bluuebunny/crossref_metadata_2025 huggingface dataset:
Dealing with Gender Bias Issues in Data-Algorithmic Processes: A Social-Statistical Perspective
Authors: Castaneda Juliana , Jover Assumpta , Calvet Laura , Yanes Sergi , Juan Angel A. , Sainz Milagros
Published: August 2022

Are algorithms sexist? This is a question that has been frequently appearing in the mass media, and the debate has typically been far from a scientific analysis. This paper aims at answering the question using a hybrid social and technical perspective. First a technical-oriented definition of the algorithm concept is provided, together with a more social-oriented interpretation. Secondly, several related works have been reviewed in order to clarify the state of the art in this matter, as well as to highlight the different perspectives under which the topic has been analyzed. Thirdly, we describe an illustrative numerical example possible discrimination in the banking sector due to data bias, and propose a simple but effective methodology to address it. Finally, a series of recommendations are provided with the goal of minimizing gender bias while designing and using data-algorithmic processes to support decision making in different environments.
A Systematic Approach for Developing a Robust Artwork Recognition Framework Using Smartphone Cameras
Authors: Theodosiou Zenonas , Thoma Marios , Partaourides Harris , Lanitis Andreas
Published: August 2022

The provision of information encourages people to visit cultural sites more often. Exploiting the great potential of using smartphone cameras and egocentric vision, we describe the development of a robust artwork recognition algorithm to assist users when visiting an art space. The algorithm recognizes artworks under any physical museum conditions, as well as camera point of views, making it suitable for different use scenarios towards an enhanced visiting experience. The algorithm was developed following a multiphase approach, including requirements gathering, experimentation in a virtual environment, development of the algorithm in real environment conditions, implementation of a demonstration smartphone app for artwork recognition and provision of assistive information, and its evaluation. During the algorithm development process, a convolutional neural network (CNN) model was trained for automatic artwork recognition using data collected in an art gallery, followed by extensive evaluations related to the parameters that may affect recognition accuracy, while the optimized algorithm was also evaluated through a dedicated app by a group of volunteers with promising results. The overall algorithm design and evaluation adopted for this work can also be applied in numerous applications, especially in cases where the algorithm performance under varying conditions and end-user satisfaction are critical factors.
The Costs of Ambiguity in Strategic Contexts
Authors: Arend Richard J.
Published: August 2022

With this research, we contribute to the study of ambiguity by analyzing how it can be handled in a rational, objective manner across the main strategic decision-making contexts that entrepreneurs and organizations face. Differentiating from most previous managerial and entrepreneurial studies, we conduct the analysis from a mathematical rather than an experimental approach, doing so by considering variants of a robust, yet simple, decision problem. Significantly, the analysis offers a simple model and approach to consider as benchmarks when assessing the impact of an ambiguity level of information against cases where more precise information is available. We identify the many costs of ambiguity, including direct absolute and relative maximum harms, as well as indirect possible penalties. We discuss the strategic entrepreneurial and managerial implications.
Effects of Digested Pig Slurry on Photosynthesis, Carbohydrate Metabolism and Yield of Tomato (Solanum lycopersicum L.)
Authors: Teng Yunfei , Shang Bin , Tao Xiuping
Published: August 2022

Soilless cultivation of vegetables is widely used in production. It is also well accepted that digested slurry is frequently applied as a fertilizer in agricultural production. However, the effect of digested pig slurry on yield and quality of tomato soilless cultivation, as well as the yield and quality influenced by plant carbohydrate metabolism, remain unexplored. Here, the dual inputs of fertilizers (digested pig slurry (D) and mineral fertilizer (M)) and soilless substrates (peat substrate (P) and cinder substrate(C)) consisted of four treatments. The dry biomass and fruit yields, photosynthetic parameters, carbohydrate contents and metabolism enzymes in leaves and fruits were recorded during the experimental period. The highest fruit yields were obtained in DP and MP treatments. Although DP treatment significantly increased the fresh weight of single fruits by 18.0% compared to MP treatment, it reduced the number of ripe fruits. The photosynthetic efficiency and carbohydrate contents (sucrose, glucose and fructose) in leaves were generally higher in DP treatment compared to other treatments, as well as the activities of sucrose phosphate synthase and AGPase in leaves. The soluble sugar contents of fruits in DP and DC treatments were enhanced by 12.3% and 37.0%, respectively, compared to MP and MC treatments. Moreover, the current results showed that DP treatment significantly increased the activity of acid invertase in fruit by 36.3%, 31.3%, and 42.2%, respectively, compared to MP, DC, and MC treatments, and decreased the activity of AGPase by 24.2%, 16.0%, and 36.4%, respectively. The current results have demonstrated that DP treatment had better yield and quality, owing to digested pig slurry increasing the photosynthetic efficiency and source strength, and regulated the activities of carbohydrate metabolism enzymes.
Acetabular Coverage Area Occupied by the Femoral Head as an Indicator of Hip Congruency
Authors: Franco-Gonçalo Pedro , Moreira da Silva Diogo , Leite Pedro , Alves-Pimenta Sofia , Colaço Bruno , Ferreira Manuel , Gonçalves Lio , Filipe Vítor , McEvoy Fintan , Ginja Mário
Published: August 2022

