bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kinetic characterization of human mRNA guanine-N7 methyltransferase
Authors: Perveen Sumera , Yazdi Aliakbar Khalili , Hajian Taraneh , Li Fengling , Vedadi Masoud 
Published: February 2024

AbstractThe 5′-mRNA-cap formation is a conserved process in protection of mRNA in eukaryotic cells, resulting in mRNA stability and efficient translation. In humans, two methyltransferases, RNA cap guanine-N7 methyltransferase (hRNMT) and cap-specific nucleoside-2′-O-methyltransferase 1 (hCMTr1) methylate the mRNA resulting in cap0 (N7mGpppN-RNA) and cap1 (N7mGpppN2′-Om-RNA) formation, respectively. Coronaviruses mimic this process by capping their RNA to evade human immune systems. The coronaviral nonstructural proteins, nsp14 and nsp10-nsp16, catalyze the same reactions as hRNMT and hCMTr1, respectively. These two viral enzymes are important targets for development of inhibitor-based antiviral therapeutics. However, assessing the selectivity of such inhibitors against human corresponding proteins is crucial. Human RNMTs have been implicated in proliferation of cancer cells and are also potential targets for development of anticancer therapeutics. Here, we report the development and optimization of a radiometric assay for hRNMT, full kinetic characterization of its activity, and optimization of the assay for high-throughput screening with a Z-factor of 0.79. This enables selectivity determination for a large number of hits from various screening of coronaviral methyltransferases, and also screening hRNMT for discovery of inhibitors and chemical probes that potentially could be used to further investigate the roles RNMTs play in cancers.
Dynamic and distinct histone modifications facilitate human trophoblast lineage differentiation
Authors: Lee Bum-Kyu , Salamah Joudi , Cheeran Elisha , Adu-Gyamfi Enoch Appiah 
Published: February 2024

AbstractThe placenta serves as an essential organ for fetal growth throughout pregnancy. Histone modification is a crucial regulatory mechanism involved in numerous biological processes and development. Nevertheless, there remains a significant gap in our understanding regarding the epigenetic regulations that influence trophoblast lineage differentiation, a fundamental aspect of placental development. Here, through comprehensive mapping of H3K4me3, H3K27me3, H3K9me3, and H3K27ac loci during the differentiation of trophoblast stem cells (TSCs) into syncytiotrophoblasts (STs) and extravillous trophoblasts (EVTs), we reveal dynamic reconfiguration in H3K4me3 and H3K27ac patterns that establish an epigenetic landscape conducive to proper trophoblast lineage differentiation. We observe that broad H3K4me3 domains are associated with trophoblast lineage-specific gene expression. Unlike embryonic stem cells, TSCs lack robust bivalent domains. Notably, the repression of ST- and EVT-active genes in TSCs is primarily attributed to the weak H3K4me3 signal rather than bivalent domains. We also unveil the inactivation of TSC enhancers precedes the activation of ST enhancers during ST formation. Our results provide a comprehensive global map of diverse histone modifications, elucidating the dynamic histone modifications during trophoblast lineage differentiation.
Biomarker screening using integrated bioinformatics for the development of “normal—impaired glucose intolerance—type 2 diabetes mellitus”
Authors: Luo Dongqiang , Gao Xiaolu , Zhu Xianqiong , Xu Jiongbo , Gao Pengfei , Zou Jiayi , Fan Qiaoming , Xu Ying , Liu Tian 
Published: February 2024

AbstractType 2 diabetes mellitus (T2DM) is a progressive disease. We utilized bioinformatics analysis and experimental research to identify biomarkers indicative of the progression of T2DM, aiming for early detection of the disease and timely clinical intervention. Integrating Mfuzz analysis with differential expression analysis, we identified 76 genes associated with the progression of T2DM, which were primarily enriched in signaling pathways such as apoptosis, p53 signaling, and necroptosis. Subsequently, using various analytical methods, including machine learning, we further narrowed down the hub genes to STK17A and CCT5. Based on the hub genes, we calculated the risk score for samples and interestingly found that the score correlated with multiple programmed cell death (PCD) pathways. Animal experiments revealed that the diabetes model exhibited higher levels of MDA and LDH, with lower expression of SOD, accompanied by islet cell apoptosis. In conclusion, our study suggests that during the progression of diabetes, STK17A and CCT5 may contribute to the advancement of the disease by regulating oxidative stress, programmed cell death pathways, and critical signaling pathways such as p53 and MAPK, thereby promoting the death of islet cells. This provides substantial evidence in support of further disease prevention and treatment strategies.
Modeling the Brazilian Cerrado land use change highlights the need to account for private property sizes for biodiversity conservation
Authors: Colman Carina Barbosa , Guerra Angélica , Almagro André , de Oliveira Roque Fabio , Rosa Isabel M. D. , Fernandes Geraldo Wilson , Oliveira Paulo Tarso S. 
Published: February 2024

