Background Previously identified asthma-susceptibility genes account for a small part of asthma heritability and their role in asthma pathogenesis is unclear. We explored associations between genetic variants in the 17q21 locus, CDHR3 (cadherin-related family member 3) , coding a receptor for Rhinovirus-C, preschool wheeze and asthma at 7 years. Methods Four genetic variants in the 17q21 locus (rs8076131, rs12603332, rs8079416, rs3859192) and rs6967330 in CDHR3 were studied regarding associations with preschool wheeze and asthma at 7 years. We compared 125 cases, enrolled during an acute wheezing episode, with 96 healthy controls at preschool age (6-45 months). At 7 years cases with asthma (N=68) and without asthma (N=31) were compared regarding genetic variants and other clinical parameters. Results Rs8076131 (AA vs GG) was associated with preschool wheeze (OR 3.50, p=0.001), and asthma at 7 years (OR 8.55, p=0.002). Rs12603332 (CC vs TT) was related to asthma at 7 years irrespective of rhinovirus infection at inclusion or current signs of airborne allergy (aOR 7.17, p=0.016). The association of rs6967330 with asthma was restricted to children with specific genotypes in the 17q21 locus; rs8076131-AA (p=0.028) , rs8079416-CC (p=0.006), and rs3859192-TT (p=0.042). Rhinovirus infection at inclusion was significantly related to asthma exclusively in homozygotes rs8079416-CC (p=0.032) and rs3859192-TT (p=0.027). Conclusion Our results highlight the impact of asthma heritability by reporting strong associations between 17q21 locus and asthma in a high-risk cohort. The association of rs6967330 in CDHR3 and early-life rhinovirus infection with asthma at school age might be dependent on specific genotypes in the 17q21 locus.

Fire-related smoke inhalation-induced acute lung injury (SI-ALI) is a prevalent condition in modern fires, characterized by high mortality and a lack of targeted therapeutic options. Previous research has been hindered by instability in smoke generation and modeling methods, limiting the investigation of SI-ALI mechanisms. This study, for the first time, utilized organ-on-a-chip and organoid technologies, optimizing chip design and precisely controlling smoke generation from non-metallic materials to establish a human-relevant, physiologically accurate model of fire-related SI-ALI. The results demonstrate that this model effectively simulates the alveolar-capillary barrier and replicates key pathological features of lung injury, including oxidative stress, apoptosis, immune cell adhesion, inflammatory responses, capillary leakage, and mitochondrial damage. Injury responses of endothelial and epithelial cells to smoke exposure were thoroughly assessed at the organ level. Integrating proteomics and molecular biology techniques, along with comparisons to animal models, identified disease-specific pathways related to the spliceosome and carbon metabolism, as well as pathogenic molecules such as catechol-O-methyltransferase (COMT) and nitrilase 1 (NIT1). Furthermore, molecular docking of COMT revealed potential therapeutic candidates from the FDA-approved drug library, including Ractopamine HCl and Bimatoprost. The efficacy of intravenous vitamin C combined with nebulized budesonide was validated on the chip model, establishing a foundation for clinical applications. This study provides a robust model for investigating fire-related SI-ALI and offers novel insights into underlying mechanisms and therapeutic development.

A three-dimensional numerical method for the analysis of Single-lap Adhesive Joints of Aluminum under bending load is presented. Firstly, a meshfree numerical method is investigated for the simulation of the single-lap joint under Four Point Bending load. The element free Galerkin numerical method based on moving least-squares shape functions is used in the meshfree method. The discontinuities at the adhesive segments are approximated with additional degrees of freedom at the nodes. Secondly, we use finite element method by using Ansys program to verify the meshfree method's results and we concluded that the results are consistent in two meshfree and finite element methods.In this meshfree method, we find the displacement in each node for a defined load by using moving least square and element free Galerkin methods, and from these displacements obtainedthe three-dimensional normal and shear stress distributions in the length and depth of the mid-plane of an adhesive layer thickness of 0.12 mm and a lap length of 25 mm, subjected to bending loads at four points. Then calculated Raghava damage criterion for nodes in adhesive segment for two meshfree and finite element methods.

