estimated variables also provided additional information regarding the acidochromism process.
Vitamin E treatment in insulin-deficient diabetic rats reduces cardiac arrhythmias and mortality during severe hypoglycemia
Authors: Reno-Bernstein Candace M. , Oxspring Milan , Bayles Justin , Huang Emily Yiqing , Holiday Ivana , Fisher Simon J.
Published: October 2022

For people with type 1 diabetes, severe hypoglycemia can be fatal. We show in our animal model that insulin-deficient diabetic rats have fatal cardiac arrhythmias during severe hypoglycemia that are associated with increased cardiac oxidative stress. Importantly, treatment with vitamin E, to reduce oxidative stress, decreased fatal cardiac arrhythmias during severe hypoglycemia.
Pupil diameter tracked during motor adaptation in humans
Authors: Yokoi Atsushi , Weiler Jeffrey
Published: October 2022

Pupil diameter is known as a noninvasive window into individuals' internal states. Despite the growing use of pupillometry in cognitive learning studies, it receives little attention in motor learning studies. Here, we characterized the pupil responses in a short-term reach adaptation paradigm by measuring pupil diameter of human participants while they adapted to abrupt, gradual, or switching force field conditions. Our results demonstrate how surprise and uncertainty reflected in pupil diameter develop during motor adaptation.
Knockdown of Long Noncoding RNA LINC00240 Inhibits Esophageal Cancer Progression by Regulating miR‐26a‐5p
Authors: Liu Yupeng , Li Tao , Peng Chunlei , Mao Qinghua , Shen Biao , Shi Minxin , Lu Haimin , Xiao Ting , Yang Aimin , Cheng Chun
Published: October 2022

Background. Esophageal cancer is the most prevalent digestive system tumor. Due to a lack of characteristic symptoms and early diagnosis, a confirmed esophageal cancer is typically detected at a progressively harmful stage. Therefore, it is critical to investigate the molecular mechanisms governing the formation and progression of esophageal cancer in order to identify new treatment targets for esophageal cancer early detection. Methods. We first screened the differentially expressed gene LINC00240 in the TCGA database. Multivariate analysis and Cox regression were performed, and a nomogram was constructed for internal validation. The correlation between LINC00240 and immune cells was analyzed using the TIMER database. The possible mechanism of action was explored through GSEA enrichment analysis. Then, in 43 esophageal cancer tissues, paracancour tissues, and cell lines, the LINC00240 expression was found. Transwell assays, CCK‐8, and clone formation assays were utilized to assess the impact of LINC00240 on the metastasis of esophageal cancer cells. The binding activity of LINC00240 to downstream miRNAs was assessed using the luciferase reporter gene. Results. TCGA database showed that LINC00240 expression was increased in cancer tissues compared to adjacent tissues. The C‐index of the nomogram is 0.712 (0.666–0.758), and the prediction model has good accuracy. According to the TIMER database, the LINC00240 expression is linked to immune infiltration and may be crucial in encouraging the immune escape of tumor cells. Gene enrichment analysis depicts that LINC00240 could influence the biological events of esophageal cancer by taking part in pathways such as affecting the cell cycle. LINC00240 expression was substantially greater in the plasma of esophageal cancer patients (3.94 ± 1.55) than in the normal control group (2.13 ± 0.89). Plasma expression of LINC00240 was linked to the degree of differentiation (P = 0.0345) and TNM stage (P = 0.0409). Knocked down LINC00240 inhibited esophageal cancer cells proliferation, lone formation, and invasion. LINC00240 might bind itself to miR‐26a‐5p and influence its expression. MiR‐26a‐5p inhibitor can dramatically limit the ability of LINC00240 knockdown on plate colony formation and relocation of esophageal cancerous cells was demonstrated in colony formation and migration experiments. Conclusion. LINC00240 expression is elevated in esophageal cancerous tissues, and knocking down LINC00240 decreases esophageal cancer cell proliferation, clone formation, invasion, and migration via miR‐26a‐5p. As a result, LINC00240 could be a novel target for esophageal cancer patients' early diagnosis and treatment.
Forming‐Free Pt/Ti/AlOx/CeOx/Pt Multilayer Memristors with Multistate and Synaptic Characteristics
Authors: Wang Wenqing , Zhao Hongbin , Zhang Baolin , Tu Hailing
Published: October 2022

