Defect-Rich Functional HfO2-x for Highly Reversible Zn Metal Anode.

Interface engineering attracted tremendous attention owing to its remarkable ability to impede dendrite growth and side reactions in aqueous zinc-ion batteries. Artificial interface layers composed of crystalline materials have been extensively employed to stabilize the Zn anode. However, the diffusion kinetics of Zn2+ in highly crystalline materials are hindered by steric effects from the lattice, thereby limiting the high-rate performance of the cell. Here, defect-rich HfO2-x polycrystals derived from metal-organic frameworks (MOFs) (D-HfO2-x) are developed to enhance the Zn deposition behavior. The discrepancy of dielectric constants between metallic Zn and HfO2 enables the building of an electrostatic shielding layer for uniform Zn deposition. More importantly, the oxygen vacancies in D-HfO2-x provide abundant active sites for Zn2+ adsorption, accelerating the kinetics of Zn2+ migration, which contributes to the preferential exposure of the Zn (002) plane during plating. Consequently, the D-HfO2-x-modified Zn anode delivers ultrastable durability of over 5000 h at 1 mA cm-2 and a low voltage hysteresis of 30 mV. The constructed defective coating provides a guarantee for the stable operation of Zn anodes, and the innovative approach of defective engineering also offers new ideas for the protection of other energy storage devices.

FHL3 promotes the formation of fast glycolytic muscle fibers by interacting with YY1 and muscle glycolytic metabolism.

The proportions of the various muscle fiber types are important in the regulation of skeletal muscle metabolism, as well as animal meat production. Four-and-a-half LIM domain protein 3 (FHL3) is highly expressed in fast glycolytic muscle fibers and differentially regulates the expression of myosin heavy chain (MyHC) isoforms at the cellular level. Whether FHL3 regulates the transformation of muscle fiber types in vivo and the regulatory mechanism is unclear. In this study, muscle-specific FHL3 transgenic mice were generated by random integration, and lentivirus-mediated gene knockdown or overexpression in muscles of mice or pigs was conducted. Functional analysis showed that overexpression of FHL3 in muscles significantly increased the proportion of fast-twitch myofibers and muscle mass but decreased muscle succinate dehydrogenase (SDH) activity and whole-body oxygen consumption. Lentivirus-mediated FHL3 knockdown in muscles significantly decreased muscle mass and the proportion of fast-twitch myofibers. Mechanistically, FHL3 directly interacted with the Yin yang 1 (YY1) DNA-binding domain, repressed the binding of YY1 to the fast glycolytic MyHC2b gene regulatory region, and thereby promoted MyHC2b expression. FHL3 also competed with EZH2 to bind the repression domain of YY1 and reduced H3K27me3 enrichment in the MyHC2b regulatory region. Moreover, FHL3 overexpression reduced glucose tolerance by affecting muscle glycolytic metabolism, and its mRNA expression in muscle was positively associated with hemoglobin A1c (HbA1c) in patients with type 2 diabetes. Therefore, FHL3 is a novel potential target gene for the treatment of muscle metabolism-related diseases and improvement of animal meat production.

Effect of low-frequency noise exposure on cognitive function: a systematic review and meta-analysis.

BACKGROUND: Low-frequency noise may cause changes in cognitive function. However, there is no established consensus on the effect of low-frequency noise on cognitive function. Therefore, this systematic review and meta-analysis aimed to explore the relationship between low-frequency noise exposure and cognitive function. METHODS: We conducted a systematic review and identified original studies written in English on low-frequency noise and cognition published before December 2022 using the PsycINFO, PubMed, Medline, and Web of Science databases. The risk of bias was evaluated according to established guidelines. A random-effects meta-analysis was performed where appropriate. To explore the association between low-frequency noise exposure and cognitive function, we reviewed eight relevant studies. These studies covered cognitive functions grouped into four domains: attention, executive function, memory, and higher-order cognitive functions. The data extraction process was followed by a random-effects meta-analysis for each domain, which allowed us to quantify the overall effect. RESULTS: Our analysis of the selected studies suggested that interventions involving low-frequency noise only had a negative impact on higher-order cognitive functions (Z = 2.42, p = 0.02), with a standardized mean difference of -0.37 (95% confidence interval: -0.67, -0.07). A moderate level of heterogeneity was observed among studies (p = 0.24, I2 = 29%, Tau2 = 0.03). CONCLUSIONS: Our study findings suggest that low-frequency noise can negatively impact higher-order cognitive functions, such as logical reasoning, mathematical calculation, and data processing. Therefore, it becomes important to consider the potential negative consequences of low-frequency noise in everyday situations, and proactive measures should be taken to address this issue and mitigate the associated potential adverse outcomes.

