bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic Determinants of Tigecycline Resistance in Mycobacteroides abscessus
Authors: Ng Hien Fuh , Ngeow Yun Fong
Published: April 2022

Mycobacteroides abscessus (formerly Mycobacterium abscessus) is a clinically important, rapid-growing non-tuberculous mycobacterium notoriously known for its multidrug-resistance phenotype. The intrinsic resistance of M. abscessus towards first- and second-generation tetracyclines is mainly due to the over-expression of a tetracycline-degrading enzyme known as MabTetX (MAB_1496c). Tigecycline, a third-generation tetracycline, is a poor substrate for the MabTetX and does not induce the expression of this enzyme. Although tigecycline-resistant strains of M. abscessus have been documented in different parts of the world, their resistance determinants remain largely elusive. Recent work on tigecycline resistance or reduced susceptibility in M. abscessus revealed the involvement of the gene MAB_3508c which encodes the transcriptional activator WhiB7, as well as mutations in the sigH-rshA genes which control heat shock and oxidative-stress responses. The deletion of whiB7 has been observed to cause a 4-fold decrease in the minimum inhibitory concentration of tigecycline. In the absence of environmental stress, the SigH sigma factor (MAB_3543c) interacts with and is inhibited by the anti-sigma factor RshA (MAB_3542c). The disruption of the SigH-RshA interaction resulting from mutations and the subsequent up-regulation of SigH have been hypothesized to lead to tigecycline resistance in M. abscessus. In this review, the evidence for different genetic determinants reported to be linked to tigecycline resistance in M. abscessus was examined and discussed.
Antibiotic Use before, during, and after Seeking Care for Acute Febrile Illness at a Hospital Outpatient Department: A Cross-Sectional Study from Rural India
Authors: Holloway Bronwen , Chandrasekar Harshitha , Purohit Manju , Sharma Ashish , Mathur Aditya , KC Ashish , Fernandez-Carballo Leticia , Dittrich Sabine , Hildenwall Helena , Bergström Anna
Published: April 2022

Antibiotic resistance is a naturally occurring phenomenon, but the misuse and overuse of antibiotics is accelerating the process. This study aimed to quantify and compare antibiotic use before, during, and after seeking outpatient care for acute febrile illness in Ujjain, India. Data were collected through interviews with patients/patient attendants. The prevalence and choice of antibiotics is described by the WHO AWaRe categories and Anatomical Therapeutic Chemical classes, comparing between age groups. Units of measurement include courses, encounters, and Defined Daily Doses (DDDs). The antibiotic prescription during the outpatient visit was also described in relation to the patients’ presumptive diagnosis. Of 1000 included patients, 31.1% (n = 311) received one antibiotic course, 8.1% (n = 81) two, 1.3% (n = 13) three, 0.4% (n = 4) four, 0.1% (n = 1) five, and the remaining 59.0% (n = 590) received no antibiotics. The leading contributors to the total antibiotic volume in the DDDs were macrolides (30.3%), combinations of penicillins, including β-lactamase inhibitors (18.8%), tetracyclines (14.8%), fluoroquinolones (14.6%), and third-generation cephalosporins (13.7%). ‘Watch’ antibiotics accounted for 72.3%, 52.7%, and 64.0% of encounters before, during, and after the outpatient visit, respectively. Acute viral illness accounted for almost half of the total DDDs at the outpatient visit (642.1/1425.3, 45.1%), for which the macrolide antibiotic azithromycin was the most frequently prescribed antibiotic (261.3/642.1, 40.7%).
Influence of Anti-Infective Periodontal Therapy on Subgingival Microbiota Evaluated by Chair-Side Test Compared to qPCR—A Clinical Follow-Up Study
Authors: Laugisch Oliver , Auschill Thorsten M. , Tumbrink Anne , Sculean Anton , Arweiler Nicole B.
Published: April 2022

A chair-side test (CST) for five periodontal pathogens (Aggregatibacter actinomycetemcomitans, A.a.; Porphyromonas gingivalis, P.g.; Prevotella intermedia, P.i.; Treponema denticola, T.d.; Tannerella forsythia, T.f.) was compared with qPCR in a previous clinical study on 100 periodontitis patients at first diagnosis (T0). Following non-surgical treatment alone (SRP) or in combination with systemic or local antibiotics, 74 patients (57.4 ± 13.5 years) were again tested at the same sites from 14 to 24 months after T0. Bacterial elimination (%; compared to T0) was determined for each single species and compared between both test systems. In all patients, all five pathogens could not be fully eliminated regardless of therapy or test method. Tested with CST, the mean elimination ranged from 90% for SRP + Amoxicillin/Metronidazole to 59.13% for SRP only. The corresponding qPCR values were 30% and 29.6%. Only A.a. was eradicated in 100% by SRP + Amoxicillin/Metronidazole tested by CST, and it was 80% when qPCR was the test method. CST agreed with qPCR in 98.7% in the detection of A.a., and 74.3%, 78.4%, 73.0%, and 48.7% for P.g., P.i., T.d., and T.f., respectively. Neither conventional treatment nor the additional use of antibiotics—even with the correct indication—could completely eradicate the tested pathogens or prevent pocket reinfection.
Hypoxia-Induced Aquaporins and Regulation of Redox Homeostasis by a Trans-Plasma Membrane Electron Transport System in Maize Roots
Authors: Hofmann Anne , Wienkoop Stefanie , Lüthje Sabine
Published: April 2022

