Browse Articles

Men’s knowledge of obstetrics danger sign and associated factors in low-income countries: a systematic review and meta-analysis

Exploratory study of serum protein biomarkers for sudden cardiac arrest using protein extension assay: A case-control study

Background Biomarkers associated with the occurrence of sudden cardiac arrest (SCA) are not currently utilized in clinical practice. We aimed to identify novel protein biomarkers associated with sudden cardiac arrest (SCA) using proteomic profiling and evaluate their predictive power alongside traditional cardiovascular risk factors. Methods A total of 42 SCA patients with medical causes, aged ≤ 65 years and whose initial rhythm was shockable, and 42 age- and sex-matched controls were analyzed. The initial serum samples obtained after emergency department visits were used for SCA cases. Using a protein extension assay, we identified significant biomarkers through correlation analysis with SCA and extracted proteins with no or weak correlation with the initial lactate level and arrest-to-sampling time to account for post-cardiac arrest changes. The area under the receiver operating characteristic curve (AUROC) was calculated to assess the predictive performance of the extracted proteins. Results Among the 246 distinct proteins that met quality criteria, 97 showed a strong correlation with SCA. Among these 97 proteins, 44 showed weak or no correlation with lactate levels, and 12 showed weak or no correlation with onset-to-sampling time. Two proteins (AXL receptor tyrosine kinase [AXL] and TIMP Metallopeptidase inhibitor 4 [TIMP-4]) met all the criteria for biomarker extraction. Both showed significant associations with SCA and enhanced predictive power when combined with traditional risk factors in multivariable analysis. The AUROC for the baseline model using traditional risk factors was 0.692 (95% confidence interval [CI] 0.578–0.806), which improved significantly with the addition of AXL and TIMP-4 (AUROC [95% CI] 0.891 [0.817–0.964] and 0.910 [0.910–0.997], respectively). Conclusion AXL and TIMP-4 may be crucial role in the early detection and risk assessment of SCA. Future research to verify the utility of AXL and TIMP-4 in large cohorts is warranted.

Explainable hybrid transformer for multi-classification of lung disease using chest X-rays

Protective effect of Pinacidil on hypoxic-reoxygenated cardiomyocytes in vitro and in vivo via HIF-1α/HRE pathway

Cardiomyocyte hypoxia-reoxygenation (HR) is considered as a major cause of heart failure. Pinacidil is a classic ATP sensitive potassium channel opener and plays a crucial role in cardiomyocyte HR injuries. However, the specific mechanism is poorly understood. We established HR rat model and introduced 5-Hydroxydecanoate (5-HD), N-(2-Mercaptopropionyl)-glycine (MPG), and Dimethylethylenediylglycine (DMOG) to investigate the protection of Pinacidil (P) on cardiomyocyte. HE staining, electron microscopy and JC-1 staining were used to observe mitochondrial structure and mitochondrial membrane potential (MMP). Reactive oxygen species (ROS), hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor A (VEGF-A), heme oxygenase-1 (HO-1), and induced nitric oxide synthase (iNOS) were analyzed in this study. Network pharmacology analysis and auto-docking were used to predict the possible target of Pinadicil under cardiomyocyte HR condition. The integrity of mitochondrial structure and MMP were effectively promoted in P and MPG+DMOG + P groups. ROS was significantly increased after HR, treatment with P or MPG+DMOG + P, the content of ROS was increased. The expressions of HIF-1α, VEGF-A, HO-1 and iNOS were significantly increased in P and MPG+DMOG + P groups compared with HR group. Docking results confirmed that prolyl hydroxylase (PHD) was the most possible target for unsaturated binding with Pinacidil guanidine. Altogether, these data indicate that Pinacidil up-regulated and activated HIF-1α protein to protect caridomyocytes against HR injuries and the mechanism may be related to Pinacidil guanidine binding to PHD.

