bluuebunny/crossref_metadata_2025_split huggingface dataset:
Substrate stiffness regulates collective colony expansion of the social bacterium Myxococcus xanthus
Authors: Faiza Nuzhat , Welch Roy , Patteson Alison 
Published: May 2024

Abstract

Many cellular functions depend on the physical properties of the cell’s environment. Many bacteria have different types of surface appendages to enable adhesion and motion on a variety of surfaces. Myxococcus xanthus is a social soil bacterium with two distinctly regulated modes of surface motility, termed the social motility mode driven by type iv pili and the adventurous motility mode based on focal adhesion complexes. How bacteria sense different surfaces and subsequently coordinate their collective motion remains largely unclear. Using polyacrylamide hydrogels of tunable stiffness, we found that wild-type M. xanthus spreads faster on stiffer substrates. Here, we show using motility mutants that disrupt adventurous motility suppresses this substrate-stiffness response, suggesting focal-adhesion-based adventurous motility is substrate-stiffness dependent. We also show that modifying surface adhesion by the addition of adhesive ligands, chitosan, increases the amount of M. xanthus flairs, a characteristic feature of adventurous motility. Taken together, we hypothesize a central role of M. xanthus adventurous motility as a driving mechanism for surface and surface stiffness sensing.
Genome-Wide Identification, Characterization and Expression Analysis of the Lhc Gene Family in Tetradesmus obliquus
Authors: Tan Hailing , Ma Yonghua , Cai Gaolei , Tan Hui , You Deyu , Yin Yuhang , Yang Jun , Tan Fengxia , Chai Yi 
Published: May 2024

Abstract

The process of photosynthesis depends heavily on the light-harvesting chlorophyll a/b-binding proteins (Lhc). However, to date, there has been a lack of systematic understanding of the Lhc gene family members in T. obliquus. This study conducted a systematic identification and analysis of the Lhc family genes in T. obliquus using bioinformatics. The findings show that 33 ToLhc genes in total, dispersed unevenly over 14 chromosomes, were found in T. obliquus. Most ToLhc genes encode stable proteins, with the majority predicted to localize in the chloroplast. The most prevalent cis-acting elements were those linked to both biotic and abiotic stress responses, according to analysis.RT-qPCR analysis showed that all ToLhc genes were down-regulated under 6 mg/L Cr6+ conditions, except for ToLhca1/5.3 and ToLhcb1.1, which maintained expression levels. This study systematically identified and characterized members of the ToLhc gene family in the green algae T. obliquus. Additionally, it offered an initial comprehension of the expression patterns of 33 genes under Cr6+ heavy metal stress. The aim was to assess and predict the ecological risk of heavy metal Cr6+ pollution to aquatic organisms, and to offer a theoretical framework for assessing how Cr6+ affects algae.
Reel for a Good Feel: Impact of Social Media Use During Microbreaks on Employee Resources
Authors: Grobelny Jaroslaw , Glinka Marta , Chirkowska-Smolak Teresa 
Published: May 2024

Abstract

This study investigates the impact of social media-related microbreaks on the resource recovery of employees. Specifically, we examined whether or not the brief, hedonic use of social media through algorithmic videos could fully replenish resources, such as vigor and fatigue, that are depleted after performing clerical tasks. We also compared this form of recovery to other established microbreak activities. We used a pre-registered, mixed-method experimental design to collect data from 308 employees. A series of mixed-method ANOVA tests complemented by quadratic linear contrast terms and post-hoc analyses were performed to test hypotheses and address research questions. The findings indicate that although social media microbreaks offer a certain degree of resource replenishment, they do not provide full recovery, particularly regarding fatigue. Social media facilitate a reasonable psychological detachment but fall short in other recovery experiences. Notably, exposure to nature yielded more beneficial results. The study contributes novel insights to a field primarily focused on the negative impacts of excessive social media use and suggests that rational and brief usage can be advantageous for employee well-being.
Research on the Identification Method of Respiratory Tract Infections Based on Multi-parameter Fusion
Authors: Zhang Jun , Chen Shaokang , Wang Jingyi , Zhao Mengmeng , Tang Jiantong , Zhang Haoyang , Wang Huiquan , Yu Xin , Zhang Yuan 
Published: May 2024

