bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of Number of Observation Wells in an Aquifer by Applying the Variation Coefficients of groundwater level and Variogram Analysis, Case Study: Sarfirouzabad Aquifer/ Iran
Authors: Gooya Hossein Rashidi , Katibeh Homayoon , Maleki Amjad 
Published: May 2022

Abstract
Groundwater monitoring of an aquifer performed by an observation well network plays an important role in the management of groundwater resources in which, if the number of wells is small, the calculation of groundwater level is less accurate, and if the number of observation wells is high, the cost of drilling and maintenance of wells and the cost of measurement will increase. This study aimed to identify observation wells' number and optimal density in an aquifer using classical statistics and geostatistical techniques. The Sarfiroozabad aquifer with 45 observation wells was selected as a case study, in which the effective range of each observation well was determined through examination of the coefficients of water table variations in parallel profiles perpendicular to the longitudinal axis of the aquifer and examining geostatistical items including variograms related to water table variations by specifying the optimal number of observation wells. Classical statistics and geostatistics showed the same effective range for wells in the northern aquifer. According to the observations, to obtain the optimal number and density of observation wells, at least 6 observation wells shall be added to the northern aquifer, while only one well should be added to the southernmost part of the southern aquifer and six wells should be eliminated that reduces the cost of sampling. Also, by adding essential wells, the accuracy of groundwater estimation increases which helps better manage groundwater resources.
Incidence and Risk Factors of Postoperative Medial Shoulder Imbalance in Lenke Type 2 Adolescent Idiopathic Scoliosis with Lateral Shoulder Balance
Authors: Deng Zhipeng , Wang Liang , Wang Linnan , Yang Xi , Wang Lei , Liu Limin , Song Yueming 
Published: May 2022

Abstract
Background
In clinical practice, there are a significant percentage of Lenke 2 AIS patients suffered from medial shoulder imbalance (MSI) despite achieving good lateral shoulder balance (LSB) following surgery. However, there are few studies evaluating the features of the medial shoulder. The objective of this study was to determine the incidence and independent risk factors for MSI with LSB after Lenke 2 AIS corrective surgery.
Methods
One hundred and twenty Lenke 2 AIS patients with LSB at the last follow-up were reviewed from 2009 to 2018. Preoperative, and 3-month and the last postoperative follow-up radiographs were measured using a number of specific measurements. At the last follow-up, patients were divided into medial shoulder balance (MSB) group and the MSI group according to whether the T1 tilt was greater than 3°.
Results
Up to 69.2% of patients suffered from MSI with LSB after Lenke Type 2 AIS corrective surgery. A stepwise multiple linear regression analysis showed that postoperative upper instrumented vertebra tilt (UIVt), proximal thoracic curve (PTC), the ratio of PTC and main thoracic curves (PTC/MTC) and T2 vertebra rotation ratio (T2-VR) were significant predictors for MSI (UIVt: b = 0.398, p < 0.001; PTC/MTC: b = 2.085, p < 0.001; PTC: b = 0.155, p < 0.001; T2-VR: b = 3.536, p = 0.008; adjusted R2 = 0.711). Only 72 patients completed the SRS-30 questionnaire survey, and the MSB group were scored the higher in in overall SRS-30 scores.
Conclusion
Although the patients with Lenke 2 AIS achieve LSB after corrective surgery, up to 69.2% of them suffered from MSI. Postoperative UIVt, PTC, PTC/MTC and T2-VR were significant predictors for MSI. Sufficient correction of these variables may facilitate the achievement of MSB.
Gastrointestinal Symptoms Are Associated with Increased Risk of Progression from Non- severe to Severe Illness in COVID-19 Patients
Authors: Zhao Shengbing , Chen Cui , Huang Xinxin , Wang Rundong , He Zixuan , Wu Jiayi , Kong Xiangyu , Zhang Yun , Zhang Yidan , Dong Xuan , Zhou Jixue , Fang Jun , Zheng Namei , Liu Jinhong , Liu Liyuan , Liu Yanping , Wang Shuling , Chang Xin , Pan Peng , Xia Tian , Wang Tongchang , Yang Xia , Li Zhaoshen , Bai Yu 
Published: May 2022

