A novel and ubiquitous miRNA-involved regulatory module ensures precise phosphorylation of RNA polymerase II and proper transcription.

Proper transcription orchestrated by RNA polymerase II (RNPII) is crucial for cellular development, which is rely on the phosphorylation state of RNPII's carboxyl-terminal domain (CTD). Sporangia, developed from mycelia, are essential for the destructive oomycetes Phytophthora, remarkable transcriptional changes are observed during the morphological transition. However, how these changes are rapidly triggered and their relationship with the versatile RNPII-CTD phosphorylation remain enigmatic. Herein, we found that Phytophthora capsici undergone an elevation of Ser5-phosphorylation in its uncanonical heptapeptide repeats of RNPII-CTD during sporangia development, which subsequently changed the chromosomal occupation of RNPII and primarily activated transcription of certain genes. A cyclin-dependent kinase, PcCDK7, was highly induced and phosphorylated RNPII-CTD during this morphological transition. Mechanistically, a novel DCL1-dependent microRNA, pcamiR1, was found to be a feedback modulator for the precise phosphorylation of RNPII-CTD by complexing with PcAGO1 and regulating the accumulation of PcCDK7. Moreover, this study revealed that the pcamiR1-CDK7-RNPII regulatory module is evolutionarily conserved and the impairment of the balance between pcamiR1 and PcCDK7 could efficiently reduce growth and virulence of P. capsici. Collectively, this study uncovers a novel and evolutionary conserved mechanism of transcription regulation which could facilitate correct development and identifies pcamiR1 as a promising target for disease control.

The effect of different high-intensity interval training protocols on cardiometabolic and inflammatory markers in sedentary young women: A randomized controlled trial.

Few studies have reported the cardiovascular health effects of different high-intensity interval training (HIIT) protocols among sedentary young women. We investigated the impact of a traditional HIIT programme and a high-intensity circuit training (HICT) programme on lipid profiles and inflammatory cytokine levels in sedentary young women. Forty-two women were randomly assigned to HICT (body weight-based training), HIIT (cycling-based training), or control groups (n = 14 each). HICT and HIIT participants completed an 8-week training programme of three sessions per week. Total cholesterol (TC), triglyceride, high- and low-density lipoprotein, leptin, resistin, tumour necrosis factor-alpha (TNF-α), interleukin-8, and interferon-gamma levels were measured before and after the intervention. Post-intervention, TC and leptin were decreased in the HICT group. The HICT group also demonstrated increased lean mass, upper and lower limb strength, and balance, while the HIIT group displayed improved lower limb strength. Additionally, the control group showed significant increases in triglyceride levels, weight, body mass index, and fat mass. In conclusion, although both HICT and HIIT interventions showed improvements in cardiovascular health and physical fitness, participants in the HICT group experienced more health benefits.

Getting to Know Named Entity Recognition: Better Information Retrieval.

Named entity recognition (NER) is a powerful computer system that utilizes various computing strategies to extract information from raw text input, since the early 1990s. With rapid advancement in AI and computing, NER models have gained significant attention and been serving as foundational tools across numerus professional domains to organize unstructured data for research and practical applications. This is particularly evident in the medical and healthcare fields, where NER models are essential in efficiently extract critical information from complex documents that are challenging for manual review. Despite its successes, NER present limitations in fully comprehending natural language nuances. However, the development of more advanced and user-friendly models promises to improve work experiences of professional users significantly.

The effect of resistance training on patients with knee osteoarthritis: a systematic review and meta-analysis.

