bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Molecular Biomarkers in Resected Early-Stage Non-Small Cells Lung Cancer: A Narrative Review
Authors: Gallina Filippo Tommaso , Bertolaccini Luca , Forcella Daniele , Mohamed Shehab , Ceddia Serena , Melis Enrico , Fusco Francesca , Bardoni Claudia , Marinelli Daniele , Buglioni Simonetta , Visca Paolo , Cappuzzo Federico , Spaggiari Lorenzo , Facciolo Francesco
Published: April 2022

Next-generation sequencing has become a cornerstone in clinical oncology practice and is recommended for the appropriate use of tailored therapies in NSCLC. While NGS has already been standardised in advanced-stage NSCLC, its use is still uncommon in the early stages. The recent approval of Osimertinib for resected EGFR-mutated NSCLC in an adjuvant setting has launched the hypothesis that other targeted therapies used in metastatic patients can also lead to improved early-stage outcomes of NSCLC. The impact of molecular biomarkers on the prognosis of patients undergoing radical surgery for NSCLC is still unclear. Notably, the heterogeneous populations included in the studies that analysed surgical patients could be the main reason for these results. In this review, we report the most important studies that analysed the impact of principal molecular biomarkers on the survival outcomes of patients who underwent radical surgery for NSCLC.
How Pyroptosis Contributes to Inflammation and Fibroblast-Macrophage Cross-Talk in Rheumatoid Arthritis
Authors: Demarco Benjamin , Danielli Sara , Fischer Fabian A. , Bezbradica Jelena S.
Published: April 2022

About thirty years ago, a new form of pro-inflammatory lytic cell death was observed and termed pyroptosis. Only in 2015, gasdermins were defined as molecules that create pores at the plasma membrane and drive pyroptosis. Today, we know that gasdermin-mediated death is an important antimicrobial defence mechanism in bacteria, yeast and mammals as it destroys the intracellular niche for pathogen replication. However, excessive and uncontrolled cell death also contributes to immunopathology in several chronic inflammatory diseases, including arthritis. In this review, we discuss recent findings where pyroptosis contributes to tissue damage and inflammation with a main focus on injury-induced and autoimmune arthritis. We also review novel functions and regulatory mechanisms of the pyroptotic executors gasdermins. Finally, we discuss possible models of how pyroptosis may contribute to the cross-talk between fibroblast and macrophages, and also how this cross-talk may regulate inflammation by modulating inflammasome activation and pyroptosis induction.
A Comparative Study on the Adipogenic Differentiation of Mesenchymal Stem/Stromal Cells in 2D and 3D Culture
Authors: Wolff Anne , Frank Marcus , Staehlke Susanne , Peters Kirsten
Published: April 2022

Mesenchymal stem/stromal cells (MSC) are capable of renewing the progenitor cell fraction or differentiating in a tissue-specific manner. Adipogenic differentiation of adipose-tissue-derived MSC (adMSC) is important in various pathological processes. Adipocytes and their progenitors are metabolically active and secrete molecules (adipokines) that have both pro- and anti-inflammatory properties. Cell culturing in 2D is commonly used to study cellular responses, but the 2D environment does not reflect the structural situation for most cell types. Therefore, 3D culture systems have been developed to create an environment considered more physiological. Since knowledge about the effects of 3D cultivation on adipogenic differentiation is limited, we investigated its effects on adipogenic differentiation and adipokine release of adMSC (up to 28 days) and compared these with the effects in 2D. We demonstrated that cultivation conditions are crucial for cell behavior: in both 2D and 3D culture, adipogenic differentiation occurred only after specific stimulation. While the size and structure of adipogenically stimulated 3D spheroids remained stable during the experiment, the unstimulated spheroids showed signs of disintegration. Adipokine release was dependent on culture dimensionality; we found upregulated adiponectin and downregulated pro-inflammatory factors. Our findings are relevant for cell therapeutic applications of adMSC in complex, three-dimensionally arranged tissues.
Estimation of Grain Size in Randomly Packed Granular Material Using Laser-Induced Breakdown Spectroscopy
Authors: Li Songting , Li Yaju , Li Xiaolong , Chen Liangwen , Qian Dongbin , Zhang Shaofeng , Ma Xinwen
Published: April 2022

Grain size is one of the most important physical parameters for randomly packed granular (RPG) materials. Its estimation, especially in situ, plays a key role in many natural and industrial processes. Here, the application of laser-induced breakdown spectroscopy (LIBS) was investigated experimentally to estimate the grain size in RPG materials. The experiment was performed by taking sieved copper microspheres with discrete median diameters ranging from 53 to 357 μm as examples and by measuring the plasma emissions induced by 1064 nm laser pulses with a duration of 7 ns in an air environment. It was found that the plasma emission measurements were successful in estimating the grain median diameter via monitoring the variations in plasma temperature (electron density) at the range of median diameter below (above) a critical value. In addition, it was demonstrated that, when plasma temperature serves as an indicator of grain size, the intensity ratio between two spectral lines from different upper energy levels of the same emitting species can be used as an alternative indicator with higher sensitivity. The results show the potential of using LIBS for in situ estimation of grain size in RPG materials for the first time.
Long-Term Changes in Four Populations of the Spiny Toad, Bufo spinosus, in Western France; Data from Road Mortalities
Authors: Meek Roger
Published: April 2022

