bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive Value of Combined Peripheral Inflammatory Markers in Patients with Head and Neck Cancers
Authors: Iuchi Hiroyuki , Ohori Junichiro , Haraguchi Megumi , Ando Yumi , Toge Sakiko , Yamashita Masaru 
Published: February 2023

AbstractBackground Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies worldwide, and patients have low survival and poor quality of life. Combined peripheral inflammatory markers are associated with poor outcomes in patients with malignancies. This study aimed to investigate the prognostic significance of combined peripheral inflammatory markers in patients with HNSCC. Methods Records of 531 patients with histologically confirmed HNSCC between January 2009 and January 2021 were reviewed. The optimal cutoff values of peripheral inflammatory markers were determined by the receiver operating characteristic curve analysis and the Youden test. The neutrophil-to-lymphocyte ratio (NLR)–platelet-to-lymphocyte ratio (PLR) score, NLR–monocyte-to-lymphocyte ratio (MLR) sore, and PLR-MLR score ranged from low to high, i.e., a high score indicated that both inflammation markers are high; mid score, either inflammation marker is high; and low score, both inflammation markers are low. The overall survival (OS) and disease-free survival (DFS) were evaluated. Univariate and multivariate analyses were performed. Results The median follow-up time was 55 (range, 3–148) months. The optimal cutoff values for pretreatment NLR, PLR, MLR, systemic inflammation response index (SIRI), and systemic immune inflammation index (SII) were 2.21, 214.24, 0.33, 0.86, and 472.44, respectively. Univariate analyses revealed that smoking status (P = 0.021), drinking status (P = 0.033), tumor stage (P < 0.001), nodal stage (P < 0.001), tumor node metastasis (TNM) stage (P < 0.001), SIRI (P = 0.031), NLR-PLR score (P = 0.007), NLR-MLR score (P = 0.004), and PLR-MLR score (P < 0.001) were significantly associated with OS. Independent prognostic factors for OS were smoking status, drinking status, tumor stage, and PLR-MLR score. Univariate analyses revealed that smoking status (P = 0.008), tumor stage (P < 0.001), nodal stage (P < 0.001), TNM stage (P < 0.001), SIRI (P = 0.003), SII (P = 0.010), NLR-PLR score (P = 0.002), NLR-MLR score (P = 0.002), and PLR-MLR score (P < 0.001) were significantly associated with DFS. Independent prognostic factors for DFS were smoking status and PLR-MLR score. Conclusions PLR-MLR score may be a valuable inflammatory marker for the prediction of survival in patients with HNSCC.
TREM2 deficiency aggravates NLRP3 inflammasome activation and pyroptosis in MPTP-induced PD mice and LPS-induced BV2 cells
Authors: Huang Peiting , Zhang Zhanyu , Zhang Piao , Feng Jiezhu , Xie Jianwei , Zheng Yinjuan , Liang Xiaomei , Zhu Baoyu , Chen Zhenzhen , Feng Shujun , Lu Jiahong , Liu Yawei , Wang Lijuan , zhang yuhu 
Published: February 2023

