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Abstract Background The epigenetic-age acceleration (EAA) represents the difference between chronological age and epigenetic age, reflecting accelerated biological aging. Observational studies suggested that oral disorders may impact DNA methylation patterns and aging, but their causal relationship remains largely unexplored. This study aimed to investigate potential causal associations between dental traits and EAA, as well as to identify possible mediators. Methods Using summary statistics of genome-wide association studies of predominantly European ancestry, we conducted univariable and multivariable Mendelian randomization (MR) to estimate the overall and independent effects of ten dental traits (dentures, bleeding gums, painful gums, loose teeth, toothache, ulcers, periodontitis, number of teeth, and two measures of caries) on four EAA subtypes (GrimAge acceleration [GrimAA], PhenoAge acceleration [PhenoAA], HannumAge acceleration [HannumAA] and intrinsic EAA [IEAA]), and used two-step Mendelian randomization to evaluate twelve potential mediators of the associations. Comprehensive sensitivity analyses were used to verity the robustness, heterogeneity, and pleiotropy. Results Univariable inverse variance weighted MR analyses revealed a causal effect of dentures on greater GrimAA (β: 2.47, 95% CI: 0.93–4.01, p = 0.002), PhenoAA (β: 3.00, 95% CI: 1.15–4.85, p = 0.001), and HannumAA (β: 1.96, 95% CI: 0.58–3.33, p = 0.005). In multivariable MR, the associations remained significant after adjusting for periodontitis, caries, number of teeth and bleeding gums. Three out of 12 aging risk factors were identified as mediators of the association between dentures and EAA, including body mass index, body fat percentage, and waist circumference. No evidence for reverse causality and pleiotropy were detected (p > 0.05). Conclusions Our findings supported the causal effects of genetic liability for denture wearing on epigenetic aging, with partial mediation by obesity. More attention should be paid to the obesity-monitoring and management for slowing EAA among denture wearers.

Heavy metals (HMs) pollution is a globally emerging concern. It is difficult to cost-effectively combat such HMs polluted soil environments. The efficient remediation of HMs polluted soil is crucial to protect human health and ecological security that could be carried out by several methods. Amidst, biological remediation is the most affordable and ecological. This review focused on the principles, mechanisms, performances, and influential factors in bioremediation of HMs polluted soil. In microbial remediation, microbes can alter metallic compounds in soils. They transform these compounds into their metabolism through biosorption and bioprecipitation. The secreted microbial enzymes act as transformers and assist in HMs immobilization. The synergistic microbial effect can further improve HMs removal. In bioleaching, the microbial activity can simultaneously produce H2SO4 or organic acids and leach HMs. The production of acids and the metabolism of bacteria and fungi transform metallic compounds to soluble and extractable form. The key bioleaching mechanisms are acidolysis, complexolysis, redoxolysis and bioaccumulation. In phytoremediation, hyperaccumulator plants and their rhizospheric microbes absorb HMs by roots through absorption, cation exchange, filtration, and chemical changes. Then they exert different detoxification mechanisms. The detoxified HMs are then transferred and accumulated in their harvestable tissues. Plant growth-promoting bacteria can promote phytoremediation efficiency; however, use of chelants have adverse effects. There are some other biological methods for the remediation of HMs polluted soil environment that are not extensively practiced. Finally, the findings of this review will assist the practitioners and researchers to select the appropriate bioremediation approach for a specific soil environment.

While the impact of the house purchase restriction (HPR) policy on the housing market in China has been deeply examined, there is still little known about how the housing market varies when such policy is abandoned. To fill this gap, we first theoretically propose two hypotheses concerning the relationship between abandoning HPR policy and housing price and transaction based on the housing literature. We then examine the hypotheses by taking Jinan, China as empirical case that offer an excellent policy setting of some districts having discarded the policy while the other remains. The results derived from Synthetic Control Method (SCM) showed that the cancellation of the HPR policy plays a vital role in increasing the transaction volume, but it fails to promote house prices. The findings remain reliable after a series of placebo and robustness tests. This article adds new insight to the debate on efficacy of government intervention via more granular quantitative data, and further contributes to policy implications regarding housing market development.

One of the core elements to enhance the resilience of the modern food industry chain is to lead enterprises to establish an integrated set of standards. To this end, it is necessary to solve the problems of difficulty in identifying key common technologies with dissemination and competitiveness and difficulty in connecting standards used by stakeholders in various links in the industry chain. Initially, an HMM-HITS Topic Keyness Identification Model was constructed based on the LDA topic clustering model, and characterized by the identification of key technologies which were not only competitive but also had strong dissemination power. Combined with the theme commonality identification model based on common skewness, a key commonality technology identification model was constructed. For the key common technologies identified by this model, based on the principles of value, rarity, difficulty in imitating, irreplaceability and inevitable implementation, the key common technologies that can enter the standard system list of leading enterprises were identified. Subsequently, based on the agricultural product supply chain mechanism, a standard connection consultation mechanism with the goal of improving resilience was built.. Finally, the standard complex formulation and optimization process for the modern grain industry chain was derived, which was verified in the formulation of the japonica rice standard complex.

