An adaptive frequency-hopping detection for slowly-varying fading dispersive channels.

Frequency hopping (FH) signals have been widely used to improve performance against frequency selective fading phenomenon of underwater channels. However, the channel is slowly varying in regard to changes in weather conditions, and thus the conventional FH detection transmitting signals with fixed frequency cannot guarantee good detection performance in the dynamic underwater environment. To overcome the performance degradation in slowly-varying fading dispersive channels, this paper proposes an adaptive frequency-hopping (AFH) target detection method. Compared with conventional FH detection methods, the AFH can adaptively select the optimal detection frequency based on premeasured background noise and channel frequency response measured from previous experiments. Numerical simulations and lake trials are conducted to verify the effectiveness of the AFH. The simulation results show that the AFH has better detection performance than the conventional FH. The lake trial results have also verified the validity and feasibility of AFH. Importantly, AFH also achieves a better output signal-to-noise ratio under actual noise interference.

Generation of a KCNQ1 (c.1032 + 2 T > C) mutant human embryonic stem cell line via CRISPR base editing.

The KCNQ1 gene encodes a voltage-gated potassium channel, which plays an important role in the repolarization of myocardial action potentials. Mutations in this gene often result in type 1 long QT syndrome (LQT1). Here, we generated a KCNQ1 (c.1032 + 2 T > C) mutant human embryonic stem cell line (WAe009-A-1D) based on the transient expression adenine base editing system that converts base A to G. The WAe009-A-1D cell maintains the morphology, pluripotency, and normal karyotype of the stem cells and is capable of differentiating into all three germ layers in vivo.

E-MFNN: an emotion-multimodal fusion neural network framework for emotion recognition.

Emotional recognition is a pivotal research domain in computer and cognitive science. Recent advancements have led to various emotion recognition methods, leveraging data from diverse sources like speech, facial expressions, electroencephalogram (EEG), electrocardiogram, and eye tracking (ET). This article introduces a novel emotion recognition framework, primarily targeting the analysis of users' psychological reactions and stimuli. It is important to note that the stimuli eliciting emotional responses are as critical as the responses themselves. Hence, our approach synergizes stimulus data with physical and physiological signals, pioneering a multimodal method for emotional cognition. Our proposed framework unites stimulus source data with physiological signals, aiming to enhance the accuracy and robustness of emotion recognition through data integration. We initiated an emotional cognition experiment to gather EEG and ET data alongside recording emotional responses. Building on this, we developed the Emotion-Multimodal Fusion Neural Network (E-MFNN), optimized for multimodal data fusion to process both stimulus and physiological data. We conducted extensive comparisons between our framework's outcomes and those from existing models, also assessing various algorithmic approaches within our framework. This comparison underscores our framework's efficacy in multimodal emotion recognition. The source code is publicly available at https://figshare.com/s/8833d837871c78542b29.

Enhancing Poly-γ-glutamic Acid Production in Bacillus tequilensis BL01 through a Multienzyme Assembly Strategy and Expression Features of Glutamate Synthesis from Corynebacterium glutamicum.

The enhancement of intracellular glutamate synthesis in glutamate-independent poly-γ-glutamic acid (γ-PGA)-producing strains is an essential strategy for improving γ-PGA production. Bacillus tequilensis BL01ΔpgdSΔggtΔsucAΔgudB:P43-ppc-pyk-gdhA for the efficient synthesis of γ-PGA was constructed through expression of glutamate synthesis features of Corynebacterium glutamicum, which increased the titer of γ-PGA by 2.18-fold (3.24 ± 0.22 g/L) compared to that of B. tequilensis BL01ΔpgdSΔggtΔsucAΔgudB (1.02 ± 0.11 g/L). To further improve the titer of γ-PGA and decrease the production of byproducts, three enzymes (Ppc, Pyk, and AceE) were assembled to a complex using SpyTag/Catcher pairs. The results showed that the γ-PGA titer of the assembled strain was 31.31% higher than that of the unassembled strain. To further reduce the production cost, 25.73 ± 0.69 g/L γ-PGA with a productivity of 0.48 g/L/h was obtained from cheap molasses. This work provides new metabolic engineering strategies to improve the production of γ-PGA in B. tequilensis BL01. Furthermore, the engineered strain has great potential for the industrial production of γ-PGA from molasses.