Abstract

Background
Cough sounds, as one of the common symptoms of respiratory diseases, are not only rich in information but also translate the health status of the respiratory system. In order to achieve non-invasive, accurate, and rapid identification of respiratory tract infections,this study designed experiments to collect cough sound data from individuals with different symptoms.
Methods
Various feature parameters were extracted from the cough sound data, and a respiratory tract infection identification model was established based on machine learning methods. A total of 20 patients with upper respiratory tract infections and 37 patients with lower respiratory tract infections were included in this study.
Results
From these patients, 165 upper respiratory tract infection cough events and 265 lower respiratory tract infection cough events were extracted. MFCC feature parameters, wavelet coefficient-related feature parameters, and entropy-related feature parameters were extracted from the cough events and various combinations were considered. Random forest was employed to construct the respiratory tract infection identification model using different combinations of feature parameters. The results showed that different feature combinations resulted in different modeling performance. Among them, three feature combination strategies showed the best performance, achieving an accuracy of 90% and an AUC of 94%.
Conclusions
This study successfully realized effective classification of respiratory tract infections through cough sounds, providing doctors with a non-invasive, accurate, and rapid auxiliary diagnostic tool.
Structure design and vibration control of vibration reduction boring bar with variable damping
Authors: Liu Qiang , Li Jingxin , Ma Jing , Gao Dayong , Han Jiaming , Li Jianran 
Published: May 2024

Abstract

A vibration reducing boring bar with variable damping is proposed as a solution to the issue of poor stability of boring bars during boring machining. This will enhance the stability of boring machining. Firstly, this article places a variable damping absorber in the cavity at the front end of the boring bar. An excitation coil, a mass block, and a cantilever beam make up the absorber structure. It contributes to damping adjustment by adjusting the excitation coil's energizing voltage, which alters the damping force on the mass block. On this basis, establish a dynamic model and analyze the damping and magnetic field of the variable damping absorber. Simultaneously building a vibration damping boring bar system platform based on LabVIEW to monitor and control the vibration status of the boring bar. Ultimately, performance testing of the absorber and boring experiments confirmed the viability of the vibration damping boring bar. The results showed that the maximum vibration acceleration of the vibration damping boring bar decreased by about 34.7%. It has been proven that the variable damping vibration reduction boring bar has good vibration reduction effect.
Single-cell RNA sequencing and transcriptomic analysis reveal the critical signatures involved in nonhealing diabetic foot ulcers
Authors: Hu Yungang , Yu Lu , Du Weili , Hu Xiaohua , Shen Yuming 
Published: May 2024

Abstract

Background Diabetic foot ulcer (DFU) is a prevalent complication associated with diabetes that is characterised by high morbidity, high disability and high mortality and involves chronic inflammation and infiltration of multiple immune cells. However, the molecular mechanisms underlying DFU remain unclear. Here, we aimed to identify the critical signatures in nonhealing DFUs using single-cell RNA sequencing and transcriptomic analysis.Methods The GSE165816, GSE134431, and GSE143735 datasets were downloaded from the GEO database. First, we preliminarily processed and screened the datasets, removed low-quality data and identified the cell subsets. Each cell subtype was annotated, and the predominant cell types contributing to the disease were analysed. Based on this information, a prediction model was constructed with the training set GSE134431 and testing set GSE143735. Key genes were identified using the LASSO regression algorithm, followed by verification of model accuracy and stability. Additionally, we investigated the molecular mechanisms and changes in signalling pathways associated with this disease using immunoinfiltration analysis, GSEA, and GSVA.Results Through scRNA-seq analysis, we identified 12 distinct cell clusters and determined that the basalKera cell type was important in disease development. A prediction model with high accuracy and stability was constructed incorporating five key genes (TXN, PHLDA2, RPLP1, MT1G, and SDC4). Immune cell infiltration analysis, GSEA, and GSVA revealed alterations in immune cells and signalling pathways throughout disease progression, primarily involving CD8+ T cells, T helper cells, the hypoxia-inducible factor signalling pathway, and the interleukin-17 signalling pathway.Conclusions Our study identified six key genes, namely, TXN, PHLDA2, RPLP1, MT1G, and SDC4, which are significantly associated with the development of nonhealing DFU and play a crucial role in immune cell infiltration. The identified genes have the potential to serve as new prevention and treatment strategies for DFU.
Gut microbiome-brain crosstalk in the early life of chicken reveals the circadian regulation of key metabolic and immune signaling processes
Authors: Gupta Mridula , Cilkiz Mustafa , Ibrahim Mohamed Magdy , Athrey Giridhar 
Published: May 2024

