bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of insulin resistance and non-alcoholic fatty liver disease using serum uric acid and related markers in children and adolescents
Authors: Song Kyungchul , Choi Youngha , Yang Hyejin , Jeon Soyoung , Cho Kyoung Won , Kim Seo Jung , Kim Sujin , LEE MYEONGSEOB , Suh Junghwan , Chae Hyun Wook , Kim Ho-Seong 
Published: April 2024

Abstract

Objective To investigate the relationship between serum uric acid (Uacid) and related parameters with insulin resistance (IR) and non-alcoholic fatty liver disease (NAFLD)and their potential as predictors of IR and NAFLD in children and adolescents
Methods The data of 1,648 participants aged 10–18 years was analyzed using nationwide survey. Logistic regression analysis was performed with IR and NAFLD as dependent variables, and odds ratios (ORs) and 95% confidence intervals (CIs) were computed for tertiles 2 and 3 of each parameter in comparison to tertile 1, which served as the reference group. Receiver operating characteristic (ROC) curves were generated to assess predictability of the parameters for IR and NAFLD.
Results Hyperuricemia, IR, and NAFLD were significantly associated each other. All Uacid and related markers showed continuous increase in ORs and 95% CIs across the tertiles for IR and NAFLD (all p < 0.001). In ROC curve, all Uacid and related markers demonstrated significant predictability for IR and NAFLD. Overall, Uacid combined with obesity indices showed higher ORs and AUC compared to Uacid alone. Uacid-body mass index (BMI) standard deviation score presented the largest AUC for IR. For NAFLD, Uacid-BMI and Uacid-waist-to-height ratio showed the largest AUC.
Conclusions Uacid combined with obesity indices are robust markers for prediction of IR and NAFLD in children and adolescents, which was superior to Uacid. Uacid and related markers have potential as simple markers which does not require fasting for screening of IR and NAFLD in children and adolescents
SARS-CoV-2 RNA-dependent RNA Polymerase is Linked to Mitochondrial Dysfunction in Mouse Heart
Authors: Naka Kazuhito , Ooshima Akira , Sakaguchi Takemasa , Sotomaru Yusuke , Koike Kanae , Sakamoto Naoya , Ishikawa Tomo-o , Kim Seong-Jin , Sawa Masaaki 
Published: April 2024

Abstract
Little is known about specific viral factors responsible for the pathogenesis and pathophysiology of long COVID. Here we describe a conditional knock-in (cKI) mouse strain inducibly expressing Nsp12, an essential component of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). Induction of Nsp12 translation was dependent on co-treatment with inhibitors of the integrated stress response in vitro and in vivo. We show that Nsp12 has a biologically significant link to mitochondrial dysfunction in vivo. In vitro, ectopic Nsp12 expression suppressed mitochondrial function in primary lung epithelial cells isolated from Nsp12 cKI mice. This functionality was physiologically relevant because, although ectopic Nsp12 expression in mouse lungs did not induce pneumonia, it did decrease mitochondrial activity in the hearts of Nsp12 cKI mice over the short and long terms. Administration in vivo of an RdRp inhibitor, EIDD-2801, restored mitochondrial function in cardiomyocytes of Nsp12 cKI mice. Our data demonstrate that SARS-CoV-2 RdRp activity in the lungs leads to cardiac mitochondrial dysfunction in vivo, generating a phenotype resembling aspects of long COVID in humans. Therapeutic targeting of SARS-CoV-2 RdRp may thus represent a novel means of preventing or mitigating intense fatigue and/or myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)-like disease caused by mitochondrial dysfunction in long COVID patients.
Comparative analysis of machine learning and time series models for cotton yield prediction in major growing districts of Karnataka
Authors: N THIMMEGOWDA M , H MANJUNATHA M , HUGGI LINGARAJ , V SOUMYA D , R JAYARAMAIAH , S SATISHA G , L NAGESHA 
Published: April 2024