Heavy metal residues in natural ecosystems have emerged as a significant global environmental problem requiring urgent resolution. Because these elements are non-biodegradable, organisms can accumulate excessive levels of heavy metal elements into their tissues. Previous studies suggest that prolonged exposure to heavy metal enrichment poses comprehensive toxicity to various organs in vertebrates. However, few studies have focused on elucidating the molecular mechanism underlying the hepatotoxic effects of heavy metal enrichment in Chiroptera. In this study, 10 Hipposideros armiger individuals were dissected from Yingde City (YD, relatively pollution-free) and Chunwan City (CW, excessive heavy metals emission). Environmental samples were also obtained. To investigate the mechanism of heavy metal toxicity in bat livers, we employed a combination of multi-omics, pathology, and molecular biology methods. Our results revealed significant enrichment of Cd and Pb in the bat livers and food sources in the CW group (P

Weak-signal limit is often used in estimating stochastic gravitational-wave background (SGWB) intensities. This approximation fails and the signal-to-noise ratio (SNR) can be much weaker when background signals are loud compared to the detector noise. In this work, we find that this issue is especially significant when dealing with networks of detectors that are widely separated. For the TianQin + LISA network, the SNR estimated under the weak-signal limit might be off by as large as an order of magnitude. Contour plots of SNR over the parameter spaces are also presented to indicate regions that will be affected by this correction. Our results suggest that DA and DB type extragalactic double white dwarfs may yield an SGWB with SNR surpassing 100 after 1 year of operation in weak-signal limit scenario, with a redshift-independent merger rate of about 500Mpc−3Myr−1. In fact, this value falls significantly below the necessary threshold. Similar influences arise for first-order phase transitions, yet pinning down the detectable parameters remains formidable due to model uncertainties.

We investigate the Λ particle motion and cluster states of BeΛ9−11 using a novel multiple cooling approach guided by the Control Neural Networks method (Ctrl.NN). The numerical results are well reproduced, and the Ctrl.NN method shows rapid convergence concerning the set of the basis states in comparison to traditional generator coordinate method (GCM) calculations. Taking advantage of this merit, we calculate ground state energies and rotational bands of BeΛ9−11 which agree well with experimental observations. By analyzing the density distributions of the main basis, a slight short-range repulsive correlation between Λ particle and α clusters in directions perpendicular to the axis of the Be8 core is revealed. The Λ particle presents a significant broad distribution as a consequence of this correlation, which we call an “analog π-orbit” structure. Furthermore, we prove that this correlation originates from the competition between kinetic energy and Λ-N interaction, as indicated by the energy curves for different configurations of BeΛ9. In the ground states of BeΛ10 and BeΛ11, the Λ particle is confined in a cage-like structure of core nuclei formed by two α clusters and valence neutrons. These structures lead to the development of more compact Λ particle configurations, and the shrinkage of α-α relative distance is also well reproduced.

BackgroundThe role of autoimmune diseases (ADs) in temporomandibular disorders (TMDs) has been emphasized in observational studies. However, whether the causation exists is unclear, and controversy remains about which specific disorder is destructive in TMDs. This Mendelian randomization (MR) study aims to estimate the causal effect of common ADs on TMDs.MethodsGenetic data from published genome-wide association studies for fourteen common ADs, specifically multiple sclerosis (MS, N = 15,283), ankylosing spondylitis (AS, N = 22,647), asthma (N = 408,422), celiac disease (N = 15,283), Graves’ disease (N = 458,620), Hashimoto thyroiditis (N = 395,640), primary biliary cirrhosis (PBC, N = 11,375), primary sclerosing cholangitis (PSC, N = 14,890), psoriasis vulgaris (N = 483,174), rheumatoid arthritis (RA, N = 417,256), systemic lupus erythematosus (SLE, N = 23,210), Type 1 diabetes (T1D, N = 520,580), inflammatory bowel disease (IBD, N = 34,652), and Sjogren’s syndrome (SS, N = 407,746) were collected. Additionally, the latest summary-level data for TMDs (N = 228,812) were extracted from the FinnGen database. The overall effects of each immune traits were assessed via inverse-variance weighted (IVW), weighted median, and MR-Egger methods, and performed extensive sensitivity analyses. Finally, 731 immune cell phenotypes (N = 3,757) were analyzed for their mediating role in the significant causality.ResultsUnivariable MR analyses revealed that genetically predicted RA (IVW OR: 1.12, 95% CI: 1.05-1.19, p < 0.001) and MS (IVW OR: 1.06, 95% CI: 1.03-1.10, p = 0.001) were associated with increased risk of TMDs. Two out of 731 immune cell phenotypes were identified as causal mediators in the associations of RA with TMDs, including “CD25++ CD8+ T cell % CD8+ T cell” (mediation proportion: 6.2%) and “CD3 on activated CD4 regulatory T cell” (5.4%). Additionally, “CD127 on granulocyte” mediated 10.6% of the total effect of MS on TMDs. No reverse directions, heterogeneity, and pleiotropy were detected in the analyses (p > 0.05).ConclusionThis MR study provides new evidence regarding the causal impact of genetic predisposition to RA or MS on the increased risk of TMDs, potentially mediated by the modulation of immune cells. These findings highlight the importance for clinicians to pay more attention to patients with RA or MS when consulting for temporomandibular discomfort. The mediating role of specific immune cells is proposed but needs further investigation.

