bluuebunny/crossref_metadata_2025 huggingface dataset:
Decreasing driveline infections in patients supported on ventricular assist devices: a care pathway approach
Authors: Seretny Julia , Pidborochynski Tara , Buchholz Holger , Freed Darren H , MacArthur Roderick , Dubyk Nicole , Cunliffe Laura , Zelaya Osiris , Conway Jennifer
Published: June 2022

Background

Driveline infections (DLIs) are a common adverse event in patients on ventricular assist devices (VADs) with incidence ranging from 14% to 59%. DLIs have an impact on patients and the healthcare system with efforts to prevent DLIs being essential. Prior to our intervention, our program had no standard driveline management presurgery and postsurgery. The purpose of this Quality Improvement (QI) initiative was to reduce DLIs and related admissions among patients with VAD within the first year post implant.

Methods

In anticipation of the QI project, we undertook a review of the programs’ current driveline management procedures and completed a survey with patients with VAD to identify current barriers to proper driveline management. Retrospective data were collected for a pre-QI intervention baseline comparison group, which included adult patients implanted with a durable VAD between 1 January 2017 and 31 July 2018. A three-pronged care pathway (CP) was initiated among patients implanted during August 2018 to July 2019. The CP included standardised intraoperative, postoperative and predischarge teaching initiatives and tracking. Using statistical process control methods, DLIs and readmissions in the first year post implant were compared between patients in the CP group and non-CP patients. P-charts were used to detect special cause variation.

Results

A higher proportion of CP group patients developed a DLI in the first year after implant (52% vs 32%). None developed a DLI during the index admission, which differed from the non-CP group and met criteria for special cause variation. There was a downward trend in cumulative DLI-related readmissions among CP group patients (55% vs 67%). There was no association between CP compliance and development of DLIs within 1 year post implant.

Conclusion

The CP did not lead to a reduction in the incidence of DLIs but there was a decrease in the proportion of patients with DLIs during their index admission and those readmitted for DLIs within 1 year post implant. This suggests that the CP played a role in decreasing the impact of DLIs in this patient population. However, given the short time period of follow-up longer follow-up will be required to look for sustained effects.
Resting heart rate and risk of left and right heart failure in 0.5 million Chinese adults
Authors: Agbor Valirie Ndip , Chen Yiping , Clarke Robert , Guo Yu , Pei Pei , Lv Jun , Yu Canqing , Li Liming , Chen Zhengming , Bennett Derrick
Published: June 2022

Objectives

To compare the shape and strength of the associations of resting heart rate (RHR) with incident heart failure (HF) and pulmonary heart disease (PHD) in Chinese adults.

Methods

The prospective China Kadoorie Biobank recruited >0.5 million adults from 10 geographically diverse regions (5 urban, 5 rural) of China during 2004–2008. After an 11-year follow-up, 6082 incident cases of HF and 5572 cases of PHD, were recorded among 491 785 participants with no prior history of heart disease or use of beta-blockers at baseline. Cox regression yielded HRs for each disease associated with usual RHR after adjustment for confounding factors.

Results

The mean (SD) baseline RHR was 79 (12) (men 78 (12); women 80 (11)) bpm, and these decreased with increasing age (by about 1 bpm per 10 years). Usual RHR showed J-shaped associations with HF and log-linear associations PHD. For HF, each 10 bpm higher usual RHR was associated with an adjusted HR of 1.25 (95% CI 1.17 to 1.34) for RHR>75 bpm. For PHD, each 10 bpm higher RHR was associated with HR of 1.74 (1.67–1.81) across the full range of usual RHR. For HF at RHR>75 bpm but not PHD, the HRs per 10 bpm higher RHR were approximately halved by further adjustment for diabetes and hypertension.

Conclusions

RHR was strongly positively associated with PHD throughout the range studied, but was only associated with HF at RHR>75 bpm, and the strength of the associations with HF were only one-third of those with PHD.
Modeling site index of selected poplar clones using airborne laser scanning data
Authors: Tompalski Piotr , Coops Nicholas C. , Achim Alexis , Cosgrove Cameron F. , Lapointe Eric , Brochu-Marier Felix
Published: June 2022

Accurate growth and yield projection for plantations is critical for evaluating management decisions and anticipating future yields. Development of site index (SI) models is often costly and can be problematic when new, short-rotation species are introduced, for example, hybrid poplar plantations, which are increasingly common due to their very fast growth and high productivity. Airborne laser scanning (ALS) allows accurate measurement of tree and stand height and is increasingly being used to develop top height models. In this paper, we demonstrate an approach to develop SI models from ALS data across hybrid poplar plantations in Quebec, Canada. We exploit a single time step ALS acquisition to generate top height estimates at 10 m grid level. Using existing information on planting date and management practices, we developed top height models for unique classes of fertilization treatment and clone. The generic models for unfertilized and fertilized stands showed good fit statistics, with R2 of 0.71 and 0.82, respectively. Clone-specific models showed similar goodness of fit, with the best model resulting in an R2 of 0.89 and relative root mean square error (RMSE) of 16.6%. Analysis of variance (ANOVA) results showed that clone, fertilization status, and the interaction term between clone and fertilization were significant. Our results confirm the development of top height models from a chronosequence of ALS data was successful and offers a new approach to derive SI models in single-species plantation sites.
Insights into Chinook salmon (Oncorhynchus tshawytscha) movement ecology in the terminal reaches of the upper Yukon River during the spawning migration
Authors: Twardek W.M. , Knight K.L. , Reid C.H. , Lennox R.J. , Cooke S.J. , Lapointe N.W.R.
Published: June 2022