Abstract
BackgroundThe involvement of gastrointestinal (GI) symptoms in the progression of illness in COVID-19 patients has not been illustrated, with the association between GI symptoms and illness severity remaining controversial. The present study aimed to evaluate the association between GI symptoms and the illness progression, severity, and prognosis in COVID-19 patients.MethodsThis study retrospectively recruited consecutive patients with laboratory-confirmed COVID-19 from three hospitals in Wuhan. The severity of illness was classified as non-severe and severe for analyses. The primary outcome was the association between GI symptoms and progression from non-severe to severe illness (PNTS) in COVID-19 patients. ResultsOf the 934 COVID-19 patients (mean age 59.3 years; 43.7% males), the prevalence of overall and specific GI symptoms at/prior to admission were 59.9% and 13.0%, respectively. Patients with GI symptoms were associated with increased risk of fever (56.1% vs. 48.1%; P=0.02), increased IL-6 (18.2% vs. 11.7%; P=0.04), ground-glass opacity (56.8% vs. 43.1%; P<0.001), bilateral pneumonia (80.4% vs. 72.3%; P=0.005), secondary infections (12.6% vs. 6.5%;, P=0.003), and hypoalbuminemia (26.2% vs. 18.4%; P=0.01). Patients with GI symptoms had a higher risk for PNTS (2.9% vs. 0.6%; P=0.02), even after full adjustments (OR, 6.50; (95%CI:1.34-31.6); P=0.02), but comparable risk for severe illness or deaths. GI symptoms and the specific GI symptoms were identified as the independent risk factors for PNTS.Conclusions The occurrence of GI symptoms is proved to be an independent risk factor for PNTS, which might be a predicting indicator in the prevention of illness deterioration at an early stage.
Chopstick technique versus cross technique in LESS hysterectomy (CCLEH study): a prospective randomized controlled trial
Authors: Dou Yuya , Deng Li , Tang Shuai , Yao Yuanyang , Liang Xiaolong , Hu Qunying , Wang Yanzhou 
Published: May 2022

Abstract
Background:The traditional cross technique can be used to complete most Laparoendoscopic single-site surgery (LESS) procedures, but some relatively fine operations, such as vaginal stump suture, are challenging. In practice, we have introduced a novel technique named the chopstick technique and applied it to more complex operations, such as cervical cancer, and found that it contributes to delicate surgery. The efficacy and safety of two different surgical techniques in LESS hysterectomy remain to be validated.Methods:Patients who receive the total hysterectomy are enrolled in this RCT. Stratified randomization will be performed according to uterine size (< 10 weeks, 10-16 weeks, ≥ 16 weeks). The participants will be divided into the chopstick technique group or cross technique group to undergo LESS-TH, then be evaluated the perioperative and postoperative data, including total operation time and other time, transfer rate, estimated blood loss, surgeon fatigue, intraoperative and postoperative complications (within 8 weeks after surgery), health-related quality of life (EQ-5D), postoperative hospital stay, and hospitalization expenses. The primary outcome is the operating time for total hysterectomy under LESS, the other outcomes are secondary. Discussion:It is expected to compare the efficacy of the two techniques in LESS: the chopstick technique vs. the cross technique and accumulate safety data on the new techniques.Trial registration: ChiCTR2000040843, registered on June 16,2020Protocol version:Version 2.0; Date: 2020.05.10
Impact of ICU bed availability on ovarian cancer surgical hospitalization rates during the first wave of the COVID-19 pandemic: an ecological study.
Authors: Moterani Vinicius Cesar , Junior Nino Jose Wilson Moterani , Pimentel Franklin Fernandes , Reis Francisco Jose Candido dos 
Published: May 2022

