bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effectiveness and safety of cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy for colorectal peritoneal metastasis: a systematic review and meta-analysis
Authors: Xu Zhonghang , Wang Xingbo , Wu Yuanyu , Wang Chengbing , Fang Xuedong 
Published: March 2022

Abstract
Objectives: This systematic review and meta-analysis aimed to evaluate the effectiveness and safety of cytoreductive surgery (CRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC) on colorectal peritoneal metastasis (CRPM) and provide more reliable evidence for clinical practice.Methods: We searched for relevant randomized controlled trials (RCTs), case-control studies and cohort studies in PubMed, Web of Science, Cochrane Library, and Embase databases from their inception to 1 January 2022. Hazard ratio (HR) and odd ratio (OR) with 95% confidence intervals (CIs) were performed a meta-analysis using RevMan 5.3 software.Results: A total of twelve studies, of which three RCTs, eight cohort studies and one case-control study were included, and 3605 participants were involved. The results showed that CRS plus HIPEC was better than other remedial measures at improving the overall survival (OS) (HR=0.46, 95% C1:0.35-0.61, P=0.02). However, the heterogeneity was obvious (P<0.0001, I2=73%). According to different control measures, it is divided into three subgroups of CRS, CRS plus intraperitoneal chemotherapy (IPC) and palliative chemotherapy (PC). The results of subgroup analysis showed that CRS plus HIPEC was better than CRS plus IPC at enhancing the OS (HR=0.58, 95% CI :0.36-0.93, P=0.02) and was more effective than PC at improving the OS (HR=0.29, 95% CI :0.24-0.35, P<0.00001). On the contrary, CRS plus HIPEC was no significant effect than CRS at improving the OS (HR=0.76, 95% CI :0.57-1.01, P=0.06). In addition, CRS plus HIPEC had more adverse events than CRS (OR=1.69, 95% CI : 1.06-2.70, P=0.03). Conclusions: This systematic review and meta-analysis suggests that CRS plus HIPEC might be effective to CRPM in improving the OS. However, compared with CRS alone, the efficacy of CRS plus HIPEC has not improved much, and CRS plus HIPEC may bring more adverse events.
Controlled Drug Release of Modified Mesoporous Silica with Higher Driving Forces Derived from the Accurate Dispersion of Azobenzene Groups
Authors: Xue Yuqing , Zhu Wenqian , Zhao Wenhui , Lv Fengzhu , Guo Sufang , Zhang Yihe 
Published: March 2022

Abstract
It is highly desirable to design delivery systems that can be activated by stimuli to control the release of guest molecules. So in the present paper two kinds of mesoporous silica (m-SiO2) with amino and azobenzene groups accurately dispersed in different position of the pores were prepared based on the reactivity difference of the raw materials and the feeding sequence. The m-SiO2 with the azobenzene groups at the corner of the particles not only had higher loading ability but also could realize high effective light-control release. ~97% of IBU could be released out from the particles under UV irradiation, almost 10 times as much as the m-SiO2 with the azobenzene groups in the out layer of particles with the same composition. The obvious release difference by the two kinds of particles was analyzed based on the arrangement of the segments in the pores of m-SiO2. The conformation change of stack accumulated azobenzene at the core of the particles produced higher driving force for IBU release and decreased the attraction between -NH2 with drug molecules. The afforded mechanism was confirmed by release drug molecules with different length.
DNMT3A low-Expression is Correlated to Poor Prognosis in Childhood B-ALL and Confers Resistance to Daunorubicin on Leukemic Cells
Authors: Li Weijing , Liu Shuguang , Wang Chanjuan , Cui Lei , Zhao Xiaoxi , Liu Wei , Zhang Ruidong , Li Zhigang 
Published: March 2022

