bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative functional and molecular analysis of oral submucous fibrosis to oral squamous cell carcinoma: A pathway-based dynamic network analysis
Authors: Kumari Pratima , Dixit Anshuman 
Published: January 2024

Abstract

OSF (Oral submucous fibrosis) has been categorized as an OPMD (oral pre-malignant disease). It is frequently associated with areca chewing, a prevalent habit in Southeast Asia. The OSF is one of the leading causes of oral cancer and OSF and high prevalence of OSF-associated oral cancer is recorded in South India and Southeast Asia. The molecular mechanism of the transformation of OSF into OSCC is not properly understood. Identifying key genes and exploring the underlying molecular mechanisms involved in the transformation of OSF into OSCC is therefore of great importance. It may lead to the identification of new diagnostics, and ways to prevent the development of oral cancer from OSF. Therefore, in the present study, we devised a bioinformatics pipeline using gene expression analysis, dynamic protein-protein interaction network, and functional enrichment analysis to understand the transformation of OSF into oral cancer.
We identified gene expressions in different stages of transformation i.e. OSF without dysplasia (OSFWT), OSF with dysplasia (OSFWD), and further Oral squamous cell carcinoma (OSCC). OSF-associated 52 dysplastic genes were identified that were found to enrich the assembly of collagen fibrils and other multimeric structures, wound healing, spreading of cells, and sodium ion transmembrane transport processes. Important dysplastic genes such as COL1A2, COL5A1, COL5A2, COL6A1, DLG4, CS, and ALDH5A1 were proposed. Important dynamic (Dy) nodes were identified using enriched pathways. MYC is identified as the most important node in OSF with a high Dn-score. Dy-nodes were mostly enriched in immune system pathways suggesting immune involvement in OSCC progression. A few important genes were identified based on their frequency in every observation such as HSPD1, MAPT, HNRNPK, TRIM24, HLA-C, FOS, CD79B, TMPO, and PTPN6. In conclusion, our study identified a group of potential genes involved in OSF and OSF transformation into oral cancer and their functions.
First discovery of inter-specific roosts of tribe Dacini (Tephritidae: Diptera) fruit flies from Asia: Maneuvering toward the efficient bio-rational management of true fruit fly pests
Authors: Singh Maneesh Pal , Sharma Sneha , Hancock David Lawrence Hancock 
Published: January 2024

Abstract
This study unveils the discovery of inter-specific roosts within the tribe Dacini of familyTephritidae (Diptera) fruit flies fromAsia, involving six species of BactroceraMacquart. In addition, we also suggest a new parameter for inter-specific communication and discuss the possibility of interspecific communication among insects. We also indicate the possibility of roles of allelochemicals in establishing phylogenetic relationships.This finding advances bio-rational management techniques and offers a promising pathway for the effective control of true fruit fly pests.
Empowering Smart Grid Security: Towards Federated Learning in 6G-Enabled Smart Grids using Cloud
Authors: J Jithish , Mahalingam Nagarajan , Seng Yeo Kiat 
Published: January 2024