Development and validation of an Immune-related Gene-based model for predicting prognosis and immunotherapy outcomes in hepatocellular carcinoma patients

Intelligent tuning method for service scheduling in electric power communication networks based on operational risk and QoS guarantee

In the operational planning of electric power communication networks, a well-structured service scheduling scheme based on the established network topology can significantly enhance the risk prevention capabilities of these networks. Since routing policies directly influence data transmission paths, routing optimization serves as an effective strategy for improving network performance by mitigating transmission risks and threats. This paper introduces an Intelligent Tuning Method for Service Scheduling in Electric Power Communication Networks Based on Operational Risk and Quality of Service (QoS) Guarantee. Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. The improvements to the ant colony algorithm are made in four key areas: the definition of heuristic information, the weighting of parameters, the state selection strategy, and the pheromone update strategy. These enhancements aim to achieve optimal routing scheduling based on risk information. At the same time, a reconfiguration algorithm for power optical communication networks, based on service priority, is proposed for specific service requests. This algorithm provides both a primary routing path and an alternate routing path for service transmission, ensuring the delivery of high-priority services even when both the primary and standby paths are unavailable. Simulation results from an actual power business communication network demonstrate that the algorithm outputs the main and alternate paths with the lowest risk costs. Additionally, the path satisfaction of the proposed algorithm is improved by 7.4% compared to the traditional ant colony algorithm. This improvement validates the accuracy and superiority of the proposed algorithm and offers a valuable reference for ensuring the reliable operation of power optical fiber communication network systems.

Ethoxychelerythrine as a potential therapeutic strategy targets PI3K/AKT/mTOR induced mitochondrial apoptosis in the treatment of colorectal cancer

Optimizing breeding strategies for early-maturing white maize through genetic diversity and population structure

Maize production and productivity in sub-Saharan Africa are constrained by various factors. Assessing the genetic diversity of newly developed elite inbred lines can help identify lines with desirable genes and explore genetic relatedness for heterotic breeding. The objectives of this study were to assess the level of genetic diversity, and population structure, and identify appropriate clustering methods for assigning maize inbreds into heterotic groups. Three hundred and seventy-six elite inbreds extracted from three source populations were genotyped using Diversity Array Technology (DArTtag) mid-density platform. Results from 1904 of 3,305 SNP marker obtained revealed average marker polymorphism information content (PIC) of 0.39, observed heterozygosity of 0.02, gene diversity of 0.37, minor allele frequency of 0.29, Shannon and Simpson indices of 6.86 and 949.09, respectively, and allele richness of 787.70. The optimum sub-population was three defined by an admixture-based model and principal component analysis. The average genetic distance was 0.303 varying from 0.03 (TZEI 2772 × TZEI 2761) to 0.372 (TZEI 2273 × TZEI 2832). For appropriate heterotic classification of the 376 elite inbreds, the use of IBS distance matrix and average linkage clustering method provided the highest cophenetic correlation coefficient (0.97). Three heterotic group (HG) were identified using IBS distance and average linkage clustering method with HG 1 have 188 inbreds, HG 2 having 137, and HG 3 having 59 inbreds. The pedigree-based phylogenetic tree showed substantial consistency with the heterotic groups identified. The F-statistics based on the underlying population structure revealed 10% variation among sub-populations and 90% variation within sub-populations with a moderate level of genetic differentiation (0.10). The elite inbred lines showed a high degree of genetic diversity, which could be beneficial for developing new, early-maturing white hybrids to mitigate production constraints in sub-Saharan Africa.

