bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring some substituted chalcones as DprE1 inhibitors for antitubercular activity: An integrated computational approach
Authors: Amengor Cedric Dzidzor Kodjo , Biniyam Prince Danan , Gyan Patrick , Kekessie Francis Klenam , Harley Benjamin Kingsley 
Published: April 2024

Abstract

The development of extensively drug resistance to Mycobacterium has further hindered WHO efforts in the fight against tuberculosis. Elucidation of new mechanistic pathways against drug-resistant TB is of primary concern. The current study aims to find potential chalcones via an in silico assessment against Decaprenylphosphoryl-β-D-ribose-2-oxidase (DprE1) which is a crucial target for ﬁnding antitubercular drug candidates. We prospected the in silico properties of a library of 30 chalcones having two aromatic rings and either an electron withdrawing or electron donating substituent against DprE1 enzyme. The results showed that the introduction of p-chloro or p-methyl substituents and an indole on the chalcones’ motif played critical roles in their inhibition of Mtb DprE1. These chalcones demonstrated favorable physicochemical, pharmacokinetic, and CYP metabolism characteristics, suggesting that they could be promising drug candidates for further investigation. Analysis of docked complexes revealed that non-covalent bonding interactions are important for the binding and stability of the chalcones within the active site of the protein with estimated free energy of binding ranging from -10.4 to -6.5 kcal/mol. The anti-TB sensitivity findings suggest that the compounds were more potent compared to the pyrazinamide against Mycobacterium tuberculosis. Furthermore, the binding stability study performed using molecular dynamics simulation of the DprE1-9C complex disclosed the conformational stability of the complex over 200 ns with average root mean square deviation not exceeding 0.25 nm (2.5 Å). The computational results could immensely contribute toward hit to lead triaging in the search for new DprE1 inhibitors with improved antitubercular activities.
Exploring the neural mechanisms underlying cooperation and competition behaviour: Insights from SEEG Hyperscanning
Authors: Zhang Junsong , Qiao Xiaojun , Li Rui , Huang Huimin , Hong Yang , Li Xiaoran , Li Ziyue , Chen Siyi , Yang Lizhi , Ong ShengTeng , Yao Yi , Wang Fengpeng , Zhang Xiaobin , Lin Gaomin , Xiao Yongna , Weng Mingxiang 
Published: April 2024

Abstract

Cooperation and competition are two of the most important social behaviours in human society. Investigating human social behavior in cooperative and competitive contexts, involving the insula and inferior frontal gyrus (IFG) related to executive function and mentalizing, is crucial for comprehending our social nature. However, the detailed study of their neural oscillations is limited by the deep location of the insula and the time resolution constraints of existing imaging techniques. This study aims to employ advanced hyperscanning and stereo-electroencephalography (SEEG), with high temporal and spatial resolution, to examine intra- and inter-brain dynamics within the insula and IFG during cooperative and competitive tasks. We identified distinct high-gamma responses and observed varying connectivity patterns, with the IFG modulating insula activity during competition, and balanced interactions between the insula and IFG occurring during cooperation. Notably, we observed enhanced inter-brain insula synchronization in competition and greater IFG synchronization in cooperation, elucidating the gamma band's role in social interactions. These results enhance our understanding of the neural bases of cooperation and competition, emphasizing the critical roles of both insula and IFG in social cognition.
Non-clinical investigations about cytotoxic and anti-platelet activities of gamma-terpinene
Authors: Souza Railson Pereira , Pimentel Vinícius Duarte , de Sousa Rayran Walter Ramos , Sena Emerson Portela , Silva Alda Cássia Alves da , Dittz Dalton , Ferreira Paulo Michel Pinheiro , de Oliveira Aldeídia Pereira 
Published: April 2024