Universal origin of glassy relaxation as recognized by configuration pattern matching.

Relaxation processes are crucial for understanding the structural rearrangements of liquids and amorphous materials. However, the overarching principle that governs these processes across vastly different materials remains an open question. Substantial analysis has been carried out based on the motions of individual particles. Here, as an alternative, we propose viewing the global configuration as a single entity. We introduce a global order parameter, namely the inherent structure minimal displacement (IS Dmin), to quantify the variability of configurations by a pattern-matching technique. Through atomic simulations of seven model glass-forming liquids, we unify the influences of temperature, pressure and perturbation time on the relaxation dissipation, via a scaling law between the mechanical damping factor and IS Dmin. Fundamentally, this scaling reflects the curvature of the local potential energy landscape. Our findings uncover a universal origin of glassy relaxation and offer an alternative approach to studying disordered systems.

Insights into the modulation of bacterial NADase activity by phage proteins.

The Silent Information Regulator 2 (SIR2) protein is widely implicated in antiviral response by depleting the cellular metabolite NAD+. The defense-associated sirtuin 2 (DSR2) effector, a SIR2 domain-containing protein, protects bacteria from phage infection by depleting NAD+, while an anti-DSR2 protein (DSR anti-defense 1, DSAD1) is employed by some phages to evade this host defense. The NADase activity of DSR2 is unleashed by recognizing the phage tail tube protein (TTP). However, the activation and inhibition mechanisms of DSR2 are unclear. Here, we determine the cryo-EM structures of DSR2 in multiple states. DSR2 is arranged as a dimer of dimers, which is facilitated by the tetramerization of SIR2 domains. Moreover, the DSR2 assembly is essential for activating the NADase function. The activator TTP binding would trigger the opening of the catalytic pocket and the decoupling of the N-terminal SIR2 domain from the C-terminal domain (CTD) of DSR2. Importantly, we further show that the activation mechanism is conserved among other SIR2-dependent anti-phage systems. Interestingly, the inhibitor DSAD1 mimics TTP to trap DSR2, thus occupying the TTP-binding pocket and inhibiting the NADase function. Together, our results provide molecular insights into the regulatory mechanism of SIR2-dependent NAD+ depletion in antiviral immunity.

Cloning and expression analysis of Janus activated kinase family genes from spotted seabass (Lateolabrax maculatus).

Janus kinases (JAKs) are important components of the JAK-STAT signaling pathway and play vital roles in innate immunity, autoimmune diseases, and inflammation. However, information about JAKs remains largely unknown in the spotted seabass, a fish species of Perciformes with great commercial value in the aquaculture industry. The aims of this study are to obtain the complete cDNA sequences of JAKs (JAK1, JAK2A, JAK2B, JAK3 and TYK2) from spotted seabass and to investigate their roles upon stimulation with lipopolysaccharides (LPS) and Edwardsiella tarda, using RT-PCR, PCR and qRT-PCR methods. All five JAK genes from the spotted seabass, each encode more than 1100 amino acids residues. JAK1 and JAK3 consist of 24 exons and 23 introns, whereas JAK2A, JAK2B and TYK2 consist of 23 exons and 22 introns. Furthermore, these five spotted seabass JAKs share high sequence identities with those of other fish species in protein domain analysis, synteny analysis, and phylogenetic analysis. Moreover, these five JAK genes were ubiquitously expressed in all tissues examined from healthy fish, and inducible expressions of JAKs were observed in the intestine, gill, head kidney, and spleen following LPS treatment or E. tarda infection. These findings indicate that all these JAK genes are involved in the antibacterial immunity of the spotted seabass and provide a basis for further understanding the mechanism of JAKs antibacterial response in the spotted sea bass.

Clinical characteristics and prognosis of patients with hypertrophic cardiomyopathy and heart failure with preserved ejection fraction.

