Browse Articles

Mechanisms and optimization for simultaneous removal of Cd(II) and Sb(V) from aqueous solutions using birnessite and fulvic acid composite

Medicaid expansion, dental visits and expenditures in veterans, older adults, and the foreign-born

Abstract We assessed the relationship between implementation of the Patient Protection and Affordable Care Act (ACA), indicated as a state expanding Medicaid, dental visits, and costs in U.S. military veterans, older adults ≥ 65 years, and foreign-born individuals. Using the 2012–2016 Medical Expenditure Panel Surveys for a secondary data analysis, logistic and two-part regressions were used to model dental visits and costs as a function of key explanatory variables. Differences-in-differences estimates compared changes in dental visits and costs in Medicaid expansion to non- expansion states. Post-Medicaid expansion and ACA implementation, the foreign-born in Medicaid expansion states had higher odds of a dental visit compared to those in non-Medicaid expansion states (OR = 1.17, 95% CI, 1.05–1.32) in adjusted analysis. While they spent $31 more than the predicted per capita expenditure of $395, this increase was not statistically significant. The changes in dental visits and expenditures for veterans and older adults ≥ 65 years were not statistically significant. These findings suggest that the ACA, through expansion of Medicaid programs has improved access for the foreign-born while controlling costs. Health care reform initiatives like Medicaid expansion can enhance access to dental care and help mitigate the economic and access to care barriers vulnerable population groups like the foreign-born face.

Prognostication of advanced CO2 capture using tunable solvents with an ensemble learning-based decision tree model

Serotype 2 Streptococcus suis growth inhibition mediated by intraspecies contact-dependent mechanism

SPKSE: secure public key searchable encryption withstand keyword guessing attacks

AI-driven UAV with image processing algorithm for automatic visual inspection of aircraft external surface

Network toxicology and bioinformatics analysis reveal the molecular mechanisms of polyethylene terephthalate microplastics in exacerbating diabetic nephropathy

Cryptic absence and genetic variation of Plasmodium falciparum PfHRP2 and PfHRP3 from isolates in Papua, Indonesia

Suppressing Phase Transitions and High-Pressure Amorphization through Tethered Organic Cations in Organochalcogenide-Halide Perovskites

Association between endogenous lactate accumulation and dysregulated activation of the NLRP3 inflammasome pathway in schizophrenia

Methodological analysis of synthesizing graphene from carbon source solvents

Drosophila melanogaster as a model organism to investigate sex specific differences

Abstract Sex differences in physiology, anatomy, behavior, and genetics are well-documented throughout the animal kingdom. These differences are often neglected in research. This imbalance can have detrimental effects, as seen in cases where certain drugs have stronger side effects in females than in males. The fruit fly, Drosophila melanogaster, presents a promising model for studying these sex-specific differences because it shares many disease-related genes and is easy to use. RNA of 10-day-old and 30-day-old D. melanogaster (w1118) was isolated and sequenced. In 10-day-old flies 3969 genes are significantly higher expressed in males than in females, and 7176 genes are significantly lower expressed in males. In 30-day-old males 3735 genes are significantly higher expressed than in females, and 7101 genes are significantly lower expressed. In detail, the present study shows that male flies exhibit higher expression levels of genes involved in toll signaling, Imd signaling, insulin signaling, and lipid metabolism. These findings highlight D. melanogaster as a valuable model organism for studying sex differences in these highly conserved signaling pathways. This model could help analyzing the sex-specific effects of dietary interventions or drugs, ultimately leading to a better understanding of sex-specific interconnections and improving the development of more effective, sex-specific medical treatments.

NECKCHECK PROJECT: enhancing diagnostic accuracy in oropharyngeal squamous cell carcinoma through computer-based radiological tools

Abstract The interpretation of radiological images for head and neck tumors often lacks standardized protocols, increasing the risk of diagnostic inconsistencies. This study introduces a computerized radiological checklist designed to enhance diagnostic accuracy and standardize the evaluation of oropharyngeal squamous cell carcinoma (OPSCC) imaging among otolaryngologists (ENTs). A radiological checklist was developed based on a comprehensive literature review and digitized into an intuitive interface. A concordance study involving 15 ENTs was conducted, assessing 90 OPSCC cases in two phases: before and after using the checklist. Diagnostic agreement with radiologists was measured using Cohen’s kappa coefficient, and a mixed-effects linear model evaluated accuracy improvements, accounting for patient sex, age, stage, and HPV status. The checklist significantly improved diagnostic concordance, increasing Cohen’s kappa from 0.28 (95% CI: 0.09–0.46) without it to 0.66 (95% CI: 0.55–0.77) with it (p < 0.01). The mixed-effects model showed a mean improvement of 2.66 correct responses in the checklist group (SE 0.31, p < 0.001). This study supports the effectiveness of this checklist in improving the diagnostic consistency and accuracy of OPSCC imaging. This method shows promise as a practical tool to reduce errors and enhance clinical practice among ENT specialists.