Habitat fragmentation is widely recognized as a contributor to the decline of biodiversity, with amphibians one of the key groups impacted. To understand the effects of habitat fragmentation on amphibian populations requires long-term data sets showing population trends. In this paper, road mortalities were employed as proxies to describe long-term numbers of four populations of the spiny toad Bufo spinosus in western France during a 17-year period. Road mortalities were found during all months in all populations but were most frequent during October, November and December, the main migratory period. Large females were found significantly more frequently during these migration months, forming 45% of the total sample, compared with their presence from January to September (34.4%). The long-term trends were evaluated using regression analysis of the logarithmic (loge) transforms of annual counts as dependent variables against year as the independent variables. All coefficients showed no significant departure from the 0 hypothetical coefficients, indicative of population stability. This was supported by jackknife analysis, which showed good agreement of the pseudo-regression coefficients with the true equations. Stepwise regression of potential climate impacts on toad numbers suggested rainfall levels in October adjusted to 2- and 3-year lags were involved in driving population change. Road mortality counts were also made during 2020 and 2021 when human movement restrictions were in place due to the COVID-19 pandemic. To estimate the potential impact on this disturbance in the methodology, the Poisson distribution was used to estimate potential differences between what would have been expected counts and the observed counts. The results indicate that the observed mortalities were significantly lower than expected in all four populations.
Employing the Defective Photonic Crystal Composed of Nanocomposite Superconducting Material in Detection of Cancerous Brain Tumors Biosensor: Computational Study
Authors: Malek C. , Al-Dossari M. , Awasthi S. , Matar Z. , Abd El-Gawaad N. , Sabra Walied , Aly Arafa
Published: April 2022

The present research is focused on the externally tunable defect mode properties of a one dimensional (1D) defective photonic crystal (DPhC) for fast detection of cancerous brain tumors. The proposed design has utilized conventional 1D DPhC whose cavity is coated with SiO2 nanoparticles embedded in a superconducting material layer called a nanocomposite layer. The purpose of a nanocomposite superconducting layer is to induce temperature dependent external tuning of the defect mode inside PBG, in addition, to changing in the angle of incidence. The inclusion of a nanocomposite layer also improves the interaction between light and different brain tissue samples under examination. In order to investigate the transmission properties of the proposed structure the transfer matrix formulation in addition to the MATLAB computational tool has been used. First, we have chosen the optimized internal parameters at normal incidence to obtain the maximum performance of the design. Secondly, the effect of change in angle of incidence has been studied to further increase the performance by means of sensitivity, quality factor, the figure of merit and limit of detection to ensure external tuning of defect mode. After achieving a maximum value of sensitivity (4139.24 nm/RIU) corresponding to a sample containing a wall of brain tissues at θ = 63° we have further investigated the effect of change in temperature of nanocomposite layers on the position and intensity both of the defect mode inside PBG. We have found that the increase in temperature results in minute changes in sensitivity but a significant increase in the intensity of defect mode which is highly required in any photonic biosensing design. The findings of this study may be very useful for designing various bio-sensing structures which could have a significant and decisive role in the field of biomedical applications.
Progress of InGaN-Based Red Micro-Light Emitting Diodes
Authors: Li Panpan , Li Hongjian , Wong Matthew S. , Chan Philip , Yang Yunxuan , Zhang Haojun , Iza Mike , Speck James S. , Nakamura Shuji , Denbaars Steven P.
Published: April 2022

InGaN-based red micro-size light-emitting diodes (μLEDs) have become very attractive. Compared to common AlInGaP-based red µLEDs, the external quantum efficiency (EQE) of InGaN red µLEDs has less influence from the size effect. Moreover, the InGaN red µLEDs exhibit a much more robust device performance even operating at a high temperature of up to 400 K. We review the progress of InGaN red μLEDs. Novel growth methods to relax the strain and increase the growth temperature of InGaN red quantum wells are discussed.
Periodicity of Superatomic Hybrid Orbitals in Substituted Superatoms and Superatomic-like X@Ga12 (X = Li~Kr) Clusters
Authors: Nishimura Takaki , Toba Teruyuki , Sakane Genta , Ishii Tomohiko
Published: April 2022

A superatom is a cluster composed of a specific number of atoms. We recently found that the superatom-like X@Ga12 (X = Li~Kr) clusters has the periodic energy levels of the specific orbitals 2S and 2P by means of the DV-Xα molecular orbital calculation method. This periodicity in energy levels has not been seen in 1D or 1F orbitals. We supposed that the periodicity of the energy levels of the 2S and 2P superatomic-like orbitals come from the same symmetry between atomic orbitals as the central atom X and the surrounding specific orbitals, according to the Jellium model. Both the s and p atomic orbitals of the central atom X in the superatom-like X@Ga12 have a large shielding effect, suggesting that the s and p atomic orbitals interact strongly with both 2S and 2P superatomic-like orbitals. The energy level periodicity has the potential to periodically change the number of electrons located in the 1D and 1F orbitals, which is related to magnetic properties and is expected to be useful for novel magnetic devices by periodically controlling the magnetism of superatoms.
Prognostic Relevance of Weight and Weight Loss during Multimodal Therapy for Oesophagogastric Tumours
Authors: Lorusso Alessandro , Bichev Dmitry , Högner Anica , Bartels Prisca , Ballhausen Alexej , Treese Christoph , Biebl Matthias , Thuss-Patience Peter
Published: April 2022