BACKGROUND: Whether heart failure with preserved ejection fraction (HFpEF) is associated with an increased risk of developing systolic dysfunction and a poor prognosis in hypertrophic cardiomyopathy (HCM) patients is unknown. OBJECTIVE: We aimed to assess risk factors for the development of end-stage (ES) heart failure (HF) (ejection fraction < 50%) and compare the prognosis of different HF phenotypes. METHODS: This retrospective study was conducted on patients with HCM in China between January 2009 and February 2023. Patients were stratified into three different groups: HCM-non-HF, HCM-HFpEF and HCM-heart failure with reduced ejection fraction (HCM-HFrEF). The primary outcome was a composite of major adverse cardiac events (MACEs), including all-cause deaths, HF hospitalization, sudden cardiac death and ventricular tachycardia. RESULTS: Of 3,620 HCM patients enrolled, 1,553 (42.9%) had non-HF, 1,666 (46.0%) had HFpEF, and 579 patients (11.1%) had HFrEF at baseline. During the median follow-up period of 4.0 years (IQR 1.4-9.4 years), patients with HCM-HFpEF exhibited a higher incidence of ES-HF than those with HCM-non-HF (12.4% vs. 2.7%, P < 0.001). HFpEF was an independent risk factor for ES-HF development (HR 3.84, 2.54-5.80, P < 0.001). MACEs occurred in 26.9% with a higher incidence in HCM-HFpEF than HCM-non-HF (36.6% vs 12.2%, P < 0.001). HFpEF was an independent predictor of MACEs (HR 2.13, 1.75-2.59, P < 0.001). CONCLUSIONS: HFpEF is common in HCM. Compared to non-HF, it increases the risk of LVEF decline and poor prognosis. It may aid in risk stratification and need close echocardiography follow-up.

OTUB1 Targets CHK1 for Deubiquitination and Stabilization to Facilitate Lung Cancer Progression and Radioresistance.

PURPOSE: Radioresistance of lung cancer poses a significant challenge when it comes to the treatment of advanced, recurrent, and metastatic cases. Ovarian tumor domain ubiquitin aldehyde binding 1 (OTUB1) is a key member of the deubiquitinase OTU superfamily. This protein is involved in various cellular functions, including cell proliferation, iron death, lipid metabolism, and cytokine secretion as well as immune response processes. However, its specific role and molecular mechanism in lung cancer radioresistance remain to be clarified. METHODS AND MATERIALS: The expression levels of OTUB1 in paired lung cancer tissues were determined by immunohistochemistry. In vitro and in vivo experiments were conducted to investigate the impact of OTUB1 on the growth and proliferation of lung cancer. Coimmunoprecipitation and Western blotting techniques were performed to examine the interaction between OTUB1 and CHK1. The DNA damage response was measured by comet tailing and immunofluorescence staining. KEGG pathways and Gene Ontology terms were analyzed based on RNA sequencing. RESULTS: Our findings reveal a high frequency of OTUB1 overexpression, which is associated with an unfavorable prognosis in patients with lung cancer. Through comprehensive investigations, we demonstrate that OTUB1 depletion impairs the process of DNA damage repair and overcomes radioresistance. In terms of the underlying mechanism, our study uncovers that OTUB1 deubiquitinates and stabilizes CHK1, which enhances CHK1 stability, thereby regulating DNA damage and repair. Additionally, we identify CHK1 as the primary downstream effector responsible for mediating the functional effects exerted by OTUB1 specifically in lung cancer. Importantly, OTUB1 has the potential to be a valuable marker for improving the efficacy of radiation therapy for lung adenocarcinoma. CONCLUSIONS: These findings unveil a novel role for OTUB1 in enhancing radioresistance by deubiquitination and stabilization of the expression of CHK1 in lung cancer and indicate that targeting OTUB1 holds great potential as an effective therapeutic approach for enhancing the efficacy of radiation therapy in lung cancer.

Effects of cerium oxide nanoparticles on adenine-induced chronic kidney disease model rats.

