bluuebunny/crossref_metadata_2025 huggingface dataset:
Describing Supportive Care Programming Access and Comfort Gathering through the COVID-19 Pandemic: An Observational Mixed Methods Study with Adults Affected by Cancer
Authors: Wurz Amanda , Janzen Anna , Ellis Kelsey , Lesser Iris , Arshad Nafeel
Published: February 2023

Supportive care programming helps many adults affected by cancer manage concerns related to their disease. Public health restrictions imposed by the COVID-19 pandemic have undoubtedly changed the nature of supportive care programming delivery. Yet, access to supportive care programming and comfort gathering through the pandemic are unknown. As a first step towards informing ongoing supportive care programming for adults affected by cancer, this observational, mixed methods study described supportive care programming access through the COVID-19 pandemic and comfort returning to in-person supportive care programming as restrictions eased. Adults affected by cancer (n = 113; mean age = 61.9 ± 12.7 years; 68% female) completed an online survey, and descriptive statistics were computed. A purposeful sample of survey participants (n = 12; mean age = 58.0 ± 14.5 years; 58% female) was subsequently recruited to complete semi-structured interviews. Interviews were analyzed using reflexive thematic analysis. Less than half (41.6%) of the survey sample reported accessing supportive care programming during the pandemic, and of those who had accessed supportive care programming, most (65.6%) perceived similar or greater access than pre-pandemic. During interviews, participants described the ways online delivery enhanced their access and reduced barriers to supportive care programming. However, physical activity programming was described as challenging to navigate online. With restrictions easing, most of the survey sample (56.6%) reported being apprehensive about returning to in-person supportive care programming and identified the protocols that would make them feel safe to gather. During interviews, participants recounted struggling to balance their need for social connection with their health and safety. This study provides evidence to inform supportive care programming for adults affected by cancer through the COVID-19 pandemic. Findings suggest online delivery can enhance access to some types of supportive care programming for some adults affected by cancer, and that efforts are needed to ensure all adults affected by cancer feel comfortable gathering in-person.
Bone Metastases from Intrahepatic Cholangiocarcinoma Confer Worse Prognosis
Authors: Garajová Ingrid , Gelsomino Fabio , Salati Massimiliano , Leonardi Francesco , De Lorenzo Stefania , Granito Alessandro , Tovoli Francesco
Published: February 2023

Background: Metastatic intrahepatic cholangiocarcinoma still has a dismal prognosis. The aim of our study was to investigate the prognostic role of bone metastases in patients affected by intrahepatic cholangiocarcinoma. Methods: A total of 186 metastatic intrahepatic cholangiocarcinoma patients were retrospectively reviewed. Clinicopathologic and survival data were collected and reviewed, in particular overall survival, progression-free survival after first-line treatment and time from end of first-line therapy to cancer death. Results: Around 11% of intrahepatic cholangiocarcinoma patients developed bone metastases. This subgroup of patients showed no differences in progression-free survival to first-line chemotherapy but had a shorter median overall survival of 4 months compared to the group with liver involvement only (p = 0.03). If treated, the outcome for ECOG PS 2 patients with bone metastases was worse in comparison to patients with liver involvement only with poor performance status (p = 0.003). The presence of bone metastases, poor performance status and no subsequent second-line treatment was associated with a worse outcome in multivariate analysis. Conclusions: Patients with intrahepatic carcinoma and bone metastases with poor ECOG performance status might be treated with best supportive care and not active chemotherapy treatment, the decisions which have to be shared with patients.
Analysis of the Anomalies in a Middle Eocene Shell of Neochelys (Pleurodira, Podocnemididae) from the Duero Basin (Zamora, Spain)
Authors: Guerrero Andrea , Ortega Francisco , Martín de Jesús Santiago , Pérez-García Adán
Published: February 2023

Turtle shells frequently exhibit anomalous osseous modifications on their surface which can sometimes compromise the survival of the organism. Nowadays, despite the large number of anomalies identified in both extant and extinct turtle shells, the etiology, as well as the pathogenesis, of the various osseous modifications remains unknown in most documented extinct representatives. In fact, the interpretation of these anomalies in most fossil turtles is often speculative, the great majority of anomalous osseous modifications being attributed to vertebrate feeding traces, without considering other potential causative agents. In this context, we herein re-analyzed the shell anomalies recognized in an individual determined as Neochelys sp. (Pleurodira, Podocnemididae) from the middle Eocene (Lutetian) of the El Tejar fossil site (Corrales del Vino, Zamora, Spain), previously proposed as traumatic injuries resulting from a crocodile attack. The re-evaluation of these osseous alterations through detailed physical examination, comparison through direct observation and from the literature on extant turtles, and the use of the files obtained from a computerized axial tomography scan, allows the proposal of diverse causal agents, none of them supporting the previous interpretation. In addition, information regarding the pathogenesis and stages of the healing of the shell anomalies studied herein is provided.
Cell Plasticity of Marine Mediterranean Diazotrophs to Climate Change Factors and Nutrient Regimes
Authors: Fernández-Juárez Víctor , Zech Elisa H. , Pol-Pol Elisabet , Agawin Nona S. R.
Published: February 2023

