bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of a radiogenomic signature based on endoplasmic reticulum stress for predicting prognosis and systemic combination therapy response in hepatocellular carcinoma
Authors: Wu Huai-Yu , Cao Shu-Ya , Xu Zheng-Gang , Wang Tian , Ji Gu-Wei , Wang Ke 
Published: June 2024

Abstract

Background:Hepatocellular carcinomais one of the most common tumors worldwide. Various factors in the tumor microenvironment can lead to the activation of endoplasmic reticulum stress, thereby affecting the occurrence and development of tumors.The objective of our study was to develop and validate a radiogenomic signature based on endoplasmic reticulum stress to predict prognosis and systemic combination therapy response
Methods:Using data from TCGA as a training cohort and data from ICGC as a testing cohort. Univariate Cox regression and multivariate Cox regression analysis were used to identify prognostic-related genes and construct a model. Hepatocellular carcinoma single-cell data obtained from GEO were used to map gene signatures and explore inter-cellular signaling communications. Finally, a radiogenomic signature was used to predict the objective response rate and overall survival.
Results:A total of four gene signatures related to ERS (including STC2, MAGEA3, BRSK2, DDX11) were identified. Macrophages were significantly different between high-risk and low-risk groups. The high-risk group showed higher PD-1 and mutated TP53 scores. Drug sensitivity analysis found that most sensitive drugs target the PI3K/mTOR signaling pathway. Further research revealed the expression of STC2 in the endothelial cells, particularly PLVAP+ endothelial cells, and may regulate the reprogramming and function of macrophages. Furthermore, we identified nine radiomic features and established a radiogenomic signature based on ERS that can predict prognosis and response to systemic combination therapy. This signature can guide systemic combination therapy for patients with unresectable hepatocellular carcinoma.
Conclusions:We established an ERS prognostic model that can predict patient prognosis. We also found that ERS is closely related to the tumor microenvironment and is mainly manifested in the interaction between tumor-associated endothelial cells and tumor-associated macrophages. Moreover, we constructed a radiogenomic signature based on the ERS. This signature can guide subsequent combination therapy for patients with unresectable HCC.
Prostaglandin I2 signaling prevents angiotensin II-induced atrial remodeling and vulnerability to atrial fibrillation in mice
Authors: Zhang Yue , Yuan Meng , Cai Wenbin , Sun Weiyan , Shi Xuelian , Liu Daiqi , Song Wenhua , Yan Yingqun , Chen Tienan , Bao Qiankun , Zhang Bangying , Liu Tong , Zhu Yi , Zhang Xu , Li Guangping 
Published: June 2024

Abstract

Atrial fibrillation (AF) is the most common arrhythmia, and atrial fibrosis is a pathological hallmark of structural remodeling in AF. Prostaglandin I2 (PGI2) can prevent the process of fibrosis in various tissues via cell surface Prostaglandin I2 receptor (IP). However, the role of PGI2 in AF and atrial fibrosis remains unclear. The present study aimed to clarify the role of PGI2 in angiotensin II (Ang II)-induced AF and the underlying molecular mechanism. PGI2 content was decreased in both plasma and atrial tissue from patients with AF and mice treated with Ang II. Treatment with the PGI2 analog, iloprost, reduced Ang II-induced AF and atrial fibrosis. Iloprost prevented Ang II-induced atrial fibroblast collagen synthesis and differentiation. RNA-sequencing analysis revealed that iloprost significantly attenuated transcriptome changes in Ang II-treated atrial fibroblasts, especially mitogen-activated protein kinase (MAPK)-regulated genes. We demonstrated that iloprost elevated cAMP levels and then activated protein kinase A, resulting in a suppression of extracellular signal-regulated kinase1/2 and P38 activation, and ultimately inhibiting MAPK-dependent interleukin-6 transcription. In contrast, cardiac fibroblast-specific IP-knockdown mice had increased Ang II-induced AF inducibility and aggravated atrial fibrosis. Together, our study suggests that PGI2/IP system protects against atrial fibrosis and that PGI2 is a therapeutic target for treating AF.
The prospectively registered trial was approved by the Chinese Clinical Trial Registry. The trial registration number is ChiCTR2200056733. Data of registration was 2022/02/12.
Comparative skin ultrastructure and transcriptome analysis of indigenous, improved meat goats, and dairy goats breeds identified key genes and potential molecular mechanisms affecting goatskin quality
Authors: Hou Xiling , Wang Xianwei , Hou Shuang , Dang Jiangyang , Zhang Xinyu , Tang Jianxiang , Shi Yinghua , Ma Sen , Xu Zejun 
Published: June 2024