AIM: Cerium oxide, particularly in nanoparticle form (nanoceria), has been investigated for biomedical applications as a promising new agent for treating several pathologies. The aim of the present study was to characterize the pharmacologic effects of nanoceria in an animal model of chronic kidney disease. METHODS: We created the chronic kidney disease animal model by feeding rats a 0.25% adenine diet. Male Wistar rats were divided into five groups: normal diet, 0.25% adenine diet, or adenine diet containing three different doses or durations of nanoceria treatment. Blood was collected weekly from the tail veins of each rat and analyzed for renal function markers. After 5 weeks, various biochemical markers in serum, plasma, and urine were also analyzed. RESULTS: In the adenine-treated group, body weight was significantly decreased, and the kidneys lost much of their healthy reddish color and became lumpy and white in appearance. In addition, levels of serum creatinine, blood urea nitrogen, and plasma uremic toxins were significantly increased in adenine-treated rats compared with controls. Renal functional and structural damage in adenine diet model rats tended to be ameliorated by nanoceria ingestion. The high-dose cerium-treated group maintained reddish areas in the kidneys, and the increases in biomarker levels of creatinine, blood urea nitrogen, and inorganic phosphorus were markedly reduced, regardless of treatment duration. CONCLUSIONS: Ingestion of nanoceria may be effective for improving or preventing renal damage caused by adenine. Geriatr Gerontol Int 2024; 24: 88-95.

Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting.

Most conventional crowd counting methods utilize a fully-supervised learning framework to establish a mapping between scene images and crowd density maps. They usually rely on a large quantity of costly and time-intensive pixel-level annotations for training supervision. One way to mitigate the intensive labeling effort and improve counting accuracy is to leverage large amounts of unlabeled images. This is attributed to the inherent self-structural information and rank consistency within a single image, offering additional qualitative relation supervision during training. Contrary to earlier methods that utilized the rank relations at the original image level, we explore such rank-consistency relation within the latent feature spaces. This approach enables the incorporation of numerous pyramid partial orders, strengthening the model representation capability. A notable advantage is that it can also increase the utilization ratio of unlabeled samples. Specifically, we propose a Deep Rank-consistEnt pyrAmid Model (), which makes full use of rank consistency across coarse-to-fine pyramid features in latent spaces for enhanced crowd counting with massive unlabeled images. In addition, we have collected a new unlabeled crowd counting dataset, FUDAN-UCC, comprising 4000 images for training purposes. Extensive experiments on four benchmark datasets, namely UCF-QNRF, ShanghaiTech PartA and PartB, and UCF-CC-50, show the effectiveness of our method compared with previous semi-supervised methods. The codes are available at https://github.com/bridgeqiqi/DREAM.

[Progress on mRNA vaccine for the prevention of major infectious diseases in humans and animals].

A large number of studies have demonstrated that mRNA vaccine has been characterized as a technique with good safety, strong immunogenicity and high developmental potential, which makes it have broad prospects in immunotherapy. In recent years, the stability and in vivo delivery efficiency of mRNA vaccines have been largely addressed by the progresses in mRNA engineering and delivery innovation. And some mRNA vaccines are now clinical approved or in preclinical trials. Here, we summarize current knowledge on the research advances, technology, and application in major infectious diseases in humans and animals of mRNA vaccines, with the aim to provide a reference for improving the development of novel mRNA vaccines.

Preparation of Co dual atomic site catalysts loaded on defect-engineered MOFs material with superb chemiluminescent enhancement effect for sensitive detection of bacteria.

BACKGROUND: Dual atomic site catalysts (DASCs) have aroused extensive interest in analytical chemistry on account of the superb catalytic activity caused by the highly-exposed active centers and synergistic effect of adjacent active centers. The reported protocols for preparing DASCs usually involve harsh conditions such as acid/base etching and high-temperature calcination, leading to unfavorable water dispersity and restricted application. It is crucial to develop DASCs with satisfactory water dispersity, improved stability, and mild preparation procedures to facilitate their application as signal probes in analytical chemistry. RESULTS: Formic acid was adopted as a modulator for preparing MOF-808 with abundant defective sites, which was used as the carrier for implanting Co atoms. Co DASCs with a special coordination structure of Co2-O10 and a high loading efficiency of 11.1 wt% were prepared with a mild solvothermal protocol. The resultant Co DASCs can significantly accelerate decay of H2O2 for forming numerous reactive oxygen radicals and boost chemiluminescent (CL) signal. Co DASCs at 1.0 µg mL-1 can enhance the CL signal of luminol-H2O2 system by about 5800 times. Thanks to their satisfactory water dispersity and excellent CL enhancement performance, they were used as ultra-sensitive CL signal probes for monitoring methicillin-resistant Staphylococcus aureus. The method shows a detection range of 102-107 CFU mL-1 and a detection limit of 47 CFU mL-1. Antibiotic susceptibility test was performed with the established CL method to prove its practicality. SIGNIFICANCE: The water dispersible Co DASCs prepared with facile and mild solvothermal protocol exhibit prominent peroxidase-like activity and can promote the production of reactive oxygen radicals for boosting CL signal. Therefore, this study paves an avenue for implanting DASCs in defect-engineered carrier to prepare signal probes suitable for development of ultra-sensitive CL analytical methods.