Abstract
PurposeThe COVID-19 pandemic, which began in 2020, disrupted healthcare services. Reports of changes in surgical activity coincide with the outbreak period. We aimed to identify if any changes could be determined in hospitalization rates of ovarian cancer patients from 2016 to 2020, comparing pre-pandemic and pandemic levels. ResultsHospitalization rates in the state fell, coinciding with the pandemic. Surgical hospitalization rate ratios were inversely correlated with COVID-specific ICU bed occupation rates during the third trimester of 2020, with a Pearson Correlation coefficient of -0.50 (95% CI: -0.78 to -0.05, p = 0.03). Observed ovarian cancer hospitaliation rates were 85% compared to expected values if pre-pandemic trends were mantained.ConclusionA 15% reduction on ovarian cancer hospitalization rates was identified in this scenario. ICU availability was inversely correlated with ovarian cancer surgical activity. These results demonstrate the impact of the COVID-19 pandemic on the treatment of conditions that compete for the same healthcare resources.
Effects of di-(2-ethylhexyl) phthalate on oxidative stress and lipid metabolism in livers of male Xenopus tropicalis
Authors: Pan Xinying , Zheng Li , Ding Yishen , Dai Zhuo , Qi Xufeng , Zhang Xiaochun , Xu Yanbin , Xie Guangyan , Qiao Qingxia 
Published: May 2022

Abstract
Di-(2-ethylhexyl) phthalate (DEHP), used as a popular plasticizer to enhance the flexibility of plastics, is a major pollutant in aquatic environments. DEHP poses severe risks to aquatic organisms since it is an endocrine-disrupting compound. To comprehensively evaluate the toxicity of DEHP on the growth and livers of male Xenopus tropicalis(X. tropicalis), sexually mature male X. tropicalis were exposed to environmentally relevant concentrations of DEHP, 0.2, 0.6, 1.8, 5.4 mg/L, for 49 days. The results showed that DEHP had a severe toxic effect on the livers of male X. tropicalis. Histopathological analysis of livers in all the DEHP-exposed groups showed changes in terms of vacuolization, loose cell cords, and an increasing amount of melanin. Large lipid droplets were markedly formed, and there were changes in the mitochondrial morphology upon DEHP exposure. In addition, oxidative stress (excessive ROS and inhibition of antioxidants) was induced through the suppression of biochemical indicators and the downregulation in the mRNA expression of genes (nrf2, cat, sod, gst, and gpx) related to oxidative stress. A reduction in expression of fatty acid metabolism-related gene (pparα) was seen post-DEHP exposure. Thus, our study suggests that the hepatotoxicity induced by DEHP could be attributed to oxidative stress and disordered fatty acid metabolism. In conclusion, long-term exposure to DEHP at environmentally relevant concentrations poses ecological risks to aquatic organisms, which serves as a reminder that the application of DEHP and other plasticizers should be limited.
Occupational injury and associated factors among building construction workers in Addis Ababa, Ethiopia: A Cross-sectional institution based Study
Authors: Wondimneh Fenta , Jiru Tilahun , Wubetie Andualem 
Published: May 2022

Abstract
Background: The World Health Organization describes the occupational injury as an epidemic problem in the field of public health in underdeveloped countries. Work-related injuries are significantly associated with various factors including lack of safety and health training programs, employing young workers, low literacy workers, smoking, low work experiences, and not using personal protective equipment.Objective: This study aimed to assess the prevalence of occupational injury and its associated factors among building construction workers in Addis Ababa, Ethiopia. Methods: Cross-sectional institution-based study was conducted on selected construction sites in Addis Ababa city, Ethiopia. Data were collected via face-to-face interviews using pretested and structured questionnaires. The collected data were entered using the epi data version 4.2.0 and exported to SPSS version 26 for further analysis and interpretation. Both bivariate and multivariate logistic regression analyses were performed to see the association between the independent and dependent variables. P< 0.05 was considered statistically significant.Results: Of 220 study participants, 88(40%) workers reported occupational injury during the past 12 months, and their main causes of injury were struck by an object 24(27.2%) and falling at ground level 23(26.1%). Factors associated with occupational injuries were temporary employment (AOR = 2.7;95% CI: 1.02,7.1]), work experience(AOR =2.9;95% CI:1.5,5.7) and prolonged working hours(AOR=2.3;95% CI:1.3,4.1).Conclusion: This study finding showed that there is high occupational injury and this is related to lack of training, less work experience, and prolonged working hours per week.
Alanine aminotransferase as marker of cardiometabolic risk in overweight adolescents
Authors: Silva Maria Eduarda Bezerra da , Pimentel Jéssica Bastos , Pinheiro Ana Beatriz Rodrigues , Araújo Eduarda Pontes dos Santos , de Azevedo Paulo Roberto Medeiros , Arrais Ricardo Fernando , de Rezende Adriana Augusto , Maciel Bruna Leal Lima , Lopes Márcia Marília Gomes Dantas , Lima Severina Carla Vieira Cunha 
Published: May 2022

