In line with the "healthy aging" principle, we aim to assess the exposure map and health risks of environmental chemicals in the elderly. Blood samples from 918 elderly individuals in Wuhan, China, were analyzed using the combined gas/liquid-mass spectrometry technology to detect levels of 118 environmental chemicals. Cluster analysis identified exposure profiles, while risk indexes and bioanalytical equivalence percentages were calculated using EPA's ToxCast database. The detection rates for 87 compounds exceeded 70%. DEHP, DiBP, naphthalene, phenanthrene, DnBP, pyrene, anthracene, permethrin, fluoranthene, and PFOS showed the highest concentrations. Fat-soluble pollutants varied across lifestyles. In cluster 2, which was characterized by higher concentrations of fat-soluble substances, the proportion of smokers or drinkers was higher than that of nonsmokers or nondrinkers. Pesticides emerged as the most active environmental chemicals in peroxisome proliferator-activated receptor gamma antagonist, thyroid hormone receptor (TR) antagonist, TR agonist, and androgen receptor (AR) agonist activity assays. Additionally, PAEs and polycyclic aromatic hydrocarbons played significant roles as active contaminants for the corresponding targets of AR antagonists and estrogen receptor alpha. We proposed a list of priority pollutants linked to endocrine-disrupting toxic effects in the elderly, which may provide the groundwork for further research into environmental etiology.
The application of disposable tableware has increased substantially in recent times due to the rapidly growing food delivery business in China. Synthetic phenolic antioxidants (SPAs) are widely used in food contact materials (FCMs) to delay the process of oxidation; however, their compositions, concentrations, and potential health hazards remain unclear. Therefore, FCMs comprised of five materials obtained from 19 categories (n = 118) in China were analyzed for SPAs concentrations. FCMs have been found to contain a variety of SPAs, with ∑SPAs concentrations ranging from 44.18 to 69,485.12 µg/kg (median: 2615.63 µg/kg). The predominant congeners identified in the sample include 2,4-di-tert-butylphenol (2,4-DTBP), 2,6-di-tert-butylphenol (2,6-DTBP), and 2,6-di-tert-butyl-p-benzoquinone (BHT-Q) with a median concentration of 885.75, 555.45 and of 217.44 µg/kg, respectively. Milky tea paper cups, instant noodle buckets, milky teacups, and disposable cups showed high levels of SPAs. 2,2'-methylenebis(4-methyl-6-tert-butylphenol) (AO 2246) was predominantly detected in polyethylene and polyethylene terephthalate-based products. The migration test identified disposable plastic cups and bowls as the predominant FCMs and 2,4-DTBP as the dominant SPA. The exposure risk of SPAs decreased with age. In children, the estimated daily intake of ∑SPAs from FCMs was determined to be 17.56 ng/kg body weight/day, which was 8.3 times higher than that of phthalic acid esters. The current findings indicate the potential ingestion risk of SPAs during the daily life application of multiple FCM categories.
Electrocatalytic nitrogen reduction reaction (NRR) is a green and highly efficient way to replace the industrial Haber-Bosch process. Herein, clusters consisting of three transition metal atoms loaded on C2N as NRR electrocatalysts are investigated using density functional theory (DFT). Meanwhile, Ca was introduced as a promoter and the role of Ca in NRR was investigated. It was found that Ca anchored to the catalyst can act as an electron donor and effectively promote the activation of N2 on M3. In both M3@C2N and M3Ca@C2N (M = Fe, Co, Ni), the limiting potential (UL) is less negative than that of the Ru(0001) surface and has the ability to suppress the competitive hydrogen evolution reaction (HER). Among them, Fe3@C2N is suggested to be the most promising candidate for NRR with high thermal stability, strong N2 adsorption ability, low limiting potential, and good NRR selectivity. The concepts of trimetallic sites and alkaline earth metal promoters in this work provide theoretical guidance for the rational design of atomically active sites in electrocatalytic NRR.
