bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental study on partial compression parallel to grain of solid timber
Authors: Totsuka Marina , Jockwer Robert , Aoki Kenji , Inayama Masahiro 
Published: May 2021

AbstractThis paper describes results and analysis of experimental testing of entire and partial compression strength and stiffness parallel to the grain of solid timber (Japanese cedar). To investigate the spreading effects, the size effect of strength and stiffness, and the mechanism of the damage zone located close to the loading plates, tests on 90 specimens were performed. As a result, it was observed that damage zones existed near the loading plates. The observed spreading effects in the compression parallel to the grain were very small which justifies neglecting them regarding strength and stiffness. Although a presence of a size effect of the compression strength parallel to the grain of glulam specimens with knots was reported, the compression strength parallel to the grain of solid wood specimens without knots does not have a size effect. The height and width of the cross-section of the specimens have an influence on the damage zones and, hence, on the effective modulus of elasticity of the full height of the specimens. The compression strength has a correlation with the density of the timber and the width of the annual rings.
Liposomal Nanomedicine: Applications for Drug Delivery in Cancer Therapy
Authors: Rommasi Foad , Esfandiari Neda 
Published: May 2021

AbstractThe increasing prevalence of cancer, a disease in which rapid and uncontrollable cell growth causes complication and tissue dysfunction, is one of the serious and tense concerns of scientists and physicians. Nowadays, cancer diagnosis and especially its effective treatment have been considered as one of the biggest challenges in health and medicine in the last century. Despite significant advances in drug discovery and delivery, their many adverse effects and inadequate specificity and sensitivity, which usually cause damage to healthy tissues and organs, have been great barriers in using them. Limitation in the duration and amount of these therapeutic agents’ administration is also challenging. On the other hand, the incidence of tumor cells that are resistant to typical methods of cancer treatment, such as chemotherapy and radiotherapy, highlights the intense need for innovation, improvement, and development in antitumor drug properties. Liposomes have been suggested as a suitable candidate for drug delivery and cancer treatment in nanomedicine due to their ability to store drugs with different physical and chemical characteristics. Moreover, the high flexibility and potential of liposome structure for chemical modification by conjugating various polymers, ligands, and molecules is a significant pro for liposomes not only to enhance their pharmacological merits but also to improve the effectiveness of anticancer drugs. Liposomes can increase the sensitivity, specificity, and durability of these anti-malignant cell agents in the body and provide remarkable benefits to be applied in nanomedicines. We reviewed the discovery and development of liposomes focusing on their clinical applications to treat diverse sorts of cancers and diseases. How the properties of liposomal drugs can be improved and their opportunity and challenges for cancer therapy were also considered and discussed.Graphic abstract
Super.FELT: supervised feature extraction learning using triplet loss for drug response prediction with multi-omics data
Authors: Park Sejin , Soh Jihee , Lee Hyunju 
Published: May 2021

AbstractBackgroundPredicting the drug response of a patient is important for precision oncology. In recent studies, multi-omics data have been used to improve the prediction accuracy of drug response. Although multi-omics data are good resources for drug response prediction, the large dimension of data tends to hinder performance improvement. In this study, we aimed to develop a new method, which can effectively reduce the large dimension of data, based on the supervised deep learning model for predicting drug response.ResultsWe proposed a novel method called Supervised Feature Extraction Learning using Triplet loss (Super.FELT) for drug response prediction. Super.FELT consists of three stages, namely, feature selection, feature encoding using a supervised method, and binary classification of drug response (sensitive or resistant). We used multi-omics data including mutation, copy number aberration, and gene expression, and these were obtained from cell lines [Genomics of Drug Sensitivity in Cancer (GDSC), Cancer Cell Line Encyclopedia (CCLE), and Cancer Therapeutics Response Portal (CTRP)], patient-derived tumor xenografts (PDX), and The Cancer Genome Atlas (TCGA). GDSC was used for training and cross-validation tests, and CCLE, CTRP, PDX, and TCGA were used for external validation. We performed ablation studies for the three stages and verified that the use of multi-omics data guarantees better performance of drug response prediction. Our results verified that Super.FELT outperformed the other methods at external validation on PDX and TCGA and was good at cross-validation on GDSC and external validation on CCLE and CTRP. In addition, through our experiments, we confirmed that using multi-omics data is useful for external non-cell line data.ConclusionBy separating the three stages, Super.FELT achieved better performance than the other methods. Through our results, we found that it is important to train encoders and a classifier independently, especially for external test on PDX and TCGA. Moreover, although gene expression is the most powerful data on cell line data, multi-omics promises better performance for external validation on non-cell line data than gene expression data. Source codes of Super.FELT are available at https://github.com/DMCB-GIST/Super.FELT.
Comparison study of differential abundance testing methods using two large Parkinson disease gut microbiome datasets derived from 16S amplicon sequencing
Authors: Wallen Zachary D. 
Published: May 2021

