bluuebunny/crossref_metadata_2025 huggingface dataset:
The silica-loaded styrene-butadiene rubber in the presence of stearamide: The tensile modulus and tensile strength
Authors: Dhoni R , Ginting M , Surya I
Published: April 2021

This study investigated the influences of stearamide on the tensile modulus and strength of silica-loaded styrene-butadiene rubber (SBR). The SBR was filled with precipitated silica reinforcing filler at a settled dose (thirty phr) and the stearamide was compounded into the silica-filled SBR with range doses from two to eight phr. The influences of stearamide incorporation on the tensile moduli i.e. M300 and M100, tensile strength and also breaking elongation of silica-filled SBR were studied. It was revealed that the stearamide caused pronounced affection in tensile properties of the SBR. The stearamide increased tensile strength and modulus up to a six phr of dose. The improvement in tensile moduli and strength was because of the role of stearamide as the extra plasticizing agent for the silica-filled SBR. The oily property of stearamide improved the silica dispersion and crosslinks level, respectively.
The effect of amount of hydrogen peroxide on utilization of unsaturated fatty acids from avocado seeds waste into sourcing of raw materials in the making of epoxy compounds
Authors: Sinaga Mersi Suriani , Tambun Rondang , Rahmadani Dea , Mardhiyani Fina Dina
Published: April 2021

Epoxy compounds are compounds that contain oxygen groups that are formed by an epoxidation reaction between peroxide acid with aromatic unsaturated compounds. Epoxy compounds can be applied as stabilizers, plasticizers in PVC (polyvinyl chloride) and can be used as antioxidants in natural rubber processing, as surfactants, anti-corrosive additives in lubricating oils and pesticide raw materials. The raw material in this research is avocado seed oil. The purpose of this study was to determine the effect of catalyst concentration, sulfuric acid, the amount of H2O2 (ml) and stirring speed (rpm) on the characteristics of epoxy compounds. In this study, the fatty acids contained in the raw material were reacted with hexane, glacial acetic acid, H2O2 with variations of 40, 50, 60 and 70 ml, sulfuric acid as a catalyst with a variations of 1.5; 2.0; and 2.5%, stirring speed with a variation of 400, 500, and 600 rpm, a reaction time of 180 minutes. The results showed that the best epoxy compound results were obtained at a catalyst concentration of 2.5%, 70 ml H2O2, reaction time of 180 minutes, and a stirring speed of 600 rpm, which obtained an oxirane oxygen content of 3.552, an iodine number of 1.269 and an oxirane oxygen conversion of 72.489%.
Simulation analysis of bio-oil from slow pyrolysis using palm empty fruit bunch
Authors: Nur T B , Yansen V , Wibowo R P
Published: April 2021

This study analyses the slow pyrolysis process of Palm Empty Fruit Bunches (EFB) from a temperature of 400-650°C in producing bio-oil in the Aspen Plus simulation. The study involves the effect of excess air for the combustion process to supply heat to be used by the pyrolysis process. From the analysis, it was found that the value of energy in the form of heat is present in high amounts if the excess air is around 40%. Heat is then used to heat the biomass, producing syngas, which then passes through a heat exchanger with a copper pipe with a length of 10 m in 200 liters of water. The bio-oil mass flow rate will decrease as the pyrolysis working temperature increased, from 0.38 kg/hour to 0.121 kg/hour, or 0.387 liters/hour to 0.124 liters/hour. The bio-oil heating value will increase with increasing pyrolysis temperature from 8713.68 J/kg to 27,130.92 J/kg, at 400 °C to 650°C, respectively. The amount of bio-oil mass-produced in the simulation compared to the yield during the experiment, and it was found that the simulation results were higher, around 39.08%. That is due to there is some bio-liquid stored at the bottom of syngas storage.
Aminopropyltriethoxy silane in natural rubber/silica composites: Torque and vulcanization properties
Authors: Philbert  , Surya I
Published: April 2021

The performance of rubbers composites in engineering application depend on the compatibility between reinforcing fillers and rubbers. It is a concern especially when forming rubbers composites with much contrasting of polarities between the rubbers matrix and the reinforcing fillers. However, correct compatibilizer will settle the poor interactions. This study; natural rubber (NR)/precipitated silica (PSi) composites were compounded together with aminopropyltriethoxy silane (AS) as a compatibilizer. The AS is one type of silane coupling agents and it was compounded into the composites of NR/PSi with varied doses i.e. one to seven phr. It was found that the AS significantly affected the torque and vulcanization properties of the NR/PSi composites. The AS decreased the viscosity/minimal torque but raised the maximal torque and torque differentiation. It was also found that the AS increased the rate of vulcanization. The increases in the torque and vulcanization properties were presumably attributed to the enhancement in rubber to filler interactions originating from coupling bonds formation in the presence of AS as a compatibilizer. Besides, the AS also role as a plasticizer which increased the degree of filler dispersion of PSi. Therefore, the addition of AS had a considerable potential to compatibilize the non-polar NR and PSi filler.
NR/precipitated silica/dodecanol composites: Torque, hardness and morphology behaviors
Authors: Philbert  , Hafni K N , Surya I
Published: April 2021