Abstract

Background
High-quality goatskins are valuable byproducts usually produced by indigenous goat breeds with poorer production performance in Asia and Africa. However, the genetic and molecular mechanisms underpinning goatskin's biomechanical properties (e.g., tensile strength) remain elusive. Mechanistic exploration of these traits could greatly aid the genetic improvement and genetic resource conservation of native breeds in these regions. To fulfill this purpose, we collected skin tissues from three goat breeds: huai goat (HG), a Chinese native variety producing high-quality goatskins; yudong meat goat (YDMG), a crossbreed of HG and Boer goat; Henan dairy goat (HNDG), a dairy goat breed.
Results
Scanning electronic microscopy analysis of skin tissues found that the collagen fiber diameters, collagen fibril diameters, and crimps significantly differed among the three goat breeds; however, collagen fibril diameters are similar in HG and HNDG. A sum of 230, 775, and 86 differentially expressed genes (DEGs) were identified from YDMG versus HNDG, HG versus HNDG, and YDMG versus HG, respectively. Functional enrichment analysis suggested that signaling pathways involved in fatty acid, retinol, steroid metabolisms, and GO items related to the physical properties of the skin (e.g., collagen-containing extracellular matrix) are significantly overrepresented in DEGs identified from meat versus dairy goats. Furthermore, 106 DEGs (e.g., COL1A1, COL1A2, and SPARC) showed specific expression patterns in HG and YDMG versus HNDG. Items about biophysical features of skin (e.g., extracellular matrix organization and ECM proteoglycans) are markedly enriched. Protein-protein interaction analysis suggested that two growth factors (IGF1 and PDGFD) are latent collagen and other ECM protein expression modulators.
Conclusion
Our study provided preliminary ultrastructural and transcriptomic insights into factors and molecular mechanisms potentially governing goatskin quality. Furthermore, a group of genes, hormones, and growth factors involved in the development and structure of goat skin tissues were identified.
Determination of 229 pesticides residue in edible oil samples using conventional QuEChERS method and solid phase microextraction based on monolithic molecularly imprinted polymer fiber and analysis with GC-MS
Authors: kardani Fatemeh , Jelyani Aniseh zarei , Khezeli Tahere , Hashemi Mohammad , Rashedinia Marzieh , Shariati Saeedeh , Mahdavinia Masoud , Noori Seyyed Mohammad Ali 
Published: June 2024

Abstract

The goal of this research is development of solid phase microextraction based on monolithic molecularly imprinted polymer fiber (SPME-MMIPF) method to determine 229 pesticides in edible oil samples using gas chromatography-mass spectrometry (GC-MS) and comparison of it with the common QuEChERS method. In QuEChERS method, acetonitrile used as extraction solvent and magnesium sulfate used as water absorbing agent. For SPME-MMIPF method, an MMIPF was synthesized by polymerization of methacrylic acid in presence of ethylene glycoldimethacrylate and azo (bis)-isobutyronitrile. The optimal conditions for the SPME-MMIPF method are: extraction time 30 min, desorption time with toluene 20 min and string speed of the aqueous sample 600 rpm. Under optimal extraction condition, the figures of merit were obtained for two methods and compared. The linear range of 1-300 µg kg− 1 for SPME-MMIPF and 10–250 µg kg− 1 for QuEChERS was obtained. The detection limit of SPME-MMIPF (0.321–0.335 µg kg− 1) method was better than the QuEChERS (0.9–2.6 µg kg− 1) method. The results showed a quantification limit of 0.8–2.2 µg kg− 1 for SPME-MMIPF and 1.5–5.2 µg kg− 1 for QuEChERS. The recoveries were in the range of 92–102% and 68–127% for SPME-MMIPF and QuEChERS, respectively.
Analyze the spatial-temporal changes and their environmental impacts on tourist spots in the Chittagong hill tract area of Bangladesh
Authors: Alzaber Md , Islam Md.Rahedul 
Published: June 2024