Ocean acidification and warming are current global challenges that marine diazotrophs must cope with. Little is known about the effects of pH and temperature changes at elevated CO2 levels in combination with different nutrient regimes on N2 fixers, especially on heterotrophic bacteria. Here, we selected four culturable diazotrophs, i.e., cyanobacteria and heterotrophic bacteria, found in association with the endemic Mediterranean seagrass Posidonia oceanica. We tested different pH (from pH 4 to 8) and temperature levels (from 12 to 30 °C), under different nutrient concentrations of both phosphorus, P (0.1 µM and 1.5 mM), and iron, Fe (2 nM and 1 µM). We also tested different CO2 concentrations (410 and 1000 particles per million (ppm)) under different P/Fe and temperature values (12, 18, and 24 °C). Heterotrophic bacteria were more sensitive to changes in pH, temperature, and CO2 than the cyanobacterial species. Cyanobacteria were resistant to very low pH levels, while cold temperatures stimulated the growth in heterotrophic bacteria but only under nutrient-limited conditions. High CO2 levels (1000 ppm) reduced heterotrophic growth only when cultures were nutrient-limited, regardless of temperature. In contrast, cyanobacteria were insensitive to elevated CO2 levels, independently of the nutrient and temperature levels. Changes in N2 fixation were mainly controlled by changes in growth. In addition, we suggest that alkaline phosphatase activity (APA) and reactive oxidative species (ROS) can be used as biomarkers to assess the plasticity of these communities to climate change factors. Unlike other studies, the novelty of this work lies in the fact that we compared the responses of cyanobacteria vs. heterotrophic bacteria, studying which changes occur at the cell plasticity level. Our results suggest that the responses of diazotrophs to climate change may depend on their P and Fe status and lifestyle, i.e., cyanobacteria or heterotrophic bacteria.
Uniportal VATS for Diagnosis and Staging in Non-Small Cell Lung Cancer (NSCLC)
Authors: Del Campo Jone Miren , Maroto Sergio , Sebastian Leyre , Vaillo Xavier , Bolufer Sergio , Lirio Francisco , Sesma Julio , Galvez Carlos
Published: February 2023

Uniportal VATS has become an accepted approach in minimally invasive thoracic surgery since its first report for lobectomy in 2011. Since the initial restrictions in indications, it has been used in almost all procedures, from conventional lobectomies to sublobar resections, bronchial and vascular sleeve procedures and even tracheal and carinal resections. In addition to its use for treatment, it provides an excellent approach for suspicious solitary undiagnosed nodules after bronchoscopic or transthoracic image-guided biopsy. Uniportal VATS is also used as a surgical staging method in NSCLC due to its low invasiveness in terms of chest tube duration, hospital stay and postoperative pain. In this article, we review the evidence of uniportal VATS accuracy for NSCLC diagnosis and staging and provide technical details and recommendations for its safe performance for that purpose.
Efficient Massive MIMO Detection for M-QAM Symbols
Authors: Quan Zhi , Luo Jiyu , Zhang Hailong , Jiang Li
Published: February 2023

Massive multiple-input multiple-output (MIMO) systems significantly outperform small-scale MIMO systems in terms of data rate, making them an enabling technology for next-generation wireless systems. However, the increased number of antennas increases the computational difficulty of data detection, necessitating more efficient detection techniques. This paper presents a detector based on joint deregularized and box-constrained dichotomous coordinate descent (BOXDCD) with iterations for rectangular m-ary quadrature amplitude modulation (M-QAM) symbols. Deregularization maximized the energy of the solution. With the box-constraint, the deregularization forces the solution to be close to the rectangular boundary set. The numerical results demonstrate that the proposed detector achieves a considerable performance gain compared to existing detection algorithms. The performance advantage increases with the system size and signal-to-noise ratio.
Random Walk Approximation for Stochastic Processes on Graphs
Authors: Polizzi Stefano , Marzi Tommaso , Matteuzzi Tommaso , Castellani Gastone , Bazzani Armando
Published: February 2023

We introduce the Random Walk Approximation (RWA), a new method to approximate the stationary solution of master equations describing stochastic processes taking place on graphs. Our approximation can be used for all processes governed by non-linear master equations without long-range interactions and with a conserved number of entities, which are typical in biological systems, such as gene regulatory or chemical reaction networks, where no exact solution exists. For linear systems, the RWA becomes the exact result obtained from the maximum entropy principle. The RWA allows having a simple analytical, even though approximated, form of the solution, which is global and easier to deal with than the standard System Size Expansion (SSE). Here, we give some theoretically sufficient conditions for the validity of the RWA and estimate the order of error calculated by the approximation with respect to the number of particles. We compare RWA with SSE for two examples, a toy model and the more realistic dual phosphorylation cycle, governed by the same underlying process. Both approximations are compared with the exact integration of the master equation, showing for the RWA good performances of the same order or better than the SSE, even in regions where sufficient conditions are not met.
Which Multivariate Multi-Scale Entropy Algorithm Is More Suitable for Analyzing the EEG Characteristics of Mild Cognitive Impairment?
Authors: Liu Jing , Lu Huibin , Zhang Xiuru , Li Xiaoli , Wang Lei , Yin Shimin , Cui Dong
Published: February 2023