The prognostic meaning of weight loss (WL) during standard treatment for operable oesophagogastric cancer is still unclear. The aim of this study is to analyse the prognostic effect of WL during perioperative chemotherapy (PC) for gastric cancer (GC) and oesophageal adenocarcinomas (OAC). We retrospectively analysed data from 128 patients (pts) with GC and OAC who underwent surgery in the context of multimodal treatment with PC. We collected data on WL during different steps of therapy together with other histopathologic and demographic information. We analysed the effects on overall survival (OS) and disease-free survival (DFS). Results: Pts with WL ≥ 5% during neoadjuvant chemotherapy exhibited significantly worse OS compared with pts with WL < 5% (median OS: 23.6 months [95% CI: 4.4–42.9] vs. 63.5 months [95% CI: 50.7–76.2], p = 0.007) and DFS (median DFS: 12.5 months [95% CI: 2.9–22.1] vs. 63.5 months [95% CI: 31.6–95.4], p = 0.016). Pts with WL ≥ 14% during the whole treatment exhibited significantly worse OS compared with pts with WL < 14% (median OS: 43.7 months [95% CI: 13.2–74.2] vs. not reached, p = 0.028) and DFS (median DFS: 34.3 months [95% CI: 14.0–54.5] vs. not reached, p = 0.038). Conclusion: WL patterns during neoadjuvant chemotherapy and during the whole treatment correlate with a significantly worse prognosis in operated pts with curative GC or OAC in the context of a multimodal treatment with PC. A validation of this prognostic effect in prospective studies is warranted.
Bycatch Dynamics from a Small-Scale Shrimp Trap Fishery in the Mediterranean Sea
Authors: Kalogirou Stefanos , Dimitriadis Charalampos , Maravelias Christos D. , Poursanidis Dimitrios , Margaritis Mihalis , Miliou Helen , Pihl Leif
Published: April 2022

Small-scale fisheries (SSFs) in the Mediterranean and Black seas play a significant social and economic role, representing 84% of the fishing fleet (70,000 vessels), 26% of total revenue (USD 633 million) and 60% of total employment (150,000 people), with the Food and Agriculture Organization (FAO) recently taking important initiatives to sustain livelihoods. Effective management of important natural fisheries resources that sustain livelihoods requires a holistic approach accounting for all parts of the catch. Quantitative data on seasonal catch dynamics together with classification of bycatch species to IUCN vulnerability status and associated revenues from retained incidental catch were used to reveal the effect of a small-scale shrimp trap fishery on bycatch. We use three main quantitative variables (i.e., density, biomass and number of bycatch species) and show a positive correlation between bycatch and the seasonal catch dynamics of the target species during late spring and summer. On the contrary, discards were proportionally lower during winter, with the majority of discarded fish species not considered endangered. Six retained species in spring–summer and five discarded species in winter were found to modulate the structure of species’ assemblage. Out of 55 bycatch species, 26 were retained and 29 discarded. Only four species were considered threatened, all of which were caught in very low numbers (<2 individuals), while the majority of the retained species was not considered endangered. The rapid sorting time (<1 min/per trap) pointed towards a decreased effect on certain discarded crustacean species and a significant reduction in total bycatch with timely haul time (from 71 to 47%). The results of this study can be used when considering future mitigation measures for this fishery, while the methodology used can provide insights into the management of similar trap fisheries worldwide when taking into account the sustainability of SSFs and the regional vulnerability status of bycatch species.
Predicting the Severity of Lockdown-Induced Psychiatric Symptoms with Machine Learning
Authors: D’Urso Giordano , Magliacano Alfonso , Rotbei Sayna , Iasevoli Felice , de Bartolomeis Andrea , Botta Alessio
Published: April 2022

During the COVID-19 pandemic, an increase in the incidence of psychiatric disorders in the general population and an increase in the severity of symptoms in psychiatric patients have been reported. Anxiety and depression symptoms are the most commonly observed during large-scale dramatic events such as pandemics and wars, especially when these implicate an extended lockdown. The early detection of higher risk clinical and non-clinical individuals would help prevent the new onset and/or deterioration of these symptoms. This in turn would lead to the implementation of public policies aimed at protecting vulnerable populations during these dramatic contingencies, therefore optimising the effectiveness of interventions and saving the resources of national healthcare systems. We used a supervised machine learning method to identify the predictors of the severity of psychiatric symptoms during the Italian lockdown due to the COVID-19 pandemic. Via a case study, we applied this methodology to a small sample of healthy individuals, obsessive-compulsive disorder patients, and adjustment disorder patients. Our preliminary results show that our models were able to predict depression, anxiety, and obsessive-compulsive symptoms during the lockdown with up to 92% accuracy based on demographic and clinical characteristics collected before the pandemic. The presented methodology may be used to predict the psychiatric prognosis of individuals under a large-scale lockdown and thus supporting the related clinical decisions.
The Need for Standardization in Next-Generation Sequencing Studies for Classic Hodgkin Lymphoma: A Systematic Review
Authors: Santisteban-Espejo Antonio , Bernal-Florindo Irene , Perez-Requena Jose , Atienza-Cuevas Lidia , Moran-Sanchez Julia , Fernandez-Valle María del Carmen , Romero-Garcia Raquel , Garcia-Rojo Marcial
Published: April 2022