The objective of this study is to investigate the beneficial effects of resistance training (RT) on individuals suffering from knee osteoarthritis (KOA). In order to gather relevant studies from the beginning of various databases until January 2023, a comprehensive search was conducted on PubMed, Embase, Scopus, Web of Science, and The Cochrane Library. Additionally, manual searches were performed on the reference lists. The association between RT and KOA was analysed using a random-effects model. The results indicated that patients with KOA who underwent RT experienced a significant reduction in the WOMAC (Western Ontario and McMaster Universities Osteoarthritis) Pain index (WMD = -2.441; 95% CI = -3.610 to -1.273; p < 0.01), the WOMAC Stiffness index (WMD = -1.018; 95% CI = -1.744 to -0.293; p < 0.01), the WOMAC Function index (WMD = -7.208; 95% CI = -10.412 to -4.004; p < 0.01), and the VAS (Visual Analogue Scale) index (WMD = -5.721; 95% CI = -9.320 to -2.121; p < 0.01). These improvements were observed when compared to the control group. However, no significant difference was found in the 6-MWT (6-Minute Walk Test) index between the two groups (WMD = 2.659; 95% CI= -16.741 to 22.058; p = 0.788). Consequently, RT has the potential to positively enhance pain, stiffness, and function in patients with KOA, while the 6-MWT index may not exhibit significant improvement.

MSFF-CDCGAN: A novel method to predict RNA secondary structure based on Generative Adversarial Network.

Access to RNA secondary structure is a prerequisite for understanding and mastering RNA function. RNA secondary structures play an important role in cells, they can cause or contribute to neurological disorders and can be applied in the medical field. However, the experimental method to obtain RNA secondary structure is costly, laborious and not universal. Although computational methods can predict RNA secondary structure more accurately for short-sequence RNAs, it cannot predict long-sequence RNAs and pseudoknot, which is the bottleneck of RNA secondary structure prediction at present. In recent years, researchers have attempted to use deep learning algorithms to predict RNA secondary structure and have achieved results. However, the small amount of data on the secondary structure of long-sequence RNAs leads to the low accuracy of deep learning methods to predict the secondary structure of RNAs across races. Similarly, RNA structure with pseudoknot is very complex and insufficient data caused the deep learning algorithm to struggle to predict the secondary structure of RNA containing pseudoknots. The RNA data are encoded into grayscale images by a unique encoding method based on the real RNA secondary structure and sequence information. Then, this paper reasonably expands the image data to increase the amount of RNA data, solves the problem of insufficient data for predicting long sequences and RNA secondary structure with pseudoknots in current deep learning methods, and provides a good data foundation for deep learning.The article proposes a multi-scale feature fusion Conditional Deep Convolutional Generative Adversarial Network prediction model (MSFF-CDCGAN) based on the improved Conditional Deep Convolutional Generative Adversarial Network (CDCGAN) model to predict RNA secondary structure. The experimental results showed that the MSFF-CDCGAN model could predict long-sequence RNAs and pseudoknots more accurately than traditional prediction methods. This paper introduces Generative Adversarial Network (GAN) to RNA secondary structure prediction for the first time. It uses a unique image encoding approach to expand the original RNA data set, thus transforming the structure prediction problem into an image analysis problem and effectively solving the bottleneck in RNA secondary structure prediction.

Associations of Device-Measured Physical Activity, Sedentary Behavior, and Executive Function in Preadolescents: A Latent Profile Approach.

PURPOSE: This study investigated the associations between physical activity (PA), sedentary behavior, and executive function in preadolescents. METHODS: One hundred and twenty preadolescents were recruited from 2 Hong Kong primary schools. PA and sedentary behavior were recorded for 7 consecutive days by accelerometer. Executive function performance, including inhibition (Stroop task and Flanker task) and working memory (Sternberg paradigm task), were measured. Body mass index and cardiorespiratory fitness (multistage fitness test) were tested. Latent profile analysis explored the profiles of PA and sedentary behavior in preadolescents. RESULTS: Three distinct profiles were identified: low activity, average activity, and high activity. Participants in low activity performed worse in the accuracy of Stroop task (vs average activity, P = .03; vs high activity, P < .01), Flanker task (vs average activity, P = .02; vs high activity, P < .001), and Sternberg paradigm task (vs average activity, P < .01; vs high activity, P < .01). No significant difference was observed between participants with average and high activities. No significant association was observed for profiles on body mass index and cardiorespiratory fitness. CONCLUSION: Supplementing the consensus of the literature that moderate to vigorous PA benefits cognition, the authors conclude that light PA may also enhance preadolescents' executive functioning.

ChatGPT, an Opportunity to Understand More About Language Models.