The effects of dodecanol (DDC) incorporations on torque, hardness and morphology behaviors/properties of natural rubber (NR)/precipitated silica (PSi) composites were studied using a typical Semi EV. The NR was loaded with the PSi at a settled dose, thirty phr. The DDC is one type of fatty alcohols that is produced based on the oil of palm kernel. The DDC was incorporated toward the PSi-loaded NR systems/compounds with various doses from one to four 4.0 phr. Because of its roles as a co-curing and internal plasticizer, it was revealed that the DDC affected the torque, hardness and morphology properties of PSi-loaded NR systems. The DDC exhibited the enhancements in torque change and hardness, especially till a three phr of DDC dose. The study on morphology behavior confirmed that the three phr of DDC was the optimum dose in which the cracked surface of PSi-loaded NR system with a three phr of DDC displayed the tremendous line of matrix fracture and surface breaking. Based on the overall results, the DDC incorporations caused the PSi-loaded NR systems in a less hardness but a higher torque change.
Redesign packaging on Aloe Vera bottle product based on Kansei Engineering
Authors: Nasution S , Hidayati J , Nissa N A , Agustiara S M
Published: April 2021

Packaged designers must be able to select packaging elements that characterize products, communicate brand products, and create packaging into attractive media to attract consumers to purchase products among the various available products. The aim of this study is to understand visual design concepts and structural design concepts in the design of aloe vera bottled bottles. The method used for the development of a design product that focuses on consumer perceptions and links it with the attributes of the product is Kansei engineering. Kansei engineering is a technology capable of translating consumer feelings into design concepts. Research came up with a visual design concept of the chosen Kansei word, which is elegant, commercial, fresh, modern, varnish, aesthetic, interesting, simple, subjective, summarized. The visual design concept is barcode, nutrition fact-general, 1ogo-word mark, brand top sign, product name-top sign, produce-bearing name, product present composition, family-size approach, back ground cool colors, font color-white, font type-san serif, Figure-original, material label-film plastic, and position label-wrap around label positions. The structural design concept is tropical as the top structure of the bottle, jugo as the center structure of the bottle, plastic colored as bottled material, and the size of the bottle 500 ml.
Index Point Detection for Text Summarization using Cosine Similarity in Educational Videos
Authors: Sharma Rekha , Mahrishi Mehul , Morwal Sudha , Sharma Girish
Published: April 2021

Explosive growth in digital content creates a trend of video-based learning and knowledge sharing. Several educational videos are shared by various trainers/bloggers/ instructors daily. It is now evident that even during emergencies like the recent ongoing CoVid-19 outbreak, video lectures are the saviors when the whole world comes to rest. This rapid and expansive growth has encouraged the researchers to efficiently and automatically index, browse, and retrieve video data. This research aims to process videos and precisely identify the index points which are discussed within the video. Experimental results show a good performance of the topic detection model in finding keywords and reducing dimensionality.
A Review on Segmentation of Vitiligo image
Authors: Agrawal Neha , Aurelia Sagaya
Published: April 2021

Digital image processing is playing a vital role in medical science. Segmentation is a very important and critical step of image processing to analyse the image. Segmentation has become an eminent objective in image analysis and computer vision algorithms. Vitiligo is a very common skin disease that causes depression for the patient suffering from it. In current work, several segmentation techniques like thresholding, watershed, Region-based RAG, Felzenszwalb Segmentation, SLIC - K-Means based image segmentation, and Quickshift image segmentation were analysed along with their experimental results on vitiligo image. The execution time of different algorithms was also measured and analysed. Some of the advantages and disadvantages of applied techniques were discussed.
Stock trend prediction and analysis using LSTM neural network and dual moving average crossover algorithm
Authors: Pradhan Rahul , Bharadwaj Kanishk , Saxena Aman , Rajpoot Vikram
Published: April 2021

In today’s world where data is the new currency, computer machines are capable enough to find and predict the future by using the previous data and the algorithms which are becoming more precise day by day. The proposed solution by us includes the pre-processing of the 10 years of Bombay Stock Exchange (BSE) stock market data of HDFC Bank. Our solution implemented the engineering techniques of deep learning and machine learning which are combined with the LSTM neural network algorithm and Dual Moving Average Crossover algorithm.
Minimizing Respiratory Diseases using Warning from Hand-Touch-Over-Face Avoidance Based Algorithm on Deep Learning
Authors: Bhatia Jitesh Kumar
Published: April 2021

The most moved parts of a human body are hands. They may get contaminated by touching any surface we are working with. The contaminated hands can intentionally or unintentionally reach the part of our face while eating, sneezing, setting of hair, itching a scratch, biting the nails, soothing down when stressed, etc. The touch of hands in eyes, nose and mouth may result in unhygienic symptoms and may result in various respiratory diseases. We need to minimize our touch to the parts of our face. In the presented work, we propose a system that warns the user each time his/her hand reaches his/her face. We have used CNN to identify the class feature automatically rather than manually. Also, we have used RNN so that the proposed system learns recursively. The use of such system may minimize the subsequent touch on face and will lead to minimizing the respiratory diseases due to unhygienic touch conditions.
Impact of Hidden Dense Layers in Convolutional Neural Network to enhance Performance of Classification Model
Authors: Helen Josephine V L , Nirmala A.P. , Alluri Vijaya Lakshmi
Published: April 2021