Abstract

As the realm of smart grids continues to evolve, embracing new technologies, researchers are exploring the potential ofupcoming 6G technology to address the challenges in management of smart grids. With the adoption of 6G technology,wireless energy meters, which play a key role in smart grid advancement, promise higher data rates, ultra-low latency, improvedconnectivity, and enhanced security. However, the integration of advanced technologies into smart grids, raises concernregarding cyberattacks such as distributed-denial-of-service (DDoS) attacks, which pose grave threat to the functionality andstability of the grid. To address these security challenges, smart grids traditionally implement intrusion detection systems (IDS)that analyse traffic logs from smart meters, but traditional IDS may face difficulties in detecting novel attacks such as subtle,multi-domain DDoS attacks. Towards securing smart grids, anomaly detection emerges as a crucial technique, integratedwith deep learning (DL), this technique can potentially identify deviations from normal, non-malicious network traffic, to detectcyberattacks, thereby enhancing grid security. However, it is seen that using user data for training DL models at the serverviolates data privacy regulations, which necessitates a balance between advanced anomaly detection and strict adherence todata privacy norms. Federated Learning (FL) has emerged as a suitable solution in this scenario, offering a privacy-focusedsolution allowing smart meters to train DL models with locally generated datasets and make predictions at the edge. In thiswork, we propose a hierarchical FL approach in smart meters for the 6G era, focusing on privacy-preserving anomaly detectionagainst DDoS attacks. Our work integrates a cloud-based service framework within an FL setup for smart grids, leveraging thescalability of cloud platforms and edge computing for efficient, secure, and cost-effective anomaly detection in line with 6Gtechnology requirements. Evaluation of our approach in local local simulation environment, using a workstation as the serverand Raspberry Pi devices as client nodes and cloud infrastructure provided by Amazon Web Services (AWS). Our goal is toinvestigate the feasibility of using cloud solutions to support federated learning-based anomaly detection in smart grids.Theperformance metrics between local and cloud simulations for our custom neural network showed that the variations betweentwo sets of simulations are not significant, and the proposed approach is suitable for deployment in real-world scenarios,especially for upcoming 6G-enabled smart grids where consistent performance is essential.
High expression of SMPD4 promotes liver cancer and is associated with poor prognosis
Authors: Rongyue Wang , Yanze Su , Zhiheng Lin , Kelaier Yang , Erbao Chen , Jikui Liu 
Published: January 2024

Abstract

Background and objective:
The expression of sphingomyelin phosphodiesterase 4 (SMPD4), a neutral sphingomyelin enzyme, is intricately associated with tumorigenesis and progression. However, its function in hepatocellular carcinoma (HCC) and its pathogenic mechanism remain largely unclear. We investigated the correlation between SMPD4 in HCC and its prognostic significance and functions in HCC cell proliferation, invasion, and migration.
Methods
The expression of SMPD4 was detected in different tumor types, such as HCC, using the database from The Cancer Genome Atlas (TCGA). The diagnostic significance of SMPD4 was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The Kaplan–Meier curve analysis was conducted to assess the ability of SMPD4 to predict HCC prognosis. The relationship between SMPD4 expression and the degree of immune cell infiltration in HCC was examined using the Tumor Immune Estimation Resource (TIMER) database. In addition, we performed quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) to verify SMPD4 expression in 20 frozen liver cancer tissue samples and paired non-carcinoma liver tissues. Small interfering RNA (siRNA) was performed to silence SMPD4 in cancer cells. The effect of SMPD4 expression in liver cancer cells was measured through qRT-PCR and western blotting. The function of SMPD4 in the proliferation, invasion, and migration of Hep3B and HepG2 cells was validated using the CCK-8, EdU, wound healing, and Transwell assays. Finally, the relationship between SMPD4 and drug sensitivity was examined.
Results
Elevated expression of SMPD4 was recorded in 22 cancer types, including HCC. SMPD4 expression was related to gender, T stage, N stage, clinical stage, and pathological grade. The area under the ROC curve was 0.952, indicating the excellent diagnostic value of SMPD4. The Kaplan–Meier analysis demonstrated that SMPD4 upregulation was related to poor overall survival (OS) in patients with HCC. The functional enrichment analysis revealed the critical effect of SMPD4 on the cell cycle. Moreover, SMPD4 expression exhibited a positive relationship between the infiltration levels of B cells, CD8 T+ cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. Knocking down SMPD4 significantly inhibited HCC cell growth, invasion, and migration. Finally, SMPD4 expression was related to drug sensitivity.
Conclusions
SMPD4 is upregulated in HCC, indicating poor prognosis. It could be used as a diagnostic and prognostic biomarker for HCC. Knocking down SMPD4 affects the ability of proliferation, migration, and invasion by regulating the expression of cell cycle genes.
Bacterial Diversity and Bioprospecting for enzyme among the Shola Forests of Idukki District, Kerala, India
Authors: Fernandez Rochelle , Ramatchandirane Prabagaran Solai 
Published: January 2024