Frequency reconfigurable PIN diode-based Reuleaux-triangle-shaped monopole antenna for UWB/Ku band applications

Abstract This paper presents a frequency reconfigurable monopole antenna developed for UWB/Ku band applications. The design employs a microstrip-fed Reuleaux-triangle-shaped patch with a defected ground structure. The antenna exhibits a wide operating bandwidth achieved due to rectangular slits integrated into the Reuleaux-triangle patch. Meanwhile, adding rectangular slots in the ground plane improves the return loss level. Frequency reconfigurability is obtained by utilizing PIN diodes to adjust the current distribution, altering the antenna’s electrical length via the capacitive and inductive effects induced by the rings near the feed line. The antenna operates in two distinct frequency bands, 2.68–8.55 GHz and 12.7–15.65 GHZ, contingent upon the PIN-diodes’ ON/OFF states. In the OFF state, the antenna covers the UWB region, in particular, the ISM band (5.8 GHz), WLAN band (5.2 GHz), and lower X-band (8 GHz), exhibiting a 10 dB impedance bandwidth from 2.68 to 8.55 GHz with a maximum gain of 2.36 dBi. In the ON state, the antenna functions in the Ku band (12.7–15.65 GHz) with gains from 2.63 to 3.85 dBi. The antenna’s dynamic switching between UWB and Ku band operations makes it suitable for applications such as satellite communications, health monitoring, 5G, aerospace, and remote sensing.

Enhanced object detection in low-visibility haze conditions with YOLOv9s

Low-visibility haze environments, marked by their inherent low contrast and high brightness, present a formidable challenge to the precision and robustness of conventional object detection algorithms. This paper introduces an enhanced object detection framework for YOLOv9s tailored for low-visibility haze conditions, capitalizing on the merits of contrastive learning for optimizing local feature details, as well as the benefits of multiscale attention mechanisms and dynamic focusing mechanisms for achieving real-time global quality optimization. Specifically, the framework incorporates Patchwise Contrastive Learning to fortify the correlation among positive samples within image patches, effectively reducing negative sample interference and enhancing the model’s capability to discern subtle local features of haze-impacted images. Additionally, the integration of Efficient Multi-Scale Attention and the Wise-IoU Dynamic Focusing Mechanism enhances the algorithm’s sensitivity to channel, spatial orientation, and locational information. Furthermore, the implementation of a nonmonotonic strategy for dynamically adjusting the loss function weights significantly boosts the model’s detection precision and training efficiency. Comprehensive experimental evaluations of the COCO2017 fog-augmented dataset indicate that the proposed algorithm surpasses current state-of-the-art techniques in various assessment metrics, including precision, recall, and mean average precision (mAP). Our source code is available at: https://github.com/PaTinLei/EOD.

Phytochemical variation, phenolic compounds and antioxidant activity of wild populations of Iranian oak

SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study

Background The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection. Methods In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time. Results Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels. Conclusions Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

SMILES-based QSAR and molecular docking studies of chalcone analogues as potential anti-colon cancer

Abstract QSAR modeling was applied to predict the anti-colon activity (against HT-29) of 193 chalcone derivatives using the Monte Carlo method, based on the index of ideality correlation (IIC) target function. The models were constructed using CORAL software, which employed optimal descriptors combining SMILES notation and hydrogen-suppressed molecular graphs (HSG). Among the developed models, Split #2 was identified as the best-performing model, with R2_validation = 0.90, IIC_validation = 0.81, and Q2_validation = 0.89. The mechanistic interpretation of the models, utilizing enhancing/reducing promoters, demonstrated that the models are capable of accurately predicting the pIC50 values of other chalcone derivatives with high robustness and precision. Based on these promoters, ten new compounds were selected from the ChEMBL database for pIC50 prediction, and molecular docking was performed using the protein with PDB ID:1SA0.

Delayed hepatic response and impaired cytokine dynamics in aged mice following burn injury: Implications for elderly patient care