Ongoing climate change mandates improved understanding of how temperature fluctuations influence organismal evolution and behavior. Detritus-based nest-retreats in spiders have originated multiple times in parallel—hypothesized to be an adaptive response to climatic fluctuations. We investigated the potential role of climate change in shaping the evolution of nest-retreats over geological timescales, and the short-term effect of temperature on the morphology and energy investment of nest-retreat in Campanicola campanulata. Phylogenetic analyses reconstruct twelve origins of nest-retreats, first appearing in the Eocene, and diversifying during the Late Cenozoic Icehouse period. Spiders respond to experimentally lowered temperatures by making larger nest-retreats, indicating a direct impact of temperature on retreat architecture. Our results for the first time affirm the thermoregulatory function of spider nests and suggest that temperature impacts nest-retreats across both evolutionary and ecological timescales. Nest-retreat spiders can serve as a model to study the origins of thermoregulatory nest-building in animals and how it may be impacted by ongoing climate change.

Long homozygous chromosome segments are known as runs of homozygosity (ROH); these reflect patterns of identity by descent and can be used to measure individual inbreeding, map recessive traits, and reconstruct demographic histories. Here we review some key considerations with ROH detection and the inferences pertaining to inbreeding and demographic analyses in wild populations.

not-yet-known not-yet-known not-yet-known unknown Host density, genetic diversity and social structure are key factors influencing disease transmission in wildlife populations, but their interactions remain poorly understood in insects. We assessed how populations of two common bumble bee species, Bombus pascuorum and B. terrestris are structured across island and mainland sites in the British Isles and France. B. pascuorum formed distinct genetic clusters on islands, with varying levels of heterozygosity with only the Isle of Arran in Scotland clustering with mainland populations. B. terrestris populations were less structured, indicating a higher dispersal ability; however, populations on the Isle of Man and the Scilly Isles showed low heterozygosity, and the Isle of Man was genetically separated from other islands and mainland populations. Nest density was similar between species. To assess how population structure affects pathogen prevalence, we tested bees for five micro-parasitic and four viral pathogens, expecting higher pathogen transmission within nests and in dense, genetically homogenous populations. B. pascuorum from the same nest showed more similar infection profiles than bees from different nests, indicating increased intra-colony transmission. Contrary to expectations, islands with high heterozygosity showed high viral prevalence and no reduction in micro-parasite infections. Bumble bee nest density was linked to a higher prevalence of Apicystis bombi, while other pathogens showed inconsistent patterns. These results suggest that while social structure affects pathogen transmission, genetic diversity does not consistently reduce prevalence. Instead, generalist bumble bee pathogens could be more affected by host species diversity and density. Island populations with limited gene flow and low genetic diversity may be more vulnerable to pathogen pressure, particularly under changing environmental conditions.

A document by shaghayegh rahmani. Click on the document to view its contents.

Binswanger's disease (BD) or sub-cortical vascular dementia is a rare form of dementia that is caused by long-time small vessel ischemic changes in the brain's white matter[1]. Commonly associated with long-standing diabetes, hypertension & previous cerebrovascular events[2]. Neurological examination, as well as radiological evidence, is important to exclude the diagnosis with other related cerebrospinal-vascular disease. Her Solving diagnostic dilemmas leads to a successful treatment & follow-up with the disease prognosis.