Abstract
Background: Alanine aminotransferase is a marker present in cases of liver damage, such as non-alcoholic fatty liver disease. Objective: To identify the relationship between serum alanine aminotransferase values and cardiovascular risk markers in overweight adolescents. Methods: In this cross-sectional study, were recruited 120 overweight adolescents aged 10-19 years. Height, weight and waist circumference were evaluated and used to calculate the body mass index. Taper index and arterial pressure were measured. Biomarkers lipid and glycemic profiles, triglycerides, high-density lipoprotein, alanine aminotransferase and aspartate aminotransferase values were measured and the triglyceride/high-density lipoprotein ratio was calculated. Statistical analysis was performed using Pearson's correlation coefficient and Fisher's exact test. Results: Boys showed significantly increased values of alanine aminotransferase (p <0.050), aspartate aminotransferase (p <0.010) and taper index (p <0.010), while girls had higher levels of fasting insulin (p <0.010). In boys, alanine aminotransferase was positively correlated with fasting insulin (p <0.050), triglycerides (p <0.050) and systolic blood pressure (p <0.050), whereas in girls, alanine aminotransferase was correlated with waist circumference (p <0.050), taper index (p <0.050), mass index body (p <0.010), fasting insulin levels (p <0.010), homeostatic model assessment of insulin resistance (p <0.010) and high-density lipoprotein (p <0.010). Conclusion: Important correlations were identified between serum alanine aminotransferase values and cardiovascular risk markers in overweight adolescents.
Epigenomic profiling of glucocorticoid responses identifies cis-regulatory disruptions impacting steroid resistance in childhood acute lymphoblastic leukemia
Authors: Bergeron Brennan , Diedrich Jonathan , Zhang Yang , Barnett Kelly , Dong Qian , Ferguson Daniel , Autry Robert , Yang Wenjian , Hansen Baranda , Smith Colton , Crews Kristine , Fan Yiping , Pui Ching-Hon , Pruett-Miller Shondra , Relling Mary , Yang Jun , LI CHUNLIANG , Evans William , Savic Daniel 
Published: May 2022

Abstract
Glucocorticoids (GCs) are a mainstay of contemporary, multi-drug chemotherapy in the treatment of childhood acute lymphoblastic leukemia (ALL), and resistance to GCs remains a major clinical concern. Resistance to GCs is predictive of ALL relapse and poor clinical outcome, and therefore represents a major hurdle limiting further improvements in survival rates. While advances have been made in identifying genes implicated in GC resistance, there remains an insufficient understanding of the impact of cis-regulatory disruptions in resistance. To address this, we mapped the gene regulatory response to GCs in two ALL cells using functional genomics and high-throughput reporter assays and identified thousands of GC-responsive changes to chromatin state, including the formation of over 250 GC-responsive super-enhancers and a depletion of AP-1 bound cis-regulatory elements implicated in cell proliferation and anti-apoptotic processes. By integrating our GC response maps with genetic and epigenetic datasets in primary ALL cells from patients, we further uncovered cis-regulatory disruptions at GC-responsive genes that impact GC resistance in childhood ALL. Overall, these data indicate that GCs initiate pervasive effects on the leukemia epigenome, and that alterations to the GC gene regulatory network contribute to GC resistance.
A semantic segmentation network based on multi-branch structures and multi-scale modules
Authors: Hui Jiangxin , Zhang Hong 
Published: May 2022