3D-printed temperature and shear stress-controlled rocker platform for enhanced biofilm incubation

Abstract Growing biofilms of thermophilic (heat-loving) and psychrotrophic (cold-tolerant) bacteria pose several challenges due to specific environmental requirements. Thermophilic bacteria typically grow between 45 and 80  $$^{\circ }$$ C, while psychrotrophic bacteria thrive between 0 and 15  $$^{\circ }$$ C. Maintaining the precise temperature and fluid conditions required for biofilm growth can be technically challenging. To overcome these challenges, we designed the Bio-Rocker, a temperature- and shear stress-controlled rocker platform for biofilm incubation. The platform supports temperatures between − 9 and 99  $$^{\circ }$$ C, while its digital controller can adjust the rocking speed from 1 to 99 $$^{\circ }$$ /s and set rocking angles up to ±19 $$^{\circ }$$ . This ability, together with data from analytical models and multi-physics simulations, provides control over the shear stress distribution at the growth surfaces, peaking at 2.4 N/m $$^2$$ . Finally, we evaluated the system’s ability to grow bacteria at different temperatures, shear stress, and materials by looking at the coverage and thickness of the biofilm, as well as the total biomass. A step-by-step guide, 3D CAD files, and controller software is provided for easy replication of the Bio-Rocker, using mostly 3D-printed and off-the-shelf components. We conclude that the Bio-Rocker’s performance is comparable to high-end commercial systems like the Enviro-Genie (Scientific Industries) yet costs less than $350 dollars to produce.

Effect of dolutegravir-based antiretroviral therapy on glycemic control in female mice

Powdery mildew resistance prediction in Barley (Hordeum Vulgare L) with emphasis on machine learning approaches

Abstract By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley (Hordeum Vulgare L). A 130-line F8-F9 barley population caused Badia and Kavir to grow at the Gonbad Kavous University Research Farm on three planting dates (19 November, 19 January, and 19 March), with three replicates in 2018/2019 and 2019/2020. The study employed RReliefF, MRMR, and F-Test feature selection algorithms to identify essential phenotype traits and molecular markers. Subsequently, Decision Tree, Random Forest, Neural Network, and Gaussian Process Regression models were compared using MAE, RMSE, and R2 metrics. The Bayesian algorithm was utilized to optimize the parameters of the machine-learning models. The results indicated that the Neural Network model accurately predicted powdery mildew disease resistance in barley lines. The evaluation based on high R2 values, as well as low MAE and RMSE, highlighted the efficacy of these models in identifying significant phenotype traits and molecular markers associated with disease resistance. The findings demonstrate machine learning models’ potential in accurately predicting powdery mildew disease resistance in Barley. The neural network model specifically showed excellent results in this area because it managed to identify critical phenotypic traits and molecular markers very well. This research highlights the importance of combining AI with molecular markers for improved disease resistance and other desirable crop traits during plant breeding.

Impact of incubation and gestation periods on the dynamics of a spatially heterogeneous eco-epidemiological model

Analysis of the influencing factors for adverse reproductive outcomes in patients with positive TPOAb and the establishment of a nomogram prediction model

Reliability assessment and small signal analysis of the enhanced switched impedance inverter with low input current ripple

Comprehensive assessment of the acute lethal, risk level, and sub-lethal effects of four insecticides on Trichogramma ostriniae

Trichogramma ostriniae is one of the most successfully used natural enemies in the integrated management of agroforestry pests. However, the extensive use of insecticides poses a significant threat to the survival and efficacy of T. ostriniae. To assess the compatibility of chemical pesticides with T. ostriniae, we investigated the acute toxicity, risk level, and sub-lethal effects of four insecticides (chlorfenapyr, emamectin benzoate, phoxim, and lambda-cyhalothrin) on reproduction, parasitism, detoxification enzymes, protective enzyme activities, and active substances under laboratory conditions. The results revealed that phoxim had the highest acute toxicity, with a median lethal concentration value of 2.8 × 10−7 mg/mL, whereas chlorfenapyr had the lowest at 5.06 × 10−3 mg/mL. Emamectin benzoate was classified as high risk, whereas the others were classified as extremely high risk. Insecticide exposure during the larval and pupal stages significantly reduced the emergence of T. ostriniae (P < 0.05). Lambda-cyhalothrin, emamectin benzoate, and chlorfenapyr extended the time required for prey-handling and reduced parasitism efficiency by 0.70%, 2.45%, and 4.50%. In contrast, phoxim increased the time required for prey-handling and improved parasitism efficiency by 25.37%. All insecticides affected protective enzyme activities, induced detoxification enzyme activity, reactive oxygen species, malondialdehyde and mitochondrial respiratory chain complex I levels, and decreased the adenosine triphosphate level. These findings underscore the differential impacts of insecticides on T. ostriniae and emphasize the need for cautious pesticide selection to balance pest control and natural enemy conservation, providing essential scientific guidance for sustainable agroforestry pest management.