bluuebunny/crossref_metadata_2025_split huggingface dataset:
Close relatives of MERS-CoV in bats use ACE2 as their functional receptors
Authors: Yan Huan , Wang Xiangxi , Xiong Qing , Cao Lei , Ma Chengbao , Liu Chen , Si Junyu , Liu Peng , Gu Mengxue , Wang Chunli , Shi Lulu , Tong Fei , Huang Meiling , zhao chufeng , Shen Chao , Chen Yu , Zhao Huabin , Lan Ke , Li Jing 
Published: March 2022

Abstract
Middle East Respiratory Syndrome coronavirus (MERS-CoV) and several bat coronaviruses employ Dipeptidyl peptidase-4 (DPP4) as their functional receptors. However, the receptor for NeoCoV, the closest MERS-CoV relative yet discovered in bats, remains enigmatic. In this study, we unexpectedly found that NeoCoV and its close relative, PDF-2180-CoV, can efficiently use some types of bat Angiotensin-converting enzyme 2 (ACE2) and, less favorably, human ACE2 for entry. The two viruses use their spikes' S1 subunit carboxyl-terminal domains (S1-CTD) for high-affinity and species-specific ACE2 binding. Cryo-electron microscopy analysis revealed a novel coronavirus-ACE2 binding interface and a protein-glycan interaction, distinct from other known ACE2-using viruses. We identified a molecular determinant close to the viral binding interface that restricts human ACE2 from supporting NeoCoV infection, especially around residue Asp338. Conversely, NeoCoV efficiently infects human ACE2 expressing cells after a T510F mutation on the receptor-binding motif (RBM). Notably, the infection could not be cross-neutralized by antibodies targeting SARS-CoV-2 or MERS-CoV. Our study demonstrates the first case of ACE2 usage in MERS-related viruses, shedding light on a potential bio-safety threat of the human emergence of an ACE2 using "MERS-CoV-2" with both high fatality and transmission rate.
Contextualizing critical thinking about health using digital technology in secondary schools in Kenya: a qualitative analysis
Authors: Chesire Faith chelagat , Ochieng Marlyn Achieng , Mugisha Michael , Senyonga Ronald , Oxman Matt , Nsangi Allen , Semakula Daniel , Nyirazinyoye Laetitia , Lewin Simon , Sewankambo Nelson K. , Kaseje Margaret , Oxman Andrew D , Rosenbaum Sarah 
Published: March 2022

Abstract
Background: Good health decisions depend on one’s ability to think critically about health claims and make informed health choices. Young people can learn these skills through school-based interventions, but learning resources need to be low-cost and built around lessons that can fit into existing curricula. As a first step to developing and evaluating digital learning resources that are feasible to use in Kenyan secondary schools, we conducted a context analysis to explore interest in critical thinking for health, map where critical thinking about health best fits in the curriculum, explore conditions for introducing new learning resources, and describe the information and communication technology (ICT) infrastructure available for teaching and learning.Methods: We employed a qualitative descriptive approach. We interviewed 10 key informants, carried out two focus group discussions, observed ICT conditions in five secondary schools, reviewed seven documents, and conducted an online catalogue of ICT infrastructure in all schools in Kisumu County. Participants included teachers, curriculum experts, and policymakers. We used a framework analysis approach to analyse data and report findings.Findings: Although critical thinking is a core competence in the curriculum, critical thinking about health is not currently taught in Kenyan secondary schools. Teachers, health officials and curriculum developers recognized the importance of teaching critical thinking about health in secondary schools. Stakeholders agreed that Informed Health Choices learning resources could be embedded in nine subjects. The National Institute of Curriculum Development regulates resources for learning; development of new resources requires collaboration and approval from this body. Most schools do not use ICT for teaching, and for those few that do, use is limited. Implementation of Kenya’s ICT policy framework for schools faces several challenges which include inadequate ICT infrastructure, poor internet connectivity, and teachers’ lack of training and experience.Conclusion: Teaching critical thinking about health is possible within the current Kenyan lower secondary school curriculum but learning resources will need to be designed for inclusion in and across existing subjects. The National ICT Plan and Vision for 2030 provides opportunity for scale up and integration of technology in teaching and learning environments, which can enable future use of digital resources in schools. However, given current ICT condition in schools in the country, digital learning resources should be designed to function with limited ICT infrastructure, unstable internet access and for use by teachers with low levels of experience using digital technology.
Clinical Applications of Machine Learning in the Survival Prediction and Classification of Sepsis：Coagulation and Heparin Usage Matter
Authors: Guo Fei , Zhu Xishun , Wu Zhiheng , Zhu Li , Wu Jianhua , Zhang Fan 
Published: March 2022