In plants, flooding-induced oxygen deficiency causes severe stress, leading to growth reduction and yield loss. It is therefore important to understand the molecular mechanisms for adaptation to hypoxia. Aquaporins at the plasma membrane play a crucial role in water uptake. However, their role during hypoxia and membrane redox changes is still not fully understood. The influence of 24 h hypoxia induction on hydroponically grown maize (Zea mays L.) was investigated using an oil-based setup. Analyses of physiological parameters revealed typical flooding symptoms such as increased ethylene and H2O2 levels, an increased alcohol dehydrogenase activity, and an increased redox activity at the plasma membrane along with decreased oxygen of the medium. Transcriptomic analysis and shotgun proteomics of plasma membranes and soluble fractions were performed to determine alterations in maize roots. RNA-sequencing data confirmed the upregulation of genes involved in anaerobic metabolism, biosynthesis of the phytohormone ethylene, and its receptors. Transcripts of several antioxidative systems and other oxidoreductases were regulated. Mass spectrometry analysis of the plasma membrane proteome revealed alterations in redox systems and an increased abundance of aquaporins. Here, we discuss the importance of plasma membrane aquaporins and redox systems in hypoxia stress response, including the regulation of plant growth and redox homeostasis.
Intranasal Administration of Nanovectorized Docosahexaenoic Acid (DHA) Improves Cognitive Function in Two Complementary Mouse Models of Alzheimer’s Disease
Authors: Zussy Charleine , John Rijo , Urgin Théo , Otaegui Léa , Vigor Claire , Acar Niyazi , Canet Geoffrey , Vitalis Mathieu , Morin Françoise , Planel Emmanuel , Oger Camille , Durand Thierry , Rajshree Shinde L. , Givalois Laurent , Devarajan Padma V. , Desrumaux Catherine
Published: April 2022

Polyunsaturated fatty acids (PUFAs) are a class of fatty acids that are closely associated with the development and function of the brain. The most abundant PUFA is docosahexaenoic acid (DHA, 22:6 n-3). In humans, low plasmatic concentrations of DHA have been associated with impaired cognitive function, low hippocampal volumes, and increased amyloid deposition in the brain. Several studies have reported reduced brain DHA concentrations in Alzheimer’s disease (AD) patients’ brains. Although a number of epidemiological studies suggest that dietary DHA consumption may protect the elderly from developing cognitive impairment or dementia including AD, several review articles report an inconclusive association between omega-3 PUFAs intake and cognitive decline. The source of these inconsistencies might be because DHA is highly oxidizable and its accessibility to the brain is limited by the blood–brain barrier. Thus, there is a pressing need for new strategies to improve DHA brain supply. In the present study, we show for the first time that the intranasal administration of nanovectorized DHA reduces Tau phosphorylation and restores cognitive functions in two complementary murine models of AD. These results pave the way for the development of a new approach to target the brain with DHA for the prevention or treatment of this devastating disease.
Quantification of Amino Acids, Phenolic Compounds Profiling from Nine Rice Varieties and Their Antioxidant Potential
Authors: Tyagi Akanksha , Lim Min-Jin , Kim Nam-Hyeon , Barathikannan Kaliyan , Vijayalakshmi Selvakumar , Elahi Fazle , Ham Hun-Ju , Oh Deog-Hwan
Published: April 2022

In recent years, the health benefits of the pigmented rice varieties have been reported due to the richness of their bioactive compounds. Therefore, this study evaluated the antioxidant, total flavonoid, total phenolic, anthocyanin content, amino acid and individual phenolic compound quantification of nine Korean-grown rice varieties using spectrophotometric, HPLC-FLD-MS/MS and UHPLC Q-TOF-MS/MS methods. Our research found that the free fractions of DM29 (red rice) had the highest free radical scavenging ability of ABTS and DPPH. In contrast, the highest ferric reducing antioxidant power was observed in the 01708 brown rice variety. The majority of phenolic compounds such as quercetin, ferulic acid, p-coumaric acid, ascorbic acid, caffeic acid and genistein were found in the DM29 sample. The phenolic content of rice varies depending on its color, with DM29 red rice having the highest TPC, TFC and TAC levels. At the same time, the presence of the majority of amino acids was quantified in the 01708 and GR (Gangwon) brown rice varieties. According to this study, colored rice varieties are high in amino acids, phenolic compounds and antioxidants. This research would be beneficial in furthering our understanding of the nutritional value of different colors of rice and their high potential as a natural antioxidant.
Oxidative Stress and Exercise
Authors: Davison Gareth W. , McClean Conor
Published: April 2022

It is now well-established that regular moderate-intensity exercise training can activate salient cell adaptive properties, leading to a state of oxidative eustress [...]
Deformation and Control of Super-Large-Diameter Shield in the Upper-Soft and Lower-Hard Ground Crossing the Embankment
Authors: You Shuang , Sun Jianan
Published: April 2022