Statistical and clustering analysis of attributes of Bitcoin backbone nodes.

Bitcoin is a decentralized digital cryptocurrency. Its network is a Peer-to-peer(P2P) network consisting of distributed nodes. Some of these nodes are always online and in this article are called Bitcoin backbone nodes. They have a significant impact on the stability and security of the Bitcoin network, so it is meaningful to analyze and discuss them. In this paper, we first continuously collect information about Bitcoin nodes from July 2021 through June 2022 (which is the longest duration of data collection to date). In total, we collect information on 127,613 Bitcoin nodes. At the same time, we conclude that the fluctuation of Bitcoin nodes is directly related to the fluctuation of onion network nodes. Further, we filtered 2694 Bitcoin backbone nodes based on our algorithm. By analyzing the backbone nodes' attributes such as geographic distribution, client version, operator, node function, and abnormal port number, it is demonstrated that these nodes are centralized and play an important role in the Bitcoin network. Based on this, three unsupervised machine learning algorithms are selected to cluster multiple attributes of backbone nodes in a more scientific way. In this paper, the whole process from data collection to cluster analysis is completed and the best results are obtained by comparison. The experiments proved the existence of centralization of Bitcoin backbone nodes and obtained the number of nodes within each cluster. Finally, cluster nodes are de-anonymized based on the optimal results. Through our experiments, we obtain organizational information about the deployers of 103 nodes, linking the Bitcoin backbone nodes to the real world, thus accurately demonstrating the existence of Bitcoin centrality.

Natural compounds efficacy in complicated diabetes: A new twist impacting ferroptosis.

Ferroptosis, as a way of cell death, participates in the body's normal physiological and pathological regulation. Recent studies have shown that ferroptosis may damage glucose-stimulated islets ß Insulin secretion and programmed cell death of T2DM target organs are involved in the pathogenesis of T2DM and its complications. Targeting suppression of ferroptosis with specific inhibitors may provide new therapeutic opportunities for previously untreated T2DM and its target organs. Current studies suggest that natural bioactive compounds, which are abundantly available in drugs, foods, and medicinal plants for the treatment of T2DM and its target organs, have recently received significant attention for their various biological activities and minimal toxicity, and that many natural compounds appear to have a significant role in the regulation of ferroptosis in T2DM and its target organs. Therefore, this review summarized the potential treatment strategies of natural compounds as ferroptosis inhibitors to treat T2DM and its complications, providing potential lead compounds and natural phytochemical molecular nuclei for future drug research and development to intervene in ferroptosis in T2DM.

Redox-Regulated Magnetic Conversions between Ferro- and Antiferromagnetism in Organic Nitroxide Diradicals.

