bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and clinical application of a deep learning model to identify acute infarct on magnetic resonance imaging
Authors: Bridge Christopher P. , Bizzo Bernardo C. , Hillis James M. , Chin John K. , Comeau Donnella S. , Gauriau Romane , Macruz Fabiola , Pawar Jayashri , Noro Flavia T. C. , Sharaf Elshaimaa , Straus Takahashi Marcelo , Wright Bradley , Kalafut John F. , Andriole Katherine P. , Pomerantz Stuart R. , Pedemonte Stefano , González R. Gilberto 
Published: February 2022

AbstractStroke is a leading cause of death and disability. The ability to quickly identify the presence of acute infarct and quantify the volume on magnetic resonance imaging (MRI) has important treatment implications. We developed a machine learning model that used the apparent diffusion coefficient and diffusion weighted imaging series. It was trained on 6,657 MRI studies from Massachusetts General Hospital (MGH; Boston, USA). All studies were labelled positive or negative for infarct (classification annotation) with 377 having the region of interest outlined (segmentation annotation). The different annotation types facilitated training on more studies while not requiring the extensive time to manually segment every study. We initially validated the model on studies sequestered from the training set. We then tested the model on studies from three clinical scenarios: consecutive stroke team activations for 6-months at MGH, consecutive stroke team activations for 6-months at a hospital that did not provide training data (Brigham and Women’s Hospital [BWH]; Boston, USA), and an international site (Diagnósticos da América SA [DASA]; Brazil). The model results were compared to radiologist ground truth interpretations. The model performed better when trained on classification and segmentation annotations (area under the receiver operating curve [AUROC] 0.995 [95% CI 0.992–0.998] and median Dice coefficient for segmentation overlap of 0.797 [IQR 0.642–0.861]) compared to segmentation annotations alone (AUROC 0.982 [95% CI 0.972–0.990] and Dice coefficient 0.776 [IQR 0.584–0.857]). The model accurately identified infarcts for MGH stroke team activations (AUROC 0.964 [95% CI 0.943–0.982], 381 studies), BWH stroke team activations (AUROC 0.981 [95% CI 0.966–0.993], 247 studies), and at DASA (AUROC 0.998 [95% CI 0.993–1.000], 171 studies). The model accurately segmented infarcts with Pearson correlation comparing model output and ground truth volumes between 0.968 and 0.986 for the three scenarios. Acute infarct can be accurately detected and segmented on MRI in real-world clinical scenarios using a machine learning model.
Bioprocess development for bacterial cellulose biosynthesis by novel Lactiplantibacillus plantarum isolate along with characterization and antimicrobial assessment of fabricated membrane
Authors: Saleh Ahmed K. , El-Gendi Hamada , Soliman Nadia A. , El-Zawawy Waleed K. , Abdel-Fattah Yasser R. 
Published: February 2022

AbstractBacterial cellulose (BC) is an ecofriendly biopolymer with diverse commercial applications. Its use is limited by the capacity of bacterial production strains and cost of the medium. Mining for novel organisms with well-optimized growth conditions will be important for the adoption of BC. In this study, a novel BC-producing strain was isolated from rotten fruit samples and identified as Lactiplantibacillus plantarum from 16S rRNA sequencing. Culture conditions were optimized for supporting maximal BC production using one variable at a time, Plackett–Burman design, and Box Behnken design approaches. Results indicated that a modified Yamanaka medium supported the highest BC yield (2.7 g/l), and that yeast extract, MgSO4, and pH were the most significant variables influencing BC production. After optimizing the levels of these variables through Box Behnken design, BC yield was increased to 4.51 g/l. The drug delivery capacity of the produced BC membrane was evaluated through fabrication with sodium alginate and gentamycin antibiotic at four different concentrations. All membranes (normal and fabricated) were characterized by scanning electron microscope, Fourier transform-infrared spectroscopy, X-ray diffraction, and mechanical properties. The antimicrobial activity of prepared composites was evaluated by using six human pathogens and revealed potent antibacterial activity against Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Streptococcus mutans, with no detected activity against Pseudomonas aeruginosa and Candida albicans.
Different perception of dry eye symptoms between patients with and without primary Sjogren’s syndrome
Authors: Kim Minjeong , Chun Yeoun Sook , Kim Kyoung Woo 
Published: February 2022

