bluuebunny/crossref_metadata_2025_split huggingface dataset:
The key role of mass spectrometry in comprehensive research on new psychoactive substances
Authors: Fabregat‐Safont David , Sancho Juan V. , Hernández Félix , Ibáñez María 
Published: June 2021

AbstractNew psychoactive substances (NPS) are a wide group of compounds that try to mimic the effects produced by the ‘classical’ illicit drugs, including cannabis (synthetic cannabinoids), cocaine and amphetamines (synthetic cathinones) or heroin (synthetic opioids), and which health effects are still unknown for most of them. Nowadays, more than 700 compounds are being monitored by official organisms, some of which have been recently identified in seizures and/or intoxication cases. Toxicological analysis plays a pivotal role in NPS research. A comprehensive investigation on NPS, from the first identification of a novel substance until its detection in drug users to help in diagnostics and medical treatment, requires the use of a wide variety of instruments and analytical strategies. This paper illustrates the key role of mass spectrometry (MS) along a comprehensive investigation on NPS. The synthetic cannabinoid XLR‐11 and the synthetic cathinone 5‐PPDi have been chosen as representative substances of the most consumed NPS families. Moreover, both compounds have been investigated at our laboratory in different stages of the three‐step strategy considered in this article. The initial identification and characterisation of the compound in consumption products, the first reported metabolic pathway and the development of analytical methodologies for its determination (and/or their metabolites) in different toxicological samples are described. The analytical strategies and MS instruments are briefly discussed to show the reader the possibilities that MS instrumentation offer to analytical scientists. This publication aims to be a starting point for those interested on the NPS research field from an analytical chemistry point of view.
High‐resolution melting curve FRET‐PCR rapidly identifies SARS‐CoV‐2 mutations
Authors: Barua Subarna , Hoque Monirul , Kelly Patrick J. , Bai Jianfa , Hanzlicek Gregg , Noll Lance , Walz Heather , Johnson Calvin , Kyriakis Constantinos , Wang Chengming 
Published: June 2021

AbstractReverse transcription fluorescence resonance energy transfer‐polymerase chain reaction (FRET‐PCRs) were designed against the two most common mutations in severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) (A23403G in the spike protein; C14408T in the RNA‐dependent RNA polymerase). Based on high‐resolution melting curve analysis, the reverse transcription (RT) FRET‐PCRs identified the mutations in american type culture collection control viruses, and feline and human clinical samples. All major makes of PCR machines can perform melting curve analysis and thus further specifically designed FRET‐PCRs could enable active surveillance for mutations and variants in countries where genome sequencing is not readily available.
Overall uncertainty of climate change impacts on watershed hydrology in China
Authors: Zhang Shaobo , Chen Jie , Gu Lei 
Published: June 2021

AbstractThe hydrological projections provided by the outputs of Global Climate Models (GCMs) combining hydrological models include multi‐source uncertainties, which may challenge the formulation of relevant adaption and mitigation policies. In this paper, the overall uncertainty and the relative contribution of each uncertainty component were investigated for hydrological projections over 408 watersheds in China by using 3 shared socioeconomic pathway emission scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5), 21 GCMs, 8 bias correction methods, 4 hydrological models, and 2 sets of optimized hydrological model parameters. The results show that the total uncertainty (T) is mainly contributed by uncertainty related to global climate models (G), with the mean percentage ranging from 60.4 to 64.1%, followed by the interaction uncertainties among all components, with the mean percentage ranging from 22.0 to 26.4%. The uncertainty contribution of hydrological models (H) (6.1–9.4%) ranks third, followed by emission scenarios (S) (2.9–5.9%) and bias correction methods (B) (0.2–1.1%). The uncertainty contribution of the optimized hydrological model parameters (P) (0.2–0.3%) is almost negligible. In terms of spatial variability, the relative contribution of uncertainty related to global climate models (G) is the highest in the near future for northern China (67.5–70.6%) and in the far future for southern China (66.1–66.7%). However, it was found to be lower for the Tibetan Plateau and northwestern China (45.3–57.9%) in the near and far future. The relative contribution of hydrological model uncertainty is higher for southwestern and northwestern China and the Tibetan Plateau (7.2–19.5%) and lower for northern, eastern, and southern China (2.5–6.6%). This study highlights the importance of including multiple GCMs and hydrological models in hydrological impact studies to consider their overall uncertainty. The development of global climate models and hydrological models is still the best way to reduce the uncertainty of climate change impact studies.
When do family brand personalities lead to brand loyalty? A study of family‐owned fashion retailers in Pakistan
Authors: Sindhu Mahwish , Saleem Irfan , Arshad Muhammad 
Published: June 2021

