bluuebunny/crossref_metadata_2025 huggingface dataset:
A Variable Ranking Method for Machine Learning Models with Correlated Features: In-Silico Validation and Application for Diabetes Prediction
Authors: Vettoretti Martina , Di Camillo Barbara
Published: August 2021

When building a predictive model for predicting a clinical outcome using machine learning techniques, the model developers are often interested in ranking the features according to their predictive ability. A commonly used approach to obtain a robust variable ranking is to apply recursive feature elimination (RFE) on multiple resamplings of the training set and then to aggregate the ranking results using the Borda count method. However, the presence of highly correlated features in the training set can deteriorate the ranking performance. In this work, we propose a variant of the method based on RFE and Borda count that takes into account the correlation between variables during the ranking procedure in order to improve the ranking performance in the presence of highly correlated features. The proposed algorithm is tested on simulated datasets in which the true variable importance is known and compared to the standard RFE-Borda count method. According to the root mean square error between the estimated rank and the true (i.e., simulated) feature importance, the proposed algorithm overcomes the standard RFE-Borda count method. Finally, the proposed algorithm is applied to a case study related to the development of a predictive model of type 2 diabetes onset.
A Review of CO2 Laser-Mediated Therapy for Oral Mucosal Lesions
Authors: Condor Daniela , Culcițchi Cristian , Blum Rebecca , Baru Oana , Buduru Smaranda , Kui Andreea , Țig Ioan
Published: August 2021

(1) Background: Several studies investigating the clinical outcomes of potentially premalignant oral epithelial lesions treated with CO2 lasers have been published over the last decades. (2) Methods: A systematic research review was performed for studies published between 2011 and 2021 in the PubMed, Science Direct, and Google Scholar databases. (3) Results: Initially, the search identified 52 relevant articles. The primary analysis of the titles and abstracts eliminated 22 articles, leaving 30 articles whose full texts were examined. A total of 22 articles met the inclusion criteria. The studies were classified into 3 categories. (4) Conclusions: After evaluating the results of all the studies included in this review, an initial general statement can be made, namely that CO2 lasers are a treatment option worth taking into consideration when approaching oral mucosal lesions. When compared to other types of lasers used in dental practice, the CO2 laser stands out due to its many advantages.
Pilot Studies of Vibrations Induced in Perambulators When Moving on Different Surfaces
Authors: Sierzputowski Gustaw , Wróbel Radosław , Mihaylov Veselin , Janeczek Maciej , Majewska-Pulsakowska Marta , Jarząb Sławomir
Published: August 2021

The ergonomics of transport is a topic widely described in the literature. One of the fields of ergonomics that researchers are engaged in is vibrometry (both laser and accelerometry) of travel and its translation into NVH (Noise, Vibration and Harshness). However, so far, the influence of baby carriage movement on the generated vibrations has not been described in more detail. The topic seems to be particularly important considering occurrence of vibrations with significant amplitudes, whose frequency range can have a direct bearing on the resonance frequencies of the child’s internal organs. The article presents the results of research consisting in the measurement of vibrations to which an infant, lying in two different types of prams, may be exposed when being transported on different surfaces. The author’s measurement system, based on accelerometry, was used for the research. The obtained weighted RMS acceleration values not only exceeded human comfort level in all cases (according to ISO standard) but several times were in the range of the highest discomfort (>2 m/s2). Furthermore, the observed vibration frequency range (≈0 ÷ 32 Hz) coincided with the frequencies of free vibration of organs and parts of the child’s body.
Microstructural Characterization of a Single Crystal Copper Rod Using Monochromatic Neutron Radiography Scan and Tomography: A Test Experiment
Authors: Grazzi Francesco , Cantini Francesco , Morgano Manuel , Busi Matteo , Park Jang-Sik
Published: August 2021

This paper reports the analysis of a single crystal copper rod aiming to characterize the microstructural features related to the homogeneity of the single crystal growth and the presence, shape and extension of spatially distributed misaligned grains or areas. The analytical method used for such analysis is wavelength scan neutron radiography and monochromatic neutron tomography. Such methods allow determination of the extent of differently oriented single crystal areas, identifying the most part of the rod volume as a single domain. It was also possible to characterize the spatial distribution and the degree of alignment of local point-like or extended defects.
Enhanced Tone Mapping Using Regional Fused GAN Training with a Gamma-Shift Dataset
Authors: Jung Sung-Woon , Kwon Hyuk-Ju , Lee Sung-Hak
Published: August 2021

High-dynamic-range (HDR) imaging is a digital image processing technique that enhances an image’s visibility by modifying its color and contrast ranges. Generative adversarial networks (GANs) have proven to be potent deep learning models for HDR imaging. However, obtaining a sufficient volume of training image pairs is difficult. This problem has been solved using CycleGAN, but the result of the use of CycleGAN for converting a low-dynamic-range (LDR) image to an HDR image exhibits problematic color distortion, and the intensity of the output image only slightly changes. Therefore, we propose a GAN training optimization model for converting LDR images into HDR images. First, a gamma shift method is proposed for training the GAN model with an extended luminance range. Next, a weighted loss map trains the GAN model for tone compression in the local area of images. Then, a regional fusion training model is used to balance the training method with the regional weight map and the restoring speed of local tone training. Finally, because the generated module tends to show a good performance in bright images, mean gamma tuning is used to evaluate image luminance channels, which are then fed into modules. Tests are conducted on foggy, dark surrounding, bright surrounding, and high-contrast images. The proposed model outperforms conventional models in a comparison test. The proposed model complements the performance of an object detection model even in a real night environment. The model can be used in commercial closed-circuit television surveillance systems and the security industry.
Usefulness of Scissors with a Power-Support Mechanism to Assist Thumb Movement: An Observational Study
Authors: Koizumi Kohei , Sasao Kumiko , Koike Yuji , Okino Akihisa , Takeda Kazuhisa , Hamaguchi Toyohiro
Published: August 2021