Accurate radiographic screening evaluation is essential in the genetic control of canine HD, however, the qualitative assessment of hip congruency introduces some subjectivity, leading to excessive variability in scoring. The main objective of this work was to validate a method-Hip Congruency Index (HCI)-capable of objectively measuring the relationship between the acetabulum and the femoral head and associating it with the level of congruency proposed by the Fédération Cynologique Internationale (FCI), with the aim of incorporating it into a computer vision model that classifies HD autonomously. A total of 200 dogs (400 hips) were randomly selected for the study. All radiographs were scored in five categories by an experienced examiner according to FCI criteria. Two examiners performed HCI measurements on 25 hip radiographs to study intra- and inter-examiner reliability and agreement. Additionally, each examiner measured HCI on their half of the study sample (100 dogs), and the results were compared between FCI categories. The paired t-test and the intraclass correlation coefficient (ICC) showed no evidence of a systematic bias, and there was excellent reliability between the measurements of the two examiners and examiners’ sessions. Hips that were assigned an FCI grade of A (n = 120), B (n = 157), C (n = 68), D (n = 38) and E (n = 17) had a mean HCI of 0.739 ± 0.044, 0.666 ± 0.052, 0.605 ± 0.055, 0.494 ± 0.070 and 0.374 ± 0.122, respectively (ANOVA, p < 0.01). Therefore, these results show that HCI is a parameter capable of estimating hip congruency and has the potential to enrich conventional HD scoring criteria if incorporated into an artificial intelligence algorithm competent in diagnosing HD.
Silymarin Modulates Microbiota in the Gut to Improve the Health of Sow from Late Gestation to Lactation
Authors: Xu Shengyu , Jiang Xiaojun , Jia Xinlin , Jiang Xuemei , Che Lianqiang , Lin Yan , Zhuo Yong , Feng Bin , Fang Zhengfeng , Li Jian , Wang Jianping , Ren Zhihua , Wu De
Published: August 2022

Inflammatory responses reduce milk production in lactating sows. Silymarin may modulate inflammatory reactions. Here, we aimed to verify whether dietary silymarin supplementation could alleviate inflammatory responses in lactating sows through microbiota change in the gut. We also investigated how silymarin impacts inflammatory response in lactating sows. One hundred and ten sows were randomly assigned to a control diet (basal diet) or treatment diet (basal diet and 40 g/d silymarin) from the 108th day of gestation to weaning. Blood, milk, and feces from sows were collected for analysis. It was shown in the results that dietary silymarin supplementation decreased the level of pro-inflammatory cytokine IL-1β (p < 0.05) on the 18th day of lactation in the blood of the sows. Dietary silymarin supplementation tended to decrease (p = 0.06) somatic cell count in the colostrum of sows. Dietary silymarin supplementation reduced the gut bacterial community and the richness of the gut microbial community (p < 0.01) using 16S rRNA gene sequencing. The fecal microbes varied at different taxonomic levels in the lactating sows with silymarin supplementation. The most representative changes included an increase in the relative abundance of Fibrobacteres and Actinobacteria (p < 0.05) and tended to reduce the relative abundance of Spirochaetaes and Tenericutes (p = 0.09, 0.06) at the phylum level. It is suggested that dietary silymarin supplementation in late gestation until lactation has anti-inflammatory effects in lactation sow, which could be associated with the modulation of gut microbiota.
Evaluation of Different Chemical Mechanisms on O3 and PM2.5 Predictions in Alberta, Canada
Authors: Shareef Mujtaba , Cho Sunny , Lyder David , Zelensky Michael , Heckbert Scott
Published: August 2022

We evaluated the uncertainty associated with secondary pollutants formation due to different chemical mechanisms in photochemical modelling. The CMAQ modelling system was utilized in conjunction with CB6R3, SAPRC07, and RACM2 chemical mechanisms and compared the concentrations of various chemical species, including ozone (O3) and particulate matter (PM2.5). Using datasets from ambient monitoring stations, we assessed the performance of each of the mechanism in summer and winter. The concentrations of various chemical species predicted by the three mechanisms varied significantly. The differences are more evident in summer than in winter for most of the species, except for hydrogen peroxide (H2O2), methyl hydroperoxide (MEPX), and Secondary Organic Aerosol—Anthropogenic. We observed that the summer daytime O3 predictions showed reasonable peaks at the three air quality monitoring sites, but the nighttime values under-predicted for all three mechanisms. In the winter, all three mechanisms tend to under-predict O3. Differences in the mean O3 values (bias) at the different sites, for the different seasons, are consistent with corrections made to previous modelling studies that modified KZMIN. PM2.5 predictions with RACM2 were slightly better. The dominant PM2.5 species in summer were sulfate and SOA-Bio, which may be attributed to non-mobile sources in the region, while NO3 became dominant in winter due to more favorable conditions for forming this species, including lower temperatures and an elevated NH4 to SO4 ratio. We concluded that the differences in O3 and PM2.5 predictions between the three mechanisms are significant, implying that when developing strategic and management actions are based on modelling, the most appropriate mechanism should be considered.
Characteristics and Provenance Implications of Rare Earth Elements and Nd Isotope in PM2.5 in a Coastal City of Southeastern China
Authors: Li Yihong , Wang Shanshan , Yan Yu , Yan Jinpei , Yu Ruilian , Hu Gongren
Published: August 2022