Education and Health care sectors are two predominant areas where societal growth is expected through innovation and technology development. Machine Learning and Deep learning classification models have been entertained in predicting, detecting, and diagnosing major diseases in the early stage. In this research paper, we have analyzed the impact of hidden dense layers in the Convolution neural network to improve the performance of the classification model. Three different classification deep network models have been constructed, analyzed and the result was tested with a diabetes dataset. Results concluded that the more layers with deeper the network better was the classification performance. The classification model with six hidden dense layers outperforms all other less number of hidden dense layers.
Comparative analysis of machine learning techniques based on chronic kidney disease dataset
Authors: Gulati Vineeta , Raheja Neeraj
Published: April 2021

Kidney failure is one of the chronic diseases that becoming a very common health issue in the world. It is a state in which kidney is damaged and cannot clean blood as well as they should. Excess fluid and waste may cause more health issue in our body and takes long period to diagnose. Moreover, with no early symptoms, the disease is detected only at a later critical end stage. As this Chronic Disease is becoming threat in today’s world, research is being done on a large scale to predict the presence of this chronic disease using machine learning. Machine learning is playing such a tremendous role in healthcare system like identify diseases and diagnoses, drug discovery and manufacturing, smart health record with the use of various techniques like Support Vector Machine, Decision Tree, Naïve Bayes, Random Forest etc. This paper comparatively analyzes the accuracy of pre-existing techniques for prediction of chronic kidney disease based on data from various research papers. Furthermore, this study also considers the different attributes from either already existing database or from real life database by using multiple techniques of machine learning. It is concluded that working with real life datasets with all possible attributes taken into consideration yields the accurate prediction for the presence of chronic kidney disease using machine learning.
Performance Study of Various Machine Learning Classifiers for Arc Fault Detection in AC Microgrid
Authors: Joga S Ramana Kumar , Sinha Pampa , Maharana Manoj Kumar
Published: April 2021

Fault is the abnormal condition in power system, which must be detected as early as possible. It is very important to detect the fault as quick as possible to reduce the effects of fault like equipment damage, property loss and human loss. Arc faults have high power discharge property between two conductors; this property causes damage to the conductors which leads to electric fire between the conductors. It is very necessary to detect these faults immediately to avoid fire accidents. There are various methods to detect these arc faults in microgrid. In this paper voltage and current signals are measured through instrumental transformers and voltage signal is decomposed by the discrete wavelet transform signal processing technique. The decomposed signals are further processed in various machines learning classifier’s for detecting the arc fault. The Proposed methodology studies the performance of various machine learning classifiers to detect arc fault in microgrid and it is carried out in MATLAB/Simulink Software.
Static Vulnerability Analysis of Docker Images
Authors: Jain Vipin , Singh Baldev , Khenwar Medha , Sharma Milind
Published: April 2021

Many organizations are renovating their businesses by grasping DevOps, microservices, and container technologies. Docker is emerged as a new technology, proving an efficient means to develop and deploy applications. Docker containers are created by images to run an application with all its dependencies so that it could run isolated from other processes. Security is always being a foremost concern as our industries are already persistent to improve the reliability and efficiency of new software applications. Security of local Docker containers from the attacks of malicious containers, perceived threats present in Docker images need to be detected and the risks identified when instances of Docker containers run on the host machine. This paper reviews Docker’s existing security mechanisms, vulnerabilities, threats and the related tools required for static security analysis.
An adaptive approach for word sense disambiguation for Hindi language
Authors: Soni Vimal Kumar , Gopalaniî Dinesh , Govil M C
Published: April 2021

Word sense disambiguation has been a classical problem and it is still considered as a big challenge for NLP researchers. Word vectors have shown remarkable improvements from baseline performances for various NLP challenges. An adaptive approach is developed to resolve the ambiguity at word level using word vectors and presented in this paper. CBOW and Skip-gram models of Word2Vec are used to generate the word embeddings. An input sentence is split into two sets: The first set contains all possible ambiguous words and the second set is constituted from all the unambiguous words. The words from the first set are processed through IndoWordNet to collect all the senses of respective words, and such senses are stored in sensedictionary. An adaptive approach is applied to find out the exact interpretation of the ambiguous word from the sense dictionary for each word from the set of ambiguous words with the context words from the set of unambiguous words. The proposed approach is evaluated on a large scale Hindi corpus and claimed better results than previous attempts.
Dispersive mirror characterization and application for mid-infrared post-compression
Authors: Flender Roland , Kurucz Mate , Grosz Timea , Borzsonyi Adam , Gimzevskis Ugnius , Samalius Arturas , Hoff Dominik , Kiss Balint
Published: April 2021

This paper presents a second harmonic assisted spectrally resolved interferometric technique that can overcome the limited spectral resolution of commercially available spectrometers in the mid-infrared. The discussed scheme was validated by measuring the group delay of several well-known and frequently used materials. Our main motivation was to characterize the spectral phase shift of newly designed and manufactured dispersive mirrors to be used for mid-infrared (MIR) post-compression. These mirrors were successfully implemented in the post-compression stage of our MIR laser system, where pulse duration was shortened below two optical cycles and the pulse peak power increased by 30.3% compared to the original output.
Measurement and control of main spatio-temporal couplings in a CPA laser chain
Authors: Kabacinski Adeline , Oubrerie Kosta , Goddet Jean-Philippe , Gautier Julien , Tissandier Fabien , Kononenko Olena , Tafzi Amar , Leblanc Adrien , Sebban Stéphane , Thaury Cédric
Published: April 2021