Although di(2-ethylhexyl) terephthalate (DOTP) is being widely adopted as a non-phthalate plasticizer, existing research primarily focuses on human and rat toxicity. This leaves a significant gap in our understanding of their impact on microbial communities. This study assessed the biodegradation and toxicity of DOTP on microbes, focusing on its impact on biofilms and microbial metabolism using Rhodococcus ruber as a representative bacterial strain. DOTP is commonly found in mass fractions between 0.6 and 20% v/v in various soft plastic products. This study used polyvinyl chloride films (PVC) with varying DOTP concentrations (range 1-10% v/v) as a surface for analysis of biofilm growth. Cell viability and bacterial stress responses were tested using LIVE/DEAD™ BacLight™ Bacterial Viability Kit and by the detection of reactive oxygen species using CellROX™ Green Reagent, respectively. An increase in the volume of dead cells (in the plastisphere biofilm) was observed with increasing DOTP concentrations in experiments using PVC films, indicating the potential negative impact of DOTP on microbial communities. Even at a relatively low concentration of DOTP (1%), signs of stress in the microbes were noticed, while concentrations above 5% compromised their ability to survive. This research provides a new understanding of the environmental impacts of alternative plasticizers, prompting the need for additional research into their wider effects on both the environment and human health.
Gesture recognition has emerged as a significant research domain in computer vision and human-computer interaction. One of the key challenges in gesture recognition is how to select the most useful channels that can effectively represent gesture movements. In this study, we have developed a channel selection algorithm that determines the number and placement of sensors that are critical to gesture classification. To validate this algorithm, we constructed a Force Myography (FMG)-based signal acquisition system. The algorithm considers each sensor as a distinct channel, with the most effective channel combinations and recognition accuracy determined through assessing the correlation between each channel and the target gesture, as well as the redundant correlation between different channels. The database was created by collecting experimental data from 10 healthy individuals who wore 16 sensors to perform 13 unique hand gestures. The results indicate that the average number of channels across the 10 participants was 3, corresponding to an 75% decrease in the initial channel count, with an average recognition accuracy of 94.46%. This outperforms four widely adopted feature selection algorithms, including Relief-F, mRMR, CFS, and ILFS. Moreover, we have established a universal model for the position of gesture measurement points and verified it with an additional five participants, resulting in an average recognition accuracy of 96.3%. This study provides a sound basis for identifying the optimal and minimum number and location of channels on the forearm and designing specialized arm rings with unique shapes.
Algorithms , Gestures , Pattern Recognition, Automated , Humans , Male , Female , Adult , Pattern Recognition, Automated/methods , Young Adult , Myography/methods , Hand/physiology , Healthy Volunteers , Reproducibility of Results
Experimental research and numerical simulations of the structural response to shock waves with pulse durations of hundreds of milliseconds, or even seconds, are extremely challenging. This paper takes typical single-layer and sandwich cylindrical shells as the research objects. The response rules of cylindrical shells under long-duration blast loadings were studied. The results show that when the pulse duration is greater than or equal to 4~5 times the first-order period of the structure, the maximum response of the structure tends to be consistent, that is, the maximum response of the cylindrical shells with different vibration shapes shows a saturation effect as the pulse duration increases. This study established the relationship between the saturation loading time and the inherent characteristics of the structure. It was found that the saturation effect was applicable under the following conditions, including different load waveforms, elastic-plastic deformation of the structure, and the loading object being a sandwich shell. This will help transform the long-duration explosion wave problem into a finite pulse-duration shock wave problem that can be realized by both experiments and numerical simulations.
All-silicon terahertz absorbers have attracted considerable interest. We present a design and numerical study of an all-silicon polarization-insensitive terahertz metamaterial absorber. The meta-atoms of the metamaterial absorber are square silicon rings which can be viewed as gratings. By properly optimizing the structure of the meta-atom, we achieve a broadband absorptivity that is above 90% ranging from 0.77 THz to 2.53 THz, with a relative bandwidth of 106.7%. Impedance matching reduces the reflection of the terahertz waves and the (0, ±1)-order diffraction induce the strong absorption. The absorption of this absorber is insensitive to the polarization of the terahertz wave and has a large incident angle tolerance of up to 60 degrees. The all-silicon metamaterial absorber proposed here provides an effective way to obtain broadband absorption in the terahertz regime. Metamaterial absorbers have outstanding applications in terahertz communication and imaging.