The source apportionment of fine particulate matters, especially PM2.5, has drawn great attention worldwide. Since rare earth elements (REEs) and Nd isotopes can serve as source tracers, in this study, the characteristics and provenance implications of REEs and Nd isotopes in PM2.5 of four seasons in Xiamen city, China, were investigated. The range of the ratios of ΣREE to PM2.5 was 1.04 × 10−5 to 8.06 × 10−4, and the mean concentration of REEs in PM2.5 were in the order of spring > autumn > winter > summer. According to the geoaccumulation index (Igeo), spring was the season in which anthropogenic sources had the greatest impact on the REEs in PM2.5. The chondrite-normalized REE distribution patterns exhibited light rare earth elements (LREEs, including La, Ce, Pr, Nd, Pm, Sm and Eu) enrichment and a flat heavy rare earth elements (HREEs, including Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) pattern. Significant negative Eu anomalies and no significant Ce anomalies were observed in the PM2.5. The results of La-Ce-Sm ternary plots indicated that the REEs in the PM2.5 might be related to both natural and anthropogenic sources. Combined with the Nd isotope, the 143Nd/144Nd versus Ce/Ce* plot further illustrated that the REEs in the PM2.5 seemed to mostly originate from multiple potential sources, in which vehicle exhaust emissions, coal burning and cement dust made a great contribution to REEs in PM2.5.
Random Forest-Based Model for Estimating Weighted Mean Temperature in Mainland China
Authors: Li Haojie , Li Junyu , Liu Lilong , Huang Liangke , Zhao Qingzhi , Zhou Lv
Published: August 2022

The weighted mean temperature (Tm) is a vital parameter for converting zenith wet delay (ZWD) into precipitation water vapor (PWV) and plays an essential part in the Global Navigation Satellite System (GNSS) inversion of PWV. To address the inability of current mainstream models to fit the nonlinear relationship between Tm and meteorological and spatiotemporal factors, whose accuracy is limited, a weighted mean temperature model using the random forest (named RFTm) was proposed to enhance the accuracy of the Tm predictions in mainland China. The validation with the Tm from 84 radiosonde stations in 2018 showed that the root mean square (RMS) of the RFTm model was reduced by 38.8%, 44.7%, and 35.5% relative to the widely used Global Pressure and Temperature 3 (GPT3) with 1° × 1°/5° × 5° versions and Bevis, respectively. The Bias and RMS of the new model in different latitude bands, various height intervals, and different times were significantly better than those of the other three comparative models. The accuracy of the new model presented a more stable adaptability. Therefore, this study provides a new idea for estimating Tm and can provide a more accurate Tm for GNSS meteorology.
Establishment of a Combined Model for Ozone Concentration Simulation with Stepwise Regression Analysis and Artificial Neural Network
Authors: Yu Jie , Xu Lingxuan , Gao Shuang , Chen Li , Sun Yanling , Mao Jian , Zhang Hui
Published: August 2022

With the development of industrialization and the increase in the number of motor vehicles in megacities in China, ozone pollution has become a prominent problem. Although different models have been used on ozone concentration simulation, the accuracy of different models still varies. In this study, the performance of two models including a linear stepwise regression (SR) model and a non-linear artificial neural network (ANN) model on the simulation of ozone concentration were analyzed in the Jing-Jin-Ji region, which is one of the most polluted areas in China. Results showed that the performance of the ANN model (adjusted R2 = 0.8299, RMSE = 22.87, MAE = 16.92) was better than the SR model (adjusted R2 = 0.7324, RMSE = 28.61, MAE = 22.30). The performance of the ANN on simulating an ozone pollution event was better than the SR model since a higher probability of detection (POD) and threat score (TS) values were obtained by the ANN model. The model performance for spring, autumn and winter was generally higher than that for summer, which may because the weights of factors on simulating high and low ozone concentrations were different. The method proposed by this study can be used in ozone concentration estimation.
Dust-Associated Bacterial and Fungal Communities in Indoor Multiple-Use and Public Transportation Facilities
Authors: Kim Jeongwon , Han Sang Jun , Yoo Keunje
Published: August 2022

Indoor microbes are readily transmitted among humans in indoor environments. Therefore, this study employed 16S rRNA gene and ITS amplicon profiling to investigate the dust-associated bacterial and fungal communities in six indoor facilities in Busan, South Korea. The collected samples were categorized into two groups: indoor multiple-use facilities (MUFs), including a public bathing facility, business office, and food court; and public transportation facilities (PTFs), including two subway stations and an airport. The bacterial diversity in the MUF samples was significantly higher than the fungal diversity (p < 0.05). However, no significant differences between bacterial and fungal diversity were observed in PTF samples (p > 0.05). Moreover, the abundances of certain microbial taxa varied, suggesting that the microbial community structure was primarily determined by the source environment. Gram-positive bacterial genera, such as Corynebacterium, Kocuria, and Staphylococcus—all of which originated in the natural environment—were relatively predominant in the MUF samples; the Aspergillus, Penicillium, and Malassezia genera, which are human commensal taxa, were relatively more predominant in the PTF samples. These results suggest that different microbial communities can be formed depending on the purpose of the indoor facility type, level of passenger traffic, and surrounding environment. The findings of this study may help researchers understand indoor microbial communities in multi-use and transportation facilities.
The Brave New World of Early Treatment of Multiple Sclerosis: Using the Molecular Biomarkers CXCL13 and Neurofilament Light to Optimize Immunotherapy
Authors: Pachner Andrew
Published: August 2022

