bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic and functional characterization of bacteriocinogenic lactic acid bacteria isolated from Boza, a traditional cereal-based beverage
Authors: Queiroz Luciano Lopes , Hoffmann Christian , Lacorte Gustavo Augusto , de Melo Franco Bernadette Dora Gombossy , Todorov Svetoslav Dimitrov 
Published: January 2022

AbstractBoza is a traditional low-alcohol fermented beverage from the Balkan Peninsula, frequently explored as a functional food product. The product is rich in Lactic Acid Bacteria (LAB) and some of them can produce bacteriocins. In this study, a sample of Boza from Belogratchik, Bulgaria, was analyzed for the presence of bacteriocinogenic LAB, and after analyses by RAPD-PCR, three representative isolates were characterized by genomic analyses, using whole genome sequencing. Isolates identified as Pediococcus pentosaceus ST75BZ and Pediococcus pentosaceus ST87BZ contained operons encoding for bacteriocins pediocin PA-1 and penocin A, while isolate identified as Pediococcus acidilactici ST31BZ contained only the operon for pediocin PA-1 and a CRISPR/Cas system for protection against bacteriophage infection. The antimicrobial activity of bacteriocins produced by the three isolates was inhibited by treatment of the cell-free supernatants with proteolytic enzymes. The produced bacteriocins inhibited the growth of Listeria monocytogenes, Enterococcus spp. and some Lactobacillus spp., among other tested species. The levels of bacteriocin production varied from 3200 to 12,800 AU/ml recorded against L. monocytogenes 104, 637 and 711, measured at 24 h of incubation at 37 °C. All bacteriocins remained active after incubation at pH 2.0–10.0. The activity mode of the studied bacteriocins was bactericidal, as determined against L. monocytogenes 104, 637 and 711. In addition, bactericidal activity was demonstrated using a cell leakage β-galactosidase assay, indicating a pore formation mechanism as a mode of action. The present study highlights the importance of combining genomic analyses and traditional microbiological approaches as way of characterizing microbial interactions in fermented foods.
Therapeutic enzyme engineering using a generative neural network
Authors: Giessel Andrew , Dousis Athanasios , Ravichandran Kanchana , Smith Kevin , Sur Sreyoshi , McFadyen Iain , Zheng Wei , Licht Stuart 
Published: January 2022

AbstractEnhancing the potency of mRNA therapeutics is an important objective for treating rare diseases, since it may enable lower and less-frequent dosing. Enzyme engineering can increase potency of mRNA therapeutics by improving the expression, half-life, and catalytic efficiency of the mRNA-encoded enzymes. However, sequence space is incomprehensibly vast, and methods to map sequence to function (computationally or experimentally) are inaccurate or time-/labor-intensive. Here, we present a novel, broadly applicable engineering method that combines deep latent variable modelling of sequence co-evolution with automated protein library design and construction to rapidly identify metabolic enzyme variants that are both more thermally stable and more catalytically active. We apply this approach to improve the potency of ornithine transcarbamylase (OTC), a urea cycle enzyme for which loss of catalytic activity causes a rare but serious metabolic disease.
The effect of lack of ANC visit and unwanted pregnancy on home child-birth in Ethiopia: a systematic review and meta-analysis
Authors: Damtie Yitayish , Kefale Bereket , Yalew Melaku , Arefaynie Mastewal , Addisu Elsabeth , Birhan Tesfaye , Cherie Nigus , Adane Bezawit , Melese Wolde , Bitew Gedamnesh , Tadesse Erkihun , Dewau Reta , Andualem Atsedemariam 
Published: January 2022