Tropilaelaps mercedesae, an ectoparasitic mite of honeybees, is currently a severe health risk to Apis mellifera colonies in Asia and a potential threat to the global apiculture industry. However, our understanding of the physiological and developmental regulation of this pest remains significantly insufficient. Using ultra-high resolution mass spectrometry, we provide the first comprehensive proteomic profile of T. mercedesae spanning its entire post-embryonic ontogeny, including protonymphs, deutonymphs, mature adults, and reproductive mites. Consequently, a total of 4,422 T. mercedesae proteins were identified, of which 2,189 proteins were significantly differentially expressed (FDR < 0.05) throughout development and maturation. Our proteomic data provide an important resource for understanding the biology of T. mercedesae, and will contribute to further research and effective control of this devastating honeybee pest.
Bees , Mites , Proteomics , Animals , Bees/parasitology , Mass Spectrometry , Mites/growth & development
BACKGROUND: Biology-guided radiotherapy (BgRT) is a novel radiotherapy delivery technique that utilizes the tumor itself to guide dynamic delivery of treatment dose to the tumor. The RefleXion X1 system is the first radiotherapy system developed to deliver SCINTIX® BgRT. The X1 is characterized by its split arc design, employing two 90-degree positron emission tomography (PET) arcs to guide therapeutic radiation beams in real time, currently cleared by FDA to treat bone and lung tumors. PURPOSE: This study aims to comprehensively evaluate the capabilities of the SCINTIX radiotherapy delivery system by evaluating its sensitivity to changes in PET contrast, its adaptability in the context of patient motion, and its performance across a spectrum of prescription doses. METHODS: A series of experimental scenarios, both static and dynamic, were designed to assess the SCINTIX BgRT system's performance, including an end-to-end test. These experiments involved a range of factors, including changes in PET contrast, motion, and prescription doses. Measurements were performed using a custom-made ArcCHECK insert which included a 2.2 cm spherical target and a c-shape structure that can be filled with a PET tracer with varying concentrations. Sinusoidal and cosine4 motion patterns, simulating patient breathing, was used to test the SCINTIX system's ability to deliver BgRT during motion-induced challenges. Each experiment was evaluated against specific metrics, including Activity Concentration (AC), Normalized Target Signal (NTS), and Biology Tracking Zone (BTZ) bounded dose-volume histogram (bDVH) pass rates. The accuracy of the delivered BgRT doses on ArcCHECK and EBT-XD film were evaluated using gamma 3%/2 mm and 3%/3 mm analysis. RESULTS: In static scenarios, the X1 system consistently demonstrated precision and robustness in SCINTIX dose delivery. The end-to-end delivery to the spherical target yielded good results, with AC and NTS values surpassing the critical thresholds of 5 kBq/mL and 2, respectively. Furthermore, bDVH analysis consistently confirmed 100% pass rates. These results were reaffirmed in scenarios involving changes in PET contrast, emphasizing the system's ability to adapt to varying PET avidities. Gamma analysis with 3%/2 mm (10% dose threshold) criteria consistently achieved pass rates > 91.5% for the static tests. In dynamic SCINTIX delivery scenarios, the X1 system exhibited adaptability under conditions of motion. Sinusoidal and cosine4 motion patterns resulted in 3%/3 mm gamma pass rates > 87%. Moreover, the comparison with gated stereotactic body radiotherapy (SBRT) delivery on a conventional c-arm Linac resulted in 93.9% gamma pass rates and used as comparison to evaluate the interplay effect. The 1 cm step shift tests showed low overall gamma pass rates of 60.3% in ArcCHECK measurements, while the doses in the PTV agreed with the plan with 99.9% for 3%/3 mm measured with film. CONCLUSIONS: The comprehensive evaluation of the X1 radiotherapy delivery system for SCINTIX BgRT demonstrated good agreement for the static tests. The system consistently achieved critical metrics and delivered the BgRT doses per plan. The motion tests demonstrated its ability to co-localize the dose where the PET signal is and deliver acceptable BgRT dose distributions.