INTRODUCTION The RIEMANN ZETA FUNCTION ζ(s) is a central object in number theory and complex analysis, defined for complex variables and intimately connected to the distribution of prime numbers through its zeros. The famous RIEMANN HYPOTHESIS conjectures that all non-trivial zeros of the zeta function lie on the critical line $(s) = {2}$. In this paper, we explore the Riemann zeta function through the lens of SET-THEORETIC and SWEEPING NET METHODS , leveraging creative comparisons of specific sets to gain deeper insight into the distribution of its zeros. By rewording and analyzing the Riemann Hypothesis using set-theoretic arguments, applying sweeping net techniques, and integrating modal logic interpretations, we aim to provide new perspectives and support for this profound conjecture. Our objectives are: - Define the zeta function and its properties relevant to the zeros. - Reword the Riemann Hypothesis using set-theoretic language and establish logical equivalence. - Introduce and compare specific sets related to the zeros of ζ(s). - Apply set-theoretic and sweeping net methods to analyze the distribution of zeros. - Provide rigorous proofs about the absence of zeros in certain regions, including mechanical justifications with all steps. - Incorporate modal logic interpretations into the proof. - Discuss implications for the Riemann Hypothesis. —

To address the multi-dimensional tracking control problem with control saturation and uncertainties, a receding horizon control (RHC) based scheme is explored. The RHC guarantees the instructions change softly and smoothly with controllable transition time by utilizing the rolling window optimization mode, whereas its practical application still suffers from the computational efficiency limitation and stability problem in presence of disturbances. To reduce the computational complexity of RHC, a rolling optimization approach is proposed for tackling the input-constrained nominal RHC problem by incorporating a regularization approach, spectral-form discretization and quadrature collocation to extend the model predictive static programming technique. To further guarantee the anti-interference ability, an input-constrained state feedback control based on the linear-matrix-inequality (LMI) theory is proposed as the ancillary correction control of RHC for restricting the disturbed states motion caused by exogenous disturbances in an admissible invariant set. Finally, the robust stability of the whole closed-loop system is theoretically illustrated. Applying the proposed method into the multi-constrained midcourse tracking guidance scenario of an anti-aircraft missile, the comparative simulations demonstrate its marked superiorities in computational performance and robustness.

not-yet-known not-yet-known not-yet-known unknown Glycosylation is a critical quality attribute in biopharmaceuticals that influences crucial properties, such as immunogenicity and stability. Current methods for modeling glycosylation typically rely on imprecise or limited data on nucleotide sugar donor dynamics. These methods use in vitro transporter kinetics or flux balance analysis, which overlook the key aspects of metabolic regulation. We devised an integrative workflow for absolute subcellular NSD quantification in both cytoplasm and secretory organelles. Using subcellular fractionation, exhaustive sample extraction, and liquid chromatography triple-quadrupole tandem mass spectrometry, we accurately measured NSD concentrations ranging 1.6 amol/cell to 3 fmol/cell. Our NSD concentration profiles aligned closely with the glycan distributions on antibodies, particularly after nutrient pulsing to stimulate NSD production. This method enables empirical observation of compartment-specific NSD dynamics. Thus, this study provides novel insights indicating that N-glycosylation, which governs NSD supply, is primarily regulated within the Golgi apparatus. This method offers a novel tool to obtain sophisticated data for the more efficient optimization of glycosylation processes in production cell lines.

Vegetables are essential for human diets, providing crucial nutrients for metabolic reactions, but their production is low in many countries due to soil-borne diseases and other factors. The strategies of microbiome on vegetable disease management, challenges and future perspectives needs attention and awareness creation. Therefore, the objective of this review is reviewing and creating awareness on the Strategies, challenges and future perspectives of microbiome in Vegetable Disease Management. Plant microbiomes, microbial communities associated with plant tissues, can help manage diseases like Fusarium wilt, bacterial wilt, root rot, and others through mechanisms such us production of Enzymes; secretion of extracellular cell wall degrading enzymes, production of Antibiotics and secondary metabolites; rhizosphere colonization, production of Siderophores, HCN and indole acetic acid, production of Antibiotics and metabolites, antibiosis induced systemic resistance, production of endo and exo glucanases and production of antimicrobial activity of organic acids respectively. Environmental and host-related factors, including agricultural practices, temperature, plant species, and developmental stages, influence plant-microbe interactions. Despite their potential, microbiome strategies face challenges and require greater awareness and more research. Future research should focus on understanding these interactions under various conditions and host-specific factors.