Introduction Burn injuries in elderly patients result in higher morbidity and mortality compared to younger individuals. This study investigates age-related differences in inflammatory hepatic responses to burn injuries. Method Young (8–10 weeks) and aged (20-21 months) female C57BL/6 mice were subjected to a 15% total body surface area burn or sham injury. Serum and liver samples collected at 3, 6-, 9-, 12-, and 24-hours post-injury were analyzed for serum amyloid A (SAA) levels, SAA1 and SAA2 hepatic gene expression, serum cytokines (IL-6, IL-1β, TNF-α, and IL-10), and hepatic STAT3 activation. Results Aged mice showed a delayed and dysregulated response. In young mice, SAA levels rose significantly at 6 hours postburn (5.09 ±  0.2-fold), while in aged mice, SAA increased at 12 hours (39.1 ±  2.06-fold), p <  0.01. Hepatic expression of SAA1 and SAA2 also peaked early in young mice (8.357 ±  1.257-fold and 5.91 ±  0.664-fold at 3 hours) but was delayed until 12 hours in aged mice. Young mice demonstrated early IL-6 peaks at 3 hours (990 ±  83.2 pg/ml), while aged mice reached a delayed, higher IL-6 peak at 24 hours (3804 ±  1408 pg/ml, p <  0.05). Similar age-related delays occurred for IL-1β and TNF-α. Aged mice had significantly elevated IL-10 at 6 hours (993.9 ±  99.41 pg/ml vs. 67.69 ±  6.635 pg/ml in young, p <  0.001). STAT3 activation peaked at 3 hours in young mice (2.686 ±  0.226-fold) but was delayed until 24 hours in aged mice (0.5958 ±  0.0368-fold, p <  0.05). Conclusions This study identifies age-related variations in inflammatory markers and acute hepatic responses to burn injuries, with aged mice showing delayed and reduced inflammatory responses compared to younger counterparts. These findings underscore the importance of age-specific strategies in burn injury management to enhance outcomes for elderly burn patients.

Misconception of Schizophyllum commune strain 20R-7-F01 origin from subseafloor sediments over 20 million years old

Cognitive diagnostic analysis of mathematics key competencies based on PISA data

As a new generation of assessment instrument, cognitive diagnosis integrates the measurement objectives into the cognitive model to diagnose the fine-grained knowledge of students. Taking the PISA 2012 dataset in mathematics from Shanghai, Hong Kong, Macau and Taiwan as the research subject, this study constructed a cognitive model with the attributes of Mathematical Abstraction, Logical Reasoning, Mathematical Modeling, Intuitive Imagination, Mathematical Operation and Data Analysis, and made an analysis of the mastery of students’ mathematical competencies of different attributes in four regions, and the learning paths of the students’ mathematical competencies were constructed. The results showed that Shanghai had the obvious advantages in each attribute; the mastery mode of Hong Kong, Macau and Taiwan showed a common trend, and they all indicated a relatively low percentages of competencies in Logical Reasoning and Intuitive Imagination. In terms of the learning paths, the learning paths in the four regions reflected diversities, but obvious main learning paths existed. Majority of the knowledge states’ abilities were below 0. While in Hong Kong, Taiwan, and Macau, more knowledge states’ abilities were above 0. This research provided a reference for the systematic analysis of students’ knowledge status and learning path.

Evaluating site selection for optimal photovoltaic installations and CO₂ emission reduction in selected districts of khyber pakhtunkhwa

Abstract As the global market for renewable energy solutions expands, geospatial analysis is becoming crucial for optimizing solar potential. The current study assesses the suitability of installing PV solar system in the Mardan, Peshawar, and Nowshera districts in Pakistan using a multi-criteria decision-making (MCDM) approach. Analysis of different parameters, such as topography, land use and land cover (LULC), solar radiation and land surface temperature (LST), were performed to find the appropriate locations for solar in their respective regions. The study employed binary classification and weighted overlay methods to detect patterns of spatial suitability. Peshawar showed maximum ability with 859.8 km² categorized as favorable with a projected annual power output capacity of 67.77 trillion kWh and a decrease in CO₂ emission of 2.78 billion metric tons. Mardan closely followed the suitable area with 828.4 km² with energy generation of 39.74 trillion kWh/year and reduction of CO₂ emissions by 1.63 billion metric tons. Nowshera has an appropriate area of 503.0 km², for energy output of 670.06 billion kWh, and CO₂ reduction of 27.46 million metric tons. These results underline the importance of combining geospatial and meteorological data for accurate planning of solar energy systems. By highlighting location-specific features, including topography and solar irradiance illustrates the importance of tailoring energy outputs and environmental impacts to local contexts. These insights help guide policymakers in driving renewable energy projects, and support Pakistan’s sustainable development and climate targets.