Classic Hodgkin lymphoma (cHL) constitutes a B cell-derived neoplasm defined by a scarce tumoral population, termed Hodgkin and Reed–Sternberg (HRS) cells, submerged into a histologically heterogeneous microenvironment. The paucity of HRS cells has historically hampered genetic studies, rendering the identification of the recurrent genetic lesions and molecular pathways deregulated in this lymphoma difficult. The advent of high-throughput sequencing methods such as next-generation sequencing (NGS) could sensibly optimize the identification of the mutational landscape of cHL. However, there is no current consensus either in the design of panels for targeted NGS or in its most relevant clinical applications. In this work, we systematically review the current state of NGS studies of cHL, stressing the need for standardization both in the candidate genes to be analyzed and the bioinformatic pipelines. As different institutions have developed and implemented their own customized NGS-based protocols, to compare and systematically review the major findings of this ongoing research area could be of added value for centers that routinely perform diagnostic, monitoring and genotyping strategies in cHL samples. The results of this systematic review should contribute to the interdepartmental harmonization and achievement of a consensus in the current clinical applications of NGS studies of cHL.
Fault Diagnosis Method of Six-Phase Permanent Magnet Synchronous Motor Based on Vector Space Decoupling
Authors: Gao Hanying , Guo Jie , Hou Zengquan , Zhang Bangping , Dong Yao
Published: April 2022

Compared with the three-phase motor, the six-phase motor has lower torque ripple and higher fault tolerance performance, which makes it widely used in aviation, ships, industrial manufacturing, and other application fields. However, the probability of failure of the polyphase motor system increases with the increase in the number of phases. In order to deal with the open phase fault and power switch fault of the six-phase inverter, a fault diagnosis method for the six-phase inverter based on vector space decoupling (VSD) is proposed. The open phase fault index is first determined according to the VSD decoupling inverse transform and the current constraints. The fault index is then optimized from the perspective of preventing misdiagnosis and improving reliability, and the open phase fault can be diagnosed in one fundamental cycle. In addition, the current trajectory of harmonic plane after switch fault is analyzed, and the back propagation (BP) neural network is used to identify the harmonic plane current trajectory of different types of switch fault. Finally, the correctness and feasibility of the proposed fault diagnosis method are verified by simulations and experiments. The obtained results demonstrate that the proposed method can quickly and accurately locate the open phase fault and switch fault without additional hardware. The proposed method is simple, efficient, and robust.
Interpretation of Eccentricity of an Enameled Wire by Capacitance Measurements
Authors: Ait-Amar Sonia , Koita Abdoulay , Vélu Gabriel
Published: April 2022

There are systems dedicated to measuring the eccentricity of enameled wires based on optical and electromagnetic phenomena. However, these methods are limited by the nature of the insulation and the conductor. The proposed solution consists of checking the wire eccentricity by an electrical measurement. Since it is a conductor on which an insulator is placed, the idea consists of forming a capacitor and measuring its capacitance in order to deduce the insulation thickness.
Prediction of the Total Base Number (TBN) of Engine Oil by Means of FTIR Spectroscopy
Authors: Wolak Artur , Molenda Jarosław , Fijorek Kamil , Łankiewicz Bartosz
Published: April 2022

The objective of this study is to develop a statistical model to accurately estimate the total base number (TBN) value of diesel engine oils on the basis of the Fourier transform infrared spectroscopy (FTIR) analysis. The research sample consisted of oils used in the course of 14,820 km. The samples were collected after each 1000 km and both FTIR and TBN measurements were performed. By applying the measured absorbance values, five statistical models aimed at predicting TBN values were elaborated with the use of the following information: aggregated values of measured absorbance in defined spectral ranges, extremes at wavenumbers, or the surface area of spectral bands related to the vibrations of specific molecular structures. The obtained models may be considered a continuation and an extension of previous studies of this type described in the literature on the subject. The results of the study and the analysis of the obtained data have led to the development of two models with high predictive capabilities (R2 > 0.98, RMSE < 0.5). Another model, which had the smallest number of variables in comparison to other models, had markedly lower R2 value (0.9496) and the highest RMSE (0.5596). Yet another model, where the dimensionality of the pre-processed full spectra was reduced to four aggregates through averaging, turned out to be slightly worse than the best one (R2 = 0.9728). The study contributes to a more in-depth understanding of the FTIR-based TBN prediction tools that may be readily available to all interested parties.
A Novel Microgrid Islanding Detection Algorithm Based on a Multi-Feature Improved LSTM
Authors: Xia Yan , Yu Feihong , Xiong Xingzhong , Huang Qinyuan , Zhou Qijun
Published: April 2022