Abstract
Background
Cotton is one of the most important commercial crop after food crops, especially in countries like India, where it’s grown extensively under rainfed condition. Because of its usage in multiple industries, such as textile, medicine and automobile industries, it has greater commercial importance. Cotton cultivation demands intensive management due to its explorative nature. The crop's performance is greatly influenced by prevailing weather dynamics. As climate change awareness grows, assessing how weather changes affect crop performance is essential. Crop models are a prominent tool for this purpose. Similarly, many techniques are vague and crop models are the dominant ones.
Results
Present study on statistical and machine learning models were compared to assess their ability to predict cotton yield across major producing districts based on long term (1990–2023) dataset on yield and weather factors. The results revealed superior performance of machine learning models such as Artificial Neural Networks (ANN) as they are iteratively trained and evaluated for higher accuracy and found that errors were within acceptable limit i.e., ± 10% and the actual and forecasted yields were in excellent agreement at both F1 and F2 stage and statistically evaluated for RMSE, nRMSE and EF, it showed good results having nRMSE value less than 10 per cent and considered as excellent for eight out of ten districts at F1 and seven districts at F2 stage because of ability of machine learning models such as ANNs to consider intricate interactive effects of weather factors. Furthermore, the tested ANN model was used to assess the importance of the dominant weather factor influencing evaluate crop performance in each district. Specifically, the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum temperature had major influence on cotton yield in most of the yield predicted districts. These difference highlighted the differential interactions of weather factors in each district, which in turn affected the crop productivity.
Conclusions
Outcomes of the study aid in understanding the weather-related yield variability and planning crop management practices and in achieving yield sustainability under changing climatic scenarios of rainfed condition in India.
Prevalence and associated factors of malnutrition among patients undergoing surgery at Saint Peter Hospital, Addis Ababa, Ethiopia,2023
Authors: Haile Robel Gemechu , Haile Abel Teklit , Habtewolde Abel Worku , Debebe Zelalem , Getu Gubala , tiruneh bitewlign , mengiste helina 
Published: April 2024

Abstract
Background: Malnutrition is an imbalance between food intake and needs. It is a clinical condition with multifactorial etiology, resulting in several disorders like immune suppression, increased susceptibility to infections, increased drug intolerance, and death.
Objective: To assess the prevalence and associated factors of malnutrition among patients undergoing surgery at Saint Peter Hospital, Addis Ababa, Ethiopia, 2023.
Methods: an institution based cross-sectional study was designed to investigate the prevalence and associated factors of malnutrition among adult patients undergoing surgery
Results: During the preoperative period, the study found that 12.5% of patients were undernourished, while 30% were overnourished. Following surgery, the prevalence of undernutrition decreased to 10%, while overnutrition remained high at 29.2%. Furthermore, a statistically significant difference in hospital length of stay was observed between patients with normal nutritional status and those with undernutrition postoperatively. The mean difference between these groups was 2.65812 (95% CI = -3.07882 to -2.23742), with a p-value of less than .001. Specifically, patients with normal nutritional status had an average stay of less than 2.66 days longer than those with undernutrition.
Assessment of Genetic Diversity of Indigenous Chicken Ecotypes in Selected Areas of Tanzania
Authors: LUCAS RHODA , KASANGA CHRISTOPHER JACOB , MWEGA ELISA DANIEL , ACKREY SISSA GOTIFRED 
Published: April 2024

Abstract
The sustainable usage and conservation of indigenous chickens require a genotypic characterization. This study was conducted in the Bahi and Songea districts of Tanzania. Blood samples of 100 indigenous chickens were collected and genotyped using eighteen microsatellite markers recommended by the International Society for Animal Genetics, Food and Agriculture Organization Advisory Group for Animal Genetics. Data were analyzed using GenAIEXv.6.5 software. Results showed that Bahi had a total of 117 alleles while Songea had 111 alleles. There were 6.5 alleles on average per locus for Bahi and 6.1 for Songea. The locus with the least number of alleles was MCW0078, with just 5 alleles, whereas the MCW0111F locus was highly polymorphic with 20 alleles. The mean number of different alleles (Na) was 7.250 ± 0.544 for Bahi and 7.000 ± 0.742 for Songea, with an overall average of 7.125 ± 0.515. The number of private alleles was 31 and 37 for Bahi and Songea, respectively. Genetic variation among the population was 17%, while within the population it was 83%. Nei’s genetic distance was calculated to be 0.589, and the principal of coordinate analysis (PCoA) revealed two clusters with some intermixes. At p < 0.05, divergence from Hard Weinberg equilibrium was significant in all loci. In conclusion, there was a considerable genetic variation between the two study populations hence, they are very useful in conservation programs of the indigenous chickens.
Rupture of Anterior Communicating Artery Aneurysm Is Associated With Bifurcation Angle, Aneurysm neck width, and Blood flow velocity
Authors: Li Yang , Wang Bangyue , Ge Xinbo , An Xiuhu , Li Hongwen , Jiang Yuhang , Li Tianxing , Zhao Yan , Zhang Nai , Song Yunfei , Zhang Suqin , Zhu Xiaowei , Liu Zhenbo , Hu Fuguang , Yang Xinyu 
Published: April 2024