In the era of rapid technological advancement, Mobile Edge Computing (MEC) has become essential for supporting latency-sensitive applications such as IoT, autonomous driving, and smart cities. However, efficient resource allocation remains a challenge due to the dynamic nature of MEC environments. This study proposes an advanced Multi-Agent Reinforcement Learning (MARL) framework combined with a lightweight neural network, LtNet, to optimize task offloading and resource management in MEC. The MARL framework allows each device to learn its optimal offloading strategy, while LtNet enhances computational efficiency using H-Swish activation and selective Squeeze-and-Excitation modules. Experimental results demonstrate that the proposed methods achieve a 12-22% reduction in task completion time, a 5-8% decrease in energy consumption, and consistently high resource utilization, making them highly effective in managing dynamic MEC environments.

The use of autonomous robots has grown in popularity during the last few years. Robots, including such wheeled and legged autonomous robots, have become such a simple answer to dull, dirty, and hazardous chores. Outdoor applications, like as on a muddy road, are possible with legged robots is harder to control and has a high cost because to its intricate structure. Despite TWSBMRs are best used on a homogeneous surface, they can also be used to substitute legged robots. Two Wheeled Self-Balancing Mobile Robots (TWSBMR) outperform other types of wheeled robots. TWSBMR occupies less space and is capable of zero-radius manoeuvring. The system dynamics modelling of the TWSBMR considering the effect of road muddiness and the design hierarchical sliding mode control (HSMC) are the key contributions of this research. In this study robot's movement is limited to a two-dimensional platform. For the system measuring performance, a criterion such as settling time, percentage overshoot, and RMSE has been presented. The proposed criteria are used to quantify the response of the system to a HSMC in simulation. The simulation findings show that under muddy road scenarios, the robot can maintain the balance and maintain the desired trajectory. Specifically, the closed loop system demonstrated excellent performance with a tilt-angle settling time of 7 seconds, a maximum overshoot of 0.2637 • , and a maximum undershoot of-6.97 •. Additionally, the position of the vehicle achieved a settling time of 5 seconds with a percentage overshoot (POS) of 7.2%. These results indicate that the controller effectively regulates the system to a standstill position, ensuring smooth movement to the desired position under muddy road condition.

The bonding across the lattice and ordered structures endow crystals with unique symmetry and determine their macroscopic properties. Crystals with unique properties such as low-dimensional materials, metal-organic frameworks, and defected crystals, in particular, exhibit different structures from bulk crystals and possess exotic physical properties, making them intriguing subjects for investigation. To accurately predict the physical and chemical properties of crystals, it is crucial to consider long-range orders. While GNN excels at capturing the local environment of atoms in crystals, they often face challenges in effectively capturing longer-ranged interactions due to their limited depth. In this paper, we propose CrysToGraph ( Crystals with Transformers on Graph), a novel and robust transformer-based geometric graph network designed for unconventional crystalline systems, and UnconvBench, a comprehensive benchmark to evaluate models’ predictive performance on multiple categories of crystal materials. CrysToGraph effectively captures short-range interactions with transformer-based graph convolution blocks as well as long-range interactions with graph-wise transformer blocks. CrysToGraph proofs its effectiveness in modelling all types of crystal materials in multiple tasks, and moreover, it outperforms most existing methods, achieving new state-of-the-art results on two benchmarks. This work enhances the development of novel crystal materials in various fields, including the anodes, cathodes, and solid-state electrolytes.

