Miracle-dz/UniFAR-FTUs huggingface dataset:
Liproxstatin-1 induces cell cycle arrest, apoptosis, and caspase-3/GSDME-dependent secondary pyroptosis in K562 cells

Leukemia is a fatal hematopoietic disorder with a poor prognosis. Drug resistance is inevitable after the long-term use of chemotherapeutic agents. Liproxstatin-1, commonly known as a ferroptosis inhibitor, has never been reported to have anticancer effects. In the present study, the antileukemic role of liproxstatin-1 in K562 leukemia cells was investigated. Liproxstatin-1 inhibited K562 cell proliferation in a doseand time-dependent manner. RNA sequencing revealed several pathways that were affected by liproxstatin-1, such as the G1/S transition of the mitotic cell cycle and extrinsic or intrinsic apoptotic signaling pathways. The results of flow cytometry indicated that liproxstatin-1 arrests the cell cycle at the G1 phase, and even at the G2/M phase. p21WAF1/CIP1, a cyclin-dependent kinase inhibitor, was upregulated. It was also determined that liproxstatin-1 induced BAX and TNF-α expression, which was accompanied by cleavage of caspase-3 and PARP. The caspase-3-specific inhibitor z-DEVD-FMK rescued some of the apoptotic cells. Interestingly, K562 cells were characterized by swelling and plasma membrane rupture when treated with a high concentration of liproxstatin-1, which was inconsistent with the typical apoptotic appearance. Thus, it was hypothesized that apoptosis-mediated pyroptosis occurs during liproxstatin-1-induced cell death. The expression of the hallmark of pyroptosis, the cleaved N-terminal GSDME, increased. Additionally, it was observed that endoplasmic reticulum stress and autophagy were involved in liproxstatin-1-induced cell death. Collectively, liproxstatin-1 induced cell cycle arrest, apoptosis, and caspase-3/GSDME-dependent secondary pyroptosis in K562 leukemia cells, which provides new hope for the treatment of leukemia.
Matrix quality determines the strength of habitat loss filtering on bird communities at the landscape scale

Habitat loss and fragmentation represent a major threat to biodiversity, however, the modulation of its effects by the non-habitat matrix surrounding habitat patches is still undervalued. The landscape matrix might change community assembly in different ways. For example, low-quality matrices can accentuate environmental filtering by reducing resource availability and/or deteriorating abiotic conditions but they may also over limit dispersal of organisms and make communities more prone to ecological drift. To understand how matrix quality modulates the effects of habitat loss, we quantified the relative importance of environmental filter and ecological drift in bird occurrences across both local and landscape gradients of habitat loss embedded in low- and high-quality matrices. We used a trait-based approach to understand habitat loss filtering effects on birds. We found that low-quality matrices, composed mainly of low-productive pasturelands, increased the severity of habitat loss filtering effects for forest specialist birds, but only at the landscape scale. Bird occurrence was in general higher in high-quality matrices, i.e., more heterogeneous and with low-contrasting edges, indicating the role of the matrix quality on attenuating species extinction risks at the landscape scale probably due to mass effect. Moreover, forest specialists presented a strong negative response to habitat loss filtering across different functional traits, while generalists presented a high variability in traits response to habitat loss. We raised evidence in supporting that landscape habitat loss filtering may be relaxed or reinforced depending on the quality of the matrix, evidencing that matrix quality has a strong impact in modulating community assembly processes in fragmented landscapes. In practical terms, it means that improving matrix quality may help in maintaining the high diversity of birds even without any increase in native forest cover.
Incidence of postural hypotension recorded in UK general practice: an electronic health records study