So far, most articles using the multivariate multi-scale entropy algorithm mainly use algorithms to analyze the multivariable signal complexity without clearly describing what characteristics of signals these algorithms measure and what factors affect these algorithms. This paper analyzes six commonly used multivariate multi-scale entropy algorithms from a new perspective. It clarifies for the first time what characteristics of signals these algorithms measure and which factors affect them. It also studies which algorithm is more suitable for analyzing mild cognitive impairment (MCI) electroencephalograph (EEG) signals. The simulation results show that the multivariate multi-scale sample entropy (mvMSE), multivariate multi-scale fuzzy entropy (mvMFE), and refined composite multivariate multi-scale fuzzy entropy (RCmvMFE) algorithms can measure intra- and inter-channel correlation and multivariable signal complexity. In the joint analysis of coupling and complexity, they all decrease with the decrease in signal complexity and coupling strength, highlighting their advantages in processing related multi-channel signals, which is a discovery in the simulation. Among them, the RCmvMFE algorithm can better distinguish different complexity signals and correlations between channels. It also performs well in anti-noise and length analysis of multi-channel data simultaneously. Therefore, we use the RCmvMFE algorithm to analyze EEG signals from twenty subjects (eight control subjects and twelve MCI subjects). The results show that the MCI group had lower entropy than the control group on the short scale and the opposite on the long scale. Moreover, frontal entropy correlates significantly positively with the Montreal Cognitive Assessment score and Auditory Verbal Learning Test delayed recall score on the short scale.
A Review of Grid Connection Requirements for Photovoltaic Power Plants
Authors: G. Landera Yandi , C. Zevallos Oscar , Neto Rafael C. , Castro Jose F. da Costa , Neves Francisco A. S.
Published: February 2023

The increasing rate of renewable energy penetration in modern power grids has prompted updates to the regulations, standards, and grid codes requiring ancillary services provided by photovoltaic-generating units similar to those applied to conventional generating units. In this work, a comprehensive survey presents a comparison of requirements related to voltage ride through reactive current injection/absorption; active power restoration; frequency stability regulation and active power control; voltage regulation and reactive power control; and the energy quality requisites included in the standards and grid codes of countries around the globe. The survey can be used to observe the differences between the requirements established in the grid codes depending on the power system operating characteristics, development of technology, and renewable energy penetration level. Many of these factors determine the parameters used to establish requisites for different grid codes, making a global standardization of the renewable energy interconnection requirements much harder.
New Method of Modeling Daily Energy Consumption
Authors: Karpio Krzysztof , Łukasiewicz Piotr , Nafkha Rafik
Published: February 2023

At present, papers concerning energy consumption and forecasting are predominantly dedicated to various known techniques and their combinations. On the other hand, the research on load modeling and forecasting methodologies is quite limited. This paper presents a new approach concerning hourly energy consumption using a multivariate linear regression model. The proposed technique provides a way to accurately model day-to-day energy consumption using just a few selected variables. The number of data points required to describe a whole day’s consumption depends on the demanded precision, which is up to the user. This model is self-configurable and very fast. The applied model shows that four hours are sufficient to describe energy consumption during the remainder of a given day. We show that for about 84% of the data points, the relative error of the model is below 2.5%, and for all the data points the error does not exceed 7.5%. We obtained a mean relative uncertainty of 1.72% in the learning data set, and 1.69% and 1.82% in the two testing data sets, respectively. In addition, we conclude that the model can also detect days with unusual energy consumption.
Common DC-Link Capacitor Harmonic Current Minimization for Cascaded Converters by Optimized Phase-Shift Modulation
Authors: Zhou Xuanyi , Choy Wei Juin , Alcaide Abraham M. , Wang Shuo , Guenter Sandro , Leon Jose I. , Monopoli Vito Giuseppe , Franquelo Leopoldo G. , Liserre Marco , Galea Michael , Gerada Chris , Buticchi Giampaolo
Published: February 2023

This paper investigates the influence of a constant carrier phase shift on the DC-link capacitor harmonic current of cascaded converters used in fuel-cell and mild-hybrid electric vehicles. In these applications, a DC-DC converter can be adopted between the battery and the motor drive inverter in a cascaded structure, where the two converters share the same DC-link. Since the DC-link capacitor of such a system represents a critical component, the optimization of the converter operation to limit the current stress and extend the lifetime of the capacitor is an primary objective. This paper proposes the use of a carrier phase shift between the modulations of the two converters in order to minimize the harmonic current of the DC-link capacitor. By harmonic analysis, an optimal carrier phase shift can be derived depending on the converter configuration. Analytical results are presented and validated by hardware-in-the-loop experiments. The findings show that the pulse width modulation carrier phase shift between the interleaved boost converter and the voltage source motor drive inverter has a significant influence on the DC-link capacitor current and thus on its lifetime. A case study with two-cell and three-cell interleaved boost converters shows a possible DC-link capacitor lifetime extension of up to 390%.
Transfer Forest: A Deep Forest Model Based on Transfer Learning for Early Drilling Kick Detection
Authors: Fu Jiasheng , Liu Wei , Zheng Xiangyu , Han Xiaosong
Published: February 2023

