bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of potential SARS-CoV-2 genetic markers resulting from host domestication
Authors: Chen Heng-Chang , Wiśniewski Janusz 
Published: September 2024

Abstract

We developed a k-mer-based pipeline, namely the Pathogen Origin Recognition Tool using Enriched K-mers (PORT-EK) to identify genomic regions enriched in the respective hosts after the comparison of metagenomes of isolates between two host species. Using it we identified thousands of k-mers enriched in US white-tailed deer and betacoronaviruses in bat reservoirs while comparing them with human isolates. We demonstrated different coverage landscapes of k-mers enriched in deer and bats and unraveled 148 mutations in enriched k-mers yielded from the comparison of viral metagenomes between bat and human isolates. We observed that the third position within a genetic codon is prone to mutations, resulting in a high frequency of synonymous mutations of amino acids harboring the same physicochemical properties as unaltered amino acids. Finally, we classified and predicted the likelihood of host species based on the enriched k-mer counts. Altogether, PORT-EK showcased its feasibility for identifying enriched viral genomic regions, illuminating the different intrinsic tropisms of coronavirus after host domestication.
Text2Protein: A Generative Model for Designated Protein Design on Given Description
Authors: Hosseini Ramtin , Zhang Siyang , Xie Pengtao 
Published: September 2024

Abstract

Designing protein structures from text is challenging in computational biology. We propose Text2Protein, a pipeline combining large language models (LLMs) with diffusion models to generate full-atomic protein structures from text. Using a conditional diffusion model and the Vicuna-7B language model, we learn data distributions of 6D interresidue coordinates, refined into full-atomic structures with PyRosetta. Trained on a curated RCSB-PDB dataset, Text2Protein focuses on single-chain proteins with 40-256 residues. Our extensive experiments validate Text2Protein’s effectiveness by generating high-fidelity protein structures similar to ground truth proteins using raw texts. We evaluate Text2Protein using multiple metrics, including Mean Square Error (MSE) of 6D coordinates, Rosetta Energy Units (REU), and TM-score. Our results show that 5% of the generated proteins have a TM-score greater than 0.5, indicating similar folds in SCOP/CATH. Additionally, 16% of pairs have a TM-score greater than 0.4, 89% have a TM-score greater than 0.3, and none have a TM-score less than 0.17, below the threshold for unrelated proteins. Text2Protein presents a promising framework for automated protein design, potentially accelerating novel protein discovery. This work opens new avenues for integrating natural language understanding with protein structure generation, with implications in drug discovery, enzyme engineering, and material science.
Effect of Processing Methods on Mineral Bioaccessibility in Common Beans (Phaseolus Vulgaris L.)
Authors: Nagessa Wabi Bajo , Chambal Borges , Macuamule Custodia 
Published: September 2024

Abstract

Mineral bioavailability is a concern in legume based foods due to presence of Antinutritional factors. Zinc and iron deficiency is widespread in low-income countries because of the low consumption of animal products due to their unaffordable costs. The objective of this study was to evaluate the effects of processing conditions on the in vitro mineral bioaccessibility of small black common beans cultivated in Mozambique. The samples were collected from ‘Instituto de Investigação Agrária de Moçambique’ (IIAM), Maputo, Mozambique. Soaking (in water and sodium bicarbonate), germination (for 24 and 48 hours at 25oC), and cooking (ordinary and pressure) were applied. The oven-dried and finely ground samples of processed beans were in vitro digested and analyzed for mineral bioaccessibility.
The in vitro gastrointestinal simulation assay was performed and the dialyzable part of the samples was used for iron, zinc, and copper bioaccessibility determination. Though there is a slight difference, all the processing methods investigated in this study; soaking, germination, and cooking treatments affected the mineral bioaccessibility of beans. The in vitro iron, zinc, and copper bioaccessibility was enhanced by the respective processing methods as compared to the control sample. The iron bioaccessibility was observed to be 2.22% for water soaking and 2.59% for sodium carbonate soaking, 2.75% for 24-hour germination 4.27% for 48-hours germination, and 3.56% for ordinary cooking and 7.79% for pressure cooking. The in vitro iron bioaccessibility is relatively low as compared to that of zinc. In vitro, Zinc bioaccessibility was found to be the same for water and sodium bicarbonate soaking which was 6.94%.
Germination for 24 and 48 hours resulted in zinc bioaccessibility of 7.58% and 10.08% respectively while zinc bioaccessibility of 6.52% for ordinary cooking and 8.41% for pressure cooking was achieved. The respective in vitro copper bioaccessibility obtained for soaking in water and sodium bicarbonate was found to be 6.04% and 6.78% which are almost similar. Similarly, the germination for 24 and 48 hours showed copper bioaccessibility of 7.01% and 7.63% in respective order whereas it was observed that copper bioaccessibility of 5.79% for ordinary cooking and 8.50% for pressure cooking was achieved in this study. This shows that it is expected that the solubility of pressure-cooked beans in the intestine and the release of minerals from its matrix is high. The result illustrates that the pressure cooking of presoaked beans had the greater value for all mineral's bioaccessibility except for zinc, and it can be concluded that the processing techniques could help improve minerals' bioaccessibility in beans which in turn helps to combat malnutrition and ensure food security in developing countries.
Hcy accelerates the biological dysfunction of ANA-1 macrophages and vascular injure via Rap1A/MAPK signal
Authors: Huang Xiaobo , Yang Yali , Wang Lexin , Liu Huijuan , Yang Ziyao , Li Xinyi , Luo Huanyu , Li Zhen , Wang Yangjia , Xu Xi , Chi Hao , Yang Guanhu , Yang Xiaoling 
Published: September 2024