Plants have established strategies to improve cold/freezing tolerance through cold acclimation in response to low-temperature stress in winter. After 10 years acclimation in cultivation to the north, the Plumbago auriculata L. has been able to overwinter in field, but the key genes and mechanisms of cold tolerance were not yet clear. MYB transcription factors were widely involved in plant growth and development, metabolism, and abiotic stress regulation. In particular, little has been reported tropical evergreen plants and their regulatory mechanisms in response to cold stress or cold acclimation. The results showed that the short-term artificial cold domestication for 10 d resulted in higher cold hardiness in Plumbago auriculata L., which explained from a physiological level that cold acclimation is an effective way to improve cold resistance. By RNA-seq profiling, PaMYBS3 was identified as a signaling gene that contributes to winter dormancy and inhibits growth and development in Plumbago auriculata L., acting as a negative regulator. Specifically, OE- PaMYBS3 promoted the growth and development compared with the TC- PaMYBS378 and TC- PaMYBS3159 conserved domain mutant lines in Arabidopsis thaliana, while freezing stress resulted in decreased photosynthetic performance, increased H 2O 2, O 2-, MDA, low soluble sugar content, and weaker cold tolerance. Virus-induced gene-silencing mediated knockdown of PaMYBS3 inhibited the growth and development of Plumbago auriculata L., and the physiological data in VIGS lines after cold stress showed that the low temperature adaptability was improved. In addition, based on RT-qPCR, the expression levels of regulating metabolism related genes in cold acclimation and VIGS lines were verified, including low-temperature dormancy, plant hormones, carbohydrates, etc., which indirectly proved that Plumbago auriculata L. had both CA and WD ecological strategies to resist cold. During cold acclimation, PaMYBS3 promoted ecological dormancy by inhibiting the growth and development cold acclimation, and enhanced cold tolerance in a CBF-independent pathway by maintaining stable carbohydrate metabolism, phytohormone signals, osmoregulatory substances, and ROS metabolism. In summary, this study provides new insights into the way PaMYBS3 responded to low temperatures, and it was regulated in tropical evergreens, using Plumbago auriculata L. as an example. It also provides more evidence for its theoretical basis for overwintering in field.

Annexin (ANX), a calcium-phospholipid-binding protein, belongs to a superfamily of calcium-dependent membrane phospholipid-binding proteins, which are widely found in prokaryotic and eukaryotic organisms. They are classified into five groups: A, B, C, D, and E according to the different species and genera. The family of Annexin A(ANXA), which consists of Annexin A1-A11 and Annexin A13, is commonly found in vertebrates. Previous studies have shown that ANXA is involved in multiple processes, such as the formation of biological membranes, the establishment of ion channels, and signal transduction, thereby playing an essential role in cellular life activities such as cell differentiation, proliferation, apoptosis, autophagy, and modulating inflammation. Annexin A1 (ANXA1), a member of the ANXA family, is involved in various disease processes, such as atherogenesis and development of atherosclerosis, tumor proliferation, apoptosis, invasion, and metastasis. This molecule has been increasingly studied, showing potential as a therapeutic target or diagnostic marker for circulatory system diseases. Therefore, this article reviews the value of ANXA1 in the diagnosis and treatment of circulatory system-related diseases.

not-yet-known not-yet-known not-yet-known unknown Heart failure is the end stage of many cardiovascular diseases, with high morbidity, mortality and re-hospitalization rates, which brings a huge medical burden and economic pressure to the society. Inflammation has a significant impact on the development, progression and prognosis of heart failure. Although a growing number of studies have demonstrated the critical role of NLRP3 inflammasome in HF, a bibliometric analysis of research hotspots and trends in this area has not been performed. In this study, we retrieved articles related to NLRP3 inflammasome in HF from the Web of Science Core Collection (WoSCC) database for the period of 2010 - 2024 and analyzed them using visualization tools such as Citespace, VOSviewer, Scimago Graphica, and Microsoft Office Excel 2021 and other visualization tools to analyze the data. After screening, we included a total of 282 papers published by 2130 researchers from 500 institutions in 35 countries/regions, with relevant papers published in 133 journals. China played an important part in this field, with the highest outputs. Abbate, Antonio was the most published author, The institutions that publish the most papers were Virginia Commonwealth University, Wuhan University, INTERNATIONAL IMMUNOPHARMACOLOGY were the most published journal, CIRCULATION was the most cited journal with the highest number of citations, which has had a greater impact on the research in this field. The current research hotspots focus on the activation and inhibition pathways of NLRP3 inflammasome, the exploration of novel targets of HF, and the connection between HF and mitochondria. The relationship between HF and pyroptosis, the clinical study of drugs related to NLRP3 inflammasome as a therapeutic target of HF are a trend for future research. Our study provides a comprehensive bibliometric analysis and summary of NLRP3 inflammasome -related studies in HF, and the analysis provides a theoretical basis for the study of NLRP3 inflammasome in HF and provides guidance for future research directions.