Abstract
Background Little is known about DNMT3A expression and its prognostic significance in childhood B cell acute lymphoblastic leukemia (B-ALL). MethodsWe determined DNMT3A mRNA expression in 102 children with B-ALL. Correlations with relapse-free survival (RFS) and common clinical characteristics were analyzed. DNMT3A was stably knocked out by CRISPR/Cas9 gene editing technology in Reh and 697 B-ALL cell lines. Cell proliferation activity after treated with daunorubicin (DNR) was determined by CCK8 assay in DNMT3A KO Reh and 697 cell lines.Results DNMT3A expression in B-ALL patients who were in continuous complete remission (CCR) was higher than in those who got relapse (P=0.0111). Receiver operating characteristic curve showed prognostic significance of DNMT3A expression (P=0.003). Low expression of DNMT3A (<0.197) was significantly correlated with poor RFS (P<0.001) in children with B-ALL. Knock-out of DNMT3A in Reh and 697 cell lines significantly increased IC50 of DNR (P=0.0201 and 0.0022 respectively), indicating elevated resistance to DNR. ConclusionLow expression of DNMT3A associates with poor prognosis in children with B-ALL. Knock-out of DNMT3A confers resistance to DNR on leukemic cells.
Health-related Quality of Life using WHODAS 2.0 and associated Factors 1 year after Stroke in Korea: a Multi-center and Cross-sectional Study
Authors: Lee HeyJean , Song Jung-Kook , Moon Jiyoung , Kim Keonyeop , Park Hyeung-Keun , Kang Gil-Won , Shin Jun-Ho , Kang Jongsoo , Kim Byoung-Gwon , Lee Young-Hoon , Jeong Hye Seon , Lee Heeyoung , Lee Won Kyung , Kim Seongheon , Park Young-Kwon 
Published: March 2022

Abstract
Background: The self-perceived level of disability for stroke survivors in community is little known. We aimed to characterize HRQoL 1 year after stroke and to investigate how socio-demographic and stroke-related factors and medical adherence explain the self-perceived level of disability among a Korean stroke population.Methods: This study was a multi-center and cross-sectional study. A total of 382 ischemic stroke survivors at 1 year after onset recruited from 11 university hospitals underwent a one-session assessment including: socioeconomic variables, the modified Rankin Scale (mRS), various neurological sequelae, the modifed Morisky scale (MMS), and the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) 36-items. The relationship between disability and different variables was analyzed using ordinal logistic regression. Results: The prevalence of disability by global WHODAS 2.0 score was 62.6% (41.6% for mild; 16.0% for moderate; 5.0% for severe) in subjects. Prevalence of severe disability was higher in Participation in society (16.8%) and Getting around (11.8%) than in the other domains. Low MMS motivation was the only factor determining the significant association between all six domains of disability after adjustment. Different predictors for specific domains were age, mRS, dysarthria, trouble seeing, cognition problem and MMS-motivation for Understanding and communicating; age, recurrent stroke, mRS, hemiplegia, facial palsy, general weakness and MMS-motivation for Getting around; age, education, mRS, hemiplegia and MMS-motivation for Self-care; education, recurrent stroke, hemiplegia, dysarthria and MMS-motivation for Getting along with people; age, education, income, mRS, hemiplegia, dysarthria, MMS-knowledge and MMS-motivation for Life activities; living without spouse, mRS, hemiplegia, dysarthria, trouble seeing, cognition problem, general weakness and MMS-motivation for Participation in society.Conclusions: Self-perceived disability by the WHODAS 2.0 had almost double the prevalence compared to hemiplegia, one of the most common neurological sequelae 1 year after stroke. Each domain of disability increased with various associated factors. Interventions promoting medical adherence of motivation seem to help high HRQoL in all domains.
Regional Variation and Factors Associated With Fetal Macrosomia in Ethiopia
Authors: Nugussu Gurmessa , Banbeta Akalu , Abdisa Jaleta , Bedada Dechasa 
Published: March 2022

