bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ad libitum dehydration is associated with poorer performance on a sustained attention task but not other measures of cognitive performance among middle‐to‐older aged community‐dwelling adults: A short‐term longitudinal study
Authors: Rosinger Asher Y. , John Jason D. , Murdock Kyle W. 
Published: February 2024

AbstractObjectiveHydration status and water intake are critical to physiological health. Despite a popular narrative that dehydration impairs cognitive performance, results are mixed in the literature. Therefore, we tested how hydration status was associated with cognitive performance in an ad libitum state over the course of 3 months.MethodsData come from a short‐term longitudinal study among middle‐to‐older aged US adults (n = 78) measured three times (207 observations). All participants were scheduled for 8:00 a.m. visits for the baseline, two‐week, and 3‐month examinations where they completed surveys, neuropsychological tests to measure cognitive performance, anthropometrics, and a blood draw for biomarker analysis. Serum osmolality (Sosm) was measured as a biomarker of hydration status using osmometry. Four cognitive performance tasks were assessed, including inhibition, working memory, cognitive flexibility, and sustained attention.ResultsPanel random effects linear regressions demonstrate that there was an inverse association between dehydration and sustained attention, whereas there were no significant relationships between dehydration and inhibition, working memory, and cognitive flexibility. Adults who were dehydrated (defined as Sosm >300 mOsm/kg) performed substantially worse (B = 0.65 z‐score; SE = 0.28; p = .020) on the sustained attention task than those who were not dehydrated adjusting for time fixed effects, age, body mass index, sex, and educational attainment.ConclusionThis short‐term longitudinal study found that dehydration was only associated with poorer performance on a cognitive performance task that required sustained attention. Maintaining adequate hydration may be increasingly important for middle‐to‐older aged adults to ensure proper cognitive function, particularly as water needs increase in future climatic scenarios.
Microglial Reactivity Correlates with Presynaptic Loss Independent of β‐Amyloid and Tau
Authors: Lan Guoyu , Chen Xuhui , Yang Jie , Sun Pan , Cai Yue , Li Anqi , Zhu Yalin , Liu Zhen , Ma Shaohua , Guo Tengfei ,   for the Alzheimer's Disease Neuroimaging Initiative
Published: February 2024

ObjectiveTriggering receptor expressed on myeloid cells‐2 (TREM2) and progranulin (PGRN) are critical regulators of microglia activation and can be detected in cerebrospinal fluid (CSF). However, whether microglial reactivity is detrimental or neuroprotective for Alzheimer disease (AD) is still debatable.MethodsWe identified 663 participants with baseline β‐amyloid (Aβ) positron emission tomography (PET) and CSF biomarker data, including phosphorylated tau181 (p‐Tau181), soluble TREM2 (sTREM2), PGRN, and growth‐associated protein‐43 (GAP‐43). Among them, 254 participants had concurrent longitudinal CSF biomarkers. We used multivariate regression analysis to study the associations of CSF microglial biomarkers with Aβ PET, CSF p‐Tau181, and CSF GAP‐43 cross‐sectionally and longitudinally. A Chinese aging cohort's independent CSF samples (n = 65) were analyzed as a validation.ResultsHigher baseline levels of CSF microglial biomarkers were related to faster rates of CSF sTREM2 increase and CSF PGRN decrease. Elevated CSF p‐Tau181 was associated with higher levels of CSF microglial biomarkers and faster rates of CSF sTREM2 increase and CSF PGRN decrease. In both cohorts, higher Aβ burden was associated with attenuated CSF p‐Tau181 effects on CSF microglial biomarker increases. Independent of Aβ PET and CSF p‐Tau181 pathologies, higher levels of CSF sTREM2 but not CSF PGRN were related to elevated CSF GAP‐43 levels and faster rates of CSF GAP‐43 increase.InterpretationThese findings suggest that higher Aβ burden may attenuate the p‐Tau‐associated microglial responses, and TREM2‐related microglial reactivity may independently correlate with GAP‐43‐related presynaptic loss. This study highlights the two‐edged role of microglial reactivity in AD and other neurodegenerative diseases. ANN NEUROL 2024;95:917–928
A Microporous Multi‐Cage Metal–Organic Framework for an Effective One‐Step Separation of Branched Alkanes Feeds
Authors: Zhou Lin , Brântuas Pedro , Henrique Adriano , Reinsch Helge , Wahiduzzaman Mohammad , Grenèche Jean‐Marc , Rodrigues Alírio E. , Silva José A. C. , Maurin Guillaume , Serre Christian 
Published: February 2024