OBJECTIVE: Recombinant monoclonal therapeutic antibodies like lecanemab, which target amyloid beta in Alzheimer's disease, offer a promising approach for modifying the disease progression. Due to its relatively short half-life, Lecanemab, administered as a bi-monthly infusion (typically 10mg/kg) has a relatively brief half-life. Interaction with abundant plasma proteins binder in the bloodstream can affect pharmacokinetics of drugs, including their half-life. In this study we investigated potential plasma protein binding interaction to lecanemab using lecanemab biosimilar. METHODS: Lecanemab biosimilar used in this study was based on publicly available sequences. ELISA and Western blotting were used to assess lecanemab biosimilar immunoreactivity in the fractions human plasma sample obtained through size exclusion chromatography. The binding of lecanemab biosimilar to candidate binders was confirmed by Western blotting, ELISA, and surface plasmon resonance analysis. RESULTS: Using a combination of equilibrium dialysis, ELISA, and Western blotting in human plasma, we first describe the presence of likely plasma protein binding partner to lecanemab biosimilar, and then identify fibrinogen as one of them. Utilizing surface plasmon resonance, we confirmed that lecanemab biosimilar does bind to fibrinogen, although with lower affinity than to monomeric amyloid beta. CONCLUSION: In the context of lecanemab therapy, these results imply that fibrinogen levels could impact the levels of free antibodies in the bloodstream and that fibrinogen might serve as a reservoir for lecanemab. More broadly, these results indicate that plasma protein binding may be an important consideration when clinically utilizing therapeutic antibodies in neurodegenerative disease.
Fenazaquin, a potent insecticide widely used to control phytophagous mites, has recently emerged as a potential solution for managing Varroa destructor mites in honeybees. However, the comprehensive impact of fenazaquin on honeybee health remains insufficiently understood. Our current study investigated the acute and chronic toxicity of fenazaquin to honeybee larvae, along with its influence on larval hemolymph metabolism and gut microbiota. Results showed that the acute median lethal dose (LD50) of fenazaquin for honeybee larvae was 1.786 µg/larva, and the chronic LD50 was 1.213 µg/larva. Although chronic exposure to low doses of fenazaquin exhibited no significant effect on larval development, increasing doses of fenazaquin resulted in significant increases in larval mortality, developmental time, and deformity rates. At the metabolic level, high doses of fenazaquin inhibited nucleotide, purine, and lipid metabolism pathways in the larval hemolymph, leading to energy metabolism disorders and physiological dysfunction. Furthermore, high doses of fenazaquin reduced gut microbial diversity and abundance, characterized by decreased relative abundance of functional gut bacterium Lactobacillus kunkeei and increased pathogenic bacterium Melissococcus plutonius. The disrupted gut microbiota, combined with the observed gut tissue damage, could potentially impair food digestion and nutrient absorption in the larvae. Our results provide valuable insights into the complex and diverse effects of fenazaquin on honeybee larvae, establishing an important theoretical basis for applying fenazaquin in beekeeping.