Abstract

Background
Circadian rhythms are innate biological systems that control everyday behavior and physiology. Furthermore, bilateral interaction between the host's circadian rhythm and the gut microbes influences a variety of health ramifications, including metabolic diseases, obesity, and mental health. Several studies have revealed how neurological components interact with GALT physiology and the microbiome population in the host. Keeping these factors in regard, we are studying the correlation between differential gene expression in the chicken brain and microbiota abundance during circadian rhythms. To study rhythmic oscillations in immune genes, we raised freshly hatched chicks under two photoperiod treatments: normal photoperiod (NP = 12/12 LD) and extended photoperiod (EP 23/1 LD). The chicks were randomly assigned to one of two treatments. After 21 days of circadian entrainment, the chicks were euthanized at nine-time points spaced six hours apart over 48 hours to characterize the brain transcriptomes. Each sample's RNA was extracted, and 36 mRNA libraries were created and sequenced using Illumina technology, followed by data processing, count data generation, and differential gene expression analysis.
Results
We generated an average of 17.5 million reads per library for 237933593.3 reads. When aligned to the Galgal6 reference genome, 11,867 genes had detectable expression levels, with a common dispersion value of 0.105. To identify the genes that follow 24-hr rhythms counts per million data were performed in DiscoRhythm. We discovered 577 genes with Cosinor and 417 with the JTK cycle algorithm that exhibit substantial rhythms. We used weighted gene co-expression network analysis (WGCNA) to analyze the correlation between differentially expressed genes and microbiota abundance. The most enriched pathways included aldosterone-regulated sodium reabsorption, endocrine and other factor-regulated calcium reabsorption, GABAergic synapse, oxidative phosphorylation, serotonergic synapse, dopaminergic synapse, and circadian entrainment.
Conclusions
Photoperiods and robust 24-hr rhythms differentially influenced key neurochemical and mitochondrial pathways during early life. Furthermore, the interaction between gut microbiota and host gene expression highlights the role that specific microbial taxa (like Lactobacillus) may play in the early-life regulation of homeostasis and provides promising avenues for application.
Sulfur doped Zinc Oxide-Nikel Oxide as Efficient Bifunctional Electrocatalyst for overall Water splitting
Authors: Saeed Faiq , arain Samia , Yong Wang 
Published: May 2024

Abstract

A mixed Sulfur-doped zinc oxide-nickel oxide nanocomposite electrocatalyst for oxygen evolution reaction (OER) was prepared. By hydrothermal method, we prepared a high-efficiency OER electrocatalyst doped with zinc oxide and nickel oxide. By applying different characterizations, the material was proven to be a new phase of (S-doped-ZnO-NiO). S-doped ZnO-NiO, ZnO-NiO did not show excellent performance. At 10 mA cm− 2, the generation potential of OER is 1.45 V and that of HER is -0.04 V. This unique morphology results in better OER performance of 240 mV at 10 mA cm− 2 in the KOH electrolyte, and similarly, the S-doped ZnO-NiO shows us excellent long-term stability in alkaline media with a small Tafel slope (77 mV dec− 1). S-doped ZnO-NiO hybrid catalysts offer great potential for electrochemical devices due to their low cost and high activity. we have successfully constructed an electrocatalyst with the dual functions of HER and OER, which can achieve efficient water splitting.
Hybrid Encryption for Securing HDFS Data in Big Data Environments
Authors: shivani shivani Awasthi 
Published: May 2024

