Browse Articles

Unlocking the therapeutic potential of Origanum majorana through GC-MS and computational analysis to identify EGFR inhibitors for breast cancer

Associations between metabolic syndrome and allergic diseases a nationwide study in Korea and literature review

Abstract Atopic dermatitis (AD), allergic rhinitis (AR), and asthma are typical allergic diseases, with a common pathogenesis involving increased type 2 immunity. Despite numerous studies, the association between these diseases and metabolic syndrome (MetS) remains controversial. This study aimed to explore relationships between AD, AR, and asthma both to MetS and to each of its components. Population-based, cross-sectional data were obtained from the Korean National Health and Nutrition Examination Survey from 2019 to 2020. Multiple logistic regression analyses were conducted to evaluate the association between allergic diseases and MetS. The results were compared with those of previous studies of the association between MetS and allergic diseases, identified in a literature review following a search of PubMed and the Cochrane Library. Based on assessments of 1,329, 4,824, and 1,172 patients with AD, AR, and asthma, respectively, negative associations between both AD and AR and MetS were determined, after adjusting for confounding factors. By contrast, asthma was positively associated with MetS (odds ratio [OR] 0.58, 95% confidence interval [CI] 0.50–0.67; OR 0.73, 95% CI 0.67–0.78; OR 1.70, 95% CI 1.51–1.92, respectively). The heterogeneous findings highlight the need for further investigation of associations between the studied allergic diseases and MetS as well as each of its components.

Impact of unmet expectations in clinical practice on nursing student competencies in a multi-center study

Antimicrobial strategies of nanoparticles and chelating agents for mitigating Staphylococcus spp. contamination on slaughterhouse surfaces

Paired regional complementarity in diffusion MRI reveals disease-specific microstructural profiles in PD, MSA, and PSP: a feasibility study

Effect of moisture content on N₂ injection displacement efficiency of methane in bituminous coal

Evaluation of cerebral blood flow and glymphatic function in acute mountain sickness by MRI ASL and DTI ALPS

Flyway population increase and emergence of new wintering grounds with climate change in an Arctic-breeding goose

Abstract Changes in climate, land cover, hunting disturbance, and food availability are often cited as drivers of bird migratory patterns. We examined long-term changes in the Pannonic flyway population of the Arctic-breeding Greater White-fronted Goose (GWfG, Anser albifrons ) in regular counts conducted in Hortobágy National Park, eastern Hungary, between 1989 and 2019. During 31 years, GWfG counts increased from fewer than 2,000 to more than 30,000 individuals, with a stronger increase in spring than in autumn. The rate of increase exceeded that of the entire Pannonic flyway population. Spring counts rose more rapidly in the early years (1989–1997), whereas autumn counts increased faster more recently (2007–2019). Overwintering began in the mid-2000s, and winter counts have increased sharply since 2007. Mean temperature influenced GWfG counts positively in winter and negatively in spring, while the number of frost days in winter and snowy days in spring had negative effects. GWfG counts decreased less from December to January when temperatures did not drop or increased. These results indicate that milder winters have played a major role in the long-term increase and appearance of overwintering. In addition, small changes in land cover and slight increases in hunting disturbance may have also contributed to the increase of the GWfG counts at the study site, whereas food availability on nearby croplands declined and may have had an opposite effect. Our study shows that the disproportionate increase in staging and overwintering GWfG is primarily driven by climate change, especially by the rising frequency of unusually mild winters.

Genome-wide identification and functional characterisation of the EDS1 gene family reveals evolutionary conservation and stress-responsive regulatory roles in barley

A universal brown dwarf desert formed between planets and stars

Giant planets and brown dwarfs play a crucial role in star and planet formation as they are situated at the boundary between planets and stars with uncertain formation mechanisms. Previous observational searches for the formation boundary were hampered by the lack of large unified samples of wide-orbit giant planets and substellar companions. A combined analysis of radial velocity and astrometry mitigates this problem and has significantly enlarged the sample. Here, we present a rigorous statistical analysis of the sample of 55 giant planets, brown dwarfs, and low-mass stellar companions orbiting FGK stars. We quantitatively analyze the occurrence rates of brown dwarfs and identify a distinct brown dwarf desert at approximately 30 M J , with no evidence of disappearance up to 20 au. Unlike previous studies that predicted a declining planet occurrence rate beyond the water-ice line, we identify a population of giant planets and low-mass brown dwarfs in this region. The metallicity and eccentricity trends in our sample suggest that these are the consequences of two different formation scenarios. Our combined population synthesis model successfully accounts for the observed brown dwarf desert, supporting the dual formation hypothesis.

A delayed pharmacological treatment strategy attenuates noise-induced tinnitus in rats

Spectral characterization and severity assessment of rice brown planthopper damage using multivariate models

Prevalence and factors associated with characteristics of hepatitis B susceptibility among vaccinated adults in Malaysia: a cross-sectional study