AbstractThe improvement of the Total Isomerization Process (TIP) for the production of high‐quality gasoline with the ultimate goal of reaching a Research Octane Number (RON) higher than 92 requires the use of specific sorbents to separate pentane and hexane isomers into classes of linear, mono‐ and di‐branched isomers. Herein we report the design of a new multi‐cage microporous Fe(III)‐MOF (referred to as MIP‐214, MIP stands for materials of the Institute of Porous Materials of Paris) with a flu‐e topology, incorporating an asymmetric heterofunctional ditopic ligand, 4‐pyrazolecarboxylic acid, that exhibits an appropriate microporous structure for a thermodynamic‐controlled separation of hydrocarbon isomers. This MOF produced via a direct, scalable, and mild synthesis route was proven to encompass a unique separation of C5/C6 isomers by classes of low RON over high RON alkanes with a sorption hierarchy: (n‐hexane≫n‐pentane≈2‐methylpentane>3‐methylpentane)low RON≫(2,3‐dimethylbutane≈i‐pentane≈2,2‐dimethylbutane)high RON following the adsorption enthalpy sequence. We reveal for the first time that a single sorbent can efficiently separate such a complex mixture of high RON di‐branched hexane and mono‐branched pentane isomers from their low RON counterparts, which is a major achievement reported so far.
Controllable Double Difluoromethylene Insertions into S−Cu Bonds: (Arylthio)tetrafluoroethylation of Aryl Iodides with TMSCF2Br
Authors: Pan Shitao , Xie Qiqiang , Wang Xiu , Huang Rumin , Lu Yuhao , Ni Chuanfa , Hu Jinbo 
Published: February 2024

AbstractA new method of constructing “ArSCF2CF2Cu” from ArSCu and TMSCF2Br (TMS=trimethylsilyl) has been developed. The cross‐coupling reactions of the obtained “ArSCF2CF2Cu” with diverse aryl iodides (Ar′I) provide an efficient access to Ar′CF2CF2SAr. Mechanistic studies demonstrate that the “ArSCF2CF2Cu” species were generated through controllable double difluoromethylene insertions into ArS−Cu bonds rather than the 1,2‐addition of ArSCu to tetrafluoroethylene.
Stretchable photochromic hydrous TiO2‐embedded glycerol‐poly(dimethylsiloxane) film for rewritable information storage
Authors: Li Chonghui , Yu Liyun , Zhao Weizhen , Madsen Frederikke Bahrt , Skov Anne Ladegaard 
Published: February 2024

AbstractPhotoreversible, color‐changing films have great potential in various optical applications. In this study, we developed a photochromic film by embedding droplets of metatitanic acid (hydrous TiO2) and glycerol in commercially available poly(dimethylsiloxane) (PDMS) silicone elastomers. Benefiting from the electron–hole pair scavenging abilities of glycerol, the resulting film exhibited rapid photoresponse, high photoreversible stability, excellent antiaging capability, and remarkable stretchability. The degree of color changes upon ultraviolet (UV) irradiation was effectively controlled by adjusting both the concentration of hydrous TiO2 (1–20 wt%) and UV irradiation time (5–30 min), thereby increasing total color‐changing ability (ΔE). High‐resolution patterns could be repetitively printed, erased, and rewritten (≥20 times) with no significant loss of clarity. After a 30‐day exposure to ambient air, there were no significant aging effects in the photochromic ability of the films, thus demonstrating promising potential as rewritable films for information storage.
For perpetuating social media collective memory proactively and inclusively: Explore the interests and tensions of stakeholders in preservation actions
Authors: Liu Hui , Zhang Dong Rong , Zhou Qing Shan , Li Bin 
Published: February 2024