Kicks can lead to well control risks during petroleum drilling, and even more serious kicks may lead to serious casualties, which is the biggest threat factor affecting the safety in the process of petroleum drilling. Therefore, how to detect kicks early and efficiently has become a focus practical problem. Traditional machine learning models require a large amount of labeled data, such kicked sample, and it is difficult to label data, which requires a lot of labor and time. To address the above issues, the deep forest is extended to a transfer learning model to improve the generalization ability. In this paper, a transfer learning model is built to detect kicks early. The source domain model adopts the deep forest model. Deep forest is an ensemble learning model with a hierarchical structure similar to deep learning. Each layer contains a variety of random forests. It is an integration of the model in depth and breadth. In the case of a small sample size (20–60 min), kick can be identified 10 min in advance. The deep forest model is established as the source domaining model, and a cascade forest is added at the last layer according to the transfer learning algorithm to form the classification model of this paper. The experimental results show that the kick prediction accuracy of the model is 80.13% by a confusion matrix. In the target domain, the proposed model performs better than other ensemble learning algorithms, and the accuracy is 5% lower than other SOTA transfer learning algorithms.
Dimensioning Air Reactor and Fuel Reactor of a Pressurized Chemical Looping Combustor to Be Coupled to a Gas Turbine: Part 1, the Air Reactor
Authors: Bartocci Pietro , Abad Alberto , Bischi Aldo , Wang Lu , Cabello Arturo , de Las Obras Loscertales Margarita , Zampilli Mauro , Yang Haiping , Fantozzi Francesco
Published: February 2023

This paper provides a simple methodology for the design of the air reactor of a chemical looping combustor to optimize its characteristics when it is employed connected to a turbo expander to produce power. The design process, given a certain objective (e.g., electric power) defines the reactor specifics, namely height and diameter, taking into account the following aspects: solids inventory of the air reactor; gas velocity; air reactor transport disengaging height (TDH); solids concentration profile along the reactor height, dense bed height; freeboard height; pressure drop depending on air reactor injectors design and configuration. The total air reactor height was about 9.5 m, while the diameter was about 1.8 m. The total inventory was about 10,880 kg; while the circulation rate in the air reactor was about 110 kg/s. The operating pressure and temperature were, respectively, 12 bar and 1200 °C. The average velocity of the gases inside the reactor was about 4 m/s. The fluidization regime resulted to be comprised between turbulent and fast fluidization. Further work must be directed into the estimate of the pressure drop of the reactor, which will affect the plant efficiency in a considerable way.
Anode Nitrogen Concentration Estimation Based on Voltage Variation Characteristics for Proton Exchange Membrane Fuel Cell Stacks
Authors: Guo Ruifeng , Chen Dongfang , Li Yuehua , Wu Wenlong , Hu Song , Xu Xiaoming
Published: February 2023

Hydrogen energy has become an important way to solve energy crises owing to its non-pollution, high level of efficiency, and wide application. Proton exchange membrane fuel cells (PEMFCs) have received wide attention as an energy conversion device for hydrogen energy. The hydrogen concentration in the PEMFC anode directly determines the output voltage of the stack. The performance of the PEMFC gradually decreases due to the accumulation of nitrogen. However, the continuous circulation of anode gas and the nitrogen accumulation at the anode due to transmembrane diffusion lead to difficulties in estimating the anode gas concentration. The relationship between anode nitrogen concentration and voltage variation characteristics was studied by increasing the anode hydrogen concentration through the method of increasing nitrogen concentration and conducting experiments on a 16-cell stack. In this paper, an estimation method for nitrogen concentration in the anode is proposed to evaluate the nitrogen concentration in the anode on the basis of voltage variation characteristics, and the method was recalibrated and validated using experimental data. Due to the inhomogeneity of the gas distribution within the PEMFC stack, the mean cell voltage can provide a more accurate estimation of the anode nitrogen concentration compared to a single cell voltage. It is shown that the proposed approach can offer a new method to estimate anode nitrogen concentration. Compared with the conventional method, the new method is simpler as it does not require additional equipment or complex algorithms. In this paper, the anode nitrogen concentration was estimated by applying this method with a maximum error of only 0.35%.
Performance of Deep Learning Techniques for Forecasting PV Power Generation: A Case Study on a 1.5 MWp Floating PV Power Plant
Authors: Khortsriwong Nonthawat , Boonraksa Promphak , Boonraksa Terapong , Fangsuwannarak Thipwan , Boonsrirat Asada , Pinthurat Watcharakorn , Marungsri Boonruang
Published: February 2023

Recently, deep learning techniques have become popular and are widely employed in several research areas, such as optimization, pattern recognition, object identification, and forecasting, due to the advanced development of computer programming technologies. A significant number of renewable energy sources (RESs) as environmentally friendly sources, especially solar photovoltaic (PV) sources, have been integrated into modern power systems. However, the PV source is highly fluctuating and difficult to predict accurately for short-term PV output power generation, leading to ineffective system planning and affecting energy security. Compared to conventional predictive approaches, such as linear regression, predictive-based deep learning methods are promising in predicting short-term PV power generation with high accuracy. This paper investigates the performance of several well-known deep learning techniques to forecast short-term PV power generation in the real-site floating PV power plant of 1.5 MWp capacity at Suranaree University of Technology Hospital, Thailand. The considered deep learning techniques include single models (RNN, CNN, LSTM, GRU, BiLSTM, and BiGRU) and hybrid models (CNN-LSTM, CNN-BiLSTM, CNN-GRU, and CNN-BiGRU). Five-minute resolution data from the real floating PV power plant is used to train and test the deep learning models. Accuracy indices of MAE, MAPE, and RMSE are applied to quantify errors between actual and forecasted values obtained from the different deep learning techniques. The obtained results show that, with the same training dataset, the performance of the deep learning models differs when testing under different weather conditions and time horizons. The CNN-BiGRU model offers the best performance for one-day PV forecasting, while the BiLSTM model is the most preferable for one-week PV forecasting.
Sizing of Hybrid Supercapacitors and Lithium-Ion Batteries for Green Hydrogen Production from PV in the Australian Climate
Authors: Ibrahim Tarek , Kerekes Tamas , Sera Dezso , Mohammadshahi Shahrzad S. , Stroe Daniel-Ioan
Published: February 2023