Abstract
A novel semantic segmentation model is proposed to improve segmentation accuracy for small and obstructed image targets. This multi-branch structure increased gradient flow paths and prevented vanishing gradients. The architecture was based on a DeepLabv3 + framework and utilized grouped convolutions in each bottleneck of the backbone network (ResNet50), to reduce both the number of model parameters and the model size. The network was also re-parameterized to increase speed during the inference period, which had little effect on the segmentation results. A multi-scale hierarchical attention module (MHAM) was applied in parallel with atrous spatial pyramid pooling (ASPP) in the encoder, to fuse feature information output from the two modules and achieve adaptive segmentation of multi-scale targets. Transfer learning and data augmentation were also used to accelerate convergence and further improve model robustness. The proposed network was evaluated using an aerial semantic segmentation benchmark (AeroScapes), to assess segmentation performance for objects at different scales. The mean intersection over union (mIoU), calculated for the validation set, improved by 43.12% and 47.51% compared with the DeepLabv3+ (Xception65) network and the DeepLabv3+ (ResNet50), respectively. In addition, the proposed network achieved a higher mIoU (84.98%) and a higher mean pixel accuracy (mPA, 97.57%) than six other advanced semantic segmentation networks (U-Net, RefineNet, PSPNet, DADA, DSRL, and HANet), as well as higher mIoUs than comparable algorithms for the CityScapes (84.96%) and ADE20K (52.72%) datasets. It was also found that doubling the number of channels after the grouping convolutions did not significantly change the number of model parameters or the model size. However, the acquired features were more detailed and the images were more complete, indicating the proposed model achieved better segmentation accuracy for small and occluded targets.
Predicting the presence of Left Ventricular Hypertrophy using Este’s Criteria with Support Vector Machine
Authors: Sinha Nidhi , JOSHI AMIT MAHESH 
Published: May 2022

Abstract
Left ventricular hypertrophy (LVH) is the heart condition where the walls of the left ventricle would be thicker than the normal condition. That obstructs the electrical activity of the heart and hence significantly decreases the pumping efficiency. LVH develops as the response to pressure overload that might arise from high blood pressure, stenosis etc. This condition of the heart can be reversed if diagnosed and treated in time. Its symptoms like short breathing, fatigue, palpitation of the heart, dizziness, chest pain after exercise are often misinterpreted or masked by the process of homeostasis, and it develops silently over the years. The prediction of presence of LVH using effective machine learning model would be helpful to have early diagnosis of the disease. This paper focuses on the prediction of Left Ventricular Hypertrophy (LVH) using the SVM machine learning model with the help of an electrocardiogram (ECG). The proposed methodology could be integrated with the IoT framework for smart healthcare solutions. Data is taken from the UCI machine learning repository i.e Cleveland, Hungary, Switzerland, and the VA Long Beach database consisting of 920 subjects. Data is split into 8:2 for training and testing purposes. Python 3.0 is used to analyze the data and the classification is verified by the 10-fold cross-validation technique. In this study, normal subjects and subjects with a high probability of LVH are classified successfully with greater ROC-AUC value than 0.5 which shows the unbiased classification. The results show that the proposed model with enhanced accuracy of 81+% and high specificity of 92.36% stands promising for futuristic smart healthcare applications.
Ensemble-based Gene Selection and an Enhanced Deep Multi-Layer Perceptron-based Classification Model for Classifying Alzheimer's disease
Authors: Mahendran Nivedhitha , PM Durai Raj Vincent 
Published: May 2022

Abstract
Memory and cognitive disabilities have been known to humankind for a long time. However, the pathology and symptoms associated with Alzheimer's Disease (AD) are documented during the current century's first decade. Over the years, AD became the common form of Dementia that has complex pathology and is termed a heterogeneous disorder. The advancements in microarray technology made capturing hundreds and thousands of gene sequences possible. However, the data generated is complex and beyond the understanding of the human brain. AD symptoms are slow but fatal, and the diagnosis is made only through autopsy. Thus, early and accurate diagnosis of the disease is critical. The significant difficulty in handling the gene expression data is the curse of dimensionality or the High Dimensional Low Sample Size (HDLSS) issue. The HDLSS issue demands interdisciplinary research, such as Artificial intelligence, machine learning, etc. This study proposed an ensemble-based feature selection to isolate the necessary genes responsible for causing AD. After selecting the relevant features, the Deep Multi-layer Perceptron (DMLP) is used to classify the AD and non-AD patients. The results are compared with other state-of-the-art feature selection techniques and classification algorithms.