Compared with the small diameter and the single stratum shield tunnel, the surface subsidence is much greater when the large-diameter shield passes through the upper-soft and lower-hard stratum. In this case, it is particularly important to control the deformation of the embankment when the large-diameter shield passes underneath the embankment. Taking a tunnel project underneath the north embankment in Zhuhai as an engineering example, this paper investigates the deformation characteristics and safety control measures of a super-large-diameter (i.e., 15.80 m) shield tunnel underneath the embankment under complex stratum conditions in upper-soft and lower-hard strata, using on-site monitoring and three-dimensional numerical simulations. The results of the numerical simulation show that grouting can effectively reduce the settlement of the embankment. Grouting is applied to practical engineering, and the monitoring data are in agreement with the numerical simulation results. The surface subsidence of the embankment gradually increases as the shield tail leaves the monitoring section and finally stabilizes. After the shield machine has passed through the embankment, the horizontal deformation troughs on the embankment’s surface conform to the Gaussian normal distribution. The maximum settlement occurs in the area directly above the central axis of the tunnel. The deformation trough covers an area about four times the diameter of the tunnel on both sides of its center line.
Applying a Deep Learning Neural Network to Gait-Based Pedestrian Automatic Detection and Recognition
Authors: Lin Chih-Lung , Fan Kuo-Chin , Lai Chin-Rong , Cheng Hsu-Yung , Chen Tsung-Pin , Hung Chao-Ming
Published: April 2022

Gait recognition is a noncontact biometric procedure that determines the identity or health status of a person by analyzing his or her walking posture and habits, including skeletal and joint movements. The most remarkable feature of this method is the possibility of conducting recognition without demanding much cooperation from participants. Therefore, this recognition technique has attracted much attention from scholars. Additionally, because of the rapid development of graphics processing unit technology, related hardware and computation performance, the applications of deep-learning technology are considerably enhanced. The objective of this study was to apply a deep neural network (DNN), which employs deep-learning technology, to achieve gait-based automatic pedestrian detection and recognition. In contrast to using wearable devices to precisely capture skeletal and joint movements, pedestrian color-image sequences were used as input in this study. Subsequently, a pretraining convolutional neural network (CNN) was employed to capture pedestrian location and extract pedestrian dense optical flow to serve as concrete low-level feature inputs. Then, a finely-tuned DNN based on the wide residual network was employed to extract high-level abstract features. In addition, to overcome the difficulty of obtaining local temporal features by using a 2D CNN, part of the 3D convolutional structure was introduced into the CNN. This design enabled use of limited memory to acquire more effective features and enhance the DNN performance. The experimental results show that the proposed method has exceptional performance for pedestrian detection and recognition.
Robustness of Model-Predictive and Passivity-Based Control in the Three-Phase DC/AC Converter Application
Authors: Dyga Łukasz , Alhasheem Mohammed , Davari Pooya , Rymarski Zbigniew
Published: April 2022

In modern controller design, various solutions for controlling power converter systems can be found depending on their applications, speed of working, pulse width modulation (PWM) techniques, switching frequencies—fc, and different load types. The need to manipulate control parameters can be often observed in classical structures, e.g., well-known PID, repetitive, or deadbeat control particularly sensitive to distinct parameters uncertainties. The purpose of this paper is to present an improved version of controllers designated for a UPS that will be considerably resistant to model changes. Proposed control techniques are independent of unexpected output filter changes: Lf—filter coil inductance and Cf—filter capacitor conductance. The second aspect of this paper is to compare effectiveness of modified predictive MPC (model-predictive control) and feedback PBC (passivity-based control) controllers in reducing output voltage total harmonic distortion (THD) for various load values. The biggest distortions of output voltage were observed during experiments with nonlinear RC load. Both simulation and experimental verification of mismatching parameters were performed and examined. Thanks to the proposed solution, the output voltage THDv quality factor was reduced below 8% in an efficient way for all the applied loads and stayed at the level of 1% when well-matched filter parameters were provided.
Hourly Power Consumption Forecasting Using RobustSTL and TCN
Authors: Lin Chih-Hsueh , Nuha Ulin , Lin Guang-Zhi , Lee Tsair-Fwu
Published: April 2022

Power consumption forecasting is a crucial need for power management to achieve sustainable energy. The power demand is increasing over time, while the forecasting of power consumption possesses challenges with nonlinearity patterns and various noise in the datasets. To this end, this paper proposes the RobustSTL and temporal convolutional network (TCN) model to forecast hourly power consumption. Through the RobustSTL, instead of standard STL, this decomposition method can extract time series data despite containing dynamic patterns, various noise, and burstiness. The trend, seasonality, and remainder components obtained from the decomposition operation can enhance prediction accuracy by providing significant information from the dataset. These components are then used as input for the TCN model applying deep learning for forecasting. TCN employing dilated causal convolutions and residual blocks to extract long-term data patterns outperforms recurrent networks in time series forecasting studies. To assess the proposed model, this paper conducts a comparison experiment between the proposed model and counterpart models. The result shows that the proposed model can grasp the rules of historical time series data related to hourly power consumption. Our proposed model overcomes the counterpart schemes in MAPE, MAE, and RMSE metrics. Additionally, the proposed model obtains the best results in precision, recall, and F1-score values. The result also indicates that the predicted data can fit the pattern of the actual data.
A Frame-to-Frame Scan Matching Algorithm for 2D Lidar Based on Attention
Authors: Huang Shan , Huang Hong-Zhong
Published: April 2022