Acaricides , Gastrointestinal Microbiome , Hemolymph , Larva , Metabolome , Animals , Gastrointestinal Microbiome/drug effects , Bees/drug effects , Larva/drug effects , Larva/growth & development , Hemolymph/metabolism , Hemolymph/drug effects , Metabolome/drug effects , Acaricides/toxicity
Despite their diverse functions, proteins are inherently constructed from a limited set of building blocks. These compositional constraints pose significant challenges to protein research and its practical applications. Strategically manipulating the cellular protein synthesis system to incorporate novel building blocks has emerged as a critical approach for overcoming these constraints in protein research and application. In the past two decades, the field of genetic code expansion (GCE) has achieved significant advancements, enabling the integration of numerous novel functionalities into proteins across a variety of organisms. This technological evolution has paved the way for the extensive application of genetic code expansion across multiple domains, including protein imaging, the introduction of probes for protein research, analysis of protein-protein interactions, spatiotemporal control of protein function, exploration of proteome changes induced by external stimuli, and the synthesis of proteins endowed with novel functions. In this comprehensive Review, we aim to provide an overview of cellular and biophysical applications that have employed GCE technology over the past two decades.
Exposure to fine particulate matter (PM2.5) is a significant concern for respiratory health. However, the sources, trigger points, and effect size of specific associations between PM2.5 components, particularly polycyclic aromatic hydrocarbons (PAHs) and the airway inflammatory marker fractional exhaled nitric oxide (FeNO) have not been fully explored. In this study, 69 healthy college students were enrolled and followed up 16 times from 2014 to 2018. Individual FeNO was measured and ambient air PM2.5 samples were collected for 7 consecutive days before each follow-up. PAHs were quantified using Gas Chromatography-Mass Spectrometry. Linear mixed-effect regression models were employed to evaluate the associations between PM2.5-bound PAHs and FeNO. Additionally, PMF (Positive Matrix Factorization) was utilized to identify sources of PM2.5-bound PAHs and assess their impact on FeNO. Throughout the study, the average (SD) of ΣPAHs concentrations was 78.50 (128.9) ng/m3. PM2.5 and PM2.5-bound PAHs were significantly associated with FeNO at various lag days. Single-day lag analyses revealed maximum effects of PM2.5 on FeNO, with an increase of 7.71% (95% CI: 4.67%, 10.83%) per interquartile range (IQR) (48.10 µg/m3) increase of PM2.5 at lag2, and ΣPAHs showed a maximum elevation in FeNO of 6.40% (95% CI: 2.33%, 10.63%) at lag4 per IQR (57.39 ng/m3) increase. Individual PAHs exhibited diversity peak effects on FeNO at lag3 (6 of 17), lag4 (9 of 17) in the single-day model, and lag0-5 (8 of 17) (from lag0-1 to lag0-6) in the cumulative model. Source apportionment indicated coal combustion as the primary contributor (accounting for 30.7%). However, a maximum effect on FeNO (an increase of 21.57% (95% CI: 13.58%, 30.13%) per IQR increase) was observed with traffic emissions at lag4. The findings imply that strategic regulation of particular sources of PAHs, like traffic emissions, during specific periods could significantly contribute to safeguarding public health.
Introduction: Rice (Oryza sativa) serves as a vital staple crop that feeds over half the world's population. Optimizing rice breeding for increasing grain yield is critical for global food security. Heading-date-related or Flowering-time-related traits, is a key factor determining yield potential. However, traditional manual phenotyping methods for these traits are time-consuming and labor-intensive. Method: Here we show that aerial imagery from unmanned aerial vehicles (UAVs), when combined with deep learning-based panicle detection, enables high-throughput phenotyping of heading-date-related traits. We systematically evaluated various state-of-the-art object detectors on rice panicle counting and identified YOLOv8-X as the optimal detector. Results: Applying YOLOv8-X to UAV time-series images of 294 rice recombinant inbred lines (RILs) allowed accurate quantification of six heading-date-related traits. Utilizing these phenotypes, we identified quantitative trait loci (QTL), including verified loci and novel loci, associated with heading date. Discussion: Our optimized UAV phenotyping and computer vision pipeline may facilitate scalable molecular identification of heading-date-related genes and guide enhancements in rice yield and adaptation.