Abstract

Tourism is related to the cost degradation of the environment and affects the social and cultural spectrum. The growth of the tourism and hospitality sector greatly impacts the environment of mountain tourist areas of Bangladesh. For this, it examines the LULC (Land Use Land Cover) change detection in tourist areas and analyzes its environmental impacts. Analyzing the LULC, NDVI (Normalized Difference Vegetation Index), and NDBI (Normalized Difference Built-Up Index) would help to know about the LULCC detection before 20 years of difference between the tourist spots Sajek, Himchari & Nilgiri by Landsat 5, Landsat 8 & Sentinel-2 satellite imagery and analyzing the LST (Land Surface Temperature) and annual rainfall data which discovers to analyze its environmental impact. Data collection, Satellite image pre-processing, Supervised image Classification, Accuracy Assessment, NDVI, NDBI, LST, and annual rainfall data are processed by the Google Earth Engine code editor with individual code and Area Calculation, LULC change detection, map analysis & design are performed by QGIS 3.28 & 2.18. LULC, NDVI, and NDBI show an increase in urban areas and a decrease in the vegetation rapidly another LST significantly increased, and annual rainfall has decreased in the last 20 years (2003–2023) which can cause the worst climatic condition of the tourists spots environmentally hazardous landslide, cyclone, saline water inundation, forest fire are influencing by rapid growth of urbanization.
Multifunctional radiative cooling cellulose fabrics by in situ grown ZnO for Personal Thermal Management
Authors: Ma Ruijie , Xue Tong , Yu Guo , Yin Yunjie 
Published: June 2024

Abstract

Personal thermal management textiles (PTMs) with cooling functions have garnered substantial interest because of their ability to regulate human body temperature and provide comfort through low energy consumption. However, the preparation of cellulose fabrics such as cotton with cooling function remains a challenge due to the often complex process of developing such textiles. A composite functional cellulosic fabric, based on cotton, is presented in this research to address the various inconveniences caused by hot summer weather. Controlled in situ growth of zinc oxide is achieved through hydrothermal synthesis. The ZnO nanorods deposited on the surface of the cotton fabric have excellent UV shielding ability and synergise solar reflection in the UV band, resulting in a UPF value of 300 + for the modified fabric, and this performance still reaches 80.25 after 100 friction cycles.The surface of the modified cotton fabric has a high solar reflectance (83.88%) and a high heat transfer coefficient (98 W·m− 2·K− 1), and a cooling effect of 3.0°C can be achieved in a simulated heating environment compared with that of the original cotton. Due to these excellent properties and simple operation steps, the cool-feeling fabrics made by in situ growth of ZnO nanorods on the surface of cotton fabrics have certain application prospects.
Explainability and Importance Estimate of TimeSeries Classifier via Embedded Neural Network
Authors: Chan Ho Tung Jeremy , Šimić Ilija , Veas Eduardo 
Published: June 2024

Abstract

Time Series is sequential data with temporal relationship of causality. Time Series can be univariate, a single ordered data sequence, or multivariate, a collection of more than one ordered data sequences. Multivariate Time Series are complex with inter- and intra-relationship between the ordered data sequences. Time Series is common across disciplines and can benefit from insightful analysis.However, analysis of interpretation and importance estimate within a Time Series context is scarce, especially Neural Network (NN) related approaches.In this work, we demonstrate NN related approaches upon Time Series with the aim of explainability and importance estimate of embedded NN classifers. We conducted an empirical study with univariate and multivariate Time Series, where we compared interpretation and importance estimate from existing embedded NN approaches, an explainable AI (xAI) approach, and our adapted method of Pairwise Importance Estimate Extension from previously. We verified interpretation and importance estiamte via ground truth when it is available, or via a combined approach of Sensitivity Analysis and Reduce and Retrain, where we Retrain with Leave-One-Out and Singleton subsets.
Regional resource evaluation and distribution for onshore carbon dioxide storage and utilization in Uzbekistan
Authors: Kamolov Azizbek , Turakulov Zafar , Norkobilov Adham , Variny Miroslav , Fallanza Marcos 
Published: June 2024

