bluuebunny/crossref_metadata_2025_split huggingface dataset:
A network pharmacology perspective for deciphering potential mechanisms of action of Solanum nigrum L. in bladder cancer
Authors: Dong Yang , Hao Lin , Fang Kun , Han Xiao-xiao , Yu Hui , Zhang Jian-jun , Cai Long-jun , Fan Tao , Zhang Wen-da , Pang Kun , Ma Wei-ming , Wang Xi-tao , Han Cong-hui 
Published: January 2021

Abstract
Background
Solanum nigrum L. decoction has been used as a folklore medicine in China to prevent the postoperative recurrence of bladder cancer (BC). However, there are no previous pharmacological studies on the protective mechanisms of this activity of the plant. Thus, this study aimed to perform a systematic analysis and to predict the potential action mechanisms underlying S. nigrum activity in BC based on network pharmacology.

Methods
Based on network pharmacology, the active ingredients of S. nigrum and the corresponding targets were identified using the Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform database, and BC-related genes were screened using GeneCards and the Online Mendelian Inheritance in Man database. In addition, ingredient-target (I–T) and protein–protein interaction (PPI) networks were constructed using STRING and Cytoscape, Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted, and then the pathways directly related to BC were integrated manually to reveal the pharmacological mechanism underlying S. nigrum-medicated therapeutic effects in BC.

Results
Seven active herbal ingredients from 39 components of S. nigrum were identified, which shared 77 common target genes related to BC. I-T network analysis revealed that quercetin was associated with all targets and that NCOA2 was targeted by four ingredients. Besides, interleukin 6 had the highest degree value in the PPI network, indicating a hub role. A subsequent gene enrichment analysis yielded 86 significant GO terms and 89 significant pathways, implying that S. nigrum had therapeutic benefits in BC through multi-pathway effects, including the HIF-1, TNF, P53, MAPK, PI3K/Akt, apoptosis and bladder cancer pathway.

Conclusions
S. nigrum may mediate pharmacological effects in BC through multi-target and various signaling pathways. Further validation is required experimentally. Network pharmacology approach provides a predicative novel strategy to reveal the holistic mechanism of action of herbs.
Fetal birthweight prediction with measured data by a temporal machine learning method
Authors: Tao Jing , Yuan Zhenming , Sun Li , Yu Kai , Zhang Zhifen 
Published: January 2021

AbstractBackgroundBirthweight is an important indicator during the fetal development process to protect the maternal and infant safety. However, birthweight is difficult to be directly measured, and is usually roughly estimated by the empirical formulas according to the experience of the doctors in clinical practice.MethodsThis study attempts to combine multiple electronic medical records with the B-ultrasonic examination of pregnant women to construct a hybrid birth weight predicting classifier based on long short-term memory (LSTM) networks. The clinical data were collected from 5,759 Chinese pregnant women who have given birth, with more than 57,000 obstetric electronic medical records. We evaluated the prediction by the mean relative error (MRE) and the accuracy rate of different machine learning classifiers at different predicting periods for first delivery and multiple deliveries. Additionally, we evaluated the classification accuracies of different classifiers respectively for the Small-for-Gestational-age (SGA), Large-for-Gestational-Age (LGA) and Appropriate-for-Gestational-Age (AGA) groups.ResultsThe results show that the accuracy rate of the prediction model using Convolutional Neuron Networks (CNN), Random Forest (RF), Linear-Regression, Support Vector Regression (SVR), Back Propagation Neural Network(BPNN), and the proposed hybrid-LSTM at the 40th pregnancy week for first delivery were 0.498, 0.662, 0.670, 0.680, 0.705 and 0.793, respectively. Among the groups of less than 39th pregnancy week, the 39th pregnancy week and more than 40th week, the hybrid-LSTM model obtained the best accuracy and almost the least MRE compared with those of machine learning models. Not surprisingly, all the machine learning models performed better than the empirical formula. In the SGA, LGA and AGA group experiments, the average accuracy by the empirical formula, logistic regression (LR), BPNN, CNN, RF and Hybrid-LSTM were 0.780, 0.855, 0.890, 0.906, 0.916 and 0.933, respectively.ConclusionsThe results of this study are helpful for the birthweight prediction and development of guidelines for clinical delivery treatments. It is also useful for the implementation of a decision support system using the temporal machine learning prediction model, as it can assist the clinicians to make correct decisions during the obstetric examinations and remind pregnant women to manage their weight.
C3 glomerulonephritis along with light chain proximal tubulopathy without crystal deposits in multiple myeloma: a case report
Authors: Xu Junhui , Yu Xiaojuan , Wang Suxia , Yan Miao , Wang Mangju , Ou Jinping , Wang Lihong , Liu Huihui , Cen Xinan 
Published: January 2021