Abstract

Gamma-terpinene (γ-TPN) is a cyclohexane monoterpene, isolated from essential oils of pharmacologically active plant species, such as tea tree (Melaleuca alternifolia), oregano (Origanum vulgare), rosemary (Rosmarinus officinalis L.), thyme (Thymus vulgaris Marchand) and eucalyptus (Eucalyptus sp.). Terpenes are widely studied for their recognized pharmacological actions on the cardiovascular system, hemostasis and antioxidant actions. The objective of this study was to investigate the cytotoxic and antiplatelet activity of γ-TPN in non-clinical study models. For the in silico evaluation, the PreADMET, SwissADME and SwissTargetPrediction software were used. Molecular docking was performed using the AutoDockVina and BIOVIA Discovery Studio databases. The cytotoxicity of γ-TPN was analyzed by the MTT assay with normal murine endothelial (SVEC4-10) and fibroblast (L929) lines. Platelet aggregation was evaluated with platelet-rich (PRP) and platelet-poor (PPP) plasma from spontaneously hypertensive rats (SHR), in addition to SVEC4-10 cells pre-incubated with γ-TPN (50, 100 and 200 µM) for 24 h. In in vivo tests, SHR animals were also used, pre-treated by gavage with γ-TPN for 7 days, distributed into four groups (control, 25, 50 and 100 mg/Kg). At the end, blood samples were collected to measure nitrites using the Griess reagent. γ-TPN proved to be quite lipid-soluble (Log P = + 4.50), with a qualified profile of similarity to the drug, good bioavailability, and adequate pharmacokinetics. The monoterpene exhibited affinity mainly for the P2Y12 receptor (6.450 ± 0.232 Kcal/mol), moderate cytotoxicity for L929 (CC50 = 333.3 µM) and SVEC 4–10 (CC50 = 366.7 µM). The presence of γ-TPN in SVEC 4–10 cells was also able to reduce platelet aggregation by 51.57 and 44.20%, respectively, at the lowest concentrations (50 and 100 µM). It was concluded that γ-TPN has a good affinity with purinergic receptors and an effect on the reversal of platelet aggregation and oxidative stress, being promising and safe for therapeutic targets and subsequent studies in the control of thromboembolic diseases.
Network-pharmacology-based study on the mechanism of fibrates regulating HIF-1A in the treatment of ischemic stroke
Authors: Yang Fengjiao , Yan Ya , Gu Yun , Wang Pengyu , Wang Min , Chen Jianjie , Du Xiaoshan , Wang Guangming 
Published: April 2024

Abstract

Ischemic stroke (IS) is a serious threat to people's health, its occurrence risk is closely related to lipid levels and genes. Fibrates are commonly used as adjunctive therapy for IS in clinical practice, some studies have reported that hypoxia-inducible factor (HIF1A) is associated with the occurrence risk of various diseases, so it is important to explore the mechanism of fibrates regulate HIF1A in the treatment of IS. Firstly, the potential targets of fibrates, IS, HIF1A and HIF1A-related genes were obtained through various databases, then their common targets were obtained through Venny 2.1.0. The PPI network of fibrates and HIF1A-related genes was plotted by String platform and Cytoscape3.8.1 software. KEGG pathways of drugs, diseases, HIF1A and HIF1A related genes were obtained by Metascape platform. Finally, molecular docking of fibrates and HIF1A was performed by AutoDock software. In this study, the structure of five fibrates were obtained by reviewing the literature and pharmacopoeia. The common targets of five fibrates and IS showed that only 3 fibrates contained HIF1A. KEGG pathway analysis and molecular docking results showed that fibrates can better regulate HIF1A to treat IS, its main action pathways are pathways in cancer, kaposi sarcoma-associated herpesvirus infection and HIF-1 signaling pathway.
Natural Language Processing method to Unravel Long COVID's clinical condition in hospitalized patients
Authors: Smaili Soraya , Veras Pilar , Araújo Vinícius , Zatti Henrique , Luis Caio Vinícius , Cavalcanti Célia Regina , de Oliveira Matheus Henrique , Leao Anderson Henrique , Junior Juracy Bertoldo , Barbosa George , Ravera Ernesto , Cebukin Alberto , David Renata , de Melo Danilo , Machado Tales , Bellei Nancy , Boaventura Viviane , Barral-Neto Manoel 
Published: April 2024