AbstractAlthough extensive efforts were made to improve maternal and child health, the magnitude of home child-birth is considerably high in Ethiopia. Therefore, this meta-analysis aimed to estimate the effect of lack of ANC visit and unwanted pregnancy on home child-birth among reproductive-age women in Ethiopia. International databases, including Cochrane Library, Google Scholar, PubMed, Global Health, HINARI, and CINAHL were searched systematically to identify studies reporting the prevalence of home child-birth and its association with lack of ANC visit and unwanted pregnancy among reproductive-age women in Ethiopia. STATA/SE version-14 was used to analyze the data and Der Simonian and Liard's method of random effect model was used to estimate the pooled effects. The heterogeneity between study and publication bias was assessed by using I-squared statistics and Egger's test respectively. A total of 19 studies with 25,228 study participants were included in this meta-analysis. The pooled prevalence of home child-birth among reproductive-age women in Ethiopia was 55.3%. Sever heterogeneity was exhibited among the included studies (I2 = 99.8, p = 0.000). The odds of home child-birth among mothers who have no ANC visit was 3.64 times higher compared to their counterparts [OR = 3.64, 95%, CI: (1.45, 9.13)]. There was significant heterogeneity among the included studies (I2 = 94%, p = 0.000). However, there was no statistical evidence of publication bias in the pooled effect of lack of ANC visit on home child-birth (P = 0.302). Women who experienced unwanted pregnancy were 3.02 times higher to give birth at home compared to women with a wanted pregnancy [OR = 3.02, 95%CI: (1.19, 7.67)]. Severe heterogeneity was exhibited (I2 = 93.1%, p = 0.000) but, there was no evidence of significant publication bias in the pooled effect of unwanted pregnancy on home child-birth (P = 0.832). The proportion of home child-birth among reproductive-age women in Ethiopia remains high. Lack of ANC visit and unwanted pregnancy had a significant effect on the practice of home child-birth. Strengthening behavioral change communication programs should be the primary focus area to improve institutional delivery service utilization among women with lack of ANC visit and unwanted pregnancy.
Infection dynamics of COVID-19 virus under lockdown and reopening
Authors: Svoboda Jakub , Tkadlec Josef , Pavlogiannis Andreas , Chatterjee Krishnendu , Nowak Martin A. 
Published: January 2022

AbstractMotivated by COVID-19, we develop and analyze a simple stochastic model for the spread of disease in human population. We track how the number of infected and critically ill people develops over time in order to estimate the demand that is imposed on the hospital system. To keep this demand under control, we consider a class of simple policies for slowing down and reopening society and we compare their efficiency in mitigating the spread of the virus from several different points of view. We find that in order to avoid overwhelming of the hospital system, a policy must impose a harsh lockdown or it must react swiftly (or both). While reacting swiftly is universally beneficial, being harsh pays off only when the country is patient about reopening and when the neighboring countries coordinate their mitigation efforts. Our work highlights the importance of acting decisively when closing down and the importance of patience and coordination between neighboring countries when reopening.
Design and implementation of a terahertz lens-antenna for a photonic integrated circuits based THz systems
Authors: Al-Daffaie Shihab , Jumaah Alaa Jabbar , Rubio Verónica Laín , Kusserow Thomas 
Published: January 2022

AbstractA new integrated lens-antenna is designed and implemented for a nanocontact based terahertz (THz) photomixer. The new design replaces the standard conventional bulky silicon lens, which normally no THz photomixer can avoid. The Fresnel Zone Plate is used to design the new lens-antenna and is simulated by the MIT open-source tool called Meep. The final design showed, with only two simple fabrication technology processing steps (standard optical lithography) that the lens-antenna can be monolithically integrated with the THz nanophotomixer. With its compact design, the THz measurements showed a comparable behavior to the conventional bulky silicon lens, therefore it would be ready for photonic integrated circuits based THz systems.
Biomarker selection and a prospective metabolite-based machine learning diagnostic for lyme disease
Authors: Kehoe Eric R. , Fitzgerald Bryna L. , Graham Barbara , Islam M. Nurul , Sharma Kartikay , Wormser Gary P. , Belisle John T. , Kirby Michael J. 
Published: January 2022