AbstractBackgroundMultiple myeloma causes different types of renal injury. C3 glomerulonephritis (C3GN) is characterised by an abnormal deposition of complement C3 in the glomeruli due to abnormal activation of the alternative pathway of the complement system. While the association between C3GN and multiple myeloma has been well established, mild renal injury by C3GN in multiple myeloma patients with high levels of light chain has not been reported.Case presentationA 55-year-old Chinese man presented with proteinuria. Combined with immunofixation electrophoresis, bone marrow biopsy, and renal biopsy, he was diagnosed with IgA-type multiple myeloma accompanied by C3GN and light chain proximal tubulopathy without crystal deposits. Although he had a higher level of lambda serum-free light chain, the renal injury in this patient was mild. After treatment with four courses of BD, one course of PAD, and autologous stem cell transplantation, he achieved a very good partial hematologic response with stable renal function.ConclusionsIn multiple myeloma, the light chain reaches a certain level and persists, resulting in C3GN renal impairment. Early diagnosis and early intensive treatment are critical for the prognosis of such patients.
Efficacy and safety of berberine for dyslipidemia: study protocol for a randomized double-blind placebo-controlled trial
Authors: Zhao Ying , Yang Yuan-Yuan , Yang Bao-Lin , Du Ya-Wei , Ren Da-Wei , Zhou Hong-Mei , Wang Jing , Yang Hui-Min , Wang Yao-Xian , Zhang Ying-Ying , Wu Sheng-Xian 
Published: January 2021

Abstract
Background
Dyslipidemia is a major risk factor for atherosclerotic cardiovascular disease and a leading cause of death worldwide. The clinical utility of commonly used lipid-lowering drugs such as statins and fibrates is sometimes limited by the occurrence of various adverse reactions. Recently, berberine (BBR) has received increasing attention as a safer and more cost-effective option to manage dyslipidemia. Thus, a high-quality randomized controlled trial to evaluate the efficacy and safety of BBR in the treatment of dyslipidemia is deemed necessary.

Methods/design
This is a randomized, double-blind, and placebo-controlled clinical trial. A total of 118 patients with dyslipidemia will be enrolled in this study and randomized into two groups at a ratio of 1:1. BBR or placebo will be taken orally for 12 weeks. The primary outcome is the percentage of low-density lipoprotein cholesterol reduction at week 12. Other outcome measures include changes in other lipid profiles, high sensitivity C-reactive protein, blood pressure, body weight, Bristol Stool Chart, traditional Chinese medicine symptom form, adipokine profiles, and metagenomics of intestinal microbiota. Safety assessment includes general physical examination, blood and urine routine test, liver and kidney function test, and adverse events.

Discussion
This trial may provide high-quality evidence on the efficacy and safety of BBR for dyslipidemia. Importantly, the findings of this trial will help to identify patient and disease characteristics that may predict favorable outcomes of treatment with BBR and optimize its indication for clinical use.

Trial registration
Chinese Clinical Trial Registry ChiCTR1900021361. Registered on 17 February 2019.
Volatile concentrate from the neotropical moss Neckeropsis undulata (Hedw.) Reichardt, existing in the brazilian Amazon
Authors: Miranda Thyago G. , Alves Raynon Joel M. , de Souza Ronilson F. , Maia José Guilherme S. , Figueiredo Pablo Luis B. , Tavares-Martins Ana Cláudia C. 
Published: January 2021

Abstract
Background
Many natural compounds have been identified and synthesized by the advancement of bryophytes phytochemistry studies. This work aimed to report the composition of Neckeropsis undulata (Hedw.) Reichardt moss volatiles, sampled in the Combú Island, Belém city, Pará state, Brazil. The volatile concentrate of N. undulata was obtained by a simultaneous distillation-extraction micro-system, analyzed by GC and GC-MS, and reported for the first time.