Abstract

Long COVID is characterized by persistent symptoms beyond established timeframes, presenting a significant challenge in understanding its clinical manifestations and implications. In this study, we present a novel application of natural language processing (NLP) techniques to automatically extract unstructured data from a Long COVID survey conducted at a prominent university hospital in São Paulo, Brazil. Our phonetic text clustering (PTC) method enables the exploration of unstructured EHR data to unify different written forms of similar terms into a single phonemic representation. We use n-gram text analysis to detect compound words and negated terms in Portuguese-BR, focusing on medical conditions and symptoms related to Long COVID. By leveraging NLP, we aim to contribute to a deeper understanding of this chronic condition and its implications for healthcare systems worldwide. The model developed in this study has the potential for scalability and applicability in other healthcare settings, facilitating broader research efforts and informing clinical decision-making for Long COVID patients.
Blockchain-Enabled Diploma Traceability and Fraud Detection: The BlockDipls Framework
Authors: MILI khaled 
Published: April 2024

Abstract
In the contemporary landscape, higher education institutions play a vital role in shaping societal values and progress. However, the reliability of accreditation systems can vary, especially in regions where the demand for skilled professionals surpasses the available supply. This imbalance has given rise to the proliferation of "certificate factories," which produce counterfeit diplomas to exploit this gap. Tackling this challenge necessitates the digitalization of diploma issuance and verification processes to uphold credential integrity and facilitate accurate hiring decisions. This paper introduces the "BlockDiplos" framework, leveraging Blockchain technology to bolster diploma traceability and combat counterfeiting and fraud through smart contract functionalities. By doing so, it fosters transparency and trust in information management practices. Our study demonstrates the effectiveness of the BlockDiplos framework in enhancing the security and reliability of diploma verification systems, thereby mitigating the risks associated with counterfeit diplomas and bolstering confidence in credential verification processes.
Monthly trends in under-5 malaria cases in Guinea: Comparative analysis between a seasonal malaria chemoprevention (SMC) and a non-SMC health district
Authors: Keita Kaba Saran , Camara Bienvenu Salim , Camara Sadan , Barry Fanta , Sidibe Tiany , Kourouma Karifa , Diallo Ramata , Toure Madeleine , Camara Alioune , Balde Mamadou Dioulde 
Published: April 2024

Abstract

Background
In Guinea, where malaria is the leading cause of morbidity and mortality in children, seasonal malaria chemoprevention (SMC) is deployed to prevent malaria transmission in children during the rainy season. However, the effect of this intervention remains under-documented. The aim of this study was to analyse monthly trends in malaria cases among under-5 children in Guinea.
Methods
This was a quasi-experimental study using routine data from the National Health Information System. The two districts (Mamou and Kindia) were selected to compare monthly trends in malaria cases in under-5 children from July to October, covering the years 2015 to 2020. Interrupted time series were used to estimate the effects of SMC.
Results
The implementation of the SMC contributed to a significant average reduction of 225 cases per month in the intervention district (95% CI -362 to -88; p = 0.002), compared with the control district. However, the effect of the SMC varied according to its monthly cycles.
Conclusions
This study suggests that the seasonal malaria chemoprevention should be extended to other health districts not yet covered, in order to accelerate the elimination of malaria in Guinea.
A Global Database to Monitor Annual Mangrove Forest Change, 2000-2020 (GMC-21)
Authors: Hamilton Stuart , Presotto Andrea 
Published: April 2024

Abstract

The absence of a high-resolution, long-term annual global database for monitoring mangrove forests has created a gap in researchers’ ability to analyze mangrove forest change rates. To address this gap, we present a new global database that tracks annual global mangrove forest change rates at high spatial and temporal resolutions since 2000. By synthesizing several remotely sensed databases such as Mangrove Forests of the World, Global Mangrove Watch, and High-Resolution Global Maps of 21st-Century Mangrove Forest Cover Change, this database provides mangrove forest change information at approximately 30 m annually and globally. It is a consistent and systematic mangrove forest change database across all years. Between 2000 and 2020, mangrove forests lost 3.42 percent of their original global area, shrinking from approximately 139,716 km2 in 2000 to 134,383 km2 in 2020, resulting in an annual loss rate of 0.17 percent. As of 2020, Indonesia, Brazil, Australia, Nigeria, and Malaysia are the top five mangrove-holding countries, containing slightly over 50 percent of the global mangrove holdings. Indonesia alone contains 22 percent of global mangrove forests. Countries or regions with high loss rates and substantial mangrove holdings are Puerto Rico, Madagascar, and Cuba.
Trade-in program in online platforms considering network externalities and recycling services
Authors: Yu Zhaoqing , Li Jing , Ji Xue 
Published: April 2024