Long-term repetitive movements, such as opening and closing scissors, increase strain on muscles and joints. Amplitude probability distribution function (APDF) analysis of surface electromyogram (sEMG) data was used to quantify the burden of muscle activity. We aimed to test the hypothesis that scissors with a power-support device assist repetitive thumb movements to reduce potential myoelectric activity. Twenty female university students who met the eligibility criteria performed a cutting experiment, with and without power-support device scissors. The primary outcome was a change in muscle load due to sEMG data that were analyzed using APDF, and the secondary outcomes investigated the occurrence of muscle fatigue and pain. The adductor pollicis muscle showed a significant decrease in muscle activity with power assistance. In addition, it was also found that fatigue and pain of the thumb and on the radial side of the forearm were significantly lower under the power-assisted conditions. The results of this study suggest that the assistive action of scissors with a power-support device compensate for muscle load on the thenar eminence. This may be used as a reference value to prevent the occurrence of hand disorders for hairdressers.
k-Labelsets Method for Multi-Label ECG Signal Classification Based on SE-ResNet
Authors: Yoo Jihye , Jin Yeongbong , Ko Bonggyun , Kim Min-Soo
Published: August 2021

Cardiovascular diseases are the leading cause of death globally. The ECG is the most commonly used tool for diagnosing cardiovascular diseases, and, recently, there are a number of attempts to use deep learning to analyze ECG. In this study, we propose a method for performing multi-label classification on standard ECG (12-lead with duration of 10 s) data. We used the ResNet model that can perform residual learning as a base model for classification in this work, and we tried to improve performance through SE-ResNet, which added squeeze and excitation blocks on the plain ResNet. As a result of the experiment, it was possible to induce overall performance improvement through squeeze and excitation blocks. In addition, the random k-labelsets (RAKEL) algorithm was applied to improve the performance in multi-label classification problems. As a result, the model that applied soft voting through the RAKEL algorithm to SE-ResNet-34 represented the best performance, and the average performances according to the number of label divisions k were achieved 0.99%, 88.49%, 92.43%, 90.54%, and 93.40% in exact match, accuracy, F1-score, precision, and recall, respectively.
Robust Flow Field Signal Estimation Method for Flow Sensing by Underwater Robotics
Authors: Lin Xinghua , Qin Qing , Wang Xiaoming , Zhang Junxia
Published: August 2021

The flow field is difficult to evaluate, and underwater robotics can only partly adapt to the submarine environment. However, fish can sense the complex underwater environment by their lateral line system. In order to reveal the fish flow sensing mechanism, a robust nonlinear signal estimation method based on the Volterra series model with the Kautz kernel function is provided, which is named KKF-VSM. The flow field signal around a square target is used as the original signal. The sinusoidal noise and the signal around a triangular obstacle are considered undesired signals, and the predicting performance of KKF-VSM is analyzed after introducing them locally in the original signals. Compared to the radial basis function neural network model (RBF-NNM), the advantages of KKF-VSM are not only its robustness but also its higher sensitivity to weak signals and its predicting accuracy. It is confirmed that even for strong nonlinear signals, such as pressure responses in the flow field, KKF-VSM is more efficient than the commonly used RBF-NNM. It can provide a reference for the application of the artificial lateral line system on underwater robotics, improving its adaptability in complex environments based on flow field information.
Three-Year Variations in Criteria Atmospheric Pollutants and Their Relationship with Rainwater Chemistry in Karst Urban Region, Southwest China
Authors: Zeng Jie , Ge Xin , Wu Qixin , Zhang Shitong
Published: August 2021

Air pollutants have been investigated in many studies, but the variations of atmospheric pollutants and their relationship with rainwater chemistry are not well studied. In the present study, the criteria atmospheric pollutants in nine monitoring stations and rainwater chemistry were analyzed in karst Guiyang city, since the time when the Chinese Ambient Air Quality Standards (CAAQS, third revision) were published. Based on the three-year daily concentration dataset of SO2, NO2, CO, PM10 and PM2.5, although most of air pollutant concentrations were within the limit of CAAQS III-Grade II standard, the significant spatial variations and relatively heavy pollution were found in downtown Guiyang. Temporally, the average concentrations of almost all air pollutants (except for CO) decreased during three years at all stations. Ratios of PM2.5/PM10 in non- and episode days reflected the different contributions of fine and coarse particles on particulate matter in Guiyang, which was influenced by the potential meteorological factors and source variations. According to the individual air quality index (IAQI), the seasonal variations of air quality level were observed, that is, IAQI values of air pollutants were higher in winter (worst air quality) and lower in summer (best air quality) due to seasonal variations in emission sources. The unique IAQI variations were found during the Chinese Spring Festival. Air pollutant concentrations are also influenced by meteorological parameters, in particular, the rainfall amount. The air pollutants are well scoured by the rainfall process and can significantly affect rainwater chemistry, such as SO42−, NO3−, Mg2+, and Ca2+, which further alters the acidification/alkalization trend of rainwater. The equivalent ratios of rainwater SO42−/NO3− and Mg2+/Ca2+ indicated the significant contribution of fixed emission sources (e.g., coal combustion) and carbonate weathering-influenced particulate matter on rainwater chemistry. These findings provide scientific support for air pollution management and rainwater chemistry-related environmental issues.
Research on Monthly Precipitation Prediction Based on the Least Square Support Vector Machine with Multi-Factor Integration
Authors: Lei Jingchun , Quan Quan , Li Pingzhi , Yan Denghua
Published: August 2021