Tracking household carbon inequality in China: Composition effect or coefficient effect?

Reasonable allocation of carbon emission reduction tasks requires addressing household carbon inequality. This study aims to track characteristics of household carbon inequality in China using the recentered influence function (RIF) based on the Household Tracking Survey data in 2018 and the multi-regional input-output table. The Oaxaca-Binder decomposition based on RIF further decomposes household carbon inequality based on spatial heterogeneity into composition and coefficient effects. The results indicate that (1) household carbon inequality is widespread in China, generally close to the 60/30 distribution, favouring high-income families. Furthermore, (2) increases in income, wealth and economic burden and declining marriage rate promote household carbon inequality, which is suppressed by the development of education and the Internet and the increase in car ownership. Additionally, (3) the carbon inequality of urban households is smaller than that of rural households, which is contributed by the composition effects of family size, education, car ownership, Internet development and the coefficient effect of income and housing. Finally, (4) under the composition effect of family size and the coefficient effect of income, the household carbon inequality in the eastern region is smaller than in the central and western regions.

Research progress on the role of ET-1 in diabetic kidney disease.

Diabetic kidney disease (DKD) is one of the common complications of diabetes mellitus, which usually progresses to end-stage renal disease and causes great damage to the health of patients. Endothelin-1 (ET-1), a molecule closely associated with the progression of DKD, has increased expression in response to high glucose stimulation and is involved in hemodynamic changes, inflammation, glomerular and tubular dysfunction in the kidney, causing an increase in proteinuria and a decrease in glomerular filtration function, ultimately leading to glomerulosclerosis and renal failure. This paper aims to review the molecular level changes, regulatory mechanisms, and mechanisms of action of ET-1 under DKD, clinical trials of ET-1 receptor antagonists in recent years and current problems, to provide basic information and new research directions and ideas for the treatment of DKD and ET-1-related research.

Controllable Solid Electrolyte Interphase by Ionic Environment Regulation for Stable Zn-Ion Battery.

Artificial solid electrolyte interphase in organic solutions is effective and facile for long-cycling aqueous zinc ion batteries. However, the specific effects on different ionic environments have not been thoroughly investigated. Herein, pyromellitic acid (PA) are employed as organic ligand to coordinate with Zn2+ under various ionic environments. The connection between the ionic environment and reaction spontaneity is analyzed to provide insights into the reasons behind the effectiveness of the SEI layer and to characterize its protective impact on the zinc anode. Notably, the PA solution (pH4) lacking OH- contributes to the formation of a dense and ultrathin SEI with Zn-PA coordination, preventing direct contact between the anode and electrolyte. Moreover, the presence of organic functional groups facilitates a uniform flux of Zn2+ . These advantages enable stable cycling of the PA4-Zn symmetric cell at a current density of 3 mA cm-2 for over 3500 h. The PA4-Zn//MVO full cell demonstrates excellent electrochemical reversibility. Investigating the influence of the ionic environment on SEI generation informs the development of novel SEI strategies.

Learning and Reusing Quadruped Robot Movement Skills from Biological Dogs for Higher-Level Tasks.

In the field of quadruped robots, the most classic motion control algorithm is based on model prediction control (MPC). However, this method poses challenges as it necessitates the precise construction of the robot's dynamics model, making it difficult to achieve agile movements similar to those of a biological dog. Due to these limitations, researchers are increasingly turning to model-free learning methods, which significantly reduce the difficulty of modeling and engineering debugging and simultaneously reduce real-time optimization computational burden. Inspired by the growth process of humans and animals, from learning to walk to fluent movements, this article proposes a hierarchical reinforcement learning framework for the motion controller to learn some higher-level tasks. First, some basic motion skills can be learned from motion data captured from a biological dog. Then, with these learned basic motion skills as a foundation, the quadruped robot can focus on learning higher-level tasks without starting from low-level kinematics, which saves redundant training time. By utilizing domain randomization techniques during the training process, the trained policy function can be directly transferred to a physical robot without modification, and the resulting controller can perform more biomimetic movements. By implementing the method proposed in this article, the agility and adaptability of the quadruped robot can be maximally utilized to achieve efficient operations in complex terrains.