We report a straightforward method to control main spatio-temporal couplings in a chirped pulse amplification (CPA) laser chain system using a specially designed chromatic doublet in a divergent beam configuration. The centering of the doublet allows for the control of the spatial chirp of the CPA laser chain, while its longitudinal position in the divergent beam enables the control of the amount of longitudinal chromatism in a wide dynamic range. The performance of this technique is evaluated by measuring main spatio-temporal couplings with a simple method, based on an ultrafast pulse shaper, which allows for a selection of narrow windows of the spectrum.
Numerical investigation of metasurface narrowband perfect absorber and a plasmonic sensor for a near-infrared wavelength range
Authors: Khonina S N , Butt M A , Kazanskiy N L
Published: April 2021

Herein, we have presented a computation study of a metasurface (MS) narrowband perfect absorber performed utilizing the three-dimensional finite element method. In the first part of the paper, the periodic sequence of silicon meta-atoms (MAs) is positioned on a ∼100 nm gold thin-film. The gold thin-film obstructs a broadband light at normal incidence, and silicon MAs are utilized to stimulate the surface plasmon by scattering light through it. The highest absorption of 96% is procured at 930.26 nm in the air medium which can be further enhanced by using a layered structure of MAs deposited on gold. The MAs are composed of Si/SiO2/Si with an optimized layers height. Consequently, the perfect impedance matching of the electric and magnetic dipoles takes place providing a 99% of absorption insensitive to the incidence angle of light and almost negligible reflection at a resonating wavelength of 889.4 nm. This feature allows us to utilize this device as a plasmonic sensor. That is why, in the second part of the paper, the proposed device design is studied for the detection of the refractive index of the surrounding medium. The sensitivity and figure of merits of the MS device are in the range of 460–492 nm RIU−1 and 76.7–82 RIU−1, respectively. We claim that the anticipated MS element can be employed in solar photovoltaic and biomedical sensing purposes.
Study of focusing parameters of wavelength-scale binary phase Fresnel zone plate
Authors: Geints Yu E , Panina E K , Minin I V , Minin O V
Published: April 2021

Binary Fresnel zone plates (FZP) are among the most commonly used focusing elements of 2D-planar optical circuits in micro- and nano-photonics. When the diameter and focal distance of a FZP are reduced to the wavelength dimensions, the parameters of the focal area experience strong influence by FZP constructive design (material, thickness, depth of zone relief). By means of the numerical simulations, the near-field diffraction of monochromatic optical wave on a wavelength-scale binary phase plate is investigated. We found a range of optimal depths of zone plate grooves etching as well as substrate thicknesses providing the best focusing of the incident circularly polarized optical wave in terms of maximum field intensity and minimum size of the focal spot. A certain improvement of these focus parameters can be achieved by filling the zone grooves with a dielectric having a specific refractive index contrast against the FZP substrate. Additionally, the concept of a super-focus binary phase plate with a solid immersion layer (SIL) in the form of a truncated cone made of the ZP substrate material is proposed. Similar to conventional SIL device, this flat SIL-FZP can focus a circularly polarized optical radiation into a subdiffraction spot with a full-width of the order λ/2n (n is FZP refraction index).
Performances on the Montreal Cognitive Assessment Along the Cardiovascular Disease Continuum
Authors: Gagnon Christine , Saillant Kathia , Olmand Miloudza , Gayda Mathieu , Nigam Anil , Bouabdallaoui Nadia , Rouleau Jean-Lucien , Desjardins-Crépeau Laurence , Bherer Louis
Published: April 2021

Cardiovascular diseases involve a continuum starting with risk factors, which can progress to coronary heart disease and eventually, to heart failure. Cognitive impairment (CI) is observed as early as cardiovascular risk factors, and in up to 50% of patients with heart failure. Because CI in cardiovascular disease is linked to poorer clinical outcomes, early detection is essential. The Montreal Cognitive Assessment (MoCA) is a screening tool widely used in clinical setting. To date, little is known about MoCA scores along the cardiovascular disease continuum.

Objective

This study compared performances of different cardiovascular disease profiles on the MoCA and its subscores.

Method

Eighty participants (>50 years) from two studies conducted at the Montreal Heart Institute were separated into four groups: low cardiovascular risk factors (<2), high cardiovascular risk factors (>2), coronary heart disease, and stable heart failure. ANCOVAs were performed on the total score and on subscores, with sex, age, and education as covariates.

Results

Group differences were observed on the MoCA total score (heart failure < low cardiovascular risk), verbal fluency (heart failure < low cardiovascular risk), memory (coronary heart disease < low cardiovascular risk), and orientation (coronary heart disease < low and high cardiovascular risk) subscores.