Accurate precipitation prediction is of great significance for regional flood control and disaster mitigation. This study introduced a prediction model based on the least square support vector machine (LSSVM) optimized by the genetic algorithm (GA). The model was used to estimate the precipitation of each meteorological station over the source region of the Yellow River (SRYE) in China for 12 months. The Ensemble empirical mode decomposition (EEMD) method was used to select meteorological factors and realize precipitation prediction, without dependence on historical data as a training set. The prediction results were compared with each other, according to the determination coefficient (R2), mean absolute errors (MAE), and root mean square error (RMSE). The results show that sea surface temperature (SST) in the Niño 1 + 2 region exerts the largest influence on accuracy of the prediction model for precipitation in the SRYE (RSST2= 0.856, RMSESST= 19.648, MAESST= 14.363). It is followed by the potential energy of gravity waves (Ep) and temperature (T) that have similar effects on precipitation prediction. The prediction accuracy is sensitive to altitude influences and accurate prediction results are easily obtained at high altitudes. This model provides a new and reliable research method for precipitation prediction in regions without historical data.
Assessment of Outdoor Thermal Comfort in Serbia’s Urban Environments during Different Seasons
Authors: Lukić Milica , Filipović Dejan , Pecelj Milica , Crnogorac Ljiljana , Lukić Bogdan , Divjak Lazar , Lukić Ana , Vučićević Ana
Published: August 2021

The urban microclimate is gradually changing due to climate change, extreme weather conditions, urbanization, and the heat island effect. In such an altered environment, outdoor thermal comfort can have a strong impact on public health and quality of life in urban areas. In this study, three main urban areas in Serbia were selected: Belgrade (Central Serbia), Novi Sad (Northern Serbia), and Niš (Southern Serbia). The focus was on the temporal assessment of OTC, using the UTCI over a period of 20 years (1999–2018) during different seasons. The main aim is the general estimation of the OTC of Belgrade, Novi Sad, and Niš, in order to gain better insight into the bioclimatic condition, current trends and anomalies that have occurred. The analysis was conducted based on an hourly (7 h, 14 h, and 21 h CET) and “day by day” meteorological data set. Findings show the presence of a growing trend in seasonal UTCI anomalies, especially during summer and spring. In addition, there is a notable increase in the number of days above the defined UTCI thresholds for each season. Average annual UTCIs values also show a positive, rising trend, ranging from 0.50 °C to 1.33 °C. The most significant deviations from the average UTCI values, both seasonal and annual, were recorded in 2000, 2007, 2012, 2015, 2017, and 2018.
Free Amino Acids Profile and Expression Analysis of Core Genes Involved in Branched-Chain Amino Acids Metabolism during Fruit Development of Longan (Dimocarpus longan Lour.) Cultivars with Different Aroma Types
Authors: Hu Wenshun , Wang Baiyu , Ali Muhammad Moaaz , Chen Xiuping , Zhang Jisen , Zheng Shaoquan , Chen Faxing
Published: August 2021

Amino acids are important component of fruit nutrition and quality. In this study, three longan cultivars, including non-aroma types ‘Shixia’ (SX), ‘Lidongben’ (LDB), and strong aroma type ‘Xiangcui’ (XC), were selected to analyze free amino acids (FAAs) variations at six distinct growth stages (S1–S6). The genome-wide identification and expression analysis of genes related to the branched-chain amino acids (BCAA) synthesis pathway were carried out. Results showed that 36 FAAs were identified, and the total FAAs content ranged from 2601.0 to 9073.5 mg/kg, which increased drastically with fruit development until ripening. L-glutamic acid (Glu), L-alanine (Ala), L-arginine (Arg), γ-Aminobutyric acid (GABA), L-aspartic acid (Asp), L-leucine (Leu), hydroxyl-proline (Hypro), and L-serine (Ser) were the predominant FAAs (1619.9–7213.9 mg/kg) in pulp, accounting for 62.28–92.05% of the total amino acids. During the period of rapid fruit expansion (S2–S4), the aroma of XC changed from light to strong, and the contents of L-alanine (Ala) and L-leucine (Leu) were significantly higher than those of SX and LDB. Furthermore, a total of two 2-isopropyl malate synthase (IPMS), two 3-isopropyl malate dehydrogenase (IPMD), and 16 BCAA transferase (BCAT) genes were identified. The expression levels of DilBCAT1, -6, and -9 genes in XC were significantly higher than those in SX and LDB, while DilBCAT16 in XC was lower. The content of Leu was negatively correlated with the expression of DilBCAT1, -6, and -9 in three varieties, but positively correlated with DilBCAT16, indicating that these four genes may be responsible for the different synthesis and degradation of Leu among cultivars.
Polyculture of Juvenile Dog Conch Laevistrombus canarium Reveals High Potentiality in Integrated Multitrophic Aquaculture (IMTA)
Authors: Chang Yung-Cheng , Ma Chia-Huan , Lee Hung-Tai , Hsu Te-Hua
Published: August 2021