A highly flexible Ni-Co MOF nanosheet coated Au/PDMS film based wearable electrochemical sensor for continuous human sweat glucose monitoring.

The development of flexible substrate materials and nanomaterials with high electrochemical performance is of great significance for constructing efficient wearable electrochemical sensors for real-time health monitoring. Herein, a wearable electrochemical sweat sensor based on a Ni-Co MOF nanosheet coated Au/polydimethylsiloxane (PDMS) film was prepared for continuous monitoring of the glucose level in sweat with high sensitivity. First, a stretchable Au/PDMS film based three-electrode system was prepared by chemical deposition of a gold layer on the hydrophilic treated PDMS. Then, Ni-Co MOF nanosheets with high electrocatalytic activity were synthesized by a facile solvothermal method and modified on the Au/PDMS electrode. The electrocatalytic activity of the Ni-Co MOF nanosheets synthesized under different Ni : Co ratios was investigated. The Ni-Co MOF/Au/PDMS (NCAP) film electrode showed excellent electrochemical performance for glucose detection with a wide linear range of 20 µM to 790 µM and a high sensitivity of 205.1 µA mM-1 cm-2. In addition, the flexible sensor shows high stability and a good electrochemical response to glucose when stretched and bent to different levels. Moreover, it maintained long-term stability and high selectivity for glucose monitoring. Lastly, a sweat-absorbent cloth was used to cover the working area of the sensor and was fixed with a needle and thread to form a wearable sweat glucose sensor. The sensor can be attached to the skin for stable, accurate and continuous monitoring of glucose levels in human sweat for one day. This work validates the potential of our high-performance wearable sensor for out-of-clinic health monitoring.

A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training.

Adequate adherence is a necessary condition for success with any intervention, including for computerized cognitive training designed to mitigate age-related cognitive decline. Tailored prompting systems offer promise for promoting adherence and facilitating intervention success. However, developing adherence support systems capable of just-in-time adaptive reminders requires understanding the factors that predict adherence, particularly an imminent adherence lapse. In this study we built machine learning models to predict participants' adherence at different levels (overall and weekly) using data collected from a previous cognitive training intervention. We then built machine learning models to predict adherence using a variety of baseline measures (demographic, attitudinal, and cognitive ability variables), as well as deep learning models to predict the next week's adherence using variables derived from training interactions in the previous week. Logistic regression models with selected baseline variables were able to predict overall adherence with moderate accuracy (AUROC: 0.71), while some recurrent neural network models were able to predict weekly adherence with high accuracy (AUROC: 0.84-0.86) based on daily interactions. Analysis of the post hoc explanation of machine learning models revealed that general self-efficacy, objective memory measures, and technology self-efficacy were most predictive of participants' overall adherence, while time of training, sessions played, and game outcomes were predictive of the next week's adherence. Machine-learning based approaches revealed that both individual difference characteristics and previous intervention interactions provide useful information for predicting adherence, and these insights can provide initial clues as to who to target with adherence support strategies and when to provide support. This information will inform the development of a technology-based, just-in-time adherence support systems.

Neprilysin gene transfer: A promising therapeutic approach for Alzheimer's disease.