Abstract
Background: Globally, there is an increase in the prevalence of high birth weight. In Sub-Sahara African countries, including Ethiopia, weighting newborns at birth are not well addressed thereby awareness of high birth weight is limited. In this paper, we aimed to assess the between-region variability of the prevalence and identify the associated factors with high birth weight in Ethiopia.Methods: The study is based on the Ethiopian Demographic and Health Survey which is conducted in 2016. A total of 2110 newborns across all regions of Ethiopia are included in the study. The multilevel logistic regression model is applied to identify the associated factors of high birth weight and to evaluate the variation of the prevalence of high birth weight across the regions of Ethiopia. Results: The prevalence of high birth weight in Ethiopia was 10.4%. Based on our analysis, mother's age, residence, mother’s educational level, mother's body mass index gestational age, socio-economic class, and the sex of the newborn baby were the significant factors associated with high birth weight. With inter-class correlation of 14%, there is a significant variation of high birth weight among the regions of Ethiopia.Conclusion: Controlling mother’s BMI, strengthening follow up for elder women and women in high socio-economic class, and prevention of post maturity (≥40 weeks) gestational age could be effective personal and public health measures to combat high birth weight in Ethiopia.
The binding between ROCK1 and KIF2A signals for the centrosome amplification triggered by high glucose, insulin and palmitic acid
Authors: Lee Shao Chin , Zhao Meng Lu , Chen Bin 
Published: March 2022

Abstract
Background: Diabetes increases the risk for various cancers without established mechanisms. Centrosome amplification can initiate tumorigenesis in genetically modified cells. However, the findings from genetically modified experimental models may be far away from reality. We have reported that diabetes promotes the occurrence of centrosome amplification in different types of cells, implicating that centrosome amplification is a candidate mechanism underlying the diabetes-promoted tumorigenesis. In the present study, we investigated the molecular mechanisms of the centrosome amplification triggered by high glucose, insulin and palmitic acid using HCT116 colon cancer cells as an experimental model. Results: We found that KIF2A was localized in the centrosomes. The experimental treatment induced the binding between ROCK1 and KIF2A, although did not increase the protein level of KIF2A. The molecular docking modeling analysis also showed that the two proteins had the binding/interaction potential. We used siRNA of each protein to knockdown their expression level, as a tool to disrupt the ROCK1-KIF2A complex, which attenuated the treatment-induced centrosome amplification. Conclusions: Our results suggest that the binding between ROCK1 and KIF2A signals for the diabetes-associated centrosome amplification. This provides a molecular target for the inhibition of the centrosome amplification, which might be required for assessing the role of centrosome amplification in cancer in the nature, such as cancer in diabetes.
Influence of tannins and mannoproteins products on the improvement of organoleptic characteristics of wines
Authors: Bilko Marina , Gunko Sergiy , Babych Iryna , Doboniy Inna 
Published: March 2022

The aim of the work was to establish an influence of oenological tannins and mannoproteins products on the change of the organoleptic parameters of table dry wines, made from grapes of aromatic and non-aromatic varieties. The materials of the researches were wines that had defects or faults, mainly related with changes in wine aroma and taste. Oenological tannins of various botanical origins and mannoproteins products of a company Martin Vialatte (France) were used in the researches. Wines with these additives were mixed intensively, kept during 3 days at a temperature, not exceeding 12 °C and then determined the sensory characteristics of wine. Control samples were wines without additives. The descriptive method of analysis was used to create aromatic profiles of wines. The effectiveness of tannins and mannoproteins products on the sensory characteristics of wines was established. The intensity of the descriptors that made a positive affect on the aroma and taste of the samples was increasing. If, at the beginning tones of oxidation or bitterness were felt in the wines, then after introduction of the additives, these tones decreased in intensity. A difference of the changes of aromatic characteristics of wines from two groups of grapes with different aromatics was established. The action of additives was spread on the tings of descriptors, enriching the aroma of samples from non-aromatic grape varieties together with eliminating faults of taste. The effect of the additives was light in the aromatic varieties of grape that is due to the strong aroma and expressed taste of the grapes of these varieties. The results of the researches can be used to improve the quality of white wines, and further researches should be focused on the expansion of assortments of wines from other varieties, as a result utilizing tannins and mannoprotein products
Evaluating the effectiveness of the Water Resources Master Plan in Campinas, Brazil
Authors: Galbetti Marcus Vinícius , Zuffo Antonio Carlos , Shinma Taís Arriero , Boulomytis Vassiliki Terezinha Galvão , Imteaz Monzur 
Published: March 2022