AbstractDespite the benefits that it can bring, family firms in emerging markets rarely take brand loyalty into account. Using self‐congruity theory and data from a sample of 381 customers of family‐owned fashion retailers in five major shopping malls in Lahore, this research sets out to answer the question, how do brand personalities help to generate a brand image, and ensure brand loyalty, for family firms in emerging markets? It focuses on the influence of three brand personalities—sincerity, competence, and excitement—on brand loyalty, and examines the mediating effect of brand image, and the moderating effect of brand sophistication. The results show that brand sincerity, competence, and excitement have a positive effect on brand image, which in turn positively influences brand loyalty, and that brand sincerity and brand excitement also have positive indirect effects on brand loyalty. The study highlights some avenues for future research and discusses the implications for managers working in family firms in emerging markets such as Pakistan.
Kinetic Modeling Characterization of Cellulose Modified Surface for Methylene Blue Removal from Aqueous Media
Authors: Azhar Siti Maizatul Ameera , Samsudin Ahmad Salihin , Ismail Wan Norfazilah Wan , Samah Nurlin Abu 
Published: June 2021

AbstractIn this work, commercial cellulose is modified with allylthiourea (Cel‐AT) to remove methylene blue (MB) from aqueous solution. Characterization study includes FTIR analysis along with UV spectrophotometer. A variety of physico‐chemical properties such as kinetic, total sorption capacity loaded and pH effect by using Cel‐AT sorbent is carried out. The main finding is the adsorption total capacity of Cel‐AT for MB is three times more than commercial cellulose (Cel) when the concentration of MB increases in batch mode. In kinetic study, the MB removal efficiency is at 90% after 5 min of removal using Cel‐AT as a sorbent and Cel‐AT fulfil pseudo second order of reaction. The optimum MB removal is at pH 11 with 95% of removal. There is spectral peak which is observed in the spectrum of FTIR and it is addressed accordingly. As a conclusion, the suggested method improves the quality of MB sorption onto the Cel‐AT in terms of contact time and less laborious.
Indian Sign Language Recognition Using Machine Learning Techniques
Authors: Sahoo Ashok Kumar 
Published: June 2021

AbstractAutomatic conversion of sign language to text or speech is indeed helpful for interaction between deaf or mute people with people who even do not have knowledge of sign language. This is the demand of current times to develop an automatic system to convert ISL signs to normal text and vice versa. This will be beneficial for both communities to express their fillings to one another in accessing publicly available facilities like ticketing, banking services, traffic signals, etc. A new feature extraction and selection technique using structural features and some of the best available classifiers are proposed to recognize ISL signs for better communication for computer‐human interface. This paper narrates a system for automatic recognition of ISL immobile numeric signs, in which a standard digital camera was only used to acquire the signs, no wearable devices are required to capture electrical signals. The system is intended to convert isolated digit signs into text, that is, each entered sign image should contain precisely one numeric sign. To recognize ISL sign images in real time environment, a sign database containing ISL digits is created which contains 5000 images, 500 images for each numeral sign (0‐9). Among two classifiers, the k‐Nearest Neighbor outperforms the Naive Bayes classifier in stipulations of classification accuracy.
Nanotechnology‐Based Approach to Combat Pandemic COVID 19: A Review
Authors: Shukla Brijesh Kumar , Tyagi Himanshi , Bhandari Hema , Garg Seema 
Published: June 2021

