bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aspartate aminotransferase/alanine aminotransferase ratio is a predictor of all-cause mortality rate among Japanese community-dwelling individuals
Authors: Kawamoto Ryuichi , Kikuchi Asuka , Ninomiya Daisuke , Kumagi Teru 
Published: June 2022

Abstract
BackgroundAn elevated ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) not only independently affects aging-related health, but also plays a critical role in mortality. However, there are limited predictive data on all-cause mortality, particularly in the context of community-dwelling individuals in Japan. This study examined the association between the AST/ALT ratio and survival prognosis using two follow-up studies based on 19-year and 7-year intervals. MethodsThe study included 1,573 male (63 years old ± 14 years; range, 20–90 years old) and 1,980 female participants (65 years old ± 12 years; range, 19–89 years old). The participants were those involved in a Nomura cohort study conducted in 2002 (first cohort) and 2014 (second cohort) that continued to participate throughout the follow-up periods (follow-up rates were 90.3% and 97.4% for each cohort). A Cox proportional hazards model was adopted to calculate the multivariate-adjusted hazard ratios (HRs) of death from the baseline health check-up to the follow-up periods while controlling for potential confounding factors.ResultsThe follow-up survey revealed that there were 473 male deaths (30.1% of total male participants) and 432 female deaths (21.8% of total female participants). The univariate Cox regression analysis showed that HRs for all-cause mortality were greater for participants in higher AST/ALT ratio quartiles (p < 0.001). The multivariate Cox regression analysis with adjusted variables showed a significant association between those in the fourth AST/ALT ratio quartile (HR: 1.83, 95% confidence interval, 1.46–2.29) and risk of all-cause mortality. This association holds irrespective of gender and age, and was particularly the case for participants with body mass index (BMI) < 25 kg/m2, without a history of cardiovascular disease (CVD) and diabetes, and with elevated gamma-glutamyl transpeptidase. ConclusionsOur results reveal that an elevated AST/ALT ratio is an independent factor that can predict risk of all-cause mortality among community-dwelling individuals.
Factors associated with COVID-19 vaccine hesitancy among healthcare workers in Cameroon and Nigeria: a web-based cross-sectional study
Authors: Aseneh Jerry Brown , Agbor Valirie Ndip , Kadia Benjamin Momo , Okolie Elvis Anyaehiechukwu , Ofomata Chinelo Janefrances , Etombi Christie Linonge , Ekaney Domin Sone M , Fru Yvonne Walburga Joko 
Published: June 2022

Abstract
Introduction: Vaccination against COVID-19 is an effective strategy to curb the burden of COVID-19, but vaccine acceptance and uptake among African healthcare workers (HCWs) remain low. This study investigated the determinants of COVID-19 vaccine hesitancy among HCWs in Cameroon and Nigeria. Methods: We conducted an analytic cross-sectional study from May to June 2021, including consenting HCWs > 18 years identified using snowball sampling. Vaccine hesitancy was defined as indecisiveness or unwillingness to receive the COVID-19 vaccine. Multilevel logistic regression yielded adjusted odds ratios (aOR) for vaccine hesitancy. Results: We included a total of 598 (~60% women) participants. Vaccine hesitancy was estimated at 56.9% and 42.4% in Cameroon and Nigeria. Little or no trust in the approved COVID-19 vaccines (aOR= 2.28, 95% CI=1.24-4.20), lower perception of the importance of the vaccine on their personal health (5.26, 2.38-11.6), greater concerns about vaccine-related adverse effects (3.45, 1.83-6.47), and uncertainty about colleagues’ acceptability of the vaccine (2.98, 1.62-5.48) were associated with higher odds of vaccine hesitancy. In addition, participants with chronic disease (aOR= 0.34, 95% CI=0.12-0.97) and higher levels of concerns about getting COVID-19 (0.40, 0.18-0.87) were less likely to be hesitant to receive the COVID-19 vaccine. Conclusion: COVID-19 vaccine hesitancy among HCWs in this study was high and was determined, broadly, by the perceived risk of COVID-19 and COVID-19 vaccines on personal health, mistrust in COVID-19 vaccines, and uncertainty about colleagues’ vaccine acceptability. Targeted interventions addressing these concerns are warranted to improve COVID-19 uptake among HCWs in these settings.
A Multicenter Prospective Comparative Study Evaluating Cataract Surgery and Endoscopic Cyclophotocoagulation either with or without iStent inject Implantation in Brazilian Patients with Glaucoma
Authors: Lima Francisco E. , Geraissate João C. , Ávila Marcos P. 
Published: June 2022