Islanding detection is one of the conditions necessary for the safe operation of the microgrid. The detection technology should provide the ability to differentiate islanded operations from power grid disturbances effectively. Given that it is difficult to set the fault threshold using the passive detection method, and because the traditional active detection method affects the output power quality, a microgrid islanding detection method based on the Sliding Window Discrete Fourier Transform (SDFT)-Empirical Mode Decomposition (EMD) and Long Short-Term Memory (LSTM) network optimized by an attention mechanism is proposed. In this paper, the inverter output current and voltage at the point of common coupling (PCC) are transformed by the SDFT. The positive sequence, zero sequence, and negative sequence components of voltage and current harmonics are calculated and reconstructed by adopting the symmetrical component method (SCM). Meanwhile, the current and voltage are decomposed into a mono intrinsic mode function (IMF). The symmetric components of voltage, current, and IMFs are used as inputs to the deep learning algorithm. An LSTM with the features extracted to classify islanding and grid disturbance is proposed. By using the attention mechanism to set the weight values of the features of hidden states obtained by the LSTM network, the proportion of important features increases, which improves the classification effect. MATLAB/Simulink simulation results indicate that the proposed method can effectively classify the islanding state under different working conditions with an accuracy level of 98.4% and a loss value of 0.0725 with a maximal detection time of 66.94 ms. It can also reduce the non-detection zone (NDZ) and detection time and has a certain level of noise resistance. Meanwhile, the problem whereby the active method affects the microgrid power quality is avoided without disturbing the current or power of the microgrid.
Diagnostics of High Water Content Paper-Oil Transformer Insulation Based on the Temperature and Frequency Dependencies of the Loss Tangent
Authors: Zukowski Pawel , Rogalski Przemyslaw , Bondariev Vitalii , Sebok Milan
Published: April 2022

The aim of the work was to prepare and test a paper-oil insulation system according to the recommendations of CIGRE (Conseil International des Grands Réseaux Électriques) with the parameters X = 50% and Y = 30%. Pressboard was moistened to a water content of (5.0 ± 0.2) wt.% The loss tangent was measured using a DIRANA meter (FDS-PDC dielectric response analyzer) in the frequency range 10−4 Hz–5000 Hz for 6 temperatures from 293.15 K to 333.15 K with a step of 8 K. The waveforms simulated by the DIRANA software were fitted to the experimental dependence of the loss tangent. The fitting process was performed using two methods. In the first method, the measuring temperature value as well as X and Y values were entered into the software. The estimated moisture content of the insulation varied from about 1.4 to about 5.2 wt.%. The average value of moisture content was (3.73 ± 1.11) wt.%. In the second method, only the measuring temperature value was entered into the software. This improved the quality of matching. The estimated average moisture content was (5.83 ± 0.25) wt.%. It was found that the dimensions of the oil channel clearly affected the quality of the fitting process. By not taking into consideration real values of oil channel, the quality of the moisture content estimation was significantly improved.
Simultaneous Lightwave and Power Transfer for Internet of Things Devices
Authors: Filho José Ilton De Oliveira , Alkhazragi Omar , Trichili Abderrahmen , Ooi Boon S. , Alouini Mohamed-Slim , Salama Khaled Nabil
Published: April 2022

A laudable goal toward achieving autonomous internet of things (IoT) devices would be to use the same circuitry for communication and harvesting energy. One way to achieve it is through simultaneous lightwave and power transfer (SLIPT) that consists of using solar cells to harvest energy and receive information signals. Here, a SLIPT-based system that uses a large area solar panel to harvest energy from light sources and decode data signals is designed. The designed system is equipped with an infrared sensor used to detect the movements of an unmanned aerial vehicle. We equally discuss the wide-scale deployment of IoT devices with SLIPT capability.
The Forest Tent Caterpillar in Minnesota: Detectability, Impact, and Cycling Dynamics
Authors: Cooke Barry J. , Sturtevant Brian R. , Robert Louis-Etienne
Published: April 2022

If periodically outbreaking forest insects are a generic source of forest decline, then why do outbreaks recur more periodically than decline episodes? Do standard field survey data and proxy data systematically underestimate the complexity in herbivore population dynamics? We examine three sources of previously un-analyzed time-series data (population, defoliation, and tree-ring radial growth) for the forest tent caterpillar, Malacosoma disstria Hübner (Lepidoptera: Lasiocampidae) feeding on trembling aspen, Populus tremuloides Michx. (Salicaceae), in Minnesota, in order to answer these questions. Spatial pattern analysis of defoliation data indicated not only that outbreaks are roughly periodic, with a 10–13-y cycle, but also that important deviations from periodic led to large-scale episodes of aspen decline starting in the 1950s and 1960s, near Duluth and International Falls, respectively. By using additional data from Alberta, Canada we identify critical population and defoliation thresholds where defoliation becomes aerially detectable and impactful on tree growth. The threshold where defoliation becomes aerially detectable was found to be ~50% defoliation, corresponding to a population density of ~12 egg bands per 20 cm DBH tree (or ~20 cocoons per 3 min of collection time, or ~10 male moths per pheromone trap), and which implies a radial growth reduction on the order of 40%. We found that not all moth population peaks occur above the threshold level where defoliation is aerially detectable. Asynchronous pulses of defoliation—which are difficult to detect—produce asynchronous signatures of outbreak in tree-ring data. When these pulses occur in close conjunction with regular cycling, it can lead to outbreaks of prolonged duration that result in anomalously high tree mortality.
How Nostalgia Drives and Derails Living with Wildland Fire in the American West
Authors: Ladino Jennifer , Kobziar Leda N. , Kredell Jack , Cohn Teresa Cavazos
Published: April 2022