Chinook salmon ( Oncorhynchus tshawytscha (Walbaum, 1792)) from the upper Yukon River are highly unique, with some populations migrating nearly 3000 km to spawning habitat near the northern range limit for the species. We conducted a 4-year study to understand the behaviour of Chinook salmon in the terminal reaches of their migration by tagging salmon with acoustic and radio transmitters in Whitehorse, Yukon, Canada, ∼2800 km from the ocean. Various migration characteristics were quantified for Chinook salmon, including en route mortality, diel behaviour, migration rates, and homing patterns, and associations with salmon origin (wild vs. hatchery), sex, size, and migration timing were explored. Salmon had high survival to spawning grounds (>98%) and migrated throughout all hours of the day, with higher proportions of nighttime movements in a smaller spawning tributary than in the Yukon River mainstem. Migration rates were faster for larger salmon as well as late-arriving salmon, which was likely necessary to ensure they had sufficient time and suitable conditions on spawning grounds to reproduce. Non-direct homing movements (e.g., tributary exploration) were more common in male salmon and considerably increased migration distance through the study area. Findings from this study may help to inform the complex international and inter-nation management of these increasingly threatened Chinook salmon populations.
Swampland criteria and reheating predictions in scalar–tensor inflation
Authors: Mohammadi Abolhassan , Golanbari Tayeb , Enayati Jamil , Jalalzadeh Shahram , Nasri Salah , Saaidi Khaled
Published: June 2022

The slow-roll inflation scenario is studied in the frame of the scalar–tensor theory of gravity, where the scalar field has a nonminimal coupling to the geometric part. After deriving the main dynamical and observable parameter, the consistency of the model with data is considered and we could determine the constants of the model. Then, using the result, the swampland criteria are studied and it is revealed that they are perfectly satisfied. Finally, reheating phase is considered and it is found that the reheating phase lasts for a few e-fold of expansion, and the universe warms up to a high temperature.
DSIT: A Dynamic Lightweight Cryptography Algorithm for Securing Image in IoT Communication
Authors: Lata Navdeep , Kumar Raman
Published: June 2022

One of the most significant challenges appears to be securing the Internet of Things (IoT) communication network. As a corollary, information security has become the basis for establishing trustworthiness in IoT network communication. Cryptography is one of the ways for securing information in this case. However, the majority of current approaches are static, making them subject to security threats. As a consequence, a new concept, dynamic encryption, is growing rapidly in IoT communication. In this paper, a dynamic encryption algorithm (DSIT) has been proposed to secure IoT communication. This algorithm is based on Feistel and Substitution–Permutation Network. DSIT is a block cipher that takes the 64-bit block of plaintext, 64-bit secret key, and a secret dynamic box (D-box) as input. It produces a 64-bit ciphertext by performing eight rounds of the DSIT algorithm. For each round, the key and D-box are updated. This dynamic effect provides high security to a dynamic IoT network. The proposed algorithm has been executed in IoT environment using Raspberry Pi 3 Model B[Formula: see text] and 50% average Avalanche effect has been achieved. The proposed algorithm efficiently encrypts the image data to secure the communication and high resistant to cryptanalysis attacks.
EVOLUTION OF BIOMEDICAL INNOVATION QUANTIFIED VIA BILLIONS OF DISTINCT ARTICLE-LEVEL MeSH KEYWORD COMBINATIONS
Authors: PETERSEN ALEXANDER M.
Published: June 2022

To what degree has the vast space of higher-order knowledge combinations been explored and how has it evolved over time? To address these questions, we first develop a systematic approach to measuring combinatorial innovation in the biomedical sciences based upon the comprehensive ontology of Medical Subject Headings (MeSH) developed and maintained by the US National Library of Medicine. As such, this approach leverages an expert-defined knowledge ontology that features both breadth (27,875 MeSH analyzed across 25 million articles indexed by PubMed that were published from 1902 onwards) and depth (we differentiate between Major and Minor MeSH terms to identify differences in the knowledge network representation constructed from primary research topics only). With this level of uniform resolution, we differentiate between three different modes of innovation contributing to the combinatorial knowledge network: (i) conceptual innovation associated with the emergence of new concepts and entities (measured as the entry of new MeSH) and (ii) recombinant innovation, associated with the emergence of new combinations, which itself consists of two types: peripheral (i.e. combinations involving new knowledge) and core (combinations comprised of pre-existing knowledge only). Another relevant question we seek to address is whether examining triplet and quartet combinations, in addition to the more traditional dyadic or pairwise combinations, provides evidence of any new phenomena associated with higher-order combinations. Analysis of the size, growth, and coverage of combinatorial innovation yield results that are largely independent of the combination order, with some subtle caveats identified at higher order (i.e. beyond the common dyadic or pairwise representation of combinations). Our main results are two-fold: (a) despite the persistent addition of new MeSH terms, the network is densifying over time meaning that scholars are increasingly exploringand realizing the vast space of all knowledge combinations and (b) conceptual innovation is increasingly concentrated within single research articles, a harbinger of the recent paradigm shift towards convergence science.
Design of a 6-DoF Parallel Robotic Platform for MRI Applications
Authors: Musa Mishek , Sengupta Saikat , Chen Yue
Published: June 2022