AbstractGoing beyond the limitations of technology, time, and platform lifecycles, achieving long‐term preservation of social media collective memory is an important issue. As a social action involving multiple stakeholders, social media preservation faces a complex problem space. Taking China as an example, this study revealed, from the perspective of stakeholders, the underlying logic of cultural, ethical, legal, and other issues that social media preservation encounters, namely, the tension arising from differences in stakeholders' interests and power inequalities. We specifically investigated and analyzed five categories of stakeholders and revealed six tensions among them in the power/interest matrix. In the final discussion, we analyzed what proactive and inclusive preservation actions should be. Our research not only contributes to the development of theories for social media preservation in information science but also provides clues for state regulators and memory institutions to make responsible and inclusive decisions.
Modelling and cycle‐by‐cycle control of an electromechanical engine valve actuator with impact speed limiter based on hydraulic damper
Authors: di Gaeta Alessandro , Montanaro Umberto , Giglio Veniero 
Published: February 2024

AbstractVariable valve actuation (VVA) systems based on electromechanical valve actuators (EMVAs) enable a flexible operation and management of internal combustion engines that results in a reduction of pollutant emission and fuel consumption while improving engine power and efficiency. However, to achieve the benefits promised by EMVAs, it is of utmost importance to guarantee the catch of the valve by the system magnets with an acceptable impact speed of the valve at the end‐strokes. Valve catching failures can severely damage engine valves while high impact speeds induce mechanical wear and unacceptable noise. The soft landing control of the valve at the end‐strokes is challenging because of system nonlinearities, parameter uncertainties, and external disturbances. The complexity of the control design increases further when industrial cost‐effective solutions are sought. This paper presents a novel solution for reducing the impact speed of the valve without the use of costly position valve sensors. The proposed solution leverages on a small hydraulic damper (HD) embedded into the EMVA and a feedback cycle‐by‐cycle controller. The passive element reduces the impact speed while the controller adjusts at every engine cycle the EMVA coil currents based on pressure peaks detected in the HD to guarantee valve catching while steering the impact speed toward its minimum. The design of the controller exploits a physics‐based model that maps the pressure peak in the HD onto the impact speed and a gradient descent algorithm is adopted searching the minimum. The closed‐loop permanence is assessed in simulation by using an experimentally validated EMVA model and considering detailed dynamics of the HD. Numerical results show the ability of the proposed control architecture to reduce the impact speed and its robustness to parameters variations (oil temperature) and external disturbances (gas pressure forces).
Are fetal microchimerism and circulating fetal extracellular vesicles important links between spontaneous preterm delivery and maternal cardiovascular disease risk?
Authors: Bonney Elizabeth A. , Lintao Ryan C. V. , Zelop Carolyn M. , Kammala Ananth Kumar , Menon Ramkumar 
Published: February 2024

AbstractTrafficking and persistence of fetal microchimeric cells (fMCs) and circulating extracellular vesicles (EVs) have been observed in animals and humans, but their consequences in the maternal body and their mechanistic contributions to maternal physiology and pathophysiology are not yet fully defined. Fetal cells and EVs may help remodel maternal organs after pregnancy‐associated changes, but the cell types and EV cargos reaching the mother in preterm pregnancies after exposure to various risk factors can be distinct from term pregnancies. As preterm delivery‐associated maternal complications are rising, revisiting this topic and formulating scientific questions for future research to reduce the risk of maternal morbidities are timely. Epidemiological studies report maternal cardiovascular risk as one of the major complications after preterm delivery. This paper suggests a potential link between fMCs and circulating EVs and adverse maternal cardiovascular outcomes post‐pregnancies, the underlying mechanisms, consequences, and methods for and how this link might be assessed.
Leveraging machine learning to dissect role of combinations of amino acids in modulating the effect of zinc on mammalian cell growth
Authors: Pandey Ujjiti , Madhugiri Indrani , Gadgil Chetan , Gadgil Mugdha 
Published: February 2024