The frame-to-frame scan matching algorithm is the most basic robot localization and mapping module and has a huge impact on the accuracy of localization and mapping tasks. To achieve high-precision localization and mapping, we propose a 2D lidar frame-to-frame scanning matching algorithm based on an attention mechanism called ASM (Attention-based Scan Matching). Inspired by human navigation, we use a heuristic attention selection mechanism that only considers the areas covered by the robot’s attention while ignoring other areas when performing frame-to-frame scan matching tasks to achieve a similar performance as landmark-based localization. The selected landmark is not switched to another one before it becomes invisible; thus, the ASM cannot accumulate errors during the life cycle of a landmark, and the errors will only increase when the landmark switches. Ideally, the errors accumulate every time the robot moves the distance of the lidar sensing range, so the ASM algorithm can achieve high matching accuracy. On the other hand, the number of involved data during scan matching applications is small compared to the total number of data due to the attention mechanism; as a result, the ASM algorithm has high computational efficiency. In order to prove the effectiveness of the ASM algorithm, we conducted experiments on four datasets. The experimental results show that compared to current methods, ASM can achieve higher matching accuracy and speed.
The Effect of Sea Salt with Low Sodium Content on Dough Rheological Properties and Bread Quality
Authors: Voinea Andreea , Stroe Silviu-Gabriel , Ropciuc Sorina , Dabija Adriana , Codină Georgiana Gabriela
Published: April 2022

The aim of this study was to analyze the effects of the addition of sea salt with low sodium content (SS) in a refined wheat flour at the levels of 0.3%, 0.6%, 0.9% 1.2% and 1.5% on the rheological properties of the dough during mixing, extension, pasting and fermentation and the bread quality in terms of bread physical properties, crumb and crust color, texture and sensory characteristics. According to the data we obtained, the SS presented a strengthening effect on the dough network by increasing its stability, dough development time, energy and resistance. Moreover, the SS addition resulted in an increase in dough extensibility, to a delay of the gelatinization process and an increase of the falling number value. The bakery products obtained with the SS were of a higher quality compared to the control sample, presenting better physical and textural characteristics, a darker color and being more appreciated by consumers with the increased level of SS addition in the wheat flour. According to the sodium content from the bread recipe, the bread samples obtained may be classified as products with a very low sodium content of up to a 0.6% SS addition in the wheat flour or with a low sodium content if at least 0.9% SS is contained in the bread recipe.
Citation Oriented AuthorRank for Scientific Publication Ranking
Authors: Zhang Jinsong , Liu Xiaozhong
Published: April 2022

It is now generally accepted that an article written by influential authors often deserves a higher ranking in information retrieval. However, it is a challenging task to determine an author’s relative influence since information about the author is, much of the time, inaccessible. Actually, in scientific publications, the author is an important metadata item, which has been widely used in previous studies. In this paper, we bring an optimized AuthorRank, which is a topic-sensitive algorithm calculated by citation context, into citation analysis for testing whether and how topical AuthorRank can replace or enhance classical PageRank for publication ranking. For this purpose, we first propose a PageRank with Priors (PRP) algorithm to rank publications and authors. PRP is an optimized PageRank algorithm supervised by the Labeled Latent Dirichlet Allocation (Labeled-LDA) topic model with full-text information extraction. We then compared four methods of generating an AuthorRank score, looking, respectively, at the first author, the last author, the most famous author, and the “average” author (of a publication). Additionally, two combination methods (Linear and Cobb–Douglas) of AuthorRank and PRP were compared with several baselines. Finally, as shown in our evaluation results, the performance of AuthorRank combined with PRP is better (p < 0.001) than other baselines for publication ranking.
Fixed-Bed Adsorption of Phenol onto Microporous Activated Carbon Set from Rice Husk Using Chemical Activation
Authors: Daffalla Samah B. , Mukhtar Hilmi , Shaharun Maizatul S. , Hassaballa Abdalhaleem A.
Published: April 2022

In the course of this research, the potential of activated carbon from rice husk was examined as being a phenol removal medium from an aqueous solution in a fixed-bed adsorption column. The activated carbon was characterized through FESEM (Field-Emission Scanning Electron Microscopy) and BET (Brunauer–Emmett–Teller) surface area. According to the FESEM micrograph and BET surface area, RHAC (rice husk activated carbon) had a porous structure with a large surface area of 587 m2·g−1 and mean diameter of pores of 2.06 nm. The concentration effects on the influent phenol (100–2000 mg·L−1), rate of flow (5–10 mL·min−1), and bed depth (8.5–15.3 cm) were examined. It was found that the capacity of bed adsorption increased according to the increase in the influent concentration and bed depth. However, the capacity of bed adsorption decreased according to the increase in the feed flow rate. The regeneration of activated carbon column using 0.1 M sodium hydroxide was found to be effective with a 75% regeneration efficiency after three regeneration cycles. Data on adsorption were observed to be in line with many well-established models (i.e., Yoon–Nelson and Adams–Bohart, as well as bed depth service time models).
Research on the Centrifugal Driving of a Water-in-Oil Droplet in a Microfluidic Chip with Spiral Microchannel
Authors: Xie Zhongqiang , Cai Yongchao , Wu Jiahao , Xian Zhaokun , You Hui
Published: April 2022