Abstract

Consumers trade their used products for new ones through online platforms, thereby integrating internet shopping and recycling. Two trade-in models are developed, i.e., the platform model where the manufacturer cooperates with an online retail platform to sell products and the online retail platform introduces trade-in program and manufacturer model where the manufacturer's own platform introduces trade-in program. This study examines the trade-in program offered by online platforms with a consideration of network externalities and heterogeneous consumers, and analyzes the decisions of pricing and recycling service. The research indicates that heightened network externalities can enhance recycling services, promote trade-in program development, and increase the demand for trade-in. The trade-in recycling service gets higher in the manufacturer model, whereas the sales price in the platform model is elevated due to sales commission rates. However, the manufacturer model does not always have higher market demand than the platform model, when both the commission rate and recycling revenue are high, the platform model have higher market demand. Although the manufacturer profits more than the online retail platform in the platform model, it is suggested that the manufacturer should introduce the trade-in program on the self-owned platform since the profit of manufacturer is larger under the manufacturer model.
Dynamic forecasting module for chronic graft-versus-host disease progression based on a disease-specific subpopulation of B cells
Authors: Xiang Andy , Ma Yuanchen , Chen Jieying , Fan Zhiping , Shi Jiahao , Li Gang , Li Xiaobo , Wang Tao , Xu Na , Liu Jialing , Li Zhishan , Zhang Xiaoran , Liu Qifa , Huang Weijun , Chen Xiaoyong 
Published: April 2024

Abstract

Due to its dynamic nature and the absence of reliable real-time monitoring tools, predicting chronic graft-versus-host disease (cGVHD) progression was challenging. This caused a significant investment of both time and financial resources to ensure good management of cGVHD. In response to this challenge, we identified a distinct B-cell subpopulation characterized by CD27+CD86+CD20-, which could precisely distinguish cGVHD from healthy donors. Leveraging this discovery, we developed cGPS, a user-friendly tool based on marker distribution, which demonstrated exceptional efficacy in tracking cGVHD progression. Its validation, conducted through retrospective and prospective studies involving 91 patients (25 non-GVHD and 66 cGVHD cases), confirmed cGPS's predictive prowess. Remarkably, our retrospective analysis revealed an impressive area under the curve (AUC) of 0.9773 for identifying non-GVHD patients at risk of cGVHD and 0.8846 for predicting disease progression in cGVHD patients. Subsequent validation in an independent prospective study yielded equally promising results, with cGPS accurately predicting all instances of cGVHD development or progression within a three-month observation window. With three independent cohorts, cGPS underscores its robust ability for sensitive and dynamic monitoring of cGVHD progression, provides a solution for early diagnosis and assessment of treatment effectiveness for cGVHD.
Long-term effects of COVID-19 on endothelial function, arterial stiffness, and blood pressure in college students: a pre-post-controlled study
Authors: Peng Jianwei , Guo Wenhuang , Li Peilun , Leng Lu , Gao Dongdong , Yu Zhendong , Huang Jinglin , Guo Jinghui , Wang Shen , Hu Min , Huang Junhao 
Published: April 2024

Abstract

BackgroundThe COVID-19 has been shown to have negative effects on the cardiovascular system, but it is unclear how long these effects last in college students. This study aimed to assess the long-term impact of COVID-19 on arterial stiffness, endothelial function, and blood pressure in college students.MethodsWe enrolled 37 college students who had been infected with COVID-19 for more than 3 months. Brachial artery flow-mediated dilation (FMD) was used to assess endothelial function, while arterial stiffness was evaluated using the ABI Systems 100, including variables such as ankle-brachial index (ABI), brachial-ankle pulse wave velocity (baPWV), carotid-femoral pulse wave velocity (cfPWV), heart rate (HR), and blood pressure (BP).ResultsOur results showed that FMD was significantly impaired after COVID-19 infection (p < 0.001), while cfPWV and systolic blood pressure (SBP) were significantly increased (p < 0.05). Simple linear regression models revealed a significant negative correlation between post-COVID-19 measurement time and baPWV change (p < 0.01), indicating an improvement in arterial stiffness over time. However, there was a significant positive correlation between post-COVID-19 measurement time and diastolic blood pressure (DBP) change (p < 0.05), suggesting an increase in BP over time. There were no significant differences in ABI and HR between pre- and post-COVID-19 measurements, and no significant correlations were observed with other variables (p > 0.05).ConclusionOur study demonstrated that COVID-19 has long-term detrimental effects on vascular function in college students. However, arterial stiffness tends to improve over time, while BP may exhibit the opposite trend.
Crohn's disease with intracranial Mycobacterium Iranian infection in children with gastrointestinal bleeding as the first symptom: a case report
Authors: Wang Fengge , Liu Qin , Wu Daiqin , Hu Chijun , Zhu Zhenni 
Published: April 2024