Abstract

Hyperhomocysteinemia (HHcy) is a kind of risk factor for various vascular diseases. The dysfunction of macrophages plays a crucial role in the development of HHcy-aggravated vascular injury. However, macrophages injure is still unclear. In this study, we propose the hypothesis that the Rap1A/ERK1/2 signal pathway is responsible for mediating the dysfunction of macrophages in HHcy-induced vascular diseases. We found that Cell proliferation, migration and invasion ability were increased after Hcy treatment. In addition, the mRNA levels of CD80 and CD86, and protein expression of Rap1A, iNOS were also increased in Hcy group. Interference of Rap1A reversed Hcy-induced cell proliferation, migration and invasion, and also reduced macrophage inflammatory response and M1 polarization. Phosphorylation of ERK1/2 was inhibited after Rap1A knockdown. Suppression of ERK1/2 alleviated Hcy-induced macrophage dysfunction. Together, Rap1A mediates Hcy-induced macrophage dysfunction via ERK1/2 signaling, which highlights a new mechanism in the pathogenesis and development of HHcy-aggravated vascular diseases.
Mechanisms of Tropical Indian Ocean circulation biases in CESM historical experiments
Authors: Mohan Soumya S , Srini Gangiredla 
Published: September 2024

Abstract

The study examines the mechanisms of Tropical Indian Ocean (TIO) circulation biases in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) historical simulations across four variants of the Community Earth System Model (CESM): CESM2, CESM2-FV2, CESM2-WACCM, and CESM2-WACCM-FV2. The dominant equatorial flow, known as the Wyrtki Jets (WJ), is considerably underestimated due to the predominance of easterly wind bias, with the fall WJs showing the least skill, particularly in CESM2-WACCM-FV2, due to the underestimated westerlies. However, the eastward Equatorial Undercurrent (EUC) is strongly overestimated in all models, with maximum amplitudes observed in CESM2-WACCM-FV2, followed by CESM2-FV2, due to wind-induced westward thermocline tilt through the positive Bjerknes feedback mechanism. The northward intensification and deepening of south equatorial currents are attributed to strong easterly wind stress in the southern TIO in CESM models. The equatorial easterly wind bias in CESM models originates from a southeasterly wind bias in their Atmospheric Model Intercomparison Project (AMIP) counterparts during June-August, with air-sea coupling driving the westerly wind bias over the equatorial region. Overly strong easterlies and the intensification of midlatitude westerlies in AMIP models contribute to the intensification and poleward shift of the subtropical gyre in CESM models. This, in turn, weakens the Agulhas leakage (AL) transport from the south Indian Ocean to the Atlantic, which is partially due to the underestimated Indonesian Throughflow (ITF) in CESM models.
Optimizing Maxillomandibular Position in Orthognathic Surgery: Introducing the T Concept in Treatment Planning
Authors: Alyahya Abdulmalik , Jasser Saud Bin 
Published: September 2024