Redox-induced magnetic transformation in organic diradicals is an appealing phenomenon. In this study, we theoretically designed twelve couples of diradicals in which two nitroxide (NO) radical groups are connected to the redox-active couplers including p-benzoquinonyl, 1,4-naphthoquinyl, 9,10-anthraquinonyl, naphthacene-5,12-dione, pentacene-6,13-dione, hexacene-6,15-dione, pyrazinyl, quinoxalinyl, phenazinyl, 5,12-diazanaphthacene, 6,13-diazapentacene, and 6,15-diazahexacene. As evidenced at both the B3LYP and M06-2X levels of theory, the calculations reveal that the magnetic reversal can take place from ferromagnetism to antiferromagnetism, or vice versa, by means of redox method in these designed organic magnetic molecules. It was observed that p-benzoquinonyl, 1,4-naphthoquinyl, 9,10-anthraquinonyl, naphthacene-5,12-dione, pentacene-6,13-dione, and hexacene-6,15-dione-bridged NO diradicals produce antiferromagnetism while their dihydrogenated counterparts exhibit ferromagnetism. Similarly, pyrazinyl, quinoxalinyl, phenazinyl, 5,12-diazanaphthacene, 6,13-diazapentacene, and 6,15-diazahexacene-bridged NO diradicals present ferromagnetism while their dihydrogenated counterparts show antiferromagnetism. The differences in the magnetic behaviors and magnetic magnitudes of each of the twelve couples of diradicals could be attributed to their distinctly different spin-interacting pathways. It was found that the nature of the coupler and the length of the coupling path are important factors in controlling the magnitude of the magnetic exchange coupling constant J. Specifically, smaller HOMO-LUMO (HOMO: highest occupied molecular orbital, LUMO: lowest unoccupied molecular orbital) gaps of the couplers and shorter coupler lengths, as well as shorter linking bond lengths, can attain stronger magnetic interactions. In addition, a diradical with an extensively π-conjugated structure is beneficial to spin transport and can effectively promote magnetic coupling, yielding a large |J| accordingly. That is, a larger spin polarization can give rise to a stronger magnetic interaction. The sign of J for these studied diradicals can be predicted from the spin alternation rule, the shape of the singly occupied molecular orbitals (SOMOs), and the SOMO-SOMO energy gaps of the triplet state. This study paves the way for the rational design of magnetic molecular switches.

Inhibitory mechanism of CRISPR-Cas9 by AcrIIC4.

CRISPR-Cas systems act as the adaptive immune systems of bacteria and archaea, targeting and destroying invading foreign mobile genetic elements (MGEs) such as phages. MGEs have also evolved anti-CRISPR (Acr) proteins to inactivate the CRISPR-Cas systems. Recently, AcrIIC4, identified from Haemophilus parainfluenzae phage, has been reported to inhibit the endonuclease activity of Cas9 from Neisseria meningitidis (NmeCas9), but the inhibition mechanism is not clear. Here, we biochemically and structurally investigated the anti-CRISPR activity of AcrIIC4. AcrIIC4 folds into a helix bundle composed of three helices, which associates with the REC lobe of NmeCas9 and sgRNA. The REC2 domain of NmeCas9 is locked by AcrIIC4, perturbing the conformational dynamics required for the target DNA binding and cleavage. Furthermore, mutation of the key residues in the AcrIIC4-NmeCas9 and AcrIIC4-sgRNA interfaces largely abolishes the inhibitory effects of AcrIIC4. Our study offers new insights into the mechanism of AcrIIC4-mediated suppression of NmeCas9 and provides guidelines for the design of regulatory tools for Cas9-based gene editing applications.

Comparison of Particulate Air Pollution From Different Emission Sources and Incident Dementia in the US.

Importance: Emerging evidence indicates that exposure to fine particulate matter (PM2.5) air pollution may increase dementia risk in older adults. Although this evidence suggests opportunities for intervention, little is known about the relative importance of PM2.5 from different emission sources. Objective: To examine associations of long-term exposure of total and source-specific PM2.5 with incident dementia in older adults. Design, Setting, and Participants: The Environmental Predictors of Cognitive Health and Aging study used biennial survey data from January 1, 1998, to December 31, 2016, for participants in the Health and Retirement Study, which is a nationally representative, population-based cohort study in the US. The present cohort study included all participants older than 50 years who were without dementia at baseline and had available exposure, outcome, and demographic data between 1998 and 2016 (N = 27 857). Analyses were performed from January 31 to May 1, 2022. Exposures: The 10-year mean total PM2.5 and PM2.5 from 9 emission sources at participant residences for each month during follow-up using spatiotemporal and chemical transport models. Main Outcomes and Measures: The main outcome was incident dementia as classified by a validated algorithm incorporating respondent-based cognitive testing and proxy respondent reports. Adjusted hazard ratios (HRs) were estimated for incident dementia per IQR of residential PM2.5 concentrations using time-varying, weighted Cox proportional hazards regression models with adjustment for the individual- and area-level risk factors. Results: Among 27 857 participants (mean [SD] age, 61 [10] years; 15 747 [56.5%] female), 4105 (15%) developed dementia during a mean (SD) follow-up of 10.2 [5.6] years. Higher concentrations of total PM2.5 were associated with greater rates of incident dementia (HR, 1.08 per IQR; 95% CI, 1.01-1.17). In single pollutant models, PM2.5 from all sources, except dust, were associated with increased rates of dementia, with the strongest associations for agriculture, traffic, coal combustion, and wildfires. After control for PM2.5 from all other sources and copollutants, only PM2.5 from agriculture (HR, 1.13; 95% CI, 1.01-1.27) and wildfires (HR, 1.05; 95% CI, 1.02-1.08) were robustly associated with greater rates of dementia. Conclusion and Relevance: In this cohort study, higher residential PM2.5 levels, especially from agriculture and wildfires, were associated with higher rates of incident dementia, providing further evidence supporting PM2.5 reduction as a population-based approach to promote healthy cognitive aging. These findings also indicate that intervening on key emission sources might have value, although more research is needed to confirm these findings.