Abstract
Background
Sepsis is a life-threatening syndrome eliciting highly heterogeneous host responses. Current prognostic evaluation methods used in clinical practice are characterized by an inadequate effectiveness in predicting sepsis mortality. Rapid identification of patients with high mortality risk is urgently needed. The patients’ phenotype will assistant invaluably in tailoring treatments.
Methods
Deep learning technology is used to determine the sepsis severity and characterize the patients’ phenotype. The database used in this study is MIMIC-III and MIMIC-IV (‘Medical information Mart for intensive care’) which is a large, public, and freely available database. Convolutional neural network (CNN) was used to predict the 28-day survival rate based on 35 blood test variables of the sepsis patients, whereas a double coefficient quadratic multivariate fitting function (DCQMFF) is utilized to predict the 28-day survival rate with only 11 features of sepsis patients. The k-means clustering is used to classify the sepsis phenotype.
Results
The survival rate prediction accuracy of CNN and DCQMFF models reached 92% and 82%, respectively. The models were tested on an external dataset (MIMIC-IV) and achieved good performance. A DCQMFF-based application platform was established for fast prediction of the 28-day survival rate. The patients were grouped into four clusters with a clear survival nomogram. The first cluster (C_1) was characterized by low white blood cell count, low neutrophil, and the highest lymphocyte proportion. C_2 obtained the lowest Sequential Organ Failure Assessment (SOFA) score and the highest survival rate. C_3 was characterized by significantly prolonged PTT, high SIC, and a higher proportion of patients using heparin than the patients in other clusters. The early mortality rate of patients in C_3 was high but with a better long-term survival rate than that in C_4. C_4 contained septic coagulation patients with the worst prognosis, characterized by slightly prolonged partial thromboplastin time (PTT), significantly prolonged prothrombin time (PT), and high septic coagulation disease score (SIC).
Conclusion
CNN and DCQMFF accurately predicted the sepsis patients’ survival, while k-means successfully identified the phenotype groups. The distinct phenotypes associated with survival, and significant features correlated with mortality were identified. The findings suggest that sepsis patients with abnormal coagulation had poor outcomes, abnormal coagulation increase mortality during sepsis. The anticoagulation effects of appropriate heparin sodium treatment may improve extensive micro thrombosis-caused organ failure.
Effect of Changing Precipitation Timing on Phylogenetic and Functional Community Structure in A Semi-Arid Steppe
Authors: Yang Zhongling , Wang Manman , Yang Jianwen , Zhang Tong , Xiao Rui 
Published: March 2022

Abstract
Changes in the amount and timing of precipitation may affect plant species coexistence. However, little is known about how these changes in precipitation structure plant communities. Here, we conducted a six-year field precipitation manipulation experiment in the semi-arid steppe of Inner Mongolia, China to assess the importance of species loss and colonization to community assembly by incorporating phylogenetic information on functional relatedness. Our results demonstrated that the decline in plant species richness under decreasing precipitation in the late and entire growing season could be attributed to a decrease in species colonization and an increase in species loss, respectively. The increase in species richness under increasing precipitation in the late growing season was mainly caused by increases in colonizing species. Species with lower initial abundances, individual size, and leaf dry matter content had greater loss probabilities when species with lower initial abundances had greater colonization likelihood. The loss of species that were more closely related to other residents under decreasing precipitation in the late growing season did not alter phylogenetic overdispersion patterns, and the colonization of species that were more distantly related to residents under increasing precipitation in the late growing season shifted functional relatedness from clustering to randomness. Thus, the colonization of functionally dissimilar species decreased the strength of environmental filtering. Our study showed that phylogenetic and functional relatedness independently affected plant community structure. This finding suggests that evolutionary processes affect community assembly independently of ecological processes.
Venlafaxine-Loaded Nanocomposite-Based Scaffolds: In Vitro, Ex Vivo and Cytotoxicity Evaluations
Authors: Hashem Heba Maher , Motawea Amira , Kamel Ayman Helmy , Bary Elsayed Mohamed Abdel , Mohamed Saad Elsayed 
Published: March 2022