Abstract

Background and Purpose：
The Anterior Communicating Artery (ACom) is one of the common sites of intracranial aneurysms (IA), and its rupture can severely affect the patient’s life and health. This study pays extensive attention to the morphological and hemodynamic characteristics of the anterior communicating artery aneurysm (ACoA) and further evaluates the causes of ACoA rupture by analyzing these factors.
Methods：
This study included patient data from January 2017 to October 2023 from the Chinese Multi-central Cerebral Aneurysm Database (CMAD), which contained imaging data for 119 cases. The relationship between clinical characteristics, morphological features, hemodynamic features, and the rupture of the ACoA was explored through traditional logistic regression models, personalized analysis of restrictive cubic spline regression (RCS) models for different factors, and correlation analysis.
Results：
In multivariable logistics regression (MLR), a history of ischemic stroke, smoking history, aneurysm neck width, and the angle between the anterior cerebral artery A1 segment and the anterior communicating artery (A1-ACom angle) are protective factors. In contrast, the diameter of the anterior communicating artery (ACom) and blood flow velocity are independent risk factors. Correlation analysis shows that there is a significant positive correlation between WFNs score and Hunt-Hess grading, and there is also a significant positive correlation between aneurysm height and aneurysm neck width, and aneurysm height and minimum wall shear stress (WSSmin). In the single-variable restricted cubic regression, the nonlinear model of aneurysm neck width shows some significance in the total threshold. There is significance between aneurysm neck width and a single covariate and all covariates.
Conclusions：
Factors such as aneurysm neck width, A1-ACom angle, the diameter of the ACom, and blood flow velocity affect the risk of rupture of the ACoA. The aneurysm neck width shows specific nonlinear characteristics in ACoA rupture.
Intraocular scatter introduced by refractive surgery may induce high-order aberrations
Authors: Zhang Zitao , Zhao Junlei , Gong Rui , Liao Meng , Yang Yanrong , Zhang Haobo , Chen Hao , Dai Yun 
Published: April 2024

Abstract
Purpose：To investigate whether intraocular scatter introduced by refractive surgery will induce high-order aberrations (HOAs).
Method：Intraocular scatter and HOAs (measured at a pupil diameter of 5mm) of 130 myopic eyes (67 patients) were analyzed and compared before surgery and at 1 week, 6 and 12 months after surgery, while 40 normal eyes were set as a control group. Autocorrelation analysis of intraocular scatter and HOAs were performed to confirm the variation trend of ocular scatter and HOAs, respectively. The causal relationship (based on eight criteria: temporal order, strength of association, correlation, exclusion of other explanations, reproducibility, evidence from experimental studies, biological plausibility, and specificity) between intraocular scatter changes and HOAs was analyzed.
Result：Intraocular scatter significantly increased during the refractive surgery and then gradually decreased. HOAs decrease slightly during the refractive surgery, and then gradually increased. The results about the causal relationship analysis: (1) There was a significant correlation between the changes of intraocular scatter during refractive surgery and the HOAs at 6 months after refractive surgery (correspond to the temporal order and correlation). (2) The correlations were also found between the changes of intraocular scatter at 6 months after refractive surgery and HOAs at 12 months after refractive surgery (correspond to the reproducibility). (3) The strong correlation within the experimental group did not exist in the control group (correspond to the exclusion of other explanations). (4) The proportion of individuals in the experimental and control groups who match the conclusions drawn from the analysis was calculated and used to calculate relative ratio (RR) of 4.769 (99.0% CI: 1.790~12.706). The z-test (z=4.106, p=0.000) indicates a high strength of causal association, and the proportion of matches in the experimental group is 4.769 times that of the control group. (5) The data collected in this study were based on clinical trials, which meet the requirements for evidence from experimental studies.
Conclusions：Intraocular scatter introduced by refractive surgery would induce HOAs.
Machine learning-based models predict postoperative cardiovascular and neurological complications after pneumonectomy: A 10-year retrospective observational study
Authors: Wang Yaxuan , Xie Shiyang , Liu Jiayun , Wang He , Yu Jiangang , Li Wenya , Guan Aika , Xu Shun , Cui Yong , Tan Wenfei 
Published: April 2024