Due to their unique electrical performance and simple structure, memristors exhibit excellent application prospects for future information technology. In this work, we fabricated Pt/Ti/AlOx/CeOx/Pt memristors demonstrating electroforming‐free bipolar resistive switching behavior with low operating voltage (−1 to 1 V), stable endurance, and retention. Space‐charge limited conduction (SCLC) as well as the formation and rupture of conductive filaments are responsible for the resistive switching behavior. Increasing the magnitude of the RESET voltage could generate multistate resistive switching. We studied the synaptic characteristics of the device by obtaining multilevel conductance states and investigating the relationship between the device resistance, pulse amplitude, pulse width, and pulse number. By applying programmed pre and postsynaptic spiking pulses, spike‐timing dependent plasticity was observed. This study shows that the device is suitable for multivalue storage and can be used as an electronic synapse device in artificial neural networks.
Research on Weld Seam Bead Recognition Based on Convolution Neural Network
Authors: Shi Chao , Sun Hongwei , Liu Chao , Tang Zhaojia
Published: October 2022

In terms of the problems of five categories of nonweld seam stripes, including inclusion, oil-spot, silk-spot, and water-spot, which interfere with weld seam recognition during robotic welding, a convolutional neural network (CNN) algorithm, combined with a multistage training strategy, is used to construct a digital model for weld seam recognition, on the basis of which the classification accuracy is compared with the standard model of seven categories of representative CNN. The results show that the ResNet model with a multistage training strategy classifies weld seams with an accuracy of 83.8%, which is superior to other standard models. In this study, the physical scenario of weld seam recognition is migrated to a neural network digital model, fulfilling the intelligent recognition of weld seams in complex scenarios based on the CNN digital model.
Stock Market Prediction Based on Financial News Text Mining and Investor Sentiment Recognition
Authors: Bi Jianxin
Published: October 2022

The stock market is usually regarded as the bellwether of the economy, which can reflect the economic operation of a country or region. As a significant part of the financial market, the equity market plays a critical role in the financial sector. Whether in academia or investment field, stock market forecasts always excite great interest. Financial news is an important source of information in the financial market, which reflects the mood swings of investors and often goes hand in hand with the market trend. However, due to the unstructured and professional characteristics of financial news, there are challenges in accurately quantifying their emotional tendencies. This research is based on Hidden Markov Model (HMM) to segment financial news text. The recognition and classification of news emotion is carried out by bidirectional long short-term memory (BI-LSTM) algorithm, and long short-term memory(LSTM) model is trained with text emotion index and stock market transaction data to realize the prediction of stock market. The results show that BI-LSTM algorithm performs better than the emotional dictionary algorithm in emotional recognition. And the emotional index of financial news text can enhance the accuracy of stock market prediction to a certain extent. Compared with using stock market technical index and news text vector only, the prediction accuracy can be improved by about 2%.
miR-223-3p Regulates NLRP3 to Inhibit Proliferation and Promote Apoptosis of ONG Cells
Authors: Nie Lili , Zou Hui , Ma Chi , Wang Xiaoke
Published: October 2022

Objective. Optic nerve glioma (ONG) is a rare disease, defined as a WHO grade I tumor, which affects the visual pathway. The objective of this study was to investigate the expression of miR-223-3p in ONG as well as its function and regulation in ONG cell lines. Methods. qRT-PCR assays were used to measure miR-223-3p expression in ONG tissues and cell lines. After overexpression of miR-223-3p in Hs683 and WERI-Rb-1 cell lines, CCK-8 and EdU assays were performed to examine cell proliferation, and flow cytometry was used to assess apoptosis. Dual luciferase assays were utilized to identify the target binding to miR-223-3p and NLRP3. Rescue assays were carried out to investigate the regulatory mechanism of miR-223-3p acting through NLRP3. Nude mouse tumorigenesis assays were established to verify the effect of miR-223-3p on ONG growth. Results. miR-223-3p was weakly expressed in both ONG tissues and cell lines. miR-223-3p inhibited the proliferative ability of Hs683 and WERI-Rb-1 cell lines and promoted apoptosis. In addition, there was binding between miR-223-3p and NLRP3. Simultaneous overexpression of NLRP3 and miR-223-3p partially counteracted the role of miR-223-3p in the cell lines. Lastly, miR-223-3p inhibited ONG growth. Conclusion. miR-223-3p plays an inhibitory role in ONG development by regulating NLRP3 to inhibit the proliferation of ONG cells and promote apoptosis.
Deep Learning-Based ECG Abnormality Identification Prediction and Analysis
Authors: Liang Weiqian
Published: October 2022