Abstract

Shola forests are unique montane vegetations found extensively along the Southern Western Ghats of India. Samples were collected in the form of soil, slurry, and water from Pampadum, Mathikettan and Anamudi Sholas. Cultivable bacteria were isolated to explore bacterial diversity of the region. Among the total 58 morphologically divergent bacterial strains, 32 isolates showed circular configuration, 24 were irregular while 2 were punctiform. Predominance of pale white colour colonies were discernible followed by white, beige, orange, yellow, pink including transparent ones. Nearly 56.89% of the isolates were found to be Gram negative rods. Distribution of Gram positive rod and Gram positive cocci were 39.65% and 3.45% respectively. Statistical analysis (Shannon and Simpsons) was recorded. Maximum and minimum diversity was observed from the samples collected from Pampadum soil and water. Identification through 16S rRNA gene sequence of the isolates revealed predominance of 4 divisions viz., Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, distributed in 9 genera. More genera were distributed in the phyla Proteobacteria followed by the Firmicutes. Least representations were by Actinobacteria and Bacteroidetes. The bacterial isolates had the ability to produce different enzymes. The isolate Acinetobacter dispersus (ASL31) was found to have maximum amylase activity of 62.6 ± 1.3 U/ml. The isolate Bacillus paralicheniformis (PS1) showed maximum protease activity of 49.2 ± 0.6 U/ml, and the isolate Bacillus aerius (MSL9) possessed maximum cellulase activity of about 86.2 ± 0.9 U/ml. Hence, the diverse environment of Shola forests provides adequate diversity to explore the place for various microorganisms for bioprospecting.
Quantifying the Effects of Sleep on Sensor-Derived Variables from Upper Limb Accelerometry in People with and without Upper Limb Impairment
Authors: Miller Allison E. , Lang Catherine E. , Bland Marghuretta D. , Lohse Keith R. 
Published: January 2024

Abstract

Background:Despite the promise of wearable sensors for both rehabilitation research and clinical care, these technologies pose significant burden on data collectors and analysts. Investigations of factors that may influence the wearable sensor data processing pipeline are needed to support continued use of these technologies in rehabilitation research and integration into clinical care settings. The purpose of this study was to investigate the effect of one such factor, sleep, on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment and across a two-day wearing period.Methods:This was a secondary analysis of data collected during a prospective, longitudinal cohort study (n = 127 individuals, 62 with upper limb impairment and 65 without). Participants wore a wearable sensor on each wrist for 48 hours. Five upper limb sensor variables were calculated over the full wear period (sleep included) and with sleep time removed (sleep excluded): preferred time, non-preferred time, use ratio, non-preferred magnitude and its standard deviation. Linear mixed effects regression was used to quantify the effect of sleep on each sensor variable and determine if the effect differed between people with and without upper limb impairment and across a two-day wearing period.Results:There were significant differences between sleep included and excluded for the variables preferred time (p < 0.001), non-preferred time (p < 0.001), and non-preferred magnitude standard deviation (p = 0.001). The effect of sleep was significantly different between people with and without upper limb impairment for one variable, non-preferred magnitude (p = 0.02). The effect of sleep was not substantially different across wearing days for any of the variables.Conclusions:Overall, the effects of sleep on sensor-derived variables of upper limb accelerometry are small, similar between people with and without upper limb impairment and across a two-day wearing period, and can likely be ignored in most contexts. Ignoring the effect of sleep would simplify the data processing pipeline, facilitating the use of wearable sensors in both research and clinical practice.
Cybersecurity entity recognition for blockchain of things via Hierarchical Attention Mechanism
Authors: Wu Chunwang , Liu Xiaolei , Ding Kangyi , Xin Bangzhou , Lu Jiazhong , Liu Jiayong , Huang Cheng 
Published: January 2024

Abstract
With the integration of blockchain technology and the Internet of Things (IoT), the blockchain of things (BCoT) has received more attention. Because of the lack of efficient security mechanisms, the number of security incidents aimed at BCoT has been growing exponentially. The traditional cybersecurity analysis methods can utilize cybersecurity knowledge graph to extract threat intelligence information with fine granularity for BCoT. Named entity recognition (NER) is the primary task for constructing cybersecurity knowledge graph for BCoT. Traditional NER models make it difficult to determine entities with complex structures and ambiguous meanings in BCoT. It also cannot efficiently extract non-local and non-sequential dependencies between the cybersecurity entities. So, the traditional NER cannot be directly applied in the field of BCoT. In this paper, we propose a novel Cybersecurity Entity Recognition model based on Hierarchical Attention Mechanism, denoted as CER-HAM, to extract cybersecurity entity in the field of BCoT. CER-HAM composes the self-attention mechanism with the graph attention mechanism to capture non-local and non-sequential dependencies between cybersecurity entities. Based on those dependencies, CER-HAM can accurately extract cybersecurity entity in the field of BCoT. In the end, the real cybersecurity dataset of BCoT is used to verify the efficiency of CER-HAM. The experimental results show that the F1-score reached by CER-HAM is better than the traditional entity recognition model.
The use of mobile applications among healthcare professionals for patient care in Accra
Authors: Brobbey Kwame Okyere , Brobbey Kwame Okyere 
Published: January 2024