Background Postural hypotension is a common condition associated with adverse outcomes in older adults. General practice plays an important role in identification of the condition. Aim To examine the incidence of postural hypotension between 2008 and 2018 in general practice and how trends vary by age, sex, year, and social deprivation. Design and setting Retrospective cohort study using electronic health records from the IQVIA Medical Research Data (IMRD) between 2008 and 2018. Method Patients were included if they were aged ≥50 years. Incident postural hypotension was identified as a new (first) recording of a postural hypotension code. Recording of incident postural hypotension was estimated per 10 000 person–years at risk (PYAR) according to age, sex, year, and social deprivation. Incident rate ratios were estimated by multivariable Poisson regression. Results Of 2 911 260 patients, 24 973 had an electronic record indicating a new diagnosis of postural hypotension between 2008 and 2018. This was equivalent to 17.9 cases per 10 000 PYAR in males (95% confidence interval [CI] = 17.6 to 18.2) and 16.2 cases per 10 000 PYAR in females (95% CI = 15.9 to 16.5). A significant age–sex interaction was identified. Recorded postural hypotension rate increased with age and social deprivation, and reduced between 2008 and 2018. The rate was higher in males compared with females, particularly in older age groups (>80 years). Conclusion To the authors’ knowledge, this is the first study to quantify incident recorded postural hypotension in general practice. The rate is lower than expected compared with studies in screened older populations. Potential barriers to identification include underreporting, underdetection owing to lack of time and/or poorly standardised methods of measurement, and poor coding. Future research should investigate current practice and approaches for increased detection such as education, practical methods of screening, and standardised measurement of postural blood pressure.
Evaluating the Impact of External Support on Green Building Construction Cost: A Hybrid Mathematical and Machine Learning Prediction Approach

As a fundamental feature of green building cost forecasting, external support is crucial. However, minimal research efforts have been directed to developing practical models for determining the impact of external public and private support on green construction projects’ costs. To fill the gap, the current research aims to develop a mathematical model to explore the balance of supply and demand under deflationary conditions for external green construction support and the accompanying spending adjustment processes. The most current datasets from 3578 green projects across Northern America were collected, pre-processed, analyzed, post-processed, and evaluated via cutting-edge machine learning (ML) techniques to retrieve the deep parameters affecting the green construction cost prediction process. According to the findings, public and private investments in green construction are projected to decrease the cost of green buildings. Furthermore, the impact of public and private investment on green construction cost reduction during deflationary periods is more significant than its influence during inflation. As a result, decision-makers may utilize the suggested model to monitor and evaluate the yearly optimal external investment in green building construction.
Experimental and Computational Approaches for Non-CpG Methylation Analysis

Cytosine methylation adjacent to adenine, thymine, and cytosine residues but not guanine of the DNA is distinctively known as non-CpG methylation. This CA/CT/CC methylation accounts for 15% of the total cytosine methylation and varies among different cell and tissue types. The abundance of CpG methylation has largely concealed the role of non-CpG methylation. Limitations in the early detection methods could not distinguish CpG methylation from non-CpG methylation. Recent advancements in enrichment strategies and high throughput sequencing technologies have enabled the detection of non-CpG methylation. This review discusses the advanced experimental and computational approaches to detect and describe the genomic distribution and function of non-CpG methylation. We present different approaches such as enzyme-based and antibody-based enrichment, which, when coupled, can also improve the sensitivity and specificity of non-CpG detection. We also describe the current bioinformatics pipelines and their specific application in computing and visualizing the imbalance of CpG and non-CpG methylation. Enrichment modes and the computational suites need to be further developed to ease the challenges of understanding the functional role of non-CpG methylation.
Performance analysis of modulation techniques in 5G communication system

In the 5th generation mobile communication (5G) system, better bitrate, better power consumption, and better Bit Error Rate are needed. To meet all these requirements in 5G, the waveform is important. Although the Orthogonal Frequency Division Multiplexing (OFDM) modulation scheme has been commonly used in 4G, it is difficult to meet the requirements of 5G. A lot of candidate waveforms are discussed in the 5G system included Filter Bank Multicarrier (FBMC), Universal Filtered Multicarrier (UFMC), Filtered OFDM (F-OFDM), and Generalized Frequency Division Multiplexing (GFDM), etc. However, since GFDM is no longer widely used, in this paper, FBMC, UFMC, and F-OFDM modulation schemes are discussed and compared with OFDM. Power Spectral Density (PSD), Bit Error Rate (BER), Transmitted Signal Power, Peak Average Power Ratio (PAPR) and Bit Rate parameters of the modulation schemes are studied and compared with OFDM. FBMC demonstrates to be the most promising modulation scheme for 5G systems.
Noun phrase based weghting scheme for sentence similarity measurement