Multiple sclerosis (MS) is a highly heterogeneous disease involving a combination of inflammation, demyelination, and CNS injury. It is the leading cause of non-traumatic neurological disability in younger people. There is no cure, but treatments in the form of immunomodulatory drugs (IMDs) are available. Experience over the last 30 years has shown that IMDs, also sometimes called disease-modifying therapies, are effective in downregulating neuroinflammatory activity. However, there are a number of negatives in IMD therapy, including potential for significant side-effects and adverse events, uncertainty about long-term benefits regarding disability outcomes, and very high and increasing financial costs. The two dozen currently available FDA-approved IMDs also are heterogeneous with respect to efficacy and safety, especially long-term safety, and determining an IMD treatment strategy is therefore challenging for the clinician. Decisions about optimal therapy have been particularly difficult in early MS, at the time of the initial clinical demyelinating event (ICDE), at a time when early, aggressive treatment would best be initiated on patients destined to have a highly inflammatory course. However, given the fact that the majority of ICDE patients have a more benign course, aggressive immunosuppression, with its attendant risks, should not be administered to this group, and should only be reserved for patients with a more neuroinflammatory course, a decision that can only be made in retrospect, months to years after the ICDE. This quandary of moderate vs. aggressive therapy facing clinicians would best be resolved by the use of biomarkers that are predictive of future neuroinflammation. Unfortunately, biomarkers, especially molecular biomarkers, have not thus far been particularly useful in assisting clinicians in predicting the likelihood of future neuroinflammation, and thus guiding therapy. However, the last decade has seen the emergence of two highly promising molecular biomarkers to guide therapy in early MS: the CXCL13 index and neurofilament light. This paper will review the immunological and neuroscientific underpinnings of these biomarkers and the data supporting their use in early MS and will propose how they will likely be used to maximize benefit and minimize risk of IMDs in MS patients.
Functional Characterization and Phenotyping of Protoplasts on a Microfluidics-Based Flow Cytometry
Authors: Dai Xingda , Zhang Shuaihua , Liu Siyuan , Qi Hang , Duan Xuexin , Han Ziyu , Wang Jiehua
Published: August 2022

A better understanding of the phenotypic heterogeneity of protoplasts requires a comprehensive analysis of the morphological and metabolic characteristics of many individual cells. In this study, we developed a microfluidic flow cytometry with fluorescence sensor for functional characterization and phenotyping of protoplasts to allow an unbiased assessment of the influence of environmental factors at the single cell level. First, based on the measurement of intracellular homeostasis of reactive oxygen species (ROS) with a DCFH-DA dye, the effects of various external stress factors such as H2O2, temperature, ultraviolet (UV) light, and cadmium ions on intracellular ROS accumulation in Arabidopsis mesophyll protoplasts were quantitatively investigated. Second, a faster and stronger oxidative burst was observed in Petunia protoplasts isolated from white petals than in those isolated from purple petals, demonstrating the photoprotective role of anthocyanins. Third, using mutants with different endogenous auxin, we demonstrated the beneficial effect of auxin during the process of primary cell wall regeneration. Moreover, UV-B irradiation has a similar accelerating effect by increasing the intracellular auxin level, as shown by double fluorescence channels. In summary, our work has revealed previously underappreciated phenotypic variability within a protoplast population and demonstrated the advantages of a microfluidic flow cytometry for assessing the in vivo dynamics of plant metabolic and physiological indices at the single-cell level.
An Apple Fungal Infection Detection Model Based on BPNN Optimized by Sparrow Search Algorithm
Authors: Zhao Changtong , Ma Jie , Jia Wenshen , Wang Huihua , Tian Hui , Wang Jihua , Zhou Wei
Published: August 2022

To rapidly detect whether apples are infected by fungi, a portable electronic nose was used in this study to collect the gas information from apples, and the collected information was processed by smoothing filtering, data dimensionality reduction, and outlier removal. Following this, we utilized K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), a convolutional neural network (CNN), a back-propagation neural network (BPNN), a particle swarm optimization–back-propagation neural network (PSO-BPNN), a gray wolf optimization–backward propagation neural network (GWO-BPNN), and a sparrow search algorithm–backward propagation neural network (SSA-BPNN) model to discriminate apple samples, and adopted the 10-fold cross-validation method to evaluate the performance of each model. The results show that SSA can effectively optimize the performance of the BPNN, such that the recognition accuracy of the optimized SSA-BPNN model reaches 98.40%. This study provides an important reference value for the application of an electronic nose in the non-destructive and rapid detection of fungal infection in apples.
Apoptosis Detection in Retinal Ganglion Cells Using Quantitative Changes in Multichannel Fluorescence Colocalization
Authors: Qiu Xudong , Gammon Seth T. , Johnson James R. , Pisaneschi Federica , Millward Steven W. , Barnett Edward M. , Piwnica-Worms David
Published: August 2022

