bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Determination of Timolol Maleate Using Silver/Tannic Acid/Titanium Oxide Nanocomposite as an Electrochemical Sensor in Real Samples
Authors: Mehmandoust Mohammad , Çakar Soner , Özacar Mahmut , Erk Nevin 
Published: December 2021

AbstractHerein, a portable and cost‐effective electrochemical sbased on Silver/tannic acid/titanium dioxide/glassy carbon electrode (Ag/TA@ TiO2/GCE) was fabricated to determine timolol(TM) assay. The Ag/TA@TiO2/GCE offered an irreversible oxidation peak at +0.99 V, and exhibited an extraordinary electrochemical performance with a wide linear working ranges from 0.01–0.84 and 0.84–49.0 μM and a low detection limit of 5.2 nM. The detection of TM in the presence of interfering agents and real samples was also analyzed. The sensor‘s selectivity was studied by comparing the binding of TM, propranolol, nebivolol, and metoprolol. The developed electrochemical sensing platform could have promising potential for the determination of TM in clinical samples.
Characterization of the Impact of Classical Cell‐culture Media on the Response of Electrochemical Sensors
Authors: Chmayssem Ayman , Petit Lauriane , Verplanck Nicolas , Mourier Véronique , Vignoud Séverine , Vrana Nihal Engin , Mailley Pascal 
Published: December 2021

AbstractBiocompatibility testing is usually performed through staining and imaging of cell lines. We propose here to monitor cytotoxicity through real‐time measurement of metabolites specifically issued from cell stress behaviour using a multiparametric electrochemical (bio)sensing platform. However, the composition of culture media varies widely according to the requirements of the utilized cell lines. This matter may have significant effects on the sensor's sensitivity. With this mind, the sensitivity of four electrochemical (bio)sensors (pH, hydrogen peroxide, nitric oxide/nitrite (NO and its by‐product) and lactate) is investigated in different cell culture media. The main culture media studied were Minimum Essential Medium Eagle (MEM), Dulbecco's Modified Eagle Medium (DMEM), Williams’ Medium E and RPMI 1640 medium that were the recommended culture media for the cell types to be monitored. This work shows the impact of the different cell culture media on the performances of the different sensors (limit of detection, sensitivity, selectivity, response time and dynamic range). More particularly, FBS strongly impacts the response of the amperometric (bio)sensors. Then, cellular viability testing was effected within optimized medium (FBS content) for electrochemical sensor read‐outs in the case of short‐term cultures (one day) devoted to cytotoxicity testing. Real‐time electrochemical monitoring provides important additional information about cell behaviour during biocompatibility testing that might be further implemented in different settings including pharmaceutical efficacy and biomaterials applications.
Advances in electrochemical detection methods for measuring contaminants of emerging concerns
Authors: Hassan Mohamed H. , Khan Reem , Andreescu Silvana 
Published: December 2021

AbstractThe presence of contaminants of emerging concerns (CECs) such as pharmaceuticals and personal care products, endocrine disrupting compounds (EDCs), per/poly‐fluorinated substances (PFAS), pesticides, and nanomaterials poses significant challenges to the environment and human health. This review discusses the current status of electrochemical sensing methods and their potential as low‐cost analytical platforms for the detection and characterization of emerging contaminants. Recent developments in advanced materials and fabrication techniques such as electrophoretic deposition, layer‐by‐layer deposition, roll‐to‐roll and 3D printing techniques, and the scalable manufacturing of low‐cost portable electrochemical devices are discussed. Examples of detection mechanisms, electrode modification procedures, device configuration, and their performance along with recent developments in fundamental electrochemistry, particularly nanoimpact methods, are provided to demonstrate the capabilities of these methods for the environmental monitoring of CECs. Finally, a critical discussion of future research needs, detection challenges, and opportunities is provided to demonstrate how electrochemistry can be used to advance field monitoring of these chemicals. These methods can be used as complementary or alternative methods to the currently used laboratory‐based analytical instrumentation to facilitate large‐scale studies and manage risks associated with the presence of CECs in the environment and other matrices.
Prediction of longwall mining‐induced stress in roof rock using LSTM neural network and transfer learning method
Authors: Qin Changkun , Zhao Wusheng , Zhong Kun , Chen Weizhong 
Published: December 2021