The need for an effective text similarity measures has led many previous studies to propose different text weighting schemes to enhance the overall performance of sentence similarity measures. Term Frequency Inverse Document Frequency (TF-IDF) is a weighting method that is commonly used to determine the occurrence of a term/word in a document. This paper proposes the use of Noun Phrase (NP) based TF-IDF weighting scheme in order to empower the efficiency of text similarity. A total of eight pairs of statements were used to validate the proposed method. The obtained results were then compared with the standard TF-IDF weighting scheme. The result shows that NP-TF-IDF has significantly improved the performance of text similarity measures as compared to the standard TF-IDF. Our findings may offer the necessary insights related to the development of text similarity applications.
Legacy of war: Pedogenesis divergence and heavy metal contamination on the WWI front line a century after battle

In Europe, the First World War left a legacy on the environment due to the extensive and intense use of artillery during this period. This study examined a small wooded area in the Pas‐de‐Calais region in France which was subject to considerably less intense fire than previously studied WWI battlefields. In a process named “bombturbation,” significant physical changes have occurred to the landscape subject to artillery fire, resulting in a divergent soil development in craters. Cratering led to higher organic matter and electrical conductivity values, but—unlike other studies—no significant difference in soil pH. Soil heavy metal concentrations did not differ within craters compared to the flat landscape. However, lead (Pb) and copper (Cu) enrichment was observed above the baseline values for the region. Despite the average concentrations of Cu and Pb being within legal limits for soils in the UK and European Union, it is likely that enrichment of Cu and Pb in the concentrations observed has caused detrimental ecotoxicological and human health effects.
RIS-Assisted Multi-Antenna AmBC Signal Detection Using Deep Reinforcement Learning

Signal detection is one of the most critical and challenging issues in ambient backscatter communication (AmBC) systems. In this paper, a multi-antenna AmBC signal detection method is proposed based on reconfigurable intelligent surface (RIS) and deep reinforcement learning. Firstly, an efficient multi-antenna AmBC system is developed based on RIS, which can achieve information transmission and energy collection simultaneously. Secondly, a smart twin delayed deep deterministic (TD3) AmBC signal detection method is presented, based on deep reinforcement learning. Extensive quantitative and qualitative experiments are performed, which show that the proposed method is more compelling than the outstanding comparison methods.
Tumor Antigenicity and a Pre-Existing Adaptive Immune Response in Advanced BRAF Mutant Colorectal Cancers

Simple Summary BRAF mutant metastatic CRCs (BRAF-mCRCs) are considered a unique clinical entity characterized by a dismal prognosis and that do not respond efficiently to both standard chemotherapy and to orally selective inhibitors of BRAFV600E. In this study, the gene expression profiles of 89 immunotherapy-naïve BRAF-CRCs were generated using the PanCancer IO 360 gene expression panel to improve the knowledge of the mechanisms involved in tumor-suppressive immune functions in BRAF-mCRCs. A significant fraction of BRAF-mCRCs shows a hot/inflamed profile and may be potential candidates for responding to immunotherapy. Only a partial overlap between these hot signatures and the presence of microsatellite instability (MSI) was observed, demonstrating that MSI tumors showed a not differential expression of MHC Class I antigen presentation pathway compared with microsatellite-stable tumors. The analysis of gene expression profiles is a promising strategy both for immune profiling of primary tumors before any treatment and for following the evolution of metastatic disease during therapy. Abstract The main hypothesis of this study is that gene expression profiles (GEPs) integrating both tumor antigenicity and a pre-existing adaptive immune response can be used to generate distinct immune-related signatures of BRAF mutant colorectal cancers (BRAF-CRCs) to identify actionable biomarkers predicting response to immunotherapy. GEPs of 89 immunotherapy-naïve BRAF-CRCs were generated using the Pan-Cancer IO 360 gene expression panel and the NanoString nCounter platform and were correlated with microsatellite instability (MSI) status and with CD8+ tumor-infiltrating lymphocyte (TIL) content. Hot/inflamed profiles were found in 52% of all cases, and high scores of Tumor Inflammation Signature were observed in 42% of the metastatic BRAF-CRCs. A subset of MSI tumors showed a cold profile. Antigen Processing Machinery (APM) signature was not differentially expressed in MSI tumors compared with MSS cases. By contrast, the APM signature was significantly upregulated in CD8+ BRAF-CRCs versus CD8− tumors. Our study demonstrates that a significant fraction of BRAF-CRCs may be a candidate for immunotherapy and that the simultaneous analysis of MSI status and CD8+ TIL content increases accuracy in identifying patients who can potentially benefit from immune checkpoint inhibitors. GEPs may be very useful in expanding the spectrum of patients with BRAF-CRCs who can benefit from immune checkpoint blockade.
Predicting Intercultural Communication in Malaysian Public Universities from the Perspective of Anxiety/Uncertainty Management (AUM) Theory