Laevistrombus canarium, also known as dog conch, is a marine gastropod mollusk widely distributed in the Indo-Pacific region. It is an economically crucial species; however, its population has been declining due to overfishing and overexploitation. In this study, the suitable salinity for juvenile L. canarium was between 20 and 35‰. Diatoms and biological detritus by using flow-water from the fish pool were the most favorable diets for newly metamorphosed and 10 mm juveniles. In the polyculture experiment, L. canarium was cultured with whiteleg shrimp, tilapia, small abalone, purple sea urchin, and collector urchin. Better growth was found in all co-culture groups except with whiteleg shrimp. We also found that the polyculture system with or without substrates significantly affected the growth of juveniles. Additionally, we observed that water temperature was the most crucial factor for growth and survival; a water temperature of less than 10 °C might cause the death of L. canarium. We have proposed a novel polyculture and water-flow method for mass production of L. canarium and evaluated the feasibility and benefits of polyculture with other species. The findings from this work reveal the potentiality of L. canarium in integrated multitrophic aquaculture (IMTA) and its implication for aquaculture and resource restoration.
Volumetric Properties of Four-Stranded DNA Structures
Authors: Chalikian Tigran V. , Macgregor Robert B.
Published: August 2021

Four-stranded non-canonical DNA structures including G-quadruplexes and i-motifs have been found in the genome and are thought to be involved in regulation of biological function. These structures have been implicated in telomere biology, genomic instability, and regulation of transcription and translation events. To gain an understanding of the molecular determinants underlying the biological role of four-stranded DNA structures, their biophysical properties have been extensively studied. The limited libraries on volume, expansibility, and compressibility accumulated to date have begun to provide insights into the molecular origins of helix-to-coil and helix-to-helix conformational transitions involving four-stranded DNA structures. In this article, we review the recent progress in volumetric investigations of G-quadruplexes and i-motifs, emphasizing how such data can be used to characterize intra-and intermolecular interactions, including solvation. We describe how volumetric data can be interpreted at the molecular level to yield a better understanding of the role that solute–solvent interactions play in modulating the stability and recognition events of nucleic acids. Taken together, volumetric studies facilitate unveiling the molecular determinants of biological events involving biopolymers, including G-quadruplexes and i-motifs, by providing one more piece to the thermodynamic puzzle describing the energetics of cellular processes in vitro and, by extension, in vivo.
Breast Cancer Mortality in the Americas and Australasia over the Period 1980–2017 with Predictions for 2025
Authors: Wojtyla Cezary , Bertuccio Paola , Ciebiera Michal , La Vecchia Carlo
Published: August 2021

Substantial progress has been made in the diagnosis, management, and treatment of breast cancer over the last decades. This has affected mortality rates but has also led to inequality in epidemiological trends between different regions of the world. We extracted death certification data for breast cancer from the World Health Organization database. We analyzed trends in breast cancer mortality in selected countries from America, Asia, and Oceania over the 1980–2017 period and predicted numbers of deaths and rates for 2025. In North America, we observed decreased breast cancer mortality, reaching a rate of about 13/100,000 women in 2017. In Latin American countries, breast cancer mortality rates did not consistently decrease. The highest decreases in mortality were observed in Australia. Mortality trends in Asian countries remained among the lowest globally. We have predicted decreased mortality from breast cancer in 2025 for most of the analyzed countries. The epidemiological situation regarding breast cancer mortality is expected to change in the coming years. Advancements in diagnosis and treatment of breast cancer must be extended in various areas of the world to obtain global control of breast cancer mortality.
Circulating Biomarkers in Neuromuscular Disorders: What Is Known, What Is New
Authors: Barp Andrea , Ferrero Amanda , Casagrande Silvia , Morini Roberta , Zuccarino Riccardo
Published: August 2021

The urgent need for new therapies for some devastating neuromuscular diseases (NMDs), such as Duchenne muscular dystrophy or amyotrophic lateral sclerosis, has led to an intense search for new potential biomarkers. Biomarkers can be classified based on their clinical value into different categories: diagnostic biomarkers confirm the presence of a specific disease, prognostic biomarkers provide information about disease course, and therapeutic biomarkers are designed to predict or measure treatment response. Circulating biomarkers, as opposed to instrumental/invasive ones (e.g., muscle MRI or nerve ultrasound, muscle or nerve biopsy), are generally easier to access and less “time-consuming”. In addition to well-known creatine kinase, other promising molecules seem to be candidate biomarkers to improve the diagnosis, prognosis and prediction of therapeutic response, such as antibodies, neurofilaments, and microRNAs. However, there are some criticalities that can complicate their application: variability during the day, stability, and reliable performance metrics (e.g., accuracy, precision and reproducibility) across laboratories. In the present review, we discuss the application of biochemical biomarkers (both validated and emerging) in the most common NMDs with a focus on their diagnostic, prognostic/predictive and therapeutic application, and finally, we address the critical issues in the introduction of new biomarkers.
Transcription-Replication Collisions—A Series of Unfortunate Events
Authors: St Germain Commodore , Zhao Hongchang , Barlow Jacqueline H.
Published: August 2021