Abstract
Background
Microglia-mediated neuroinflammation plays a crucial role in the pathogenesis of PD. Triggering receptor expressed on myeloid cells 2(TREM2) confers strong neuroprotective effects in PD by regulating the phenotype of microglia. Recent studies suggest that TREM2 regulates high glucose-induced microglial inflammation through the NLRP3 signaling pathway. This study aimed to investigate the effect of TREM2 on NLRP3 inflammasome activation and neuroinflammation in PD.
Method
The AAV-TREM2-shRNA was injected into the substantia nigra of both sides of the mouse brain using a stereotactic injection method. The chronic PD mouse model was established by intraperitoneal injection of MPTP. Motor behavior test, immunohistochemistry of TREM2 and TH, immunohistochemistry and immunofluorescence Iba1, Western blot of NLRP3 inflammasome and its downstream inflammatory factors IL−1β and IL−18, and the key pyroptosis factors GSDMD and GSDMD-N were performed to explore the effect of TREM2 on NLRP3 inflammasome and neuroinflammation. In vitro experiment, Lentivirus was used to interfere with the expression of TREM2 in BV2 microglia, then LPS and ATP were used to stimulate inflammation to construct a cellular inflammation model. The expression differences of NLRP3 inflammasome and its components were detected by qPCR and western blot.
Result
In vivo, TREM2 expression was decreased, dopaminergic neuron loss was increased, and motor function was decreased, indicating that TREM2 knockdown and PD mouse models were successfully constructed. After TREM2 knockdown, the number of activated microglia was significantly increased, and the expression of cleaved caspase−1, NLRP3 inflammasome, IL−1β, GSDMD, GSDMD-N was increased. In vitro, TREM2 knockdown aggravated the inflammatory response of BV2 cells stimulated by LPS and promoted the activation of NLRP3 inflammasome through the NF-κB pathway. In addition, TREM2 knockdown also promoted the expression of TLRP4/MyD88, an upstream factor of the NF-κB pathway.
Discussion
Our in vivo and in vitro data showed that TREM2 knockdown promoted NLRP3 inflammasome activation and downstream inflammatory response, promoted pyroptosis, and aggravated dopaminergic neuron loss, which extends previous findings and support the notion that TREM2 acts as an important anti-inflammatory factor to ameliorate neuroinflammation in PD.
Engineered MED12 mutations drive uterine fibroid-like transcriptional and metabolic programs by altering the 3D genome compartmentalization
Authors: Buyukcelebi Kadir , Chen Xintong , Abdula Fatih , Duval Alexander , Ozturk Harun , Seker-Polat Fidan , Jin Qiushi , Yin Ping , Feng Yue , Wei Jian-Jun , Bulun Serdar , Yue Feng , Adli Mazhar 
Published: February 2023

Abstract
Uterine fibroid (UF) tumors originate from a mutated smooth muscle cell (SMC). Nearly 70% of these tumors are driven by hotspot recurrent somatic mutations in the MED12 gene; however, there are no tractable genetic models to study the biology of UF tumors because, under culture conditions, the non-mutant fibroblasts outgrow the mutant SMC cells, resulting in the conversion of the population to WT phenotype. The lack of faithful cellular models hampered our ability to delineate the molecular pathways downstream of MED12 mutations and identify therapeutics that may selectively target the mutant cells. To overcome this challenge, we employed CRISPR knock-in with a sensitive PCR-based screening strategy to precisely engineer cells with mutant MED12 Gly44, which constitutes 50% of MED12 exon two mutations. Critically, the engineered myometrial SMC cells recapitulate several UF-like cellular, transcriptional and metabolic alterations, including enhanced proliferation rates in 3D spheres and altered Tryptophan/kynurenine metabolism. Our transcriptomic analysis supported by DNA synthesis tracking reveals that MED12 mutant cells, like UF tumors, have heightened expression of DNA repair genes but reduced DNA synthesis rates. Consequently, these cells accumulate significantly higher rates of DNA damage and are selectively more sensitive to common DNA-damaging chemotherapy, indicating mutation-specific and therapeutically relevant vulnerabilities. Our high-resolution 3D chromatin interaction analysis demonstrates that the engineered MED12 mutations drive aberrant genomic activity due to a genome-wide chromatin compartmentalization switch. These findings indicate that the engineered cellular model faithfully models key features of UF tumors and provides a novel platform for the broader scientific community to characterize genomics of recurrent MED12 mutations and discover potential therapeutic targets.
Predictors Associated With Mental Help Seeking Attitude Among Malaysian College Foundation Students in the Midst of Covid-19 Pandemic: a Cross Sectional Study
Authors: Mesran Nur Nadhirah , Abdul-Razak Suraya , Nikmat Azlina Wati 
Published: February 2023

