bluuebunny/crossref_metadata_2025_split huggingface dataset:
β-asarone relieves Parkinson’s disease through reducing intracellular Ca2+ in PINK1 mutant Drosophila melanogaster
Authors: Yin Lanxiang , Liu Haoyu , Yang Chengling , Si Nana , Liu Zhihua , Chen Xiangtao 
Published: May 2023

Abstract
β-asarone, an effective volatile oil component of Acorus chinensis, has been found to hold beneficial effects on Parkinson's disease (PD), but its mechanism remains incompletely understood. Ca2+ dys-homeostasis in dopaminergic neurons underlies the pathology of PD, thus this study aims to investigate whether β-asarone protects against PD by modulating Ca2+ level. Drosophila melanogaster with PINK1 (PTEN induced putative kinase 1) mutations, a prototype PD model, was used in this study. We found that calcium chelation in the diet profoundly alleviated a spectrum of PD symptoms in Drosophila. Whereas, calcium supplementation made the case worse, suggesting accumulated calcium contributes to progression of PD. β-asarone administration decreased calcium level in PD flies, accompanied by alleviated behavioral and neural defects. Further study demonstrated that β-asarone downregulated Dmca1D, a gene encodes L-type Ca2+ channel, which was increased in PD flies. Besides, β-asarone decreased expression of Itpr (1,4,5 - trisphosphate receptor, also known as IP3R), which is responsible for calcium release from endoplasmic reticulum (ER). Knockdown of either Dmca1D or Itpr specifically in dopaminergic neurons alleviated behavioral and neural defects effects in PD flies. While, overexpression of Itpr aggravated PD symptoms. The results indicated that increased calcium influx and intracellular release triggered calcium dyshomeostasis in PD flies. And β-asarone protected against PD by restoring calcium homeostasis. Overall, the study demonstrated that β-asarone can serve as a promising nutritional intervention of PD or other calcium dyshomeostasis related biological events.
Associated Risk of Anxiety among CAD patients in PSCC in Qassim, Saudi Arabia
Authors: Alharbi Mansour 
Published: May 2023

Abstract
Context:
The presence of anxiety in individuals with coronary heart disease (CHD) is widespread, and it is related to a higher risk of negative outcomes. There has been a dearth of research on the management of anxiety in people with coronary artery disease.
Aims:
The present study aimed to determine the associated risk of anxiety among coronary artery disease (CAD).
Settings and Design: This was a cross-sectional study conducted on a group of patients with IHD between the ages of 20 and 60 years.
Methods and Material:
A total of 200 individuals participated. Medical records were one of the data sources. The data of patients who meet the selection criteria gathered from the cardiology departments of the PSCC in KFSH.
Statistical analysis used: Statistical package for Social Science (SPSS) version 23 was used for statistical analysis.
Results:
This research comprised 200 patients, the majority of whom were male (81%) and female (19%). According to the findings, 70% of people had minimal depression, 13.5 percent had mild depression, 8.5 percent had moderate depression, 4.5 percent had severe depression, and 3.5 percent had moderately severe depression. Medications were utilized in the majority of cases (98%).
Conclusions:
Anxiety disorders that manifest themselves in the setting of heart disease must be recognized and treated with caution in the early stages of the disease. When giving medical therapy, it is important to examine the effects of the drugs on the heart, as well as the possibility of drug-drug interactions.
Prediction of Treatment Response in Major Depressive Disorder using a Hybrid of Convolutional Recurrent Deep Neural Networks and Effective connectivity based on EEG Signal
Authors: Mirjebreili Seyed Morteza , Shalbaf Reza , Shalbaf Ahmad 
Published: May 2023