Representations of fire in the U.S. are often tinged with nostalgia: for unburned landscapes, for less frequent fires, for more predictable fire behavior, or for a simpler, more harmonious relationship between human communities and wildfire. Our perspective piece identifies four prevalent nostalgic figures that recur in popular representations of wildfire: the Giant Sequoia, the Heroic Firefighter engaged in “the Good Fight”, the Lone Frontiersman, and the “Noble Savage”. We assess the affordances and constraints of each of these figures for helping and/or hindering fire management. We consider how some forms of nostalgia position particular humans as heroes and fire as a villain, how others prioritize the communities that come together to face catastrophic fire events, and how some romanticize Indigenous burning practices. Drawing on knowledge from fire science, human geography, and the environmental humanities, we suggest that a more nuanced understanding of nostalgia can be useful for fire management and for finding healthier ways of living with more fire in the future.
Determinants of Choice and Wine Consumption Behaviour: A Comparative Analysis between Two Counties of Romania
Authors: Brata Anca Monica , Chiciudean Daniel I. , Brata Vlad Dumitru , Popa Dorin , Chiciudean Gabriela O. , Muresan Iulia C.
Published: April 2022

Wine, one of the world’s oldest and most popular beverages, has a distinct variety matching a diverse base of consumers worldwide. The study was conducted in two counties of Romania in order to identify consumers’ perception towards wine consumption, as well as the driving factors behind wine consumption and the decision process of choosing a certain type of wine. Thus, four factors were identified through principal component analysis: intrinsic cues and consumers’ experience, extrinsic cues and origin, notoriety and the label and package of the wine, correlating them with the socio-demographic characteristics of our respondents. It might be concluded that the intrinsic cues and consumer experience ranked highest among the priorities of the participants between 35 and 45 years old when choosing a certain type of wine. Additionally, notoriety was more valued by people with higher income, and people with experience in the domain inclined to pay more for a bottle of wine.
Beneficial Effects of Three Dietary Cyclodextrins on Preventing Fat Accumulation and Remodeling Gut Microbiota in Mice Fed a High-Fat Diet
Authors: Zhu Tong , Zhang Baixi , Feng Yan , Li Zhaofeng , Tang Xiaoshu , Ban Xiaofeng , Kong Haocun , Li Caiming
Published: April 2022

Globally, obesity and its metabolic complications, which are intimately linked to diet, are major public health problems. Cyclodextrins (CDs) are cyclic oligosaccharides consisting of (α-1,4)-linked D-glucopyranose units that can reduce fat bioavailability and affect metabolism by improving intestinal flora as prebiotics. We compared the effects of three CDs on preventing fat accumulation and remodeling gut microbiota in a high-fat diet-fed C57BL/6J mouse model. α-CD maximized energy expenditure by 12.53%, caused the RER value to drop from 0.814 to 0.788, and increased the proportion of fatty acid oxidation for energy supply. β-CD supplementation resulted in a marked 24.53% reduction in weight gain and a decrease in epididymal-fat-relative weight from 3.76% to 2.09%. It also minimized ectopic fat deposition and improved blood lipid parameters. γ-CD maximized the concentration of SCFAs in the cecum from 6.29 to 15.31 μmol/g. All three CDs reduced the abundance ratio of Firmicutes and Bacteroidetes to a low-fat diet level, increased the abundance of Lactobacillus and Akkermansia, and reduced the abundance of Allobaculum and Ruminococcus. These findings imply that a combination of multiple CDs may exert superior effects as a potential strategy for obesity prevention.
Carbon Footprint Reduction by Transitioning to a Diet Consistent with the Danish Climate-Friendly Dietary Guidelines: A Comparison of Different Carbon Footprint Databases
Authors: Trolle Ellen , Nordman Matilda , Lassen Anne Dahl , Colley Tracey A. , Mogensen Lisbeth
Published: April 2022

Dietary transitions are important for combating many of the environmental challenges humanity is facing today and reducing the global burden of disease. Different dietary patterns are associated with substantially different carbon footprints (CFs). This study aims to estimate the potential CF reduction on a transition from the current Danish diet to a plant-rich diet consistent with the Danish food-based dietary guidelines (FBDG) and to compare results obtained from the use of two different CF databases. Dietary intake data for adults aged 18–64 years from the national dietary survey 2011–2013 were used to calculate the CF of the current diet, and this was compared with the estimated CF of the plant-rich diet modelled for the FBDG. Calculations were carried out using an attributional life cycle assessment (LCA) database (AU-DTU data) and compared to calculations using a top-down hybrid consequential LCA database (BCD data). The transition from the current diet to the plant-rich diet showed a substantial estimated CF reduction of 31% with AU-DTU data, and a greater reduction with BCD data (43%). Ruminant meat reduction was the largest contributor to this CF reduction, especially with the use of BCD data, and other animal-based foods also contribute considerably to the CF reduction, especially with AU-DTU data. These results indicate that the choice of LCA methodology and CF database is important in estimation of dietary CF and for the development of guidelines to promote dietary change.
m5CRegpred: Epitranscriptome Target Prediction of 5-Methylcytosine (m5C) Regulators Based on Sequencing Features
Authors: He Zhizhou , Xu Jing , Shi Haoran , Wu Shuxiang
Published: April 2022