KcapTR488 is a dual-fluorophore peptide sensor for the real-time reporting of programmed cell death by fluorescence imaging. KcapTR488 contains a nuclear localization sequence (NLS) conjugated with Texas Red, a caspase-cleavable sequence (DEVD), and a C-terminus conjugated to Alexa Fluor 488 (AF488). The synthesis and preliminary evaluation in cellulo of KcapTR488 for monitoring cell death by fluorescence imaging has been previously reported, but its utility in vivo has yet to be tested or validated. Herein, in vitro solution experiments verified the intramolecular fluorescence resonance energy transfer (FRET) between the two fluorophores and enabled a quantitative analysis of enzyme rates and selectivity. The sensor delivery kinetics in live rat models were quantified by ex vivo fluorescence microscopy. Studies in healthy control retinas demonstrated that KcapTR488 concentrated in the nucleus of retinal ganglion cells (RGC), with a strong colocalization of red and green fluorescence signals producing robust FRET signals, indicating an intact reporter. By contrast, using an acute but mild NMDA-induced retinal injury model, dual-color confocal ex vivo microscopy of cleaved KcapTR488 identified sensor activation as early as 2 h after injection. Quantitative changes in fluorescence colocalization were superior to changes in FRET for monitoring injury progression. Longitudinal monitoring revealed that the NLS-Texas Red fragment of the cleaved sensor moved out of the cell body, down the axon, and exited the retina, consistent with anterograde axonal transport. Thus, KcapTR488 may be a powerful tool to study RGC death pathways in live preclinical models of glaucoma.
An Immunochromatographic Assay for the Rapid and Qualitative Detection of Mercury in Rice
Authors: Lv Shuai , Xu Xinxin , Song Shanshan , Xu Liguang , Liu Liqiang , Xu Chuanlai , Kuang Hua
Published: August 2022

Mercury is a major pollutant in food crops. In this study, we synthesized an anti-mercury monoclonal antibody (mAb; IC50 was 0.606 ng mL−1) with high sensitivity and specificity and different immunogens and coating antigens and developed an immuno-chromatographic assay (ICA) for the detection of mercury in rice. The ICA strip had a visible detection limit of 20 ng g−1 and a cut-off value of 500 ng g−1 in rice. The performance of the ICA strip was consistent with that of ICP-MS and ic-ELISA. The recoveries of mercury in rice ranged from 94.5% to 113.7% with ic-ELISA and from 93.6% to 116.45% with ICP-MS. Qualitative analysis by ICA can be obtained with the naked eye. The ICA strip is an effective and practical method for the rapid and high-throughput determination of mercury in rice.
Aggregation-Induced Ignition of Near-Infrared Phosphorescence of Non-Symmetric [Pt(C^N*N’^C’)] Complex in Poly(caprolactone)-based Block Copolymer Micelles: Evaluating the Alternative Design of Near-Infrared Oxygen Biosensors
Authors: Zharskaia Nina A. , Solomatina Anastasia I. , Liao Yu-Chan , Galenko Ekaterina E. , Khlebnikov Alexander F. , Chou Pi-Tai , Chelushkin Pavel S. , Tunik Sergey P.
Published: August 2022

In the present work, we described the preparation and characterization of the micelles based on amphiphilic poly(ε-caprolactone-block-ethylene glycol) block copolymer (PCL-b-PEG) loaded with non-symmetric [Pt(C^N*N’^C’)] complex (Pt1) (where C^N*N’^C’: 6-(phenyl(6-(thiophene-2-yl)pyridin-2-yl)amino)-2-(tyophene-2-yl)nicotinate). The obtained nanospecies displayed the ignition of near-infrared (NIR) phosphorescence upon an increase in the content of the platinum complexes in the micelles, which acted as the major emission component at 12 wt.% of Pt1. Emergence of the NIR band at 780 nm was also accompanied by a 3-fold growth of the quantum yield and an increase in the two-photon absorption cross-section that reached the value of 450 GM. Both effects are believed to be the result of progressive platinum complex aggregation inside hydrophobic poly(caprolactone) cores of block copolymer micelles, which has been ascribed to aggregation induced emission (AIE). The resulting phosphorescent (Pt1@PCL-b-PEG) micelles demonstrated pronounced sensitivity towards molecular oxygen, the key intracellular bioanalyte. The detailed photophysical analysis of the AIE phenomena revealed that the NIR emission most probably occurred due to the excimeric excited state of the 3MMLCT character. Evaluation of the Pt1@PCL-b-PEG efficacy as a lifetime intracellular oxygen biosensor carried out in CHO-K1 live cells demonstrated the linear response of the probe emission lifetime towards this analyte accompanied by a pronounced influence of serum albumin on the lifetime response. Nevertheless, Pt1@PCL-b-PEG can serve as a semi-quantitative lifetime oxygen nanosensor. The key result of this study consists of the demonstration of an alternative approach for the preparation of NIR biosensors by taking advantage of in situ generation of NIR emission due to the nanoconfined aggregation of Pt (II) complexes inside the micellar nanocarriers.
Preliminary Results on the Comparative Evaluation of Alkaline Phosphatase Commercial Tests Efficiency in Non-Cow Milk Pasteurization
Authors: Tsiamita Asimo , Valiakos George , Natsaridis Nikolaos , Fotiadou Stamatia , Manouras Athanasios , Malissiova Eleni
Published: August 2022