In this work, the design, analysis, and characterization of a parallel robotic motion generation platform with 6-degrees of freedom (DoF) for magnetic resonance imaging (MRI) applications are presented. The motivation for the development of this robot is the need for a robotic platform able to produce accurate 6-DoF motion inside the MRI bore to serve as the ground truth for motion modeling; other applications include manipulation of interventional tools such as biopsy and ablation needles and ultrasound probes for therapy and neuromodulation under MRI guidance. The robot is comprised of six pneumatic cylinder actuators controlled via a robust sliding mode controller. Tracking experiments of the pneumatic actuator indicates that the system is able to achieve an average error of 0.69 [Formula: see text] 0.14[Formula: see text]mm and 0.67 [Formula: see text] 0.40[Formula: see text]mm for step signal tracking and sinusoidal signal tracking, respectively. To demonstrate the feasibility and potential of using the proposed robot for minimally invasive procedures, a phantom experiment was performed in the benchtop environment, which showed a mean positional error of 1.20 [Formula: see text] 0.43[Formula: see text]mm and a mean orientational error of 1.09 [Formula: see text], respectively. Experiments conducted in a 3T whole body human MRI scanner indicate that the robot is MRI compatible and capable of achieving positional error of 1.68 [Formula: see text] 0.31[Formula: see text]mm and orientational error of 1.51 [Formula: see text] 0.32∘ inside the scanner, respectively. This study demonstrates the potential of this device to enable accurate 6-DoF motions in the MRI environment.
Laser Range Scanners for Enabling Zero-overhead WiFi-based Indoor Localization System
Authors: Rizk Hamada , Yamaguchi Hirozumi , Youssef Moustafa , Higashino Teruo
Published: June 2022

Robust and accurate indoor localization has been the goal of several research efforts over the past decade. Toward achieving this goal, WiFi fingerprinting-based indoor localization systems have been proposed. However, fingerprinting involves significant effort—especially when done at high density—and needs to be repeated with any change in the deployment area. While a number of recent systems have been introduced to reduce the calibration effort, these still trade overhead with accuracy. This article presents
LiPhi++
, an accurate system for enabling fingerprinting-based indoor localization systems without the associated data collection overhead. This is achieved by leveraging the sensing capability of transportable laser range scanners to automatically label WiFi scans, which can subsequently be used to build (and maintain) a fingerprint database. As part of its design,
LiPhi++
leverages this database to train a deep long short-term memory network utilizing the signal strength history from the detected access points.
LiPhi++
also has provisions for handling practical deployment issues, including the noisy wireless environment, heterogeneous devices, among others. Evaluation of
LiPhi++
using Android phones in two realistic testbeds shows that it can match the performance of manual fingerprinting techniques under the same deployment conditions without the overhead associated with the traditional fingerprinting process. In addition,
LiPhi++
improves upon the median localization accuracy obtained from crowdsourcing-based and fingerprinting-based systems by 284% and 418%, respectively, when tested with data collected a few months later.
DFI: The Data Flow Interface for High-Speed Networks
Authors: Thostrup Lasse , Skrzypczak Jan , Jasny Matthias , Ziegler Tobias , Binnig Carsten
Published: June 2022

In this paper, we propose the Data Flow Interface (DFI) as a way to make it easier for data processing systems to exploit high-speed networks without the need to deal with the complexity of RDMA. By lifting the level of abstraction, DFI factors out much of the complexity of network communication and makes it easier for developers to declaratively express how data should be efficiently routed to accomplish a given distributed data processing task. As we show in our experiments, DFI is able to support a wide variety of data-centric applications with high performance at a low complexity for the applications.
No PANE, No Gain
Authors: Yang Renchi , Shi Jieming , Xiao Xiaokui , Yang Yin , Bhowmick Sourav S. , Liu Juncheng
Published: June 2022

Given a graph G where each node is associated with a set of attributes, attributed network embedding (ANE) maps each node v 2 G to a compact vector Xv, which can be used in downstream machine learning tasks in a variety of applications. Existing ANE solutions do not scale to massive graphs due to prohibitive computation costs or generation of low-quality embeddings. This paper proposes PANE, an effective and scalable approach to ANE computation for massive graphs in a single server that achieves state-of-the-art result quality on multiple benchmark datasets for two common prediction tasks: link prediction and node classification. Under the hood, PANE takes inspiration from well-established data management techniques to scale up ANE in a single server. Specifically, it exploits a carefully formulated problem based on a novel random walk model, a highly efficient solver, and non-trivial parallelization by utilizing modern multi-core CPUs. Extensive experiments demonstrate that PANE consistently outperforms all existing methods in terms of result quality, while being orders of magnitude faster.
Effectiveness and Safety of Low Dose of Tenofovir Disoproxil Fumarate in Malagasy Patients with Chronic Hepatitis B
Authors: Razafindrazoto Chantelli Iamblaudiot , Rabenjanahary Tovo Harimanana , Rakotozafindrabe Andry Lalaina Rinà , Rakotondrasoa Sedera Radoniaina , Randriamifidy Nitah Harivony , Rasolonjatovo Anjaramalala Sitraka , Razafimahefa Soloniaina Hélio , Ramanampamonjy Rado Manitrala
Published: June 2022