Abstract

Addressing the escalating threat of climate change requires a global response, with significant actions from every nation. Uzbekistan, a member of the Paris Agreement, is actively pursuing sustainable development by reducing greenhouse gas emissions and promoting renewable energy. However, the country's Green Economy strategies currently lack Carbon Capture, Storage, and Utilization (CCSU) technology. A feasibility assessment is crucial to evaluating CCSU's potential for achieving net-zero emissions, benefiting both the public and scientific communities by informing policy decisions and providing valuable data. The primary aim of this study is to evaluate Uzbekistan’s potential for carbon dioxide (CO2) storage and utilization (CSU) in the near and mid-term. To achieve this, this work proposes a methodology for efficient CO2 source-sink matching to facilitate the deployment of CCSU technologies in Uzbekistan. Resource evaluation and spatial analysis methods are used to estimate the total CSU capacity of the region and the geographical distribution of CO2 sources in two large-scale emitting sectors, specifically from the power and cement plants. According to the results, Uzbekistan has an annual CSU capacity of 1171 million tonnes CO2, which is several times higher than the annual CO2 emission rate. Additionally, CSU resources are primarily located in the eastern, western, and southern regions of the country, while CO2 sink locations near the capital city and its surrounding areas are limited compared to their abundance of CO2 sources. Overall, while the country has ample CO2 storage capacity for CCSU deployment, the prospects for its chemical utilization remain limited in scale.
Machine Learning for Diagnosing Water Potability and Explainable AI for Contextual Insights
Authors: Hossain Md. Mamun , Rahman Md. Hasibur , Rahman Md. Ashiqur , Ahmed Humayra 
Published: June 2024

Abstract

Availability of water is one of the most important aspects of Earth’s status as the only planet capable of supporting life. Although water makes up 70% of the earth’s surface, the availability of drinkable water is extremely limited. Water makes up about 70% of the human body and aids in the healthy functioning of the human body. Contaminated water can have a pernicious effect on the human body, thus it’s important to find a safe drinking water source. Five machine learning algorithms were explored to estimate the potability of water in this study. Three regression algorithms are applied to estimate the missing values in this study. Among the implemented, a Deep Neural Network (DNN) model achieves a better accuracy of 66.1%, with precision, recall, and AUC scores of 61.2%, 35.8%, and 67%, respectively which is comparable with the present state-of-the-art. The Support Vector Machine (SVM) applied has achieved the highest precision and the lowest recall, despite having the second-highest accuracy of 65.1% in this study. AdaBoost (ADB) achieves the highest recall of 44.1%, as well as the highest AUC score of 74.5%. In addition, a local explanation artificial algorithm called LIME is applied to explain why a certain sample of water is potable.
Surface highlight removal method for metal ingots in variablelighting conditions based on double-mask-guided CycleGANnetwork
Authors: Liu Jiazhen , Xu Degang 
Published: June 2024

Abstract

This paper introduces a novel method for removing highlights from the surface of metal ingots, which is a critical pre-processing task for ingot detection and quality assessment. The highlight removal problem is further complicated by the huge area, high intensity, and color similarity to the background, as well as the difficulties of gathering a sufficient number of labeled datasets for network training. To overcome these, this paper proposes a Cycle-GAN network based on double-mask guidance to remove highlight signals from unlabeled metal ingots. This network utilizes double-mask guidance to extract features from both highlight and highlight-free areas in the image. Additionally, a residual attention module and a channel attention module are incorporated to enhance the representation of regional features. To enhance the restoration of texture structural information within the highlight regions, we propose a Texture Recovery Attention Module. This module utilizes extracted features from highlight-free regions to compute similarity attention, effectively combining texture features within the highlight regions and transferring the texture information. For training the proposed network, we introduce a highlight-robust feature perception loss function that supervises the training of the network. Experimental results demonstrate that the proposed method achieves the best result in the task of removing highlights from metal surfaces, preserving more detailed texture information. To verify the generality of the method, we conducted experiments on the SHIQ dataset and achieved better results in the recovery of details. Finally, we verify the effectiveness of each module through ablation experiments.
Target-Oriented Reference Construction for supervised cell-type identification in scRNA-seq
Authors: Wei Xin , Ma Wenjing , Wu Zhijin , Wu Hao 
Published: June 2024