Abstract
Background: Few global and local studies have investigated the use of smartphones and associated applications among healthcare professionals, particularly in the context of patient care. The surge in mobile health applications, approximately300,000 times, available on platforms such as theGoogle Play Store and the iPhone app store highlights an increasing trend. In resource-constrained environments such asGhana, leveraging these technologies could facilitate secure health information exchange, deliver evidence-based care, and minimize errors in caregiving.
Purpose: This study exploredthe adoption and utilization of mobile technologies, specifically health applications, to support patient care in Ghana. The objectives include understanding healthcare professionals' usage patterns and perceived benefits, identifying the types of applications in use, and anticipating future applicationsto enhance patient care.
Methods: A structured questionnaire was administered to 233 randomly selected healthcare professionals, including doctors, nurses, pharmacists, laboratory technicians, X-ray technicians, and physician assistants. The participants, sourced from two hospitals in Accra, provided insights into their opinions regarding the use of mobile health applications in patient care.
Results: The findings revealed that 52.8% of healthcare professionals actively utilize mobile applications for patient care. Medscape emerged as the most commonly used tool (31.33%). The keybenefits identified by users included aiding medical calculations (98.4%). Additionally, 33.5% expressed preferences for specific types of applications.
Conclusion: While there is significant adoption of mobile applications for patient care, challenges persist, including limited support from hospital leadership and awareness gaps among healthcare professionals. The study underscores the need for heightened awareness campaigns and support structures, including financial supportfrom management, to facilitate and enhance the integration of mobile technologies in patient care delivery.
Radiation combined with PD-1 inhibitor induces time-dependent changes in myocardial injury by regulating HMGB1-associated inflammatory microenvironment
Authors: Liu Yao , Wu Bibo , Wang Yu , Bai Jie , Wang Gang , Zhao Shasha , Su Shengfa , Lu Bing , Hu Yinxiang , OuYang Weiwei , Guo Zhenneng , Wan Jun 
Published: January 2024

Abstract
Background
PD-1 inhibitors may superimpose the toxicity of radiotherapy while increasing the antitumor effect. However, there are fewer studies on immune myocarditis caused by radiotherapy plus anti-PD-1 and the mechanism is still under exploration.
Methods
40 C57BL/6 mice were randomly assigned to 4 groups. A: Control, B: PD-1 inhibitor, C: cardiac irradiation and D: thoracic irradiation + PD-1 inhibitor, mice were treated with either anti-PD-1 antibody with or without thoracic radiation (15Gy). Each group contained ten mice, five of which were studied for a duration of 1 month and the remaining five for 3 months. Tunel staining was utilized to observe apoptosis of cardiac tissues; histological analysis was performed to analyze the structural and morphological alterations, fibrosis of the heart tissue. The infiltration of CD3+, CD4+, and CD8 + T-cells into the cardiac was analyzed through flow cytometry; Elisa measured the expression levels of TNF-α, IL-1β, and TLR-4 in the cardiac; and immunoprotein blotting and qPCR were used to observe the protein and mRNA expression levels of HMGB1, TLR-4, and NF-κB p65.
Results
Group D exhibited a greater degree of cardiac injury, fibrosis, and apoptosis in comparison to groups A, B, and C. Additionally, there was an increase in injury, AI, and CVF values after three months as opposed to one month (P < 0.05).After one month, there was no statistically significant difference in cardiac damage, AI, or CVF values between groups A and B; however, after three months, there was a significant difference (P < 0.05). Group D also had higher levels of IL-1β, IL-6, TNF-α and T-lymphocyte distribution, HMGB1, TLR4, NF-κB P65 protein, and mRNA expression than the other three groups. However, each group's index expression declined over the course of three months as opposed to one month, and this difference was statistically significant (P < 0.05).
Conclusion
PD-1 inhibitors exacerbated myocardial injury based on radiation by upregulating the expression of inflammatory factors in the HMGB1 signaling pathway. In the early stages of myocardial damage, inflammatory alterations predominated, while in the later stages, fibrosis.
Visual direction perception is pulled toward direction of head rotation
Authors: Pickard Kate , Davidson M. J. , Alais David 
Published: January 2024