Abstract
Purpose
Compare 12-month (12M) safety and efficacy of endoscopic cyclophotocoagulation (ECP) + cataract surgery (Group 1) versus ECP + cataract surgery + iStent inject trabecular micro-bypass implantation (Group 2) in Brazilian patients with open-angle glaucoma (OAG).
Methods
This prospective, multicenter, comparative case series included patients with OAG and cataract who were randomized to receive treatment in Group 1 or Group 2. Outcomes included intraocular pressure (IOP); number of glaucoma medications; visual acuity; adverse events; and secondary surgeries.
Results
Preoperatively, Groups 1 and 2 had similar mean IOP (22.1 and 22.0 mmHg, respectively) and medication burden (3.3 and 3.4 medications, respectively). At all follow-up timepoints through 12M, both groups achieved significant IOP and medication reductions versus preoperative (IOP p < 0.001 and meds p < 0.001 for both groups). At 12M, IOP reductions were 24.2% (Group 1) and 43.6% (Group 2) (p < 0.001); medication reductions were 50.2% and 71.5%, respectively. Mean postoperative IOP and medications were higher in Group 1 than Group 2 (IOP p < 0.01 all visits, medication p < 0.01 at 6M and 12M). Adverse events were generally mild and infrequent in both groups.
Conclusion
In this prospective comparative study of ECP + phacoemulsification, either with/without iStent inject implantation, both treatment groups achieved significant and safe reductions in IOP and medications versus preoperative in Brazilian OAG patients. Reductions were significantly greater, and mean postoperative IOP and medications were significantly lower, in the group receiving iStent inject with ECP and phacoemulsification.
CD31 promotes diffuse large B cell lymphoma metastasis by upregulating OPN and mTOR
Authors: He Zhengchang , Shen Shaoxian , Yi Yuyao , Ren Lingli , Chen Yingying , Tao Huan , Wang Fujue , Qin Yao , Zhai Xingyu , Li Xia , Hu Jianyu , Lei Da , Jia Yongqian 
Published: June 2022

Abstract
Background
Diffuse large B cell lymphoma (DLBCL) will progress to recurrence/ refractory because of ongoing metastasis in various organizations (including the brain and testicles) and it is difficult for first-line chemotherapy agents to cross the physical barriers (Such as the blood-brain barrier and blood-testosterone barrier). At present, the mechanism of invasion is unknow and there is no effective drugs to effectively inhibit the metastasis of DLBCL.
Methods
In this study, 40 newly diagnosis DLBCL patients samples were analyzed by real-time PCR. Western-blot, immunofluorescence staining, immunohistochemical staining and RNA sequence were used to identify diferentially expressed genes of different invasive DLBCL cells. Xenograft models were constructed to validate the different invasive DLBCL cells in vivo. Scanning electron microscope were used to detect the effect of overexpression CD31 DLBCL cells on integrity of blood brain barrier.
Results
Osteopontin (OPN) was upregulated in multiple metastases patients compared with single or less metastases patients. Overexpression OPN DLBCL cells didn’t respond to R-CHOP and more easily progress to recurrence/refractory. In vivo experiments, the DLBCL cells aggressiveness positively correlated with OPN. Overexpression OPN DLBCL cells formed more tumor metastases over time in mice and it also shortened mice survival time. Using RNA sequencing and in vitro studies, we showed that OPN was obviously upregulated by Platelet endothelial cell adhesion molecule-1 (CD31) through AKT pathway. CD31 also helped DLBCL foci hide from immune cells by recruiting function suppressed CD31 + memory T cells in xenografts. CD31 inhibited CD31 + memory T cells to synthetic INF-γ, TNF-α and perforin effectively by abnormally activated mTOR pathway. Finally, CD31 disrupted the tight junctions (TJ) between endothelial cells of blood-brain barrier by activating OPN-EGFR-ZO-1/ZO-2 axis, allowing DLBCL cells to metastasize to brain.
Conclusions
Overall, CD31 is a marker for DLBCL metastasis and targeting CD31 may be a valuable strategy to reduced DLBCL cells aggressiveness and prevent patients progress to recurrence/ refractory because of ongoing metastasis.
Upregulation of phosphoglyceric acid mutase (PGAM)-1 is related to lymph node metastasis in gastric cancer
Authors: Wang Helei , Wang Daguang , Liu Zhicheng , Wang Lei , Wang Zitian , Cacalano Nicholas A. , Suo Jian 
Published: June 2022