Conclusion

Results suggest that the MoCA, particularly verbal fluency and memory subscores, can detect cognitive changes in later stages of the cardiovascular disease continuum, such as heart failure. Detecting cognitive changes earlier on the cardiovascular disease continuum may require more in depth neuropsychological assessments.
Nitrogen deficiency maintains the yield and improves the antioxidant activity of Coreopsis tinctoria Nutt.
Authors: Li Zhiyuan , Jiang Hong , Qin Yanan , Yan Huizhuan , Jiang Xiumei , Qin Yong
Published: April 2021

Nitrogen (N) deficiency levels were investigated for their potential to maintain the yield and improve antioxidant activity of Coreopsis tinctoria. Inflorescences and leaves at 0, 10, 20, 30, 40, and 50 d after flowering were frozen at −80 °C and plant growth, antioxidant activity, bioactive substance, enzyme activity, and gene expression were evaluated. N deficiency maintained the total number of flowers, promoted phenol and flavonoid accumulation, and enhanced antioxidant activity. Moreover, N deficiency stimulated activities of phenylalanine ammonia-lyase (PAL), cinnamate-4-hydroxylase (C4H) and 4-coumarate:coenzyme A ligase (4CL), and induced CtPAL, CtC4H and Ct4CL gene expression. The data also suggest that N-deficiency-induced phenolic and flavonoid accumulation occurs due to the activation of biosynthetic pathways in C. tinctoria. We characterize the unique features of C. tinctoria under N-deficiency conditions and provide valuable information for the cultivation of high-N use efficiency varieties with low input and high output.
Confidence regions in Wasserstein distributionally robust estimation
Authors: Blanchet Jose , Murthy Karthyek , Si Nian
Published: April 2021

Estimators based on Wasserstein distributionally robust optimization are obtained as solutions of min-max problems in which the statistician selects a parameter minimizing the worst-case loss among all probability models within a certain distance from the underlying empirical measure in a Wasserstein sense. While motivated by the need to identify optimal model parameters or decision choices that are robust to model misspecification, these distributionally robust estimators recover a wide range of regularized estimators, including square-root lasso and support vector machines, among others. This paper studies the asymptotic normality of these distributionally robust estimators as well as the properties of an optimal confidence region induced by the Wasserstein distributionally robust optimization formulation. In addition, key properties of min-max distributionally robust optimization problems are also studied; for example, we show that distributionally robust estimators regularize the loss based on its derivative, and we also derive general sufficient conditions which show the equivalence between the min-max distributionally robust optimization problem and the corresponding max-min formulation.
Reporting guideline for interventional trials of primary and incisional ventral hernia repair
Authors: Parker S G , Halligan S , Berrevoet F , de Beaux A C , East B , Eker H H , Jensen K K , Jorgensen L N , Montgomery A , Morales-Conde S , Miserez M , Renard Y , Sanders D L , Simons M , Slade D , Torkington J , Blackwell S , Dames N , Windsor A C J , Mallett S
Published: April 2021

Background

Primary and incisional ventral hernia trials collect unstandardized inconsistent data, limiting data interpretation and comparison. This study aimed to create two minimum data sets for primary and incisional ventral hernia interventional trials to standardize data collection and improve trial comparison. To support these data sets, standardized patient-reported outcome measures and trial methodology criteria were created.

Methods

To construct these data sets, nominal group technique methodology was employed, involving 15 internationally recognized abdominal wall surgeons and two patient representatives. Initially a maximum data set was created from previous systematic and panellist reviews. Thereafter, three stages of voting took place: stage 1, selection of the number of variables for data set inclusion; stage 2, selection of variables to be included; and stage 3, selection of variable definitions and detection methods. A steering committee interpreted and analysed the data.

Results

The maximum data set contained 245 variables. The three stages of voting commenced in October 2019 and had been completed by July 2020. The final primary ventral hernia data set included 32 variables, the incisional ventral hernia data set included 40 variables, the patient-reported outcome measures tool contained 25 questions, and 40 methodological criteria were chosen. The best known variable definitions were selected for accurate variable description. CT was selected as the optimal preoperative descriptor of hernia morphology. Standardized follow-up at 30 days, 1 year, and 5 years was selected.

Conclusion

These minimum data sets, patient-reported outcome measures, and methodological criteria have allowed creation of a manual for investigators aiming to undertake primary ventral hernia or incisional ventral hernia interventional trials. Adopting these data sets will improve trial methods and comparisons.
HOPS-associated neurological disorders (HOPSANDs): linking endolysosomal dysfunction to the pathogenesis of dystonia
Authors: Monfrini Edoardo , Zech Michael , Steel Dora , Kurian Manju A , Winkelmann Juliane , Di Fonzo Alessio
Published: April 2021

The homotypic fusion and protein sorting (HOPS) complex is the structural bridge necessary for the fusion of late endosomes and autophagosomes with lysosomes.

Recent publications linked mutations in genes encoding HOPS complex proteins with the aetiopathogenesis of inherited dystonias (i.e. VPS16, VPS41, and VPS11). Functional and microstructural studies conducted on patient-derived fibroblasts carrying mutations of HOPS complex subunits displayed clear abnormalities of the lysosomal and autophagic compartments.