Results
Ten compounds were identified in the volatile concentrate, corresponding to 91.6% of the total, being 1-octen-3-ol (35.7%), α-muurolol (21.4%), naphthalene (11.3%), and n-hexanal (10.0 %) the main constituents. Most of the constituents of the N. undulata volatile concentrate have been previously identified in other mosses, and liverworts spread wide in the world.

Conclusions
1-Octen-3-ol, n-hexanal, 2-ethylhexanol, isoamyl propionate, and octan-3-one are already known metabolic products obtained from enzymatic oxidation of polyunsaturated fatty acids, belonging to the large family of minor oxygenated compounds known as oxylipins. The knowledge of the composition of volatiles from moss N. undulata could contribute to the Neckeraceae species’ chemotaxonomy.
CAMK2N1/RUNX3 methylation is an independent prognostic biomarker for progression-free and overall survival of platinum-sensitive epithelial ovarian cancer patients
Authors: Heinze Karolin , Rengsberger Matthias , Gajda Mieczyslaw , Jansen Lars , Osmers Linea , Oliveira-Ferrer Leticia , Schmalfeldt Barbara , Dürst Matthias , Häfner Norman , Runnebaum Ingo B. 
Published: January 2021

Abstract
Background
To date, no predictive or prognostic molecular biomarkers except BRCA mutations are clinically established for epithelial ovarian cancer (EOC) despite being the deadliest gynecological malignancy. Aim of this biomarker study was the analysis of DNA methylation biomarkers for their prognostic value independent from clinical variables in a heterogeneous cohort of 203 EOC patients from two university medical centers.

Results
The marker combination CAMK2N1/RUNX3 exhibited a significant prognostic value for progression-free (PFS) and overall survival (OS) of sporadic platinum-sensitive EOC (n = 188) both in univariate Kaplan–Meier (LogRank p < 0.05) and multivariate Cox regression analysis (p < 0.05; hazard ratio HR = 1.587). KRT86 methylation showed a prognostic value only in univariate analysis because of an association with FIGO staging (Fisher’s exact test p < 0.01). Thus, it may represent a marker for EOC staging. Dichotomous prognostic values were observed for KATNAL2 methylation depending on BRCA aberrations. KATNAL2 methylation exhibited a negative prognostic value for PFS in sporadic EOC patients without BRCA1 methylation (HR 1.591, p = 0.012) but positive prognostic value in sporadic EOC with BRCA1 methylation (HR 0.332, p = 0.04) or BRCA-mutated EOC (HR 0.620, n.s.).

Conclusion
The retrospective analysis of 188 sporadic platinum-sensitive EOC proved an independent prognostic value of the methylation marker combination CAMK2N1/RUNX3 for PFS and OS. If validated prospectively this combination may identify EOC patients with worse prognosis after standard therapy potentially benefiting from intensive follow-up, maintenance therapies or inclusion in therapeutic studies. The dichotomous prognostic value of KATNAL2 should be validated in larger sample sets of EOC.
CAR T cells in solid tumors: challenges and opportunities
Authors: Marofi Faroogh , Motavalli Roza , Safonov Vladimir A. , Thangavelu Lakshmi , Yumashev Alexei Valerievich , Alexander Markov , Shomali Navid , Chartrand Max Stanley , Pathak Yashwant , Jarahian Mostafa , Izadi Sepideh , Hassanzadeh Ali , Shirafkan Naghmeh , Tahmasebi Safa , Khiavi Farhad Motavalli 
Published: January 2021

Abstract
Background
CARs are simulated receptors containing an extracellular single-chain variable fragment (scFv), a transmembrane domain, as well as an intracellular region of immunoreceptor tyrosine-based activation motifs (ITAMs) in association with a co-stimulatory signal.

Main body
Chimeric antigen receptor (CAR) T cells are genetically engineered T cells to express a receptor for the recognition of the particular surface marker that has given rise to advances in the treatment of blood disorders. The CAR T cells obtain supra-physiological properties and conduct as “living drugs” presenting both immediate and steady effects after expression in T cells surface. But, their efficacy in solid tumor treatment has not yet been supported. The pivotal challenges in the field of solid tumor CAR T cell therapy can be summarized in three major parts: recognition, trafficking, and surviving in the tumor. On the other hand, the immunosuppressive tumor microenvironment (TME) interferes with T cell activity in terms of differentiation and exhaustion, and as a result of the combined use of CARs and checkpoint blockade, as well as the suppression of other inhibitor factors in the microenvironment, very promising results were obtained from the reduction of T cell exhaustion.