Abstract
BACKGROUND: Gastric cancer (GC) is the most common malignancy of the digestive system, causing over two hundred thousand deaths annually in China and over 750,000 deaths worldwide. The high invasiveness and metastatic rates are mainly responsible for mortality due to GC. Thus, it is an urgent priority to explore the mechanisms underlying GC metastasis to improve cancer diagnosis develop more effective biological targeting agents. METHODS: High-throughput RNA sequencing, quantitative PCR (q-PCR) and immunohistochemistry were used to compare PGAM1 levels in lymph node metastasis (LNM) tissues and carcinoma in situ (CIS) and noncancerous tissues from GC patients and correlated PGAM1 expression with patient prognosis, disease recurrence and mortality. In two GC cell lines (SGC7901 and BGC823) with sh-RNA-mediated PGAM1 knockdown, we analyzed cell growth in vitro, apoptosis and cell cycle progression by flow cytometry, and cell migration in wound-healing studies and transwell assays. In vivo subcutaneous growth of control and PGAM1 knockdown GC cell lines was measured in immunodeficient mice, and the potential role of PGAM1 in the expression of metastatic proteins and activation of migratory signaling was determined by flow cytometry and phospho-western blot analysis. RESULTS: We found that elevated PGAM1 expression in LNM, but not CIS tissues correlated with increased disease recurrence and death of GC patients. PGAM1 knockdown impaired proliferation, cell cycle progression and migration of GC cell lines. In a murine xenograft model, GC cells with a PGAM1 knockdown displayed decreased growth capacity in vivo relative to control cells. Western blot and flow cytometry analysis showed that PGAM1 knockdown in SGC7901 and BGC823 decreased the expression of metalloproteinases MMP2 and MMP9 as well as the adhesion molecule ICAM-I, and impaired phosphorylation of Src, FAK and Paxillin relative to parental cells. CONCLUSIONS: Our results indicate that PGAM1 is a novel biomarker of metastatic GC and may play an important role in promoting GC lymph node metastasis by driving cell proliferation, activating cytoskeletal reorganization and cell migration through the Src/FAK/Paxillin pathway and promoting digestion of the extracellular matrix by upregulating the expression of MMP2 and MMP9.
Predictive Modelling for High-risk Stage II Colon Cancer Using Auto-artificial Intelligence
Authors: Ishizaki Tetsuo , Mazaki Junichi , Enomoto Masanobu , Udo Ryutaro , Tago Tomoya , Kasahara Kenta , Nagakawa Yuichi 
Published: June 2022