We propose to name this group of diseases HOPS-associated neurological disorders (HOPSANDs), which are mainly characterized by dystonic presentations. The delineation of HOPSANDs further confirms the connection of lysosomal and autophagic dysfunction with the pathogenesis of dystonia, prompting researchers to find innovative therapies targeting this pathway.
Anti-inflammatory chemoprevention attenuates the phenotype in a mouse model of esophageal adenocarcinoma
Authors: Baumeister Theresa , Ingermann Jonas , Marcazzan Sabrina , Fang Hsin-Yu , Oellinger Rupert , Rad Roland , Engleitner Thomas , Kleigrewe Karin , Anand Akanksha , Strangmann Julia , Schmid Roland M , Wang Timothy C , Quante Michael
Published: April 2021

Barrett’s esophagus (BE) is the main known precursor condition of esophageal adenocarcinoma (EAC). BE is defined by the presence of metaplasia above the normal squamous columnar junction and has mainly been attributed to gastroesophageal reflux disease and chronic reflux esophagitis. Thus, the rising incidence of EAC in the Western world is probably mediated by chronic esophageal inflammation, secondary to gastroesophageal reflux disease in combination with environmental risk factors such as a Western diet and obesity. However, (at present) risk prediction tools and endoscopic surveillance have shown limited effectiveness. Chemoprevention as an adjunctive approach remains an attractive option to reduce the incidence of neoplastic disease. Here, we investigate the feasibility of chemopreventive approaches in BE and EAC via inhibition of inflammatory signaling in a transgenic mouse model of BE and EAC (L2-IL1B mice), with accelerated tumor formation on a high-fat diet (HFD). L2-IL1B mice were treated with the IL-1 receptor antagonist Anakinra and the nonsteroidal anti-inflammatory drugs (NSAIDs) aspirin or Sulindac. Interleukin-1b antagonism reduced tumor progression in L2-IL1B mice with or without a HFD, whereas both NSAIDs were effective chemoprevention agents in the accelerated HFD-fed L2-IL1B mouse model. Sulindac treatment also resulted in a marked change in the immune profile of L2-IL1B mice. In summary, anti-inflammatory treatment of HFD-treated L2-IL1B mice acted protectively on disease progression. These results from a mouse model of BE support results from clinical trials that suggest that anti-inflammatory medication may be effective in the chemoprevention of EAC.
Speaker–Listener Neural Coupling Reveals an Adaptive Mechanism for Speech Comprehension in a Noisy Environment
Authors: Li Zhuoran , Li Jiawei , Hong Bo , Nolte Guido , Engel Andreas K , Zhang Dan
Published: April 2021

Comprehending speech in noise is an essential cognitive skill for verbal communication. However, it remains unclear how our brain adapts to the noisy environment to achieve comprehension. The present study investigated the neural mechanisms of speech comprehension in noise using an functional near-infrared spectroscopy-based inter-brain approach. A group of speakers was invited to tell real-life stories. The recorded speech audios were added with meaningless white noise at four signal-to-noise levels and then played to listeners. Results showed that speaker–listener neural couplings of listener’s left inferior frontal gyri (IFG), that is, sensorimotor system, and right middle temporal gyri (MTG), angular gyri (AG), that is, auditory system, were significantly higher in listening conditions than in the baseline. More importantly, the correlation between neural coupling of listener’s left IFG and the comprehension performance gradually became more positive with increasing noise level, indicating an adaptive role of sensorimotor system in noisy speech comprehension; however, the top behavioral correlations for the coupling of listener’s right MTG and AG were only obtained in mild noise conditions, indicating a different and less robust mechanism. To sum up, speaker–listener coupling analysis provides added value and new sight to understand the neural mechanism of speech-in-noise comprehension.
Detection of Severe Acute Respiratory Syndrome Coronavirus 2 on Self-Collected Saliva or Anterior Nasal Specimens Compared With Healthcare Personnel–Collected Nasopharyngeal Specimens
Authors: Marx Grace E , Biggerstaff Brad J , Nawrocki Courtney C , Totten Sarah E , Travanty Emily A , Burakoff Alexis W , Scott Tracy , De Hey Jesse Chavez-Van , Carlson Jesse J , Wendel Karen A , Harcourt Jennifer L , Tamin Azaibi , Thomas Jennifer D , Rowan Sarah E ,   Colorado Department of Public Health and Environment COVID-19 Laboratory Response Team, Matzinger Shannon R , Hudziec Meghan , Hetherington-Rauth Molly C , Pysnack Nicholas J , Delmonico Christopher , Huynh-Templeman Kimberly , Stitzlein Tara M , Rossheim Alexandria E B ,   Centers for Disease Control and Prevention COVID-19 Laboratory Response Team, Folster Jennifer , Medrzycki Magdalena , Wong Phili , Jain Shilpi , Thornburg Natalie
Published: April 2021

Background

Nasopharyngeal specimens (NPS) are commonly used for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing but can be uncomfortable for patients. Self-collected saliva specimens (SS) or anterior nasal specimens (ANS) for SARS-CoV-2 detection are less invasive, but the sensitivity of these specimen types has not been thoroughly evaluated.

Methods

During September–November 2020, 730 adults undergoing SARS-CoV-2 testing at community testing events and homeless shelters in Denver provided self-collected SS and ANS before NPS collection and answered a short survey about symptoms and specimen preference. Specimens were tested for SARS-CoV-2 by means of real-time reverse-transcription polymerase chain reaction (rRT-PCR); viral culture was performed on a subset of specimens positive by rRT-PCR. The sensitivity of SS and ANS for SARS-CoV-2 detection by rRT-PCR was measured against that of NPS. Subgroup analyses included test outcomes by symptom status and culture results.