AbstractThe emergence of a novel Corona virus (COVID 19) originated on December 19 from China. The city of Wuhan, the capital city of Hubei province, China, is responsible for an outbreak of respiratory illness known as COVID 19 and it has been rapidly spread across the world claiming millions of lives. The sudden outbreak of novel Coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2 or 2019‐nCoV), is a big concern for their speedy mitigation using the predictable treatment and creating its approach around the world. Researchers and doctors are in search of rapid diagnosis kit, drugs, and viral‐resistant personal protective equipment (PPE) to clinical diagnosis, medication, and prevent the spread of COVID 19. A rational approach with adaptability and broad viewpoint to challenge the growing pain could be overcome by the application of appropriate technology. The nanotechnology‐based approach can significantly serve the purpose of the current pandemic situation of COVID 19. But same time implementation of innovative and creative nanotech approach, there is a decisive need for the full knowledge of SARS‐CoV‐2 pathogenesis. Moreover, to defeat COVID 19, particularly nanotech‐based system with their viral inhibitory properties to increase the effective nanotech approach is essential. In this scenario, this review aims to summarize the past, present, and future of nanotech‐based systems that can be used to treat COVID 19, highlighting Nano‐based compounds. Lastly, the potential application of the different category of Inorganic Nanomaterials/Inorganic organic conjugate /hybrid system and their practical applicability as suitable means for inspiring against COVID 19 has also been discussed.
Assessing a transmission network of Mycobacterium tuberculosis in an African city using single nucleotide polymorphism threshold analysis
Authors: Yassine Edriss , Galiwango Ronald , Ssengooba Willy , Ashaba Fred , Joloba Moses L. , Zalwango Sarah , Whalen Christopher C. , Quinn Frederick 
Published: June 2021

AbstractTuberculosis (TB) is the leading cause of death in humans by a single infectious agent worldwide with approximately two billion humans latently infected with the bacterium Mycobacterium tuberculosis. Currently, the accepted method for controlling the disease is Tuberculosis Directly Observed Treatment Shortcourse (TB‐DOTS). This program is not preventative and individuals may transmit disease before diagnosis, thus better understanding of disease transmission is essential. Using whole‐genome sequencing and single nucleotide polymorphism analysis, we analyzed genomes of 145 M. tuberculosis clinical isolates from active TB cases from the Rubaga Division of Kampala, Uganda. We established that these isolates grouped into M. tuberculosis complex (MTBC) lineages 1, 2, 3, and 4, with the most isolates grouping into lineage 4. Possible transmission pairs containing ≤12 SNPs were identified in lineages 1, 3, and 4 with the prevailing transmission in lineages 3 and 4. Furthermore, investigating DNA codon changes as a result of specific SNPs in prominent virulence genes including plcA and plcB could indicate potentially important modifications in protein function. Incorporating this analysis with corresponding epidemiological data may provide a blueprint for the integration of public health interventions to decrease TB transmission in a region.
Impact of replacing or adding placental growth factor on Down syndrome screening: A prospective cohort study
Authors: Sin Angela Wing To , Poon Liona C. , Chaemsaithong Piya , Wah Yi Man Isabella , Hui Shuk Yi Annie , Ting Yuen Ha , Law Kwok Ming , Leung Tak Yeung , Sahota Daljit Singh 
Published: June 2021

AbstractObjectivesTo assess whether adding placental growth factor (PlGF) or replacing pregnancy‐associated plasma protein‐A (PAPP‐A) improves the first trimester combined test performance for trisomy 21.MethodsA total of 11,518 women with a singleton pregnancy who underwent the first trimester combined test between December 2016 and December 2019 were included. PlGF was measured and estimated term risk for trisomy 21 was calculated by (1) adding PlGF to the combined test and (2) replacing PAPP‐A with PlGF.ResultsTwenty‐nine pregnancies had trisomy 21. The combined tests detection rate (DR), false positive rate (FPR) and screen positive rate (SPR) were 89.7%, 5.7% and 6% respectively. DR when adding PlGF to the combined test or replacing PAPP‐A remained unchanged. Replacing PAPP‐A by PlGF increased FPR and SPR to 6.2% and 6.4% respectively. Adding PlGF to the combined test gave FPR and SPR rates of 5.5% and 5.7% respectively. Change in FPR and SPR was not significant (p > 0.1 for all).ConclusionAdding PlGF to the combined test or replacing PAPP‐A with PlGF did not improve trisomy 21 DR and resulted in a non‐significant marginal change in FPR and SPR.
A constant shear stress strategy for establishing in situ viscosity models of photoinduced polymerization of acrylamide
Authors: Sun Guangdong , Huang Yi , Lv Lingling , Li Dapeng , Fan Qinguo , Li Yongqiang , Shao Jianzhong 
Published: June 2021