Abstract
Venlafaxine (VEN) is an antidepressant drug, but its delivery progress combined with a dependence on pathways and the incidence of toxicities that have infrequently led to FDA endorsement. This work focuses on developing novel electrospun polymeric nanofibers (NFs) for buccal delivery of VEN to avoid the hepatic metabolism, enzymatic degradation in the GIT, and develop an effective control of drug release. The optimized NFs were obtained by blending polylactic acid (PLA) and poly (ɛ-caprolactone) (PCL) and were characterized for morphology, drug-loading, FTIR, XRD, DSC, and in vitro drug release. Ex vivo permeability of the blend NFs was assessed using chicken pouch mucosa compared to VEN suspension followed by histopathological examination. Further, the cytotoxic effect was evaluated in three different cell lines using WST-1 assay. SEM morphologies refer to defect-free uniform NFs of PLA, PCL, and PLA/PCL mats. These fibers had a diameter ranging from 200–500 nm. The physico-thermal characterization of NFs depicted that the drug was successfully loaded and in an amorphous state in the PLA/PCL NFs. The cumulative release of NFs substantiated a bi-phasic profile with an initial burst release and a second sustained phase that reached 80% over 96 h following a non-Fickian diffusion mechanism. Ex vivo permeation emphasizes the major enhancement of the sustained drug release and the noticeable decrease in the permeability of the drug from NFs. Histopathology and cell toxicity studies demonstrated the preserved mucosal architecture and the preclinical safety. The developed PLA/PCL NFs can be promising drug carriers to introduce a step-change in improved psychiatric treatment healthcare.
Effect of D-π-A substituted Bromomethylcoumarin Derivatives on Optoelectronic Properties: Experimental and Computational Studies
Authors: Madar Mahesh , Pujar Malatesh S , H Shridhar A , Basanagouda Mahantesh M , Sidarai Ashok H 
Published: March 2022

Abstract
Here we report a simple method for the synthesis of a D−π−A substituted bromomethyl coumarin derivatives 1-(6-Bromo-benzo[1, 3]dioxol-5-yloxymethyl)-benzo[f]chromen-3-one (1BDYMBC) and 4-(6-Bromo-benzo[1, 3]dioxol-5-yloxymethyl)-benzo[h]chromen-2-one (4BDYMBC) via a one-pot chemical reaction. The FT-IR, 1H-NMR, and MS results confirmed the corresponding structure of the synthesized dyes. The substitution effect, on optoelectronic properties was verified using experimental and theoretical techniques. The absorption and fluorescence spectra of fluorescent dyes were recorded in different solvents of different polarity. Stoke's shift exhibits a redshift with an increase in solvent polarity for all molecules indicating a π−π∗ transition. The ground state dipole moments of all fluorescent dyes are estimated theoretically from ab initio computations (integral equation formalism of polarizable continuum model) and experimentally from the solvatochromic method and the results are compared. The excited state dipole moments are estimated using solvatochromic correlations equation and results show that the excited state dipole moments are higher than the ground state dipole moments which suggests that, all fluorescent dyes are more polar in the excited state. The HOMO-LUMO energy gaps computed from density functional theory and absorption threshold wavelengths are found to be in good agreement with each other and also support intramolecular charge transfer (ICT). The chemical hardness of the molecules is determined and the chemical stability is discussed. Further, using DFT molecular electrostatic potential (MESP) plots, the electrophilic site and nucleophilic site which are useful in photochemical reactions were identified. Finally, all the preliminary observations and results suggest that the fluorescent dyes can be considered as potential candidates for fluorescent probes and for the construction of dye sensitized solar cell in future.
Anxiety and Coping Strategies during the Covid-19 Pandemic among Students at a Multi- Campus University in Uganda
Authors: Ojilong Daniel , Kanyike Andrew Marvin , Nakawuki Ashley Winfred , Lutwama Dinah Maria , Nakanwagi Dorothy , Nekaka Rebecca 
Published: March 2022