AbstractWe provide a pipeline for data preprocessing, biomarker selection, and classification of liquid chromatography–mass spectrometry (LCMS) serum samples to generate a prospective diagnostic test for Lyme disease. We utilize tools of machine learning (ML), e.g., sparse support vector machines (SSVM), iterative feature removal (IFR), andk-fold feature ranking to select several biomarkers and build a discriminant model for Lyme disease. We report a 98.13% test balanced success rate (BSR) of our model based on a sequestered test set of LCMS serum samples. The methodology employed is general and can be readily adapted to other LCMS, or metabolomics, data sets.
Underactuated USV path following mechanism based on the cascade method
Authors: Lin Mingzhen , Zhang Zhiqiang , Pang Yandong , Lin Hongsheng , Ji Qing 
Published: January 2022

AbstractThe path following control under disturbance was studied for an underactuated unmanned surface vehicle (USV) subject to the rudder angle and velocity constraints. For this reason, a variable look-ahead integral line-of-sight (LOS) guidance law was designed on the basis of the disturbance estimation and compensation, and a cascade path following control system was created following the heading control law based on the model prediction. Firstly, the guidance law was designed using the USV three-degree-of-freedom (DOF) motion model and the LOS method, while the tracking error state was introduced to design the real-time estimation of disturbance observer and compensate for the influence of ocean current. Moreover, the stability of the system was analyzed. Secondly, sufficient attention was paid to the rudder angle and velocity constraints and the influence of system delay and other factors in the process of path following when the heading control law was designed with the USV motion response model and the model predictive control (MPC). The moving horizon optimization strategy was adopted to achieve better dynamic performance, effectively overcome the influence of model and environmental uncertainties, and further prove the stability of the control law. Thirdly, a simulation experiment was carried out to verify the effectiveness and advancement of the proposed algorithm. Fourthly, the “Sturgeon 03” USV was used in the lake test of the proposed control algorithm to prove its feasibility in the engineering practices.
Multiphase arterial spin labeling imaging to predict early recurrent ischemic lesion in acute ischemic stroke
Authors: Nam Ki-Woong , Kim Chi Kyung , Yoon Byung-Woo , Hwang Inpyeong , Sohn Chul-Ho 
Published: January 2022

AbstractIn acute ischemic stroke (AIS), the hemodynamics around the lesion are important because they determine the recurrence or prognosis of the disease. This study evaluated the effects of perfusion deficits in multiphase arterial spin labeling (ASL) and related radiological parameters on the occurrence of early recurrent ischemic lesions (ERILs) in AIS. We assessed AIS patients who underwent multiphase ASL within 24 h of symptom onset and follow-up diffusion-weighted imaging within 7 days. ASL perfusion deficit, arterial transit artifact (ATA), and intra-arterial high-intensity signal (IAS) were manually rated as ASL parameters. A total of 134 patients were evaluated. In the multivariable analyses, ASL perfusion deficit [adjusted odds ratio (aOR) = 2.82, 95% confidence interval = 1.27–6.27] was positively associated with ERIL. Furthermore, when ATA was accompanied, the ASL perfusion deficit was not associated with ERIL occurrence. Meanwhile, IAS showed a synergistic effect with ASL perfusion deficit on the occurrence of ERIL. In conclusion, we demonstrated the association between perfusion deficits in multiphase ASL with ERIL in patients with AIS. This close association was attenuated by ATA and was enhanced by IAS. ASL parameters may help identify high-risk patients of ERIL occurrence during the acute period.
Copy number alterations analysis of primary tumor tissue and circulating tumor cells from patients with early-stage triple negative breast cancer
Authors: Silvestri Marco , Dugo Matteo , Vismara Marta , De Cecco Loris , Lanzoni Davide , Vingiani Andrea , Folli Secondo , De Santis Maria Carmen , de Braud Filippo , Pruneri Giancarlo , Di Cosimo Serena , Cappelletti Vera 
Published: January 2022

