bluuebunny/crossref_metadata_2025_split huggingface dataset:
Subthalamic and Pallidal Stimulations in Patients with Parkinson's Disease: Common and Dissociable Connections
Authors: Zhang Chencheng , Lai Yijie , Li Jun , He Naying , Liu Yu , Li Yan , Li Hongyang , Wei Hongjiang , Yan Fuhua , Horn Andreas , Li Dianyou , Sun Bomin 
Published: August 2021

ObjectiveThe subthalamic nucleus (STN) and internal globus pallidus (GPi) are the most effective targets in deep brain stimulation (DBS) for Parkinson's disease (PD). However, the common and specific effects on brain connectivity of stimulating the 2 nuclei remain unclear.MethodsPatients with PD receiving STN‐DBS (n = 27, 6 women, mean age 64.8 years) or GPi‐DBS (n = 28, 13 women, mean age 64.6 years) were recruited for resting‐state functional magnetic resonance imaging to assess the effects of STN‐DBS and GPi‐DBS on brain functional dynamics.ResultsThe functional connectivity both between the somatosensory‐motor cortices and thalamus, and between the somatosensory‐motor cortices and cerebellum decreased in the DBS‐on state compared with the off state (p < 0.05). The changes in thalamocortical connectivity correlated with DBS‐induced motor improvement (p < 0.05) and were negatively correlated with the normalized intersection volume of tissues activated at both DBS targets (p < 0.05). STN‐DBS modulated functional connectivity among a wider range of brain areas than GPi‐DBS (p = 0.009). Notably, only STN‐DBS affected connectivity between the postcentral gyrus and cerebellar vermis (p < 0.001) and between the somatomotor and visual networks (p < 0.001).InterpretationOur findings highlight common alterations in the motor pathway and its relationship with the motor improvement induced by both STN‐ and GPi‐DBS. The effects on cortico‐cerebellar and somatomotor‐visual functional connectivity differed between groups, suggesting differentiated neural modulation of the 2 target sites. Our results provide mechanistic insight and yield the potential to refine target selection strategies for focal brain stimulation in PD. ANN NEUROL 2021;90:670–682
Automated Electrical Quantification of Vitamin B1 in a Bodily Fluid using an Engineered Nanopore Sensor
Authors: Lucas Florian Leonardus Rudolfus , Piso Tjemme Rinze Cornelis , van der Heide Nieck Jordy , Galenkamp Nicole Stéphanie , Hermans Jos , Wloka Carsten , Maglia Giovanni 
Published: August 2021

AbstractThe ability to measure the concentration of metabolites in biological samples is important, both in the clinic and for home diagnostics. Here we present a nanopore‐based biosensor and automated data analysis for quantification of thiamine in urine in less than a minute, without the need for recalibration. For this we use the Cytolysin A nanopore and equip it with an engineered periplasmic thiamine binding protein (TbpA). To allow fast measurements we tuned the affinity of TbpA for thiamine by redesigning the π‐π stacking interactions between the thiazole group of thiamine and TbpA. This substitution resulted furthermore in a marked difference between unbound and bound state, allowing the reliable discrimination of thiamine from its two phosphorylated forms by residual current only. Using an array of nanopores, this will allow the quantification within seconds, paving the way for next‐generation single‐molecule metabolite detection systems.
Near‐Infrared‐Excited Multicolor Afterglow in Carbon Dots‐Based Room‐Temperature Afterglow Materials
Authors: Zheng Yihao , Wei Haopeng , Liang Ping , Xu Xiaokai , Zhang Xingcai , Li Huihong , Zhang Chenlu , Hu Chaofan , Zhang Xuejie , Lei Bingfu , Wong Wai‐Yeung , Liu Yingliang , Zhuang Jianle 
Published: August 2021

AbstractRoom‐temperature afterglow (RTA) materials with long lifetime have shown tremendous application prospects in many fields. However, there is no general design strategy to construct near‐infrared (NIR)‐excited multicolor RTA materials. Herein, we report a universal approach based on the efficient radiative energy transfer that supports the reabsorption from upconversion materials (UMs) to carbon dots‐based RTA materials (CDAMs). Thus, the afterglow emission (blue, cyan, green, and orange) of various CDAMs can be activated by UMs under the NIR continuous‐wave laser excitation. The efficient radiative energy transfer ensured the persistent multicolor afterglow up to 7 s, 6 s, 5 s, and 0.5 s by naked eyes, respectively. Given the unusual afterglow properties, we demonstrated preliminary applications in fingerprint recognition and information security. This work provides a new avenue for the activation of NIR‐excited afterglow in CDAMs and will greatly expand the applications of RTA materials.
An investigation of structure, Hirshfeld surface, and fluorescence properties of two dinuclear Ni (II) and Zn (II) salamo‐type complexes
Authors: Pu Lu‐Mei , Li Peng , Li Shi‐Zhen , Xu Wei‐Bing , Long Hai‐Tao , Dong Wen‐Kui 
Published: August 2021