AbstractHere, we investigated the different perception of dry eye symptoms between in patients with and without primary Sjogren’s syndrome (pSS). In this study, 221 patients with dry eye disease (DED) without pSS (non-SS DED group) and 55 patients with DED with pSS (SS DED group) were included. The ocular discomfort was evaluated using ocular surface disease index (OSDI) questionnaire and patients were further divided into 3 severity subgroups according to OSDI scores. The OSDI score was higher in the non-SS DED group even after matching corneal erosion scores despite the ocular surface erosions and tear deficiency was worse in the SS DED group. The corneal sensitivity was nearly normal in both groups without inter-group difference (Non-SS DED group: 5.82 ± 0.54 cm, SS DED group: 5.90 ± 0.29 cm, p = 0.217). Moreover, all clinical parameters were not significantly correlated with OSDI scores in both non-SS DED group and SS DED group. In the mild and severe OSDI subgroups, the ocular surface erosions and tear deficiency were worse in the SS DED group whereas the OSDI scores were not different between groups. In conclusion, clinicians should be aware that pSS patients may complain less of their discomfort unlike their actual severe status of DED.
Characterization of influenza A virus induced transposons reveals a subgroup of transposons likely possessing the regulatory role as eRNAs
Authors: Shen Steven S. , Nanda Hezkiel , Aliferis Constantin , Langlois Ryan A. 
Published: February 2022

AbstractAlthough many studies have observed genome-wide host transposon expression alteration during viral infection, the mechanisms of induction and the impact on the host remain unclear. Utilizing recently published influenza A virus (IAV) time series data and ENCODE functional genomics data, we characterized virus induced host differentially expressed transposons (virus-induced-TE) by investigating genome-wide spatial and functional relevance between the virus-induced-TEs and epigenomic markers (e.g. histone modification and chromatin remodelers). We found that a significant fraction of virus-induced-TEs are derived from host enhancer regions, where CHD4 binding and/or H3K27ac occupancy is high or H3K9me3 occupancy is low. By overlapping virus-induced-TEs to human enhancer RNAs (eRNAs), we discovered that a proportion of virus-induced-TEs are either eRNAs or part of enhancer RNAs. Upon further analysis of the eRNA targeted genes, we found that the virus-induced-TE related eRNA targets are overrepresented in differentially expressed host genes of IAV infected samples. Our results suggest that changing chromatin accessibility from repressive to permissive in the transposon docked enhancer regions to regulate host downstream gene expression is potentially one of the virus and host cell interaction mechanisms, where transposons are likely important regulatory genomic elements. Our study provides a new insight into the mechanisms of virus-host interaction and may lead to novel strategies for prevention and therapeutics of IAV and other virus infectious diseases.
An experimental and theoretical approach to electrochemical sensing of environmentally hazardous dihydroxy benzene isomers at polysorbate modified carbon paste electrode
Authors: Ganesh Pattan-Siddappa , Kim Sang-Youn , Kaya Savas , Salim Rajae 
Published: February 2022

AbstractIt is well known that, surfactants provide a neutral, positive and/or negative charge on the electrode surface by forming a monolayer, which in turn affects the charge transfer and redox potential during the electroanalysis process. However, the molecular level understanding of these surfactant-modified electrodes is worth investigating because the interaction of the analyte with the electrode surface is still unclear. In this report, we used quantum chemical models based on computational density functional theory (DFT) to investigate the polysorbate 80 structure as well as the locations of energy levels and electron transfer sites. Later, the bare carbon paste electrode (bare/CPE) was modified with polysorbate 80 and used to resolve the overlapped oxidation signals of dihydroxy benzene isomers. The m/n values obtained at polysorbate/CPE was approximately equal to 1, signifying the transfer of same number of protons and electrons. Moreover, the analytical applicability of the modified electrode for the determination of catechol (CC) and hydroquinone (HQ) in tap water samples gave an acceptable recovery result. Overall, the application of DFT to understand the molecular level interaction of modifiers for sensing applications laid a new foundation for fabricating electrochemical sensors.
Efficient oil–water separation coating with robust superhydrophobicity and high transparency
Authors: Chen Baiyi , Zhang Rongrong , Fu Hexuan , Xu Jiadai , Jing Yuan , Xu Guohe , Wang Bin , Hou Xu 
Published: February 2022