ChatGPT, a leading large language model, has achieved some success beyond previous language models and caught the world's attention since its release in late 2022. Businesses and healthcare professional fields have raised strong interests in investing in large language models to assist various kinds of information searching in their domain of expertise. Under the influence of ChatGPT, searched information may be received in a new personalized chat format, in contrast to the traditional search engines with pages of results for users to evaluate and open. Large language models and generative AI present new opportunities for librarians to understand more about language models' development as well as the future directions of the language models that are developed behind the user interfaces. Being aware of how language models impact the communication of information will enrich librarians' abilities to examine the quality of AI outputs and awareness of users' rights and data curation policies, to better assist patrons' research activities that involve using language models in the foreseeable future.

Prompt Engineers or Librarians? An Exploration.

The article explores the role of "prompt engineers" as a professional title, extending beyond the field of generative AI for developers, comparing certain tasks to the role of librarians, such as conducting search queries. It is possible for librarians to work with AI models in conjunction with traditional literature databases with emphasizing the need to recognize the distinct nature of these information resources. We should take cautious consideration of the specific skills worth acquiring to improve work efficiency, as well as an understanding of the development trends in generative AI and library science.

The consensus Nglyco -X-S/T motif and a previously unknown Nglyco -N-linked glycosylation are necessary for growth and pathogenicity of Phytophthora.

Asparagine (Asn, N)-linked glycosylation within Nglyco -X-S/T; X ≠ P motif is a ubiquitously distributed post-translational modification that participates in diverse cellular processes. In this work, N-glycosylation inhibitor was shown to prevent Phytophthora sojae growth, suggesting that N-glycosylation is necessary for oomycete development. We conducted a glycoproteomic analysis of P. sojae to identify and map N-glycosylated proteins and to quantify differentially expressed glycoproteins associated with mycelia, asexual cyst, and sexual oospore developmental stages. A total of 355 N-glycosylated proteins was found, containing 496 glycosites, potentially involved in glycan degradation, carbon metabolism, glycolysis, or other metabolic pathways. Through PNGase F deglycosylation assays and site-directed mutagenesis of a GPI transamidase protein (GPI16) upregulated in cysts and a heat shock protein 70 (HSP70) upregulated in oospores, we demonstrated that both proteins were N-glycosylated and that the Nglyco -N motif is a target site for asparagine - oligosaccharide linkage. Glycosite mutations of Asn 94 Nglyco -X-S/T in the GPI16 led to impaired cyst germination and pathogenicity, while mutation of the previously unknown Asn 270 Nglyco -N motif in HSP70 led to decreased oospore production. In addition to providing a map of the oomycete N-glycoproteome, this work confirms that P. sojae has evolved multiple N-glycosylation motifs essential for growth.

Probing the mechanism of thermally driven thiol-Michael dynamic covalent chemistry.

The kinetics and mechanism of the thermally activated dynamic covalent exchange of thiol-Michael adducts is investigated. A model system of thiol-Michael adducts between thiophenol and phenylvinylketone derivatives and adducts between 2-mercaptoethanol phenylvinylketone derivatives in N,N-dimethylformamide (DMF) at elevated temperatures is used to probe the underlying exchange mechanism. The kinetic data show negligible free Michael acceptor, which is consistent with the highly efficient thiol-Michael reaction being a "click"-like reaction that significantly favors the adduct form. At elevated temperatures of 90 °C in DMF the thiol-Michael adducts reach equilibrium after 24 h, although equilibration did not occur within 24 h at 60 °C or 75 °C, and negligible exchange occurs under ambient conditions. A kinetic model was developed to describe the dynamic covalent exchange and equilibration. The experimental and simulation kinetic data of dynamic covalent exchange are consistent with the thiol-Michael adducts undergoing a retro-Michael reaction, followed by subsequent addition of a free thiol to the liberated Michael acceptor. Kinetic analysis is consistent with the fragmentation, or retro-Michael reaction, being the rate-determining step in the dynamic covalent exchange. This suggests that the key step in dynamic covalent exchange is not enhanced by addition of free thiol or free Michael acceptor, since the addition reaction is much faster than the retro-Michael reaction. This fundamental study will guide the design of organic compounds, materials, and bioconjugates that utilize the thermally activated dynamic covalent thiol-Michael linkages.