AbstractReal‐time monitoring of three‐dimensional stress in the field is an effective approach to detect evolving stress in roof rock and to evaluate rock bursts risk. However, the sensors or data transmission cables may be damaged due to the volatile environment found in coal mines, which can lead to the loss of relevant monitoring data, and some critical information for rock burst prediction may be missed entirely. A number of methods that use historical data to predict missing data or future structural states have been proposed. However, the performance of these methods is poor when the training data are insufficient owing to lack of data. To address this issue, a methodology framework is proposed to predict the mining‐induced stress when some monitoring data are missing. The framework uses a long short‐term memory neural network integrated with the transfer learning method. The proposed method can transfer the knowledge learned from complete monitored data of adjacent sensor to target sensor to boost forecasting. A case study has been conducted to evaluate the method. The results show that the developed model can significantly improve the prediction performance for the target domain, which can be improved further by increasing the size of the target domain training data available.
Performance enhancement with inorganic phase change materials for the application of thermal energy storage: A critical review
Authors: Kundu Rohan , Kar Satya Prakash , Sarangi Radhakanta 
Published: December 2021

AbstractIn the current energy crisis, energy saving becomes important to reduce the gap of supply and demand of energy. Phase change material (PCM) plays a bigger role to store energy due to its high latent of fusion. The present article provides an insight into the present developments in enhancing the performance of inorganic PCMs. In this article, a comprehensive review of different techniques like mixing of different salts, addition of nanoparticle, addition of nucleating agents, encapsulation methods and so on are discussed in detail. Special attention is given to know the enhancement in high thermal conductivity, large phase change enthalpy, high density, thermal stability, corrosion resistance and so on.
Mitochondria‐targeted nanoparticles in treatment of neurodegenerative diseases
Authors: Zhang Yue , Yang Han , Wei Daohe , Zhang Xinhui , Wang Jian , Wu Xiaoli , Chang Jin 
Published: December 2021

AbstractNeurodegenerative diseases (NDs) are a class of heterogeneous diseases that includes Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. Mitochondria play an important role in oxidative balance and metabolic activity of neurons; therefore, mitochondrial dysfunction is associated with NDs and mitochondria are considered a potential treatment target for NDs. Several obstacles, including the blood‐brain barrier (BBB) and cell/mitochondrial membranes, reduce the efficiency of drug entry into the target lesions. Therefore, a variety of neuron mitochondrial targeting strategies has been developed. Among them, nanotechnology‐based treatments show especially promising results. Owing to their adjustable size, appropriate charge, and lipophilic surface, nanoparticles (NPs) are the ideal theranostic system for crossing the BBB and targeting the neuronal mitochondria. In this review, we discussed the role of dysfunctional mitochondria in ND pathogenesis as well as the physiological barriers to various treatment strategies. We also reviewed the use and advantages of various NPs (including organic, inorganic, and biological membrane‐coated NPs) for the treatment and diagnosis of NDs. Finally, we summarized the evidence and possible use for the promising role of NP‐based theranostic systems in the treatment of mitochondrial dysfunction‐related NDs.
An adaptive mesh refinement‐multiphase lattice Boltzmann flux solver for three‐dimensional simulation of droplet collision
Authors: Yuan Hai‐Zhuan , Liu Qing , Zeng Gang 
Published: December 2021

AbstractA three‐dimensional adaptive mesh refinement‐multiphase lattice Boltzmann flux solver (3D‐AMR‐MLBFS) is developed for effectively simulating complex multiphase flows with large density ratio and high Reynolds number. In the method, the multiphase lattice Boltzmann flux solver (MLBFS) is used to solve the flow field and the level set method is adopted to capture the interface. In addition, a free energy‐based continuum surface tension force (FE‐CSF) model, which has a clear physical basis and does not need to introduce a regularization function, is applied to calculate the surface tension force. In order to improve the computational efficiency and at the same time ensure accuracy, the adaptive mesh refinement technology is introduced. This method is used to simulate three‐dimensional collision of two equal‐sized droplets for a wide range of parametric conditions. We not only verify the developed method by comparing with available literature data but also successfully reproduce four typical outcomes of droplet collision, namely coalescence, reflexive separation, stretching separation, and liquid membrane shattering, for which the evolutions of droplet morphologies and various energies are revealed.
Interaction between bacterial diversity and biogenic amines production in a salted mackerel stored at soft frozen (−7℃–0℃) storage
Authors: Tao Zhihua , Liu Weiqi , Hu Qinxia , Wu Xue , Xie Shuying , Zhang Hongmei , Fu Minghui , Yang Jing , Jiang Yan 
Published: December 2021