Abstract

Purpose:
Orthognathic surgery aims to align the jaws with the facial skeleton and correct dental occlusion. This study introduces the T concept, incorporating the maxillary central incisor, chin, and occlusal plane as a novel predictor for properly positioning the maxillomandibular complex (MMC).
Methods:
The background, hypothesis, and rationale of the new T concept are explained. A case of a 28-year-old male with skeletal class III malocclusion and an open bite was used to illustrate the application of the T concept in step-by-step surgical planning. The planning encompasses four phases: phase one involves correcting frontal deformity and various asymmetries, phase two involves correcting chin anterior-posterior deformity, phase three involves correcting anterior-posterior and vertical MMC position, and phase four involves correcting MMC rotation.
Results:
The T concept provided a structured approach to MMC positioning, considering the vertical alignment of the maxillary central incisor, occlusal plane angulation, and chin positioning. The resulting postoperative outcomes showed an improved facial profile without the need for unnecessary genioplasty.
Conclusion:
A reliable MMC positioning in orthognathic surgery is offered by the T concept, addressing both functional and aesthetic concerns. By incorporating the chin as a key landmark, surgeons can achieve better alignment and avoid compensatory procedures. This method serves as a checkpoint where the MMC position is verified.
Insight into the Structural and Dynamic Properties of Novel HSP90 Inhibitors through DFT Calculations and Molecular Dynamics Simulations
Authors: Saouli Ibtissam , Abrane Rahma , Bidjou-Haiour Chahra , Boudiba Sameh 
Published: September 2024

Abstract

Context:
Heat-shock proteins (HSPs), particularly HSP90, are critical molecular chaperones that maintain protein stability, especially in cancer cells. Elevated HSP90 levels in tumors aid in oncogenic protein stabilization. This study focuses on developing potent, selective HSP90 inhibitors to disrupt its chaperone function, targeting cancer cell survival. Using a de novo hybridization approach, we designed novel inhibitors by integrating structural fragments from a known HSP90-binding drug, leading to the creation of hybrid compounds C1, C2, and C3. A 300 ns molecular dynamics simulation of each system revealed that C1, C2, and C3 formed more stable complexes with HSP90 compared to the reference compound, MEY. RMSD, RMSF, Rg, SASA, and MM-PBSA metrics supported these findings. DCCM and FEL analyses confirmed that the inhibitors did not alter HSP90's initial configuration. Further DFT calculations with the B3LYP/6-311++(d,p) basis set assessed frontier molecular orbitals, MEP surfaces, ELF, LOL maps, TDOS and PDOS, affirming their potential as new anti-cancer therapies.
Methods
Maestro 11.8, Discovery Studio Visualizer, Gromacs-2023, Gaussian 16, and online platforms like SwissADME and ProTox-II were utilized. Fragments generated from eight known HSP90-binding drugs were subjected to SP-docking, leading to 170 fragments. The highest-scoring fragments were merged using the breed panel to create new HSP90 inhibitors. XP-docking and ADMET analyses identified C1, C2, and C3 as the most promising candidates. These compounds were selected for a 300 ns dynamic simulation and subsequent DFT calculations.
Deep Learning for Effective Electronic Waste Management and Environmental Health
Authors: Oise Godfrey Perfectson , Susan Konyeha 
Published: September 2024

Abstract

Creating an advanced deep learning methodology for efficient management of electronic waste (e-waste) and preservation of environmental health is the aim of this research. The research tackles the growing problem of e-waste by compiling and preprocessing various datasets of e-waste images using a Sequential Neural Network (SNN) with TensorFlow and Keras. To improve the model's performance, this all-inclusive approach uses image augmentation techniques. In this work, efforts have been made to enhance the performance and computational efficiency of deep learning classifiers using hyperparameters. The study utilized e-waste data obtained from standard online repositories. The hyperparameter tuned modified CNN-based Sequential Neural Network model achieved an accuracy of 87%, precision of 87%, recall of 86% and f1_score of 86%. This model's strong performance highlights its real-time application potential and ease of integration into current e-waste management workflows. The suggested system is ready for widespread implementation and offers substantial advantages for environmental sustainability and resource conservation. This deep learning system helps reduce health risks associated with improper e-waste disposal, while also supporting ecological preservation by enabling the efficient sorting and classification of e-waste. The innovation resides in its capacity to streamline and automate the management of e-waste, offering a viable resolution to one of the most urgent environmental problems. This study is an excellent example of how cutting-edge artificial intelligence technologies can be integrated to improve waste management systems, giving global environmental health initiatives a scalable and useful tool.
MS-NET-v2: Modular Selective Network Optimized by Systematic Generation of Expert Modules
Authors: Chowdhury Md Intisar , Zhao Qiangfu 
Published: September 2024