Objective: To assess the ability of 2 commercially available smartwatches to accurately detect clinically significant hypoxia in patients hospitalized with coronavirus-19 (COVID-19). Patients and Methods: A prospective multicenter validation study was performed from November 1, 2021, to August 31, 2022, assessing the Apple Watch Series 7 and Withings ScanWatch inbuilt pulse oximetry, against simultaneous ward-based oximetry as the reference standard. Patients hospitalized with active COVID-19 infection not requiring intensive care admission were recruited. Results: A total of 750 smartwatch pulse oximetry measurements and 400 ward oximetry readings were successfully obtained from 200 patients (male 54%, age 66±18 years). For the detection of clinically significant hypoxia, the Apple Watch had a sensitivity and specificity of 34.8% and 97.5%, respectively with a positive predictive value of 78.1% and negative predictive value of 85.6%. The Withings ScanWatch had a sensitivity and specificity of 68.5% and 80.8%, respectively with a positive predictive value of 44.7% and negative predictive value of 91.9%. The overall accuracy was 84.9% for the Apple Watch and 78.5% for the Withings ScanWatch. The Spearman rank correlation coefficients reported a moderate correlation to ward-based photoplethysmography (Apple: rs=0.61; Withings: rs=0.51, both P

Abstract Background The role of thyroid health in temporomandibular disorders (TMDs) has been emphasized in observational studies. However, whether the causation exists is unclear, and controversy remains about which specific disorder, such as hypothyroidism or hyperthyroidism, is destructive in TMDs. This study aims to investigate the overall and specific causal effects of various thyroid conditions on TMDs. Methods Mendelian randomization (MR) studies were performed using genetic instruments for thyrotropin (TSH, N = 119,715), free thyroxine (fT4, N = 49,269), hypothyroidism (N = 410,141), hyperthyroidism (N = 460,499), and TMDs (N = 211,023). We assessed the overall effect of each thyroid factor via inverse-variance weighted (IVW), weighted median, and MR-Egger methods, and performed extensive sensitivity analyses. Additionally, multivariable MR was conducted to evaluate the direct or indirect effects of hypothyroidism on TMDs whilst accounting for TSH, fT4 and hyperthyroidism, and vice versa. Results Univariable MR analyses revealed a causal effect of hypothyroidism on an increased risk of TMDs (IVW OR: 1.12, 95% CI: 1.05–1.20, p = 0.001). No significant association between genetically predicted hyperthyroidism, TSH, or fT4 and TMDs. In the multivariable MR analyses, the effects of hypothyroidism on TMDs occurrence remained significant even after adjSusting for TSH, fT4 and hyperthyroidism (multivariable IVW OR: 1.10, 95% CI: 1.03–1.17, p = 0.006). No pleiotropy and heterogeneity were detected in the analyses (p > 0.05). Conclusions Hypothyroidism might causally increase the risk of TMDs through a direct pathway, highlighting the critical role of managing thyroid health in the prevention of TMDs. Clinicians should give heightened attention to patients with hypothyroidism when seeking medical advice for temporomandibular discomfort. However, caution is warranted due to the potential confounders, pleiotropy, and selection bias in the MR study.

The scheduling of smart home appliance electricity tasks can effectively distribute power loads and enhance the operational efficiency and stability of power grids. Additionally, effectively shifting the working hours of household appliances to off-peak hours with lower electricity prices could reduce the cost of household electricity consumption. Therefore, we aim to study a bi-objective household appliance scheduling problem under time-of-use (TOU) and threshold-based pricing tariffs, where the objectives are to simultaneously minimize the total electricity usage cost and peak load within a day. A bi-objective mathematical model is first presented for this problem. To the best of our knowledge, this is the first study to propose a novel bi-objective chemical reaction optimization (CRO) algorithm with problem-specific encoding and decoding schemes, as well as molecular reaction operators to solve the studied problem. Finally, the computational results of well-known multi-objective optimization benchmark instances and case study were reported and analyzed. The results indicate that our proposed approach achieves a better balance between exploitation and exploration, yields high-quality trade-offs between reducing the electricity cost and peak load, and outperforms existing algorithms in terms of solution quality and diversity.