The demand for non-cow milk and the products derived from it, is constantly increasing; thus, correct and effective pasteurization becomes necessary. Typical practices for evaluating milk pasteurization are mainly based on the thermal inactivation of an endogenous enzyme, alkaline phosphatase (ALP). The ALP tests, originally designed and applied to pasteurized cow milk, are often used to control pasteurization in non-cow milk, without sufficient data on their suitability; EFSA calls on the scientific world for collecting more information on the subject. In this study, the pertinent details of the ALP assay for non-cow milk products are summarized, and a comparison is performed regarding the evaluation of the adequacy of commercially available tests for the determination of ALP activity in non-cow milk. At the same time, raw and pasteurized non-cow milk was analyzed microbiologically using standard ISO methods and MALDI-TOF MS in order to confirm the thermal effect on common microorganisms. In these preliminary results, various ALP tests do not appear to be fully reliable as indicators for the pasteurization of some types of non-cow milk such as camel and donkey milk or even goat and sheep milk, using the EFSA proposed limits. ALP commercial kits may not be suitable as pasteurization indicators for various types on non-cow milk, and alternatives should be investigated.
Where Is My Mind…? The Link between Mind Wandering and Prospective Memory
Authors: Girardeau Jean-Charles , Sperduti Marco , Blondé Philippe , Piolino Pascale
Published: August 2022

Mind wandering (MW) is a common feature of the human experience occurring when our attention shifts from the task at hand to inner thoughts. MW seems to be often future-oriented and could be used to help people to carry out their planned actions (Prospective Memory PM). Here, we tested the link between MW and the ability to perform PM intentions. We assessed MW and PM over 15 days using experience-sampling probes via mobile phone (226 participants) associated with a naturalistic PM task. We confirmed that MW occupies a significant proportion of our mental activity (40%). This time seems to be mainly used to project ourselves into the future (64%), whether to anticipate and imagine the long term (20%) or to plan daily obligations (44%). Intriguingly, only past-oriented thoughts (9%) predict the PM performance. We discuss the possible functional role played by MW in maintaining intentions in mind.
Development of a Machine Learning Model to Discriminate Mild Cognitive Impairment Subjects from Normal Controls in Community Screening
Authors: Jiang Juanjuan , Zhang Jieming , Li Chenyang , Yu Zhihua , Yan Zhuangzhi , Jiang Jiehui
Published: August 2022

Background: Mild cognitive impairment (MCI) is a transitional stage between normal aging and probable Alzheimer’s disease. It is of great value to screen for MCI in the community. A novel machine learning (ML) model is composed of electroencephalography (EEG), eye tracking (ET), and neuropsychological assessments. This study has been proposed to identify MCI subjects from normal controls (NC). Methods: Two cohorts were used in this study. Cohort 1 as the training and validation group, includes184 MCI patients and 152 NC subjects. Cohort 2 as an independent test group, includes 44 MCI and 48 NC individuals. EEG, ET, Neuropsychological Tests Battery (NTB), and clinical variables with age, gender, educational level, MoCA-B, and ACE-R were selected for all subjects. Receiver operating characteristic (ROC) curves were adopted to evaluate the capabilities of this tool to classify MCI from NC. The clinical model, the EEG and ET model, and the neuropsychological model were compared. Results: We found that the classification accuracy of the proposed model achieved 84.5 ± 4.43% and 88.8 ± 3.59% in Cohort 1 and Cohort 2, respectively. The area under curve (AUC) of the proposed tool achieved 0.941 (0.893–0.982) in Cohort 1 and 0.966 (0.921–0.988) in Cohort 2, respectively. Conclusions: The proposed model incorporation of EEG, ET, and neuropsychological assessments yielded excellent classification performances, suggesting its potential for future application in cognitive decline prediction.
General Factor of Personality and Its Relationship with the Dark Triad and Social Intelligence in Slovenian Adolescents
Authors: Jug Vesna
Published: August 2022

The general factor of personality (GFP) represents the shared variance between personality traits that yield social adjustment and acts as a core personality disposition. In the present study, the existence of GFP in a sample of 249 Slovenian adolescents aged 15–19 years was investigated, and the relationship between GFP, the Dark Triad, and social intelligence was researched. The study used three self-report questionnaires to measure the Big Five, the Dark Triad, and three dimensions of social intelligence. It was found that, in adolescents, GFP exists (although in a somewhat different composition than in previous studies) and is negatively correlated with Machiavellianism and psychopathy and positively correlated with social skills and social awareness. GFP acts as a significant positive predictor of all social intelligence dimensions, and Machiavellianism acts as a significant positive predictor of social information processing and social skills. It can be concluded that GFP and, to a certain extent, perhaps some manipulative tendencies positively predict how an individual functions in society. With these findings, the study contributes to the understanding of the (hierarchical) structure of personality and its association with behavior in social interactions, which is one of the most important developmental tasks in adolescence.
Application of LightGBM Algorithm in the Initial Design of a Library in the Cold Area of China Based on Comprehensive Performance
Authors: Zhou Yihuan , Wang Wanjiang , Wang Ke , Song Junkang
Published: August 2022

The proper application of machine learning and genetic algorithms in the early stage of library design can obtain better all-around building performance. The all-around performance of the library, such as indoor temperature, solar radiation, indoor lighting, etc., must be fully considered in the initial design stage. Aiming at building performance optimization and based on the method of “generative design”, this paper constructs the library’s comprehensive performance evaluation workflow and rapid prediction combined with the LightGBM algorithm. A library in a cold region of China is taken as the research object to verify its application. In this study, 5000 scheme samples generated in the iterative genetic optimization process were taken as data sets. The LightGBM algorithm was used to classify and predict design schemes, with a precision of 0.78, recall rate of 0.93, and F1-Score of 0.851. This method can help architects to fully exploit the optimization potential of the building’s all-around performance in the initial stage of library design and ensure the timely interaction and feedback between design decisions and performance evaluation.
Online Sifting Technique for Structural Health Monitoring Data Based on Recursive EMD Processing Framework
Authors: Dan Danhui , Wang Chenqi , Pan Ruiyang , Cao Yangmei
Published: August 2022

