Browse Articles

Integrating machine learning and structure-based approaches for repurposing potent tyrosine protein kinase Src inhibitors to treat inflammatory disorders

The burden of prostate cancer in the North Africa and Middle East Region from 1990 to 2021

Willingness to pay a premium for eco-label products in China: a mediation model based on quality value

A kurtosis-ESPRIT algorithm for RealTime stability assessment in droop controlled microgrids

Abstract Although detailed analytical models for droop-controlled microgrids are available, they are computationally complex and do not consider real-time variations in microgrid parameters and operating conditions. This paper proposes Kurtosis-Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) to identify the dominant modes in droop-controlled inverter-based microgrids (IBMGs) using local real-time measurements. In the proposed approach, a short-duration small disturbance is applied to the selected DG’s active power droop gain, and then, the system’s dominant modes are estimated from its local measurements. Additionally, a kurtosis measure is proposed as a quick measure to assess the estimation signal’s characteristics and evaluate the presence and prominence of significant modes within the signal. The effectiveness of the developed approach is validated via MATLAB/SIMULINK simulations. Four case studies were conducted to verify the robustness of the proposed algorithm as follows: under different values of active power droop gains, several variations of lines’ X/R ratios, various levels of noise, and under large load changes and topological disturbances. Besides, a controller-in-the-loop (CIL) experiment was conducted using OPAL-RT to provide a real-time validation of the results. The modes obtained from the proposed algorithm are validated against the analytically derived modes and the estimation accuracy is compared to the recent methods: Prony, Matrix Pencil, and Subspace Identification techniques. Results show higher estimation accuracy for the proposed approach with a robust performance in noisy environments, across varying load conditions, and under different network configurations.

Prognostic assessment of early-stage liver cirrhosis induced by HCV using an integrated model of CX3CR1-associated immune infiltration genes

Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination

Basic psychological needs satisfaction, coping functions, and emotional experiences in competitive athletes: a multi-states theory perspective

Language style (mis)matching: Consuming entertainment media from someone unlike you is linked to positive attitudes

Impact of driving characteristic parameters and vehicle type on fuel consumption and emissions performance over real driving cycles

With the growing need for sustainable transportation solutions, understanding the relationship between driving characteristic parameters, vehicle type, and their impact on emissions and fuel consumption over real driving scenarios is becoming increasingly important. In this paper, four conventional vehicles and one hybrid vehicle with different technologies were compared in four distinct routes in Tehran city. Nineteen real driving cycles were generated using widely employed K-means and PCA algorithms. The vehicles were simulated on MATLAB/Simulink according to their specifications. Twelve driving characteristic parameters, fuel consumption, CO, NOx, HC, and CO2 of vehicles with different powertrains, engines, and body styles were calculated over real and standard driving cycles. Notable findings show that driving characteristic parameters exhibit distinct influences on fuel consumption and emissions, depending on the specific driving conditions and vehicle type. Additionally, the hybrid vehicle achieved 39% and 26% fuel savings compared to gasoline and dual fuel vehicles, respectively. However, it emitted significantly higher levels of CO and HC. In contrast, the turbocharged vehicle increased CO and HC emissions compared to the naturally aspirated vehicle, but consumed less fuel (approximately 6%) and emitted lower amounts of CO2 (approximately 19%). In real driving cycles, the sedan vehicle generally exhibited slightly lower values compared to petrol SUV due to lower weight and drag coefficient.

Exploring the comorbidity mechanisms between atherosclerosis and hashimoto’s thyroiditis based on microarray and single-cell sequencing analysis