Instead of storing the energy produced by photovoltaic panels in batteries for later use to power electric loads, green hydrogen can also be produced and used in transportation, heating, and as a natural gas alternative. Green hydrogen is produced in a process called electrolysis. Generally, the electrolyser can generate hydrogen from a fluctuating power supply such as renewables. However, due to the startup time of the electrolyser and electrolyser degradation accelerated by multiple shutdowns, an idle mode is required. When in idle mode, the electrolyser uses 10% of the rated electrolyser load. An energy management system (EMS) shall be applied, where a storage technology such as a lithium-ion capacitor or lithium-ion battery is used. This paper uses a state-machine EMS of PV microgrid for green hydrogen production and energy storage to manage the hydrogen production during the morning from solar power and in the night using the stored energy in the energy storage, which is sized for different scenarios using a lithium-ion capacitor and lithium-ion battery. The mission profile and life expectancy of the lithium-ion capacitor and lithium-ion battery are evaluated considering the system’s local irradiance and temperature conditions in the Australian climate. A tradeoff between storage size and cutoffs of hydrogen production as variables of the cost function is evaluated for different scenarios. The lithium-ion capacitor and lithium-ion battery are compared for each tested scenario for an optimum lifetime. It was found that a lithium-ion battery on average is 140% oversized compared to a lithium-ion capacitor, but a lithium-ion capacitor has a smaller remaining capacity of 80.2% after ten years of operation due to its higher calendar aging, while LiB has 86%. It was also noticed that LiB is more affected by cycling aging while LiC is affected by calendar aging. However, the average internal resistance after 10 years for the lithium-ion capacitor is 264% of the initial internal resistance, while for lithium-ion battery is 346%, making lithium-ion capacitor a better candidate for energy storage if it is used for grid regulation, as it requires maintaining a lower internal resistance over the lifetime of the storage.
Microbial Behavior and Influencing Factors in the Anaerobic Digestion of Distiller: A Comprehensive Review
Authors: Li Gang , Xu Fuzhuo , Yang Tenglun , Wang Xiqing , Lyu Tao , Huang Zhigang
Published: February 2023

Anaerobic digestion technology is regarded as the most ideal technology for the treatment of a distiller in terms of environmental protection, resource utilization, and cost. However, there are some limitations to this process, the most prominent of which is microbial activity. The purpose of this paper is to provide a critical review of the microorganisms involved in the anaerobic digestion process of a distiller, with emphasis on the archaea community. The effects of operating parameters on microbial activity and process, such as pH, temperature, TAN, etc., are discussed. By understanding the activity of microorganisms, the anaerobic treatment technology of a distiller can be more mature. Aiming at the problem that anaerobic treatment of a distiller alone is not effective, the synergistic effect of different substrates is briefly discussed. In addition, the recent literature on the use of microorganisms to purify a distiller was collected in order to better purify the distiller and reduce harm. In the future, more studies are needed to elucidate the interactions between microorganisms and establish the mechanisms of microbial interactions in different environments.
The Use of Some Polyphenols in the Modulation of Muscle Damage and Inflammation Induced by Physical Exercise: A Review
Authors: Volpe-Fix Andressa Roehrig , de França Elias , Silvestre Jean Carlos , Thomatieli-Santos Ronaldo Vagner
Published: February 2023

Food bioactive compounds (FBC) comprise a vast class of substances, including polyphenols, with different chemical structures, and they exert physiological effects on individuals who consume them, such as antioxidant and anti-inflammatory action. The primary food sources of the compounds are fruits, vegetables, wines, teas, seasonings, and spices, and there are still no daily recommendations for their intake. Depending on the intensity and volume, physical exercise can stimulate oxidative stress and muscle inflammation to generate muscle recovery. However, little is known about the role that polyphenols may have in the process of injury, inflammation, and muscle regeneration. This review aimed to relate the effects of supplementation with mentation with some polyphenols in oxidative stress and post-exercise inflammatory markers. The consulted papers suggest that supplementation with 74 to 900 mg of cocoa, 250 to 1000 mg of green tea extract for around 4 weeks, and 90 mg for up to 5 days of curcumin can attenuate cell damage and inflammation of stress markers of oxidative stress during and after exercise. However, regarding anthocyanins, quercetins, and resveratrol, the results are conflicting. Based on these findings, the new reflection that was made is the possible impact of supplementation associating several FBCs simultaneously. Finally, the benefits discussed here do not consider the existing divergences in the literature. Some contradictions are inherent in the few studies carried out so far. Methodological limitations, such as supplementation time, doses used, forms of supplementation, different exercise protocols, and collection times, create barriers to knowledge consolidation and must be overcome.
Associating Compositional, Nutritional and Techno-Functional Characteristics of Faba Bean (Vicia faba L.) Protein Isolates and Their Production Side-Streams with Potential Food Applications
Authors: Krause Magdalena , Sørensen Jens Christian , Petersen Iben Lykke , Duque-Estrada Patrícia , Cappello Claudia , Tlais Ali Zein Alabiden , Di Cagno Raffaella , Ispiryan Lilit , Sahin Aylin W. , Arendt Elke K. , Zannini Emanuele
Published: February 2023