Abstract
In this study, we have developed a novel method based on deep learning and brain effective connectivity to classify responders and non-responders to selective serotonin reuptake inhibitors (SSRIs) antidepressants in major depressive disorder (MDD) patients prior to the treatment using EEG signal. The effective connectivity of 30 MDD patients was determined by analyzing their pretreatment EEG signals, which were then concatenated into delta, theta, alpha, and beta bands and transformed into images. Using these images, we then fine tuned a hybrid Convolutional Neural Network (CNN) that is enhanced with bidirectional Long Short-Term Memory (BLSTM) cells based on transfer learning (TL). The Inception-v3, ResNet18, DenseNet121, and EfficientNet-B0 models are implemented as base models. Finally, the models are followed by BiLSTM and dense layers in order to classify responders and non-responders to SSRI treatment. Results showed that the EfficiencyNet-B0 has the highest accuracy of 98.33, followed by DensNet121, ResNet18 and Inception-v3. Therefore, a new method was proposed in this study that uses deep learning models to extract both spatial and temporal features automatically, which will improve classification results. The proposed method provides accurate identification of MDD patients who are responding, thereby reducing the cost of medical facilities and patient care.
The need to implement noise reduction measurements in a neonatal intensive care unit in hospitals in low and middle-income countries – A case study
Authors: Pozo David Emmanuel Del , Donoso Natalia Carolina , Ojeda Galo Antonio , Valle Bryan Gabriel , Gázquez Manuel Jesús 
Published: May 2023

Abstract

Purpose Improving the neonatal intensive care unit (NICU) noise conditions in public hospitals is challenging, especially in low- and middle-income countries. The Isidro Ayora General Hospital in Loja-Ecuador does not fall out of this reality. Therefore, this case study evaluates the noise levels in a NICU of a public hospital and proposes a noise mitigation program based on the obtained results.Methods A descriptive, observational, and quantitative study was carried out to determine the A decibels to which newborns at two NICUs are exposed. An HD2010UC/A Class 1 integrating portable sound level meter was used to detect noise pollution. Data were recorded in 60 seconds intervals during 24 continuous hours for 7 days. The device was placed at the basic (NICU-B) and intensive-intermediate (NICU-IEI) units, considering height and wall proximity.Results In the NICU-B maximum and minimum values were 74.1 and 49.7 dBA; an equivalent daily noise level of 49.3 dBA was recorded. In the NICU-IEI, values were between 71.4 dBA and 47.9 dBA, and the equivalent daily noise level was 53.1 dBA. These results exceed the recommended levels by the World Health Organization (WHO) and the Ecuadorian Ministerial Agreement 097-A, Regulatory Annex 5.Conclusions Other studies evaluating noise levels in other public hospitals in Ecuador or low and middle-income countries are necessary to support these findings. Noise levels in neonatal rooms should be known to implement noise reduction measurements such as incubators with effective acoustic attenuation characteristics, earmuffs to be used on neonates, periodical strict noise controls, etc.
Deep Learning Approaches for Time-resolved Laser Absorptance Prediction in Additive Manufacturing
Authors: Jiang Runbo , Smith John , Yi Yu-Tsen , Sun Tao , Simonds Brian , Rollett Anthony 
Published: May 2023

Abstract
The quantification of absorbed light is essential for understanding laser-material interactions and melt pool dynamics in order to minimize defects in additively manufactured metal components. The geometry of a vapor depression, also known as a keyhole, in melt pools formed during laser melting is closely related to laser energy absorption. This relationship has been observed by the state-of-the-art in situ high speed synchrotron x-ray visualization and integrating sphere radiometry. These two techniques create a temporally resolved dataset consisting of keyhole images and corresponding laser absorptance. In this work, we propose two different approaches to predict laser absorptance. The end-to-end approach uses deep convolutional neural networks to learn features of unprocessed x-ray images automatically without human supervision and predict the laser energy absorptance. The two-stage approach uses a semantic segmentation model to engineer geometric features and predict absorptance using classical regression models. Though with different advantages, both approaches reached a smooth mean absolute error less than 3.4%.
Deep Autoencoder-based Multivariate Outlier Detection for the Classification of Hypertension: Case study COVID-19
Authors: Dashdondov Khongorzul , Kim Mi-Hye , Song Mi-Hwa 
Published: May 2023