Abstract Atherosclerosis (AS) is a chronic vascular disease characterized by inflammation of the arterial wall and the formation of cholesterol plaques. Hashimoto’s thyroiditis (HT) is an autoimmune disorder marked by chronic inflammation and destruction of thyroid tissue. Although previous studies have identified common risk factors between AS and HT, the specific etiology and pathogenic mechanisms underlying these associations remain unclear. We obtained relevant datasets for AS and HT from the Gene Expression Omnibus (GEO). By employing the Limma package, we pinpointed common differentially expressed genes (DEGs) and discerned co-expression modules linked to AS and HT via Weighted Gene Co-expression Network Analysis (WGCNA). We elucidated gene functions and regulatory networks across various biological scenarios through enrichment and pathway analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Core genes were identified using Cytoscape software and further validated with external datasets. We also conducted immune infiltration analysis on these core genes utilizing the CIBERSORT method. Lastly, Single-cell analysis was instrumental in uncovering common diagnostic markers. Based on differential analysis and WGCNA, we identified 119 candidate genes within the cohorts for AS and HT. KEGG and GO enrichment analyses indicate that these genes are significantly involved in antigen processing and presentation, along with various immune-inflammatory pathways. Two pivotal genes, PTPRC and TYROBP, were identified using five algorithms from the cytoHubba plugin. Validation through external datasets confirmed their substantial diagnostic value for AS and HT. Moreover, the results of Gene Set Enrichment Analysis (GSEA) indicated that these core genes are significantly enriched in various receptor interactions and signaling pathways. Immune infiltration analysis revealed a strong association of lymphocytes and macrophages with the pathogenesis of AS and HT. Single-cell analysis demonstrated predominant expression of the core genes in macrophages, monocytes, T cells and Common Myeloid Progenitor (CMP). This study proposes that an aberrant immune response might represent a shared pathogenic mechanism in AS and HT. The genes PTPRC and TYROBP are identified as critical potential biomarkers and therapeutic targets for these comorbid conditions. Furthermore, the core genes and their interactions with immune cells could serve as promising targets for future diagnostic and therapeutic strategies.

Effect of rising fuel prices on small-scale fisheries livelihoods and marine sustainability in Ghana

This study investigates the effects of fuel price hikes on the livelihoods of small-scale coastal fisherfolk in Ghana. The study applied a mixed-methods approach consisting of a questionnaire survey of 320 fisherfolk and 20 interviews with stakeholders in the fisheries sector. Increase in expenses, reduced frequency of fishing, an upsurge in social vices, and declining small-scale fisheries opportunities were found to be the main effects of fuel price hikes on fisherfolk livelihoods. The results reveal that fisherfolk experienced financial, emotional and psychological shocks due to the high cost of fuel. Dependency on savings, borrowing, petty trading, migration and farming were found to the main coping strategies. However, the various livelihood coping strategies deployed by fisherfolk were not sufficient to ameliorate their economic hardship. The findings show that fuel price hikes can contribute to reduction in fishing pressure and overcapacity despite the current socioeconomic hardship experienced by fishing households. The study recommends interest-free loans to support fisherfolk who are already engaged in small businesses. The provision of supplementary livelihoods could also improve fisherfolk’s income and well-being.

Titin fragment is a sensitive biomarker in Duchenne muscular dystrophy model mice carrying full-length human dystrophin gene on human artificial chromosome

Abstract Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder caused by mutations of the dystrophin gene, which spans 2.4 Mb on the X chromosome. Creatine kinase (CK) activity in blood and titin fragment levels in urine have been identified as biomarkers in DMD to monitor disease progression and evaluate therapeutic intervention. However, the difference in the sensitivity of these biomarkers in DMD remains unclear. Previously, we generated transchromosomic mice carrying the full-length human dystrophin gene on a human artificial chromosome (DYS-HAC1) vector. The human dystrophin derived from DYS-HAC1 improved pathological phenotypes observed in DMD-null mice, which lack the entire 2.4 Mb of the dystrophin gene. In this study, we compared the values of plasma CK activity and urine/plasma titin fragment levels in wild-type (WT), DYS-HAC1, DMD-null, and DYS-HAC1; DMD-null mice. Plasma CK activity and urine/plasma titin fragment levels in DMD-null mice were significantly higher than those in WT mice. Although plasma CK activity showed no significant difference between WT and DYS-HAC1; DMD-null mice, urine/plasma titin fragment levels in DYS-HAC1; DMD-null mice were higher than those in WT mice. Human dystrophin in DYS-HAC1; DMD-null mice drastically improved muscular dystrophy phenotypes seen in DMD-null mice; however, the proportion of myofibers with central nuclei in DYS-HAC1; DMD-null mice had a tendency to be slightly higher than that in WT mice. These results suggest that urine/plasma titin fragment levels could be a more sensitive biomarker than plasma CK activity.