Abstract
From 2013 to 2015, the Brazilian southeast region experienced the most severe and intense drought recorded, the Water Crisis. This outstanding drought led the government to make efforts toward an adequate water resources management. In Campinas, the third most populous city of the State of São Paulo, the government proposed the Campinas Water Resources Master Plan (CWRMP), the main objective of which was to ensure the quantity and quality of water, reducing water vulnerability in the municipality. In this study, we evaluated the effectiveness of this plan through the major guidelines into four actions: (1) increase the permeability rate and the soil infiltration capacity, (2) increase the vegetation cover, (3) improve the sanitation services, and (4) minimize the number of contaminated areas. For Actions 1 and 2, we inferred that the aforementioned parameters have increased after the CWRMP enactment. About the Action 3, we found that Campinas has historically provided good sanitation services to the population, regardless of the CWRMP promulgation. However, more improvements should be given to waste collection and recycling services. The underground water consumption also has to be regulated, as significant exploitation has no legal permit. Finally, considering Action 4, the number of contaminated areas was reduced in the available data period. Therefore, the CWRMP was considered a valuable initiative to support an integrated and sustainable use of water, improving the water resources management in Campinas.
Adsorption of Congo red and tetracycline onto water treatment sludge biochar: characterisation, kinetic, equilibrium and thermodynamic study
Authors: He Liwenze , Chen Yu , Li Yanjun , Sun Fei , Zhao Yuting , Yang Shunsheng 
Published: March 2022

Abstract
In this study, readily available inexpensive water treatment sludge (WTS) was used to prepare adsorbent for the removal of Congo red (CR) and tetracycline (TC) from aqueous solutions. The structural characteristics and adsorption properties of WTS biochar were characterised via scanning electron microscope, energy dispersive X-ray spectroscopy, Brunauer-Emmett-Teller and Fourier Transform infrared spectroscopy. In batch experiments, the adsorption factors, kinetics, isothermal curves and thermodynamics of the adsorption properties were investigated. The optimum preparation condition of WTS biochar was 400 °C for 4 h under O2-limited pyrolysis, which exhibited increased specific surface area and pore structures. The best adsorption was observed when the pH of the CR and TC solutions was 7 and 4, respectively. The adsorption process followed the pseudo-second-order model, indicating that the main control step was the chemical adsorption process. Isotherm data were best described by the Langmuir model, and the maximum adsorption capacities for CR and TC were 116.4 and 58.5 mg·g−1, respectively. Thermodynamic parameters revealed that the adsorption process was spontaneous and endothermic. According to the analysis, the adsorption mechanism of CR could be attributed to electrostatic attraction, π–π conjugation and hydrogen bonding, whereas that of TC was potentially associated with cation exchange, complex precipitation, π–π conjugation and hydrogen bonding.
A Digital Screening System for Alzheimer Disease Based on a Neuropsychological Test and a Convolutional Neural Network: System Development and Validation
Authors: Cheah Wen-Ting , Hwang Jwu-Jia , Hong Sheng-Yi , Fu Li-Chen , Chang Yu-Ling , Chen Ta-Fu , Chen I-An , Chou Chun-Chen 
Published: March 2022

Background
Alzheimer disease (AD) and other types of dementia are now considered one of the world’s most pressing health problems for aging people worldwide. It was the seventh-leading cause of death, globally, in 2019. With a growing number of patients with dementia and increasing costs for treatment and care, early detection of the disease at the stage of mild cognitive impairment (MCI) will prevent the rapid progression of dementia. In addition to reducing the physical and psychological stress of patients’ caregivers in the long term, it will also improve the everyday quality of life of patients.

Objective
The aim of this study was to design a digital screening system to discriminate between patients with MCI and AD and healthy controls (HCs), based on the Rey-Osterrieth Complex Figure (ROCF) neuropsychological test.

Methods
The study took place at National Taiwan University between 2018 and 2019. In order to develop the system, pretraining was performed using, and features were extracted from, an open sketch data set using a data-driven deep learning approach through a convolutional neural network. Later, the learned features were transferred to our collected data set to further train the classifier. The first data set was collected using pen and paper for the traditional method. The second data set used a tablet and smart pen for data collection. The system’s performance was then evaluated using the data sets.