Abstract
Background In recent years, the incidence of hypertension has increased dramatically in both the elderly and young populations. The incidence of hypertension also increased with the outbreak of the COVID-19 pandemic. The aims of this study to improve the prediction of hypertension detection using a multivariate outlier removal method based on the deep autoencoder (DAE) method on Korean national health data from the Korea National Health and Nutrition Examination Survey (KNHANES) database. Several studies have identified various risk factors for chronic hypertension. Chronic diseases are often multifactorial rather than single and have been identified to be associated with COVID-19. Therefore, it is necessary to study disease detection by considering complex factors.Methods This study was divided into two modules. The first module, data pre-processing, initially integrated external features for COVID-19 patients merged by region, age, and gender value for KHNANE-2020 year and Kaggle data. Following performed multicollinearity-based feature selection for the KNHANES dataset and integrated dataset. The next module uses the predictive analysis step to detect and predict hypertension based on OrdinalEncoder (OE) normalization and multivariate outlier removal using a deep autoencoder from KNHANES data.Results In this study, we compared the accuracy, F1 score, and area under the ROC curve (AUC) of each classification model. The experimental results showed that the proposed XGBoost model achieved the best results with an accuracy rate of 87.78%, an F1 score of 89.95%, and an AUC of 92.28% for COVID-19 cases, and an accuracy rate of 87.72%, an F1 score of 89.94%, and an AUC of 92.23% for non-COVID-19 cases with the DAE_OE model.Conclusions We successfully improved the prediction performance of the classifiers utilized in all of the experiments by developing a high-quality training dataset implementing DAE and OE in our proposed method. Moreover, we experimentally demonstrate how the steps of our proposed method improve performance. The proposed method can be used not only for hypertension but also for the detection of various diseases such as stroke and cardiovascular disease.
Application of Nutritional Prehabilitation in Elderly Patients undergoing Abdominal Tumor Surgery: a prospective cohort study
Authors: Wang Shu-An , Gu Jingyue , Guo Kedi , Yang Jiayao , Chen Xiaotian , Xu Yan 
Published: May 2023

Abstract
Objective
To explore the effect of nutritional prehabilitation on the clinical prognosis of elderly patients undergoing abdominal tumor surgery.
Methods
A prospective cohort study was conducted. Participants were divided into two groups according to whether they received oral nutritional supplementation at the first outpatient visit. The nutritional prehabilitation group (n = 41) adopted nutritional prehabilitation mode, while the control group (n = 55) was treated with routine care-mode. All patients underwent laparoscopic surgery according to National Comprehensive Cancer Network (NCCN) guidelines. The changes of nutritional status, complications, psychological status, hospitalization days and expenditures were compared between the two groups.
Results
Both of the weight of patients in two groups were decreased. The decline of body weight in prehabilitation group was less than control group (-1.87 vs. -2.55 kg, P < 0.01). The improvement of hospital anxiety scale score in the nutritional prehabilitation group was significant. (4.78 vs. 5.31, P = 0.01). The infection rate of nutritional prehabilitation group was lower than that of control group (17.07% vs. 36.36%, P = 0.04). At discharge, patients in the nutritional prehabilitation group had significantly fewer hospitalization days (14.29 vs. 17.11 d, P = 0.03).
Conclusion
In elderly patients undergoing abdominal tumor surgery, nutritional prehabilitation model may help maintain better physical and mental status,reducing infection rate and shorten hospitalization days.
Tomography of memory engrams in self-organizing nanowire connectomes
Authors: Ricciardi Carlo , Milano Gianluca , Cultrera Alessandro , Boarino Luca , Callegaro Luca 
Published: May 2023

Abstract
Self-organizing memristive nanowire connectomes have been exploited for physical (in materia) implementation of brain-inspired computing paradigms. Despite the emergent behavior was shown to rely on weight plasticity at single junction/synapse level and wiring plasticity involving topological changes, a shift to multiterminal paradigms is needed to unveil dynamics at the network level. Here, we report on tomographical evidence of memory engrams(or memory traces) in nanowire connectomes, i.e., chemical and physical changes in biological neural substrates supposed to endow the representation of experience stored in the brain. An experimental/modeling approach shows that spatially correlated short-term plasticity effects can turn into long-lasting engram memory patterns inherently related to network topology inhomogeneities. The ability to exploit both encoding and consolidation of information on the same physical substrate would open radically new perspectives for in materiacomputing, while offering to neuroscientists an alternative platform to understand the role of memory in learning and knowledge.
Intrapulmonary ectopic thymoma with severe myasthenia gravis after thymoma surgery: A case report and literature review
Authors: Yang Xin , Li JinYao , He Weiwei , Xiong Cheng , Huang ZhiQiang , Yang ShuangFeng , Wang Xiaoming 
Published: May 2023