Alzheimer's disease (AD) is characterized by widespread neurodegeneration throughout the association cortex and limbic system, deposition of amyloid-ß (Aß) in the neuropil and around blood vessels, and formation of neurofibrillary tangles. Aß accumulation is considered the major pathological change in AD progression. In recent years, several therapeutic strategies for treating AD have focused on reducing the Aß burden in the brain. Among these approaches, the expression of Aß-degrading enzymes in the brain has been effective but, so far, impractical for treating patients. Neprilysin (NEP), the most prominent of the Aß-degrading enzymes in vivo, has been successfully delivered intracranially by viral vectors and is a promising therapeutic approach for reducing Aß accumulation and treating AD. However, some challenges are associated with the use of viral and nonviral vectors, including secondary toxicity, activation of the immune response, and low efficiency. Therefore, safe and efficient NEP delivery systems that could avoid the viral problems with minor injury and high transfection efficiency are required to deliver AD medical applications. This Mini-Review summarizes NEP gene transfer technologies that use viral and nonviral vectors and discusses the rationale and benefits of these delivery systems for AD treatment trials, providing a reference for basic and clinical studies on AD.

Celastrol Alleviates Mitochondrial Oxidative Stress and Brain Injury After Intracerebral Hemorrhage by Promoting OPA1-Dependent Mitochondrial Fusion.

Mitochondrial oxidative stress is one of the characteristics of secondary brain injury (SBI) after intracerebral hemorrhage (ICH), contributing largely to the apoptosis of neurons. Celastrol, a quinone methide triterpene that possesses antioxidant and mitochondrial protective properties, has emerged as a neuroprotective agent. However, the activity of celastrol has not been tested in ICH-induced SBI. In this study, we found that celastrol could effectively alleviate neurological function deficits and reduce brain oedema and neuronal apoptosis caused by ICH. Through electron microscopy, we found that celastrol could significantly attenuate mitochondrial morphology impairment. Therefore, we tested the regulatory proteins of mitochondrial dynamics and found that celastrol could reverse the downwards trend of OPA1 expression after ICH. In view of this, by culturing OPA1-deficient primary neurons and constructing neuron-specific OPA1 conditional knockout mice, we found that the protective effects of celastrol on mitochondrial morphology and function after ICH were counteracted in the absence of OPA1. Further experiments also showed that OPA1 is indispensable for the protective effects of celastrol on ICH-induced secondary brain injury. In summary, we have demonstrated that celastrol is a potential drug for the treatment of ICH and have revealed a novel mechanism by which celastrol exerts its antioxidant effects by promoting OPA1-mediated mitochondrial fusion.

Identifying Internet addiction profiles among adolescents using latent profile analysis: Relations to aggression, depression, and anxiety.

BACKGROUND: While many studies have established a positive correlation between adolescents' internet addiction and mental health problems, most of these studies have overlooked the internal heterogeneity of Internet addiction. This study aims to identify latent profiles among adolescents based on their Internet addiction and to examine the differences in aggression, depression, and anxiety across these profiles. METHODS: We conducted a survey involving 7422 adolescents and administered the Young's Internet Addiction Test, Aggression Behavior Questionnaire, Patient Health Questionnaire-9, and Generalized Anxiety Disorder Scale. Latent profile analysis was utilized to categorize Internet addiction profiles among adolescents. Associations between Internet addiction profiles and related factors were examined using the Bolck-Croon-Hagenaars method. RESULTS: Latent profile analysis suggested four profiles of Internet addiction, which were labeled: Regular, Risk, Low Internet addiction, and Internet addiction. The Internet addiction profile showed higher levels of aggression, depression, and anxiety than the Low Internet addiction profile. The Low Internet addiction profile had higher levels of aggression, depression, and anxiety than the Risk profile. The Risk profile demonstrated higher levels of aggression, depression, and anxiety when compared to the Regular profile. LIMITATIONS: Limitations include the cross-sectional design and the self-report measures. CONCLUSIONS: The identified Internet addiction profiles offer differential predictions for aggression, depression, and anxiety. These results underscore the significance of employing latent profile analysis when exploring the associations between Internet addiction and mental health issues.

Building Flame-Retardant Polymer Electrolytes via Microcapsule Technology for Stable Lithium Batteries.