Abstract

Background
Reducing postoperative cardiovascular and neurological complications (PCNC) in thoracic surgery is key for improving postoperative survival. Therefore, we aimed to investigate the independent predictors of PCNC, develop machine learning models, and construct a predictive nomogram for PCNC in patients undergoing thoracic surgery for lung cancer.
Methods
This study used data from a previous retrospective study of 16,368 lung cancer patients with American Standards Association physical status I-IV who underwent surgery. Postoperative information was collected from electronic medical records; the optimal model was analyzed and filtered using multiple machine learning models (Logistic regression, eXtreme Gradient Boosting, Random Forest, Light Gradient Boosting Machine, and Naïve Bayes). The predictive nomogram was built, and the efficacy, accuracy, discriminatory power, and clinical validity were assessed using receiver operator characteristics, calibration curves, and decision curve analysis.
Results
Multivariate logistic regression analysis showed that age, duration of surgery, intraoperative intercostal nerve block, postoperative patient-controlled analgesia, bronchial blocker, and sufentanil were independent predictors of PCNC. Random forest was identified as the optimal model with an area under the curve of 0.898 in the training set and 0.752 in the validation set, confirming the excellent prediction accuracy of the nomogram. All the net benefits of five machine learning models in the training and validation sets demonstrated excellent clinical applicability, and calibration curves also showed good agreement between the predicted and observed risks.
Conclusion
The combination of machine learning models and nomograms may contribute to the early prediction and reduction of the incidence of PCNC.
Assessment of Aflatoxin Contamination in Roasted Peanut Samples from Gondar City, Ethiopia: Risk Evaluation and Health Implications
Authors: Tibebe Dessie , Kassaw Moges , Mulugeta Marye , Kassa Yezbie , Moges Zerubabel , Yenealem Dereje , Fentie Tarekegn , Amare Agmas , Sheferaw Hailu 
Published: April 2024

Abstract

The study aimed to detect the level of aflatoxin contamination and risk assessment of aflatoxins. A total of eighteen roasted peanut samples were collected and analyses in different area of Gondar City. The aflatoxin was extracted from peanut with (Acetonitrile: Methanol: Water (15: 25: 60) and the analyses were performed using High-Performance Liquid Chromatography detector method. From the result, A good linearity of standard calibration was found for AFB1, AFB2, AFG1 and AFG2 at a range of 0.2–50 ppb. Regression coefficient (R2) values were >0.996. The average recoveries for spiked sample were ranged from 81.83 to 108.16% and Limit of detection and quantification ranged from (0.138 - 0.6 ppb), (0.46 - 2.0 ppb), respectively. The determined aflatoxin contamination levels in roasted peanut samples ranged from 2.6± 0.081-246.42± 0.082, 0.64± 0.012-23.41±0.016, 9.02± 0.008-156.10± 0.041, 1.49± 0.048 -19.25± 0.04 μg/kg for AFB1, AFB2, AFG1, AFG2, respectively. Moreover, the total amount of aflatoxin detected ranged from 14.05μg/Kg to 445.18μg/Kg. All the analyzed samples exceeded tolerance limit of European Union,(recommended maximum limit of 4μg/kg. Hence, US Food and Drug Administration and World Health Organization tolerance limit 20 μg/kg of aflatoxin total. The Estimated Daily Intakes (EDI) of the total aflatoxins in the peanut samples was 0.531, 0.299 and 0.229μg/Kgbw/day for children, adolescents, and adults respectively. For the Margin of Exposure (MOE), values of 753.3, 1337.8 and 1746.7 were recorded respectively. The average potency of the aflatoxins was 0.00825 ng Aflatoxins/kgbw/day and produced a population risk of 4.4 × 10-3, 2.5 × 10-3 and 1.9 × 10-3 respectively. In this study, a probable menace for cancer was projected at 0.0019− 0.0044 cancers per year per 100,000 person’s health among some community in Gondar, Ethiopia that could be harmed by aflatoxins in toxication via consumption of peanuts and products with an estimated daily intake (EDI) of 0.087 ng/kg bw/day of peanuts in a Gondar, Ethiopia population.
The potential causal association between aspirin consumption and the risk of prostate cancer incidence: a Mendelian randomization analysis
Authors: Zhu Wenliang , Lai Xiaomin , Lai Huajian , Qiu Wenfeng , Xiao Chutian , Hu Daoyuan , Yan Dong , Tao Yiran , Wang Dejuan , Qiu Jianguang 
Published: April 2024