5-methylcytosine (m5C) is a common post-transcriptional modification observed in a variety of RNAs. m5C has been demonstrated to be important in a variety of biological processes, including RNA structural stability and metabolism. Driven by the importance of m5C modification, many projects focused on the m5C sites prediction were reported before. To better understand the upstream and downstream regulation of m5C, we present a bioinformatics framework, m5CRegpred, to predict the substrate of m5C writer NSUN2 and m5C readers YBX1 and ALYREF for the first time. After features comparison, window lengths selection and algorism comparison on the mature mRNA model, our model achieved AUROC scores 0.869, 0.724 and 0.889 for NSUN2, YBX1 and ALYREF, respectively in an independent test. Our work suggests the substrate of m5C regulators can be distinguished and may help the research of m5C regulators in a special condition, such as substrates prediction of hyper- or hypo-expressed m5C regulators in human disease.
Tearas Feollon: Tears and Weeping in Old English Literature
Authors: Magennis Hugh
Published: April 2022

This contribution surveys the range of images of weeping in Old English literature, concentrating particularly on weeping due to suffering, grief and unhappiness, and on tears of compunction, but examining other types of weeping as well, including supplicatory and sympathetic weeping (these latter are found in prose but not in poetry). Taking account of contemporary theory, the study understands weeping to be a physical manifestation of distress, but also to function as a social gesture, as reflected in the circumstance that most weeping in Old English is public rather than private. It is noted that saints do not normally weep in the literature despite the suffering they typically endure, and also that in traditional Old English poetry weeping is seen as not appropriate for men, or at least for men in the prime of life. Some of the most interesting instances of weeping in Old English, however, are to be found in episodes that appear to contradict or problematize such expectations, as is illustrated by the examination of a number of relevant examples. The references to weeping cited in this study are in the majority of cases based on Latin models, and reflect the wider Christian literary tradition in the early Middle Ages, rather than being specific to Anglo-Saxon England; but, in both religious and secular works, Old English writers are shown to be thoughtful and imaginative in their treatment of weeping and to deploy images of it to forceful emotive effect.
Exercise Interventions for Women with Ovarian Cancer: A Realist Review
Authors: McGrath Deirdre , O’Halloran Peter , Prue Gillian , Brown Malcolm , Millar Joanne , O’Donnell Adrina , McWilliams Lisa , Murphy Claire , Hinds Gwyneth , Reid Joanne
Published: April 2022

Background: Despite evidence indicating the benefits of exercise interventions for women with ovarian cancer both during and following treatment, uptake is poor. There is limited research exploring the implementation of such interventions for this cohort of women. The purpose of this review was to identify implementation theories in relation to exercise interventions for women with stages I–IV ovarian cancer, both during and following treatment; to explain positive and negative contextual factors, which may help or hinder implementation; and to develop a theory on how exercise interventions for women with ovarian cancer may be implemented. Methods: This realist review sourced literature from five electronic databases: CINAHL plus, Medline, Embase, PsycINFO and Google Scholar. Methodological rigour was assessed using the relevant critical appraisal skills programme tools. Results: Nine papers were included. Two intervention stages were identified: first, optimising uptake by providing education to patients on the benefits of exercise, approaching patients when symptoms are adequately managed and offering a personalised exercise programme; second, adherence and retention are influenced by the provision of an “autoregulated” exercise programme with additional supportive infrastructure, individualised goal setting and symptom management support where required. Conclusion: Women with ovarian cancer are reluctant to engage in exercise interventions, despite the supporting evidence in terms of positive clinical outcomes. This realist review elucidates underlying mechanisms and important contextual factors that will support and guide the implementation of exercise interventions for this cohort of women.
Patient Profile and Management of Delirium in Older Adults Hospitalized Due to COVID-19
Authors: Jorge-Samitier Pablo , Juárez-Vela Raúl , Santolalla-Arnedo Iván , Antón-Solanas Isabel , Gea-Caballero Vicente , Sánchez-González Juan Luis , Fernández-Rodrigo María Teresa
Published: April 2022

SARS-CoV-2 can cause neurologic symptoms, as well as respiratory ones. Older adults are at risk of developing acute delirium in older persons (ADOP). The combination of experiencing respiratory isolation due to COVID-19, as well as other associated risk factors for older adults, may have had an impact on ADOP and ADOP management in the acute hospital setting. This study aimed to analyze the characteristics of ADOP in patients admitted to a COVID-19 unit. An observational prospective study on a sample of 108 patients was carried out between November 2020 and May 2021. The following data were collected: sociodemographic characteristics, risk factors for ADOP, management of ADOP, and impact on ADOP on both functional and cognitive deterioration. A 29.6% proportion of older adults admitted to an acute COVID-19 unit presented hyperactive ADOP, mainly during the night. Management of ADOP in our sample involved mainly pharmacological treatment and had a serious impact on hospital stay and both functional and cognitive deterioration. Preventive strategies and being accompanied by a relative or a carer may be useful to manage ADOP during hospital admission due to COVID-19.
Nanoliposomes in Cancer Therapy: Marketed Products and Current Clinical Trials
Authors: Taléns-Visconti Raquel , Díez-Sales Octavio , de Julián-Ortiz Jesus Vicente , Nácher Amparo
Published: April 2022