Abstract
Background
Uganda has had the longest COVID-19-induced closures of schools world over of over 20 months, according to a recent UNICEF report, which has greatly affected learning and mental health of University students. This study assessed levels of anxiety, challenges and coping strategies of students at a university in Uganda during the COVID-19 pandemic lock down.
Methods
We conducted an online, descriptive, cross-sectional study between 26th June and 26th July 2021 using mixed quantitative and qualitative methods among students of Busitema University in Eastern Uganda. The survey assessed anxiety levels of students using General Anxiety Disorder 7 (GAD-7) scale, and its associations using the Chi-Square or Fischer’s exact test and multivariate logistic regression. We also explored the challenges and coping strategies employed by students through in-depth interviews.
Results
A total of 338 students participated, 213 (63%) were male with median age of 23 years (21–25), majority from Faculty of health sciences (n = 153, 45%). Overall, 179 (53%) of the students had anxiety which was mostly mild anxiety (n = 127, 38%). Students concerned about inadequate internet facilities to support online learning were twice more likely to have anxiety (aOR 2.0, 95% CI 1.1–3.7; p = 0.021). Among those with anxiety, avoidance coping strategies had higher scores with a median of 8 (3–12) compared to other strategies (p < 0.001). In-depth interviews revealed challenges with online learning, academic progress, and changes to daily routine and fear of contracting COVID-19 and getting vaccinated.
Conclusion
The largest number of students had anxiety especially those from faculty of health sciences and engineering of which most used avoidance strategies to cope up with the anxiety. This highlights areas where the university authorities should gear effort to design appropriate strategies to maintain mental health of students even after the pandemic.
Risk factors of recurrence and pregnancy in patients with borderline ovarian tumors: a retrospective study with 16-year follow-up
Authors: Lu Qi , Deng Yupeng , Zhang Zhiqiang , Liu Chongdong 
Published: March 2022

Abstract
Objective: This study analyzed the risk factors affecting recurrence in patients with borderline ovarian tumors （BOTs） after radical surgery and influencing recurrence and pregnancy in patients after fertility sparing surgery (FSS).Methods: This is a retrospective cohort study. Data was collected from clinical data of patients in the Beijing Chaoyang Hospital affiliated to Capital Medical University from January 2005 to November 2021. The clinicopathological and surgical variables were analyzed by univariate analyses and survival curves.Results: A total of 169 BOT patients were included in the study. The median age was 45 years. Median follow-up time was 81months. Among these patients, 21 patients relapsed. There were 60 patients with FSS, of the 16 patients attempting to conceive, 13 patients have successfully conceived spontaneously. In univariate analyses, FIGO stage, invasive implantation, and chemotherapy were risk factors for recurrence of BOTs. FIGO stage was the only one risk factor after multivariate analysis. Tumor size and tumor site were risk factors for recurrence of BOTs receiving FSS. We didn’t find any risk factor for pregnancy of BOTs receiving FSS.Conclusion: After univariate analysis and multivariate analysis, we found some risk factors for recurrence after radical surgery or FSS, but they didn’t affect the overall survival rate and pregnancy rate. Laparoscopy procedure is recommended and chemotherapy is not recommended for patients receiving FSS. We suggest that patients who preserve fertility should get pregnant as soon as possible and follow up closely.
Three-Dimensional SAR Imaging with Sparse Linear Array using Tensor Completion in Embedded Space
Authors: Zhang Siqian , Ding Ding , Zhao Chenxi , Zhao Lingjun 
Published: March 2022

Abstract
Due to the huge data storage and transmission pressure, sparse data collection strategy has provided opportunities and challenges for 3-D SAR imaging. However, sparse data brought by the sparse linear array will produce high-level side-lobes, as well as the aliasing and the false-alarm targets. Simultaneously, the vectorizing or matrixing of 3-D data makes high computational complexity and huge memory usage, which is not practicable in real applications. To deal with these problems, tensor completion (TC), as a convex optimization problem, is used to solve the 3-D sparse imaging problem efficiently. Unfortunately, the traditional TC methods are invalid to the incomplete tensor data with missing slices brought by sparse linear arrays. In this paper, a novel 3-D imaging algorithm using TC in embedded space is proposed to produce 3-D images with efficient side-lobes suppression. With the help of sparsity and low-rank property hidden in the 3-D radar signal, the incomplete tensor data is taken as the input and converted into a higher order incomplete Hankel tensor by multiway delay embedding transform (MDT). Then, the Tucker decomposition with incremental rank has been applied for completion. Subsequently, any traditional 3-D imaging methods can be employed to obtain excellent imaging performance for the completed tensor. The proposed method achieves high resolution and low-level sidelobes compared with the traditional TC-based methods. It is verified by several numerical simulations and multiple comparative studies on real data. Results clearly demonstrate that the proposed method can generate 3-D images with small reconstruction error even when the sparse sampling rate or signal to noise ratio is low, which confirms the validity and advantage of the proposed method.
Experimental and Numerical Behavior of Horizontally Loaded Piled Rafts with a Defective Pile
Authors: García Francisco Javier Alva , Cunha Renato Pinto da , de Albuquerque Paulo José Rocha , de Farias Márcio Muniz , Bernardes Heitor Cardoso 
Published: March 2022