Transcription-replication interactions occur when DNA replication encounters genomic regions undergoing transcription. Both replication and transcription are essential for life and use the same DNA template making conflicts unavoidable. R-loops, DNA supercoiling, DNA secondary structure, and chromatin-binding proteins are all potential obstacles for processive replication or transcription and pose an even more potent threat to genome integrity when these processes co-occur. It is critical to maintaining high fidelity and processivity of transcription and replication while navigating through a complex chromatin environment, highlighting the importance of defining cellular pathways regulating transcription-replication interaction formation, evasion, and resolution. Here we discuss how transcription influences replication fork stability, and the safeguards that have evolved to navigate transcription-replication interactions and maintain genome integrity in mammalian cells.
Benefits of Metformin Combined with Pemetrexed-Based Platinum Doublets as a First-Line Therapy for Advanced Lung Adenocarcinoma Patients with Diabetes
Authors: Wang Jiun-Long , Tsai Yi-Ting , Lin Ching-Heng , Cidem Abdulkadir , Staniczek Theresa , Chang Gary Ro-Lin , Yen Chih-Ching , Chen Wei , Chong Kowit-Yu , Chen Chuan-Mu
Published: August 2021

Lung cancer remains a challenge in daily practice. Chemotherapy is first considered for advanced lung adenocarcinoma bearing no active driver mutations. Maintaining drug efficacy and overcoming drug resistance are essential. This study aimed to explore the real-world use of anti-diabetic agent metformin in combination with pemetrexed-based platinum doublets in a first-line setting. We retrospectively collected data during 2004~2013 from TaiwaN′s National Health Insurance Research Database to access the survival benefit of metformin combined with pemetrexed-based platinum doublets as a first-line therapy for diabetic patients with advanced lung adenocarcinoma. Demographic data and information regarding platinum reagents, diabetes medications, and metformin doses were gathered, and overall survival status regarding metformin use was analyzed. Overall survival status based on the daily dose and the calculated cumulative defined daily dose (DDD) of metformin prescribed during the first 3 months after lung cancer was diagnosed was also assessed. A total of 495 patients were enrolled with a mean age of 67 years old, and the majority of the patients were male. After adjusting for age, sex, diabetes medication, and platinum reagents used, the adjusted hazard ratio (HR) for the metformin-user group was 0.61 (95% confidence interval (CI); 0.46~0.79; p < 0.001). The metformin-user group had a survival benefit (log-rank p < 0.001). We analyzed metformin dosing during the first 3 months after lung cancer diagnosis, and for a daily dose ≥ 1500 mg, the adjusted hazard ratio (aHR) was 0.42 (95% CI; 0.27~0.65; p < 0.001). Regarding the cumulative DDD of metformin, a DDD equal to or exceeding 21 resulted in aHR of 0.48 (95% CI; 0.34~0.69; p < 0.001). In this study, we found that the combination of metformin and pemetrexed-based platinum doublets provides a robust survival benefit as a first-line therapy for diabetic patients with advanced lung adenocarcinoma. It is worth conducting a large and randomized clinical trial to further investigate the antitumor effects of metformin on advanced lung adenocarcinoma when used as a first-ling therapy, including in non-diabetic patients.
Transcriptional Regulation of MECP2E1-E2 Isoforms and BDNF by Metformin and Simvastatin through Analyzing Nascent RNA Synthesis in a Human Brain Cell Line
Authors: Buist Marjorie , Fuss David , Rastegar Mojgan
Published: August 2021

Methyl CpG binding protein 2 (MeCP2) is the main DNA methyl-binding protein in the brain that binds to 5-methylcytosine and 5-hydroxymethyl cytosine. MECP2 gene mutations are the main origin of Rett Syndrome (RTT), a neurodevelopmental disorder in young females. The disease has no existing cure, however, metabolic drugs such as metformin and statins have recently emerged as potential therapeutic candidates. In addition, induced MECP2-BDNF homeostasis regulation has been suggested as a therapy avenue. Here, we analyzed nascent RNA synthesis versus steady state total cellular RNA to study the transcriptional effects of metformin (an anti-diabetic drug) on MECP2 isoforms (E1 and E2) and BNDF in a human brain cell line. Additionally, we investigated the impact of simvastatin (a cholesterol lowering drug) on transcriptional regulation of MECP2E1/E2-BDNF. Metformin was capable of post-transcriptionally inducing BDNF and/or MECP2E1, while transcriptionally inhibiting MECP2E2. In contrast simvastatin significantly inhibited BDNF transcription without significantly impacting MECP2E2 transcripts. Further analysis of ribosomal RNA transcripts confirmed that the drug neither individually nor in combination affected these fundamentally important transcripts. Experimental analysis was completed in conditions of the presence or absence of serum starvation that showed minimal impact for serum deprival, although significant inhibition of steady state MECP2E1 by simvastatin was only detected in non-serum starved cells. Taken together, our results suggest that metformin controls MECP2E1/E2-BDNF transcriptionally and/or post-transcriptionally, and that simvastatin is a potent transcriptional inhibitor of BDNF. The transcriptional effect of these drugs on MECP2E1/E2-BDNF were not additive under these tested conditions, however, either drug may have potential application for related disorders.
Covid19Risk.ai: An Open Source Repository and Online Calculator of Prediction Models for Early Diagnosis and Prognosis of Covid-19
Authors: Halilaj Iva , Chatterjee Avishek , van Wijk Yvonka , Wu Guangyao , van Eeckhout Brice , Oberije Cary , Lambin Philippe
Published: August 2021