Abstract
Purpose Recently, stratification of high-risk stage II colon cancer (CC) and the need for adjuvant chemotherapy have been the focus of attention. This retrospective study aimed to define high-risk factors for recurrent stage II CC using Prediction One auto-artificial intelligence (AI) software and develop a new predictive model for high-risk stage II CC. Methods The study included 259 consecutive pathological stage II CC patients undergoing curative resection (January 2000–December 2016). Prediction One software with five-fold cross-validation was used to create a predictive model and receiver operating characteristic (ROC) curve. Predictive accuracy of AI was evaluated using the area under the ROC curve (AUC). We also evaluated the importance of variables (IOV) using a method based on permutation feature importance (IOV > 0.01 defined high-risk factors) to evaluate disease-free survival (DFS).Results The median observation period was 6.1 (range = 0.3–15.8) years. Thirty-seven patients had recurrence (14.3%); the AUC of the AI model was 0.775. Preoperative carcinoembryonic antigen > 5.0 ng/mL (IOV = 0.047), venous invasion (IOV = 0.014), and obstruction (IOV = 0.012) were high-risk factors contributing to cancer recurrence. Patients with 2–3 high-risk factors had lower 5-year DFS than those with 0–1 factor (87.4% vs 62.7%, p < 0.001). Conclusion We developed a new predictive model that could predict recurrent high-risk stage II CC with high probability using auto-AI Prediction One software. Patients with ≥ 2 of the aforementioned factors are considered to have high risks for recurrent stage II CC and may benefit from adjuvant chemotherapy.
Arabic Dialect Identification Using Different Machine Learning Methods
Authors: Nahar Khalid M.O. , Al-Hazaimeh Obaida M. , Abu-Ein Ashraf , Al-Betar Mohammed Azmi 
Published: June 2022

Abstract
Arabic Dialect Identification is the process of identifying the speaker’s dialect based on several features in the corresponding acoustic wave. In this research, machine learning models for detecting Arabic dialects from acoustic wave is proposed using ADI17 corpus with a short duration (i.e., less than 5 seconds) which contains 1717 wave files with a total of 2 hours, 2 minutes, and 11 seconds. The Mel-Frequency Cepstrum Coefficients (MFCC) and Triangular Filter Bank Cepstral Coefficients (TFCC) are used for features extraction from the input acoustic signal. The extracted features represent the speaker’s features matrix which is used for automatic recognition based on K-Nearest Neighbor (KNN), Random Forest (RF), Multi-Layer Perceptron (MLP), and Artificial Neural Networks (ANN). The Experimental results are validated using MFCC features with an accuracy of 76% for KNN, 64% for RF, 41% for ANN, and 34% for the MLP model, while the obtained results using TFCC features were 62% for KNN, 60% for RF, 42% for ANN, and 33% for the MLP model.
Bioaccumulation of Pesticides in the Selected Group of Fishes from Chettuva Backwater, Thrissur, Kerala
Authors: K Sreekala L 
Published: June 2022

Abstract
In an agricultural country like India, pesticides are a major aquatic chemical pollutant. The pesticides are a broad class of chemical and biological agents that damage or kill pests. There are mainly three groups of synthetic organic pesticides-organochlorines, organophosphates and carbamates. Fishes are the major vulnerable biotic components as they sequester the effects to higher organisms including man through food chain. In this paper an attempt has been made to study the levels of pesticide residues in order to elucidate the status of these chemical contaminants in fish meant for human consumption. Specimens were collected from Chettuva backwater in Thrissur district, Kerala. Samples were cleaned in tap water, muscle tissues dissected, minced into smaller pieces. Quantitative analysis of OCs, OPs and Carbomates were made with Gas Chromatography. The result revealed that among the OPs, Trizophos was detected maximum and it contributed more than 50% to the total OPs, whereas Phorate showed the least contribution. Among organochlorines pesticides, α-endosulfan and endosulfan sulphate were the most frequently detected pesticides. Percentage composition of endosulfan pesticide was also computed and the result revealed that endosulfan sulphate was detected the maximum. The level of total carbamate residue was also recorded. Among carbamate pesticides, Carbofuran were the most frequently detected pesticide. Percentage composition of carbamate pesticides revealed that the Carbofuran contributed more than 65% to the total Carbofuran pesticides.
Digital mapping of selected soil properties using machine learning and geostatistical techniques in Mashhad plain, northeastern Iran
Authors: Mousavi Amin , Karimi Alireza , Maleki Sedigheh 
Published: June 2022