AbstractTwo dinuclear Ni (II) and Zn (II) salamo‐type complexes, [Ni2(L)(μ‐OAc)(MeOH)]·2CHCl3 (1) and [{Zn2(L)(μ‐OMe)}3]·3CHCl3·MeOH (2), have been successfully synthesized by wet‐chemical method and characterized by elemental analyses, IR spectra, UV–Vis spectra and single crystal X‐ray diffraction. Complex 1 consists of two closely related dinuclear units 1A and 1B, and complex 2 consists of three closely related dinuclear units 2A, 2B and 2C. The five units are unique example of crystallographically independent but chemically identical molecules. The Ni (II) atoms of complex 1 are located in the N2O4 coordination cavities, possessing six‐coordinated distorted octahedral geometries, but all Zn (II) atoms in complex 2 are located in the N2O3 coordination cavities, possessing five‐coordinated distorted square‐pyramid and triangular bipyramid geometries, the geometries about the Zn (II) atoms (Zn3 and Zn6) that obtain in 2B and 2C where τ5 is very close to 0.500, which is τ5Zn3 = 0.5006 and τ5Zn6 = 0.4941, respectively. The interactions were quantitatively determined by Hirshfeld surfaces analyses. Significantly, fluorescence properties were also investigated.
The effect of polyethylene‐graft‐maleic anhydride on ultrahigh molecular weight polyethylene/carboxymethyl cellulose blends
Authors: Ozcan Sonay , Dandan Doganci Merve 
Published: August 2021

AbstractIn this study, it is aimed to produce biocompatible polymer blends by using ultrahigh molecular weight polyethylene (UHMWPE) as a matrix and a cellulose‐based polymer, carboxymethyl cellulose (CMC) as filler at different concentrations. Polyethylene‐graft‐maleic anhydride (PE‐g‐MA) was used as compatibilizer in order to ensure effective distribution of hydrophilic cellulose particles in hydrophobic UHMWPE matrix and its effect on blends was investigated. The UHMWPE/CMC blends were fabricated by sintering of two powder materials and effects of different sintering conditions such as sintering temperature and time were examined on the morphological and surface properties of blends. The hardness, air permeability, contact angle variations on the blend surfaces were investigated. 150°C–30 min sintering condition was determined as optimum sintering time and temperature to prepare the blends having adequate hardness with high‐air permeability properties. It was found that with the increase of CMC content in the blends the hardness, air permeability and contact angle values were decreased. The addition of PE‐g‐MA caused an increment for blends prepared at 150°C–30 min conditions having high‐air permeability.
Protected areas and frugivorous fish in tropical rivers: Small‐scale fisheries, conservation and ecosystem services
Authors: Nagl Paula , Hallwass Gustavo , Tomazoni‐Silva Luís H. , Nitschke Pedro P. , Rowedder Anais R. P. , Romero‐Martinez Astrid Tatiana , Silvano Renato A. M. 
Published: August 2021

Abstract

Frugivorous fish provide often conflicting ecosystem services of seed dispersal and food provisioning in tropical rivers. Fishing may reduce the size and abundance of frugivorous fish, thus affecting their potential as seed dispersers, which could affect the conservation of these fish and of floodplain forests.
The goal of this study was to assess the influence of co‐managed protected areas in the form of extractive reserves (RESEX) and small‐scale fisheries on frugivorous fish in the Tapajós and Negro rivers, in the Brazilian Amazon. The study examined whether: (i) frugivorous fish are important for fisheries and selectively caught; and (ii) frugivorous fish abundance, size and fisheries catch per unit of effort are higher inside the RESEX than outside.
The analyses included fisheries‐dependent data (3,753 fish landings) and independent data (12,730 sampled fish) collected in 16 fishing communities (eight for each river). In both rivers, frugivorous fish are among the 10 species caught the most and frugivorous biomass was proportionately higher in landings than in samplings, indicating fisheries selectivity towards these fishes.
In both rivers, catches of frugivorous fish were higher outside the RESEX than inside. Catch per unit effort and the proportion of frugivores in the catch were higher outside the RESEX in the Tapajós River but did not vary between sites inside and outside the RESEX in the Negro River. Frugivorous fish were larger inside the RESEX in the Negro, but smaller inside the RESEX in the Tapajós.
The results indicated that the ecosystem services of seed dispersal and food source provided by frugivorous fish are not in conflict in the tropical rivers studied. Therefore, these clearwater and blackwater rivers in the Brazilian Amazon show a balance between fisheries and conservation of frugivorous fish, which play an essential role in the functioning of tropical floodplain forest ecosystems.
A Golgi study of neurons in the camel cerebellum (Camelus dromedarius)
Authors: Al‐Hussain Saleh M. , Yousuf Mustafa S. , Hani Ayat Bani , Zaqout Sami , Djouhri Laiche , Mustafa Ayman G. 
Published: August 2021