Abstract

In the previous era, Conventional encryption schemes that work on file were linked with a lot of processing overhead that negatively impacted performance in the Hadoop framework. But now, With the help of the MapReduce framework or parallel processing method, this paper suggests a unique solution for securing large data and boosting performance: A hybrid encryption technique that combines the Twofish and AES algorithms with the map-reduce framework inside the HDFS (Hadoop Distributed File System) environment. Different conventional methods exist like Twofish + RSA, and AES + Twofish as hybrid encryption that is not decent for dealing with large data, our solution drastically improves performance through parallel encryption by mapper-reducer processes and advances the security of HDFS storage data. In this paper, we use hybrid encryption using AES with Twofish because Twofish provides better data security, and AES is used for optimizing the speed of data encryption, and decryption. Empirical findings validate the suggested approach's effectiveness in protecting private information kept in HDFS and improving performance in terms of speed of encryption ≅ 2–3%, throughput ≅1–2%, and efficiency ≅ 1–2% parameters. This work enhances the performance and reduces the risks associated with unwanted access to important data assets by data security in HDFS-based systems.
Dispersion analysis of generalized wave equations under the single-parameter second-order strain gradient theory
Authors: CHEN CHAOPU , BAI WENLEI , LIU HONG , WANG ZHIYANG , LI YOUMING 
Published: May 2024

Abstract

The construction of wave equations describing the wave propagation in real medium is a critical problem to be solved for oil and gas seismic exploration. Researches show that the microstructural interactions by different scales will trigger the heterogeneous response of the medium, which in turn has an impact on the mechanical behavior of macro-scales. The heterogeneous response triggered by microstructural interactions in the medium is portrayed by introducing higher-order spatial derivatives of the strain and additional parameters of the characteristic scale of the medium under the framework of the generalized continuum mechanics theory (GCMT). When considering the heterogeneous responses triggered by microstructural interactions of the medium, seismic waves propagate in a dispersion manner. In this paper, we introduce the generalized wave equations under the single-parameter second-order strain gradient theory (SSSGT) by considering the nonlocal effects, give the decoupled generalized wave equations using the Helmholtz decomposition theorem, and derive the expression of the phase-velocity of the P- and S-wave to analyze the theoretical dispersion. Combined with numerical modeling, we further investigate the dispersion in the propagation of P- and S-wave triggered by the microstructural interactions. Numerical modeling and dispersion analysis indicate that the wave propagation is affected by the characteristic scale of the micropore of the medium and the frequency, and the dispersion of P- and S-wave is prominent increasingly with the frequency and the characteristic scale of the micropore increasing.
Telehealth-delivered cognitive rehabilitation for people with cognitive impairment as part of the post-COVID syndrome: Protocol for a randomised controlled trial as part of the CICERO (Cognitive Impairment in Long COVID: Phenotyping and Rehabilitation) study
Authors: Vanova Martina , Patel Aysha Mohamed Rafik , Scott Iona , Gilpin Gina , Manning Emily N , Ash Charlotte , Wittenberg Philippa , Lim Jason , Hoare Zoe , Evans Rachel , Bray Nathan , Kipps Christopher M , Devine Ciara , Ahmed Saliha , Dunne Ross , Koniotes Anna , Warren Catherine , Chan Dennis , Suárez-González Aida 
Published: May 2024