Abstract
Background: Nontuberculosis mycobacteria are prone to infect patients with immunodeficiency or immunosuppressive diseases. There have been reports of Crohn's disease in the intestine combined with gastrointestinal bleeding, but there have been no reports of gastrointestinal bleeding in Crohn's children with intracranial Mycobacterium Iranian infection.
Patient presentation: A 10-year-old Chinese boy developed fever and gastrointestinal bleeding. A continuous decrease in hemoglobin leads to shock. Surgical pathology confirmed Crohn's disease. In addition, Mycobacterium Iranian infection was detected in his cerebrospinal fluid through metagenomic next-generation sequencing (mNGS). Therefore, after surgical resection of the bleeding intestine, the patient received antituberculosis treatment for intracranial infection, followed by full screening for latent tuberculosis infection (LTBI) and regular treatment with biological agents.
Conclusion: A boy with Crohn's disease and gastrointestinal bleeding was diagnosed with intracranial Mycobacterium Iranian infection. It is emphasized that when Crohn's disease is complicated by gastrointestinal bleeding, surgery combined with biological agent therapy should be considered to save lives and reduce the risk of recurrent bleeding. Postoperative caution should be exercised against opportunistic infections and the appropriate use of anti-tuberculosis drugs.
Gradient Boosting Machine based prediction of chemotherapy response and role of p53 mutational and smoking status for progression free survival in metastatic colorectal cancer
Authors: Yıldız Oğuzhan , Gürbüz Ali Fuat , Eryılmaz Melek Karakurt , Araz Murat , Yıldırım Mahmut Selman , Bozcuk Hakan Şat , Artaç Mehmet 
Published: April 2024

Abstract

Background: Identifying predictors of response or progression after first-line chemotherapy for stage 4 colorectal cancer remains a challenge. This study aims to evaluate the correlation between patient outcomes and the p53 mutational status and smoking status of tumors using various machine learning methods.
Material and methods: We consecutively recruited all patients diagnosed with metastatic colorectal cancer at an academic center within a specified time period. Response to first-line chemotherapy and associated factors were assessed using various machine learning models. The most accurate model was further optimized. Additionally, common clinical features, MMR, p53, and RAS status were tested for correlation with the outcome. Feature importance and calibration plots were generated, and univariate and multivariate Cox models were utilized to analyze associates of progression-free survival (PFS).
Results: A total of 101 newly diagnosed metastatic colorectal cancer patients initiating first-line chemotherapy were included. The median age was 62, and 69% of the cases were male. We evaluated 15 machine learning models to predict the binary outcome of best response to chemotherapy, among which LightGBM demonstrated the highest baseline accuracy of 0.71. Further tuning of the LightGBM model improved accuracy to 0.79, with a macro average AUC value of 0.82. Age at diagnosis, maximum metastatic dimension of cancer, and metastatic status at diagnosis were identified as the three most important features. Genetic variables did not establish significant feature importance for response analysis. Survival analysis revealed an association between PFS and p53 mutation status (Exp(B) = 0.52, Wald = 6.98, P = 0.008) and smoking pack years (Exp(B) = 0.99, Wald = 4.28, P = 0.039).
Discussion: Utilizing LightGBM as a machine learning method, we developed a predictive model with good accuracy for assessing response to first-line treatment. If confirmed and further improved, such a model could aid in identifying responders to first-line chemotherapy in metastatic colorectal cancer patients and suggesting alternative chemotherapy options for non-responders. Furthermore, our findings highlight the prognostic importance of genetic features, particularly p53 mutation status, and smoking pack years for PFS duration in this context.