AbstractSimulating future land use changes can be an important tool to support decision-making, especially in areas that are experiencing rapid anthropogenic pressure, such as the Cerrado–Brazilian savanna. Here we used a spatially-explicit model to identify the main drivers of native vegetation loss in the Cerrado and then extrapolate this loss for 2050 and 2070. We also analyzed the role of property size in complex Brazilian environmental laws in determining different outcomes of these projections. Our results show that distance to rivers, roads, and cities, agricultural potential, permanent and annual crop agriculture, and cattle led to observed/historical loss of vegetation, while protected areas prevented such loss. Assuming full adoption of the current Forest Code, the Cerrado may lose 26.5 million ha (± 11.8 95% C.I.) of native vegetation by 2050 and 30.6 million ha (± 12.8 95% C.I.) by 2070, and this loss shall occur mainly within large properties. In terms of reconciling conservation and agricultural production, we recommend that public policies focus primarily on large farms, such as protecting 30% of the area of properties larger than 2500 ha, which would avoid a loss of more than 4.1 million hectares of native vegetation, corresponding to 13% of the predicted loss by 2070.
Circulating miR-let7a levels predict future diagnosis of chronic thromboembolic pulmonary hypertension
Authors: Kenneweg Franziska , Hobohm Lukas , Bang Claudia , Gupta Shashi K. , Xiao Ke , Thum Sabrina , Ten Cate Vincent , Rapp Steffen , Hasenfuß Gerd , Wild Philipp , Konstantinides Stavros , Wachter Rolf , Lankeit Mareike , Thum Thomas 
Published: February 2024

AbstractDistinct patterns of circulating microRNAs (miRNAs) were found to be involved in misguided thrombus resolution. Thus, we aimed to investigate dysregulated miRNA signatures during the acute phase of pulmonary embolism (PE) and test their diagnostic and predictive value for future diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH). Microarray screening and subsequent validation in a large patient cohort (n = 177) identified three dysregulated miRNAs as potential biomarkers: circulating miR-29a and miR-720 were significantly upregulated and miR-let7a was significantly downregulated in plasma of patients with PE. In a second validation study equal expression patterns for miR-29a and miR-let7a regarding an acute event of recurrent venous thromboembolism (VTE) or deaths were found. MiR-let7a concentrations significantly correlated with echocardiographic and laboratory parameters indicating right ventricular (RV) dysfunction. Additionally, circulating miR-let7a levels were associated with diagnosis of CTEPH during follow-up. Regarding CTEPH diagnosis, ROC analysis illustrated an AUC of 0.767 (95% CI 0.54–0.99) for miR-let7a. Using logistic regression analysis, a calculated patient-cohort optimized miR-let7a cut-off value derived from ROC analysis of ≥ 11.92 was associated with a 12.8-fold increased risk for CTEPH. Therefore, miR-let7a might serve as a novel biomarker to identify patients with haemodynamic impairment and as a novel predictor for patients at risk for CTEPH.
The potato rhizosphere microbiota correlated to the yield of three different regions in Korea
Authors: Bak Gye-Ryeong , Lee Kiseok Keith , Clark Ian M. , Mauchline Tim H. , Kavamura Vanessa Nessner , Lund George , Jee Samnyu , Lee Jeong-Tae , Kim Hyun , Lee Yong-Hwan 
Published: February 2024