Flame retardants could improve the safety properties of lithium batteries (LBs) with the sacrifice of electrochemical performance due to parasitic reactions. To concur with this, we designed thermal-response clothes for hexachlorophosphazene (HCP) additives by the microcapsule technique with urea-formaldehyde (UF) resin as the shell. HCP@UF combines with polyacrylonitrile (PAN) by hydrogen bonds successfully to form PAN-HCP@UF as the flame-retardant solid polymer electrolyte. The hydrogen bonds ensure excellent mechanical properties of the polymer electrolyte. The multiscale free radical-annihilating agent HCP effectively eliminates hydrogen free radicals of electrolytes under high temperature, showing excellent flame retardation. During the operation of the battery, functional groups on the UF resin act as active sites to promote the migration of lithium ions, while the internal HCP is protected from electrochemical reaction. With 25% HCP@UF addition, the limiting oxygen index of the PAN-HCP@UF increases to 28% and the Li+ transfer number up to 0.80. By UF protection, the initial capacity retention rate of the Li||LFP battery that assembles with PAN-HCP@UF is 88.8% after 500 cycles at 0.5 C. Thus, the microcapsule-encapsulated approach is deemed to provide an innovative strategy to prepare high-safety solid-state LB with a stable long cycle life.

Highly sensitive SERS sensors for glucose detection based on enzyme@MOFs and ratiometric Raman.

Diabetes is a common chronic metabolic disease. The frequent fluctuation of glucose is the main cause of most diabetes complications, which in turn causes harm to the health of patients. Surface-enhanced Raman scattering (SERS) spectroscopy has attracted much attention in the rapid detection of glucose due to its unique molecular fingerprinting ability, ultra-high sensitivity and fast response. However, due to the low affinity between glucose and SERS substrate, poor signal, susceptibility to complex environmental interference, and poor stability of SERS detection, it is still a challenge for SERS to accurately and sensitively determine glucose in complex environments. In this work, we encapsulated 4-mercaptobutyronitrile (4-MBN) as an internal standard (IS) in Au@Ag NRs inside and then Au@4-MBN@Ag NRs, Leucomalachite Green (LMG), glucose oxidase (GOx) and horseradish peroxidase (HPR) were encapsulated in ZIF-8 to prepare a tandem enzyme catalytic ratiometric SERS sensor Au@4-MBN@Ag@LMG@ZIF-8(GOx, HPR) for the detection of glucose in saliva. Because ZIF-8 enhanced the catalytic activity of the enzyme, the ability of glucose enrichment, and weakens the aggregation of Ag NRs. The internal standard signal molecule improves the accuracy and sensitivity of detection. The ratiometric Raman signal I412/I2233 of glucose has a good linear relationship with the concentration in the range of 0.1-100 µM, and the limit of detection (LOD) could be down to 0.03 µM. At the same time, it has excellent selectivity, repeatability and accuracy. The recovery rate of glucose in saliva is 96.50%-105.56 %, which proves the feasibility of the method. The Au@4-MBN@Ag@LMG@ZIF-8(GOx, HPR) sensor prepared in this study showed excellent SERS performance, which was able to detect glucose quickly, sensitively and accurately. This work provides a new strategy for the design of enzyme-catalyzed SERS sensors.

Terms of Engagement: Understanding the Motivations, Preferences, and Attitudes of Older Adults Toward Mobile Cognitive Assessment and Training.

BACKGROUND AND OBJECTIVES: The future of cognitive assessment is likely to involve mobile applications for smartphones and tablets; cognitive training is also often delivered in these formats. Unfortunately, low adherence to these programs can hinder efforts at the early detection of cognitive decline and interfere with examining cognitive training efficacy in clinical trials. We explored factors that increase adherence to these programs among older adults. RESEARCH DESIGN AND METHODS: Focus groups were conducted with older adults (N = 21) and a younger adult comparison group (N = 21). Data were processed using reflexive thematic analysis with an inductive, bottom-up approach. RESULTS: Three primary themes related to adherence were developed from the focus group data. Switches of engagement reflects factors that must be present; without them, engagement is unlikely. Dials of engagement reflects a cost-benefit analysis that users undergo, the outcome of which determines whether a person will be more or less likely to engage. Bracers of engagement reflects factors that nudge users toward engagement by minimizing barriers associated with the other themes. Older adults in general were more sensitive to opportunity costs, preferred more cooperative interactions, and were more likely to mention technology barriers. DISCUSSION AND IMPLICATIONS: Our results are important for informing the design of mobile cognitive assessment and training apps for older adults. These themes provide guidance about ways apps could be modified to increase engagement and adherence, which in turn can more effectively facilitate the early detection of cognitive impairment and the evaluation of cognitive training efficacy.