Background. Accessibility of full dose daily of tenofovir disoproxil fumarate (TDF) is limited in Madagascar with an estimated cost well above the purchasing power of Malagasy population. Objective. The study is aimed at evaluating the efficacy and safety of low‐dose tenofovir for the treatment of chronic hepatitis B (CHB). Methods. This prospective cohort study from January 2018 to December 2020 was conducted in the Department of Hepato‐Gastroenterology, University Hospital Joseph Raseta Befelatanana, Antananarivo, Madagascar. The patients enrolled in the study received low dose of TDF 900 mg/week (300 mg daily, three days per week). Results. A total of 45 patients (male/female: 31/14) were included. The mean age was 45.1 ± 11.5 years. Fifteen patients were nucleos(t)ide (NA)‐naïve, and 30 patients had prior NA therapy (NA‐experienced). Thirty patients were HBeAg positive. A complete virological response (CVR) was achieved in 36/45 patients (80%) at 3 months, 41/45 (91.1%) at 6 months, and 43/45 (95.6%) at 12 months. High viral load at baseline was negative predictive factor of CVR at 3 months (HR: 0.14; 95% CI: 0.022–0.92; p: 0.041). There was no significant difference in response between HBeAg‐positive and HBeAg‐negative patients, NA‐naïve and NA‐experienced patients, and cirrhotic and noncirrhotic patients. Low dose of tenofovir was well tolerated. Ten patients (22.22%) had mild side effects. Mild renal failure was observed in 3 patients (6.7%) during follow‐up. Conclusion. Low dose of tenofovir is effective, safe, and well tolerated in a Malagasy population sample. These results still require verification in a large population.
Single-Cell Analysis Reveals the Role of the Neuropeptide Receptor FPR2 in Monocytes in Kawasaki Disease: A Bioinformatic Study
Authors: Wang Tengyang , Liu Guanghua , Guo Xiaofeng , Ji Wei
Published: June 2022

Exploring the role of neuropeptides in the communication between monocyte subtypes facilitates an investigation of the pathogenesis of Kawasaki disease (KD). We investigated the patterns of interaction between neuropeptide-associated ligands and receptors in monocyte subpopulations in KD patients. Single-cell analysis was employed for the identification of cell subpopulations in KD patients, and monocytes were classified into 3 subpopulations: classical monocytes (CMs), intermediate monocytes (IMs), and nonclassical monocytes (NCMs). Cell-cell communication and differential analyses were used to identify ligand-receptor interactions in monocytes. Five neuropeptide-related genes (SORL1, TNF, SORT1, FPR2, and ANXA1) were involved in cell-cell interactions, wherein FPR2, a neuropeptide receptor, was significantly highly expressed in KD. Weighted gene coexpression network analysis revealed a significant correlation between the yellow module and FPR2 (

p
<
0.001

,

CC
=
0.43

). Using the genes in the yellow module, we constructed a PPI network to assess the possible functions of the FPR2-associated gene network. Gene set enrichment analysis showed that increased FPR2 levels may be involved in immune system regulation. FPR2 in CMs mediates the control of inflammation in KD. The findings of this study may provide a novel target for the clinical treatment of KD.
Research on Marketing Strategy of Railway Passenger Travel Behaviour Analysis in Competitive Section
Authors: Hao Xiaopei , Zhu Jiansheng , Shan Xinhua , Li Wen
Published: June 2022

The deep mining of passengers’ travel data can identify competitive segments and gain insights into passengers’ characteristics and differentiated demands. This can not only effectively support precise marketing strategy adjustment of railway transport but also improve its competitiveness in the passenger transportation market. In this paper, hidden railway travel behaviour is introduced and integrated with railway travel behaviour to create a complete passenger travel chain, based on existing distance-based competitive segment recognition methods. The loyalty index values of passengers are calculated using this travel chain to identify competitive segments. Furthermore, passenger classification and grouping currently ignore social relationships as well as personal travel characteristics. Therefore, a novel passenger grouping method is proposed; it integrates individuals’ travel characteristics and social relations. Individual travel labels are created for travellers based on their travel data. Social relation topologies, such as ticketing relation, the relation of travelling together, and benefit relation via point redemption, can be extracted using these labels. Social relation traits can be retrieved using graph attention networks and multigraph fusion. Finally, travellers are categorised based on their individual travel characteristics. As an example, and a case study, the grouping of Guangzhou–Shanghai passengers in 2020 is taken which shows that the suggested method has the potential to improve both the precision and the feasibility of grouping railway passengers. As a result, new ideas for passenger grouping in railway marketing might be offered.
Big Transfer Learning for Fine Art Classification
Authors: Zhao Wentao , Jiang Wei , Qiu Xinguo
Published: June 2022