AbstractBackgroundTesting for differential abundance of microbes in disease is a common practice in microbiome studies. Numerous differential abundance (DA) testing methods exist and range from traditional statistical tests to methods designed for microbiome data. Comparison studies of DA testing methods have been performed, but none performed on microbiome datasets collected for the study of real, complex disease. Due to this, DA testing was performed here using various DA methods in two large, uniformly collected gut microbiome datasets on Parkinson disease (PD), and their results compared.ResultsOverall, 78–92% of taxa tested were detected as differentially abundant by at least one method, while 5–22% were called differentially abundant by the majority of methods (depending on dataset and filtering of taxonomic data prior to testing). Concordances between method results ranged from 1 to 100%. Average concordance for datasets 1 and 2 were 24% and 28% respectively, and 27% for replicated DA signatures. Concordances increased when removing rarer taxa before testing, increasing average concordances by 2–32%. Certain methods consistently resulted in higher concordances (e.g. ANCOM-BC, LEfSe), while others consistently resulted in lower (e.g. edgeR, fitZIG). Hierarchical clustering revealed three groups of DA signatures that were (1) replicated by the majority of methods on average and included taxa previously associated with PD, (2) replicated by a subset of methods and included taxa largely enriched in PD, and (3) replicated by few to one method(s).ConclusionsDifferential abundance tests yielded varied concordances, and amounts of detected DA signatures. Some methods were more concordant than others on both filtered and unfiltered data, therefore, if consistency with other study methodology is a key goal, one might choose among these methods. Even still, using one method on one dataset may find true associations, but may also detect false positives. To help lower false positives, one might analyze data with two or more DA methods to gauge concordance, and use a built-in replication dataset. This study will hopefully serve to complement previously reported DA method comparison studies by implementing and coalescing a large number of both previously and yet to be compared methods on two real gut microbiome datasets.
Clustering of cancer data based on Stiefel manifold for multiple views
Authors: Tian Jing , Zhao Jianping , Zheng Chunhou 
Published: May 2021

AbstractBackgroundIn recent years, various sequencing techniques have been used to collect biomedical omics datasets. It is usually possible to obtain multiple types of omics data from a single patient sample. Clustering of omics data plays an indispensable role in biological and medical research, and it is helpful to reveal data structures from multiple collections. Nevertheless, clustering of omics data consists of many challenges. The primary challenges in omics data analysis come from high dimension of data and small size of sample. Therefore, it is difficult to find a suitable integration method for structural analysis of multiple datasets.ResultsIn this paper, a multi-view clustering based on Stiefel manifold method (MCSM) is proposed. The MCSM method comprises three core steps. Firstly, we established a binary optimization model for the simultaneous clustering problem. Secondly, we solved the optimization problem by linear search algorithm based on Stiefel manifold. Finally, we integrated the clustering results obtained from three omics by using k-nearest neighbor method. We applied this approach to four cancer datasets on TCGA. The result shows that our method is superior to several state-of-art methods, which depends on the hypothesis that the underlying omics cluster class is the same.ConclusionParticularly, our approach has better performance than compared approaches when the underlying clusters are inconsistent. For patients with different subtypes, both consistent and differential clusters can be identified at the same time.
Comparative evaluation of full-length isoform quantification from RNA-Seq
Authors: Sarantopoulou Dimitra , Brooks Thomas G. , Nayak Soumyashant , Mrčela Antonijo , Lahens Nicholas F. , Grant Gregory R. 
Published: May 2021