Conclusion
Nowadays, identifying and defeating the mechanisms associated with CAR T cell dysfunction is crucial to establish CAR T cells that can proliferate and lyse tumor cells severely. In this review, we discuss the CAR signaling and efficacy T in solid tumors and evaluate the most significant barriers in this process and describe the most novel therapeutic methods aiming to the acquirement of the promising therapeutic outcome in non-hematologic malignancies.
The delivery of hsa-miR-11401 by extracellular vesicles can relieve doxorubicin-induced mesenchymal stem cell apoptosis
Authors: Li Huifang , Huang Haoyan , Chen Xiaoniao , Chen Shang , Yu Lu , Wang Chen , Liu Yue , Zhang Kaiyue , Wu Lingling , Han Zhong-Chao , Liu Na , Wu Jie , Li Zongjin 
Published: January 2021

Abstract
Background
Chemotherapy is an effective anti-tumor treatment. Mesenchymal stem cells (MSCs), exerting therapy effect on injured tissues during chemotherapy, may be damaged in the process. The possibility of self-healing through long-range paracrine and the mechanisms are unclear.

Methods
Doxorubicin, a commonly used chemotherapy drug, was to treat human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) for 6 h as an in vitro cell model of chemotherapy-induced damage. Then we use extracellular vesicles derived from placental mesenchymal stem cells (hP-MSCs) to investigate the therapeutic potential of MSCs-EVs for chemotherapy injury. The mechanism was explored using microRNA sequencing.

Results
MSC-derived extracellular vesicles significantly alleviated the chemotherapy-induced apoptosis. Using microRNA sequencing, we identified hsa-miR-11401, which was downregulated in the Dox group but upregulated in the EV group. The upregulation of hsa-miR-11401 reduced the expression of SCOTIN, thereby inhibiting p53-dependent cell apoptosis.

Conclusions
Hsa-miR-11401 expressed by MSCs can be transported to chemotherapy-damaged cells by EVs, reducing the high expression of SCOTIN in damaged cells, thereby inhibiting SCOTIN-mediated apoptosis.
Screening of Potential Stress Biomarkers in Sweat Associated with Sports Training
Authors: Nunes Maria João , Cordas Cristina M. , Moura José J. G. , Noronha João Paulo , Branco Luís Cobra 
Published: January 2021

Abstract
Background
Intense and continuous physical training in sports is related with psychological and physiological stress, affecting the health and well-being of athletes. The development of non-invasive sampling methodologies is essential to consider sweat as a potential biological fluid for stress biomarker assessment. In the current work, the identification in sweat samples of potential molecules that may be used as stress biomarkers was pursued.

Methods
A sweat pool sample from football players after a 90-min intense training game was studied.

Results
An analysis method using liquid chromatography with detection by tandem mass spectrometry (LC-MSMS) to attain a screening profile of sweat composition is presented. The major focus was on neurotransmitters (e.g. monoamines and metabolites) and other biological molecules related with physical training, such as precursors of biogenic amines (phenylaniline, tyrosine, etc.).

Conclusions
This study allowed the identification of small biomolecules, neurotransmitters and other related molecules in sweat that are potentially associated with stress conditions. The developed methodology intends to contribute to the assessment and study of physical and psychological stress biomarkers related with intense sports using non-invasive methods.
Energy storage system design for large-scale solar PV in Malaysia: techno-economic analysis
Authors: Laajimi Mahmoud , Go Yun Ii 
Published: January 2021