Automatic classification and retrieval of fine art collections have received much attention in recent years. In this article, we explore the applicability of convolutional neural networks (CNNs) for art-related image classification tasks. To examine how hyperparameters affect model performance, we use different hyperparameters in our experiments and find that a higher resolution and appropriate training steps with mix-up can improve model performance. To determine how transfer learning affects the final results, we systematically compare the efforts of five weight initializations of the models for different tasks. We show that fine-tuning networks pretrained on a larger dataset have better generalizability. This phenomenon shows the a priori knowledge that models learn in the real world also applies to the art world, and we call this method as big transfer learning (BiT). Through extensive experiments on fine art classification, we demonstrate that the proposed transfer learning approach outperforms the previous work by a large margin and achieves state-of-the-art performance in the art field. Furthermore, to show how computers capture features in paintings to make classifications, we visualized the results of different classification tasks to help us understand the operation mechanism of the models. Additionally, we use our models to retrieve paintings by analyzing different image similarity aspects. The results show that models can be employed to retrieve paintings even if they are computer-generated.
Cardioprotective Potential of Aqueous Extract of Fumaria indica on Isoproterenol-Induced Myocardial Infarction in SD Rats
Authors: Sajid Aimen , Ahmad Taseer , Ikram Muhammad , Khan Taous , Shah Abdul Jabbar , Mahnashi Mater H. , Alhasaniah Abdulaziz Hassan , Al Awadh Ahmed Abdullah , Almazni Ibrahim Abdullah , Alshahrani Mohammed Merae
Published: June 2022

Ischemic heart disease (IHD) treatments and preventions by using plant extract and its phytochemical constituents have achieved considerable attention globally due to its cardioprotective effects. This study is aimed at investigating the cardioprotective and vascular effects of Fumaria indica (F. indica) crude extract on isoproterenol- (ISO-) induced myocardial infarction (MI) in Sprague-Dawley (SD) rats. Rats treated with isoproterenol (85 mg/kg, s.c), administered. Twice at an interval of 24 h showed a significant ST-segment elevation in ECG, edema, and necrosis in histopathology and also in troponin I (cTnI), creatine phosphokinase (CPK), lactate dehydrogenase (LDH), and aspartate aminotransferase (AST). Pretreatment with F. indica (10, 30, and 100 mg/kg, p.o) for 21 days significantly reversed the effects of isoproterenol-induced ischemic changes in the ECG, levels of cTnI, CPK, LDH, and AST, and histopathological changes. In isolated rat atrial strips, F. indica induced negative chronotropic and inotropic effects which were not affected by pretreatment with atropine, excluding role of cardiac muscarinic receptors. Cumulative addition of the extract induced a vasorelaxant effect on phenylephrine-evoked contractions in isolated rat aortic rings, which remained unchanged when challenged with L-NAME, excluding role of endothelial NO. However, extract of F. indica concentration dependently reversed contractions evoked with high K+, indicating calcium entry blocking effect. In conclusion, the F. indica extract is a cardioprotective remedy that ameliorates the isoproterenol-induced cardiotoxic effects and reverses cardiac ischemia, and the calcium antagonistic effect might be of useful in the treatment of MI.
Research on the Construction of University Campus Economic Management System Based on the Concept of Big Data
Authors: Fang Yan , Wang Qiao
Published: June 2022

At present, in order to adapt to the development of the era of big data, more and more industries use the concept of big data, and the economic and financial management system is no exception. In the context of the concept of big data, the campus economy has also ushered in new opportunities and challenges. Combined with the basic knowledge of big data, this paper makes a systematic research on industrial economic information analysis, which will contribute to the application practice of industrial big data. Using the value of big data will promote revolutionary changes in the work of the school’s economic management department. Taking this as the starting point, this paper systematically analyzes the analysis methods of campus economic information under the background of big data and its role in macro decision-making.
Construction of Remote Sensing Model of Fresh Corn Biomass Based on Neural Network
Authors: Chen Jianjian , Zhang Hui , Bian Yunlong , Li Xiangnan , Lv Guihua
Published: June 2022

Corn has a high yield and is widely used. Therefore, developing corn production and accurately estimating corn biomass yield are of great significance to improving people’s lives, developing rural economy and climate issues. In this paper, a 3-layer BP neural network model is constructed by using the LM algorithm as the training algorithm of the corn biomass BP network model. From the three aspects of elevation, slope, and aspect, combined with the BP neural network model of corn biomass, the spatial distribution of corn biomass in the study area is analyzed. The results showed that the average biomass per unit area of maize increased with the increase in altitude below 1000 m. There are relatively more human activities in low altitude areas, which are more active in forestry production. The best planting altitude of corn is 0 ∼ 1000 m. When the altitude is higher than 1000 m, the corn biomass gradually decreases. In terms of slope, if the slope is lower than 15°, the biomass of maize increases with the increase in slope. If the slope is lower than 15°, the biomass of maize decreases gradually with the increase in slope. The biomass of maize on sunny slope was higher than that on shady slope.
IL-21/IL-21R Regulates the Neutrophil-Mediated Pathologic Immune Response during Chlamydial Respiratory Infection
Authors: Zeng Jiajia , Xu Yueyue , Tan Lu , Zha Xiaoyu , Yang Shuaini , Zhang Hong , Tuo Yuqing , Sun Ruoyuan , Niu Wenhao , Pang Gaoju , Sun Lida , Bai Hong
Published: June 2022