Adherence Promotion With Tailored Motivational Messages: Proof of Concept and Message Preferences in Older Adults.

This study examined the feasibility of using tailored text messages to promote adherence to longitudinal protocols and determined what facets of text message tone influence motivation. Forty-three older adults (Mage = 73.21, SD = 5.37) were recruited to engage in video-game-based cognitive training for 10 consecutive days. Participants received encouraging text messages each morning that matched their highest or lowest ranking reasons for participating in the study, after which they rated how effective each message was in motivating them to play the games that day. After 10 days, participants rated all possible messages and participated in semi-structured interviews to elicit their preferences for these messages. Results showed that messages matching participants' reasons for participating were more motivating than mismatched messages. Further, participants preferred messages that were personalized (i.e., use second person voice) and in formal tones. Messages consistent with these preferences were also rated as more motivating. These findings establish the feasibility of using message tailoring to promote adherence to longitudinal protocols and the relevance of tailoring messages to be personal and formal.

Astrocyte-Derived Extracellular Vesicular miR-143-3p Dampens Autophagic Degradation of Endothelial Adhesion Molecules and Promotes Neutrophil Transendothelial Migration after Acute Brain Injury.

Pivotal roles of extracellular vesicles (EVs) in the pathogenesis of central nervous system (CNS) disorders including acute brain injury are increasingly acknowledged. Through the analysis of EVs packaged miRNAs in plasma samples from patients with intracerebral hemorrhage (ICH), it is discovered that the level of EVs packaged miR-143-3p (EVs-miR-143-3p) correlates closely with perihematomal edema and neurological outcomes. Further study reveals that, upon ICH, EVs-miR-143-3p is robustly secreted by astrocytes and can shuttle into brain microvascular endothelial cells (BMECs). Heightened levels of miR-143-3p in BMECs induce the up-regulated expression of cell adhesion molecules (CAMs) that bind to circulating neutrophils and facilitate their transendothelial cell migration (TEM) into brain. Mechanism-wise, miR-143-3p directly targets ATP6V1A, resulting in impaired lysosomal hydrolysis ability and reduced autophagic degradation of CAMs. Importantly, a VCAM-1-targeting EVs system to selectively deliver miR-143-3p inhibitor to pathological BMECs is created, which shows satisfactory therapeutic effects in both ICH and traumatic brain injury (TBI) mouse models. In conclusion, the study highlights the causal role of EVs-miR-143-3p in BMECs' dysfunction in acute brain injury and demonstrates a proof of concept that engineered EVs can be devised as a potentially applicable nucleotide drug delivery system for the treatment of CNS disorders.

The m6A methyltransferase METTL3 drives neuroinflammation and neurotoxicity through stabilizing BATF mRNA in microglia.

Persistent neuroinflammation and progressive neuronal loss are defining features of acute brain injury including traumatic brain injury (TBI) and cerebral stroke. Microglia, the most abundant type of brain-resident immune cells, continuously surveil the environment and play a central role in shaping the inflammatory state of the central nervous system (CNS). In the study, we discovered that the protein expression of METTL3 (a m6A methyltransferase) was upregulated in inflammatory microglia independent of increased Mettl3 gene transcription following TBI in both human and mouse subjects. Subsequently, we identified TRIP12, a HECT-domain E3 ubiquitin ligase, as a negative regulator of METTL3 protein expression by facilitating METTL3 K48-linked polyubiquitination. Importantly, selective ablation of Mettl3 inhibited microglial pathogenic activities, diminished neutrophil infiltration, rescued neuronal loss and facilitated functional recovery post-TBI. Using MeRIP-seq and CUT&Tag sequencing, we identified that METTL3 promoted the expression of Basic Leucine Zipper Transcriptional Factor ATF-Like (BATF), which in turn directly bound to a cohort of characteristic inflammatory cytokines and chemokine genes. Enhanced activities of BATF in microglia elicited TNF-dependent neurotoxicity and can also promote neutrophil recruitment through releasing CXCL2. Pharmacological inhibition of METTL3 using a BBB-penetrating drug-loaded nano-system showed satisfactory therapeutic effects in both TBI and stroke mouse models. Collectively, our findings identified METTL3-m6A-BATF axis as a potential therapeutic target for terminating detrimental neuroinflammation and progressive neuronal loss following acute brain injury. METTL3 protein is significantly up-regulated in inflammatory microglia due to the decreased proteasomal degradation mediated by TRIP12 and ERK-USP5 pathways. METTL3 stabilized BATF mRNA stability and promoted BATF expression through the m6A-IGF2BP2-dependent mechanism. Elevated expression of BATF elicits a pro-inflammatory gene program in microglia, and aggravates neuroinflammatory response including local immune responses and peripheral immune cell infiltration. Genetic deletion or pharmaceutically targeting METTL3-BATF axis suppressed microglial pro-inflammatory activities and promoted neurological recovery following TBI and stroke.