AbstractTriple negative breast cancer (TNBC) is characterized by clinical aggressiveness, lack of recognized target therapy, and a dismal patient prognosis. Several studies addressed genomic changes occurring during neoadjuvant chemotherapy (NAC) focusing on somatic variants, but without including copy number alterations (CNAs). We analyzed CNA profiles of 31 TNBC primary tumor samples before and after NAC and of 35 single circulating tumor cells (CTCs) collected prior, during and after treatment by using next-generation sequencing targeted profile and low-pass whole genome sequencing, respectively. In pre-treatment tissue samples, the most common gains occurred on chromosomes 1, 2 and 8, and SOX11 and MYC resulted the most altered genes. Notably, amplification of MSH2 (4/4 versus 0/12, p < 0.01) and PRDM1 and deletion of PAX3 (4/4 versus 1/12, p < 0.01) significantly characterized primary tumors of patients with pathological complete response. All patients with paired pre- and post-NAC samples reported a change in post-treatment CNAs compared to baseline, despite they showed at least one common alteration. CNAs detected after treatment involved genes within druggable pathways such as EGFR, cell cycle process and Ras signaling. In two patients, CTCs shared more alterations with residual rather than primary tumor involving genes such as MYC, BCL6, SOX2, FGFR4. The phylogenetic analysis of CTCs within a single patient revealed NAC impact on tumor evolution, suggesting a selection of driver events under treatment pressure. In conclusion, our data showed how chemoresistance might arise early from treatment-induced selection of clones already present in the primary tumor, and that the characterization of CNAs on single CTCs informs on cancer evolution and potential druggable targets.
The relationship between running distance and coaches’ perception of team performance in professional soccer player during multiple seasons
Authors: Ponce-Bordón J. C. , García-Calvo T. , Candela-Guardiola J. M. , Serpiello F. R. , del Campo R. López , Resta R. , Pulido J. J. 
Published: January 2022

AbstractThis study analyzed how the physical movement profile of soccer matches evolved throughout a season by assessing the variability of different metrics depending on the season phase. In addition, the evolution of running distances was investigated in the relation to the team performance based on the coaches’ perception. Games from four consecutives Spanish LaLiga seasons (n = 1520) were recorded using an optical tracking system (i.e., ChyronHego). Total distance (TD), distance covered between 14 and 21 km h−1 (MIRD), 21–24 km h−1 (HIRD), and > 24 km h−1 (VHIRD) were analyzed, as well as the number of efforts between 21 and 24 km h−1 (Sp21) and > 24 km h−1 (Sp24). Seasons were divided into four phases (P): P1 (matches 1–10), P2 (11–19), P3 (20–29), and P4 (30–38). Linear mixed models revealed that soccer players covered significantly greater distances and completed a higher number of sprints in P2 and P3. Also, team performance evaluated by soccer coaches was positively related to TD, HIRD, VHIRD and Sp21 in P1. A negative relationship was observed between team performance and distance covered at speeds below 21 km h−1 in P2 and P3. Team performance was negatively related to TD, MIRD, and HIRD, and Sp21 in P4. As conclusion, the team performance perceived by coaches is related to the movement profile throughout a season, and it significantly influences the evolution of soccer players’ movement profiles. Specifically, it seems that the players of the best teams have the best physical performance at the beginning of the season with respect to the rest of the phases.
The vibration response mechanism of a blade disk rotor system under the coupling effects of cracks and aerodynamic forces
Authors: Yang J. , Xie J. , Wang T. , Yang F. , Chen J. 
Published: January 2022

AbstractThe important role of a dynamic model is to study the response characteristics of a system under different parameters or fault states. These response characteristics can be used in many aspects, such as condition monitoring and fault diagnosis. Usually, the response characteristics can be obtained through numerical analysis, but we do not know why such characteristics appear, which hinders our understanding and utilization of vibration. The innovation of this paper is to reasonably explain why such response characteristics appear. First, a simplified dynamic model of a typical blade disk rotor system is constructed by using the classical continuous parameter modeling method. Based on the dynamic model, for two structural forms of moving and stationary blades, the typical characteristics of the vibration response under the actions of aerodynamic force and blade cracks are analyzed by means of numerical solution. Then, from the perspective of kinematics and dynamics, the internal mechanism between the vibration responses and the excitations is revealed. Finally, based on Number Theory, the response characteristics and mechanisms of typical structures are summarized, and the general laws of responses with general structural forms are established.
Machine learning-based approaches for identifying human blood cells harboring CRISPR-mediated fetal chromatin domain ablations
Authors: Li Yi , Zaheri Shadi , Nguyen Khai , Liu Li , Hassanipour Fatemeh , Pace Betty S. , Bleris Leonidas 
Published: January 2022

