bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hematopoietic stem cell-derived fibrocytes as targets and tools for cancer therapy: mechanisms and therapeutic implications
Authors: Zhang Liyi , Qiu Haibo , Zhang Xu , Qi Jiali , Zhang Jiangwen , Tong Yin , Li Lei , Fu Li , Qin Yan-Ru , Guan Xinyuan 
Published: March 2022

Abstract
Background: Cancer-associated fibroblast (CAF) is an ideal target for cancer treatment. Recent studies have focused on eliminating CAFs and their effects by targeting their markers or blocking individual CAF-secreted factors. However, these strategies have been limited by their specificity for targeting CAFs and effectiveness in blocking widespread influence of CAFs. Here, we aimed to explore the molecular mechanisms of CAF generation and optimize CAF-targeted therapeutic strategies.Methods: Using FGFR2 as a tracing marker, we identified a novel origin of CAFs in esophageal squamous cell carcinoma (ESCC). Furthermore, we successfully isolated CAF precursors from peripheral blood of ESCC patients and explored the mechanisms underlying their expansion, recruitment and differentiation via RNA-sequencing and bioinformatics analysis.Results: We found that FGFR2+ hematopoietic stem cell (HSC)-derived fibrocytes could be induced by ESCC cells, homing into tumor xenografts, and differentiate into functional CAFs. They could be mobilized by cancer-secreted FGF2 and recruited into tumor sites via the CXCL12/CXCR4 axis. Moreover, they differentiate into CAFs through the activation of YAP-TEAD complex which is trigger by directly contract with tumor cells. FGF2 and CXCR4 neutralizing antibodies could effectively block the mobilization and recruitment process of FGFR2+ CAFs. The YAP-TEAD complex-based mechanism can be used to locally activate the production of genetically encoded therapeutic payloads in tumor sites.Conclusion: We identified a novel CAF origin and systematically studied the process of mobilization, recruitment, and maturation of CAFs in ESCC under the guidance of tumor cells. These findings give rise to new approaches that target CAFs before their incorporation into tumor stroma and use CAF- precursors as cellular vehicles to target cancer cells.
Improving Infinium MethylationEPIC data processing: focus on enhancers and long noncoding RNA genes
Authors: Jeschke Jana , Bizet Martin , Defrance Matthieu , Calonne Emilie , Bontempi Gianluca , Sotiriou Christos , Fuks François 
Published: March 2022

Abstract
BackgroundIllumina Infinium DNA Methylation (5mC) profiling arrays are a popular technology for low-cost, high-throughput, genome-scale measurement of 5mC distribution, especially in cancer and other complex diseases. After the success of its HumanMethylation450 array (450k), Illumina released the MethylationEPIC array (850k) featuring, in addition to the regulatory regions primarily covered by 450k (promoters, gene bodies), increased coverage of enhancers. Despite the widespread use of 850k, analysis of the corresponding data remains suboptimal: it still relies mostly on Illumina’s default annotation, which underestimates enhancers and long noncoding RNAs. ResultsWe have thus developed an approach, based on the ENCODE and LNCipedia databases, which greatly improves upon Illumina’s default annotation of enhancers and long noncoding transcripts. We then compared the re-annotated 850k with both 450k and reduced-representation bisulfite sequencing (RRBS), another high-throughput 5mC profiling technology. We found 850k to cover at least three times as many enhancers and long noncoding RNAs as either 450k or RRBS. We further investigated the reproducibility of the three technologies, applying various normalisation methods to the 850k data. Most of these methods reduced variability to a level below that of RRBS data. We then used 850k with our new annotation and normalisation to profile 5mC changes in breast cancer biopsies. 850k highlighted aberrant enhancer methylation as the predominant feature, in agreement with previous reports.ConclusionOur study provides an updated processing approach for 850k data, based on refined probe annotation and normalisation and allowing improved analysis of methylation at enhancers and long noncoding RNA genes. Overall, our findings will help to further advance understanding of the DNA methylome in health and disease.
Barriers in Implementation of Circular Economy Approach with the Consumption of Oilfield Produced Water
Authors: Attaran Mohsen , Sarma Sumita , Attaran Sharmin 
Published: March 2022