Integrating status-neutral and targeted HIV testing in Zimbabwe: A complementary strategy

Introduction Zimbabwe exclusively implemented targeted HIV testing until 2022 when Status-neutral testing was embraced. Whilst targeted testing aims to expand access and uptake of testing among high-risk individuals, status-neutral testing emphasizes post-test linkage to prevention and treatment services. To address how the two concepts relate in practice, we explored how status-neutral and targeted testing concepts correlate, in developing a double-edged strategy for effective case identification and linkage to prevention and treatment. Methods We conducted a cross-sectional study on 36 multi-stage sampled sites across 4/10 provinces of Zimbabwe. A national screening algorithm was used to determine patient risk profiling and eligibility for testing. Screened-out patients were offered HIVST. Both screened and non-screened patients were tested and analysed for positivity ratios and linkage to post-test services. Epicollect5 was used to collect data and analysed using EpiData software and Stata. Univariate, bivariate and multivariate analyses were conducted at a 5% significance level. Results Of 23,058 HIV tests done, females constituted 55% (n = 12,698), whilst 63.5% (n = 14,650) were retested. Through screening, at-risk patients contributed 75.1% to the overall positivity (1,296/1,727), from 66% (n = 15,289) of the total HIV tests conducted. All screened-out patients were non-reactive on HIVST: 1,182/1,182. The 45–49-year category was 3.6 times more likely to test positive (a95%CI:2.67,4.90). Males were 3.09 times more likely to test positive in adjusted analysis (a95%CI: 2.74, 3.49). First tests were 65% more likely to test HIV positive (a95%CI: 1.43, 1.91) whilst screened patients were 3.89 times more likely to link to HIV prevention services (a95%CI: 3.05, 4.97), against 25.5% (n = 1,871) linkage among patients not screened. Conclusion The complementarity of the status-neutral and targeted testing approaches is evident from our results. By prioritizing high-risk individuals for testing and ensuring comprehensive linkage to both prevention and treatment services, these integrated strategies can effectively identify and manage people living with HIV. This combined approach optimizes resource use, particularly in low- and middle-income countries, and contributes to improved health outcomes and reduced HIV transmission rates.

Enhanced antimicrobial efficacy and biocompatibility of albumin nanoparticles loaded with Mentha extract against methicillin resistant Staphylococcus aureus

Deeper Effects of fiscal multidimensional poverty reduction: household characteristics, financial lags and elite capture

The governance of multidimensional relative poverty is a key challenge in rural poverty alleviation in the new era, as well as an important practice of the implementation of the United Nations Sustainable Development Goals in China. Based on provincial fiscal and financial data as well as data from the China Family Panel Studies (CFPS), this article employs multilevel linear regression and structural equation modeling to empirically examine the impact and mechanisms of fiscal investment in agriculture on multidimensional relative poverty among farmers. The research results indicate that fiscal investment in agriculture can effectively alleviate multidimensional relative poverty among rural households, and this conclusion still holds after the robustness and endogeneity tests of traditional measurement and Double Machine Learning. However, differences in household characteristics affect the performance of fiscal poverty alleviation. Households in the central and western regions, with larger family sizes, younger members, and lower levels of education, exhibit higher policy responsiveness. In terms of mechanisms, digital inclusive finance and social capital serve as important channels for fiscal multidimensional poverty reduction. However, attention should be paid to the positive lag effect of digital inclusive finance and the risk of “elite capture” in households with low levels of social capital. Accordingly, the article recommends that fiscal spending should be increased and made more efficient, with precise policy measures, strengthened institutional coordination, and efforts to cultivate optimal levels of social capital. While the article is limited by data availability to allow for a more in-depth and complex discussion, it still provides insights for fiscal strategies aimed at building high-quality shared prosperity.