AbstractBackgroundFull-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short.ResultsHere we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control.ConclusionsSalmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.
Conserved and non-conserved functions of the rice homologs of the Arabidopsis trichome initiation-regulating MBW complex proteins
Authors: Zheng Kaijie , Wang Xutong , Wang Yating , Wang Shucai 
Published: May 2021

AbstractBackgroundTrichome initiation in Arabidopsis is regulated by a MYB-bHLH-WD40 (MBW) transcriptional activator complex formed by the R2R3 MYB transcription factor GLABRA1 (GL1), MYB23 or MYB82, the bHLH transcription factor GLABRA3 (GL3), ENHANCER OF GLABRA3 (EGL3) or TRANSPARENT TESTA8 (TT8), and the WD40-repeat protein TRANSPARENT TESTA GLABRA1 (TTG1). However, the functions of the rice homologs of the MBW complex proteins remained uncharacterized.ResultsBased on amino acid sequence identity and similarity, and protein interaction prediction, we identified OsGL1s, OsGL3s and OsTTG1s as rice homologs of the MBW complex proteins. By using protoplast transfection, we show that OsGL1D, OsGL1E, OsGL3B and OsTTG1A were predominantly localized in the nucleus, OsGL3B functions as a transcriptional activator and is able to interact with GL1 and TTG1. By using yeast two-hybrid and protoplast transfection assays, we show that OsGL3B is able to interact with OsGL1E and OsTTG1A, and OsGL1E and OsTTG1A are also able to interact with GL3. On the other hand, we found that OsGL1D functions as a transcription activator, and it can interact with GL3 but not OsGL3B. Furthermore, our results show that expression ofOsTTG1Ain thettg1mutant restored the phenotypes including alternations in trichome and root hair formation, seed color, mucilage production and anthocyanin biosynthesis, indicating that OsTTG1A and TTG1 may have similar functions.ConclusionThese results suggest that the rice homologs of the Arabidopsis MBW complex proteins are able to form MBW complexes, but may have conserved and non-conserved functions.
Post-operative pain management modalities employed in clinical trials for adult patients in LMIC; a systematic review
Authors: Afshan Gauhar , Khan Robyna Irshad , Ahmed Aliya , Siddiqui Ali Sarfraz , Rehman Azhar , Raza Syed Amir , Kerai Rozina , Mustafa Khawaja 
Published: May 2021