Abstract
A circular economy approach within wastewater consumption for agriculture has gained relevance in recent years. Extreme climate conditions (e.g., megadrought in California) have resulted in severe water shortages, yet there seems to be a reluctance to accept alternative water sources. Despite the numerous local initiatives towards oilfield water reuse, barriers remain to its implementation in practice. This study identifies the barriers towards widespread adoption of Oilfield Produced Water (OPW) for crop irrigation. Semi-structured interviews were conducted with five major stakeholder groups of the OPW: oil and gas managers/ business owners, farmers, entrepreneurs, water district managers, and water board personnel. This study used qualitative data analysis to identify factors influencing the beneficial uses and barriers to reusing OPW. The findings highlighted three macro-categories: water shortages, costs of treatment Vs. the expected benefits, and public perceptions vs. scientific studies based on thematic relevance and coherence. The interviews revealed the need for a tighter collaboration among the various stakeholder groups in this ecosystem that involves public-private partnerships and shared governance in managing the environment—addressing these barriers aids the development of a circular economy for wastewater.
Binary classifiers for noisy datasets: a comparative study of existing quantum machine learning frameworks and some new approaches
Authors: Schetakis N. , Aghamalyan D. , Griffin P. , Boguslavsky M. 
Published: March 2022

Abstract
One of the most promising areas of research to obtain practical advantage is Quantum Machine Learning which was born as a result of cross-fertilisation of ideas between Quantum Computing and Classical Machine Learning. In this paper, we apply Quantum Machine Learning (QML) frameworks to improve binary classification models for noisy datasets which are prevalent in financial datasets. The metric we use for assessing the performance of our quantum classifiers is the area under the receiver operating characteristic curve (ROC/AUC). By combining such approaches as hybrid-neural networks, parametric circuits, and data re-uploading we create QML inspired architectures and utilise them for the classification of non-convex 2 and 3-dimensional figures. An extensive benchmarking of our new FULL HYBRID classifiers against existing quantum and classical classifier models, reveals that our novel models exhibit better learning characteristics to asymmetrical Gaussian noise in the dataset compared to known quantum classifiers and performs equally well for existing classical classifiers, with a slight improvement over classical results in the region of the high noise.
Primary Malignant Brain Tumor Trends in Southern Iran, 2001- 2017: an alarming increase in glioblastoma
Authors: Ahrari Iman , Soltani Ahmad , Eqbal Meisam , Owji Seyed Hossein , Amin Amir Mousaie , Khosravizadegan Zahra , Rezaianzadeh Abbas , Shahraki Hadi Raeisi 
Published: March 2022

Abstract
Introduction: Primary Brain tumors which include a 1.7 percent of all cancers among which glioblastomas are the most lethal and the most frequent malignant types. Ionizing radiation and some genetic factors have been reported as the etiology of such cancers. We are reporting the trends in the Brain tumors with a focus on malignant types and its outcome in the South of the Iran for the first time.Methods: We selected all the patients with primary brain tumors who undergone brain surgery at teaching hospitals the Shiraz Medical School between 2001 and 2017. Data was obtained from Fars Population-based Cancer Registry. ICD-O-3 morphology coding system according to WHO 2007 classification of CNS tumors was used for grouping the tumors. Using SPSS, Total Growth Rate (TGR) and Incidence Rate (IR) were calculated to assess the changes overtime.Results: A total number of 2130 (male: 890, 41.8% and female: 1240, 58.2%) brain tumor cases from 2001 to 2017 were included in this study. The highest Incidence Rate (IR) was found in ‘unspecified tumors of the brain’ (2.74 per 100000) between 2011 and 2015 followed by ‘Astrocytoma’ (1.34 per 100000) between 2006 and 2010) and ‘Glioblastoma’ (1.25 per 100000) between years 2011 and 2016. Additionally, the Glioblastoma showed the highest IR in those aged between 30 and 59 of years (0.42 per 100000). Conclusion: An upward trend in the rate of malignant brain tumors in the Fars province could be an alarm sign for more studies to be done especially from the etiology point of view.
Automatic Classification of Real-Time Diseased Cotton Leaves and Plants Using a Deep-Convolutional Neural Network
Authors: Rai Chitranjan Kumar 
Published: March 2022