AbstractWe examined potato rhizosphere bacterial and fungal communities across three regions: Cheongju, Pyeongchang, and Gangneung. These regions have varying soil and climate conditions, resulting in different yields. We found that precipitation was the main limiting factor in our study while soil physiochemical factors affect bacterial and fungal microbiota in correlation with yield. Both bacterial and fungal microbiota showed distinct patterns according to the regions. ASVs positively correlated with yield were predominantly found in the Pyeongchang region which also produced the highest yields, while ASVs negatively correlated with yield were associated with Gangneung where the lowest yields were observed. The greatest bacterial and fungal diversity was detected in Pyeongchang consisting of Propionibacteriales, Burkholderiales, and Vicinamibacteriales. Gangneung, on the other hand primarily belong to Sordariales, Mortierellales, Cystofilobasidiales, and Tremellales. The putative yield-negative ASVs detected in Gangneung may have been influenced by drought stress. This work has highlighted key bacterial and fungal taxa as well as core taxa that may potentially be associated with high and low yields of potato in relation to metadata which includes soil chemical and physical parameters as well as weather data. Taken together we suggest that this information can be used to assess site suitability for potato production.
An improved sparrow search algorithm and CNN-BiLSTM neural network for predicting sea level height
Authors: Li Xiao , Zhou Shijian , Wang Fengwei , Fu Laiying 
Published: February 2024

AbstractAccurate prediction of sea level height is critically important for the government in assessing sea level risk in coastal areas. However, due to the nonlinear, time-varying and highly uncertain characteristics of sea level change data, sea level prediction is challenging. To improve the accuracy of sea level prediction, this paper uses a new swarm intelligence algorithm named the sparrow search algorithm (SSA), which can imitate the foraging behavior and antipredation behavior of sparrows, to determine optimal solutions. To avoid the algorithm falling into a local optimal situation, this paper integrates the sine–cosine algorithm and the Cauchy variation strategy into the SSA to obtain an algorithm named the SCSSA. The SCSSA is used to optimize the parameter values of the CNN-BiLSTM (convolutional neural network combined with bidirectional long short-term memory neural network) model; finally, a combined neural network model (named SCSSA-CNN-BiLSTM) is proposed. In this paper, the time series data of seven tidal stations located in coastal China are used for experimental analysis. First, the SCSSA-CNN-BiLSTM model is compared with the CNN-BiLSTM model to predict the time series data of SHANWEI Station. With respect to the training and test sets of data, the SCSSA-CNN-BiLSTM model outperforms the other models on all the evaluation metrics. In addition, the remaining six tide station datasets and five neural network models, including the SCSSA-CNN-BiLSTM model, are used to further study the performance of the proposed prediction model. Four evaluation indices including the root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) are adopted. For six stations, the RMSE, MAE, MAPE and R2of SCSSA-CNN-BiLSTM model are ranged from 20.9217 ~ 27.8427 mm, 9.4770 ~ 17.8603 mm, 0.1322% ~ 0.2482% and 0.9119 ~ 0.9759, respectively. The experimental analysis results show that the SCSSA-CNN-BiLSTM model makes effective predictions at all stations, and the prediction performance is better than that of the other models. Even though the combination of SCSSA algorithm may increase the complexity of the model, indeed the proposed model is a new prediction method with good accuracy and robustness for predicting sea level change.
Implantable theranostic device for in vivo real-time NMR evaluation of drug impact in brain tumors
Authors: Deborne Justine , Benkhaled Imad , Bouchaud Véronique , Pinaud Noël , Crémillieux Yannick 
Published: February 2024

AbstractThe evaluation of the efficacy of a drug is a fundamental step in the development of new treatments or in personalized therapeutic strategies and patient management. Ideally, this evaluation should be rapid, possibly in real time, easy to perform and reliable. In addition, it should be associated with as few adverse effects as possible for the patient. In this study, we present a device designed to meet these goals for assessing therapeutic response. This theranostic device is based on the use of magnetic resonance imaging and spectroscopy for the diagnostic aspect and on the application of the convection-enhanced delivery technique for the therapeutic aspect. The miniaturized device is implantable and can be used in vivo in a target tissue. In this study, the device was applied to rodent glioma models with local administration of choline kinase inhibitor and acquisition of magnetic resonance images and spectra at 7 Tesla. The variations in the concentration of key metabolites measured by the device during the administration of the molecules demonstrate the relevance of the approach and the potential of the device.
Extracting interpretable features for pathologists using weakly supervised learning to predict p16 expression in oropharyngeal cancer
Authors: Adachi Masahiro , Taki Tetsuro , Sakamoto Naoya , Kojima Motohiro , Hirao Akihiko , Matsuura Kazuto , Hayashi Ryuichi , Tabuchi Keiji , Ishikawa Shumpei , Ishii Genichiro , Sakashita Shingo 
Published: February 2024