IL-21/IL-21R was documented to participate in the regulation of multiple infection and inflammation. During Chlamydia muridarum (C. muridarum) respiratory infection, our previous study had revealed that the absence of this signal induced enhanced resistance to infection with higher protective Th1/Th17 immune responses. Here, we use the murine model of C. muridarum respiratory infection and IL-21R deficient mice to further identify a novel role of IL-21/IL-21R in neutrophilic inflammation. Resistant IL-21R-/- mice showed impaired neutrophil recruitment to the site of infection. In the absence of IL-21/IL-21R, pulmonary neutrophils also exhibited reduced activation status, including lower CD64 expression, MPO activity, and neutrophil-produced protein production. These results correlated well with the decrease of neutrophil-related chemokines (KC and MIP-2), inflammatory cytokines (IL-6, IL-1β, and TNF-α), and TLR/MyD88 pathway mediators (TLR2, TLR4, and MyD88) in infected lungs of IL-21R-/- mice than normal mice. Complementarily, decreased pulmonary neutrophil infiltration, activity, and levels of neutrophilic chemotactic factors and TLR/MyD88 signal in infected lungs can be corrected by rIL-21 administration. These results revealed that IL-21/IL-21R may aggravate the neutrophil inflammation through regulating TLR/MyD88 signal pathway during chlamydial respiratory infection.
Integrating In Silico and In Vitro Approaches to Screen the Antidiabetic Properties from Tabernaemontana divaricata (Jasmine) Flowers
Authors: Muzammil Saima , Andleeb Rahat , Hayat Sumreen , Ijaz Muhammad Umar , Ashraf Asma , Zafar Nimrah , Naz Shabana , Shaheen Mubashera
Published: June 2022

The purpose of this study was to assess different in vitro biological activities such as phytochemical constituents, enzymatic antioxidant status, cytotoxicity through hemolytic activity, and antidiabetic potential of plant methanolic extract through glucose uptake by yeast cells. Further, using in silico approach by the SwissADME technique the drug-likeness rules for bioactive components were characterized, while potential interactions were identified via molecular docking of a ligand with target proteins by GOLD 5.3.0. The results showed that T. divaricata was rich in TPC and TFC, i.e., 62.32 ± 4.02 and 24.53 ± 0.61, respectively, and the cytotoxic potential was 10% towards human RBCs, while protein estimation revealed the presence of protein in the extract, which was 22.82 ± 4.6. DPPH assay in comparison with ascorbic acid and several enzymatic assays, such as CAT, SOD, and POD, showed maximum antioxidant potential, i.e.,15.9 ± 2.33%, 65.57 ± 13.4%, 3.02 ± 3.4, 15.87 ± 0.5, and 0.74 ± 0.2, respectively. Glucose uptake by yeast cells, i.e., α-amylase and α-glucosidase, showed a maximum antidiabetic potential such as 75.11 ± 1.44%, 41.81 ± 3.75%, and 35.9 ± 1.24%, respectively. Our results indicate that the methanolic extract of T. divaricata has antioxidant potential and inhibits α-amylase and α-glucosidase activity and possesses maximum antidiabetic potential. The results provide scientific proof that the medicinal plant being studied is a powerful source of natural antioxidant, antidiabetic, and medicinally significant substances. In silico study, using a molecular docking, unveiled that two compounds showed good interactions with 5kzw protein with considerable binding affinities and fulfilled docking parameters. It may conclude that T. divaricata is an important vegetable with a potent source of natural antioxidants and antidiabetic activity justifying its traditional use in green therapeutics.
Negative Impact of Vitamin D Deficiency at Diagnosis on Breast Cancer Survival: A Prospective Cohort Study
Authors: Almeida-Filho Benedito Souza , Omodei Michelle Sako , Buttros Daniel A. B. , Carvalho-Pessoa Eduardo , Carvalho-Pessoa Carla Priscila , De Luca Vespoli Heloisa , Nahas Eliana Aguiar Petri
Published: June 2022

Objective. We prospectively evaluated the association between vitamin D concentration at diagnosis and overall survival (OS), disease-free survival (DFS), and cancer-specific survival (CSS) in postmenopausal women treated for breast cancer. Methods. This study included 192 patients newly diagnosed with invasive breast cancer, aged ≥45 years, and serum 25-hydroxy vitamin D (25 (OH)D) concentration assessment at diagnosis. Patients were classified into groups according to 25 (OH)D concentrations: sufficient (≥30 ng/mL), insufficient (between 20 and 29 ng/mL), and deficient (<20 ng/mL). The primary outcome was OS, and the secondary outcomes were DFS and CSS. The Kaplan–Meier curve and Cox regression model were used to assess the association between 25 (OH)D concentrations and survival rates. Differences in survival were evaluated by hazard ratios (HRs). Results. The mean age was 61.3 ± 9.6 years, 25 (OH)D concentration was 26.9 ± 7.5 ng/mL (range 12.0–59.2 ng/mL), and the follow-up period was between 54 and 78 months. Sufficient 25 (OH)D was detected in 33.9% of patients, insufficient in 47.9%, and deficient in 18.2%. A total of 51 patients (26.6%) died during the study period, with a mean OS time of 54.4 ± 20.2 months (range 9–78 months). Patients with 25 (OH)D deficiency and insufficiency at diagnosis had a significantly lower OS, DFS, and CSS compared with patients with sufficient values (