AbstractIn situ viscosity kinetics models for blue light induced radical polymerization of acrylamide (AM) were proposed and established with camphorquinone/4‐(dimethylamino)‐2‐ethylbenzoate/diphenyl iodonium hexafluorophosphateas the photoinitiators. In order to minimize the impact of shear effect on polymer network, a constant shear stress technique of photo‐rheometry was proposed to characterize in‐situ viscosity behavior of acrylamide solution during the photopolymerization. The effect of various factors, for example, the dosages of initiator, monomer, and light intensities, on viscosity, polymerization and gelation behavior of AM solution was systematically analyzed. The viscosity advancement behavior was shaped by the joint action of the movement, growth and entanglement of molecular chains, and shear orientation. Different power‐law kinetic models were found in three curves, time‐related viscosity, shear rate‐related viscosity and time‐related shear rate. Such school of thought on constructing the viscosity advancement model provides a new theory and method of systematical studying on the photorheological theories. Furthermore, a trinitarian theoretical model that represented the access from the microscopic kinetics of free radical polymerization to the movement behavior of polymer chains was successfully established by mapping the photoinduced viscosity kinetics model onto the polymerization and crosslinking kinetics model.
A systems pharmacology model for gene therapy in sickle cell disease
Authors: Zheng Bo , Wille Lucia , Peppel Karsten , Hagen David , Matteson Andrew , Ahlers Jeffrey , Schaff James , Hua Fei , Yuraszeck Theresa , Cobbina Enoch , Apgar Joshua F. , Burke John M. , Roberts John , Das Raibatak 
Published: June 2021

AbstractWe developed a mathematical model for autologous stem cell therapy to cure sickle cell disease (SCD). Experimental therapies using this approach seek to engraft stem cells containing a curative gene. These stem cells are expected to produce a lifelong supply of red blood cells (RBCs) containing an anti‐sickling hemoglobin. This complex, multistep treatment is expensive, and there is limited patient data available from early clinical trials. Our objective was to quantify the impact of treatment parameters, such as initial stem cell dose, efficiency of lentiviral transduction, and degree of bone marrow preconditioning on engraftment efficiency, peripheral RBC numbers, and anti‐sickling hemoglobin levels over time. We used ordinary differential equations to model RBC production from progenitor cells in the bone marrow, and hemoglobin assembly from its constituent globin monomers. The model recapitulates observed RBC and hemoglobin levels in healthy and SCD phenotypes. Treatment simulations predict dynamics of stem cell engraftment and RBC containing the therapeutic gene product. Post‐treatment dynamics show an early phase of reconstitution due to short lived stem cells, followed by a sustained RBC production from stable engraftment of long‐term stem cells. This biphasic behavior was previously reported in the literature. Sensitivity analysis of the model quantified relationships between treatment parameters and efficacy. The initial dose of transduced stem cells, and the intensity of myeloablative bone marrow preconditioning are predicted to most positively impact long‐term outcomes. The quantitative systems pharmacology approach used here demonstrates the value of model‐assisted therapeutic design for gene therapies in SCD.
Dense Pt Nanowire Electrocatalyst for Improved Fuel Cell Performance Using a Graphitic Carbon Nitride‐Decorated Hierarchical Nanocarbon Support
Authors: Fang Baizeng , Daniel Lius , Bonakdarpour Arman , Govindarajan Ruben , Sharman Jonathan , Wilkinson David P. 
Published: June 2021