Combining the advantages of droplet-based microfluidics and centrifugal driving, a method for centrifugally driving W/O droplets with spiral microchannel is proposed in this paper. A physical model of droplet flow was established to study the flow characteristics of the W/O droplet in the spiral microchannel driven by centrifugal force, and kinematic analysis was performed based on the rigid body assumption. Then, the theoretical formula of droplet flow rate was obtained. The theoretical value was compared with the actual value measured in the experiments. The result shows that the trend of the theoretical value is consistent with the measured value, and the theoretical value is slightly larger than the experimentally measured value caused by deformation. Moreover, it is found that the mode of centrifugal driving with spiral microchannel has better flow stability than the traditional centrifugal driving structure. A larger regulation speed range can be achieved by adjusting the motor speed without using expensive equipment or precise instruments. This study can provide a basis and theoretical reference for the development of droplet-based centrifugal microfluidic chips.
Applying Taguchi Methodology to Optimize the Brain Image Quality of 128-Sliced CT: A Feasibility Study
Authors: Tseng Hsien-Chun , Lin Hung-Chih , Tsai Yu-Che , Lin Cheng-Hsun , Changlai Sheng-Pin , Lee Yueh-Chun , Chen Chien-Yi
Published: April 2022

Injuries due to traffic accidents have been significant causes of death in Taiwan and traffic accidents have been most common in recent years. Brain computed tomography (CT) examinations can improve imaging quality and increase the value of an imaging diagnosis. The image quality of the brain gray/white matter was optimized using the Taguchi design with an indigenous polymethylmethacrylate (PMMA) slit gauge to imitate the adult brain and solid water phantoms. The two gauges without coating contrast media were located inside the center of a plate to simulate the brain and scanned to obtain images for further analysis. Five major parameters—CT slice thickness, milliampere-seconds, current voltage, filter type, and field of view—were optimized. Analysis of variance was used to determine individual interactions among all control parameters. The optimal experimental acquisition/settings were: slice thickness 2.5 mm, 300 mAs, 140 kVp, smooth filter, and FOV 200 mm2. Signal-to-noise was improved by 106% (p < 0.001) over a routine examination. The effective dose (HE) is approximately 1.33 mSv. Further clinical verification and the image quality of the ACR 464 head phantom is also discussed.
Efficient Open-Set Recognition for Interference Signals Based on Convolutional Prototype Learning
Authors: Chen Xiangwei , Zhao Zhijin , Ye Xueyi , Zheng Shilian , Lou Caiyi , Yang Xiaoniu
Published: April 2022

Interference classification plays an important role in anti-jamming communication. Although the existing interference signal recognition methods based on deep learning have a higher accuracy than traditional methods, these have poor robustness while rejecting interference signals of unknown classes in interference open-set recognition (OSR). To ensure the classification accuracy of the known classes and the rejection rate of the unknown classes in interference OSR, we propose a new hollow convolution prototype learning (HCPL) in which the inner-dot-based cross-entropy loss (ICE) and the center loss are used to update prototypes to the periphery of the feature space so that the internal space is left for the unknown class samples, and the radius loss is used to reduce the impact of the prototype norm on the rejection rate of unknown classes. Then, a hybrid attention and feature reuse net (HAFRNet) for interference signal classification was designed, which contains a feature reuse structure and hybrid domain attention module (HDAM). A feature reuse structure is a simple DenseNet structure without a transition layer. An HDAM can recalibrate both time-wise and channel-wise feature responses by constructing a global attention matrix automatically. We also carried out simulation experiments on nine interference types, which include single-tone jamming, multitone jamming, periodic Gaussian pulse jamming, frequency hopping jamming, linear sweeping frequency jamming, second sweeping frequency jamming, BPSK modulation jamming, noise frequency modulation jamming and QPSK modulation jamming. The simulation results show that the proposed method has considerable classification accuracy of the known classes and rejection performance of the unknown classes. When the JNR is −10 dB, the classification accuracy of the known classes of the proposed method is 2–7% higher than other algorithms under different openness. When the openness is 0.030, the unknown class rejection performance plateau of the proposed method reaches 0.9883, while GCPL is 0.9403 and CG-Encoder is 0.9869; when the openness is 0.397, the proposed method is more than 0.89, while GCPL is 0.8102 and CG-Encoder is 0.9088. However, the rejection performance of unknown classes of CG-Encoder is much worse than that of the proposed method under low JNR. In addition, the proposed method requires less storage resources and has a lower computational complexity than CG-Encoder.
The Optimal Tolerance Solution of the Basic Interval Linear Equation and the Explanation of the Lodwick’s Anomaly
Authors: Piegat Andrzej , Pluciński Marcin
Published: April 2022