AbstractTwo common hemoglobinopathies, sickle cell disease (SCD) and β-thalassemia, arise from genetic mutations within the β-globin gene. In this work, we identified a 500-bp motif (Fetal Chromatin Domain, FCD) upstream of human ϒ-globin locus and showed that the removal of this motif using CRISPR technology reactivates the expression of ϒ-globin. Next, we present two different cell morphology-based machine learning approaches that can be used identify human blood cells (KU-812) that harbor CRISPR-mediated FCD genetic modifications. Three candidate models from the first approach, which uses multilayer perceptron algorithm (MLP 20-26, MLP26-18, and MLP 30-26) and flow cytometry-derived cellular data, yielded 0.83 precision, 0.80 recall, 0.82 accuracy, and 0.90 area under the ROC (receiver operating characteristic) curve when predicting the edited cells. In comparison, the candidate model from the second approach, which uses deep learning (T2D5) and DIC microscopy-derived imaging data, performed with less accuracy (0.80) and ROC AUC (0.87). We envision that equivalent machine learning-based models can complement currently available genotyping protocols for specific genetic modifications which result in morphological changes in human cells.
Simultaneous measurement of two biological signals using a multi-layered polyvinylidene fluoride sensor
Authors: Manh Long-Nguyen , Li Jinghua , Kweon Hyunkyu , Chae Younghun 
Published: January 2022

AbstractCardiovascular and deep breathing diseases can be detected by measuring human signals such as heart rate, respiration, and blood pressure, which are important physiological parameters for accessing the state of the body. However, conventionally, heart and respiration rates are monitored using different sensors, which is cumbersome and can further increase the psychological burden on patients. To address these issues, this report proposes a sensor consisting of two stacked elements that can simultaneously measure heart and respiration rates. The two signals received can be expressed separately as heart and respiration rates after signal processing. The two stacked elements are composed of polyvinylidene fluoride thin film bonded to a polydimethylsiloxane substrate. One element (element 1) measures movement related to the heart, and the other (element 2) measures movement related to breathing. Elements 1 and 2 were experimentally observed to have sensitivities of 0.163 V/N and 0.209 V/N, respectively. In addition, the proposed system was compared with a commercial digital heart rate and respiration rate measurement instrument and was verified to be effective for simultaneous measurement of human vital signals with multiple sensors. In addition, the proposed system is flexible, lightweight, and inexpensive, making it convenient and economical.
High expression of tight junction protein 1 as a predictive biomarker for bladder cancer grade and staging
Authors: Lee Yi-Chen , Tsai Kuo-Wang , Liao Jia-Bin , Kuo Wei-Ting , Chang Yu-Chan , Yang Yi-Fang 
Published: January 2022

AbstractTight junction proteins 1–3 (TJP1–3) are components of tight junctions that can link transmembrane proteins to the actin cytoskeleton, and their incidence directly correlates to metastasis. However, the role of the TJP family in bladder cancer has not been adequately evaluated. In this study, we evaluated the genetic changes, mRNA and protein expressions of the target genes of the TJP family in bladder cancer patients using online database and immunohistochemistry, respectively. We found that TJP1 was amplified in bladder cancer tissue and that the protein expression levels were significantly associated with age (p = 0.03), grade (p = 0.007), and stage (p = 0.011). We also examined the correlation between TJP1 and other high-frequency mutation genes using TIMER. TJP1 mRNA levels were positively correlated with TTN and RYR3 mRNA levels in bladder cancer tissue. Taken together, TJP1 expression is associated with poor clinical outcomes in patients with bladder cancer and can be a useful predictive biomarker for bladder cancer staging.