AbstractThe bacterial diversity of salted mackerel “one‐night courtyard” at soft frozen area (−7℃–0℃) storage was studied. The fish samples at 0, 14, 21, 28, and 35 days were analysis for bacterial structure using high‐throughput sequencing technologies (HTS) and biogenic amines using high‐performance liquid chromatography (HPLC). The analysis results of HTS showed that the dominant bacteria species was varied gradually following with storage time. On the 0th, 21st, and 28th days of storage, dominant Vibrionaceae was accounting for 71.70%, 59.16%, and 70.68% of the total sequences analyzed, respectively. On the 14th and 35th days, Shewanellaceae was the dominant bacterial, accounting for 87.53% and 70.95% of the total sequences analyzed, respectively. In addition, 21st and 28th days, an abundance of Operational Taxonomic Units (OTUs) was top. The dominant bacterial of Proteobacteria, Firmicutes, was producer of biogenic amines. Furthermore, the analysis results of HPLC shown the total biogenic amines of maximum amount 363.01 mg/kg in the sample of HY.14 lower than 1000 mg/kg of the FDA regulation. The range ability of cadaverine was obvious following with the storage time. Cadaverine was 87.36 mg/kg on the 0th day, and it was maximum amount of 276.89 mg/kg on the 14th days. Putrescine was 20 mg/kg on the 0th day and maximum amount of 55.04 mg/kg on the 28thdays of storage. The tyramine was smallest amount of production, and the largest amount was 38.99 mg/kg on 28th, and the smallest amount was 11.97 mg/kg on 35th. Nevertheless, the maximum amount of histamine was 55.04 mg/kg on the 0th day and about 23.14 mg/kg of histamine was little change from 14th to 35th days of storage. Dominant bacteria affect the change of biogenic amines. The study can help understand the interaction between microbial flora and biogenic amines in the salted mackerel of one‐night courtyard.
Transcriptome analysis reveals the contribution of oligodendrocyte and radial glia‐derived cues for maintenance of microglia identity
Authors: Timmerman Raissa , Zuiderwijk‐Sick Ella A. , Oosterhof Nynke , 't Jong Anke E. J. , Veth Jennifer , Burm Saskia M. , van Ham Tjakko J. , Bajramovic Jeffrey J. 
Published: December 2021

AbstractMicroglia are increasingly being recognized as druggable targets in neurodegenerative disorders, and good in vitro models are crucial to address cell biological questions. Major challenges are to recapitulate the complex microglial morphology and their in vivo transcriptome. We have therefore exposed primary microglia from adult rhesus macaques to a variety of different culture conditions including exposure to soluble factors as M‐CSF, IL‐34, and TGF‐β as well as serum replacement approaches, and compared their morphologies and transcriptomes to those of mature, homeostatic in vivo microglia. This enabled us to develop a new, partially serum‐free, monoculture protocol, that yields high numbers of ramified cells. We also demonstrate that exposure of adult microglia to M‐CSF or IL‐34 induces similar transcriptomes, and that exposure to TGF‐β has much less pronounced effects than it does on rodent microglia. However, regardless of culture conditions, the transcriptomes of in vitro and in vivo microglia remained substantially different. Analysis of differentially expressed genes inspired us to perform 3D‐spherical coculture experiments of microglia with oligodendrocytes and radial glia. In such spheres, microglia signature genes were strongly induced, even in the absence of neurons and astrocytes. These data reveal a novel role for oligodendrocyte and radial glia‐derived cues in the maintenance of microglial identity, providing new anchor points to study microglia in health and disease.
Machine learning can identify patients at risk of hyperparathyroidism without known calcium and intact parathyroid hormone
Authors: Greer Melody L. , Davis Kyle , Stack Brendan C. 
Published: December 2021

AbstractBackgroundTo prove the concept of diagnosing primary hyperparathyroidism (pHPT) without calcium and parathyroid hormone (PTH) values and identifying potential risk factors for pHPT.MethodsData were extracted from the clinical data warehouse (CDW) at the University of Arkansas for Medical Sciences (UAMS) Epic EHR (2014–2019).Results1737 patients with over 185 000 rows of clinical data were provided in a relational structure and processed/flattened to facilitate modeling. Phenotype elements were identified for pHPT without advance knowledge of calcium and PTH levels. The area under the curve (AUC) for the prediction of pHPT using our model was 0.86 with sensitivity and specificity of 0.8953 and 0.6686, respectively, using a 0.45 probability threshold.ConclusionPrimary hyperparathyroidism was predicted from a dataset excluding calcium and PTH data with 86% accuracy. This approach needs to be validated/refined on larger samples of data and plans are in place to do this with other regional/national datasets.
Acceptability of the Direct Health Facility Financing (DHFF) initiative in Tanzania: A mixed methods process evaluation of the moderating factors
Authors: Kalolo Albino , Kapologwe Ntuli A. , Samky Hendry , Kibusi Stephen M. 
Published: December 2021