Faba beans (Vicia faba L.) show exciting prospects as a sustainable source of protein and fibre, with the potential to transition to a more sustainable food production. This study reveals the compositional, nutritional and techno-functional characteristics of two protein isolates from faba beans (Vicia faba L.), a high-starch fraction and a high-fibre side-stream. During the analysis of those four ingredients, particular attention was paid to the isolates’ protein profile and the side-streams’ carbohydrate composition. The isoelectric precipitated protein isolate 1 showed a protein content of 72.64 ± 0.31% DM. It exhibited low solubility but superior digestibility and high foam stability. High foaming capacity and low protein digestibility were observed for protein isolate 2, with a protein content of 71.37 ± 0.93% DM. This fraction was highly soluble and consisted primarily of low molecular weight proteins. The high-starch fraction contained 83.87 ± 3.07% DM starch, of which about 66% was resistant starch. Over 65% of the high-fibre fraction was insoluble dietary fibre. The findings of this study provide a detailed understanding of different production fractions of faba beans, which is of great value for future product development.
Genetic-Phenotype Analysis of Bifidobacterium bifidum and Its Glycoside Hydrolase Gene Distribution at Different Age Groups
Authors: Wei Xiaojing , Yu Leilei , Zhang Chuan , Ni Yongqing , Zhang Hao , Zhai Qixiao , Tian Fengwei
Published: February 2023

Human gut microbiota interfere with host development and aging. Bifidobacterium is a microbial genus found in the human digestive tract that has probiotic activities such as improving constipation and enhancing immunity. The species and numbers present change with age, but there has been limited research on probiotic gut microbiota at specific ages. This study analyzed the distribution of 610 bifidobacteria in subjects in several age groups (0−17, 18−65, and 66−108 y) using 486 fecal samples and determined the distribution of glycoside hydrolases based on genetic analysis of strains representing 85% of the Bifidobacterium species abundance in each age group. 6’-Sialyllactose is a major component of acidic breast milk oligosaccharides, which can promote human neurogenesis and bifidobacteria growth. Using genotypic and phenotypic association analysis, we investigated the utilization of 6’-sialyllactose by six B. bifidum strains isolated from subjects 0–17 and 18–65 y. A comparative genomic analysis of the six B. bifidum strains revealed differences in genomic features across age groups. Finally, the safety of these strains was evaluated by antibiotic gene and drug resistance phenotype analysis. Our results reveal that the distribution of glycoside hydrolase genes in B. bifidum varies with age, thus affecting the phenotypic results. This provides important insights for the design and application of probiotic products for different ages.
A Systematic Quantitative Determination of the Antimicrobial Efficacy of Grape Seed Extract against Foodborne Bacterial Pathogens
Authors: Kitsiou Melina , Purk Lisa , Gutierrez-Merino Jorge , Karatzas Kimon Andreas , Klymenko Oleksiy V. , Velliou Eirini
Published: February 2023

Concerns regarding the role of antimicrobial resistance (AMR) in disease outbreaks are growing due to the excessive use of antibiotics. Moreover, consumers are demanding food products that are minimally processed and produced in a sustainable way, without the use of chemical preservatives or antibiotics. Grape seed extract (GSE) is isolated from wine industry waste and is an interesting source of natural antimicrobials, especially when aiming to increase sustainable processing. The aim of this study was to obtain a systematic understanding of the microbial inactivation efficacy/potential of GSE against Listeria monocytogenes (Gram-positive), Escherichia coli and Salmonella Typhimurium (Gram-negative) in an in vitro model system. More specifically, for L. monocytogenes, the effects of the initial inoculum concentration, bacterial growth phase and absence of the environmental stress response regulon (SigB) on the GSE microbial inactivation potential were investigated. In general, GSE was found to be highly effective at inactivating L. monocytogenes, with higher inactivation achieved for higher GSE concentrations and lower initial inoculum levels. Generally, stationary phase cells were more resistant/tolerant to GSE as compared to exponential phase cells (for the same inoculum level). Additionally, SigB appears to play an important role in the resistance of L. monocytogenes to GSE. The Gram-negative bacteria under study (E. coli and S. Typhimurium) were less susceptible to GSE as compared to L. monocytogenes. Our findings provide a quantitative and mechanistic understanding of the impact of GSE on the microbial dynamics of foodborne pathogens, assisting in the more systematic design of natural antimicrobial-based strategies for sustainable food safety.
Wild Mushrooms as a Source of Protein: A Case Study from Central Europe, Especially the Czech Republic
Authors: Procházka Petr , Soukupová Jana , Mullen Kevin J. , Tomšík Karel , Čábelková Inna
Published: February 2023