Multifaceted barriers associated with clinical breast examination in sub-Saharan Africa: A multilevel analytical approach

Objectives Clinical breast examination (CBE) open the pathway to early detection and diagnosis of breast cancer. This study examined barriers to CBE uptake in seven sub-Saharan African (SSA) countries. Methods Data from the most current Demographic and Health Surveys of Burkina Faso, Cote d’Ivoire, Ghana, and Kenya Mozambique, Senegal and Tanzania was used. A weighted sample size of 65,486 women aged 25–49 years was used to estimate the pooled prevalence of CBE. We employed a multilevel logistic regression modelling technique, with results presented in adjusted odds ratios (aOR) along with a 95% confidence interval (CI). Results The pooled prevalence of CBE uptake in the studied SSA countries is low at 19.2% [95%CI: 18.5–19.8]. Screening uptake was significantly low among women reporting difficulty in getting permission (aOR = 0.88, 95% CI: 0.82–0.95), and distance (aOR = 0.95, 95% CI: 0.89–0.99), as well as those who reported financial constraints (aOR = 0.92, 95% CI: 0.88–0.97), as barriers to access healthcare facilities. However, surprisingly, women who faced travel-alone barriers were 1.19 times (95%CI: 1.10–1.28) more likely to utilise CBE than those who did not face this barrier. Conclusions We conclude that barriers such as difficulties in obtaining permission, long distances to healthcare facilities, and financial constraints significantly reduce the likelihood of women undergoing CBE. The study underscores a need to improve access to healthcare facilities. Practically, this can be achieved by expanding mobile health services and integrating CBE into primary healthcare will help overcome distance-related challenges. Additionally, targeted outreach and transportation initiatives are necessary to support women facing travel barriers.

Eye movements follow the dynamic shifts of attention through serial order in verbal working memory

Pharmacophore modeling and QSAR analysis of anti-HBV flavonols

Due to its global burden, Targeting Hepatitis B virus (HBV) infection in humans is crucial. Herbal medicine has long been significant, with flavonoids demonstrating promising results. Hence, the present study aimed to establish a way of identifying flavonoids with anti-HBV activities. Flavonoid structures with anti-HBV activities were retrieved. A flavonol-based pharmacophore model was established using LigandScout v4.4. Screening was performed using the PharmIt server. A QSAR equation was developed and validated with independent sets of compounds. The applicability domain (AD) was defined using Euclidean distance calculations for model validation. The best model, consisting of 57 features, was generated. High-throughput screening (HTS) using the flavonol-based model resulted in 509 unique hits. The model’s accuracy was further validated using a set of FDA-approved chemicals, demonstrating a sensitivity of 71% and a specificity of 100%. Additionally, the QSAR model with two predictors, x4a and qed, exhibited predictive solid performance with an adjusted-R2 value of 0.85 and 0.90 of Q2. PCA showed essential patterns and relationships within the dataset, with the first two components explaining nearly 98% of the total variance. Current HBV therapies tend to fail to provide a complete cure, emphasizing the need for new therapies. This study’s importance was to highlight flavonols as potential anti-HBV medicines, presenting a supplementary option for existing therapy. The QSAR model has been validated with two separate chemical sets, guaranteeing its reproducibility and usefulness for other flavonols by utilizing the predictive characteristics of X4A and qed. These results provide new possibilities for discovering future anti-HBV drugs by integrating modeling and experimental research.

Assessing the impact of energy coaching with smart technology interventions to alleviate energy poverty

Abstract Energy poverty affects 550,000 homes in the Netherlands yet policy interventions to alleviate this issue are rare. Therefore, we test two energy coaching interventions in Amsterdam: a static information group (n = 67) which received energy efficient products and one energy-use report, and a smart information group (n = 50), which also had a display providing real-time feedback on energy-use. Results across both groups, show a 75% success rate for alleviating energy poverty. On average homes reduced monthly electricity consumption by 62 kWh (33%), gas by 41 m3 (42%), bills by €104 (53%) and percentage of income spent on energy from 10.1% to 5.3%.