The mission to promote national unity has become more strenuous with the decline of intercultural engagement among multicultural students in Malaysian public universities. Underpinned by Anxiety/Uncertainty Management (AUM) theory, this article examines barriers to intercultural communication by integrating ethnocentrism as an additional barrier. Based on a quantitative approach, 449 valid responses were collected from undergraduates from five public universities in Malaysia. Partial-least-squares software (SmartPLS3) was used to test the proposed relationships. The findings reveal that anxiety, uncertainty, and ethnocentrism have a significant negative relationship with intercultural communication.
Comparison of Effectiveness and Safety between High-Power Short-Duration Ablation and Conventional Ablation for Atrial Fibrillation: A Systematic Review and Meta-Analysis

Aim We aimed to evaluate the effectiveness and safety between high-power short-duration (HPSD) radiofrequency ablation (RFA) and conventional RFA in patients with atrial fibrillation (AF). Methods Studies comparing HPSD and traditional applications in patients undergoing initial catheter ablation for atrial fibrillation from inception through December 2021 were searched on Pubmed, Medline, Cochrane, and Clinicaltrials.gov. Results The meta-analysis included seventeen studies with a total of 4934 patients. HPSD group decreased procedure duration (mean difference (MD) −38.28 min, P < 0.001), RF duration (MD −20.51 min, P < 0.001), fluoroscopy duration (MD −5.19 min, P < 0.001), and acute pulmonary vein reconnection (Odds ratio (OR) 0.40, P < 0.001), while improving the freedom from atrial arrhythmia at one year (OR 1.48, 95% confidence interval (CI) 1.12–1.94, P=0.005) and rates of first-pass isolation (OR 8.92, P=0.001). Compared with the conventional group, freedom from atrial arrhythmia at one-year follow-up was higher in the HPSD group without the guidance of AI/LSI (OR 1.66, P=0.01) and studies with a power setting of 40–50 W (OR 1.93, P=0.002). Nevertheless, the two groups had similar effectiveness with a power setting of 50 W in the HPSD RFA (OR 1.10, P=0.52). There was no difference in complications between the two groups (P=0.71). Conclusion HPSD RFA was associated with shorter procedure duration, higher freedom from atrial arrhythmia, and comparable safety compared to conventional RFA.
Important Citation Identification by Exploding the Sentiment Analysis and Section-Wise In-Text Citation Weights