AbstractAlthough the contributions of individual components of cell culture media are largely known, their combinatorial effects are far less understood. Experiments varying one component at a time cannot identify combinatorial effects, and analysis of the large number of experiments required to decipher such effects is challenging. Machine learning algorithms can help in the analysis of such datasets to identify multi‐component interactions. Zinc toxicity in vitro is known to change depending on amino acid concentration in the extracellular medium. Multiple amino acids are known to be involved in this protection. Thirty‐two amino acid compositions were formulated to evaluate their effect on the growth of CHO cells under high zinc conditions. A sequential machine learning analysis methodology was used, which led to the identification of a set of amino acids (threonine, proline, glutamate, aspartate, asparagine, and tryptophan) contributing to protection from zinc. Our results suggest that a decrease in availability of these set of amino acids due to consumption may affect cell growth in media formulated with high zinc concentrations, and in contrast, normal levels of these amino acids are associated with better tolerance to high zinc concentration. Our sequential analysis method may be similarly employed for high throughput medium design and optimization experiments to identify interactions among a large number of cell culture medium components.
Green Synthesis of Selenium Nanoparticles using Green Coffee Beans: An Optimization Study
Authors: Baluken Pınar , Kamiloglu Aybike , Kutlu Naciye 
Published: February 2024

AbstractIn this study, ultrasonication extraction of some bioactive compounds from green coffee beans was optimized with the response surface method using Box‐Behnken experimental design. The best condition was selected as 90.90 W ultrasonic power, 33.63 min sonication time and 30 % solid concentration. The responses obtained under optimum conditions had TPC, DPPH and CUPRAC values identified as 6603.33±2025.94 ppm GAE, 9638.31±372.17 ppm TE and 98.83 mmol, respectively. Microwave‐assisted selenium nanoparticle production was carried out using the extract obtained under optimized conditions. The produced selenium nanoparticles showed absorbance between 350–400 nm. The surface morphology and size of the nanoparticles were determined by transmission electron microscopy (TEM) and spherical nanoparticles of about 100 nm were produced. Functional groups affecting the reduction were determined by FTIR analysis. In addition, the produced selenium nanoparticles had amorphous (non‐uniform) structure and could maintain their stability at high temperatures.
Rational Design of a Circularly Permuted Flavin‐Based Fluorescent Protein
Authors: Anderson Nolan T. , Xie Jason S. , Chacko Asish N. , Liu Vannie L. , Fan Kang‐Ching , Mukherjee Arnab 
Published: February 2024

AbstractFlavin‐based fluorescent proteins are oxygen‐independent reporters that hold great promise for imaging anaerobic and hypoxic biological systems. In this study, we explored the feasibility of applying circular permutation, a valuable method for the creation of fluorescent sensors, to flavin‐based fluorescent proteins. We used rational design and structural data to identify a suitable location for circular permutation in iLOV, a flavin‐based reporter derived from A. thaliana. However, relocating the N‐ and C‐termini to this position resulted in a significant reduction in fluorescence. This loss of fluorescence was reversible, however, by fusing dimerizing coiled coils at the new N‐ and C‐termini to compensate for the increase in local chain entropy. Additionally, by inserting protease cleavage sites in circularly permuted iLOV, we developed two protease sensors and demonstrated their application in mammalian cells. In summary, our work establishes the first approach to engineer circularly permuted FbFPs optimized for high fluorescence and further showcases the utility of circularly permuted FbFPs to serve as a scaffold for sensor engineering.
Enantioselective separation and determination of ibuprofen: Stereoselective pharmacokinetics, pharmacodynamics and analytical methods
Authors: Vashistha Vinod Kumar , Kumar Tarun , Yadav Suman , Das Dipak Kumar 
Published: February 2024

AbstractIbuprofen (IBP), the 29th most prescribed drug in the United States in 2019, is a widely used nonsteroidal anti‐inflammatory drug (NSAID) comprising two enantiomers, (R)‐IBP and (S)‐IBP, collectively known as (RS)‐IBP. This critical review examines analytical techniques for the enantioselective separation and determination of IBP enantiomers, crucial for pharmaceutical and clinical applications. The review focuses on state‐of‐the‐art methods, including chromatographic techniques including high‐performance liquid chromatography, gas chromatography, liquid chromatography–tandem mass spectrometry, and some other techniques. This review addresses pharmacokinetics, pharmacology, and side effects of each enantiomer, ensuring safe drug usage. By consolidating diverse analytical methods and their applicability in different matrices, this review serves as a valuable resource for researchers, analysts, and practitioners in pharmaceutical analysis, pharmacology, and clinical studies.
Optimizing nanofluid additives for enhanced thermophysical properties in anionic crude oil for EOR applications
Authors: Heris Saeed Zeinali , Bagheri Hamid , Mousavi Seyed Borhan , Hosseini Nami Shamin 
Published: February 2024