Determining the tolerance solution (TS) of interval linear systems (ILSs) has been a task under consideration for many years. It seems, however, that this task has not been fully and unequivocally solved. This is evidenced by the multiplicity of proposed methods (which sometimes provide different results), the existence of many questions, and the emergence of strange solutions provided by, for example, Lodwick’s interval equation anomaly (LIEA). The problem of solving ILEs is probably more difficult than we think. The article presents a new method of ILSs solving, but it is limited to the simplest, basic equation [a̲,a¯]X=[b̲,b¯], which is an element of all more complex forms of ILSs. The method finds the optimal TS for this equation by using multidimensional interval arithmetic (MIA). According to the authors’ knowledge, this is a new method and it will allow researchers to solve more complex forms of ILSs and various types of nonlinear interval equations. It can also be used to solve fuzzy linear systems (FLSs). The paper presents several examples of the method applications (including one real-life case).
Effects of Atmospheric Heat Source on the Tibetan Plateau Vortex in Different Stages: A Case Study in June 2016
Authors: Zhou Shu , Sun Fang , Wang Meirong , Zhou Shunwu , Qing Yiyu
Published: April 2022

The Tibetan Plateau (TP) vortex (TPV), one of the crucial weather systems triggering rainfall, plays a key role in modulating precipitation over TP and downstream regions. The role of atmospheric heat source in TPV development is explored by a case study in June 2016, using high-resolution ERA5 reanalysis, black-body temperature (TBB) obtained from the Fengyun-2E (FY-2E) satellite, and precipitation amount from the Tropical Rainfall Measurement Mission (TRMM). The evolutions of TPV can be split into three stages, i.e., generation, development, and pre-moving-off stage. The intensity of TPV increases with fluctuations, with weaker and shallower TPV in the generation stage, strongest in the development stage and deepest in the pre-moving-off stage. Importantly, the genesis of TPV is related to the surface warming center driven by surface sensible heating while its development is primarily dependent on the latent heat of condensation. The main contributor of the latent heat of condensation is further analyzed as a vertical transport of the water vapor that promotes TPV development.
Seasonal Climate Trends across the Wild Blueberry Barrens of Maine, USA
Authors: Tasnim Rafa , Birkel Sean , Calderwood Lily , Roberts Samuel , Zhang Yong-Jiang
Published: April 2022

Wild blueberries in Maine, USA are facing threats from our changing climate. While summer climate variations have been affecting this important commercial crop directly, significant climate variations in other seasons also can be potentially detrimental to blueberry production. Therefore, we analyzed annual and seasonal climate trends (temperature, rainfall, snow cover) over the past 41 years (1980–2020) for seven Maine counties (Piscataquis, Washington, Hancock, Knox, Lincoln, Kennebec, York) with large wild blueberry areas. We found that, across all blueberry production fields (or “barrens”), historical temperatures increased significantly (p < 0.05) in the fall and winter followed by summer, but not in the spring. Additionally, precipitation increased slightly (0.5–1.2 mm/year) in the winter and fall, whereas no changes were found in the spring and summer. Furthermore, we found that historical temperatures were lower in Piscataquis (north-central) and Washington (north-east) counties, whereas in south-western counties (Hancock to York) experienced a relatively warmer climate. The rate of increasing temperature was comparatively slower in the warmer barrens located towards the south-west (Hancock to York). Moreover, the growing season lengthened towards the fall season consistently in all locations, whereas lengthening towards the spring was inconsistent. These findings inform the wild blueberry growers in different locations of Maine about the seasonal shifts occurring for their crop. This knowledge may assist with land management planning in order for the growers to prepare for future impacts.
Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations
Authors: Luffarelli Marta , Govaerts Yves , Franceschini Lucio
Published: April 2022

The Combined Inversion of Surface and AeRosols (CISAR) algorithm for the joint retrieval of surface and aerosol single scattering properties has been further developed in order to extend the retrieval to clouds and overcome the need for an external cloud mask. Pixels located in the transition zone between pure cloud and pure aerosol are often discarded by both aerosol and cloud algorithms, despite being essential for studying aerosol–cloud interactions, which still represent the largest source of uncertainty in climate predictions. The proposed approach aims at filling this gap and deepening the understanding of aerosol properties in cloudy environments. The new CISAR version is applied to Sentinel-3A/SLSTR observations and evaluated against different satellite products and ground measurements. The spatial coverage is greatly improved with respect to algorithms processing only pixels flagged as clear sky by the SLSTR cloud mask. The continuous retrieval of aerosol properties without any safety zone around clouds opens new possibilities for studying aerosol properties in cloudy environments.
Functional Remodeling of the Contractile Smooth Muscle Cell Cortex, a Provocative Concept, Supported by Direct Visualization of Cortical Remodeling
Authors: Suphamungmee Worawit , Lehman William , Morgan Kathleen G.
Published: April 2022