AbstractThere has been a growing interest in oil–water separation due to the massive economic and energy loss caused by world-wide oil spill. In the past decades, a new type of superhydrophobic surface has been developed for the efficient oil–water separation, but its large-scale use is significantly limited by its expensive, sophisticated, and fragile roughness structure. Meanwhile, to handle complex operating conditions, the transparency of the superhydrophobic surface has been more attractive due to its potential visual oil–water separation and optical application scenarios. Herein, we showed a simple and versatile strategy to fabricate superhydrophobic coating with robustness and high transparency. Subsequently, this multifunctional superhydrophobic coating was utilized for oil–water separation and indicated excellent separation efficiency. In this strategy, candle soot composed of carbon nanoparticles was deposited onto the substrate and used as a rough surface template. Then, a filmy and hard silica shell was modified onto this template via chemical vapor deposition to reinforce the roughness structure. Following, this soot-silica coated substrate was calcined in air to remove the candle soot template. Finally, based on a rational surface design, this robust silica coating achieved excellent superhydrophobicity thereby showing inherently oil–water separation benefits. This reinforced superhydrophobic coating presented robust superhydrophobicity even after 410 s sand impacting with the height of 40 cm and 20 cycles of sandpaper abrasion. Also, it retained excellent oil–water separation efficiency even after reuses.
Nitrate sources and mixing in the Danube watershed: implications for transboundary river basin monitoring and management
Authors: Halder J. , Vystavna Y. , Wassenaar L. I. 
Published: February 2022

AbstractDispersed and unknown pollution sources complicate water management in large transboundary watersheds. We applied stable isotopes of water and nitrate together with contaminants of emerging concern (CECs: carbamazepine, caffeine, sulfamethoxazole, perfluorooctanoic acid and 2,4-dinitrophenol) to evaluate mixing and inputs of water and contaminants from tributaries into the mainstem of the transboundary Danube River. Stable isotope (δ18O, δ2H) variations from low values (− 13.3 ‰, − 95.1 ‰) in the Upper Danube after the Inn River confluence to high values (− 9.9 ‰, − 69.7 ‰) at the Danube River mouth revealed snowmelt dominated tributary mixing (~ 70%) in the mainstem. Stable isotopes of nitrate (δ15N-NO3) in the Danube River varied from lower values (+ 6.7 ‰) in the Upper Danube to higher values after the mixing with Morava River (+ 10.5 ‰) and showed that cold snowmelt can reduce biological activity and controls nitrate biotransformation processes in the mainstem up to 1000 km downstream. Data on emerging contaminants affirmed the low biodegradation potential of organic compounds transferred into the mainstem by tributaries. We found pollutant source tracing in large rivers is complicated by mixing of multiple sources with overlapping isotopic signatures, but additional tracers such as CECs improve the interpretation of hydrological processes (e.g., water transit time) and support tracing of nitrate pollution sources, and biogeochemical processes. Our approach can be applied to other watersheds to improve the understanding of dilution and mixing processes. Moreover, it provides directions for improving national and transboundary water quality monitoring networks.
Blood–brain barrier disruption as a cause of various serum neuron-specific enolase cut-off values for neurological prognosis in cardiac arrest patients
Authors: Kang Changshin , You Yeonho , Ahn Hong Joon , Park Jung Soo , Jeong Wonjoon , Min Jin Hong , In Yong Nam , Yoo Insool , Cho Yongchul , Ryu Seung , Lee Jinwoong , Kim Seung Whan 
Published: February 2022