Abstract
The automated detection and classification of plant diseases based on images of leaves is a significant milestone in agriculture. In this paper, the concept of deep learning was used to identify and predict cotton plant disease status using real-time images of leaves and plants. The models were trained using a database of 2293 images of cotton leaves and plants. The data included four distinct classes of leaves, plants disease combinations, and their respective categories. Python version 3.6.9 is used to implement the developed model. The model includes a deep learning package such as Keras, TensorFlow, and a Googlecolab cloud-based jupyter notebook as the development environment. For classifying leaves and plant diseases in cotton plants, our model attained an accuracy of 97.98%. The proposed technique outperformed the recent approaches indicated in earlier literature for relevant parameters. As a result, the technique is intended to reduce the time spent identifying cotton leaf disease in significant production regions and human error and time spent determining its severity.
Overweight Effects on Metabolic Rate, Chronic Diseases, Time Perception, Aging, and Lifespan: a Systematic Review
Authors: Oshakbayev Kuat , Bedelbayeva Gulnara , Gazaliyeva Meruyert , Dukenbayeva Bibazhar , Tordai Attila , Sabir Abdul Rakhimi 
Published: March 2022

Abstract
Background: The hypothesis that metabolic rate is inversely correlated with lifespan has long been debating. Another area of controversy is an evidence of a relationship between metabolic rate (MR) and time-flow perception (TFP), and aging. Aim: to study the impact of overweight and food intake on MR, TFP, chronic diseases, aging, lifespan; difficulties in weight loss.Methods. Design: a systematic review. Settings: Web of Science, Scopus, Science Direct, Kopernio, PubMed, Mendeley were searched for articles published from January 1979 until February 2022. The study bases on a viewpoint supported by a systematic literature review of 3612 articles published worldwide.Results: In total, 107 full-text articles were assessed for eligibility. From them, 22 articles were excluded with reasons. Overweight and overeating accelerate MR, leading to hyper-metabolic mode of the body. MR and lifespan are inversely correlated. TFP depends on MR; accelerated MR leads to deceleration of TFP. Every person has an individual ability to gain weight up to 'maximum bodyweight', which indicates the individual potential energy to weight gain. Overweight excessively consumes the body ‘vital energy’, is a soil to grow diseases; devours body potential energy. Weightloss creates ‘body power to weight gain’ that increases physical/mental activity, recovering from diseases, or weight regain. The body needs less calorie intake due to the decrease in MR by age. For weight loss should use very-low-calorie diets and manage metabolic intoxication.Conclusions: Our findings support that overweight and overeating increase metabolic rate, which delays time-flow perception, accelerates aging, limits lifespan. For weight loss should manage very-low-calorie diets.
Chronic Stress Disrupts the Homeostasis and Progeny Progression of Oligodendroglial Lineage Cells, Associating Immune Oligodendrocytes With Prefrontal Cortex Hypomyelination
Authors: Tsirka Stella , Kokkosis Alexandros , Madeira Miguel , Mullahy Matthew 
Published: March 2022

Abstract
Major Depressive Disorder (MDD) is a chronic debilitating illness affecting yearly 300 million people worldwide. Oligodendrocyte-lineage cells have emerged as important neuromodulators in synaptic plasticity and crucial components of MDD pathophysiology. Using the repeated social defeat (RSDS) mouse model, we demonstrate that chronic psychosocial stress induces long-lasting losses and transient proliferation of oligodendrocyte-precursor cells (OPCs), aberrant differentiation into oligodendrocytes, and severe hypomyelination in the prefrontal cortex. Exposure to chronic stress results in OPC morphological impairments, excessive oxidative stress, and oligodendroglial apoptosis, implicating integrative-stress responses in depression. Analysis of single-nucleus transcriptomic data from MDD patients revealed oligodendroglial-lineage dysregulation and the presence of immune-oligodendrocytes (Im-OL), a novel population of cells with immune properties and myelination deficits. Im-OL were also identified in mice after RSDS, where oligodendrocyte-lineage cells expressed immune-related markers. Our findings demonstrate cellular and molecular changes in the oligodendroglial lineage in response to chronic stress and associate hypomyelination with Im-OL emergence during depression.
The origin of the period-$2T/7$ quasi-breathing in disk-shaped Gross-Pitaevskii breathers
Authors: Torrents Jordi , Dunjko Vanja , Gonchenko Marina , Astrakharchik Gregory , Olshanii Maxim 
Published: March 2022