Background: The current pandemic has led to a proliferation of predictive models being developed to address various aspects of COVID-19 patient care. We aimed to develop an online platform that would serve as an open source repository for a curated subset of such models, and provide a simple interface for included models to allow for online calculation. This platform would support doctors during decision-making regarding diagnoses, prognoses, and follow-up of COVID-19 patients, expediting the models’ transition from research to clinical practice. Methods: In this pilot study, we performed a literature search in the PubMed and WHO databases to find suitable models for implementation on our platform. All selected models were publicly available (peer reviewed publications or open source repository) and had been validated (TRIPOD type 3 or 2b). We created a method for obtaining the regression coefficients if only the nomogram was available in the original publication. All predictive models were transcribed on a practical graphical user interface using PHP 8.0.0, and were published online together with supporting documentation and links to the associated articles. Results: The open source website currently incorporates nine models from six different research groups, evaluated on datasets from different countries. The website will continue to be populated with other models related to COVID-19 prediction as these become available. This dynamic platform allows COVID-19 researchers to contact us to have their model curated and included on our website, thereby increasing the reach and real-world impact of their work. Conclusion: We have successfully demonstrated in this pilot study that our website provides an inclusive platform for predictive models related to COVID-19. It enables doctors to supplement their judgment with patient-specific predictions from externally validated models in a user-friendly format. Additionally, this platform supports researchers in showcasing their work, which will increase the visibility and use of their models.
Sharing the Same Perspective. Mental Disorders and Central Serous Chorioretinopathy: A Systematic Review of Evidence from 2010 to 2020
Authors: Pandolfo Gianluca , Genovese Giovanni , Bruno Antonio , Palumbo Diletta , Poli Umberto , Gangemi Sebastiano , Aragona Pasquale , Meduri Alessandro
Published: August 2021

Background: The relevance of the association between mental disorders and other conditions might have been underestimated due to its complexity. Central Serous Chorioretinopathy (CSC) is an ophthalmological disorder associated with many psychiatric factors. The aim of this systematic review is to evaluate the association between mental disorders and CSC. Methods: Articles about studies performed on humans on CSC published in peer-reviewed journals from 1 January 2010 to 31 December 2020 were included in the review. Results: We selected 21 research papers. Nine studies measured stress and anxious depressive symptoms, which are associated with CSC onset and recurrences, emerging as a state marker of the disease. Four out of the five studies focused on sleep disorders suggested a reliable association with CSC. Four studies evaluated other various psychiatric factors. The role of psychopharmacological medication has still not been elucidated (three studies). Conclusion: Multiple pieces of evidence highlights that CSC might arise in the context of systemic disease. This notion, together with the increasing evidence supporting a link between psychiatric disorders and choroidal thickness, suggests that CSC and mental disorders may share some etiopathogenetic pathways. Further research is needed to better investigate possible common etiopathogenetic pathways, especially vascular, immunological and endocrinological systems.
Adrenomedullin: A Novel Therapeutic for the Treatment of Inflammatory Bowel Disease
Authors: Ashizuka Shinya , Kita Toshihiro , Inatsu Haruhiko , Kitamura Kazuo
Published: August 2021

Adrenomedullin (AM) is a bioactive peptide with various physiological functions, including vasodilation, angiogenesis, anti-inflammation, organ protection, and tissue repair. AM suppresses inflammatory cytokine production in the intestinal mucosa, improves vascular and lymphatic regeneration and function, mucosal epithelial repair, and immune function in the intestinal bacteria of animal models with intestinal inflammation. We have been promoting translational research to develop novel therapeutic agents for inflammatory bowel disease (IBD) using AM and have started clinical research for IBD patients since 2010. A multicenter clinical trial is currently underway in Japan for patients with refractory ulcerative colitis and Crohn’s disease. Moreover, since current AM administration is limited to continuous intravenous infusion, the development of a subcutaneous formulation using long-acting AM is underway for outpatient treatment.
The Combined Effect of Branching and Elongation on the Bioactivity Profile of Phytocannabinoids. Part I: Thermo-TRPs
Authors: Mattoteia Daiana , Schiano Moriello Aniello , Taglialatela-Scafati Orazio , Amodeo Pietro , De Petrocellis Luciano , Appendino Giovanni , Vitale Rosa Maria , Caprioglio Diego
Published: August 2021