AbstractWe compared the cut-off and prognostic value of serum neuron-specific enolase (NSE) between groups with and without severe blood–brain barrier (BBB) disruption to reveal that a cause of various serum NSE cut-off value for neurological prognosis is severe BBB disruption in out-of-hospital cardiac arrest (OHCA) patients underwent target temperature management (TTM). This was a prospective, single-centre study conducted from January 2019 to June 2021. Severe BBB disruption was indicated using cerebrospinal fluid-serum albumin quotient values > 0.02. The area under the receiver operating characteristic curve of serum NSE obtained on day 3 of hospitalisation to predict poor outcomes was used. In patients with poor neurologic outcomes, serum NSE in those with severe BBB disruption was higher than in those without (P = 0.006). A serum NSE cut-off value of 40.4 μg/L for poor outcomes in patients without severe BBB disruption had a sensitivity of 41.7% and a specificity of 96.0%, whereas a cut-off value of 34.6 μg/L in those with severe BBB disruption had a sensitivity of 86.4% and a specificity of 100.0%. We demonstrated that the cut-off and prognostic value of serum NSE were heterogeneous, depending on severe BBB disruption in OHCA patients treated with TTM.
Co-occurrence CDK4/6 amplification serves as biomarkers of de novo EGFR TKI resistance in sensitizing EGFR mutation non-small cell lung cancer
Authors: Sitthideatphaiboon Piyada , Teerapakpinyo Chinachote , Korphaisarn Krittiya , Leelayuwatanakul Nophol , Pornpatrananrak Nopporn , Poungvarin Naravat , Chantranuwat Poonchavist , Shuangshoti Shanop , Aporntewan Chatchawit , Chintanapakdee Wariya , Sriuranpong Virote , Vinayanuwattikun Chanida 
Published: February 2022

AbstractDespite the development of predictive biomarkers to shape treatment paradigms and outcomes, de novo EGFR TKI resistance advanced non-small cell lung cancer (NSCLC) remains an issue of concern. We explored clinical factors in 332 advanced NSCLC who received EGFR TKI and molecular characteristics through 65 whole exome sequencing of various EGFR TKI responses including; de novo (progression within 3 months), intermediate response (IRs) and long-term response (LTRs) (durability > 2 years). Uncommon EGFR mutation subtypes were significantly variable enriched in de novo resistance. The remaining sensitizing EGFR mutation subtypes (exon 19 del and L858R) accounted for 75% of de novo resistance. Genomic landscape analysis was conducted, focusing in 10 frequent oncogenic signaling pathways with functional contributions; cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGF-β, p53 and β-catenin/Wnt signaling. Cell cycle pathway was the only significant alteration pathway among groups with the FDR p-value of 6 × 10–4. We found only significant q-values of < 0.05 in 7 gene alterations; CDK6, CCNE1, CDK4, CCND3, MET, FGFR4 and HRAS which enrich in de novo resistance [range 36–73%] compared to IRs/LTRs [range 4–22%]. Amplification of CDK4/6 was significant in de novo resistance, contrary to IRs and LTRs (91%, 27.9% and 0%, respectively). The presence of co-occurrence CDK4/6 amplification correlated with poor disease outcome with HR of progression-free survival of 3.63 [95% CI 1.80–7.31, p-value < 0.001]. The presence of CDK4/6 amplification in pretreatment specimen serves as a predictive biomarker for de novo resistance in sensitizing EGFR mutation.
Oropharyngeal administration of mother’s own milk influences levels of salivary sIgA in preterm infants fed by gastric tube
Authors: Chen Li-Lian , Liu Jie , Mu Xiao-He , Zhang Xi-Yang , Yang Chuan-Zhong , Xiong Xiao-Yun , Wang Mei-Qi 
Published: February 2022

AbstractThe aim of the present study was to explore the effect of oropharyngeal mother’s milk administration on salivary secretory immunoglobulin A (sIgA) levels in preterm infants fed by gastric tube. Infants (n = 130) with birth weight < 1500 g were randomly allocated into two groups which both received breast milk for enteral nutrition. The experimental group (n = 65) accepted oropharyngeal mother’s milk administration before gastric tube feeding for 14 days after birth. The control group (n = 65) accepted oropharyngeal 0.9% normal saline administration. Saliva concentration of sIgA were assessed at the 2 h, 7th and 14th day after birth. The level of salivary sIgA in experimental group were significantly higher than those in control group on the 7th day after birth (p < 0.05), but there were no differences in salivary sIgA levels on the 14th day between the two groups. The results of quantile regression analysis showed that oropharyngeal mother’s milk administration, delivery mode and gestational age had significant effects on the increase of sIgA. SIgA in experimental group and the total number of intervention had a significant positive correlation (p < 0.05). Oropharyngeal mother’s milk administration can improve salivary sIgA levels of preterm infants.
A novel method to design and evaluate artificial neural network for thin film thickness measurement traceable to the length standard
Authors: Lee Joonyoung , Jin Jonghan 
Published: February 2022