In recent years, China’s economy has been developing rapidly, and people’s life and quality of life have been improving; more importantly, people’s habits and living habits have also developed from the previous “unhygienic” and “not very careful” to the current “Healthier, more hygienic, greener and more sophisticated” direction. In the process of this development, due to the rapid development of the economy and the industrialization of cities, the incidence of heart disease is also increasing year by year. According to relevant studies, China’s urbanization process has been unprecedented, the number of urbanized people in China has exploded in recent years, and the ratio of urban to rural population has increased from about 20 percent to about 75 percent today. The effects of the population and the urbanization of urban architecture are affecting people’s physical and mental health, both consciously and unconsciously, causing both positive and negative physical and mental effects on the psychological and physical levels. In this paper, the concept of deep learning is fully utilized to train the CNN neural network model and apply it to the ECG abnormality recognition and prediction examination. In order to fully validate the application and significance of deep learning in ECG abnormality identification and prediction, the whole project was completed through subjective and objective experiments. The experimental results show that, from the subjective aspect, the ECG examination has been accepted by most people for different age groups, and the analysis results of the ECG examination with the deep learning model in this paper are more satisfactory; from the objective aspect, the CNN-ECG abnormality recognition prediction network model trained in this paper has high. The accuracy of the model for ECG abnormality recognition prediction can reach 86% when the learning rate is set to 0.0001 and the batch size is set to 120, and the model can reduce the burden of medical personnel to a certain extent.
Downregulation of Matriptase Inhibits Porphyromonas gingivalis Lipopolysaccharide‐Induced Matrix Metalloproteinase‐1 and Proinflammatory Cytokines by Suppressing the TLR4/NF‐κB Signaling Pathways in Human Gingival Fibroblasts
Authors: Kim Jeong-Mi , Noh Eun-Mi , You Yong-Ouk , Kim Min Seuk , Lee Young-Rae
Published: October 2022

Matriptases are cell surface proteolytic enzymes belonging to the type II transmembrane serine protease family that mediate inflammatory skin disorders and cancer progression. Matriptases may affect the development of periodontitis via protease‐activated receptor‐2 activity. However, the cellular mechanism by which matriptases are involved in periodontitis is unknown. In this study, we examined the antiperiodontitis effects of matriptase on Porphyromonas gingivalis‐derived lipopolysaccharide (PG‐LPS)‐stimulated human gingival fibroblasts (HGFs). Matriptase small interfering RNA‐transfected HGFs were treated with PG‐LPS. The mRNA and protein levels of proinflammatory cytokines and matrix metalloproteinase 1 (MMP‐1) were evaluated using the quantitative real‐time polymerase chain reaction (qRT‐PCR) and an enzyme‐linked immunosorbent assay (ELISA), respectively. Western blot analyses were performed to measure the levels of Toll‐like receptor 4 (TLR4)/interleukin‐1 (IL‐1) receptor‐associated kinase (IRAK)/transforming growth factor β‐activated kinase 1 (TAK1), p65, and p50 in PG‐LPS‐stimulated HGFs. Matriptase downregulation inhibited LPS‐induced proinflammatory cytokine expression, including the expression of IL‐6, IL‐8, tumor necrosis factor‐α (TNF‐α), and IL‐Iβ. Moreover, matriptase downregulation inhibited PG‐LPS‐stimulated MMP‐1 expression. Additionally, we confirmed that the mechanism underlying the effects of matriptase downregulation involves the suppression of PG‐LPS‐induced IRAK1/TAK1 and NF‐κB. These results suggest that downregulation of matriptase PG‐LPS‐induced MMP‐1 and proinflammatory cytokine expression via TLR4‐mediated IRAK1/TAK1 and NF‐κB signaling pathways in HGFs.
[Retracted] The Practical Effect of Action Intervention Strategy Combined Based on Surgical and Psychological Factors
Authors: Tong Haiyan , Xu Jingjuan , Tang Lin
Published: October 2022

This study mainly analyzes the related surgical and psychological factors that cause the change of thirst degree after gastrointestinal surgery, and observes the practical effect of action intervention strategy combined with the two factors on reducing postoperative thirst degree. Based on this, the clinical data of 87 patients who underwent gastrointestinal tumor resection in our hospital from January 2020 to January 2021 is retrospectively analyzed. The degree of thirst is evaluated by the visual analogue scale (VAS) and the subjects are divided into three groups: a mild group (n = 29), a moderate group (n = 35), and a severe group (n = 23), and their psychological and surgical indicators are compared and analyzed. The results show that the thirst degree and light comfort of mouth in the study group are better than those in the control group at 2 h after surgery, and there is no significant difference when compared to 6 h after surgery, but the thirst degree and oral discomfort in the control group at 6 h after surgery are significantly higher than those in the study group at 2 h after surgery. It is suggested that an action research intervention strategy with a high practical effect can effectively reduce postoperative thirst and oral discomfort.
[Retracted] The Understanding of Medical Informatics among Dental and Medical Students
Authors: Allabun Sarah M.
Published: October 2022