p
<
0
.001

). After adjustment for clinical and tumoral prognostic factors, patients with 25 (OH)D concentrations considered deficient at diagnosis had a significantly higher risk of global death (HR, 4.65; 95% CI, 1.65–13.12), higher risk of disease recurrence (HR, 6.87; 95% CI, 2.35–21.18), and higher risk of death from the disease (HR, 5.91; 95% CI, 1.98–17.60) than the group with sufficient 25(OH)D concentrations. Conclusion. In postmenopausal women treated for breast cancer, vitamin D deficiency and insufficiency at diagnosis were independently associated with lower OS, DFS, and CSS compared with patients with sufficient 25(OH)D concentrations.
Experimental Study of Potential CD8+ Trivalent Synthetic Peptides for Liver Cancer Vaccine Development Using Sprague Dawley Rat Models
Authors: Zafar Sidra , Bai Baogang , Guo Jinlei , Muhammad Syed Aun , Naqvi Syeda Tahira Qousain , Shabbir Muhammad Nauman , Imran Imran , Shaikh Rehan Sadiq , Ali Amjad
Published: June 2022

Background. Liver cancer (LC) is the most devastating disease affecting a large set of populations in the world. The mortality due to LC is escalating, indicating the lack of effective therapeutic options. Immunotherapeutic agents may play an important role against cancer cells. As immune cells, especially T lymphocytes, which are part of cancer immunology, the design of vaccine candidates for cytotoxic T lymphocytes may be an effective strategy for curing liver cancer. Results. In our study, based on an immunoinformatics approach, we predicted potential T cell epitopes of MHC class I molecules using integrated steps of data retrieval, screening of antigenic proteins, functional analysis, peptide synthesis, and experimental in vivo investigations. We predicted the binding affinity of epitopes LLECADDRADLAKY, VSEHRIQDKDGLFY, and EYILSLEELVNGMY of LC membrane‐bounded extracellular proteins including butyrophilin‐like protein‐2 (BTNL2), glypican‐3 (GPC3), and serum albumin (ALB), respectively, with MHC class I molecules (allele: HLA‐A∗01:01). These T cell epitopes rely on the level of their binding energy and antigenic properties. We designed and constructed a trivalent immunogenic model by conjugating these epitopes with linkers to activate cytotoxic T cells. For validation, the nonspecific hematological assays showed a significant rise in the count of white blood cells (5 × 109/l), lymphocytes (13 × 109/l), and granulocytes (5 × 109/l) compared to the control after administration of trivalent peptides. Specific immunoassays including granzyme B and IgG ELISA exhibited the significant concentration of these effector molecules in blood serum, indicating the activity of cytotoxic T cells. Granzyme concentration increased to 1050 pg/ml at the second booster dose compared to the control (95 pg/ml), while the concentration of IgG raised to 6 g/l compared to the control (2 g/l). Conclusion. We concluded that a potential therapeutic trivalent vaccine can activate and modulate the immune system to cure liver cancer on the basis of significant outcomes of specific and nonspecific assays.
Dexmedetomidine Reduces Incidences of Ventricular Arrhythmias in Adult Patients: A Meta-Analysis
Authors: Zhong Qiaonan , Kumar Ashish , Deshmukh Abhishek , Bennett Courtney
Published: June 2022

Purpose. To assess the antiarrhythmic properties of dexmedetomidine in patients in the intensive care unit. Methods. A literature review was conducted with Ovid MEDLINE (R), Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Embase, and Scopus. Study Selection. Randomized controlled trials were included, examining the incidence of ventricular arrhythmias, ventricular tachycardia, or ventricular fibrillation with dexmedetomidine compared to placebo or an alternative sedative agent. For each publication that met the selection criteria, the patient demographics, incidence of arrhythmias, mortality, and adverse events were collected. Data extraction was carried out by two authors independently. Results. We identified 6 out of 126 studies that met the selection criteria for our meta-analysis, all of which focused on the perioperative cardiac surgery period. Patients receiving dexmedetomidine demonstrated a significant reduction of the overall incidence of ventricular arrhythmias (RR 0.35, 95% CI 0.16, 0.76). In particular, dexmedetomidine significantly decreased the risk of ventricular tachycardia compared with control (RR 0.25, 95% CI 0.08, 0.80, I2 0%). Regarding adverse events, dexmedetomidine significantly increased the frequency of bradycardia (RR 2.78 95% CI 2.00, 3.87). However, there was no significant difference in mortality (RR 0.59 95% CI 0.12, 3.02). Conclusion. From this meta-analysis, we report a decreased incidence of ventricular tachycardia with dexmedetomidine in critically ill patients. This result favors the use of dexmedetomidine for its antiarrhythmic properties.
Heat Transfer Analysis on Carboxymethyl Cellulose Water‐Based Cross Hybrid Nanofluid Flow with Entropy Generation
Authors: Ali F. , Loganathan K. , Eswaramoorthi S. , Prabu K. , Zaib A. , Chaudhary Dinesh Kumar
Published: June 2022