Abstract
Background
Globally, the Coronavirus Disease-2019 (COVID-19) pandemic results in major psychological sequalae across age groups including adolescents. Mental illness rates are high, yet mental help seeking attitude (MHSA) among adolescents is evidently low in developed countries during the pandemic. However, data is scarce in developing countries, hence the aim of this study was to determine the MHSA and its predictors including psychological wellbeing of Malaysian college foundation students during the COVID-19 pandemic.
Methods
A cross sectional study was conducted among college foundation students, aged 18 to 19 years old, from a private college in Klang Valley from 1st December 2021 until 30th March 2022. All college foundation students were invited, and eligible students completed self-administered online questionnaires. Data on MHSA, sociodemographic, clinical factors, availability, accessibility and affordability of mental health service, mental health literacy, self-stigma of seeking help and psychological wellbeing were collected. An independent T-test analysis was performed to compare mean of MHSA between psychological distressed and non-psychological distressed. Multiple linear regression analysis was done to identify predictors of MHSA.
Results
345 participants completed the questionnaires and the response rate was 62.9%. The mean age was 18.7 (± 0.75) years old. More than half were female (64.3%, n=222) and a majority had no past history of mental health illness (95.1%, n=328). Almost half had personal history of COVID-19 infection (49.3%, n=170). The mean of MHSA was 50.98 ±10.39. The predictors associated with MHSA were; self-stigma of help seeking (β=-0.59 (95% CI: -0.76, -0.42) p<0.01); mental health literacy (β=0.22 (95% CI: 0.13, 0.30) p<0.01); and affordability of mental health service facility (β=3.29 (95% CI: 1.42, 5.16) p<0.01). The prevalence of psychologically distressed was 23.2%, (95%CI: 20.4, 26.1), in which psychological distressed had a higher mean of MHSA than that of non-psychological distressed (53.29 ±10.48 vs. 50.29 ±10.29, p=0.02)
Conclusion
Mental help seeking attitude among Malaysian college foundation students was low during the COVID-19 pandemic. This may result in lost opportunities for early diagnosis and treatment. Strategies to reduce self-stigma of seeking help for mental illness is vital, while efforts to educate young adults about mental health and make mental health services affordable are warranted.
A global virome of methanogenic archaea highlights novel diversity and adaptations to the gut environment
Authors: Medvedeva Sofia , Borrel Guillaume , Krupovic Mart , Gribaldo Simonetta 
Published: February 2023

Abstract
Mobile genetic elements (MGEs), especially viruses, have a major impact on microbial communities. Methanogenic archaea play key environmental and economical roles, being the main producers of methane -a potent greenhouse gas and an energy source. They are widespread in diverse anoxic artificial and natural environments, including animal gut microbiomes. However, their viruses remain vastly unknown. Here, we carried out a global investigation of MGEs in 3436 genomes and metagenome-assembled genomes covering all known diversity of methanogens and using a newly assembled CRISPR database consisting of 60,000 spacers of methanogens, the most extensive collection to date. We obtained 248 high-quality (pro)viral and 63 plasmid sequences assigned to hosts belonging to nine main orders of methanogenic archaea, including the first MGEs of Methanonatronarchaeales, Methanocellales and Methanoliparales archaea. We found novel CRISPR arrays in ‘Ca. Methanomassiliicoccus intestinalis’ and ‘Ca. Methanomethylophilus’ genomes with spacers targeting small ssDNA viruses of the Smacoviridae, supporting and extending the hypothesis of an interaction between smacoviruses and gut associated Methanomassiliicoccales. Gene network analysis shows that methanogens encompass a unique and interconnected MGE repertoire, including novel viral families belonging to head-tailed Caudoviricetes, but also icosahedral and archaeal-specific pleomorphic, spherical, and spindle (pro)viruses. We reveal well-delineated modules for virus-host interaction, genome replication and virion assembly, and a rich repertoire of defense and counter-defense systems suggesting a highly dynamic and complex network of interactions between methanogens and their MGEs. We also identify potential conjugation systems composed of VirB4, VirB5 and VirB6 proteins encoded on plasmids and (pro)viruses of Methanosarcinales, the first report in Euryarchaeota. We identified 15 new families of viruses infecting Methanobacteriales, the most prominent archaea in the gut microbiome. These encode a large repertoire of protein domains for recognizing and cleaving pseudomurein for viral entry and egress, suggesting convergent adaptation of bacterial and archaeal viruses to the presence of a cell wall. Finally, we highlight an enrichment of glycan-binding domains (immunoglobulin-like (Ig-like)/Flg_new) and diversity-generating retroelements (DGRs) in viruses from gut-associated methanogens, suggesting a role in adaptation to host environments and remarkable convergence with phages infecting gut-associated bacteria. Our work represents an important step toward the characterization of the vast repertoire of MGEs associated with methanogens, including a better understanding of their role in regulating their communities globally and the development of much-needed genetic tools.
Major adverse cardiovascular events and hyperuricemia during tuberculosis treatment
Authors: Shin Hong-Joon , Na Young-Ok , Lee Jae-Kyeong , Kho Bo Gun , Kim Tae-Ok , Kim Yu-Il , Lim Sung-Chul , Jeong Sae-Hee , Kwon Yong-Soo 
Published: February 2023