AbstractDespite wide agreement that stakeholder acceptability plays a critical role in an intervention's effectiveness, gaps remain on understanding acceptability of complex health financing interventions. We aimed to understand the moderators of acceptability of the Direct Health Facility Financing (DHFF) initiative across primary health facilities in Tanzania. Employing a mixed methods approach and guided by the theoretical framework for acceptability (TFA), we collected data from implementers and their supervisors using a structured questionnaire and semi‐structured interview guides. We analysed data using a chi square test, logistic regression, and thematic analysis. We recruited 238 participants, of whom 71% were females and 54% were below 37 years old. Acceptability was found to be 63% and received high rating in qualitative interviews. Moderators of acceptability included sex (AOR = 1.93, p = 006), work experience (AOR = 3.47, p = 0.001), knowledge (13.8, p = 0.00), supportive work environment (AOR = 2.28, p = 0.019), and capability to implement the programme (AOR = 0.12, p = 0.00). Moderators reported in qualitative interviews related to individual and contextual factors. This study suggests that the DHFF initiative is acceptable and influenced by factors operating at the individual level and beyond. Addressing moderators of acceptability as programs are designed and implemented is the holy grail of acceptability of complex interventions.
Dupilumab may be an alternative option in the treatment of acquired reactive perforating collagenosis combined with AD
Authors: Ying Yang , Shuang Chen , Zhen‐Ying Zhang 
Published: December 2021

AbstractThe management of acquired reactive perforating collagenosis (ARPC) is challenging. Here, we shared two cases of ARPC combined with elderly atopic dermatitis (AD) that did not respond well to conventional treatment but responded well to the monotherapy of dupilumab, which suggests that dupilumab may be an alternative option for the treatment.
CR‐SSL: A closely related self‐supervised learning based approach for improving breast ultrasound tumor segmentation
Authors: Mishra Arnab Kumar , Roy Pinki , Bandyopadhyay Sivaji , Das Sujit Kumar 
Published: December 2021

AbstractBreast ultrasound (BUS) tumor segmentation can help with the early detection of breast cancer; however, the lack of human‐labeled training data is a big problem in this area. To deal with this, we propose a novel self‐supervised learning approach (CR‐SSL), where several related pretext tasks like unsupervised segmentation and edge detection are firstly learned, followed by the target tumor segmentation based fine‐tuning. Learning such related pretext tasks ensures better representation learning. Experimental study shows that CR‐SSL can improve the mean Dice and Jaccard scores by more than 4–5%, with ≥0.6 scores while having access to only 20–50 human‐labeled training samples. The best Dice scores of 0.7303 and 0.8207, and Jaccard scores of 0.7082 and 0.8015 are obtained by CR‐SSL on the test datasets. Compared with the No‐SSL baseline, CR‐SSL can achieve (10–20)% improvements in segmentation quality while working in small‐sized training dataset scenarios, suggesting its high potential practical utility.
Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk
Authors: Whittier Danielle E , Samelson Elizabeth J , Hannan Marian T , Burt Lauren A , Hanley David A , Biver Emmanuel , Szulc Pawel , Sornay-Rendu Elisabeth , Merle Blandine , Chapurlat Roland , Lespessailles Eric , Wong Andy Kin On , Goltzman David , Khosla Sundeep , Ferrari Serge , Bouxsein Mary L , Kiel Douglas P , Boyd Steven K 
Published: December 2021

ABSTRACT
Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p &lt; 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).
Dense fine speckled immunofluorescence pattern in a Chinese population: Prevalence and clinical association
Authors: Zhang Keyi , Su Zhenzhen , Hu Jing , Huang Zhuochun , Hu Chaojun , Yang Bin 
Published: December 2021

AbstractObjectiveTo provide information on the prevalence and possible clinical association in a Chinese population for medical practice of the dense fine speckled pattern (DFS pattern).MethodsA retrospective study was conducted with patients who had the DFS pattern from June 2018 to December 2019 in West China Hospital.ResultsA total of 469 patients (1.27% of patients with positive anti‐nuclear antibody indirect immunofluorescence (ANA IIF) test results) revealed the DFS pattern, of which 92.96% had isolated DFS pattern and 23.67% had titers above/equal to 1:320. The average age of patients with the DFS pattern was 43.45 years, and females accounted for 76.97% of them. Ten different kinds of diseases made up the vast majority of the disease spectrum, in which inflammatory or infectious diseases (46.11%), mental diseases (21.45%), and systemic autoimmune rheumatic diseases (SARDs) (18.23%) ranked in the top three. The most common SARDs were rheumatoid arthritis (RA), undifferentiated connective tissue disease (UCTD), and systemic lupus erythematosus (SLE). Forty‐six patients (10.55%) had positive or suspicious extractable nuclear antigen (ENA) antibodies test results and a higher risk of suffering from SARDs. Forty‐seven patients would be missed if the DFS pattern with negative ENA antibodies test result was considered as exclusion criterion of SARDs.ConclusionsThe DFS pattern is basically isolated and with low titer. It is unwise to exclude the diagnosis of SARDs only depending on the appearance of the DFS pattern. Autoimmune diseases‐related antibodies, clinical information of patients, and long‐term follow‐up are of great importance to avoid missed or delayed diagnosis of SARDs.