Results

Sensitivity for SARS-CoV-2 detection by rRT-PCR appeared higher for SS than for ANS (85% vs 80%) and higher among symptomatic participants than among those without symptoms (94% vs 29% for SS; 87% vs 50% for ANS). Among participants with culture-positive SARS-CoV-2 by any specimen type, the sensitivities of SS and ANS by rRT-PCR were 94% and 100%, respectively. SS and ANS were equally preferred by participants; most would undergo NPS collection again despite this method’s being the least preferred.

Conclusions

SS were slightly more sensitive than ANS for SARS-CoV-2 detection with rRT-PCR. With both SS and ANS, SARS-CoV-2 was reliably detected among participants with symptoms. Self-collected SS and ANS offer practical advantages, are preferred by patients, and might be most useful for testing people with coronavirus disease 2019 symptoms.
Neonatal Listeriosis Presentation and Outcome: A Prospective Study of 189 Cases
Authors: Charlier Caroline , Kermorvant-Duchemin Elsa , Perrodeau Elodie , Moura Alexandra , Maury Mylène M , Bracq-Dieye Hélène , Thouvenot Pierre , Valès Guillaume , Leclercq Alexandre , Ravaud Philippe , Lecuit Marc
Published: April 2021

Background

Listeriosis is caused by the foodborne pathogen Listeria monocytogenes. It can present as a maternal–neonatal infection. We implemented a nationwide prospective cohort and analyzed the features of neonatal listeriosis.

Methods

We studied all neonates born alive from mothers with microbiologically proven maternal–neonatal listeriosis enrolled from November 2009 to December 2017. We analyzed presentation, neonatal outcome at discharge, and predictors of severe presentation and outcome.

Results

We studied 189 infants; 133 of 189 (70%) had abnormal clinical status at birth, including acute respiratory distress in 106 of 189 (56%). There were 132 of 189 (70%) infants who developed early-onset listeriosis and 12 of 189 (6%) who developed late-onset listeriosis; all presented with acute meningitis. There were 17 of 189 (9%) infants who had major adverse outcomes: 3%, (5 of 189) death; 6% (12 of 189), severe brain injury; and 2% (3 of 189), severe bronchopulmonary dysplasia. Fifteen of 17 infants were born <34 weeks of gestation (P < .0001 vs infants born ≥34 weeks of gestation). Maternal antimicrobial treatment ≥1 day before delivery was associated with a significant decrease in presentation severity for the infant, resulting in significantly fewer inotropic drugs, fluid resuscitation, and mechanical ventilation requirement (odds ratio, 0.23; 95% confidence interval, 0.09–0.51; P < .0001).

Conclusions

Antenatal maternal antimicrobial treatment is associated with reduced neonatal listeriosis severity, justifying the prescription of preemptive maternal antimicrobial therapy when maternal–fetal listeriosis is suspected. Neonatal outcome is better than reported earlier, and its major determinant is gestational age at birth.

Clinical Trials Registration

NCT01520597.
Late Conditions Diagnosed 1–4 Months Following an Initial Coronavirus Disease 2019 (COVID-19) Encounter: A Matched-Cohort Study Using Inpatient and Outpatient Administrative Data—United States, 1 March–30 June 2020
Authors: Chevinsky Jennifer R , Tao Guoyu , Lavery Amy M , Kukielka Esther A , Click Eleanor S , Malec Donald , Kompaniyets Lyudmyla , Bruce Beau B , Yusuf Hussain , Goodman Alyson B , Dixon Meredith G , Nakao Jolene H , Datta S Deblina , MacKenzie William R , Kadri Sameer S , Saydah Sharon , Giovanni Jennifer E , Gundlapalli Adi V
Published: April 2021

Background

Late sequelae of COVID-19 have been reported; however, few studies have investigated the time course or incidence of late new COVID-19–related health conditions (post-COVID conditions) after COVID-19 diagnosis. Studies distinguishing post-COVID conditions from late conditions caused by other etiologies are lacking. Using data from a large administrative all-payer database, we assessed type, association, and timing of post-COVID conditions following COVID-19 diagnosis.

Methods

Using the Premier Healthcare Database Special COVID-19 Release (release date, 20 October 2020) data, during March–June 2020, 27 589 inpatients and 46 857 outpatients diagnosed with COVID-19 (case-patients) were 1:1 matched with patients without COVID-19 through the 4-month follow-up period (control-patients) by using propensity score matching. In this matched-cohort study, adjusted ORs were calculated to assess for late conditions that were more common in case-patients than control-patients. Incidence proportion was calculated for conditions that were more common in case-patients than control-patients during 31–120 days following a COVID-19 encounter.

Results

During 31–120 days after an initial COVID-19 inpatient hospitalization, 7.0% of adults experienced ≥1 of 5 post-COVID conditions. Among adult outpatients with COVID-19, 7.7% experienced ≥1 of 10 post-COVID conditions. During 31–60 days after an initial outpatient encounter, adults with COVID-19 were 2.8 times as likely to experience acute pulmonary embolism as outpatient control-patients and also more likely to experience a range of conditions affecting multiple body systems (eg, nonspecific chest pain, fatigue, headache, and respiratory, nervous, circulatory, and gastrointestinal symptoms) than outpatient control-patients.