Abstract
The present paper aims to investigate the effects of defective piles in horizontally loaded piled raft foundations. Close to real scale foundation models of defective and intact three-piled systems were submitted to horizontal load tests. The models used bored type piles drilled with 5 m in length and 0.25 m in diameter, connected to a concrete raft founded on a tropical soil profile at the University of Campinas research site. Based on the experimental data, a tridimensional finite element analysis was initially calibrated and consequently used to study the effects of the defective element at the pile load distribution and the horizontal subgrade forces at the pile shaft. The results show that the presence of a defective pile increases the raft tilting, which affects both vertical and horizontal load distributions among the raft and the piles, and among trailing and leading piles.
Ursolic acid-enriched kudingcha extractive enhances the antitumor activity of bacteria-mediated cancer immunotherapy
Authors: Xu Haixia , Piao Linghua , Liu Xiande , Jiang Shengnan 
Published: March 2022

Abstract
Background
Bacteria-mediated cancer immunotherapy (BCI) robustly stimulates the immune system and represses angiogenesis, but tumor recurrence and metastasis commonly occur after BCI. The natural product Ilex kudingcha C.J Tseng enriched with ursolic acid has anti-cancer activity and could potentially augment the therapeutic effects of BCI. The objective of the present study was to determine potential additive effects of these modalities.
Methods
We investigated the anti-cancer activity of KDCE (Kudingcha extractive) combined with S.t△ppGpp in the mice colon cancer models.
Results
In the present study, KDCE combined with S.t△ppGpp BCI improved antitumor therapeutic efficacy compared to S.t△ppGpp or KDCE alone. KDCE did not prolong bacterial tumor-colonizing time, but enhanced the antiangiogenic effect of S.t△ppGpp by downregulatingVEGFR2.
Conclusions
Combination therapy with S.t△ppGpp and KDCE is a potential cancer therapeutic strategy.
C-reactive protein/albumin ratio and modified Glasgow prognostic score are associated with prognosis and infiltration of Foxp3+ or CD3+ lymphocytes in colorectal liver metastasis
Authors: Kanno Hiroki , Hisaka Toru , Akiba Jun , Hashimoto Kazuaki , Fujita Fumihiko , Akagi Yoshito 
Published: March 2022

Abstract
Background: Inflammatory indices and tumor-infiltrating lymphocytes (TILs) have prognostic value in many cancers. This study aimed to assess the prognostic value of inflammatory indices and evaluate their correlation with survival and the presence of TILs in colorectal liver metastasis (CRLM).Methods: Medical records of 117 patients who underwent hepatectomy for CRLM were retrospectively reviewed. We calculated inflammatory indices such as neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, C-reactive protein/albumin ratio (CAR), and modified Glasgow prognostic score (mGPS) and evaluated their relationship with survival rates and immunohistochemical results of tumor-infiltrating CD3+, CD8+, and Foxp3+ lymphocytes. Results: Patients with low CAR values and low mGPS had significantly better overall survival in the log-rank test (p=0.0246 and p=0.0121, respectively). In multivariate analysis using the Cox proportional hazard model, CAR (hazard ratio [HR], 0.5717; 95% confidence interval [CI], 0.3288–0.9939; p=0.0475) and mGPS (HR, 0.4000; 95% CI, 0.1934–0.8270; p=0.0134) were independent prognostic factors. Additionally, Foxp3+ lymphocytes were more common in samples of patients with low CAR (p=0.0409), and the number of CD3+ TILs was significantly higher in patients with low mGPS (p=0.0152). Conclusions: CAR and mGPS are simple, inexpensive, and objective markers associated with survival of patients with CRLM. Moreover, they can predict the presence of Foxp3+ and CD3+ lymphocytes in the invasive margin of the tumor.