Considerable controversy has surrounded the functional anatomy of the cytoskeleton of the contractile vascular smooth muscle cell. Recent studies have suggested a dynamic nature of the cortical cytoskeleton of these cells, but direct proof has been lacking. Here, we review past studies in this area suggesting a plasticity of smooth muscle cells. We also present images testing these suggestions by using the technique of immunoelectron microscopy of metal replicas to directly visualize the cortical actin cytoskeleton of the contractile smooth muscle cell along with interactions by representative cytoskeletal binding proteins. We find the cortical cytoskeletal matrix to be a branched, interconnected network of linear actin bundles. Here, the focal adhesion proteins talin and zyxin were localized with nanometer accuracy. Talin is reported in past studies to span the integrin–cytoplasm distance in fibroblasts and zyxin is known to be an adaptor protein between alpha-actinin and VASP. In response to activation of signal transduction with the alpha-agonist phenylephrine, we found that no movement of talin was detectable but that the zyxin-zyxin spacing was statistically significantly decreased in the smooth muscle cells examined. Contractile smooth muscle is often assumed to have a fixed cytoskeletal structure. Thus, the results included here are important in that they directly support the concept at the electron microscopic level that the focal adhesion of the contractile smooth muscle cell has a dynamic nature and that the protein–protein interfaces showing plasticity are protein-specific.
The Synergistic Cooperation between TGF-β and Hypoxia in Cancer and Fibrosis
Authors: Mallikarjuna Pramod , Zhou Yang , Landström Maréne
Published: April 2022

Transforming growth factor β (TGF-β) is a multifunctional cytokine regulating homeostasis and immune responses in adult animals and humans. Aberrant and overactive TGF-β signaling promotes cancer initiation and fibrosis through epithelial–mesenchymal transition (EMT), as well as the invasion and metastatic growth of cancer cells. TGF-β is a key factor that is active during hypoxic conditions in cancer and is thereby capable of contributing to angiogenesis in various types of cancer. Another potent role of TGF-β is suppressing immune responses in cancer patients. The strong tumor-promoting effects of TGF-β and its profibrotic effects make it a focus for the development of novel therapeutic strategies against cancer and fibrosis as well as an attractive drug target in combination with immune regulatory checkpoint inhibitors. TGF-β belongs to a family of cytokines that exert their function through signaling via serine/threonine kinase transmembrane receptors to intracellular Smad proteins via the canonical pathway and in combination with co-regulators such as the adaptor protein and E3 ubiquitin ligases TNF receptor-associated factor 4 (TRAF4) and TNF receptor-associated factor 6 (TRAF6) to promote non-canonical pathways. Finally, the outcome of gene transcription initiated by TGF-β is context-dependent and controlled by signals exerted by other growth factors such as EGF and Wnt. Here, we discuss the synergistic cooperation between TGF-β and hypoxia in development, fibrosis and cancer.
Recent Advances in Poly(α-L-glutamic acid)-Based Nanomaterials for Drug Delivery
Authors: Zhang Yu , Song Wenliang , Lu Yiming , Xu Yixin , Wang Changping , Yu Deng-Guang , Kim Il
Published: April 2022

Poly(α-L-glutamic acid) (PGA) is a class of synthetic polypeptides composed of the monomeric unit α-L-glutamic acid. Owing to their biocompatibility, biodegradability, and non-immunogenicity, PGA-based nanomaterials have been elaborately designed for drug delivery systems. Relevant studies including the latest research results on PGA-based nanomaterials for drug delivery have been discussed in this work. The following related topics are summarized as: (1) a brief description of the synthetic strategies of PGAs; (2) an elaborated presentation of the evolving applications of PGA in the areas of drug delivery, including the rational design, precise fabrication, and biological evaluation; (3) a profound discussion on the further development of PGA-based nanomaterials in drug delivery. In summary, the unique structures and superior properties enables PGA-based nanomaterials to represent as an enormous potential in biomaterials-related drug delivery areas.
Maximization of the Minicircle DNA Vaccine Production Expressing SARS-CoV-2 RBD
Authors: Ventura Cathy , Eusébio Dalinda , Gonçalves Ana M. , Barroca-Ferreira Jorge , Costa Diana , Cui Zhengrong , Passarinha Luís A. , Sousa Ângela
Published: April 2022

Nucleic acid vaccines have been proven to be a revolutionary technology to induce an efficient, safe and rapid response against pandemics, like the coronavirus disease (COVID-19). Minicircle DNA (mcDNA) is an innovative vector more stable than messenger RNA and more efficient in cell transfection and transgene expression than conventional plasmid DNA. This work describes the construction of a parental plasmid (PP) vector encoding the receptor-binding domain (RBD) of the S protein from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the use of the Design of Experiments (DoE) to optimize PP recombination into mcDNA vector in an orbital shaker. First, the results revealed that host cells should be grown at 42 °C and the Terrific Broth (TB) medium should be replaced by Luria Broth (LB) medium containing 0.01% L-arabinose for the induction step. The antibiotic concentration, the induction time, and the induction temperature were used as DoE inputs to maximize the % of recombined mcDNA. The quadratic model was statistically significant (p-value < 0.05) and presented a non-significant lack of fit (p-value > 0.05) with a suitable coefficient of determination. The optimal point was validated using 1 h of induction, at 30 °C, without the presence of antibiotics, obtaining 93.87% of recombined mcDNA. Based on these conditions, the production of mcDNA was then maximized in a mini-bioreactor platform. The most favorable condition obtained in the bioreactor was obtained by applying 60% pO2 in the fermentation step during 5 h and 30% pO2 in the induction step, with 0.01% L-arabinose throughout 5 h. The yield of mcDNA-RBD was increased to a concentration of 1.15 g/L, when compared to the orbital shaker studies (16.48 mg/L). These data revealed that the bioreactor application strongly incremented the host biomass yield and simultaneously improved the recombination levels of PP into mcDNA. Altogether, these results contributed to improving mcDNA-RBD biosynthesis to make the scale-up of mcDNA manufacture simpler, cost-effective, and attractive for the biotechnology industry.
Genetically Encoded Ratiometric pH Sensors for the Measurement of Intra- and Extracellular pH and Internalization Rates
Authors: Karsten Lennard , Goett-Zink Lukas , Schmitz Julian , Hoffrogge Raimund , Grünberger Alexander , Kottke Tilman , Müller Kristian M.
Published: April 2022