The drugs used for cancer treatment have many drawbacks, as they damage both tumor and healthy cells and, in addition, they tend to be poorly soluble drugs. Their transport in nanoparticles can solve these problems as these can release the drug into tumor tissues, as well as improve their solubility, bioavailability, and efficacy, reducing their adverse effects. This article focuses on the advantages that nanotechnology can bring to medicine, with special emphasis on nanoliposomes. For this, a review has been made of the nanoliposomal systems marketed for the treatment of cancer, as well as those that are in the research phase, highlighting the clinical trials being carried out. All marketed liposomes studied are intravenously administered, showing a reduced intensity of side-effects compared with the nonliposomal form. Doxorubicin is the active ingredient most frequently employed. Ongoing clinical trials expand the availability of liposomal medicines with new clinical indications. In conclusion, the introduction of drugs in nanoliposomes means an improvement in their efficacy and the quality of life of patients. The future focus of research could be directed to develop multifunctional targeted nanoliposomes using new anticancer drugs, different types of existing drugs, or new standardized methodologies easily translated into industrial scale.
TBP, PPIA, YWHAZ and EF1A1 Are the Most Stably Expressed Genes during Osteogenic Differentiation
Authors: Franko Nina , Vrščaj Lucija Ana , Zore Taja , Ostanek Barbara , Marc Janja , Lojk Jasna
Published: April 2022

RT-qPCR is the gold standard and the most commonly used method for measuring gene expression. Selection of appropriate reference gene(s) for normalization is a crucial part of RT-qPCR experimental design, which allows accurate quantification and reliability of the results. Because there is no universal reference gene and even commonly used housekeeping genes’ expression can vary under certain conditions, careful selection of an appropriate internal control must be performed for each cell type or tissue and experimental design. The aim of this study was to identify the most stable reference genes during osteogenic differentiation of the human osteosarcoma cell lines MG-63, HOS, and SaOS-2 using the geNorm, NormFinder, and BestKeeper statistical algorithms. Our results show that TBP, PPIA, YWHAZ, and EF1A1 are the most stably expressed genes, while ACTB, and 18S rRNA expressions are most variable. These data provide a basis for future RT-qPCR normalizations when studying gene expression during osteogenic differentiation, for example, in studies of osteoporosis and other bone diseases.
TcdB of Clostridioides difficile Mediates RAS-Dependent Necrosis in Epithelial Cells
Authors: Stieglitz Florian , Gerhard Ralf , Hönig Rabea , Giehl Klaudia , Pich Andreas
Published: April 2022

A Clostridioides difficile infection (CDI) is the most common nosocomial infection worldwide. The main virulence factors of pathogenic C. difficile are TcdA and TcdB, which inhibit small Rho-GTPases. The inhibition of small Rho-GTPases leads to the so-called cytopathic effect, a reorganization of the actin cytoskeleton, an impairment of the colon epithelium barrier function and inflammation. Additionally, TcdB induces a necrotic cell death termed pyknosis in vitro independently from its glucosyltransferases, which are characterized by chromatin condensation and ROS production. To understand the underlying mechanism of this pyknotic effect, we conducted a large-scale phosphoproteomic study. We included the analysis of alterations in the phosphoproteome after treatment with TcdA, which was investigated for the first time. TcdA exhibited no glucosyltransferase-independent necrotic effect and was, thus, a good control to elucidate the underlying mechanism of the glucosyltransferase-independent effect of TcdB. We found RAS to be a central upstream regulator of the glucosyltransferase-independent effect of TcdB. The inhibition of RAS led to a 68% reduction in necrosis. Further analysis revealed apolipoprotein C-III (APOC3) as a possible crucial factor of CDI-induced inflammation in vivo.
TransPhos: A Deep-Learning Model for General Phosphorylation Site Prediction Based on Transformer-Encoder Architecture
Authors: Wang Xun , Zhang Zhiyuan , Zhang Chaogang , Meng Xiangyu , Shi Xin , Qu Peng
Published: April 2022

Protein phosphorylation is one of the most critical post-translational modifications of proteins in eukaryotes, which is essential for a variety of biological processes. Plenty of attempts have been made to improve the performance of computational predictors for phosphorylation site prediction. However, most of them are based on extra domain knowledge or feature selection. In this article, we present a novel deep learning-based predictor, named TransPhos, which is constructed using a transformer encoder and densely connected convolutional neural network blocks, for predicting phosphorylation sites. Data experiments are conducted on the datasets of PPA (version 3.0) and Phospho. ELM. The experimental results show that our TransPhos performs better than several deep learning models, including Convolutional Neural Networks (CNN), Long-term and short-term memory networks (LSTM), Recurrent neural networks (RNN) and Fully connected neural networks (FCNN), and some state-of-the-art deep learning-based prediction tools, including GPS2.1, NetPhos, PPRED, Musite, PhosphoSVM, SKIPHOS, and DeepPhos. Our model achieves a good performance on the training datasets of Serine (S), Threonine (T), and Tyrosine (Y), with AUC values of 0.8579, 0.8335, and 0.6953 using 10-fold cross-validation tests, respectively, and demonstrates that the presented TransPhos tool considerably outperforms competing predictors in general protein phosphorylation site prediction.