AbstractOne drawback of existing artificial intelligence (AI)-based histopathological prediction models is the lack of interpretability. The objective of this study is to extract p16-positive oropharyngeal squamous cell carcinoma (OPSCC) features in a form that can be interpreted by pathologists using AI model. We constructed a model for predicting p16 expression using a dataset of whole-slide images from 114 OPSCC biopsy cases. We used the clustering-constrained attention-based multiple-instance learning (CLAM) model, a weakly supervised learning approach. To improve performance, we incorporated tumor annotation into the model (Annot-CLAM) and achieved the mean area under the receiver operating characteristic curve of 0.905. Utilizing the image patches on which the model focused, we examined the features of model interest via histopathologic morphological analysis and cycle-consistent adversarial network (CycleGAN) image translation. The histopathologic morphological analysis evaluated the histopathological characteristics of image patches, revealing significant differences in the numbers of nuclei, the perimeters of the nuclei, and the intercellular bridges between p16-negative and p16-positive image patches. By using the CycleGAN-converted images, we confirmed that the sizes and densities of nuclei are significantly converted. This novel approach improves interpretability in histopathological morphology-based AI models and contributes to the advancement of clinically valuable histopathological morphological features.
The diagnostic performance evaluation of Panbio and STANDARD Q coronavirus disease 2019 antigen tests against real-time polymerase chain reaction in southern Ethiopia
Authors: Tamene Elias , Beyene Alemitu , Atsbeha Hanibale , Shimelis Techalew 
Published: February 2024

AbstractThe coronavirus disease 2019 (COVID-19) pandemic has created a public health crisis. This study aimed to evaluate the diagnostic performance of the Panbio and STANDARD Q COVID-19 antigen rapid diagnostic tests (RDTs) against the real-time polymerase chain reaction (RT-PCR) at one of the largest hospitals in southern Ethiopia. Nasopharyngeal samples, which were collected during the pandemic from individuals suspected of COVID-19 and stored at − 70 °C, were analyzed in June and July 2022. The performance of the Panbio COVID-19 antigen tests was evaluated in 200 randomly selected nasopharyngeal samples (100 positives and 100 negatives for severe acute respiratory syndrome 2 by RT-PCR). The STANDARD Q test was evaluated using 100 positive and 50 negative samples. The respective sensitivity, specificity, positive predictive value and negative predictive values were 88%, 99%, 98.9% and 89.2% for the Panbio test and 91%, 98%, 98.9% and 84.5%, for the STANDARD Q test. The kappa values were 0.87 for the Panbio and 0.86 for the STANDARD Q test. Based on the findings presented here, the RDTs could be utilized as an alternative to conventional RT-PCR when it is challenging to diagnose COVID-19 owing to a lack of time, skilled lab personnel, or suitable equipment or electricity.
Efficiency optimization in quantum computing: balancing thermodynamics and computational performance
Authors: Śmierzchalski Tomasz , Mzaouali Zakaria , Deffner Sebastian , Gardas Bartłomiej 
Published: February 2024

AbstractWe investigate the computational efficiency and thermodynamic cost of the D-Wave quantum annealer under reverse-annealing with and without pausing. Our demonstration on the D-Wave 2000Q annealer shows that the combination of reverse-annealing and pausing leads to improved computational efficiency while minimizing the thermodynamic cost compared to reverse-annealing alone. Moreover, we find that the magnetic field has a positive impact on the performance of the quantum annealer during reverse-annealing but becomes detrimental when pausing is involved. Our results, which are reproducible, provide strategies for optimizing the performance and energy consumption of quantum annealing systems employing reverse-annealing protocols.
Diabetes mellitus modifies the association between chronic kidney disease–mineral and bone disorder biomarkers and aortic stiffness in peritoneal dialysis patients
Authors: Huang Hsiang-Jung , Hsu Bang-Gee , Wang Chih-Hsien , Tsai Jen-Pi , Chen Yi-Hsin , Hung Szu-Chun , Lin Yu-Li 
Published: February 2024