pH-sensitive fluorescent proteins as genetically encoded pH sensors are promising tools for monitoring intra- and extracellular pH. However, there is a lack of ratiometric pH sensors, which offer a good dynamic range and can be purified and applied extracellularly to investigate uptake. In our study, the bright fluorescent protein CoGFP_V0 was C-terminally fused to the ligand epidermal growth factor (EGF) and retained its dual-excitation and dual-emission properties as a purified protein. The tandem fluorescent variants EGF-CoGFP-mTagBFP2 (pK′ = 6.6) and EGF-CoGFP-mCRISPRed (pK′ = 6.1) revealed high dynamic ranges between pH 4.0 and 7.5. Using live-cell fluorescence microscopy, both pH sensor molecules permitted the conversion of fluorescence intensity ratios to detailed intracellular pH maps, which revealed pH gradients within endocytic vesicles. Additionally, extracellular binding of the pH sensors to cells expressing the EGF receptor (EGFR) enabled the tracking of pH shifts inside cultivation chambers of a microfluidic device. Furthermore, the dual-emission properties of EGF-CoGFP-mCRISPRed upon 488 nm excitation make this pH sensor a valuable tool for ratiometric flow cytometry. This high-throughput method allowed for the determination of internalization rates, which represents a promising kinetic parameter for the in vitro characterization of protein–drug conjugates in cancer therapy.
Detection of Unamplified E. coli O157 DNA Extracted from Large Food Samples Using a Gold Nanoparticle Colorimetric Biosensor
Authors: Dester Emma , Kao Kaily , Alocilja Evangelyn C.
Published: April 2022

Rapid detection of foodborne pathogens such as E. coli O157 is essential in reducing the prevalence of foodborne illness and subsequent complications. Due to their unique colorimetric properties, gold nanoparticles (GNPs) can be applied in biosensor development for affordability and accessibility. In this work, a GNP biosensor was designed for visual differentiation between target (E. coli O157:H7) and non-target DNA samples. Results of DNA extracted from pure cultures indicate high specificity and sensitivity to as little as 2.5 ng/µL E. coli O157 DNA. Further, the biosensor successfully identified DNA extracted from flour contaminated with E. coli O157, with no false positives for flour contaminated with non-target bacteria. After genomic extraction, this assay can be performed in as little as 30 min. In addition, food sample testing was successful at detecting approximately 103 CFU/mL of E. coli O157 magnetically extracted from flour after only a 4 h incubation step. As a proof of concept, these results demonstrate the capabilities of this GNP biosensor for low-cost and rapid foodborne pathogen detection.
Modifications of Functional Human Brain Networks by Transcutaneous Auricular Vagus Nerve Stimulation: Impact of Time of Day
Authors: von Wrede Randi , Bröhl Timo , Rings Thorsten , Pukropski Jan , Helmstaedter Christoph , Lehnertz Klaus
Published: April 2022

Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel non-invasive treatment option for different diseases and symptoms, such as epilepsy or depression. Its mechanism of action, however, is still not fully understood. We investigated short-term taVNS-induced changes of local and global properties of EEG-derived, evolving functional brain networks from eighteen subjects who underwent two 1 h stimulation phases (morning and afternoon) during continuous EEG-recording. In the majority of subjects, taVNS induced measurable modifications of network properties. Network alterations induced by stimulation in the afternoon were clearly more pronounced than those induced by stimulation in the morning. Alterations mostly affected the networks’ topology and stability properties. On the local network scale, no clear-cut spatial stimulation-related patterns could be discerned. Our findings indicate that the possible impact of diurnal influences on taVNS-induced network modifications would need to be considered for future research and clinical studies of this non-pharmaceutical intervention approach.
The Percentages of Cognitive Skills Deficits among Chinese Children with Developmental Dyslexia: A Systematic Review and Meta-Analysis
Authors: Li Xin , Hu Mingming , Liang Huadong
Published: April 2022

The current study was conducted to examine the percentages of cognitive skills deficits among Chinese children with developmental dyslexia. Via a systematic review, we collated twenty-two available studies on the proportion of cognitive skills deficits, including phonological awareness, rapid automatized naming, morphological awareness, orthographic knowledge, short-term memory and working memory, and visual and motor skills deficits, among Chinese children with developmental dyslexia. The results of a meta-analysis showed that the rapid automatized naming deficits are the core deficit of developmental dyslexia among Chinese children, with a pooled percentage of 44%. This is followed by orthographic knowledge deficits (43%), phonological awareness deficits (41%), morphological awareness deficits (40%), visual and motor skills deficits (33%), and short-term memory and working memory deficits (25%). At the same time, we compared the proportions of different locations, ages, standards and control groups.