AbstractThis research delved into the effects of introducing multi‐walled carbon nanotubes (MWCNTs) and sodium dodecyl sulphate (SDS) into crude oil with an anionic base, aiming to enhance its thermophysical attributes in the EOR process. The investigation encompassed a range of properties, including interfacial tension, viscosity, density, and electrical conductivity, measured using an LV rheometer with spindle 18. Various ratios of MWCNTs and SDS were mixed with the crude oil to evaluate their impacts. The study uncovered that the 1:1 ratio of MWCNTs to SDS achieved a noteworthy 10% reduction in interfacial tension while minimally affecting viscosity, showing promise for practical applications. Temperature had diverse effects on viscosity and interfacial tension, displaying fluctuating trends. The highest observed result was a substantial 190% viscosity increase at 40°C with a 2:1 ratio, whereas the lowest was a slight −0.81% density change at 60°C for the 1:1 ratio. Additionally, interfacial tension consistently decreased over time for all ratios at various temperatures, with the most significant reductions observed at 40 and 60°C, particularly for the 1:2 and 1:1 ratios. Furthermore, adding MWCNTs and SDS led to a remarkable drop in electrical conductivity, indicating a substantial decrease in salt content within the crude oil. However, it was noted that higher MWCNT concentrations might not be cost‐effective, emphasizing the importance of optimizing additive ratios for a balance between performance and economic viability. This study highlights the potential of tailored nanofluid formulations to improve the thermophysical properties of crude oil, potentially enhancing extraction and refining processes.
Nano‐Engineering Strategies for Tumor‐Specific Therapy
Authors: Li Zijin , Xie Hai‐Yan , Nie. Weidong 
Published: February 2024

AbstractNanodelivery systems (NDSs) provide promising prospects for decreasing drug doses, reducing side effects, and improving therapeutic effects. However, the bioapplications of NDSs are still compromised by their fast clearance, indiscriminate biodistribution, and limited tumor accumulation. Hence, engineering modification of NDSs aiming at promoting tumor‐specific therapy and avoiding systemic toxicity is usually needed. An NDS integrating various functionalities, including flexible camouflage, specific biorecognition, and sensitive stimuli‐responsiveness, into one sequence would be “smart” and highly effective. Herein, we systematically summarize the related principles, methods, and progress. At the end of the review, we predict the obstacles to precise nanoengineering and prospects for the future application of NDSs.
Time‐based DDoS attack detection through hybrid LSTM‐CNN model architectures: An investigation of many‐to‐one and many‐to‐many approaches
Authors: Habib Beenish , Khursheed Farida 
Published: February 2024

SummaryInternet data thefts, intrusions and DDoS attacks are some of the big concerns for the network security today. Detection of these anomalies, is gaining tremendous impetus with the development of machine learning and artificial intelligence. Even now researchers are shifting the base from machine learning to the deep neural architectures with auto‐feature selection capabilities. We in this paper propose multiple deep neural network architectures which can select, co‐learn and teach the gradients of the neural network by itself with no human intervention. This is what we call as meta‐learning. The models are configured in both many to one and many to many design architectures. We combine long short‐term memory (LSTM), bi‐directional long short‐term memory (BiLSTM), convolutional neural network (CNN) layers along with attention mechanism to achieve the higher accuracy values among all the available deep learning model architectures. LSTMs overcomes the vanishing and exploding gradient problem of RNN and attention mechanism mimics the human cognitive attention that screens the network flow to obtain the key features for network traffic classification. In addition, we also add multiple convolutional layers to get the key features for network traffic classification. We get the time series analysis of the traffic done for the possibility of a DDoS attack without using any feature selection techniques and without balancing the dataset. The performance analysis is done based on confusion matrix scores, that is, accuracy, false alarm rate (FAR), sensitivity, specificity, false‐positive rate (FPR), F1 score, area under curve (AUC) analysis and loss functions on well‐known public benchmark KDD Cup'99 data set. The results of our experiments reveal that our models outperform existing techniques, showing their superiority in performance.