Abstract
Hyperuricemia is common during tuberculosis (TB) treatment, mainly pyrazinamide (PZA). This study investigated the relationship between major adverse cardiovascular events (MACEs) and hyperuricemia during TB treatment.
From January 2010–June 2017, this study retrospectively evaluated TB patients treated in a South Korean tertiary hospital. Hyperuricemia was defined as elevated serum uric acid >7.0 mg/dL (men) and >6.0 mg/dL (women).
A total of 1,143 patients were enrolled in this study, and PZA was used in 1081 (94.6%), while hyperuricemia was detected in 941 (84.4%). Eight patients developed MACEs. Multivariate analysis using logistic regression revealed that previous ischemic heart disease was associated with MACE development (OR, 19.071; 95% CI, 4.648–78.249; P < 0.000), while hyperuricemia was not (OR, 1.505; 95% CI, 0.184–12.299; P = 0.703). Among patients without drug-resistant TB, no hyperuricemia was associated with increased deaths (OR, 2.923; 95% CI, 1.119–7.638; P = 0.029), while hyperuricemia was associated with increased favorable outcomes (OR, 3.366; 95% CI, 1.787–6.340; P < 0.001).
In conclusions, most patients who received PZA had hyperuricemia; however, it was not associated with MACE development. Hyperuricemia during TB treatment was associated with better outcomes, possibly due to good compliance with TB treatment.
On the nature of the interlayer magnetic interactions in biphase ferromagnetic films
Authors: Silva E. F. , Gamino M. , Oliveira A. B. , Correa M. A. , Bohn F. 
Published: February 2023

Abstract
We report on the nature of the interlayer magnetic interactions in NiFe/Cu/Co films.By probing the quasi-static and dynamic magnetic properties of biphase ferromagnetic films, with soft and hard ferromagnetic phases intermediated by a non-magnetic layer, we address aspects of the coupling between magnetic layers. Our results demonstrate the nature of the interlayer magnetic coupling in biphase films. We also disclose the asymmetric magnetoimpedance effect as a fingerprint of the nature of the magnetic interlayer interactions playing key role in the magnetization dynamics of the system. We revisit in literature data and ideas on the asymmetric magnetoimpedance and the nature of the magnetic interactions in biphase ferromagnetic systems. Then, we compare our findings with results for biphase ribbons and microwires. Our observations raise the fundamental similarities and differences in the magnetoimpedance response of these structures, hence providing a single framework to interpret the phenomenon of asymmetric magnetoimpedance.
Social Capital and Economic Growth: A Meta-Analysis
Authors: Xue Xindong , Reed W. Robert , Aert Robbie C. M. van 
Published: February 2023

Abstract
This study collects and analyses 993 estimates from 81 studies to generate an overall assessment of the empirical literature on social capital and economic growth. Using a variety of estimation procedures, we reach the following conclusions. First, there is evidence that a meaningful relationship exists between social capital and economic growth. The estimated sizes of the overall mean effect in our specifications range from somewhat larger than “small” to somewhat larger than “medium” depending on the estimation method we use. Second, our analysis does not indicate that the associated empirical literature is distorted by publication bias. Third, there is evidence to indicate that cognitive social capital (e.g., trust) has a larger effect on economic growth than other types of social capital, though the evidence is not strong. Finally, while the coefficient signs of our meta-regression analysis lined up with prior expectations, the associated effect sizes were generally small to negligible. The most noteworthy finding is that social capital is estimated to have a smaller effect on economic growth in the US compared to other parts of the world.
JEL Classifications: B40, O31, O40, O47, R11, Z10
Optimal Intelligent Information Retrieval and Reliable Storage Scheme for Cloud Environment And E-Learning Big Data Analytics
Authors: Venkatachalam Chandrasekar , Venkatachalam Shanmugavalli 
Published: February 2023