The affinity of cannabinoids for their CB1 and CB2 metabotropic receptors is dramatically affected by a combination of α-branching and elongation of their alkyl substituent, a maneuver exemplified by the n-pentyl -> α,α-dimethylheptyl (DMH) swap. The effect of this change on other cannabinoid end-points is still unknown, an observation surprising since thermo-TRPs are targeted by phytocannabinoids with often sub-micromolar affinity. To fill this gap, the α,α-dimethylheptyl analogues of the five major phytocannabinoids [CBD (1a), Δ8-THC (6a), CBG (7a), CBC (8a) and CBN (9a)] were prepared by total synthesis, and their activity on thermo-TRPs (TRPV1-4, TRPM8, and TRPA1) was compared with that of one of their natural analogues. Surprisingly, the DMH chain promoted a shift in the selectivity toward TRPA1, a target involved in pain and inflammatory diseases, in all investigated compounds. A comparative study of the putative binding modes at TRPA1 between DMH-CBC (8b), the most active compound within the series, and CBC (8a) was carried out by molecular docking, allowing the rationalization of their activity in terms of structure–activity relationships. Taken together, these observations qualify DMH-CBC (8b) as a non-covalent TRPA1-selective cannabinoid lead that is worthy of additional investigation as an analgesic and anti-inflammatory agent.
A Rapid Single-Cell Antimicrobial Susceptibility Testing Workflow for Bloodstream Infections
Authors: Forsyth Britney , Torab Peter , Lee Jyong-Huei , Malcom Tyler , Wang Tza-Huei , Liao Joseph C. , Yang Samuel , Kvam Erik , Puleo Chris , Wong Pak Kin
Published: August 2021

Bloodstream infections are a significant cause of morbidity and mortality worldwide. The rapid initiation of effective antibiotic treatment is critical for patients with bloodstream infections. However, the diagnosis of bloodborne pathogens is largely complicated by the matrix effect of blood and the lengthy blood tube culture procedure. Here we report a culture-free workflow for the rapid isolation and enrichment of bacterial pathogens from whole blood for single-cell antimicrobial susceptibility testing (AST). A dextran sedimentation step reduces the concentration of blood cells by 4 orders of magnitude in 20–30 min while maintaining the effective concentration of bacteria in the sample. Red blood cell depletion facilitates the downstream centrifugation-based enrichment step at a sepsis-relevant bacteria concentration. The workflow is compatible with common antibiotic-resistant bacteria and does not influence the minimum inhibitory concentrations. By applying a microfluidic single-cell trapping device, we demonstrate the workflow for the rapid determination of bacterial infection and antimicrobial susceptibility testing at the single-cell level. The entire workflow from blood to categorical AST result can be completed in less than two hours.
Stability Assessment of Four Chimeric Proteins for Human Chagas Disease Immunodiagnosis
Authors: Celedon Paola Alejandra Fiorani , Leony Leonardo Maia , Oliveira Ueriton Dias , Freitas Natália Erdens Maron , Silva Ângelo Antônio Oliveira , Daltro Ramona Tavares , Santos Emily Ferreira , Krieger Marco Aurélio , Zanchin Nilson Ivo Tonin , Santos Fred Luciano Neves
Published: August 2021

The performance of an immunoassay relies on antigen-antibody interaction; hence, antigen chemical stability and structural integrity are paramount for an efficient assay. We conducted a functional, thermostability and long-term stability analysis of different chimeric antigens (IBMP), in order to assess effects of adverse conditions on four antigens employed in ELISA to diagnose Chagas disease. ELISA-based immunoassays have served as a model for biosensors development, as both assess molecular interactions. To evaluate thermostability, samples were heated and cooled to verify heat-induced denaturation reversibility. In relation to storage stability, the antigens were analyzed at 25 °C at different moments. Long-term stability tests were performed using eight sets of microplates sensitized. Antigens were structurally analyzed through circular dichroism (CD), dynamic light scattering, SDS-PAGE, and functionally evaluated by ELISA. Data suggest that IBMP antigens are stable, over adverse conditions and for over a year. Daily analysis revealed minor changes in the molecular structure. Functionally, IBMP-8.2 and IBMP-8.3 antigens showed reactivity towards anti-T. cruzi antibodies, even after 72 h at 25 °C. Long-term stability tests showed that all antigens were comparable to the control group and all antigens demonstrated stability for one year. Data suggest that the antigens maintained their function and structural characteristics even in adverse conditions, making them a sturdy and reliable candidate to be employed in future in vitro diagnostic tests applicable to different models of POC devices, such as modern biosensors in development.
Neural Representation of Costs and Rewards in Decision Making
Authors: Chen Yixuan
Published: August 2021

Decision making is crucial for animal survival because the choices they make based on their current situation could influence their future rewards and could have potential costs. This review summarises recent developments in decision making, discusses how rewards and costs could be encoded in the brain, and how different options are compared such that the most optimal one is chosen. The reward and cost are mainly encoded by the forebrain structures (e.g., anterior cingulate cortex, orbitofrontal cortex), and their value is updated through learning. The recent development on dopamine and the lateral habenula’s role in reporting prediction errors and instructing learning will be emphasised. The importance of dopamine in powering the choice and accounting for the internal state will also be discussed. While the orbitofrontal cortex is the place where the state values are stored, the anterior cingulate cortex is more important when the environment is volatile. All of these structures compare different attributes of the task simultaneously, and the local competition of different neuronal networks allows for the selection of the most appropriate one. Therefore, the total value of the task is not encoded as a scalar quantity in the brain but, instead, as an emergent phenomenon, arising from the computation at different brain regions.
Prefrontal Transcranial Direct Current Stimulation Globally Improves Learning but Does Not Selectively Potentiate the Benefits of Targeted Memory Reactivation on Awake Memory Consolidation
Authors: Gilson Médhi , Nitsche Michael A. , Peigneux Philippe
Published: August 2021