Real-time and online screening techniques for single load effect signal monitoring are one of the key issues in smart structure monitoring. In this paper, an online signal sifting framework called online recursive empirical mode decomposition (EMD) is proposed. The framework is based on an improved EMD that optimizes the boundary effect by using extreme value recursion and eigensystem realization algorithm (ERA) extension, and combines the intrinsic mode functions (IMFs) correlation coefficient and adaptive filtering to select IMFs for signal reconstruction to achieve the sifting purpose. When applied to simulated signals, the method satisfies the requirements of signal sifting in an online environment with high adaptivity, low parameter sensitivity and good robustness. The method was applied to the dynamic strain data collected by the health monitoring system of Daishan Second Bridge to achieve real-time online sifting of strain signals caused by traffic loads, which provided the basis for subsequent data analysis applications and confirmed the value of the application in a real bridge health monitoring system.
P2Y2R-Mediated PAK1 Activation Is Involved in ESM-1 Overexpression in RT-R-MDA-MB-231 through FoxO1 Regulation
Authors: Jin Hana , Kim Hye Jung
Published: August 2022

ESM-1, overexpressed in several cancer types, is a potential cancer diagnostic and prognostic indicator. In our previous study, we determined that RT-R-TNBC cells were more aggressive than TNBC cells, and this difference was associated with ESM-1 overexpression. However, the mechanism explaining upregulated ESM-1 expression in RT-R-TNBC cells compared to TNBC cells was unclear. Therefore, we aimed to identify the mechanism by which ESM-1 is overexpressed in RT-R-MDA-MB-231 cells. RT-R-MDA-MB-231 cells were treated with various ESM-1 transcription factor inhibitors, and only the FoxO1 inhibitor downregulated ESM-1 expression. FoxO1 nuclear localization was modulated by JNK and p38 MAPKs, which were differentially regulated by PKC, PDK1 and PAK1. PAK1 profoundly modulated JNK and p38 MAPKs, whereas PKC and PDK1 affected only p38 MAPK. P2Y2R activated by ATP, which is highly released from RT-R-BC cells, was involved in PAK1 activation, subsequent JNK and p38 MAPK activation, FoxO1 induction, and ESM-1 expression in RT-R-MDA-MB-231 cells. These findings suggest for the first time that ESM-1 was overexpressed in RT-R-MDA-MB-231 cells and regulated through the P2Y2R-PAK1-FoxO1 signaling pathway.
Cancer Histology and Natural History of Patients with Lung Cancer and Venous Thromboembolism
Authors: Ruiz-Artacho Pedro , Lecumberri Ramón , Trujillo-Santos Javier , Font Carme , López-Núñez Juan J. , Peris María Luisa , Díaz Pedroche Carmen , Lobo José Luis , López Jiménez Luciano , López Reyes Raquel , Jara Palomares Luis , Pedrajas José María , Mahé Isabelle , Monreal Manuel ,   The RIETE Investigators
Published: August 2022

Background: In patients with lung cancer and venous thromboembolism (VTE), the influence of cancer histology on outcome has not been consistently evaluated. Methods: We used the RIETE registry (Registro Informatizado Enfermedad TromboEmbólica) to compare the clinical characteristics and outcomes during anticoagulation in patients with lung cancer and VTE, according to the histology of lung cancer. Results: As of April 2022, there were 482 patients with lung cancer and VTE: adenocarcinoma 293 (61%), squamous 98 (20%), small-cell 44 (9.1%), other 47 (9.8%). The index VTE was diagnosed later in patients with squamous cancer than in those with adenocarcinoma (median, 5 vs. 2 months). In 50% of patients with adenocarcinoma, the VTE appeared within the first 90 days since cancer diagnosis. During anticoagulation (median 106 days, IQR: 45–214), 14 patients developed VTE recurrences, 15 suffered major bleeding, and 218 died: fatal pulmonary embolism 10, fatal bleeding 2. The rate of VTE recurrences was higher than the rate of major bleeding in patients with adenocarcinoma (11 vs. 6 events), and lower in those with other cancer types (3 vs. 9 events). On multivariable analysis, patients with adenocarcinoma had a non-significantly higher risk for VTE recurrences (hazard ratio [HR]: 3.79; 95%CI: 0.76–18.8), a lower risk of major bleeding (HR: 0.29; 95%CI: 0.09–0.95), and a similar risk of mortality (HR: 1.02; 95%CI: 0.76–1.36) than patients with other types of lung cancer. Conclusions: In patients with lung adenocarcinoma, the rate of VTE recurrences outweighed the rate of major bleeding. In patients with other lung cancers, it was the opposite.
Overcoming the Impact of Hypoxia in Driving Radiotherapy Resistance in Head and Neck Squamous Cell Carcinoma
Authors: Hill Rhianna M. , Rocha Sonia , Parsons Jason L.
Published: August 2022

