Porphyromonas gingivalis: A key role in Parkinson's disease with cognitive impairment?

Cognitive impairment (CI) is a common complication of Parkinson's disease (PD). The major features of Parkinson's disease with cognitive impairment (PD-CI) include convergence of α-Synuclein (α-Syn) and Alzheimer's disease (AD)-like pathologies, neuroinflammation, and dysbiosis of gut microbiota. Porphyromonas gingivalis (P. gingivalis) is an important pathogen in periodontitis. Recent research has suggested a role of P. gingivalis and its virulence factor in the pathogenesis of PD and AD, in particular concerning neuroinflammation and deposition of α-Synuclein (α-Syn) and amyloid-β (Aβ). Furthermore, in animal models, oral P. gingivalis could cause neurodegeneration through regulating the gut-brain axis, suggesting an oral-gut-brain axis might exist. In this article, we discussed the pathological characteristics of PD-CI and the role of P. gingivalis in them

Construction and experimental validation of a signature for predicting prognosis and immune infiltration analysis of glioma based on disulfidptosis-related lncRNAs

BackgroundsDisulfidptosis, a newly discovered mechanism of programmed cell death, is believed to have a unique role in elucidating cancer progression and guiding cancer therapy strategies. However, no studies have yet explored this mechanism in glioma.MethodsWe downloaded data on glioma patients from online databases to address this gap. Subsequently, we identified disulfidptosis-related genes from published literature and verified the associated lncRNAs.ResultsThrough univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) regression algorithms analyses, we identified 10 lncRNAs. These were then utilized to construct prognostic prediction models, culminating in a risk-scoring signature. Reliability and validity tests demonstrated that the model effectively discerns glioma patients’ prognosis outcomes. We also analyzed the relationship between the risk score and immune characteristics, and identified several drugs that may be effective for high-risk patients. In vitro experiments revealed that LINC02525 could enhances glioma cells’ migration and invasion capacities. Additionally, knocking down LINC02525 was observed to promote glioma cell disulfidptosis.ConclusionThis study delves into disulfidptosis-related lncRNAs in glioma, offering novel insights into glioma therapeutic strategies

Geometric Parameter Identification of Medical Robot Based on Improved Beetle Antennae Search Algorithm

To improve the accuracy of common intelligent algorithms when identifying the parameters of geometric error in medical robots, this paper proposes an improved beetle antennae search algorithm (RWSAVSBAS). We first establish a model for the kinematic error in medical robots, and then add the random wandering behavior of the wolf colony algorithm to the search process of the beetle antennae search algorithm to strengthen its capability for local search. Following this, we improve the global convergence ability of the beetle antennae search algorithm by using the simulated annealing algorithm. We compare the accuracy of end positioning of the proposed algorithm with the frog-jumping algorithm and the beetle antennae search algorithm with variable step length through simulations. The results show that the proposed algorithm has a higher accuracy of convergence, and can significantly improve the accuracy of end positioning of the medical robot

A New Method for Identifying Kinetic Parameters of Industrial Robots

Identifying the kinetic parameters of an industrial robot is the basis for designing a controller for it. To solve the problems of the poor accuracy and easy premature convergence of common bionic algorithms for identifying the dynamic parameters of such robots, this study proposed simulated annealing with similar exponential changes based on the beetle swarm optimization (SEDSABSO) algorithm. Expressions for the dynamics of the industrial robot were first obtained through the SymPyBotics toolkit in Python, and the required trajectories of excitation were then designed to identify its dynamic parameters. Following this, the search pattern of the global optimal solution for the beetle swarm optimization algorithm was improved in the context of solving for these parameters. The global convergence of the algorithm was improved by improving the iterative form of the number N of skinks in it by considering random perturbations and the simulated annealing algorithm, whereas its accuracy of convergence was improved through the class exponential change model. The improved beetle swarm optimization algorithm was used to identify the kinetic parameters of the Zhichang Kawasaki RS010N industrial robot. The results of experiments showed that the proposed algorithm was fast and highly accurate in identifying the kinetic parameters of the industrial robot

New Insight into Utilization of Fish By-Product Proteins and Their Skin Health Promoting Effects