AbstractThis study aimed to investigate the relationship of four chronic kidney disease–mineral and bone disorder (CKD–MBD) biomarkers, including intact parathyroid hormone (PTH), fibroblast growth factor 23 (FGF23), soluble klotho, and fetuin-A, with aortic stiffness in peritoneal dialysis (PD) patients, comparing those with and without diabetes mellitus (DM). A total of 213 patients (mean age 58 ± 14 years; 81 (38.0%) patients with DM) were enrolled. Their aortic pulse wave velocity (PWV) was measured using pressure applanation tonometry, while serum intact PTH, FGF23, α-klotho, and fetuin-A levels were measured using enzyme-linked immunosorbent assay. Overall, patients with DM had higher aortic PWV than those without (9.9 ± 1.8 vs. 8.6 ± 1.4 m/s, p < 0.001). Among the four CKD–MBD biomarkers, FGF23 levels were significantly lower in DM group (462 [127–1790] vs. 1237 [251–3120] pg/mL, p = 0.028) and log-FGF23 independently predicted aortic PWV in DM group (β: 0.61, 95% confidence interval: 0.06–1.16, p = 0.029 in DM group; β: 0.10, 95% confidence interval: − 0.24–0.45, p = 0.546 in nonDM group; interaction p = 0.016). In conclusion, the association between FGF23 and aortic PWV was significantly modified by DM status in PD patients.
Assessing the role of dryness and burning sensation in diagnosing laryngopharyngeal reflux
Authors: Zheng Xiaowei , Chen Zhiwei , Chen Ting , Zhou Liqun , Liu Chaofeng , Zheng Jingyi , Hu Renyou 
Published: February 2024

AbstractLaryngopharyngeal reflux disease (LPRD) is a condition characterized by the regurgitation of stomach and duodenal contents into the laryngopharynx, with variable and non-specific symptoms. Therefore, developing an accurate symptom scale for different regions is essential. Notably, the symptoms of “dryness and burning sensation in the laryngopharynx or mouth” are prevalent among the Chinese population but are often omitted from conventional symptom assessment scales, such as the Reflux Symptom Index (RSI) and Reflux Symptom Score-12 (RSS-12) scales. To address this gap, our study incorporated the symptoms into the RSI and RSS-12 scales, developing the RSI-10/RSS-13 scales. Afterward, we assessed the role of the new scale’s reliability (Cronbach’s α and test–retest reliability), construct validity (confirmatory factor analysis and confirmatory factor analysis), and diagnostic efficiency. Our study encompassed 479 participants (average = 39.5 ± 13.4 years, 242 female) and 91 (average = 34.01 ± 13.50 years, 44 female) completed 24 h MII-pH monitoring. The Cronbach’s α values of 0.80 and 0.82 for the RSI-10 and RSS-13 scales, respectively. RSI-10 and RSS-13 exhibited strong test–retest reliability (ICCs = 0.82–0.96) and diagnostic efficacy (AUC = 0.84–0.85). Furthermore, the factor analysis identified the RSS-13 and its three sub-scales (ear-nose-throat, digestive tract, respiratory tract) exhibited good to excellent structural validity (χ2/df = 1.95, P < 0.01; CFI = 0.95, RMSEA = 0.06, SRMR = 0.05). The AUC optimal thresholds for the RSI-10 and RSS-13 in the Chinese population were 13 and 36, respectively. Besides, the inclusion of the new item significantly improved the diagnostic efficiency of the RSI scale (P = 0.04), suggesting that RSI-10 holds promise as a more effective screening tool for LPRD, and global validation is needed to demonstrate the impact of this new symptom on the diagnosis of LPRD.
Glymphatic and lymphatic communication with systemic responses during physiological and pathological conditions in the central nervous system
Authors: Licastro Ester , Pignataro Giuseppe , Iliff Jeffrey J. , Xiang Yanxiao , Lo Eng H. , Hayakawa Kazuhide , Esposito Elga 
Published: February 2024

AbstractCrosstalk between central nervous system (CNS) and systemic responses is important in many pathological conditions, including stroke, neurodegeneration, schizophrenia, epilepsy, etc. Accumulating evidence suggest that signals for central-systemic crosstalk may utilize glymphatic and lymphatic pathways. The glymphatic system is functionally connected to the meningeal lymphatic system, and together these pathways may be involved in the distribution of soluble proteins and clearance of metabolites and waste products from the CNS. Lymphatic vessels in the dura and meninges transport cerebrospinal fluid, in part collected from the glymphatic system, to the cervical lymph nodes, where solutes coming from the brain (i.e., VEGFC, oligomeric α-syn, β-amyloid) might activate a systemic inflammatory response. There is also an element of time since the immune system is strongly regulated by circadian rhythms, and both glymphatic and lymphatic dynamics have been shown to change during the day and night. Understanding the mechanisms regulating the brain-cervical lymph node (CLN) signaling and how it might be affected by diurnal or circadian rhythms is fundamental to find specific targets and timing for therapeutic interventions.