FNDC5 prevents oxidative stress and neuronal apoptosis after traumatic brain injury through SIRT3-dependent regulation of mitochondrial quality control.

Mitochondrial dysfunction and oxidative stress are important mechanisms for secondary injury after traumatic brain injury (TBI), which result in progressive pathophysiological exacerbation. Although the Fibronectin type III domain-containing 5 (FNDC5) was reported to repress oxidative stress by retaining mitochondrial biogenesis and dynamics, its possible role in the secondary injury after TBI remain obscure. In present study, we observed that the level of serum irisin (the cleavage product of FNDC5) significantly correlated with the neurological outcomes of TBI patients. Knockout of FNDC5 increased the lesion volume and exacerbated apoptosis and neurological deficits after TBI in mice, while FNDC5 overexpression yielded a neuroprotective effect. Moreover, FNDC5 deficiency disrupted mitochondrial dynamics and function. Activation of Sirtuin 3 (SIRT3) alleviated FNDC5 deficiency-induced disruption of mitochondrial dynamics and bioenergetics. In neuron-specific SIRT3 knockout mice, FNDC5 failed to attenuate TBI-induced mitochondrial damage and brain injuries. Mechanically, FNDC5 deficiency led to reduced SIRT3 expression via enhanced ubiquitin degradation of transcription factor Nuclear factor erythroid 2-related factor 2 (NRF2), which contributed to the hyperacetylation and inactivation of key regulatory proteins of mitochondrial dynamics and function, including OPA1 and SOD2. Finally, engineered RVG29-conjugated nanoparticles were generated to selectively and efficiently deliver irisin to the brain of mice, which yielded a satisfactory curative effect against TBI. In conclusion, FNDC5/irisin exerts a protective role against acute brain injury by promoting SIRT3-dependent mitochondrial quality control and thus represents a potential target for neuroprotection after TBI.

Control Beliefs Mediate the Within-Person Relationship Between Everyday Activity Volition and Daily Subjective Age.

OBJECTIVES: Appraisal and interpretation of personal experiences resulting from interaction with situational contexts might play an important role in shaping subjective age at the within-person level, but it is unclear how this process unfolds. We propose that older adults evaluate situational contexts and reflect on their general psychological resources when determining their subjective age, and tested this proposal with volition of daily activities as a proxy for appraisal of situational contexts and control beliefs as a proxy for psychological resources. We hypothesize that appraising daily activities one engaged in as obligatory would deplete one's perceived control and concomitantly make one feel older. METHODS: Older adults (n = 116) ranging in age from 60 to 90 (M = 64.84) completed a 9-day daily diary study online, resulting in 743 total days. Participants reported their sociodemographic characteristics on Day 1 and major daily activities, volition of every reported activity, felt age, and control beliefs on Days 2-9. RESULTS: On days when older adults felt that activities they engaged in were of their own volition, they also felt more in control. A lower-level mediation result suggested that within-person control beliefs mediated the relationship between volition of daily activities and subjective age. DISCUSSION: Our findings suggest that older adults evaluate situational contexts and reflect on their control beliefs as a general psychological resource when determining their subjective age. These findings show the important role psychological resources play in determining subjective age from a within-person perspective and extended the within-person process proposed in previous theoretical models.