AbstractBackgroundUnrelieved postoperative pain afflicts millions each year in low and middle income countries (LMIC). Despite substantial advances in the study of pain, this area remains neglected. Current systematic review was designed to ascertain the types of clinical trials conducted in LMIC on postoperative pain management modalities over the last decade.MethodsA comprehensive search was performed in June 2019 on PubMed, Cochrane Library, CINAHL Plus, and Web of Science databases to identify relevant trials on the management of postoperative pain in LMIC. Out of 1450 RCTs, 108 studies were reviewed for quality evidence using structured form of critical appraisal skill program. Total of 51 clinical trials were included after applying inclusion/exclusion criteria.ResultsResults are charted according to the type of surgery. Eleven trials on laparoscopic cholecystectomy used multimodal analgesia including some form of regional analgesia. Different analgesic modalities were studied in 4 trials on thoracotomy, but none used multimodal approach. In 11 trials on laparotomy, multimodal analgesia was employed along with the studied modalities. In 2 trials on hysterectomy, preemptive pregabalin or gabapentin were used for reduction in rescue analgesia. In 13 trials on breast surgical procedures and 10 on orthopaedic surgery, multimodal analgesia was used with some form of regional analgesia.ConclusionWe found that over the past 10 years, clinical trials for postoperative pain modalities have evolved in LMIC according to the current postoperative pain management guidelines i.e. multi-modal approach with some form of regional analgesia. The current review shows that clinical trials were conducted using multimodal analgesia including but not limited to some form of regional analgesia for postoperative pain in LMIC however this research snapshot (of only three countries) may not exactly reflect the clinical practices in all 47 countries.Post Operative Pain Management Modalities Employed in Clinical Trials for Adult Patients in LMIC; A Systematic Review.
Combined management can decrease blood pressure: an investigation of health-seeking behaviors among hypertensive patients in urban communities in China
Authors: Wang Si , Liu Kai , Zhang Xin , Meng Qingtao , Li Xinran , Ye Runyu , Zhang Zhipeng , Chen Xiaoping 
Published: May 2021

Abstract
Background
Hypertensive patients can freely choose informal medical facilities, such as pharmacies, community health service centres, and cardiology clinics in secondary or tertiary hospitals, as routine places for medical treatment in China currently. The proportions, influencing factors and effects of different health-seeking behaviours on blood pressure (BP) among hypertensive patients in urban communities are not clear. The aim of the study was to investigate health-seeking behaviours and the effects of different health-seeking behaviours on BP among hypertensive patients in urban communities in China.

Methods
A cross-sectional survey of hypertension was conducted in urban communities in Chengdu. A total of 437 hypertensive patients seeking medical help regularly were sequentially enrolled to complete a the questionnaire on health-seeking behaviours.

Results
The average age was 67.1 ± 7.5 years old. The control rate of BP was 41.0%, and the systolic blood pressure (SBP) and diastolic blood pressure (DBP) were 144.2 ± 17.9 mm Hg and 75.4 ± 10.4 mm Hg, respectively. Among the hypertensive patients investigated, 62.8% chose community health service centre, 5.2% chose informal medical facilities, 21.5% chose cardiology clinics in secondary or tertiary hospitals, and 10.5% chose both community health service centre and cardiology clinics as the usual places for medical treatment. There were significant differences in education levels, proportions of home BP monitoring, establishment of chronic disease archives in the community, medication adherence and side effects of drugs among the four groups. The control rates of BP were 39.4%, 23.8%, 43.0% and 54.8% (P = 0.100), respectively. The SBPs were 145.1 ± 18.0, 150.9 ± 19.8, 143.8 ± 17.5 and 136.3 ± 15.1 mm Hg (P = 0.007), respectively, and it was significantly lower in the combined management group than in the other three groups. Compared with patients choosing community health service centre, patients in the combined management group had a significantly lower BP level (β = −0.119, P = 0.038) adjusting for age, sex, education level, establishment of chronic disease archives, medication adherence and number of antihypertensive drugs.

Conclusions
Combined management with both community health service centre and higher-level hospitals can decrease BP.
Confounding influences of malnutrition and Plasmodium falciparum and Schistosoma haematobium infections on haematological parameters in school children in Muyuka, Cameroon
Authors: Sumbele Irene Ule Ngole , Otia Ofon Vitalis , Francis Lorraine , Bopda Orelien Sylvain Mtopi , Ebai Calvin Bisong , Ning Teh Rene , Kimbi Helen Kuo Kuo , Nkuo-Akenji Theresa 
Published: May 2021

Abstract
Background
School-aged children (SAC) are a high-risk demographic group for infectious diseases and malnutrition. The objective of this study was to assess the burden and the effect of Plasmodium falciparum and Schistosoma haematobium infections on the haematological indices in SAC and the confounding influence of malnutrition on the outcomes.