Abstract

In order to effectively navigate the world around us, we must be able to correctly attribute motion signals to a wide variety of sources, including ourselves. Previous research has examined how we accurately split visual motion signals into those caused by self-motion or object motion, however this misses the key fact that we are active observers in our environment. To understand how we successfully disentangle complex motion signals, we must investigate how active components of self-motion signals might influence visual motion perception. The current study utilises virtual reality (VR) technology to investigate perceived direction of visual retinal motion across two experiments during active head rotations. Experiment 1 investigates the influence of horizontal active head rotations on the perceived direction of motion for 16 motion angles spaced equally around 360°. Experiment 2 additionally manipulated the strength of visual motion signals in order to examine how vestibular and visual signals might be weighted when one sensory signal is unreliable. In both experiments, perceived direction of visual motion was consistently biased toward the direction of head rotation, demonstrating an influence of active movement on vision. In addition, directions of motion that were adjacent to the cardinal axes (e.g. ±22.5° from vertical/horizontal) were repelled away from the cardinal reference during head rotations and stationary conditions, indicating an additional effect of reference repulsion.
Current status of Trypanosoma grosi and Babesia microti in small mammals in the Republic of Korea
Authors: Kim Hyun Jung , Han BoGyeong , Lee Hee-Il , Ju Jung Won , Shin Hyun-Il 
Published: January 2024

Abstract
Background: Small mammals are natural reservoir hosts of zoonotic diseases, including parasitic protozoa. To assess the risk of rodent borne parasitic protozoa in the Republic of Korea (ROK), this study investigated the status of parasitic protozoa, namely Trypanosoma, Babesia, and Theileria in small mammals.
Methods: Small mammals were captured during the spring and autumn at 16 sites. In total, 331 blood samples from small mammals were analyzed for the presence of parasites using PCR.
Results: Samples were positive for Trypanosoma grosi (23.9 %; n=79) and Babesia microti (10 %; n=33). However, Theileria was not detected. The small mammals collected from Seogwipo showed the highest infection rate of T. grosi (48.4 %), while the highest B. micrtoti infection rate was observed in small mammals collected from Gangneung (25.6 %). Sequence data of T. grosi from small mammals revealed that it belonged to the T. grosi AKHA strain. Phylogenetic analysis of B. microti revealed two genotypes: the US and Kobe types. B. microti US-type-infected small mammals were detected throughout the country, but the Kobe type was only detected in Seogwipo.
Conclusions: To the best of our knowledge, this is the first nationwide survey to confirm T. grosi and B. microti infections at the species level in small mammals in the ROK and the first study to identify the Kobe type of B. microti. These results provide useful information for further molecular epidemiological studies on these parasites.
Antimicrobial and Anticancer Activity of Gallic acid-Cu(II) Hybrid Nanoflowers and Gallic acid-Zn(II) Hybrid Nanoflowers
Authors: YILMAZ Burcu SOMTURK 
Published: January 2024

Abstract
Herein, synthesis and characterization of hybrid nanoflowers using gallic acid as organic components, and Cu(II), Zn(II) ions which were involved as the inorganic component was carried out. In the first part of the study, the morphologies of the synthesized hybrid nanoflowers (hNFs) were investigated using SEM, EDX, XRD, FT-IR and mapping. In the second part of the study, the antimicrobial activities of the synthesized hybrid nanoflowers were examined. Antimicrobial activities of hNFs were systematically studied against Staphylococcus aureus, Escherichia coli, P. aeruginosa and Candida albicans with broth microdilution and short time-kill assay. In addition to, anticancer activity of hNFs was examined. For this, A549 and MCF7 cell line were used.