Objective: We explored the correlation between the presence of isocitrate dehydrogenase-1 (IDH1) mutations and the incidence of postoperative epilepsy in patients with glioblastoma, as well as assessed the efficacy of preemptive administration of antiepileptic medications in mitigating the occurrence of postoperative epilepsy. Methods: Fifty-three patients who received a postoperative pathological diagnosis of glioblastoma, were enrolled in this study. Tumor specimens were subjected to IDH1 gene analysis. The patient cohort was stratified based on their IDH1 mutation status and the administration of prophylactic antiepileptic drugs during the postoperative phase. We subsequently conducted a comparative analysis of postoperative epileptic complications within each patient subgroup. Results: In the cohort of 53 patients under study, the occurrence of epilepsy was observed in 10 out of 21 patients carrying IDH1 mutations, while 5 out of 32 patients with wild-type IDH1 also experienced epilepsy, revealing a statistically significant difference (P < 0.05). Among the 27 patients who received prophylactic antiepileptic drugs, 6 of them developed epilepsy, whereas 9 out of 26 patients who did not receive prophylactic antiepileptic drugs exhibited concurrent epilepsy, with no statistically significant difference (P > 0.05). However, when performing a subgroup analysis, it was found that 3 out of 12 patients with IDH1 mutations who received prophylactic antiepileptic drugs experienced epilepsy, whereas 7 out of 9 patients who did not receive prophylactic antiepileptic drugs developed epilepsy, demonstrating a statistically significant difference (P < 0.05). Furthermore, within the group of 15 patients with wild-type IDH1, 3 patients who received prophylactic antiepileptic drugs developed epilepsy, while 2 cases of epilepsy occurred among the 17 patients who did not receive prophylactic antiepileptic drugs, with no statistically significant difference (P > 0.05). Conclusion: In individuals with IDH1 mutant glioblastoma who have undergone surgical resection, the implementation of preventive antiepileptic therapy demonstrates a potential to diminish the occurrence of postoperative epilepsy.
The artificial brain is conceived as advanced intelligence technology, capable to emulate in-memory processes occurring in the human brain by integrating synaptic devices. Within this context, improving the functionality of synaptic transistors to increase information processing density in neuromorphic chips is a major challenge in this field. In this article, Li-ion migration promoting long afterglow organic light-emitting transistors, which display exceptional postsynaptic brightness of 7000 cd m-2 under low operational voltages of 10 V is presented. The postsynaptic current of 0.1 mA operating as a built-in threshold switch is implemented as a firing point in these devices. The setting-condition-triggered long afterglow is employed to drive the photoisomerization process of photochromic molecules that mimic neurotransmitter transfer in the human brain for realizing a key memory rule, that is, the transition from long-term memory to permanent memory. The combination of setting-condition-triggered long afterglow with photodiode amplifiers is also processed to emulate the human responding action after the setting-training process. Overall, the successful integration in neuromorphic computing comprising stimulus judgment, photon emission, transition, and encoding, to emulate the complicated decision tree of the human brain is demonstrated.
A new method based on a digital twin is proposed for fault diagnosis, in order to compensate for the shortcomings of the existing methods for fault diagnosis modeling, including the single fault type, low similarity, and poor visual effect of state monitoring. First, a fault diagnosis test platform is established to analyze faults under constant and variable speed conditions. Then, the obtained data are integrated into the Unity3D platform to realize online diagnosis and updated with real-time working status data. Finally, an industrial test of the digital twin model is conducted, allowing for its comparison with other advanced methods in order to verify its accuracy and application feasibility. It was found that the accuracy of the proposed method for the entire reducer was 99.5%, higher than that of other methods based on individual components (e.g., 93.5% for bearings, 96.3% for gear shafts, and 92.6% for shells).