Methods
This cross-sectional study was conducted in SAC 4–14 years old living in Ikata, Bafia and Mile 14-Likoko in Muyuka, Cameroon. Anthropometric measures of malnutrition were obtained and blood samples collected were used for detection of malaria parasites by Giemsa-stained blood films using light microscopy and complete blood count analysis using an automated haematology analyser. Urine samples collected were used to detect micro haematuria with the aid of reagent strips and the eggs of S. haematobium by urine filtration technique. Multiple linear regression model was used to examine influence of independent variables on haematological parameters.

Results
Out of the 606 SAC examined, the prevalence of single infections with Plasmodium or S. haematobium and co-infection with both parasites was 16.2, 16.3 and 8.3%, respectively. Overall, malaria parasite (MP), urogenital schistosomiasis, malnutrition, anaemia, haematuria, microcytosis and thrombocytopenia was prevalent in 24.4, 24.6, 25.9, 74.4, 12.2, 45.4 and 11.1% of SAC, respectively. A significant linear decline (P = 0.023) in prevalence of P. falciparum infection with the severity of stunting was observed. Factors that significantly influenced haematological parameters included haemoglobin: age, stunting and MP; haematocrit: age and MP; white blood cell count: age; red blood cell count; age and MP; lymphocyte counts: stunting; mean cell volume: age; mean cell haemoglobin: age and stunting; mean cell haemoglobin concentration: sex, stunting and red cell distribution width-coefficient of variation: sex, age and stunting.

Conclusions
Malnutrition, Plasmodium and S. haematobium infections are common while anaemia is a severe public health problem in Muyuka, Cameroon. The interaction between haematological parameters with malaria parasites as well as linear growth index was negative and other interactions indicate systemic inflammation. While findings provide contextual intervention targets to ensure the judicious use of the limited resources, there is need for regular monitoring and proper treatment to improve the health of the underserved population.
Factors associated with negative pleural adenosine deaminase results in the diagnosis of childhood pleural tuberculosis
Authors: Han Xing-Fen , Han Chao , Jin Feng , Wang Jun-Li , Wang Mao-Shui 
Published: May 2021

AbstractBackgroundUntil now, the influential factors associated with pleural adenosine deaminase (ADA) activity among children remain unclear. This retrospective study was therefore conducted aiming to investigate the factors associated with negative pleural ADA results in the diagnosis of childhood pleural tuberculosis (TB).MethodsBetween January 2006 and December 2019, children patients with definite or possible pleural TB were recruited for potential analysis. Then, patients were stratified into two categories: negative pleural ADA results group (experimental group, ≤40 U/L) and positive pleural ADA results group (control group, > 40 U/L). Univariate and multivariate logistic regression analyses were performed to estimate risk factors for negative pleural ADA results.ResultsA total of 84 patients with pleural TB were recruited and subsequently classified as experimental (n = 17) and control groups (n = 67). Multivariate analysis (Hosmer–Lemeshow goodness-of-fit test: χ2 = 1.881, df = 6,P = 0.930) revealed that variables, such as chest pain (age-adjusted OR = 0.0510, 95% CI: 0.004, 0.583), pleural total protein (≤45.3 g/L, age-adjusted OR = 27.7, 95% CI: 2.5, 307.7), pleural lactate dehydrogenase (LDH, ≤505 U/L, age-adjusted OR = 59.9, 95% CI: 4.2, 857.2) and blood urea nitrogen (≤3.2 mmol/L, age-adjusted OR = 32.0, 95% CI: 2.4, 426.9), were associated with negative pleural ADA results when diagnosing childhood pleural TB.ConclusionOur findings demonstrated that chest pain, pleural total protein, pleural LDH, and blood urea nitrogen were associated with a negative pleural ADA result for the diagnosis of pleural TB among children. When interpreting pleural ADA levels in children with these characteristics, a careful clinical assessment is required for the pleural TB diagnosis.