A massive research corpus is generated in this epoch based on some previously established concepts or findings. For the acknowledgment of the base knowledge, researchers perform citations. Citations are the key considerations used in finding the different research measures, such as ranking the institutions, researchers, countries, computing the impact factor of journals, allocating research funds, etc. But in calculating these critical measures, citations are treated equally. However, researchers have argued that all citations can never be equally influential. Therefore, researchers have proposed other techniques to identify the important content-based, meta-data-based, and bibliographic-based citations. However, the produced results by the state-of-the-art still need to be improved. In this research work, we proposed an approach based on two primary modules, 1) The section-wise citation count and 2) Sentiment based analysis of citation sentences. The first technique is based on extracting the different sections of the research articles and performing citation count. We applied Neural Network and Multiple Regression on section-wise citations for automatic weight assignment. The citation sentences were extracted in the second approach, and sentiment analysis was used for sentences. Citations were classified with Support Vector Machine, Multilayer Perceptron, and Random Forest. F-measure, Recall, and Precision were considered to evaluate the results, compared with the state-of-the-art results. The value of precision with the proposed approach was enhanced to 0.94.
A Resource-Sensitive Semantics for Equi and Raising

Lexical Functional Grammar (LFG) analyses of equi and raising involve functional control equations, which structure-share the values of grammatical functions, making them token-identical at the level of f(unctional)-structure. Glue semantics for LFG works from f-structure and is resource-sensitive. This seems at first to be incompatible with structure-sharing. It is demonstrated that this is not so. By using LFG’s parallel projection architecture, the Glue analysis of equi proposed here treats the clausal equi complement as denoting a property, which has been argued for on independent grounds by Chierchia (1984). It is also shown that the same approach can provide an analysis of raising in which clausal complements of raising verbs denote propositions, as required. The analysis also explains the ability of raising verbs to take expletive subjects and the inability of equi verbs to do so.
Yeast Diversity in the Qaidam Basin Desert in China with the Description of Five New Yeast Species

The Qaidam Basin is the highest and one of the largest and driest deserts on Earth. It is considered a mars analog area in China. In contrast to numerous studies concerning its geology, geophysical, and chemistry, relatively few studies have reported microbial diversity and distribution in this area. Here, we investigated culturable yeast diversity in the northeast Qaidam Basin. A total of 194 yeast strains were isolated, and 12 genera and 21 species were identified, among which 19 were basidiomycetous yeasts. Naganishia albida, N. adeliensis, and Filobasidium magnum were the three most dominant species and were distributed in thirteen samples from eight locations. Five new species (Filobasidium chaidanensis, Kondoa globosum, Symmetrospora salmoneus, Teunia nitrariae, and Vishniacozyma pseudodimennae) were found and described based on ITS and D1D2 gene loci together with phenotypic characteristics and physiochemical analysis. Representative strains from each species were chosen for the salt-tolerant test, in which species showed different responses to different levels of NaCl concentrations. Further, the strain from soil can adapt well to the higher salt stress compared to those from plants or lichens. Our study represents the first report of the yeast diversity in the Qaidam Basin, including five new species, and also provides further information on the halotolerance of yeasts from the saline environment in mars analog.
Performances of THz cameras with enhanced sensitivity in sub-terahertz region

Uncooled microbolometer-type 640x480 and 320x240 Terahertz (THz) focal plane arrays (FPAs) with enhanced sensitivity in sub-THz region are developed, and incorporated into 640x480 and 320x240 cameras, respectively. The pixel in the THz-FPA has such a structure that an area sensitive to electromagnetic wave is suspended above read-out integrated circuit (ROIC). A thin metallic layer is formed on the top of the sensitive area, while a thick metallic layer is formed on the surface of ROIC. The structure composed of the thin metallic layer and the thick metallic layer behaves as an optical cavity. The THz-FPAs reported in this paper have a modified pixel structure which has several times longer optical-cavity length than NEC’s previous pixel does, by forming a thick SiN layer on the ROIC. The extended optical-cavity structure is favorable for detecting electromagnetic wave with lower frequency. Consequently, the Minimum Detectable Power per pixel (MDP) is improved ten times in sub-THz region, especially 0.5-0.6 THz. This paper presents spectral frequency dependences of MDP values for THz-FPA with the modified pixel structure and THz-FPA with the previous pixel structure, using THz free electron laser (FEL) developed by Osaka University. The modification of pixel structure extends high sensitivity region to lower frequency region, such as sub-THz region, and the wider spectral coverage of THz camera surely expands its applicability