Abstract
Background: Ectopic thymoma are rare thymic tumorslocated in regions other than the anterior mediastinum. It is even rarer to find patients with intrapulmonary ectopic thymoma and myasthenia gravis . In particular, patients with pulmonary masses with pulmonary symptoms such as cough, sputum, and dyspnea are highly susceptible to misdiagnosis. Here, we report the clinical data, tumor pathology, treatment, and prognosis of a patient with intrapulmonary ectopic thymoma and myasthenia gravis after thymoma surgery and review the relevant literature.
Case presentation: Forty-five days ago, a 54-year-old female patient with a 12-year earlier clinical diagnosis of myasthenia gravis (type II) with thymoma (type B1) and thymoma resection presented with ptosis of the right upper eyelid with double vision. Enhanced chest computed tomography revealed a tumorous lesion in the supraglottic segment of the upper lobe of the left lung. After wedge resection of the upper lobe of the lung, the pathological biopsy and immunohistochemistry suggested pulmonary thymoma (mainly type B3). After surgery, the patient was treated with long-term oral pyridostigmine bromide combined with adjuvant radiation therapy.
Discussions and Conclusion: This case report and review of the related literature show that even after removal for thymoma, there is a possibility of recurrence and unexpected sites of recurrence, such as the lungs.It is also important to consider the possibility of other rare neurological diseases such as thymoma located in the lungs in addition to lung tumors in patients with pulmonary masses, whether the patient presents with or without myasthenia gravis.Early lung biopsy can lead to early identification and treatment of the disease.This case provide a reference for the clinical diagnosis of intrapulmonary ectopic thymoma and improve its clinical treatment.
WITHDRAWN: A case presenting with thyrotoxicosis, which is thought to be related to radiation-induced thyroiditis radiation-induced thyroiditis
Authors: Boyacı İhsan 
Published: May 2023

Abstract
Background: Thyrotoxicosis is characterized by diverse symptoms, various etiological causes, and a number of different treatment options. Rational and appropriate treatment requires an accurate diagnosis. A well-made differential diagnosis and consideration of concomitant medical conditions are essential for an accurate diagnosis. We present a detailed differential diagnosis of an instructive case with thyrotoxicosis onset which might be associated with more than one etiological factor.Case Report: A 45-year-old woman who received chemoradiotherapy for a known laryngeal tumor was admitted with complaints of palpitation, tremor, sweating, and amenorrhea. She had also been using lithium for nearly two years with a diagnosis of bipolar disorder. On examination, she was pale, with tremors, and sweaty. Her heartbeat was 124 beats/min. The thyroid was nonpalpable. TSH was suppressed, free T3 and free T4 were high. TSHR-Ab and autoantibodies were not detected. Acute phase reactants were found to be normal. Bilateral thyroid lobes and size of isthmus were normal in thyroid ultrasonography. The technetium uptake level was determined as 0%. In the etiology, it was thought that the case of thyrotoxicosis, which developed based on radiotherapy-induced thyroiditis, developed hypothyroidism over time due to permanent damage to the thyroid follicles. L-thyroxine was started in the hypothyroid phase, euthyroid was provided with 75 µg and she was followed up.Conclusion: For a rational treatment and follow-up, the etiology must be determined precisely. For this, a detailed anamnesis, a comprehensive physical examination, and rational, cost-effective, and good laboratory practices are required. It should be kept in mind that thyrotoxicosis may pass into the hypothyroid phase in the follow-up. The fact that each step contains clinical lessons and that it is an educational and instructive case necessitated presenting it.
Conjugated microporous polymers containing benzothiazole groups for the efficient removal of RhB from water
Authors: Yuan Yu , Yang Zhishun , Chen Wenwen , Deng Chenghuai , Cai Jingyu , Xiao Longqiang , Zhao Yulai , Hou Linxi 
Published: May 2023

