Browse Articles

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.

A machine learning method for predicting molecular antimicrobial activity

Values, motivation, and physical activity among Chinese sport sciences students

Different studies have shown that values and motivation predict physical activity, but no study has tested how values and motivation may interact to predict physical activity. Specifically, the present research aimed to test how values and motivation toward physical activity measured within the SDT could predict global physical activity among Chinese sports science students. The indirect effects of openness to change and self-transcendence values on predicting physical activity through autonomous motivation were significant. These results help us understand how highly abstract psychological constructs such as values may influence physical activity through motivation. Studying values combined with motivation may help better understand the factors that motivate or inhibit physical activity.

An isogeometric modeling and vibro-acoustic characteristics analysis of a double panel-acoustic cavity coupling system with in-plane functionally graded materials

Cryptic speciation in arid mountains: An integrative revision of the Pristurus rupestris species complex (Squamata, Sphaerodactylidae) from Arabia based on morphological, genetic and genomic data, with the description of four new species

In the arid landscapes of the Arabian Peninsula, high levels of cryptic diversity among reptiles, and especially in geckos, have recently been revealed. Mountain ranges within the peninsula were shown to contain the highest richness of reptile endemicity, serving as refugia to species less adapted to the hyper-arid conditions of the lowlands. With up to 19 endemic reptile species, the Hajar Mountains of southeastern Arabia are a clear example of this pattern. Owing to its old geological history, complex topography and geographic isolation from the rest of the peninsula, this mountain range rises as a hotspot of reptile biodiversity and endemicity in Arabia, and provides the perfect scenario to study the processes of evolution and diversification of reptiles in arid mountain ranges. In the present study we investigate the systematics of the Pristurus rupestris species complex, a group of geckos exhibiting cryptic morphological traits along with a remarkably deep evolutionary history. Initially considered a single species distributed throughout coastal Arabia, and with some scattered populations at the Horn of Africa, several recent studies have shown that Pristurus rupestris actually comprises a species complex restricted to the Hajar Mountains of southeastern Arabia. Here, we utilize an integrative approach assembling several morphological, genetic, genomic, and ecological datasets to resolve this long-standing systematic challenge. Results support the existence of four new cryptic Pristurus species in the Hajar Mountains with three new Oman endemics. While no unique diagnostic morphological characters were identified, some slight morphological differences occur between species, especially among high-elevation species relative to the rest. Despite the lack of clear morphological differentiation, extreme levels of genetic variation were found between species with genetic distances of up to 24% in the 12S mitochondrial marker, resulting from deep divergence times of up to 10 mya. Moreover, all species have been found in sympatry with at least another representative of the species complex and without any signs of apparent and ongoing gene flow among them. These findings yield profound implications for conservation efforts, as one of these newly described species presents an extremely restricted distribution (only known from a single locality and three individuals), requiring immediate attention for protection. Overall, this study sheds light on the hidden diversity within the P. rupestris species complex, emphasizing the importance of preserving biodiversity in the face of ongoing environmental changes, while highlighting, once again, the Hajar Mountains of southeastern Arabia as a cradle of reptile biodiversity.

Crosado embalming related alterations in the morpho-mechanics of collagen rich tissues

Abstract Crosado-embalming has been successfully used as embalming technique in research and teaching for over 20 years. It is applied in biomechanical testing experiments if the fresh tissues are unavailable, e.g., for cultural, ethical, logistical or health and safety reasons. However, features of human Crosado-embalmed tissues biomechanical characteristics including its load-deformation properties in comparison to fresh tissues and its controllability through hydration fluids may be insightful and therefore need to be studied further. This study compared the uniaxial load-deformation properties and the cross-sectional area (CSA) measurements of fresh-frozen and Crosado-embalmed collagen-rich tissues, namely the iliotibial band (ITB, 16 unembalmed and 35 embalmed specimens) and cranial dura mater (DM, 60 unembalmed cadavers, and 25 embalmed specimens). The water content of 120 Crosado-embalmed ITB samples (30 cadavers) were analysed considering established rehydration treatments, including polyethylene glycol (PEG). Crosado-embalmed tissues presented an increased elastic modulus (EM) (all p < 0.050; e.g., Crosado ITB PEG only 306 ± 91 MPa vs. fresh-frozen ITB PEG only 108 ± 31 MPa; mean ± standard deviation; p < 0.001) and ultimate tensile strength (UTS) (e.g., Crosado ITB PEG only 46 ± 15 MPa vs. fresh-frozen ITB PEG only 21 ± 8 MPa; p < 0.001) when rehydrated similar to the fresh tissues. The maximum force was different for the dura mater (Crosado 25 ± 13 N vs. fresh 21 ± 20 N; mean ± standard deviation; p = 0.050) but not for the ITB. The CSA following rehydration in PEG only was decreased for Crosado-embalmed samples (3.4 ± 1.2mm2, ITB; 1.1 ± 0.5 mm2, DM) compared to fresh-frozen (5.8 ± 2.1mm2, ITB; 3.1 ± 1.2mm2, DM) (all p ≤ 0.003). Furthermore, rehydration effects were observed following 24 h of PEG treatment (untreated tissues, 49 ± 9% vs. PEG only, 77 ± 4%; p < 0.001), in comparison to fresh samples (69%) tissues were hyperhydrated. In conclusion, Crosado-embalming appears to alter collagen-rich tissues’ morphological and mechanical properties. While an increase in material properties of Crosado-embalmed tissues was observed (Emod and UTS), the overall load-bearing capacity and peak structural strength remained unaltered for ITB tissues. This may result from CSA-related, geometric or molecular alterations after the fixative and osmotic water protocols related to changes in the collagen backbone and water-binding capacity.