AbstractAn innovative strategy is presented to engineer supported‐Pt nanowire (NW) electrocatalysts with a high Pt content for the cathode of hydrogen fuel cells. This involves deposition of graphitic carbon nitride (g‐CN) onto 3D multimodal porous carbon (MPC) (denoted as g‐CN@MPC) and using the g‐CN@MPC as an electrocatalyst support. The protective coating of g‐CN on the MPC provides good stability for the electrocatalyst support against electrochemical oxidation, and also enhances oxygen adsorption and provides additional active sites for the oxygen reduction reaction. Compared with commercial carbon black Vulcan XC‐72R (denoted as VC) support material, the larger hydrophobic surface area of the g‐CN@MPC enables the supported high‐content Pt NWs to disperse uniformly on the support. In addition, the unique 3D interconnected pore networks facilitate improved mass transport within the g‐CN@MPC support material. As a result, the g‐CN@MPC‐supported high‐content Pt catalysts show improved performance with respect to their counterparts, namely, MPC, VC, and g‐CN@VC‐supported Pt NW catalysts and the conventional Pt nanoparticle (NP) catalyst (i.e., Pt(20 wt%)NPs/VC (Johnson Matthey)) used as the benchmark. More importantly, the g‐CN‐tailored high‐content Pt NW (≈60 wt%) electrocatalyst demonstrates high PEM fuel cell power/performance at a very low cathode catalyst loading (≈0.1 mgPt cm−2).
Bone Histomorphometry and 18F-Sodium Fluoride Positron Emission Tomography Imaging: Comparison Between only Bone Turnover-based and Unified TMV-based Classification of Renal Osteodystrophy
Authors: Aaltonen Louise , Koivuviita Niina , Seppänen Marko , Burton Inari S. , Kröger Heikki , Löyttyniemi Eliisa , Metsärinne Kaj 
Published: June 2021

AbstractBone biopsy is the gold standard for characterization of renal osteodystrophy (ROD). However, the classification of the subtypes of ROD based on histomorphometric parameters is not unambiguous and the range of normal values for turnover differ in different publications.18F-Sodium Fluoride positron emission tomography (18F-NaF PET) is a dynamic imaging technique that measures turnover.18F-NaF PET has previously been shown to correlate with histomorphometric parameters. In this cross-sectional study, 26 patients on dialysis underwent a18F-NaF PET and a bone biopsy. Bone turnover-based classification was assessed using Malluche’s historical reference values for normal bone turnover. In unified turnover-mineralization-volume (TMV)-based classification, the whole histopathological picture was evaluated and the range for normal turnover was set accordingly. Fluoride activity was measured in the lumbar spine (L1–L4) and at the anterior iliac crest. On the basis of turnover-based classification of ROD, 12% had high turnover and 61% had low turnover bone disease. On the basis of unified TMV-based classification of ROD, 42% had high turnover/hyperparathyroid bone disease and 23% had low turnover/adynamic bone disease. When using unified TMV-based classification of ROD,18F-NaF PET had an AUC of 0.86 to discriminate hyperparathyroid bone disease from other types of ROD and an AUC of 0.87, for discriminating adynamic bone disease. There was a disproportion between turnover-based classification and unified TMV-based classification. More research is needed to establish normal range of bone turnover in patients with CKD and to establish the role of PET imaging in ROD.
Evaluation of sonographic detectability of different markers within an in vitro simulation model of the axilla
Authors: Guergan Selin , Hoopmann Uta , Roehm Carmen , Boeer Bettina , Fugunt Regina , Helms Gisela , Seller Anna , Marx Mario , Oberlechner Ernst , Hartkopf Andreas , Preibsch Heike , Brucker Sara , Wallwiener Diethelm , Hahn Markus , Gruber Ines Verena 
Published: June 2021

Abstract
Purpose
Clip-marking of axillary lymph nodes with initial biopsy-confirmed metastasis is required for targeted axillary dissection (TAD), which includes sentinel lymph node dissection (SLND) and selective localization and removal of the clipped targeted lymph node. There have been several studies which examined the feasibility of TAD in routine clinical use. In this context, the optimal clip visualisation was noted as one of the crucial limiting factors. We, therefore, evaluated the sonographic detectability of 10 different commercially available markers within an in vitro model simulating the anatomical composition of the axilla.

Methods
In this standardised model consisting of porcine fat with 30 mm thickness, the visibility of a total of ten markers was analysed in all 3 planes (parallel, diagonal, orthograde) with wire guidance and then classified into either “visibility good”, “visibility moderate” or “visibility poor” with regard to the alignment of the transducer. Additionally, “real-life conditions” were simulated, in which the markers were searched without any wires guidance.

Results
It was observed that, while not all markers are detectable in fatty tissue, markers with spherical shape (non-embedded Inconel or Nitinol) or rectangular-shaped Titanium markers with embedded material have a clear advantage. 3D-shaped markers can always be detected in all three axes, which is of particular importance in the axilla with its pyramid shape and fatty tissue.

Conclusion
The shape and the embedding of the material play a crucial role for visibility and efficacy of the marker, as reliable marking of suspicious and pathological axillary lymph nodes is essential for TAD.