In regions reliant on fisheries for livelihoods, a significant number of fish by-products are generated annually due to processing. These discarded parts contain valuable biological resources, such as proteins, fish oils, and trace elements, thus holding enormous potential for reutilization. In recent years, fish by-product proteins have been widely utilized in skincare products due to their rich collagen content, biosafety, and biocompatibility. This review summarizes the research into and applications of fish by-product proteins in skin health, including alleviating oxidative stress and skin inflammation, reducing DNA damage, mitigating melanin production, improving skin hydration, slowing skin matrix degradation, and promoting synthesis. Additionally, the possibility of improving skin health by improving the abundance of gut microbiota is also discussed. This review underscores the importance of fish by-product proteins in the fisheries, food processing, cosmetics, and biomedical industries

QTL Mapping for Root Traits and Their Effects on Nutrient Uptake and Yield Performance in Common Wheat (<i>Triticum aestivum</i> L.)

Wheat is one of the most important crops in the world. Mapping QTLs for root traits is essential for the selection of wheat roots desirable for the efficient acquisition of nutrients. Here, a QTL analysis for wheat root traits was performed using 142 recombinant inbred lines derived from two wheat varieties Xiaoyan 54 and Jing 411 in a soil column culture trial. The genetic map used in this study contained 470 SSR markers and covered 3438.4 cM of wheat genome. A total of 25 QTLs for root and shoot traits were detected, located at 16 marker intervals of 13 chromosomes. The percentage of phenotypic variation explained by individual QTLs varied from 6.1% to 22.0%. The QTLs regulating RDW and root distribution on chromosomes 1A, 3A, 4A, and 5B are important for root growth in both the top- and subsoils. For qRDW-1A, qRDW-3A, and qRDW-5B, the nearest markers to the QTLs were much closer than that of qRDW-4A, with the genetic distances ranging from 0.01 to 1.18 cM. Combining these three QTLs not only increased RDW and nutrient uptake, but also increased GW, SDW, and BDW under low nitrogen conditions in the field trial. Therefore, these QTLs are valuable for marker-assisted selection of wheat root traits

A New Parameter Identification Method for Industrial Robots with Friction

Commonly used intelligent algorithms that are used to identify the parameters of friction of industrial robots have poor accuracy or involve complex coding, which is not conducive to their use in engineering. This paper uses the random wandering simulated annealing-based variable-step beetle antennae search (RWSAVSBAS) algorithm to identify the parameters of friction of industrial robots. The moment of friction of the third joint of the robot is experimentally obtained and used to establish a Stribeck friction model. Following this, the RWSAVSBAS algorithm is used to identify the frictional parameters of the industrial robot. These parameters can be used to accurately predict the friction-induced torque of the robot

A New Parameter Identification Method for Industrial Robots with Friction

Commonly used intelligent algorithms that are used to identify the parameters of friction of industrial robots have poor accuracy or involve complex coding, which is not conducive to their use in engineering. This paper uses the random wandering simulated annealing-based variable-step beetle antennae search (RWSAVSBAS) algorithm to identify the parameters of friction of industrial robots. The moment of friction of the third joint of the robot is experimentally obtained and used to establish a Stribeck friction model. Following this, the RWSAVSBAS algorithm is used to identify the frictional parameters of the industrial robot. These parameters can be used to accurately predict the friction-induced torque of the robot

Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells

Aflatoxin B1 (AFB1) is widely prevalent in foods and animal feeds and is one of the most toxic and carcinogenic aflatoxin subtypes. Existing studies have proved that the intestine is targeted by AFB1, and adverse organic effects have been observed. This study aimed to investigate the relationship between AFB1-induced intestinal toxicity and N6-methyladenosine (m6A) RNA methylation, which involves the post-transcriptional regulation of mRNA expression. The transcriptome-wide m6A methylome and transcriptome profiles in human intestinal cells treated with AFB1 are presented. Methylated RNA immunoprecipitation sequencing and mRNA sequencing were carried out to determine the distinctions in m6A methylation and different genes expressed in AFB1-induced intestinal toxicity. The results showed that there were 2289 overlapping genes of the differentially expressed mRNAs and differentially m6A-methylation-modified mRNAs. After enrichment of the signaling pathways and biological processes, these genes participated in the terms of the cell cycle, endoplasmic reticulum, tight junction, and mitophagy. In conclusion, the study demonstrated that AFB1-induced HCT116 injury was related to the disruptions to the levels of m6A methylation modifications of target genes and the abnormal expression of m6A regulators