We address the origins of the quasi-periodic breathing observed in
[Phys. Rev. X vol. 9, 021035 (2019)] in disk-shaped harmonically trapped
two-dimensional Bose condensates, where the quasi-period
T_{\text{quasi-breathing}}\simTquasi-breathing∼~2T/72T/7
and TT
is the period of the harmonic trap. We show that, due to an unexplained
coincidence, the first instance of the collapse of the hydrodynamic
description, at t^{*} = \arctan(\sqrt{2})/(2\pi) T \approx T/7t*=arctan(2)/(2π)T≈T/7,
emerges as a `skillful impostor’ of the quasi-breathing half-period
T_{\text{quasi-breathing}}/2Tquasi-breathing/2.
At the time t^{*}t*,
the velocity field almost vanishes, supporting the requisite
time-reversal invariance. We find that this phenomenon persists for
scale-invariant gases in all spatial dimensions, being exact in one
dimension and, likely, approximate in all others. In
\bm{d}𝐝
dimensions, the quasi-breathing half-period assumes the form
T_{\text{quasi-breathing}}/2 \equiv t^{*} = \arctan(\sqrt{d})/(2\pi) TTquasi-breathing/2≡t*=arctan(d)/(2π)T.
Remaining unresolved is the origin of the
period-2T2T
breathing, reported in the same experiment.
Green infrastructure and climate change impacts on the flows and water quality of urban catchments: Salmons Brook and Pymmes Brook in north-east London
Authors: Bussi Gianbattista , Whitehead Paul G. , Nelson Rosie , Bryden John , Jackson Christopher R. , Hughes Andrew G. , Butler Adrian P. , Landström Catharina , Peters Helge , Dadson Simon , Russell Ian 
Published: March 2022

Abstract
Poor water quality is a widespread issue in urban rivers and streams in London. Localised pollution can have impacts on local communities, from health issues to environmental degradation and restricted recreational use of water. The Salmons and Pymmes Brooks, located in the London Borough of Enfield, flow into the River Lee, and in this paper, the impacts of misconnected sewers, urban runoff and atmospheric pollution have been evaluated. The first step towards finding a sustainable and effective solution to these issues is to identify sources and paths of pollutants and to understand their cycle through catchments and rivers. The INCA water quality model has been applied to the Salmons and Pymmes urban catchments in north-east London, with the aim of providing local communities and community action groups such as Thames21 with a tool they can use to assess the water quality issue. INCA is a process-based, dynamic flow and quality model, and so it can account for daily changes in temperature, flow, water velocity and residence time that all affect reaction kinetics and hence chemical flux. As INCA is process-based, a set of mitigation strategies have been evaluated including constructed wetland across the catchment to assess pollution control. The constructed wetlands can make a significant difference reducing sediment transport and improving nutrient control for nitrogen and phosphorus. The results of this paper show that a substantial reduction in nitrate, ammonium and phosphorus concentrations can be achieved if a proper catchment-scale wetland implementation strategy is put in place. Furthermore, the paper shows how the nutrient reduction efficiency of the wetlands should not be affected by climate change.
How much does it cost to meet the standards for making healthcare facilities water, sanitation, and hygiene (WASH) compliant?: analysis from Assam, India
Authors: Bhavsar Priya , Kalpana Pachillu , Kaul Annapurna , Patnaik Sweta , Ryavanki Sridhar , Saha Somen , Saxena Deepak 
Published: March 2022

Abstract
Inadequate water, sanitation, and hygiene (WASH) standards in healthcare facilities (HCFs) pose a severe risk to those who seek treatment. In India, more than one in every four HCFs lack basic water services and only 55% of facilities have access to improved sanitation. The study aims to estimate the cost to meet the standards for making WASH compliant HCFs. This cross-sectional study was centered on assessing 60 selected HCFs of Assam. The assessment comprises four steps: in the first step, domains and sub-domains were identified; in the second step, gaps were analyzed for the selected domains; in the third step, the cost was estimated for the domains and sub-domains, and in the final step, costs were estimated to meet the standards. The findings show that the cost required for the improvement varied for different types of facilities. The total annual cost to make all the selected facilities WASH compliant was found to be USD 13,73,741. The majority (93.3%) of the cost is required for human resources. District hospitals would require significant investment, followed by the sub-divisional hospitals and first referral units. The least cost is required to improve the state dispensary.
Evaluation of the measurement performance of water meters depending on water quality
Authors: Kroner Corinna , Akselli Başak , Benková Miroslava , Borchling Alexander , Büker Oliver , Christoffersen Nikki , Pavlas Jan , Schumann Daniel , Seypka Veit , Ünsal Bülent , Warnecke Heiko 
Published: March 2022