Abstract

Modular architectures enhance Deep Neural Networks (DNNs) by reducing error rates, enabling uncertainty estimation, and increasing inference efficiency through selective module execution. While modular ensemble methods like bagging, boosting, and stacking improve DNNs performance, they are often computationally intensive. Adaptive inference strategies, such as the Modular Selective Network (MS-NET), address these issues by using independent router and expert modules, allowing parallel training and selective inference. In this study, we introduce MS-NET-v2, an optimized version of MS-NET, which enhances the construction of subsets and the expert training methodology. First, we introduce a cut-off variable, O, which systematically limits the sampling of binary class pairs from the Inter-Class Correlation (ICC) matrix. Next, we propose a subset merging algorithm that generates multi-class subsets from these binary subsets. This algorithm creates subsets that encode coarse concepts, in contrast to the fine-grained concepts represented by binary subsets. Based on loss landscape theory and to exploit the non-convexity of DNNs, we train these experts from scratch on multi-class subsets. This approach enhances diversity by covering several unique local minima , resulting in improved collective accuracy. We conduct extensive empirical studies with MS-NET-v2 on the CIFAR-10, CIFAR-100, Tiny-ImageNet, and Pets datasets. To verify the enhanced diversity of the expert networks, we perform function and weight space analyses on MS-NET-v2 experts. These studies demonstrate that MS-NET-v2 significantly improves collective accuracy, expert networks' diversity, and parameter efficiency compared to its predecessor. Additionally, MS-NET-v2 outperforms heavier ensemble methods in both single and multi expert settings.
Incidence and influencing factors of preterm birth, low birth weight and small for gestational age neonates with congenital heart disease in Changsha City, China, 2022-2023
Authors: Fu Jin , Zhang Bei , Liao Wenbo , Xiao Yaling , Wang Jinlian , Chen Huan , Fang Jie 
Published: September 2024

Abstract

Objective To analyze the incidence and influencing factors of preterm birth (PTB), low birth weight (LBW) and small for gestational age (SGA) neonates with congenital heart disease (CHD) in Changsha City, to provide a scientific basis for the development of target preventive measures. Methods Neonates with CHD reported by all obstetrics institutions in Changsha City from 2022 to 2023, elucidating the incidence of PTB, LBW and SGA. Statistical methods such as Chi-square tests and binary logistic regression were utilized to determine the associations of influencing factors with PTB, LBW and SGA neonates with CHD. Results A total of 1040 neonates with CHD were eligible for analysis, and the incidence of PTB, LBW and SGA were 15.00% (156/1040), 13.27% (138/1040) and 12.12% (126/1040), respectively. Binary logistic regression analysis showed that both taking folic acid during pregnancy (aOR = 0.386, 95% CI: 0.217–0.687), and parity 1 (aOR = 0.400, 95% CI: 0.243–0.659) or 2 (aOR = 0.278, 95% CI: 0.160–0.482) were protective factors for PTB While cesarean delivery (aOR = 2.517, 95% CI: 1.725–3.671) was a risk factor for PTB. Cesarean delivery (aOR = 2.130, 95% CI: 1.447–3.134), female infants (aOR = 1.589, 95% CI: 1.100–2.297), midwifery institutions of municipal level or above (aOR = 2.379, 95% CI: 1.334–4.245) were risk factors for LBW. Parity 1 (aOR = 5.083, 95% CI: 1.824–14.164) was a risk factor for SGA, while assisted reproduction(aOR = 0.332, 95% CI: 0.131–0.838) was a protective factor. Conclusions The incidence of PTB, LBW and SGA neonates with CHD in Changsha City is not in high level, and it was affected by maternal folic acid consumption, parity, mode of delivery, level of midwifery institutions, mode of conception, as well as neonatal gender.
MicroRNA-130a-3p regulates osimertinib resistance by targeting runt-related transcription factor 3 in lung adenocarcinoma
Authors: Shintani Takuya , Shun Yu-Ting , Toyozumi Yuji , Ikemura Kenji , Takeda Yoshito , Shiroyama Takayuki , Nagatomo Izumi , Kumanogoh Atsushi , Okuda Masahiro , Jingushi kentaro 
Published: September 2024