AbstractLarge-scale solar is a non-reversible trend in the energy mix of Malaysia. Due to the mismatch between the peak of solar energy generation and the peak demand, energy storage projects are essential and crucial to optimize the use of this renewable resource. Although the technical and environmental benefits of such transition have been examined, the profitability of energy storage systems combined with large-scale solar PV has not been studied in Malaysia. This project aims to determine the most profitable business model of power systems, in terms of PV installed capacity, and energy storage capacity, and power system components. A comparative study has been done to compare the economic outcomes from different types of projects, with different scales and multiple configurations of large-scale solar PV combined with energy storage. The lowest values of LCOE are guaranteed with energy storage output to LSS output ratio, A = 5%. In this case, 30-MW projects have the cheapest electricity, equal to RM 0.2484/kWh. On the other hand, increasing the energy storage output to LSS output ratio, A to 60% results in the increase of LCOE, exceeding RM 0.47/kWh. On the economical side, with a difference of 0.06 kWh/m2/day for the analysis carried out in Pahang and Perak, the difference in net present worth is more than 7.5% of the net present cost. The difference between the two locations is comparatively higher for 50-MW projects. It is equal to RM 11.67 Million for A = 60%, while it is equal to RM 13.5 Million with A = 5%. Due to the energy prices in Malaysia, the projects that include large-scale solar only are more profitable technically and financially than those including large-scale solar and energy storage. It is found that adding storage to a large-scale solar project is more profitable technically and financially with greater large-scale solar capacities and smaller storage capacities. Nevertheless, with the current energy prices in Malaysia, projects that include only energy storage are not financially profitable. This study determined the parameters that affect the profitability of large-scale solar energy projects and energy storage projects, and the configurations that maximize financial profits. The findings of this study are useful for the future regulations that intend to enhance the deployment of large-scale solar PV and energy storage in Malaysia.
QTL mapping of agronomic and economic traits for four F2 populations of upland cotton
Authors: LI Hongge , PAN Zhaoe , HE Shoupu , JIA Yinhua , GENG Xiaoli , CHEN Baojun , WANG Liru , PANG Baoyin , DU Xiongming 
Published: January 2021

Abstract
Background
Upland cotton (Gossypium hirsutum) accounts for more than 90% of the annual world cotton output because of its high yield potential. However, yield and fiber quality traits often show negative correlations. We constructed four F2 populations of upland cotton, using two normal lines (4133B and SGK9708) with high yield potential but moderate fiber quality and two introgression lines (Suyuan04–3 and J02–247) with superior fiber quality, and used them to investigate the genetic basis underlying complex traits such as yield and fiber quality in upland cotton. We also phenotyped eight agronomic and economic traits and mapped quantitative trait loci (QTLs).

Results
Extensive phenotype variations and transgressive segregation were found across the segregation populations. We constructed four genetic maps of 585.97 centiMorgan (cM), 752.45 cM, 752.45 cM, and 1 163.66 cM, one for each of the four F2 populations. Fifty QTLs were identified across the four populations (7 for plant height, 27 for fiber quality and 16 for yield). The same QTLs were identified in different populations, including qBW4 and qBW2, which were linked to a common simple sequence repeat (SSR) marker, NAU1255. A QTL cluster containing eight QTLs for six different traits was characterized on linkage group 9 of the 4133B × Suyuan04–3 population.

Conclusions
These findings will provide insights into the genetic basis of simultaneous improvement of yield and fiber quality in upland cotton breeding.
Can microRNA become next-generation tools in molecular diagnostics and therapeutics? A systematic review
Authors: Saini Vandana , Dawar Rajni , Suneja Shilpa , Gangopadhyay Sukanya , Kaur Charanjeet 
Published: January 2021

AbstractBackgroundMicroRNAs (miRNAs) represent a novel class of single-stranded RNA molecules of 18–22 nucleotides that serve as powerful tools in the regulation of gene expression. They are important regulatory molecules in several biological processes.Main bodyAlteration in the expression profiles of miRNAs have been found in several diseases. It is anticipated that miRNA expression profiling can become a novel diagnostic tool in the future.Hence, this review evaluates the implications of miRNAs in various diseases and the recent advances in miRNA expression level detection and their target identification. A systematic approach to review existing literature available on databases such as Medline, PubMed, and EMBASE was conducted to have a better understanding of mechanisms mediating miRNA-dependent gene regulation and their role as diagnostic markers and therapeutic agents.ConclusionA clear understanding of the complex multilevel regulation of miRNA expression is a prerequisite to explicate the origin of a wide variety of diseases. It is understandable that miRNAs offer potential targets both in diagnostics and therapeutics of a multitude of diseases. The inclusion of specific miRNA expression profiles as biomarkers may lead to crucial advancements in facilitating disease diagnosis and classification, monitoring its prognosis, and treatment. However, standardization of methods has a pivotal role in the success of extensive use of miRNA expression profiling in routine clinical settings.