AbstractThe artificial neural networks (ANNs) have been often used for thin-film thickness measurement, whose performance evaluations were only conducted at the level of simple comparisons with the existing analysis methods. However, it is not an easy and simple way to verify the reliability of an ANN based on international length standards. In this article, we propose for the first time a method by which to design and evaluate an ANN for determining the thickness of the thin film with international standards. The original achievements of this work are to choose parameters of the ANN reasonably and to evaluate the training instead of a simple comparison with conventional methods. To do this, ANNs were built in 12 different cases, and then trained using theoretical spectra. The experimental spectra of the certified reference materials (CRMs) used here served as the validation data of each trained ANN, with the output then compared with a certified value. When both values agree with each other within an expanded uncertainty of the CRMs, the ANN is considered to be reliable. We expect that the proposed method can be useful for evaluating the reliability of ANN in the future.
Comprehensive characterization of the alternative splicing landscape in ovarian cancer reveals novel events associated with tumor-immune microenvironment
Authors: Sun Dan , Zhao Xingping , Yu Yang , Li Waixing , Gu Pan , Zhi Zhifu , Xu Dabao 
Published: February 2022

Abstract
Background: Ovarian cancer (OV) is a serious threat to women’s health. Immunotherapy is a new approach. Alternative splicing (AS) of messenger RNA (mRNA) and its regulation are highly relevant for understanding every cancer hallmark and may offer a broadened target space.
Methods: We downloaded the clinical information and mRNA expression profiles of 587 tumor tissues from The Cancer Genome Atlas (TCGA) database. We constructed a risk score model to predict the prognosis of OV patients. The association between AS-based clusters and tumor-immune microenvironment features was further explored. The ESTIMATE algorithm was also carried out on each OV sample depending on the risk score groups. A total of three immune checkpoint genes that have a significant correlation with risk scores were screened.
Results: The AS-events were a reliable and stable independent risk predictor in the OV cohort. Patients in the high-risk score group had a poor prognosis (P&lt;0.001). Mast cells activated, NK cells resting, and Neutrophils positively correlated with the risk score. The number of Macrophages M1 was also more numerous in the low-risk score group (P&lt;0.05). Checkpoint genes CD274, CTLA-4, and PDCD1LG2, showed a negative correlation with the risk score of AS in OV.
Conclusions: The proposed AS signature is a promising biomarker for estimating overall survival (OS) in OV. The AS-events signature combined with tumor-immune microenvironment enabled a deeper understanding of the immune status of OV patients, and also provided new insights for exploring novel prognostic predictors and precise therapy methods.
Research of key technologies for multi‐rotor UAV automatic aerial recovery system
Authors: Xing Zhenlin , Zhang Li , Ai Jianliang 
Published: February 2022

AbstractThis study proposes an aerial recovery technology that can complete aerial recovery for target unmanned aerial vehicles (UAVs) by a platform UAV to overcome the limitation of ground recovery for multi‐rotor UAVs. To ensure the safety of automatic aerial recovery, more requirements are made for the stability of multi‐rotor UAVs. This study proposes a back‐stepping trajectory tracking controller for feedforward compensation of uncertain disturbances. The results of the simulation show that the controller can effectively prevent external disturbance and meet requirements for the desired trajectory tracking. Furthermore, based on a you only look once (YOLO) network, this study designs a real‐time image recognition and positioning system, which can achieve real‐time positioning for platform UAV by the target UAV with an image‐processing rate of 8 frames per second (FPS). With the main objective of safety, this study designs an automatic recovery guiding system for target UAVs using a fuzzy controller. The target UAVs can automatically realize a soft landing on the platform UAV effect of the guiding system. Finally, this study conducts dynamic recovery tests in‐flight and verifies the feasibility of automatic aerial recovery technology for multi‐rotor UAVs.