Background. Current medical care deeply relies on informatics during all stages of patient care, which is significantly enhanced due to its use. The healthcare professional’s formation in medical informatics results crucial for their everyday practice. However, healthcare study programs not always provide education about the use of this wide variety of systems, and young professionals find that they need to learn about it over the experience. The aim of this study was to assess the understanding of medical and dental students regarding medical informatics and ICTs. Materials and Methods. A questionnaire was produced with 3 sections and a total of 24 questions. Students replied to the survey before and after taking the medical informatics course. Results. A total of 719 students from second year of medical and dental school were recruited for the study between the period of September of 2017‐May 2018, September 2018‐May 2019, September 2019‐May 2020, and September 2020‐May 2021. Medical and dental students showed a good level of understanding regarding medical informatics, as well as a good perception of the relevance of ICT learning for the professional practice. Course attendance increased the percentage of students that felt confident of their knowledge about medical informatics. However, most students felt that little or no medical informatics education was lectured at their schools and that the University should adapt the academic program to include it. After taking the course, the student’s perception on this matter was improved. Conclusion. Medical and dental students find medical informatics learning useful for their future professional practice and feel inclined to use it. However, they feel that Universities need to adapt their programs in order to include medical education courses and trainings; partly because they are not completely aware of the use of ICTs that already are established in their courses.
Critical Review on Plant Micropropagation of Ethiopian Plants Reported So Far: Existing Gaps, Required Standardization, and Future Research Direction
Authors: Birmeta Genet , Safawo Tura , Dida Mulatu Geleta , Bekele Endashaw
Published: October 2022

Plant micropropagation research in Ethiopia requires concerted efforts to meet desired levels of application for sustainable utilization of the country's diverse plant genetic resources. The purpose of the present review is to provide an update on the results of plant micropropagation conducted so far in Ethiopia. It assessed their strengths and identified gaps in order to standardize research methods and indicate future research directions. Two cereals, three oil crops, three spices, five medicinal plants, two high-value crops, six fruit plants, nine root crops, and one endangered multipurpose shrub were reviewed. The assessment of previously published research was carried out in terms of methods used in the selection of ex plants and their disinfestations, culture vessels, and media used with a variety of combinations and concentrations of plant growth regulators, macro- and micronutrient requirements, culture environments, and genetic stability of regenerated plantlets. Further assessments include the utilization of plant growth-promoting microbes and applications of “omics” research in order to establish standardized, efficient, and cost-effective micropropagation techniques. The findings of the assessments are summarized and current advances are highlighted, along with recommendations for future plant micropropagation studies in the country.
[Retracted] Effects of Different Doses of Dex Anesthesia on Inflammatory Factors and Hemodynamics in Patients Undergoing Neurosurgery and Its Relationship with RSS Score
Authors: Lu Qiaoling , Wu Chengwei , Wu Zhenhua , Wang Xinbin , Cheng Hao
Published: October 2022

The effects of different doses of dexmedetomidine (Dex) anesthesia on inflammatory factors and hemodynamics in patients undergoing neurosurgery and its relationship with RSS scores are analyzed. A total of 102 patients who received neurosurgery in our hospital from March 2021 to March 2022 are selected. According to different intraoperative Dex dose, the enrolled patients are randomly divided into low‐, medium‐, and high‐dose groups, 34 patients in each group. In this study, hemodynamic indexes, inflammatory factors, anesthesia effect, and the Ramsay sedation scale (RSS) score are compared in each groups. The experimental results show that in neurosurgery, compared with low‐dose Dex, high‐dose Dex can better maintain patients’ intraoperative hemodynamic parameters and effectively inhibit postoperative inflammatory response, but postoperative awakening time is also relatively prolonged, while medium‐dose Dex can effectively control patients’ awakening time.
[Retracted] Analysis of the Correlation between College Music Education and Public Mental Health Based on Deep Learning
Authors: Huang Jingle
Published: October 2022

With the continuous changes of college music education and public mental health problems, conventional solutions are no longer sufficient. At this time, we adopted a method based on deep learning to study them. The experiments showed that ① deep learning can be well integrated into two. Among them, the rapport rate between them reached 91%, and the sometimes‐unstable state of the system was solved by optimizing the model. Finally, through the evaluation algorithm, the overall score of the model was obtained to fluctuate between 85 and 90. ② According to the data in the figures and tables, it can be concluded that university music education under deep learning has received more attention in my country, and the investment amount has also increased from 2.4 billion to 3.7 billion. The highest music education activities in universities have become 55% of concerts and 41% of musical instrument experience classes, and finally, my country’s public mental health problem has become a country with the lowest level in the world.