Wild mushroom foraging has a long tradition, especially in the region of Central Europe. Wild mushrooms are a valuable food resource, as they provide nutritional benefits to the European population. They offer a relatively high content of protein and are traditionally used in many European cuisines as a substitute for meat. This is particularly true in times of crisis, such as wars and pandemics. The study presented in this paper shows that wild mushrooms can substitute around 0.2 percent of daily protein intake and contribute around 3% to the agricultural output of the Czech economy, which was selected as a representative for Central Europe. The calculated real price of wild mushrooms indicates their increasing popularity as a source of food protein in Central Europe, while their price seems to be independent of the quantity supplied.
Impact of the COVID-19 Pandemic on Dermatology Care in the Chilean Public Health Sector
Authors: Aragón-Caqueo Diego , Aedo Gabriel , Suárez Javier , Toloza Claudio , Guglielmetti Antonio
Published: February 2023

Due to the Coronavirus-19 (COVID-19) pandemic, most resources of the public health system were allocated to the increasing demand from respiratory patients. From this, it is expected that specialty consultations would decrease drastically. Access to dermatology care in the Chilean public health has been historically limited. To evaluate the impact of the pandemic on dermatology care, the total number of dermatological consultations (DCs) to the Chilean public sector in 2020 is analyzed according to sex and age range and compared with the available databases from 2017 to 2019. From this, 120,095 DCs were performed during 2020, with an incidence of 6.3 consultations per 1000 inhabitants. When compared to 2019 (n = 250,649), there was a 52.1% decrease. The regions most affected were located in the central part of Chile, which correlates with the regions most affected by the pandemic. Age and sex distributions remained similar to previous years but lower in amplitude. The month with the lowest number of consultations was April, with a gradual increase observed thereafter until December 2020. Although DCs decreased drastically in the Chilean public sector during 2020, sex and age range proportions were conserved, thus affecting all groups in a similar manner.
Stigma, Sociodemographic Factors, and Clinical Factors Associated with Psychological Distress among COVID-19 Survivors during the Convalescence Period: A Multi-Centre Study in Malaysia
Authors: Abdul Taib Nur Iwana , Nik Jaafar Nik Ruzyanei , Azman Nazirah , Leong Bin Abdullah Mohammad Farris Iman , Mohamad Kamal Nurul Ain , Baharudin Azlin , Bin Abdullah Muhammad Najib , Chidambaram Suresh Kumar , Adlan Alif , Tan Loong Hui , Tamilselvam Satya , Mohamed Said Mohd Shahrir , Abd Samad Anuar , Binti Dollah Siti Nordiana
Published: February 2023

High rates of psychological distress among COVID-19 survivors and stigmatisation have been reported in both early and late convalescence. This study aimed to compare the severity of psychological distress and to determine the associations among sociodemographic and clinical characteristics, stigma, and psychological distress among COVID-19 survivors across two different cohorts at two different time points. Data were collected cross-sectionally in two groups at one month and six months post-hospitalisation among COVID-19 patient from three hospitals in Malaysia. This study assessed psychological distress and the level of stigma using the Kessler Screening Scale for Psychological Distress (K6) and the Explanatory Model Interview Catalogue (EMIC) stigma scale, respectively. At one month after discharge, significantly lower psychological distress was found among retirees (B = −2.207, 95% confidence interval [95% CI] = −4.139 to −0.068, p = 0.034), those who received up to primary education (B = −2.474, 95% CI = −4.500 to −0.521, p = 0.014), and those who had an income of more than RM 10,000 per month (B = −1.576, 95% CI = −2.714 to −0.505, p = 0.006). Moreover, those with a history of psychiatric illness [one month: (B = 6.363, 95% CI = 2.599 to 9.676, p = 0.002), six months: (B = 2.887, CI = 0.469–6.437, p = 0.038)] and sought counselling services [one month: (B = 1.737, 95% CI = 0.385 to 3.117, p = 0.016), six months: (B = 1.480, CI = 0.173–2.618, p = 0.032)] had a significantly higher severity of psychological distress at one month and six months after discharge from the hospital. The perceived stigma of being infected with COVID-19 contributed to greater severity of psychological distress. (B = 0.197, CI = 0.089–0.300, p = 0.002). Different factors may affect psychological distress at different periods of convalescence after a COVID-19 infection. A persistent stigma contributed to psychological distress later in the convalescence period.
Classification of Regional Healthy Environment and Public Health in China
Authors: Hu Cheng , Pan Wulin , Wen Li , Pan Wei
Published: February 2023