Results
The performance of the designed system when using the data set that was collected using the traditional pen and paper method resulted in a mean area under the receiver operating characteristic curve (AUROC) of 0.913 (SD 0.004) when distinguishing between patients with MCI and HCs. On the other hand, when discriminating between patients with AD and HCs, the mean AUROC was 0.950 (SD 0.003) when using the data set that was collected using the digitalized method.

Conclusions
The automatic ROCF test scoring system that we designed showed satisfying results for differentiating between patients with AD and MCI and HCs. Comparatively, our proposed network architecture provided better performance than our previous work, which did not include data augmentation and dropout techniques. In addition, it also performed better than other existing network architectures, such as AlexNet and Sketch-a-Net, with transfer learning techniques. The proposed system can be incorporated with other tests to assist clinicians in the early diagnosis of AD and to reduce the physical and mental burden on patients’ family and friends.
Web-Based Skin Cancer Assessment and Classification Using Machine Learning and Mobile Computerized Adaptive Testing in a Rasch Model: Development Study
Authors: Yang Ting-Ya , Chien Tsair-Wei , Lai Feng-Jie 
Published: March 2022

Background
Web-based computerized adaptive testing (CAT) implementation of the skin cancer (SC) risk scale could substantially reduce participant burden without compromising measurement precision. However, the CAT of SC classification has not been reported in academics thus far.

Objective
We aim to build a CAT-based model using machine learning to develop an app for automatic classification of SC to help patients assess the risk at an early stage.

Methods
We extracted data from a population-based Australian cohort study of SC risk (N=43,794) using the Rasch simulation scheme. All 30 feature items were calibrated using the Rasch partial credit model. A total of 1000 cases following a normal distribution (mean 0, SD 1) based on the item and threshold difficulties were simulated using three techniques of machine learning—naïve Bayes, k-nearest neighbors, and logistic regression—to compare the model accuracy in training and testing data sets with a proportion of 70:30, where the former was used to predict the latter. We calculated the sensitivity, specificity, receiver operating characteristic curve (area under the curve [AUC]), and CIs along with the accuracy and precision across the proposed models for comparison. An app that classifies the SC risk of the respondent was developed.

Results
We observed that the 30-item k-nearest neighbors model yielded higher AUC values of 99% and 91% for the 700 training and 300 testing cases, respectively, than its 2 counterparts using the hold-out validation but had lower AUC values of 85% (95% CI 83%-87%) in the k-fold cross-validation and that an app that predicts SC classification for patients was successfully developed and demonstrated in this study.

Conclusions
The 30-item SC prediction model, combined with the Rasch web-based CAT, is recommended for classifying SC in patients. An app we developed to help patients self-assess SC risk at an early stage is required for application in the future.
Sentiment Analysis Of Energy Independence Tweets Using Simple Recurrent Neural Network
Authors: Muludi Kurnia , Akbar Mohammad Surya , Shofiana Dewi Asiah , Syarif Admi 
Published: March 2022

Sentiment analysis is part of computational research that extracts textual data to obtain positive, or negative values related to a topic. In recent research, data are commonly acquired from social media, including Twitter, where users often provide their personal opinion about a particular subject. Energy independence was once a trending topic discussed in Indonesia, as the opinions are diverse, pros and cons, making it interesting to be analyzed. Deep learning is a branch of machine learning consisting of hidden layers of neural networks by applying non-linear transformations and high-level model abstractions in large databases. The recurrent neural network (RNN) is a deep learning method that processes data repeatedly, primarily suitable for handwriting, multi-word data, or voice recognition. This study compares three algorithms: Simple Neural Network, Bernoulli Naive Bayes, and Long Short-Term Memory (LSTM) in sentiment analysis using the energy independence data from Twitter. Based on the results, the Simple Recurrent Neural Network shows the best performance with an accuracy value of 78% compared to Bernoulli Naive Bayes value of 67% and LSTM with an accuracy value of 75%. Keywords— Sentiment Analysis; Simple RNN; LSTM; Bernoulli Naive Bayes; Energy Independence;