The Method and Study of Detecting Phenanthrene in Seawater Based on a Carbon Nanotube-Chitosan Oligosaccharide Modified Electrode Immunosensor.

Phenanthrene (PHE), as a structurally simple, tricyclic, polycyclic aromatic hydrocarbon (PAHs), is widely present in marine environments and organisms, with serious ecological and health impacts. It is crucial to study fast and simple high-sensitivity detection methods for phenanthrene in seawater for the environment and the human body. In this paper, a immunosensor was prepared by using a multi-wall carbon nanotube (MWCNTs)-chitosan oligosaccharide (COS) nanocomposite membrane loaded with phenanthrene antibody. The principle was based on the antibody-antigen reaction in the immune reaction, using the strong electron transfer ability of multi-walled carbon nanotubes, coupled with chitosan oligosaccharides with an excellent film formation and biocompatibility, to amplify the detection signal. The content of the phenanthrene in seawater was studied via differential pulse voltammetry (DPV) using a potassium ferricyanide system as a redox probe. The antibody concentration, pH value, and probe concentration were optimized. Under the optimal experimental conditions, the response peak current of the phenanthrene was inversely proportional to the concentration of phenanthrene, in the range from 0.5 ng·mL-1 to 80 ng·mL-1, and the detection limit was 0.30 ng·mL-1. The immune sensor was successfully applied to the detection of phenanthrene in marine water, with a recovery rate of 96.1~101.5%, and provided a stable, sensitive, and accurate method for the real-time monitoring of marine environments.

The analysis and solution for intercity travel behaviors during holidays in the post-epidemic era based on big data.

The COVID-19 had a huge impact on the transportation industry. In the post-epidemic stage, intercity transportation will face great challenges as places are unsealed, tourism and other service industries begin to recover, and residents' travel demand gradually increases. An in-depth study of residents' intercity travel behavior during holidays in the post-epidemic era will help restore public trust in public transportation and improve the quality of public transportation services. Based on traditional research on ways of travelling, the study adopted the Complex Network Analysis Theory. The city clusters of Shandong Peninsula were taken as the research region. The research studied the impact of the differences in regional attributes of the cities in Shandong Peninsula on residents' intercity travel in the post-epidemic times. A dynamic evolution model of how residents choose to travel was built to simulate the changes to their ways of traveling in the post-epidemic era under two conditions, which are: traveling under the government's supervision of intercity travel and traveling under the government's optimization of intercity travel conditions. The conclusions drawn from the analyses of Complex Network Theory and Evolutionary Game Theory are as follows. First, in the holiday intercity travel in the post-epidemic times, the neighboring cities of Shandong Peninsula are closely connected, thus traveling between neighboring cities dominates intercity travel. Second, the travel network concentration of residents on long-term holidays is lower than that on short-term holidays, and the migration intensity of residents is higher than that on short-term holidays, while the willingness of residents' migration on short-term holidays is higher than that on long-term holidays. The willingness to migrate on holidays is generally lower than that before the epidemic. Third, in a normal intercity travel network, the travel between two cities with medium and long distances is mainly by public transport. However, the dominance of public transport will be affected under the impact of the epidemic. In short-distance travel between two cities, private transport is in an advantageous position, and under the impact of the epidemic, this advantage will become more significant. The government can improve the position of public transport in short-distance travel by making optimizations.