Abstract
Understanding the spatial variation of soil properties is essential to monitor land capabilities as well as sustainable management of soil resources. The aim of this study was to predict digital soil properties mapping using 23 environmental variables i.e. terrain attributes and remote sensing (RS) indicis through 1500 km2 of Mashhad plain lands. To achieve this purpose, a total of 180 soil samples (0-10 cm) were taken. The random forest (RF) model combined with ordinary kriging (OK), as well as regression kriging (RK) were applied to relate environmental variables and the studied soil properties. The results revealed that RF-OK was the best model with R2 and RMSE for silt (0.89 and 0.10%) followed by calcium carbonate equivalent (0.88 and 3.30%), clay (0.87 and 2.26%), soil organic carbon (0.86 and 0.24%), sand (0.84 and 4.21%), and pH (0.82 and 5.42%). The RS covariates including band 5 (B5), modified soil adjusted vegetation index (MSAVI), difference vegetation index (DVI), band 2 (B2), carbonate rock index (CRI2), gypsum index (GI) and enhanced vegetation index (EVI) and terrain attributes including topographic wetness index (TWI) and elevation (EL), and topographic position index (TPI) were the most important variables in modeling of different soil properties. Finally, RF-OK model with low cost and high accuracy can be applicable to use for predicting different soil properties as well as spatial information acquired from an effort to maps to managing agriculture in areas at different conditions. This method can be applied to other regions of similar characteristics and for similar purposes.
Effect of baseline status on cardiovascular responses post-isometric handgrip exercise.
Authors: Gupta Nidhi , Gupta Kapil , Dave Harsh S , Singh Yogesh , Tak Amit 
Published: June 2022

Abstract
Background
Isometric handgrip (IHG) exercise causes changes in heart rate variability (HRV) and hemodynamic responses with individual differences. We test the hypothesis that baseline measurements affect post-exercise outcomes.
Methods
In this cross-sectional study, 45 males aged 17 to 22 years were enrolled from SMS Medical College, Jaipur (India). Hemodynamic and HRV data were collected at baseline, during, and after 5 minutes of IHG exercise. The absolute and relative responses were compared before, during, and after the exercise using nonparametric tests. The relationship of baseline with outcomes was evaluated using Pearson's correlation.
Results
The study showed a significant increase in the absolute values of hemodynamic parameters and LF/HF ratio during and after 5 minutes of IHG exercise compared to the baseline. However, a significant decrease and increase occurred in all the relative hemodynamic and most HRV parameters respectively after 5 minutes than during the IHG exercise. Hemodynamic parameters showed a significant correlation with baseline during and after 5 minutes of IHG exercise. Similarly, baseline affects all the HRV parameters during IHG exercise, but not after 5 minutes of IHG exercise.
Conclusion
The present study concludes that initial baseline status should be considered while evaluating the post-IHG exercise responses.
Assessment of Knowledge and Skills on Covid-19 among Frontline Nurses in Zanzibar: Baseline Data from Quasi-Experimental Study
Authors: Omar Hamad M. , Kibusi Stephen 
Published: June 2022

Abstract
Background: Covid-19 is one of the most serious pandemic outbreaks in history the world ever experienced. Its emergency and reemergence poses a substantial threat to nurses who often get close contact with patients, their knowledge and skills on managing the suspected and confirmed cases serve the foundation for positive response toward the outbreak; thus this study aimed at assessing the knowledge and skills of Zanzibar nurses on Covid-19Methods: A descriptive cross-section web-based survey was conducted in a set of 139 nurses from Zanzibar to assess their knowledge and skills for the covid-19 pandemic outbreak. Multistage sampling was employed to select the regions, hospitals and final the participants. Computer-generated questionnaires with a total of 50 items were used to collect information on the recruited respondents; data were analyzed using SPSS software. Results: The assessment of knowledge and skills on covid-19 among frontline nurses from Zanzibar indicate that; the overall mean score knowledge of all respondents was (20.7±3.06) ranged from 13-26 while the overall cognitive skills scores were (20.69±3.06) ranged from 8-18. Age, level of education and working experience were found to be a significant predictor for both knowledge and skills on covid-19 at the level of 5% while working at the referral was only significant to skill. Conclusion: The participants were knowledgeable and skilled regarding the topic of interest however this competence wasn’t directly associated with the study domain of covid-19 rather were significantly associated with other domains related to nursing activities such as IPC and general nursing care.