AbstractNeurons in the cerebellar cortex of camels were studied using modified Golgi impregnation methods. Neurons were classified according to their position, morphology of their soma, density and distribution of dendrites, and the course of their axons. Accordingly, eight types of neurons were identified. Three types were found in the molecular layer: upper and lower stellate cells and basket cells, and four types were found in the granular layer: granule cells, Golgi Type II cells, Lugaro cells, and unipolar brush cells. Only the somata of Purkinje cells were found in the Purkinje cell layer. The molecular layer is characterized by the presence of more dendrites, dendritic spines, and transverse fibers. Golgi cells also show extensive dendritic branching and spines. The results illustrate the neuronal features of the camel cerebellum as a large mammal living in harsh environmental conditions. These findings should contribute to advancing our understanding of species‐comparative anatomy in achieving better coordination of motor activity.
Scandium Reduced Arene Complex: Protonation and Reaction with Azobenzene
Authors: Ghana Priyabrata , Spaniol Thomas P. , Okuda Jun 
Published: August 2021

AbstractThe reactivity of the reduced anthracene complex of scandium [Li(thf)3][Sc{N(tBu)Xy}2(anth)] (2‐anth‐Li) (Xy=3,5‐Me2C6H3; anth=C14H102−, thf=tetrahydrofuran) toward Brønsted acid [NEt3H][BPh4] and azobenzene is reported. While a stepwise protonation of 2‐anth‐Li with two equivalents of [NEt3H][BPh4] afforded the scandium cation [Sc{N(tBu)Xy}2(thf)2][BPh4] (3), reduction of azobenzene gave a thermolabile, anionic scandium reduced azobenzene complex [Li(thf)][Sc{N(tBu)Xy}2(η2‐PhNNPh)] (4), which slowly lost one of the anilide ligands to form the neutral scandium azobenzene complex dimer [Sc{N(tBu)Xy}(μ‐η2:η2‐Ph2N2)]2 (5). Exposure of 3 to CO2 produced the scandium carbamate complex [Sc{κ2‐O2CN(tBu)(Xy)}2][BPh4] (6) as a result of CO2 insertion into the Sc−N bonds. In an attempt to prepare scandium hydrides, the reaction of 3 with the hydride sources LiAlH4 and Na[BEt3H] led to the terminal aluminum hydride [AlH{N(tBu)Xy}2(thf)] (7) and the scandium n‐butoxide [Sc{N(tBu)(Xy)}2(μ‐OnBu)] (8) after Sc/Al transmetalation and nucleophilic ring‐opening of THF, respectively. All reported compounds isolated in moderate to good yields were fully characterized.
L‐malic acid production from xylose by engineered Saccharomyces cerevisiae
Authors: Kang Nam Kyu , Lee Jae Won , Ort Donald R. , Jin Yong‐Su 
Published: August 2021

AbstractL‐malic acid is widely used in the food, chemical, and pharmaceutical industries. Here, we report on production of malic acid from xylose, the second most abundant sugar in lignocellulosic hydrolysates, by engineered Saccharomyces cerevisiae. To enable malic acid production in a xylose‐assimilating S. cerevisiae, we overexpressed PYC1 and PYC2, coding for pyruvate carboxylases, a truncated MDH3 coding for malate dehydrogenase, and SpMAE1, coding for a Schizosaccharomyces pombe malate transporter. Additionally, both the ethanol and glycerol‐producing pathways were blocked to enhance malic acid production. The resulting strain produced malic acid from both glucose and xylose, but it produced much higher titers of malic acid from xylose than glucose. Interestingly, the engineered strain had higher malic acid yield from lower concentrations (10 g L‒1) of xylose, with no ethanol production, than from higher xylose concentrations (20 and 40 g L‒1). As such, a fed‐batch culture maintaining xylose concentrations at low levels was conducted and 61.2 g L‒1 of malic acid was produced, with a productivity of 0.32 g L‒1 h. These results represent successful engineering of S. cerevisiae for the production of malic acid from xylose, confirming that that xylose offers the efficient production of various biofuels and chemicals by engineered S. cerevisiae.
Degenerative disease‐on‐a‐chip: Developing microfluidic models for rapid availability of newer therapies
Authors: Jahagirdar Devashree , Bangde Prachi , Jain Ratnesh , Dandekar Prajakta 
Published: August 2021