Abstract
Conjugated microporous polymers (CMPs) are widely used as adsorbents due to their unique advantages, including microporous structure, large π-conjugated system, and structural stability. In this study, three types of CMP adsorbents (B-BTD-CMPs) containing different amounts of benzothiadiazole groups were obtained through Suzuki-Miyaura cross-coupling polycondensation reactions to investigate their performances in organic dye removal. The high charge density of nitrogen atoms in benzothiadiazole groups facilitates binding of small molecule dyes through a variety of non-covalent interactions. The results showed B-BTD-1,2,4,5, which containing the most benzothiadiazole groups, had the highest adsorption capacity of for rhodamine B (RhB) up to 531.20 mg g− 1. Furthermore, the adsorption performances of these CMPs on RhB under acidic, neutral, and basic conditions were almost identical, suggesting excellent acid and alkaline resistance. The adsorption capacity of CMPs decreased by less than 10% after five cycles, indicating excellent cyclic stability. It can be deduced that B-BTD-CMPs with stable structures and properties are excellent candidate adsorbents for dye wastewater treatment. This study also demonstrates that introducing N-containing functional groups into porous polymers is beneficial for the adsorption of small-molecule dyes, providing new design ideas for absorbents for dye wastewater treatment.
Application of Artificial Intelligence for Forecasting Surface Quality Index of Irrigation Systems in the Red River Delta, Vietnam
Authors: Duc Phong , Ha Duong Hai , Ngoc Thang Trinh , Minh Tu Nguyen 
Published: May 2023

Abstract
Water sources for irrigation systems in the Red River Delta are very important for the socio-economic development of localities in the region. In recent years, the water source has been polluted due to human activities (discharge), and the water source upstream is limited. Currently, the irrigation systems in the study area, in addition to supplying water for agriculture, also supply water for domestic, industrial, and service purposes. To assess the quality of surface water in irrigation systems for different purposes. Usually, the surface water quality index (WQI) is used, which is calculated from many surface water quality parameters (physical, chemical, microbiological, heavy metal, etc.). However, the calculation of WQI from water quality monitoring parameters is still limited due to the need for many monitoring parameters and the fact that the calculation is relatively complicated. Finding an effective WQI calculation method is very important and necessary to better serve the assessment of surface water quality for the study area. This study will apply machine learning and deep learning algorithms (models) to calculate WQI based on input data (minimum water quality parameters) to reduce surface water quality monitoring costs. The study applied the Bayesian method (BMA) to select optimal water quality parameters (BOD5, NH4+, PO43−, turbidity, TSS, Coliform and DO) to calculate WQI. The results show that the machine learning model has better predictive results than the deep learning model. The gradient boosting model has the most accurate prediction results; these models have high accuracy, ranging from 84–96%.
Plants Competitions Influence Carbon Partitioning Below and Above Ground Parts among Warm Season Cereals (Maize, Sorghum &amp; Millets)
Authors: Amanullah  
Published: May 2023

Abstract

Increasing the efficiency of carbon (C) sequestration through cropping system e.g., intercropping and mixed cropping play an important role to increase total C accumulation and it’s partitioning into shoots above the ground and roots below the ground. Unfortunately, there is lack of research on carbon content (CC) accumulation and its partitioning into roots and shoots when the plants competes each other in mixed cropping. Therefore, a hypothesis on the CC accumulation and partitioning into shoots and roots of summer cereals crops as mixed cropping under two different water levels (low and high) was tested. The hypothesis was supported by the results, and considerable variation was observed in ACC, BCC and TCC under different stands and water levels. The corn plants in pure stand (T1) had higher ACC (7.82 g C plant− 1), BCC (1.43 g C plant− 1) and TCC (9.24 g C plant− 1) than the pure stands of sorghum (T2) and millets (T3). The ACC, BCC and TCC of the three crops mixed stand was lower than two crops mixed stand. Corn mixed either with sorghum (T4) or millets (T5) had higher ACC, BCC and TCC than sorghum and millets, and sorghum mixed with millets had higher ACC, BCC and TCC than millets plants. Among the three crops, the higher ACC, BCC and TCC of corn (T7) was attributed to its higher CGR, higher WUE, higher competition ratio, higher DM accumulation and greater partitioning into shoots and roots. Grain sorghum ranked second and foxtail millets ranked third in terms of ACC, BCC and TCC in the mixed (corn > sorghum > millets). Corn was found the best competitor to sequester more CO2 from atmosphere when grown mixed either with sorghum or millets, while millets was declared the least competitor that sequester the less atmospheric CO2 when grown mixed with corn or sorghum (corn > sorghum > millets i.e. 9.24, 2.17 and 1.31 g C plant− 1, respectively).