The physical phenomena of convective flow of Cross fluid containing carboxymethyl cellulose water over a stretching sheet with convective heating were studied. Cross nanofluid containing Al2O3, Cu nanoparticles, and based fluid of CMC water is used. Entropy generation minimization is examined in the current analysis. The system of PDEs is altered into a set of ODEs through suitable conversion. Further, these equations are computed numerically through the MATLAB BVP4c technique. The behavior of governing parameters on the velocity, temperature, entropy generation, and Bejan number is plotted and reported via graphs. It is found that the larger value of unsteady variable reduced the velocity, thermal layer, and entropy production. Surface drag frication of the Al2O3 and Cu and Al2O3 + Cu is enhanced with the more presence of unsteady parameter. Comparison of current results in a limiting case is obtained with earlier analysis and found an optimum agreement.
Baptism of Fire: Modeling the Effects of Prescribed Fire on Lyme Disease
Authors: Guo Emily , Agusto Folashade B.
Published: June 2022

Recently, tick-borne illnesses have been trending upward and are an increasing source of risk to people’s health in the United States. This is due to range expansion in tick habitats as a result of climate change. Thus, it is imperative to find a practical and cost-efficient way of managing tick populations. Prescribed burns are a common form of land management that can be cost-efficient if properly managed and can be applied across large amounts of land. In this study, we present a compartmental model for ticks carrying Lyme disease and uniquely incorporate the effects of prescribed fire using an impulsive system to investigate the effects of prescribed fire intensity (high and low) and the duration between burns. Our study found that fire intensity has a larger impact in reducing tick population than the frequency between burns. Furthermore, burning at high intensity is preferable to burning at low intensity whenever possible, although high-intensity burns may be unrealistic due to environmental factors. Annual burns resulted in the most significant reduction in infectious nymphs, which are the primary carriers of Lyme disease.
Positive Invertibility of Matrices and Exponential Stability of Linear Stochastic Systems with Delay
Authors: Kadiev Ramazan , Ponosov Arcady
Published: June 2022

The work addresses the exponential moment stability of solutions of large systems of linear differential Itô equations with variable delays by means of a modified regularization method, which can be viewed as an alternative to the technique based on Lyapunov or Lyapunov-like functionals. The regularization method utilizes the parallelism between Lyapunov stability and input-to-state stability, which is well established in the deterministic case, but less known for stochastic differential equations. In its practical implementation, the method is based on seeking an auxiliary equation, which is used to regularize the equation to be studied. In the final step, estimation of the norm of an integral operator or verification of the property of positivity of solutions is performed. In the latter case, one applies the theory of positive invertible matrices. This report contains a systematic presentation of how the regularization method can be applied to stability analysis of linear stochastic delay equations with random coefficients and random initial conditions. Several stability results in terms of positive invertibility of certain matrices constructed for general stochastic systems with delay are obtained. A number of verifiable sufficient conditions for the exponential moment stability of solutions in terms of the coefficients for specific classes of Itô equations are offered as well.
Continued Fraction Interpolation of Preserving Horizontal Asymptote
Authors: Zhao Yushan , Wu Kaiwen , Tan Jieqing
Published: June 2022

The classical Thiele‐type continued fraction interpolation is an important method of rational interpolation. However, the rational interpolation based on the classical Thiele‐type continued fractions cannot maintain the horizontal asymptote when the interpolated function is of a horizontal asymptote. By means of the relationship between the leading coefficients of the numerator and the denominator and the reciprocal differences of the continued fraction interpolation, a novel algorithm for the continued fraction interpolation is constructed in an effort to preserve the horizontal asymptote while approximating the given function with a horizontal asymptote. The uniqueness of the interpolation problem is proved, an error estimation is given, and numerical examples are provided to verify the effectiveness of the presented algorithm.
An Optimization Method for Enterprise Resource Integration Based on Improved Particle Swarm Optimization
Authors: Guo Aifang , Zhu Lina , Chang Lingjie
Published: June 2022

An enterprise’s development and growth are inextricably linked to rational and efficient resource integration and optimization. This study focuses on the reorganization and integration of industrial elements inside the firm from the standpoint of resource integration. The ideal resource integration strategy is investigated by integrating the industrial parts of a certain enterprise in order to increase the efficiency of project completion and lower enterprise expenses. The enterprise’s internal material and human resources are limited, but it is frequently necessary to execute numerous activities at the same time, and each activity must meet multiple goals. This research investigates how to properly integrate and schedule resources while attaining different goals. This research proposes using an enhanced particle swarm optimization technique (IPSO) to combine firms’ internal resources. In order to address the issue of uneven particle dispersion caused by random population initialization, IPSO incorporates chaos theory into particle population initialization. The logistic mapping sequence generates a huge number of particles, and the particles with the highest quality are chosen for initialization. This can increase particle quality, allowing particles to be spread equally during setup. In the late stage, the classic particle swarm optimization algorithm (PSO) has a slow convergence rate, causing the algorithm to readily slip into a local optimal solution. This research proposes a dynamic inertia weight update approach based on fitness value. In the later stages of the algorithm, this strategy can improve the convergence speed and quality of the global optimal solution, allowing the particles to do a global search and eventually identify the population’s ideal solution. Furthermore, IPSO creates a fitness function depending on task completion time. IPSO is used to test the performance of an enterprise’s resource integration case. Experiments show that the method utilized can swiftly locate the ideal solution, complete the integration, and optimization of enterprise resources in the shortest job completion time, and for the least amount of money.