Conclusions

These findings add to the evidence of late health conditions possibly related to COVID-19 in adults following COVID-19 diagnosis and can inform healthcare practice and resource planning for follow-up COVID-19 care.
From secondary to tertiary mitral regurgitation: the paradigm shifts, but uncertainties remain
Authors: Landi Antonio , Faletra Francesco Fulvio , Pavon Anna Giulia , Pedrazzini Giovanni , Valgimigli Marco
Published: April 2021

Secondary mitral regurgitation (MR) is the most common and undertreated form of MR, whose contribution to poor prognosis and indications to correction remains under discussion. MR has been characterized into ‘proportionate’ or ‘disproportionate’, based on left ventricle (LV) and regurgitant volumes, whereas ‘tertiary’ MR identifies conditions, in which regurgitation is pathologic per se and actively contributes to LV dysfunction. Echocardiographic and anatomo-pathological studies revealed that secondary MR prompts subtle leaflet maladaptive changes, actively contributing to the dynamic progression of secondary MR. We critically discuss the paradigm shift from secondary to tertiary MR and question the notion that MV leaflets play a passive role in secondary MR. We also review the role of standard transthoracic echocardiography for appraising and quantifying maladaptive MV leaflet changes and LV volumes and call for a more sophisticated and comprehensive imaging framework for classifying MR in future interventional studies.
Cardiac surgery following transcatheter aortic valve replacement
Authors: Saha Shekhar , Peterss Sven , Mueller Christoph , Deseive Simon , Sadoni Sebastian , Hausleiter Jörg , Massberg Steffen , Hagl Christian , Joskowiak Dominik
Published: April 2021

OBJECTIVES

The objective of this study was to retrospectively analyse surgical outcomes of patients undergoing secondary cardiac surgery after initial transcatheter aortic valve replacement (TAVR).

METHODS

Between December 2012 and February 2020, a total of 41 consecutive patients underwent cardiac surgery after a TAVR procedure at our institution. Patients who underwent emergency operations due to periprocedural complications such as ventricular rupture and TAVR dislocation were excluded from this study (n = 12). Thus, 29 patients were included in the analysis. Data are presented as medians (25th–75th quartiles) or as absolute numbers (percentages).

RESULTS

The median age was 76 years (68–80); 58.6% were men. The median time to a secondary conventional procedure was 23 months (8–40), with 8 patients requiring surgical intervention within the first year post TAVR. The indications for secondary conventional procedures were prosthesis endocarditis (n = 15), prosthesis degeneration or dysfunction (n = 7) and progression of valvular, aortic or coronary artery disease (n = 7). Surgical redo aortic valve replacement was performed in 24 patients (82.8%). No complications involving the aortic root or the aortomitral continuity were observed. The operative mortality was 10.3%. Extracorporeal life support was required in 3 patients (10.3%) for a median duration of 3 days (3–3 days). No adverse cerebrovascular events were observed postoperatively. Postoperatively, 4 patients (13.8%) required a pacemaker and 7 patients (24.1%) required renal replacement therapy. Overall survival at 1 year was 83.0%.

CONCLUSIONS

Conventional cardiac surgical procedures following TAVR are feasible with reasonable results and a low complication rate.
Changes in mortality disparities by education in Russia from 1998 to 2017: evidence from indirect estimation
Authors: Shkolnikov Vladimir M , Andreev Evgeny M , Jasilionis Domantas
Published: April 2021

This article addresses two unresolved methodological issues related to prior research on Russia that was based on census-unlinked data and did not account for the substantial increase in the share of death records with missing information on education. The study uses a proportional mortality analysis method relying on a case–control framework, together with a plausible imputation-based solution for the redistribution of the unknown education on death records. The new results suggest that high levels of inequality persist, but they do not support recent findings indicating that the educational gap in life expectancy has substantially widened.
Analysis of glycerol and dihydroxyacetone metabolism in Enterococcus faecium
Authors: Staerck Cindy , Wasselin Valentin , Budin-Verneuil Aurélie , Rincé Isabelle , Cacaci Margherita , Weigel Markus , Giraud Caroline , Hain Torsten , Hartke Axel , Riboulet-Bisson Eliette
Published: April 2021

Glycerol (Gly) can be dissimilated by two pathways in bacteria. Either this sugar alcohol is first oxidized to dihydroxyacetone (DHA) and then phosphorylated or it is first phosphorylated to glycerol-3-phosphate (GlyP) followed by oxidation. Oxidation of GlyP can be achieved by NAD-dependent dehydrogenases or by a GlyP oxidase. In both cases, dihydroxyacetone phosphate is the product. Genomic analysis showed that Enterococcus faecium harbors numerous genes annotated to encode activities for the two pathways. However, our physiological analyses of growth on glycerol showed that dissimilation is limited to aerobic conditions and that despite the presence of genes encoding presumed GlyP dehydrogenases, the GlyP oxidase is essential in this process. Although E. faecium contains an operon encoding the phosphotransfer protein DhaM and DHA kinase, which are required for DHA phosphorylation, it is unable to grow on DHA. This operon is highly expressed in stationary phase but its physiological role remains unknown. Finally, data obtained from sequencing of a transposon mutant bank of E. faecium grown on BHI revealed that the GlyP dehydrogenases and a major intrinsic family protein have important but hitherto unknown physiological functions.