Environmental pollution has become a hot topic of concern for the government, academia and the public. The evaluation of environmental health should not only relate to environmental quality and exposure channels but also the level of economic development, social environmental protection responsibility and public awareness. We put forward the concept of the “healthy environment” and introduced 27 environmental indicators to evaluate and classify the healthy environment of 31 provinces and cities in China. Seven common factors were extracted and divided into economic, medical, ecological and humanistic environment factors. Based on the four environmental factors, we classify the healthy environment into five categories—economic leading healthy environment, robust healthy environment, developmental healthy environment, economic and medical disadvantageous healthy environment and completely disadvantageous healthy environment. The population health differences among the five healthy environment categories show that economic environment plays a major role in population health. Public health in regions with sound economic environment is significantly better than that in other areas. Our classification result of healthy environment can provide scientific support for optimizing environmental countermeasures and realizing environmental protection.
The Correlation between Peripheral Blood Index and Immune Cell Expansion in Vietnamese Elderly Lung Cancer Patients
Authors: Nguyen Hoang-Phuong , Bui Viet Anh , Hoang Ai-Xuan Thi , Van Nguyen Phong , Nguyen Dac-Tu , Mai Hien Thi , Le Hai-Anh , Nguyen Thanh-Luan , Hoang Nhung Thi My , Nguyen Liem Thanh , Nguyen Xuan-Hung
Published: February 2023

(1) Background: The dysfunction and reduced proliferation of peripheral CD8+ T cells and natural killer (NK) cells have been observed in both aging and cancer patients, thereby challenging the adoption of immune cell therapy in these subjects. In this study, we evaluated the growth of these lymphocytes in elderly cancer patients and the correlation of peripheral blood (PB) indices to their expansion. (2) Method: This retrospective study included 15 lung cancer patients who underwent autologous NK cell and CD8+ T cell therapy between January 2016 and December 2019 and 10 healthy individuals. (3) Results: On average, CD8+ T lymphocytes and NK cells were able to be expanded about 500 times from the PB of elderly lung cancer subjects. Particularly, 95% of the expanded NK cells highly expressed the CD56 marker. The expansion of CD8+ T cells was inversely associated with the CD4+:CD8+ ratio and the frequency of PB-CD4+ T cells in PB. Likewise, the expansion of NK cells was inversely correlated with the frequency of PB-lymphocytes and the number of PB-CD8+ T cells. The growth of CD8+ T cells and NK cells was also inversely correlated with the percentage and number of PB-NK cells. (4) Conclusion: PB indices are intrinsically tied to immune cell health and could be leveraged to determine CD8 T and NK cell proliferation capacity for immune therapies in lung cancer patients.
Investigation of Glypican-4 and -6 by Infrared Spectral Imaging during the Hair Growth Cycle
Authors: Colin-Pierre Charlie , Untereiner Valérie , Sockalingum Ganesh D. , Ramont Laurent , Brézillon Stéphane
Published: February 2023

The expression of glypicans in different hair follicle (HF) compartments is still poorly understood. Heparan sulfate proteoglycans (HSPGs) distribution in HF is classically investigated by conventional histology, biochemical analysis, and immunohistochemistry. Our previous study proposed a novel approach to assess hair histology and glypican-1 (GPC1) distribution changes in the HF at different phases of the hair growth cycle using infrared spectral imaging (IRSI). We show in the present manuscript for the first time complementary data on the distribution of glypican-4 (GPC4) and glypican-6 (GPC6) in HF at different phases of the hair growth cycle using IR imaging. Findings were supported by Western blot assays focusing on the GPC4 and GPC6 expression in HFs. Like all proteoglycan features, the glypicans are characterized by a core protein to which sulfated and/or unsulfated glycosaminoglycan (GAG) chains are covalently linked. Our study demonstrates the capacity of IRSI to identify the different HF tissue structures and to highlight protein, proteoglycan (PG), GAG, and sulfated GAG distribution in these structures. The comparison between anagen, catagen, and telogen phases shows the qualitative and/or quantitative evolution of GAGs, as supported by Western blot. Thus, in one analysis, IRSI can simultaneously reveal the location of proteins, PGs, GAGs and sulfated GAGs in HFs in a chemical and label-free manner. From a dermatological point of view, IRSI may constitute a promising technique to study alopecia.
Transformation of a Metal Chelate into a “Catch and Anchor” Inhibitor of Botulinum A Protease
Authors: Lin Lucy , Patel Ealin N. , Nielsen Alexander L. , Turner Lewis D. , Tepp William H. , Nguyen Kong , Pellett Sabine , Janda Kim
Published: February 2023

Targeting the botulinum neurotoxin light chain (LC) metalloprotease using small-molecule metal chelate inhibitors is a promising approach to counter the effects of the lethal toxin. However, to overcome the pitfalls associated with simple reversible metal chelate inhibitors, it is crucial to investigate alternative scaffolds/strategies. In conjunction with Atomwise Inc., in silico and in vitro screenings were conducted, yielding a number of leads, including a novel 9-hydroxy-4H-pyrido [1,2-a]pyrimidin-4-one (PPO) scaffold. From this structure, an additional series of 43 derivatives were synthesized and tested, resulting in a lead candidate with a Ki of 150 nM in a BoNT/A LC enzyme assay and 17 µM in a motor neuron cell-based assay. These data combined with structure-activity relationship (SAR) analysis and docking led to a bifunctional design strategy, which we termed “catch and anchor” for the covalent inhibition of BoNT/A LC. Kinetic evaluation was conducted on structures prepared from this catch and anchor campaign, providing kinact/Ki values, and rationale for inhibition seen. Covalent modification was validated through additional assays, including an FRET endpoint assay, mass spectrometry, and exhaustive enzyme dialysis. The data presented support the PPO scaffold as a novel candidate for targeted covalent inhibition of BoNT/A LC.