Abstract Hepatitis B vaccination is a cornerstone of global disease prevention, yet susceptibility among vaccinated individuals remains a concern. This study aimed to determine the prevalence and factors associated with hepatitis B susceptibility in vaccinated adults in Malaysia. A cross-sectional analysis was conducted using data from the National Health and Morbidity Survey (NHMS) 2020, involving 4,083 respondents aged 15 years and older. Serological testing for hepatitis B virus (HBV) markers, HBsAg, anti-HBs, and anti-HBc assays was performed. Susceptibility was defined based on serological profiles, and complex sampling logistic regression was employed to identify associated risk factors. Among the participants, 64.9% (2,649/4,083) were susceptible to HBV infection, with a prevalence of 22.9% among vaccinated individuals. Susceptibility was notably higher in young adults aged 15–29 (19.0%), and Malay ethnic group (20.5%). Additionally, individuals with tertiary education (18.9%) and single marital status (20.1%) exhibited elevated susceptibility. Multivariate analysis revealed significant associations with ethnicity, where Chinese (aOR 7.10, 95% CI: 2.67, 18.91) and other ethnic groups (aOR 5.67, 95% CI: 2.03, 15.92) had higher odds of susceptibility compared to Malays. Education level was another strong predictor, with tertiary (aOR 9.82, 95% CI: 3.61, 26.73), secondary (aOR 8.88, 95% CI: 3.42, 23.11), and primary education (aOR 6.96, 95% CI: 2.77, 17.51) showing substantially increased odds relative to no formal education. This study highlights a substantial prevalence of hepatitis B susceptibility among vaccinated adults in Malaysia. Ethnicity and education level emerged as significant factors. These findings underscore the need for targeted interventions, such as booster vaccinations or enhanced screening, particularly for high-risk groups like the Chinese and other minority ethnicities, as well as those with higher education levels. Further research is warranted to explore these associations’ underlying reasons and optimize vaccination strategies in Malaysia.

Abnormal elevated PANX1 expression hampers endometrial decidualization by upregulating extracellular ATP concentration in patients with recurrent implantation failure

Practices for glucose measurement with a glucometer in a population of diabetic patients. An observational study

Antimicrobial use and Escherichia coli resistance patterns in Hungarian pig farms: a data-driven farm-level analysis

Abstract Antimicrobial resistance (AMR) poses a critical challenge to both human and veterinary medicine, with pig production recognized as one of the major contributor due to intensive antimicrobial usage (AMU). This study aimed to explore the relationship between AMU and AMR patterns of Escherichia coli isolated from commercial pig farms, using data-driven analytical methods. Farm-level records were harmonized with microbiological data from 203 isolates collected in December 2023 across four Hungarian farms. AMU was summarized over 3-, 6-, 9-, and 12-month retrospective windows and expressed in modified population-corrected units, while AMR was quantified as mean minimum inhibitory concentration (MIC) and AMR rate under epidemiological and clinical breakpoints. The results revealed substantial variation in AMU among farms, with amoxicillin predominating across timeframes. Farm-specific comparisons indicated that higher AMU may not always coincide with elevated resistance levels, and data analysis did not consistently identify a direct association between use and resistance at the individual farm level, which warrants further investigation in larger datasets. Correlation analyses identified strong intra-class relationships among β-lactams and fluoroquinolones, as well as a cross-class linking, suggesting concurrent selection pressures. Overall, the integration of AMU and AMR data demonstrated the feasibility of farm-level surveillance for AMR modelling and provides a foundation for future predictive systems to support antimicrobial stewardship in livestock production.

Learning-aided observer design for improving autonomous vehicle safety

Abstract This paper introduces a novel method for the enhancement of automated vehicle safety and efficiency during critical manoeuvres. The fundamental of the presented method is the observer design architecture, in which lateral dynamic states of the vehicle are evaluated. The novel observer consists of both model-based and machine-learning-based methods to ensure the selected design performances, such as efficient trajectory tracking and safety evaluation of the autonomous vehicle. In contrast to the already introduced and applied stability index-based methods, the proposed safety evaluation process is able detect stability loss and performance degradation of the autonomous vehicle. In the proposed observer-based safety evaluation method, stability and performance loss detection is based on the comparison of model-based and learning-based state observation. The main novelty of the paper is the design of the reinforcement learning (RL) based observer in a guaranteed structure that results in small observation error even under nonlinear vehicle dynamics. Furthermore, a lateral safety index is defined based on the value of the improvement vector representing the addition to the model-based estimation. By this means, with the proposed safety evaluation method both safety and performance loss hazards can be identified simultaneously.

Author Correction: The effects of cosolutes and crowding on the kinetics of protein condensate formation based on liquid–liquid phase separation: a pressure-jump relaxation study

Floquet angular modulation for 6G systems

Abstract This paper introduces a computationally efficient method for angular modulation analysis in 5G/6G systems, significantly reducing numerical complexity and computation time compared to conventional techniques. Inspired by optical spectroscopy, we present novel approaches tailored for 5G/6G applications like reconfigurable intelligent surfaces (RIS) and metasurfaces. Unlike traditional direct methods (Fourier, Jones matrix, Bessel series, orbital angular momentum), our technique employs a modified Fourier method combined with Floquet analysis.

Square-slotted THz metamaterial-inspired MIMO antenna design optimized with machine learning for TWPAN networks and next-generation communication systems

Abstract The growing demand for high-speed communication necessitates antennas operating at higher frequencies in the THz range with broad bandwidth, compact size and higher gain. In this research, we have proposed a compact THz antenna designed with metamaterial-inspired elements to achieve improved gain and wideband performance. This paper presents the design and performance analysis of a high-efficiency MIMO antenna system for terahertz (THz) communication applications. The proposed antenna is optimized to deliver robust diversity performance, low mutual coupling, and minimal channel degradation. The design is also optimized with machine learning, with the highest R 2 value of 0.95. The optimized design gives 54 THz bandwidth and 7.6 dBi gain. The ECC remains well below 0.005, ensuring excellent isolation between elements. The TARC exhibits values below − 10 dB across the critical bandwidth, confirming low reflection under simultaneous port excitation. These results demonstrate the designed structure’s potential for integration into THz communication and THz Wireless Personal Area Network.