Characterization of methane microseepage from natural gas reservoirs in mild climate: A case study of Xinchang gas field

Methane microseepage from oil and gas fields significantly contributes to atmospheric methane level, making it a critical factor in global climate change. Therefore, accurate monitoring of surface flux and investigating migration mechanism are pivotal to evaluating and mitigating the impact of methane microseepage. In this study, methane microseepage from natural gas reservoirs in a mild climate was investigated, using Xinchang gas field as a case study. Soil samples were collected to analyze geochemical anomalies of acid-hydrolyzed hydrocarbons (AHH) and altered carbonates (AC). Surface methane flux from natural gas reservoirs were monitored, using a greenhouse gas analyzer and static gas collection chambers. Methane release patterns and migration mechanism were then discussed. Headspace and soil gas samples were collected to determine the hydrocarbon composition and carbon isotope profile. The results indicate that surface methane flux in Xinchang gas field is weak, exhibiting three release patterns: continuous, episodic, and flat. Spiked anomalies of AHH and AC co-exist in the test area, suggesting methane migration from reservoirs to surface. Hydrocarbon composition and carbon isotope profile in headspace and soil gas samples confirm thermogenic origin of methane. These findings offer new insights into the behavior of methane microseepage from natural gas reservoirs in mild climate. It is also suggested that close monitoring and stringent regulation of methane microseepage, as well as continuous investigation on factors affecting this phenomenon, are essential to the management of geological methane emissions. The conclusions of this work align with previous studies and are applicable to managing methane microseepage from oil and gas reservoirs in a wider scope.

Hyperkalemia is associated with short- and mid-term mortalities in critically ill patients in the MIMIC IV database

Interventions to improve adherence/compliance to home noninvasive positive pressure ventilation in stable hypercapnic chronic obstructive pulmonary disease patients: A systematic review protocol

Introduction Chronic obstructive pulmonary disease (COPD) is a prevalent condition often leading to chronic hypercapnic respiratory failure in its advanced stages. Home noninvasive positive pressure ventilation (Home-NIPPV) has emerged as a key therapeutic strategy for managing stable hypercapnic COPD patients, improving survival rates, and enhancing quality of life. Despite these benefits, patient adherence/compliance to Home-NIPPV remains a significant challenge, hindered by various barriers. The present paper is a protocol of a systematic review that aims to identify and evaluate interventions designed to improve adherence/compliance to Home-NIPPV in stable hypercapnic COPD patients. Methods The protocol is developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines and was registered in PROSPERO (CRD42024581616). A comprehensive literature search across PubMed, Scopus and Cochrane Library will be conducted. Eligible studies will include randomized controlled trials that focus on interventions that aims to improve adherence/compliance to Home-NIPPV in stable hypercapnic COPD patients. Data extraction will be meticulously carried out by two independent reviewers. The Joanna Briggs Institute critical appraisal tool will be utilized to assess the quality and risk of bias of the included studies. The findings of this systematic review will be synthesized to provide a thorough understanding of effective strategies to enhance adherence/compliance to Home-NIPPV in stable hypercapnic COPD patients. Conclusion The results of this review could inform clinical practice and guide the development of targeted strategies to improve adherence/compliance to Home-NIPPV and consequently outcomes in stable hypercapnic COPD patients. Registration This protocol was registered in the International Prospective Register of Systematic Reviews under the reference code CRD42024581616.

Coupling process of carbon sink service flow based on metacoupling framework

Development and validation of predictive models for diabetic retinopathy using machine learning

Objective This study aimed to develop and compare machine learning models for predicting diabetic retinopathy (DR) using clinical and biochemical data, specifically logistic regression, random forest, XGBoost, and neural networks. Methods A dataset of 3,000 diabetic patients, including 1,500 with DR, was obtained from the National Population Health Science Data Center. Significant predictors were identified, and four predictive models were developed. Model performance was assessed using accuracy, precision, recall, F1-score, and area under the curve (AUC). Results Random forest and XGBoost demonstrated superior performance, achieving accuracies of 95.67% and 94.67%, respectively, with AUC values of 0.991 and 0.989. Logistic regression yielded an accuracy of 76.50% (AUC: 0.828), while neural networks achieved 82.67% accuracy (AUC: 0.927). Key predictors included 24-hour urinary microalbumin, HbA1c, and serum creatinine. Conclusion The study highlights random forest and XGBoost as effective tools for early DR detection, emphasizing the importance of renal and glycemic markers in risk assessment. These findings support the integration of machine learning models into clinical decision-making for improved patient outcomes in diabetes management.