Abstract
Water meters of different types and sizes are used to monitor and bill the water supply. Although the water is of drinking water quality, its chemo-physical properties often adversely affect the measuring behaviour of a meter after a while. There is thus the risk that they no longer meet legal requirements and may no longer be used. In this paper a test regime with a focus on pH, total hardness and particle load is presented which allows water meters to be tested closer to their operating conditions prior to placing them on the market. The regime goes beyond the conventional continuous durability test as described in OIML R49:2013(E) and ISO 4064:2014. The feasibility and reliability of the test regime has been demonstrated through implementation at different facilities. In the study, the measurement performance of water meters of various types and from different manufacturers was also investigated. A heterogeneous spread of measurement errors was found for both, water meters in mint conditions and those which were exposed to a defined water quality. Furthermore, compared to the conventional continuous durability test, the test regime developed in the study generally leads to stronger changes in the measurement error of the water meters.
Effect of Sodium Valproate on Weight, Body Mass Index, Uric Acid, Vitamin D3, Blood Insulin, and Serum Lipid Profile in Children
Authors: Vafaee-Shahi Mohammad , Soheilipour Fahimeh , Mohagheghi Parisa , Riahi Aina , Borghei Nafise-Sadat , Talebi Atefeh 
Published: March 2022

Introduction:
Due to the high prevalence of epilepsy and the use of sodium valproate as an antiepileptic drug by these patients, accurate recognition of its side effects and its effects on serum lipids profile, liver enzymes, uric acid level, and thyroid function tests, especially in cases that need long-term treatment seems essential. This study aimed to evaluate the effects of sodium valproate on weight, body mass index (BMI), vitamin D3, blood insulin, uric acid level, and serum lipids profile in children with newly diagnosed epilepsy.

Materials and Methods:
This prospective study was performed on 30 children between 3 and 8 years of age who suffered from newly diagnosed epilepsy and received sodium valproate as monotherapy. Data including demographic information (age, sex, height, weight, and waist and hip circumference of children), as well as clinical characteristics, such as liver enzymes (ALT, AST, ALK-P), serum lipids level (TG, TC, HDL-C, LDL-C), thyroid tests (TSH, T4), fasting blood sugar (FBS), uric acid level, 25 OH Vitamin D3 (Vit-D3), and blood insulin level of children before and six months after the consumption of sodium valproate, were examined.

Results:
The mean weight of children before and six months after the start of sodium valproate treatment was 18.54±2.99 and 21.13±3.93 (kg), respectively. This difference was statistically significant (P=0.005). Also, the mean weight Z-score of children before and after taking sodium valproate was -2.497 and -2.293, respectively, which was statistically significant too. In addition to weight gain, there was also a significant increase in the abdominal and hip circumference of children after taking valproate, whereas the increase in mean BMI before and after valproate administration was not statistically significant (P=0.114). However, mean weight gain, as well as the increase in the waist and hip circumference, had no relationship with gender (P> 0.05). Also, sodium valproate significantly increased the ALT level (P=0.046). Moreover, sodium valproate did not affect other liver function markers (AST), thyroid hormones (TSH, T4), fasting blood sugar (FBS), uric acid level, 25 OH Vit-D3, and the children's blood insulin levels (P> 0.05).

Conclusion:
According to the findings of this study, it can be concluded that sodium valproate is a good drug for children between 3 and 8 years of age, but it should be noted that taking this drug increases the chance of obesity in children. The main side effect of this drug is weight gain. Due to the significant increase in ALT enzyme, as observed in this study, it is recommended to check liver enzymes before, one, and six months after starting treatment as it can prevent the irreversible permanent side effects of this drug.