Abstract

Cell-type identification is the most crucial step in single cell RNA-seq (scRNA-seq) data analysis, for which the supervised cell-type identification method is a desired solution due to the accuracy and efficiency. The performance of such methods is highly dependent on the quality of the reference data. Even though there are many supervised cell-type identification tools, there is no method for selecting and constructing reference data. Here we develop Target-Oriented Reference Construction (TORC), a widely applicable strategy for constructing reference given target dataset in scRNA-seq supervised cell-type identification. TORC alleviates the differences in data distribution and cell-type composition between reference and target. Extensive benchmarks on simulated and real data analyses demonstrate consistent improvements in cell-type identification from TORC. TORC is freely available at https://github.com/weix21/TORC.
A Label-Free Quantification Method for Assessing Sex from Modern and Ancient Bovine Tooth Enamel
Authors: Kotli Paula 
Published: June 2024

Abstract

Identification of the sex of modern, fossil and archaeological animal remains offers many insights into their demography, mortality profiles and domestication pathways. However, due to manifold factors, sex determination of osteological remains is often problematic. To overcome this, we have developed an innovative protocol to determine an animal’s sex from tooth enamel, by applying label-free quantification (LFQ) of two unique AmelY peptides ‘LRYPYP’ (AmelY;[M+2]2+ 404.7212 m/z) and ‘LRYPYPSY’ (AmelY;[M+2]2+ 529.7689 m/z) that are only present in the enamel of males. We applied this method to eight modern cattle (Bos taurus) of known sex, and correctly assigned them to sex. We then applied the same protocol to twelve archaeological Bos teeth from the Neolithic site of Beisamoun, Israel (8th–7th millennium BC) and determined the sex of the archaeological samples. Since teeth are usually better preserved than bones, this innovative protocol has potential to facilitate sex determination in ancient and modern bovine remains, that currently cannot be sexed.
Evaluation of the impact of anthropogenic storage on the hydrological drought propagation in two contrasting semi-arid river basins
Authors: Pachore Akshay , Agrawal Nirav , Omonov Nurmuhammadkhon , Rakhmonov Komiljon , Umirzakov Gulomjon , Mujumdar Sanskriti , Remesan Renji 
Published: June 2024

ABSTRACT
This study quantitatively investigated reservoir-effects on drought propagation in two semi-arid river basins: India’s Tapi basin with the Ukai reservoir and Uzbekistan’s Chirchik basin with the Charvak reservoir. Meteorological drought (MD) is analyzed using the Standardized Precipitation Index (SPI) and hydrological drought (HD) using the Standardized Streamflow Index (SSI) for the duration from 1980 to 2004. Both the river basins, especially in upstream reservoir areas, exhibited a notable correlation between HD and MD. Reservoir operation was observed to reduce the downstream MD–HD correlation at shorter SPI timescales. Hit-score-based evaluations indicated that reservoir operation has induced changes in the drought propagation patterns for both river basins. Due to the contrasting characteristics, the river basins showed a significant variation in the drought propagation time (DPT), with distinct influences from monsoon (Tapi) and snow-melting (Chirchik). The average DPT (average DPT over 12 months) for the reservoir-influenced part of the Tapi (∼ six months) and Chirchik (∼ nine months) basins is higher than that of the natural parts of both basins (Tapi: ∼ four months; Chirchik: ∼ six months) as a result of the natural and anthropogenic storage influence.
Optical Molecular Probes for Imaging and Early Diagnosis of Acute
Kidney Injury
Authors: He Junbing , Chen Zhenzhou , Lin Yao , Liu Qinghua 
Published: June 2024

Abstract::
The kidneys play an irreplaceable role in metabolism and excretion. However,
Acute Kidney Injury (AKI) often occurs due to high local concentrations of drugs, inflammation,
and trauma. Activated optical probes with excellent detection performance
can effectively identify biomarkers in the initial stage of AKI and play an important role
in evaluating AKI and preventing the development of diseases. This article summarizes
representative design strategies for molecular probes and special diagnostic applications.
These molecular probes show great potential in basic research and clinical diagnosis, enabling
enhanced images of tissue structure and biomarkers, as well as early diagnosis of
AKI. In addition, the difficulties and challenges that optical probes may face in the development
and application of AKI are also discussed in this article.