Targeted memory reactivation (TMR) and transcranial direct current stimulation (tDCS) can enhance memory consolidation. It is currently unknown whether TMR reinforced by simultaneous tDCS has superior efficacy. In this study, we investigated the complementary effect of TMR and bilateral tDCS on the consolidation of emotionally neutral and negative declarative memories. Participants learned neutral and negative word pairs. Each word pair was presented with an emotionally compatible sound. Following learning, participants spent a 20 min retention interval awake under four possible conditions: (1) TMR alone (i.e., replay of 50% of the associated sounds), (2) TMR combined with anodal stimulation of the left DLPFC, (3) TMR combined with anodal stimulation of the right DLPFC and (4) TMR with sham tDCS. Results evidenced selective memory enhancement for the replayed stimuli in the TMR-only and TMR-sham conditions, which confirms a specific effect of TMR on memory. However, memory was enhanced at higher levels for all learned items (irrespective of TMR) in the TMR-anodal right and TMR-anodal left tDCS conditions, suggesting that the beneficial effects of tDCS overshadow the specific effects of TMR. Emotionally negative memories were not modulated by tDCS hemispheric polarity. We conclude that electrical stimulation of the DLPFC during the post-learning period globally benefits memory consolidation but does not potentiate the specific benefits of TMR.
An Integrated Sensitivity Analysis Method for Energy and Comfort Performance of an Office Building along the Chinese Coastline
Authors: Chen Ruijun , Tsay Yaw-Shyan
Published: August 2021

This study aimed to evaluate the comprehensive percentage influence of input parameters on building energy and comfort performance by a new approach of sensitivity analysis (SA) and explore the most reliable and neutral sampling and sensitivity assessment method. The research combined 7 sampling methods with 13 SA methods to comprehensively integrate the percentage influence of 25 input parameters on building energy and comfort performance in 24 coastal cities of China. The results have found that the percentage influence of many important input parameters is affected by geographical position. Considering both energy and comfort performance of the building, the key parameters are heating setpoint, infiltration rate, cooling setpoint, roof U value, roof solar absorptance, window solar heat gain coefficient, equipment, and occupant density, all of which could comprehensively impact 70% of energy demand and comfort performance along the Chinese coastline. This is of great significance for policymakers to formulate relative building regulations. After comparing the F-test and the exceed percentage test, we recommended the Pearson with Quasi-random sampling method as the most reliable SA assessment method in building simulation, followed by the standardized regression coefficient in random sampling and Latin hypercube sampling methods, which can achieve data closest to the average value.
The Unfolded Protein Response Is a Major Driver of LCN2 Expression in BCR–ABL- and JAK2V617F-Positive MPN
Authors: Tillmann Stefan , Olschok Kathrin , Schröder Sarah K. , Bütow Marlena , Baumeister Julian , Kalmer Milena , Preußger Vera , Weinbergerova Barbora , Kricheldorf Kim , Mayer Jiri , Kubesova Blanka , Racil Zdenek , Wessiepe Martina , Eschweiler Jörg , Isfort Susanne , Brümmendorf Tim H. , Becker Walter , Schemionek Mirle , Weiskirchen Ralf , Koschmieder Steffen , Chatain Nicolas
Published: August 2021

Lipocalin 2 (LCN2), a proinflammatory mediator, is involved in the pathogenesis of myeloproliferative neoplasms (MPN). Here, we investigated the molecular mechanisms of LCN2 overexpression in MPN. LCN2 mRNA expression was 20-fold upregulated in peripheral blood (PB) mononuclear cells of chronic myeloid leukemia (CML) and myelofibrosis (MF) patients vs. healthy controls. In addition, LCN2 serum levels were significantly increased in polycythemia vera (PV) and MF and positively correlated with JAK2V617F and mutated CALR allele burden and neutrophil counts. Mechanistically, we identified endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) as a main driver of LCN2 expression in BCR-ABL- and JAK2V617F-positive 32D cells. The UPR inducer thapsigargin increased LCN2 expression >100-fold, and this was not affected by kinase inhibition of BCR-ABL or JAK2V617F. Interestingly, inhibition of the UPR regulators inositol-requiring enzyme 1 (IRE1) and c-Jun N-terminal kinase (JNK) significantly reduced thapsigargin-induced LCN2 RNA and protein expression, and luciferase promoter assays identified nuclear factor kappa B (NF-κB) and CCAAT binding protein (C/EBP) as critical regulators of mLCN2 transcription. In conclusion, the IRE1–JNK-NF-κB–C/EBP axis is a major driver of LCN2 expression in MPN, and targeting UPR and LCN2 may represent a promising novel therapeutic approach in MPN.