Abstract

Background
Between 25–75% of people with persistent post-acute sequelae of SARS-CoV-2 infection (PASC) experience cognitive difficulties, compromising functional ability, quality of life, and activities of daily living, including work. However, despite this significant morbidity, there is a paucity of interventions for this disorder that have undergone evaluation within a formal trial setting. Therefore, we have developed a cognitive rehabilitation programme, specifically designed to address the cognitive symptoms of PASC, notably impaired attention and processing speed, while also accounting for other PASC symptoms (fatigue, post-exertional malaise) that may aggravate the cognitive impairment. This study protocol outlines a randomised controlled trial (RCT) designed to evaluate the effectiveness of this programme compared to standard clinical care.
Methods
This is a multi-centre, parallel-group, individually randomised control trial, comparing standard clinical care with and without cognitive rehabilitation. We will recruit 120 non-hospitalised adults (aged 30–60 years) from three NHS sites in England with a history of COVID-19 infection and cognitive impairment persisting more than three months after the acute infection. Participants will be randomised (1:1) to the intervention or control groups, with the latter represented as a provision of standard clinical care without cognitive rehabilitation. The cognitive rehabilitation programme consists of ten one-hour sessions, delivered weekly. Outcomes will be collected at baseline, three and six months, with participant-defined goal-attainment scores, relating to functional goals, at three months as the primary outcome measure. Secondary outcomes will be cognitive function, measures of quality of life, social functioning, mental health, fatigue, sleep, post-exertional malaise, and social and health care service use. We will also evaluate the health-economic benefits of cognitive rehabilitation in this population.
Discussion
Cognitive impairment in PASC is a major cause of functional disability with no effective treatment. Accordingly, we will undertake an RCT of cognitive rehabilitation, the protocol of which is published here. If this trial is successful in delivering improvements in trial outcomes, it will address a major unmet need relating to this emergent disorder, with a significant impact on affected individuals and the wider health economy.
Trial registration
NCT05731570.
Nanotechnology Enabled Advances in Oral Delivery of Therapeutic Peptides: Mechanistic Insights for Translation to Clinic
Authors: Raval Harshvardhan M. , Sangave Preeti C. 
Published: May 2024

Abstract:
Peptides represent a rapidly expanding class of novel treatments with distinct pharmacokinetic
properties when compared to macromolecular proteins or small-molecule medications.
Peptides are polymers with a molecular mass of less than 10 kDa. Protein-protein interactions
have been the primary goal of oral delivery of peptide drugs for the last two decades. Recent
trends suggest the possibility of mechanistically targeting challenging binding interfaces with the
right binding affinity and specificity for molecules like peptides that bring conformational flexibility.
Over 80 peptide medications have received regulatory approval to treat a range of conditions,
from human immunodeficiency infection caused by viruses to fatal diseases like cancer. This review
covers the need for peptide delivery via the oral route and offers insights to overcome the
challenges. For successful translation to the clinic, oral delivery of therapeutic peptides coupled
with nano formulation strategies has gained increased attention in recent years. The role of permeation
boosters, and digestive enzyme inhibitors to overcome major hurdles such as degradation in
the gastrointestinal tract and low intestinal permeability are presented here. Alteration of physicochemical
characteristics of peptide molecules, the addition of functional excipients to specifically
designed drug delivery systems, nanoformulation approaches, amongst other recent methodologies,
to increase the oral bioavailability of peptide medications, are also presented herein. Numerous
peptide candidates, both approved and under clinical trials, are included in this review.
REQUISITE OF SUB-ATTRIBUTES FOR SMART CITY CONCEPTUAL FRAMEWORK
Authors: Azmi Nurul Afiqah , Rozman Ahmad Tajjudin , Sukereman Anis Syazwani , Wijayaningtyas Maranatha 
Published: May 2024

A smart city requires citizen participation and key metrics such as smart city elements and performances. This paper aims to identify the sub-attributes for smart city elements and performances that required the formation of the conceptual framework. This research has studied the past literature related to smart city studies and citizen’s needs from the Smart City. This research continues the study by identifying two categories of variables which are Smart City elements and Smart City performance. The investigation of past literature shows that Smart City elements consist of eight attributes namely Administration, Social, Infrastructure and Utilities, Transport, Technology, Human, Economy and Environment. The result of past studies also determines that constructs that are important to Smart City performance are Quality of Life, Resource Management and Economic Competitiveness. To ensure the success of smart city initiatives, this study provides sub-attributes of smart city elements and performance that can assist policymakers and government in selecting the best criteria for sub-attributes for a smart city conceptual framework.