In this paper, a trajectory tracking control strategy based on radial basis function neural network (RBFNN) learning control is proposed for servo systems. A multi-parameter adaptive RBFNN is first constructed with update rate design. Subsequently, weight generalization rules are introduced to achieve high-precision tracking of test trajectories based on learned knowledge without retraining. Furthermore, for trajectory magnification scenarios, a specific generation algorithm is designed, which is combined with the generalization rules and achieves high-precision tracking of magnified trajectories that are not included in the training data. Experiment results demonstrate that the proposed method can achieve high-precision tracking of test trajectories and generalization to similar trajectories.

The right subclavian artery (RSA) — superior vena cava (SVC) fistula is a rare form of arteriovenous fistula, characterized by the presence of abnormal channels connecting arteries and veins. For the first time, we report the diagnosis of an RSA-SVC fistula in a fetus. It can be challenging to differentiate this condition from supra-cardiac total anomalous pulmonary venous connection (TAPVC). However, findings suggest that simultaneous dilation of the innominate artery and superior vena cava, bidirectional blood flow within the aortic arch, and a biphasic unidirectional spiculated blood flow spectrum at the confluence can serve as three key indicators for differentiation.

This study assesses the effectiveness of Sustainable Urban Drainage Systems (SuDS) in mitigating urban flooding and enhancing stormwater management in Machala, Ecuador. The implementation of SuDS resulted in a 57.64% reduction in flood volume and a decrease in peak flow from 10.50 m 3s -1 to 5.91 m 3s -1. Infiltration capacity improved from 0.75 mm to 2.43 mm, while average surface runoff was nearly halved from 19.27 mm to 10.48 mm. A specially designed porous concrete with approximately 30% porosity showed optimal performance. These findings indicate that SuDS can significantly contribute to urban planning and flood management in coastal developing cities. The study recommends prioritizing rain gardens and porous pavements, creating local SuDS guidelines, integrating these systems into urban planning, establishing long-term monitoring, and involving local communities. The insights gained here offer valuable guidance for other coastal cities in Ecuador and similar regions, demonstrating a sustainable approach to managing urban flooding and enhancing water resilience.

A document by Ayotunde Giwa. Click on the document to view its contents.

There is a sizeable body of scholarship on health inequalities and morality. What is less well covered in the literature is research which considers health inequalities and morbidity. This article specifically examines the issue of long-term illness (LTI) in the United Kingdom, which may or may not limit people’s daily activities and the work they are able to do. It poses the research question, was the propensity of LTI aggravated by the Covid pandemic? The evidence suggests that existing health inequalities associated with LTI have worsened since the pandemic. Using a multinomial logit model, the paper then computes the probability of working-age respondents to the UK-LFS having a long-term illness and, if they do, further computing the probability of this illness being limiting in either moderate or severe form. Following this, the paper computes the likelihood of a person with a LTLI having various health conditions. Lastly, the paper compares the probabilities of persons having a LTLI between 2019 and 2022 and tests whether the pandemic significantly altered these probabilities both in aggregate and for the narrower categories of population subgroups.

To define the optimistic multiple-granulation(OMG) supra interior operator i n t R A and the OMG-supra closure operator c l R A associated with a set A in a multiple-granulation approximation space, we used the concepts of the OMG-lower set O L Σ m i = 1 R i ( A ) and the OMG-upper set O U Σ m i = 1 R i ( A ) . These operators establish an approximate topological space referred to as optimistic multiple-granulation supra topological spaces. Additionally, we introduce the concepts of OMG-supra-open and OMG-supra-closed approximation sets, as well as OMG-supra-continuous and OMG-irresolute approximations.