AbstractBackgroundUnderstanding the pathophysiology of degenerative diseases pertaining to nervous system, ocular region, bone/cartilage, and muscle are still being comprehended, thus delaying the availability of targeted therapies.Purpose and ScopeNewer micro‐physiological systems (organ‐on‐chip technology) involves development of more sophisticated devices, modelling a range of in vitro human tissues and an array of models for diseased conditions. These models expand opportunities for high throughput screening (HTS) of drugs and are likely to be rapid and cost‐effective, thus reducing extensive usage of animal models.ConclusionThrough this review article, we aim to present an overview of the degenerative disease models that are presently being developed using microfluidic platforms with the aim of mimicking in vivo tissue physiology and micro‐architecture. The manuscript provides an overview of the degenerative disease models and their potential for testing and screening of possible biotherapeutic molecules and drugs. It highlights the perspective of the regulatory bodies with respect to the established‐on chip models and thereby enhancing its translational potential.
Synergisms of machine learning and constraint‐based modeling of metabolism for analysis and optimization of fermentation parameters
Authors: Khaleghi Mohammad Karim , Savizi Iman Shahidi Pour , Lewis Nathan E. , Shojaosadati Seyed Abbas 
Published: August 2021

AbstractRecent noteworthy advances in developing high‐performing microbial and mammalian strains have enabled the sustainable production of bio‐economically valuable substances such as bio‐compounds, biofuels, and biopharmaceuticals. However, to obtain an industrially viable mass‐production scheme, much time and effort are required. The robust and rational design of fermentation processes requires analysis and optimization of different extracellular conditions and medium components, which have a massive effect on growth and productivity. In this regard, knowledge‐ and data‐driven modeling methods have received much attention. Constraint‐based modeling (CBM) is a knowledge‐driven mathematical approach that has been widely used in fermentation analysis and optimization due to its ability to predict the cellular phenotype from genotype through high‐throughput means. On the other hand, machine learning (ML) is a data‐driven statistical method that identifies the data patterns within sophisticated biological systems and processes, where there is inadequate knowledge to represent underlying mechanisms. Furthermore, ML models are becoming a viable complement to constraint‐based models in a reciprocal manner when one is used as a pre‐step of another. As a result, a more predictable model is produced. This review highlights the applications of CBM and ML independently and the combination of these two approaches for analyzing and optimizing fermentation parameters.
Challenges for graduate students' mentors during COVID‐19 pandemic
Authors: Li Honglin , Zhang Dake , Liang Boying , Zhong Lichao , Cao Yue , Shen Jie 
Published: August 2021

AbstractThe outbreak of COVID‐19 pandemic results in the suspension of universities' academic laboratory activities. This brought a difficult time for graduate students majored in molecular biology and their mentors, since the student's thesis progress relies on the data from wet experiments in the lab. Even facing the challenges during the pandemic, mentors could still play an active role. This COVID‐19 crisis requires mentors to have more thinking, innovation, and sharing in guiding graduate students.
Symmetry of bilateral hallux valgus deformity: A radiographic study
Authors: Crooks Sophie A , Lewis Thomas L , Ray Robbie , Gordon David J 
Published: August 2021

AbstractHallux valgus (HV) is a common anatomical deformity leading to pain and difficulty with footwear and mobility. Bilateral HV deformity is much more common than unilateral although it remains unclear whether the severity of deformity is equal between feet. The objective was to investigate the severity and symmetry of HV in patients with bilateral symptomatic deformity presenting for surgery. Weight‐bearing radiographs of patients presenting with symptomatic bilateral HV were reviewed. The hallux valgus angle (HVA) and intermetatarsal angle (IMA) were measured and classified as mild, moderate, or severe. Left‐to‐right comparison was undertaken to assess whether the degree of deformity was similar for each foot. The relationship between age, HVA, and IMA was also assessed. Between July 2014 and June 2020, 322 ft (161 patients with bilateral deformity) underwent corrective HV surgery. Of those, 6.8%, 64.6%, and 28.4% were classified as mild, moderate, and severe, respectively on the left side, and on the right 6.2%, 67.7%, and 26.1% were classified as mild, moderate, and severe respectively. There was no statistically significant difference between feet for either IMA (p = 0.06) or HVA (p = 0.85). There was a moderate correlation (R = 0.41,p ≤ 0.001) between HVA and IMA. There was only a ‘weak’ or ‘very weak’ correlation between age and HVA or IMA. Patients presenting for surgery with symptomatic bilateral HV have symmetrical moderate radiographic deformity at the time they present for consideration of surgical intervention.
Three models that predict the efficacy of immunotherapy in Chinese patients with advanced non‐small cell lung cancer
Authors: Zhao Qian , Li Butuo , Xu Yiyue , Wang Shijiang , Zou Bing , Yu Jinming , Wang Linlin 
Published: August 2021