Abstract

Overcoming resistance to epidermal growth factor receptor tyrosine kinase inhibitors, including osimertinib, is urgent to improve lung cancer treatment outcomes. Extracellular vesicle (EV)-derived microRNAs (EV-miRNAs) play important roles in drug resistance and serve as promising biomarkers. In this study, we aimed to identify EV-miRNAs associated with osimertinib resistance and investigate their clinical relevance. The release of excess EVs was confirmed in an osimertinib-resistant lung adenocarcinoma cell line (PC9OR). The exposure of EVs and EV-miRNAs derived from PC9OR cells to PC9 cells increased cell viability after osimertinib treatment. Microarray analysis revealed that miR-130a-3p was upregulated in EVs derived from PC9OR cells and another osimertinib-resistant cell line (H1975OR). Transfection with miR-130a-3p attenuated osimertinib-induced cytotoxicity and apoptosis in both PC9 and H1975 cells, whereas osimertinib resistance in PC9OR cells was reversed after miR-130a-3p inhibition. Bioinformatics analysis revealed that runt-related transcription factor 3 is a target gene of miR-130a-3p, and it induced osimertinib resistance in PC9 cells. Finally, patients with lower baseline serum miR-130a-3p concentrations had longer progression-free survival. miR-130a-3p is a potential therapeutic target and a predictive biomarker of osimertinib resistance in adenocarcinoma.
A novel mechanism by which c-MYC is aberrantly activated by epigenetic silencing in cancer cells
Authors: Hu Xuming , wei ye , Zhang Meiying , Dou Chunfeng , Wang Liping , Zaib Gul , Wu Huixian , Guo Wang , Wang Xiaoyuan , Chen Shihao , Xu Qi , Guo Mingzhou , Cui Hengmi 
Published: September 2024

Abstract

Proto-oncogenes are abnormally activated in nearly all types of tumors. However, the epigenetic mechanism of proto-oncogene activation has not yet been well elucidated. Here, we show that a subset of proto-oncogenes, including c-MYC, possess antisense RNAs. Upregulation of c-MYC in cancer tissues was attributed to the silencing of its antisense RNA MYC-AS1 via DNA hypermethylation. MYC-AS1 RNA markedly inhibited the proliferation of cancer cells in vitro and impeded tumor growth in nude mice in vivo by repressing the expression of c-MYC via an RNAi mechanism. MYC-AS1 RNA bound directly to the HuR protein in the cytoplasm, enhancing the RNA stability of MYC-AS1. Furthermore, MYC-AS1 inhibited c-MYC-targeted gene LDHA expression. Our work provides a novel mechanism by which c-MYC is activated in cancer cells by epigenetic silencing of its antisense RNA, which functions as a tumor suppressor.
Device-Aware Decomposition and Mapping of Multiple-Control Toffoli Circuits in Quantum Computing Systems
Authors: Jiang Yibo , Cheng Xueyun , Zhu Pengcheng , Gu Hui , Guan Zhijin 
Published: September 2024

Abstract

With the rapid development of quantum computing, quantum computing devices have entered the Noisy Intermediate-Scale Quantum(NISQ)era. However, current NISQ quantum computing devices still face the challenge of physical limitations. To enable quantum algorithms to be directly executed on quantum computing devices, high-level quantum gates (such as MCT gates) in quantum circuits need to be decomposed and mapped onto quantum computing devices. This paper proposes a quantum device-aware method for decomposing high-level quantum gates. This method selects an optimal sub-topology of the quantum device as the target based on the circuit scale and the goal of reducing error rates. According to the proposed MCT gate decomposition rules, an associated gate-pairs generation algorithm is designed to facilitate subsequent decomposition. The control bits of the MCT gates are partitioned based on the associated gate-pair to better match the selected sub-topology. After eliminating redundant gates through the inverse decomposition of associated gate-pairs, the mapping is performed. Experimental results show that the proposed decomposition method reduces the number of basic quantum gates in quantum circuits, with an average optimization rate of 14.6%. For benchmark circuits decomposed using the method, applying the routing algorithm for mapping requires fewer additional gates, with an average optimization rate of 20.6%. The fidelity of the circuits improved by an average of 14.1% after mapping.