Hypoxia is very common in most solid tumours and is a driving force for malignant progression as well as radiotherapy and chemotherapy resistance. Incidences of head and neck squamous cell carcinoma (HNSCC) have increased in the last decade and radiotherapy is a major therapeutic technique utilised in the treatment of the tumours. However, effectiveness of radiotherapy is hindered by resistance mechanisms and most notably by hypoxia, leading to poor patient prognosis of HNSCC patients. The phenomenon of hypoxia-induced radioresistance was identified nearly half a century ago, yet despite this, little progress has been made in overcoming the physical lack of oxygen. Therefore, a more detailed understanding of the molecular mechanisms of hypoxia and the underpinning radiobiological response of tumours to this phenotype is much needed. In this review, we will provide an up-to-date overview of how hypoxia alters molecular and cellular processes contributing to radioresistance, particularly in the context of HNSCC, and what strategies have and could be explored to overcome hypoxia-induced radioresistance.
Leveraging Comprehensive Cancer Registry Data to Enable a Broad Range of Research, Audit and Patient Support Activities
Authors: Lee Belinda , Gately Lucy , Lok Sheau Wen , Tran Ben , Lee Margaret , Wong Rachel , Markman Ben , Dunn Kate , Wong Vanessa , Loft Matthew , Jalili Azim , Anton Angelyn , To Richard , Andrews Miles , Gibbs Peter
Published: August 2022

Traditional cancer registries have often been siloed efforts, established by single groups with limited objectives. There is the potential for registry data to support a broad range of research, audit and education initiatives. Here, we describe the establishment of a series of comprehensive cancer registries across the spectrum of common solid cancers. The experience and learnings of each registry team as they develop, implement and then use collected data for a range of purposes, that informs the conduct and output of other registries in a virtuous cycle. Each registry is multi-site, multi-disciplinary and aims to collect data of maximal interest and value to a broad range of enquiry, which would be accessible to any researcher with a high-quality proposal. Lessons learnt include the need for careful and continuous curation of data fields, with regular database updates, and the need for a continued focus on data quality. The registry data as a standalone resource has supported numerous projects, but linkage with external datasets with patients in common has enhanced the audit and research potential. Multiple projects have linked registry data with matched tissue specimens to support prognostic and predictive biomarker studies, both validation and discovery. Registry-based biomarker trials have been successfully supported, generating novel and practice-changing data. Registry-based clinical trials, particularly randomised studies exploring the optimal use of available therapy options are now complementing the research conducted in traditional clinical trials. More recent projects supported by the registries include health economic studies, personalised patient education material, and increased consumer engagement, including consumer entered data.
The Clinical Utility of Systemic Immune-Inflammation Index Supporting Charlson Comorbidity Index and CAPRA-S Score in Determining Survival after Radical Prostatectomy—A Single Centre Study
Authors: Zapała Piotr , Garbas Karolina , Lewandowski Zbigniew , Zapała Łukasz , Ślusarczyk Aleksander , Ślusarczyk Cezary , Mielczarek Łukasz , Radziszewski Piotr
Published: August 2022

The selection of candidates for the curative treatment of PCa requires a careful assessment of life expectancy. Recently, blood-count inflammatory markers have been introduced as prognosticators of oncological and non-oncological outcomes in different settings. This retrospective, monocentric study included 421 patients treated with radical prostatectomy (RP) for nonmetastatic PCa and aimed at determining the utility of a preoperative SII (neutrophil count × platelet count/lymphocyte count) in predicting survival after RP. Patients with high SIIs (≥900) presented significantly shorter survival (p = 0.02) and high SIIs constituted an independent predictor of overall survival [HR 2.54 (95%CI 1.24–5.21); p = 0.01] when adjusted for high (≥6) age-adjusted CCI (ACCI) [HR 2.75 (95%CI 1.27–5.95); p = 0.01] and high (≥6) CAPRA-S [HR 2.65 (95%CI 1.32–5.31); p = 0.006]. Patients with high scores (ACCI and/or CAPRA-S) and high SIIs were at the highest risk of death (p < 0.0001) with approximately a one-year survival loss during the first seven years after surgery. In subgroup of high CAPRA-S (≥6), patients with high ACCIs and high SIIs were at the highest risk of death (p <0.0001). Our study introduces the SII as a straightforward marker of mortality after RP that can be helpful in pre- and postoperative decision-making.
Altered Adipokine Expression in Tumor Microenvironment Promotes Development of Triple Negative Breast Cancer
Authors: Papakonstantinou Efthymia , Piperigkou Zoi , Karamanos Nikos K. , Zolota Vasiliki
Published: August 2022

Obesity is a remarkably important factor for breast carcinogenesis and aggressiveness. The implication of increased BMI in triple negative breast cancer (TNBC) development is also well established. A malignancy-promoting role of the adipose tissue has been supposed, where the adipocytes that constitute the majority of stromal cells release pro-inflammatory cytokines and growth factors. Alterations in adipokines and their receptors play significant roles in breast cancer initiation, progression, metastasis, and drug response. Classic adipokines, such as leptin, adiponectin, and resistin, have been extensively studied in breast cancer and connected with breast cancer risk and progression. Notably, new molecules are constantly being discovered and the list is continuously growing. Additionally, substantial progress has been made concerning their differential expression in association with clinical and pathological parameters of tumors and the prognostic and predictive value of their dysregulation in breast cancer carcinogenesis. However, evidence regarding the mechanisms by which adipose tissue is involved in the development of TNBC is lacking. In the present article we comment on current data on the suggested involvement of these mediators in breast cancer development and progression, with particular emphasis on TNBC, to draw attention to the design of novel targeted therapies and biomarkers.