Abstract
Currently, online learning systems in the education sector are widely used and have become a new trend, generating large amounts of educational data based on students' activities. In order to improve online learning experiences, sophisticated data analysis techniques are required. Adding value to E-learning platforms through the efficient processing of big learning data is possible with Big Data. With time, the E-learning management system's repository expands and becomes a rich source of learning materials. Subject matter experts may benefit from using E-learning resources to reuse previously created content when creating online content. In addition, it might be beneficial to the students by giving them access to the pertinent documents for achieving their learning objectives effectively. An improved intelligent information retrieval and reliable storage (OIIRS) scheme is proposed for E-learning using hybrid deep learning techniques. Assume that relevant E-learning documents are stored in cloud and dynamically updated according to users' status. First, we present a highly robust and lightweight crypto i.e. optimized CLEFIA, for securely storing data in local repositories that improve the reliability of data loading. We develop an improved butterfly optimization (IBO) algorithm to provide an optimal solution for CLEFIA that selects private keys. In addition, a hybrid deep learning method, i.e., backward diagonal search based deep recurrent neural network (BD-DRNN) is introduced for optimal intelligent information retrieval based on keywords rather than semantics. Here, feature extraction and key feature matching are performed by the modified Hungarian optimization (MHO) algorithm that improves searching accuracy. Finally, we test our proposed OIIRS scheme with different benchmark datasets and use simulation results to test the performance.
An analysis of atmospheric stability indices and parameters under air pollution conditions
Authors: Yavuz Veli 
Published: February 2023

Abstract

The stability of the atmosphere plays an important role in changes in air pollutant concentrations. Stable atmospheric conditions cause pollutant concentrations to reach high values, which degrades the air quality in a particular region. This study aims to reveal the relationship between atmospheric stability indices/parameters (thermodynamic indices) and changes in air pollutant concentrations. Pollutant concentrations of PM10, PM2.5, SO2, NO2, CO, and O3 were statistically analyzed for a 10-year (2013-2022) period for nine air quality stations located in the megacity Istanbul. Based on national and international air quality standards, 145 episode days were determined for the days when these parameters exceeded the threshold values. Five stability indices (Showalter Index – SI, Lifted Index – LI, Severe Weather Index – SWEAT, K Index – KI, Totals Totals Index – TTI), and three stability parameters (Convective Available Potential Energy – CAPE, Convective Inhibition – CIN, Bulk Richardson Number – BRN) were used to determine the stability of the atmosphere for episode days. It has been found that in cases where air pollutant concentrations are high, the stability parameters reveal the stability of the atmosphere better than the stability indices. It was also found that there was at least one vertical inversion layer on 122 of the 145 episode days, these layers mostly (84%) occurred between the surface and 850 hPa levels, and the layer thicknesses were mostly between 0-250 m (84%).
Landslide susceptibility modeling derived from remote sensing, multi-criteria decision analysis, and GIS techniques: A case study in the Southeast Bohol Province, Philippines
Authors: Tubog Michael Vincent , Villahermosa Ryan Lester , Perong John Glenn 
Published: February 2023

Abstract
The Philippines has conducted several landslide hazard susceptibility mapping over the past years to increase the requirement for vulnerability assessment. As a karstic mountainous region in the country, the southeast Bohol province is accustomed to frequent landslide occurrences, causing hazard risks in adjacent communities. These landslides are generally controlled by both extrinsic (e.g., road network, fault) and intrinsic (e.g., geomorphologic and geologic) factors. Field observation denotes several occurrences along steep slopes and stream banks. However, challenges in updating the landslide hazard susceptibility maps arose from the scarcity of updated field information and high-precision digital elevation models. With data access limitations, this study aims to generate accurate and precise landslide susceptibility models using remote sensing and statistical-based analysis processed in Geographic Information System (GIS). This study uses open-sourced medium-resolution satellite data and digital elevation models to generate and process the eight (8) landslide factor maps such as the geology, slope gradient, aspect, vegetation, proximity to stream and road networks, soil cover, and fault. These maps were analyzed through Analytical Hierarchy Process (AHP) and Fuzzy Logic Overlay. The generated landslide susceptibility models were validated using Forest-based Classification and Regression (FBCR), analysis of variance (ANOVA), and ordinary linear regression. The AHP-based model shows significant accuracy and compatibility with the actual susceptibility of the site since the p-value of the map is 0.031 in ANOVA, while the Fuzzy-based model cannot be considered accurate since it generated a 0.266 p-value result. Moreover, both models were analyzed in FBCR and resulted in a p-value of 2.2x10− 16 in the ordinary linear regression validation, making both as significant landslide prediction models. This result signifies that medium-resolution satellite data can generate accurate and compatible landslide susceptibility and prediction models, and this process will give disaster risk reduction managers an avenue to generate landslide models that are not bounded by data access limitations. It is also noteworthy to indicate the impact of changing climate in the Philippines where extreme cyclones have been frequent for the past years. Such events contribute to the occurrences of slope and river bank erosion and water saturation to the slope causing the periodic distribution of landslides throughout the study area.