Differential insulin response characteristics of graphene oxide–gold nanoparticle composites under varied synthesis conditions

The structural alterations in the constituent materials of nanocomposites such as graphene nanocomposites typically induce changes in their properties including mechanical, electrical, and optical properties. Therefore, by altering the preparation conditions of nanocomposites and investigating their responsiveness to basic biomolecules (such as proteins), it is possible to explore the application potentials of the composites and guide development of new nanocomposite preparation. In this study, different composites of graphene oxide and gold nanoparticles (AuNPs/GO) were obtained by varying the volumes of reducing agents used in the one-pot hydrothermal method. Insulin was chosen as a basic protein to study the response characteristics of AuNPs/GO under different preparation conditions. Optical responses of these composites to pure insulin and various commercial insulin types were all explored for the first time. The results indicated that AuNPs/GO could optically respond to insulin, including pure insulin and various types of commercial insulin, and changes in the preparation conditions could really influence this response. Moreover, optimal preparation conditions could be determined by an optical method for the largest responses of the nanocomposites to insulin. Based on previous research and the results of this study, it is speculated that the responses of AuNPs/GO to insulin may attribute to glutamic acids, asparagines, and glutamines on insulin, which may interact with AuNPs/GO, particularly with the AuNPs in the composites. Besides, the AuNPs/GO could exhibit relatively stable responses to various commercial insulin types and detect the concentration of specific branded commercial insulin with smaller errors. In summary, this study demonstrated the application potential of AuNPs/GO in areas such as drug testing and production, while also furnishing an experimental foundation and direction for further applications of AuNPs/GO in biosensing and biomolecule detection.

Structural modification of defective WO3 by g-C3N4 for photocatalytic gold recovery from non-cyanide-based plating effluent

Comparison of a non-invasive point-of-care measurement of anemia to conventionally used HemoCue devices in Gambella refugee camp, Ethiopia, 2022

Annual surveys of refugees in Gambella, Ethiopia suggest that anemia is a persistent public health problem among non-pregnant women of reproductive age (NP-WRA, 15–49 years). Measurement of anemia in most refugee camp settings is conducted using an invasive HemoCue 301. We assessed the accuracy and precision of a non-invasive, pulse CO-oximeter in measuring anemia among NP-WRA in four Gambella refugee camps. We conducted a population-representative household survey between November 7 and December 4, 2022. Hemoglobin (Hb) concentration was measured by HemoCue 301, using capillary blood, and Rad-67, a novel non-invasive device. We collected four measurements per participant: two per device. We calculated Rad-67 bias and precision of Hb measurements and sensitivity and specificity of detecting anemia. Of the 812 NP-WRAs selected, 807 (99%) participated in the study. Anemia was detected in 39% of NP-WRA as classified by the Rad-67 compared with 47% of NP-WRA as classified by the HemoCue 301. Average bias of Rad-67 measurements was 1.1 ± 1.0 SD g/dL, using HemoCue 301 as a comparator. Absolute mean difference between the first and second measurements was 0.9 g/dL (95% CI 0.8, 0.9) using the Rad-67, compared with 0.6 g/dL (95% CI 0.5, 0.6) using the HemoCue 301. The Rad-67 had 49% sensitivity and 70% specificity for detecting anemia, compared with the HemoCue 301. The Rad-67 can be a useful tool for anemia screening; however, lower accuracy and precision, and poor sensitivity suggest it cannot immediately replace the HemoCue 301 in the study area.

Microscopic and quantitative characterization of germanium-indium bearing by-product from heavy metal metallurgy

Abstract This article presents the results of study on the material characterization of germanium-indium drosses (Ge-In-D). Ge-In-D are a by-product of obtaining zinc and lead, which are currently not processed yet. Due to the exceptionally high concentrations of germanium and indium in them, as well as the commercial value of these elements, it became important to properly identify Ge-In-D, which was the aim of this work. Ge-In-D were characterized quantitatively and microscopic analyzes were also performed. The chemical composition of Ge-In-D was determined as follows (percentage by mass): 27.195% Sn; 20.737% Pb; 15.764% Cu; 9.782% As; 9.274% Ge; 7.875% In; 3.872% Fe; 2.617% Ag; S, Ni, Zn, Ga, Se, Cd, Sb as the rest. The combination of granulometry and chemical analyzes shows that germanium and indium tend to accumulate in fine fractions.