BackgroundMany tools have been developed to predict the efficacy of immunotherapy, such as lung immune prognostic index (LIPI), EPSILoN [Eastern Cooperative Oncology Group performance status (ECOG PS), smoking, liver metastases, lactate dehydrogenase (LDH), neutrophil‐to‐lymphocyte ratio (NLR)], and modified lung immune predictive index (mLIPI) scores. The aim of this study was to determine the ability of three predictive scores to predict the outcomes in Chinese advanced non‐small cell lung cancer (aNSCLC) patients treated with immune checkpoint inhibitors (ICIs).MethodsWe retrospectively analyzed 429 patients with aNSCLC treated with ICIs at our institution. The predictive ability of these models was evaluated using area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis. Calibration was assessed using the Hosmer–Lemeshow test (H–L test) and Spearman's correlation coefficient. Progression‐free survival (PFS) and overall survival (OS) curves were generated using the Kaplan–Meier method.ResultsThe AUC values of LIPI, mLIPI, and EPSILoN scores predicting PFS at 6 months were 0.642 [95% confidence interval (CI):0.590–0.694], 0.720 (95% CI: 0.675–0.762), and 0.633 (95% CI: 0.585–0.679), respectively (p < 0.001 for all models). The AUC values of LIPI, mLIPI, and EPSILON scores predicting objective response rate (ORR) were 0.606 (95% CI: 0.546–0.665), 0.683 (95% CI: 0.637–0.727), and 0.666 (95% CI: 0.620–0.711), respectively (p < 0.001 for all models). The C‐indexes of LIPI, mLIPI, and EPSILoN scores for PFS were 0.627 (95% CI 0.611–6.643), 0.677 (95% CI 0.652–0.682), and 0.631 (95% CI 0.617–0.645), respectively.ConclusionsAs mLIPI scores had the highest accuracy when used to predict the outcomes in Chinese aNSCLC patients, this tool could be used to guide clinical immunotherapy decision‐making.
Supercritical Fluid and Ultrasound‐assisted Green Extraction Technologies for Catechin Recovery
Authors: Dutta Sayantani , Priyadarshini S. R. , Moses Jeyan A. , Anandharamakrishnan C. 
Published: August 2021

AbstractThe epimers of catechin include epicatechin, epigallocatechin and epigallocatechin gallate, and others. They are important bioactives that have salutary effects, and hence are valuable. For ascertaining biologically‐safe and green extraction methods that are non‐thermal, this review evaluates the efficiencies of ultrasound assisted extraction (UAE) and supercritical (SC) fluid extraction (with CO2). Standalone SC‐CO2 could be preferred over UAE, given its selectivity (purer product, no co‐extracts) and absence of downstream processing. GRAS solvents as water and ethanol or a hydro‐alcoholic mix are preferable for UAE. However, considering the core competency of ultrasound in disrupting cell organelles, a tandem approach with sequential SC extraction is recommended to justify process economics and ensure quality yield of catechin using green technologies.
Application of Machine Learning in Industrial Boilers: Fault Detection, Diagnosis, and Prognosis
Authors: Meng Yang , Wu Xinyun , Oladejo Jumoke , Dong Xinyue , Zhang Zhiqian , Deng Jie , Yan Yuxin , Zhao Haitao , Lester Edward , Wu Tao , Pang Cheng Heng 
Published: August 2021

AbstractEnhancement in boiler efficiency via controlled operation could lead to energy savings and reduction in pollutant emission. Activities such as scheduled maintenance could be improved by increasing boiler availability and reducing running costs. However, the time interval between recommended maintenance is varied depending on boilers. The application of fault detection, diagnosis and prognosis (FDDP) in industrial boilers plays an important role in optimizing operation, early‐warning of faults, and identification of root causes. This review discusses the application of machine learning (ML)‐based algorithms (knowledge‐driven and data‐driven) for FDDP, thus allowing the identification of fit‐for‐purpose techniques for specific applications leading to improved efficiency, operability, and safety.