Abstract
Background
Currently, the potential link between aspirin use and the development of prostate cancer remains uncertain. The purpose of this study using two-sample Mendelian randomization (MR) was to elucidate the causal effect of aspirin use on prostate cancer (PCa) risk.
Methods
This study included pooled statistics from two Genome-Wide Association Study (GWAS), one for aspirin use (61583 cases and 50427 control) and the other for PCa of European descent (22534 cases and 270176 control). Inverse variance weighting (IVW) was used as the main method, MR-Egger method, weighted median method and weighted model method were used to evaluate the causal relationship between aspirin use and PCa risk. Cochran's Q test was used to check the heterogeneity, and the MR-Egger intercept test was used to analyze the horizontal pleotropy of the results, and a residual analysis was carried out to confirm the robustness and reliability of the results.
Results
Inverse variance weighting was used to infer that aspirin use had a protective effect on reducing the incidence of PCa (OR = 0.986, 95% CI = 0.978–0.994, P = 0.001). Sensitivity analysis showed that pleiotropy and heterogeneity were not observed. Furthermore, the remain-one analysis showed that the survey results were not significantly affected by any instrumental variable.
Conclusion
There is a causal relationship between aspirin use and the development of PCa, that is, aspirin use reduces the risk of PCa.
An Adaptive Exponentially Weighted Moving Average Based Support Vector Data Description Machine for Multivariate Process
Authors: Ahsan Muhammad , Mashuri Muhammad , Jaya Andi Indra , Rifki Kevin Agung Fernanda , Prasetya Ichwanul Kahfi , Lee Muhammad Hisyam 
Published: April 2024

Abstract

In recent years, modern manufacturing systems have become increasingly complex and generate a wide variety of data. This poses challenges for finding patterns and effective monitoring processes. One-class classification (OCC) is a machine learning technique suitable for finding data patterns. OCC algorithms learn a model of normal process behavior and flag deviations. This helps to detect outliers and process shifts. Support Vector Data Description (SVDD), an OCC type, was used to monitor high-dimensional data. It constructs a hypersphere around normal data and flag outliers. However, SVDD is sensitive to volatile process shifts. Adaptive Exponentially Weighted Moving Average (AEWMA) control charts address this issue. They dynamically adjust the control limits based on the process-mean changes. This study proposes a new AEWMA-based SVDD control chart (D'AEWMA) for monitoring multivariate processes. The D'AEWMA chart outperformed the traditional D'EWMA chart in detecting out-of-control signals and minimizing false alarms.
Elemental detection and mapping of rat bone matrix induced by chemoradiotherapy with confocal μ-XRF
Authors: Li Qiuxia , Chen Hongchi , Zhou Lazhen , Li Fangzuo 
Published: April 2024

Abstract
Breast cancer is among the most prevalent malignant tumors in women. The administration of chemotherapy and radiotherapy for breast cancer treatment can lead to amenorrhea and substantial bone loss in women. Consequently, postmenopausal women are susceptible to the morbidity and mortality risks associated with breast cancer and postmenopausal osteoporosis. In this study, we investigated the impact of chemotherapy and radiotherapy on osteoporosis in female rats using confocal microbeam X-ray fluorescence (µ-XRF) method. The female Sprague Dawley (SD) rats were categorized into three groups: the control group (G1), the chemotherapy and radiotherapy group (G2), and the radiotherapy-only group (G3). The SD rats were euthanized six weeks post chemotherapy and radiotherapy, and femur slices with a thickness of 1mm were obtained for confocal µ-XRF analysis. The results demonstrate a significant loss of calcium in the G2 and G3 groups, while the G2 group exhibited a substantial increase in Fe content compared to the G1 group. The conclusion can be drawn that the occurrence of osteoporosis is related to chemotherapy and radiotherapy, while the significant elevation in bone iron content signifies the progression of osteoporosis.