A core-shell nanostructure of gold nanoparticles@covalent organic framework (COF) loaded with palladium nanoparticles (AuNPs@COF-PdNPs) was designed for the rapid monitoring of catalytic reactions with surface-enhanced Raman spectroscopy (SERS). The nanostructure was prepared by coating the COF layer on AuNPs and then in situ synthesizing PdNPs within the COF shell. With the respective SERS activity and catalytic performance of the AuNP core and COF-PdNPs shell, the nanostructure can be directly used in the SERS study of the catalytic reaction processes. It was shown that the confinement effect of COF resulted in the high dispersity of PdNPs and outstanding catalytic activity of AuNPs@COF-PdNPs, thus improving the reaction rate constant of the AuNPs@COF-PdNPs-catalyzed hydrogenation reduction by 10 times higher than that obtained with Au/Pd NPs. In addition, the COF layer can serve as a protective shell to make AuNPs@COF-PdNPs possess excellent reusability. Moreover, the loading of PdNPs within the COF layer was found to be in favor of avoiding intermediate products to achieve a high total conversion rate. AuNPs@COF-PdNPs also showed great catalytic activities toward the Suzuki-Miyaura coupling reaction. Taken together, the proposed core-shell nanostructure has great potential in monitoring and exploring catalytic processes and interfacial reactions.
Gold , Metal Nanoparticles , Palladium , Spectrum Analysis, Raman , Gold/chemistry , Spectrum Analysis, Raman/methods , Palladium/chemistry , Metal Nanoparticles/chemistry , Catalysis , Metal-Organic Frameworks/chemistry , Surface Properties , Hydrogenation
Short-term exposure to air pollution is associated with a decline in cognitive function. Standardized test scores have been employed to evaluate the effects of air pollution exposure on cognitive performance. Few studies aimed to prove whether air pollution is responsible for reduced test scores; none have implemented a "gold-standard" method for assessing the association such as a randomized, double-blind intervention. This study used a "gold-standard" methodârandomized, double-blind crossoverâto assess whether reducing short-term indoor particle concentrations results in improved test scores in college students in Tianjin, China. Participants (n = 162) were randomly assigned to one of two similar classrooms and completed a standardized English test on two consecutive weekends. Air purifiers with active or sham (i.e., filter removed) particle filtration were placed in each classroom. The filtration mode was switched between the two test days. Linear mixed-effect models were used to evaluate the effect of the intervention mode on the test scores. The results show that air purification (i.e., reducing PM) was significantly associated with increases in the z score for combined (0.11 [95%CI: 0.02, 0.21]) and reading (0.11 [95%CI: 0.00, 0.22]) components. In conclusion, a short-term reduction in indoor particle concentration led to improved test scores in students, suggesting an improvement in cognitive function.
Air Pollution, Indoor , Cross-Over Studies , Particulate Matter , Students , Humans , Double-Blind Method , Male , Female , China , Air Pollutants/analysis , Young Adult , Air Pollution
The impact of mitochondrial dysfunction on the pathogenesis of cardiovascular disease is increasing. However, the precise underlying mechanism remains unclear. Mitochondria produce cellular energy through oxidative phosphorylation while regulating calcium homeostasis, cellular respiration, and the production of biosynthetic chemicals. Nevertheless, problems related to cardiac energy metabolism, defective mitochondrial proteins, mitophagy, and structural changes in mitochondrial membranes can cause cardiovascular diseases via mitochondrial dysfunction. Mitofilin is a critical inner mitochondrial membrane protein that maintains cristae structure and facilitates protein transport while linking the inner mitochondrial membrane, outer mitochondrial membrane, and mitochondrial DNA transcription. Researchers believe that mitofilin may be a therapeutic target for treating cardiovascular diseases, particularly cardiac mitochondrial dysfunctions. In this review, we highlight current findings regarding the role of mitofilin in the pathogenesis of cardiovascular diseases and potential therapeutic compounds targeting mitofilin.
Cardiovascular Diseases , Mitochondrial Proteins , Muscle Proteins , Humans , Animals , Cardiovascular Diseases/metabolism , Cardiovascular Diseases/drug therapy , Muscle Proteins/metabolism , Muscle Proteins/genetics , Mitochondrial Proteins/metabolism , Mitochondria, Heart/metabolism , Mitochondria, Heart/drug effects