N6-methyloxyadenine-mediated detoxification and ferroptosis confer a trade-off between multi-fungicide resistance and fitness.

Multi-fungicide resistance (MFR) is a serious environmental problem, which results in the excessive use of fungicides. Fitness penalty, as a common phenomenon in MFR, can partially counteract the issue of resistance due to the weakened vigor of MFR pathogens. Their underlying mechanism and relationship remain unexplained. By Oxford Nanopore Technologies sequencing and dot blot, we found that N6-methyloxyadenine (6mA) modification, the dominate epigenetic marker in Phytophthora capsici, was significantly altered after MFR emerged. Among the differently methylated genes, PcGSTZ1 could efficiently detoxify SYP-14288, a novel uncoupler, through complexing the fungicide with glutathione and induce MFR. Interestingly, PcGSTZ1 overexpression was induced by elevated 6mA levels and chromatin accessibility to its genomic loci. Moreover, the overexpression led to reactive oxygen species burst and ferroptosis in SYP-14288-resistant mutants, which enhanced the resistance and induced fitness penalty in P. capsici through triggering low energy shock adaptive response. Furthermore, this study revealed that the 6mA-PcGSTZ1-ferroptosis axis could mediate intergenerational resistance memory transmission and enabled adaptive advantage to P. capsici. In conclusion, the findings provide new insights into the biological role of 6mA as well as the mechanisms underlying the trade-off between MFR and fitness. These could also benefit disease control through the blockade of the epigenetic axis to resensitize resistant isolates.IMPORTANCEN6-methyloxyadenine (6mA) modification on DNA is correlated with tolerance under different stress in prokaryotes. However, the role of 6mA in eukaryotes remains poorly understood. Our current study reveals that DNA adenine methyltransferase 1 (DAMT1)-mediated 6mA modification at the upstream region of GST zeta 1 (GSTZ1) is elevated in the resistant strain. This elevation promotes the detoxification uncoupler and induces multifungicide resistance (MFR). Moreover, the overexpression led to reactive oxygen species burst and ferroptosis in SYP-14288-resistant mutants, which enhanced the resistance and induced fitness penalty in Phytophthora capsici through triggering low energy shock adaptive response. Furthermore, this study revealed that the 6mA-PcGSTZ1-ferroptosis axis could mediate intergenerational resistance memory transmission and enabled adaptive advantage to P. capsici. Overall, our findings uncover an innovative mechanism underlying 6mA modification in regulating PcGSTZ1 transcription and the ferroptosis pathway in P. capsici.

GERWR: Identifying the Key Pathogenicity- Associated sRNAs of Magnaporthe Oryzae Infection in Rice Based on Graph Embedding and Random Walk With Restart.

Rice blast, caused by Magnaporthe oryzae(M.oryzae), is a destructive rice disease that reduces rice yield by 10% to 30% annually. It also affects other cereal crops such as barley, wheat, rye, millet, sorghum, and maize. Small RNAs (sRNAs) play an essential regulatory role in fungus-plant interaction during the fungal invasion, but studies on pathogenic sRNAs during the fungal invasion of plants based on multi-omics data integration are rare. This paper proposes a novel approach called Graph Embedding combined with Random Walk with Restart (GERWR) to identify pathogenic sRNAs based on multi-omics data integration during M.oryzae invasion. By constructing a multi-omics network (MRMO), we identified 29 pathogenic sRNAs of rice blast fungus. Further analysis revealed that these sRNAs regulate rice genes in a many-to-many relationship, playing a significant regulatory role in the pathogenesis of rice blast disease. This paper explores the pathogenic factors of rice blast disease from the perspective of multi-omics data analysis, revealing the inherent connection between pathogenic factors of different omics. It has essential scientific significance for studying the pathogenic mechanism of rice blast fungus, the rice blast fungus-rice model system, and the pathogen-host interaction in related fields.

Evaluating the rate of reversal of fentanyl-induced respiratory depression using a novel long-acting naloxone nanoparticle, cNLX-NP.

Introduction: Fentanyl and fentanyl analogs (F/FA) have become increasingly common adulterants in counterfeit prescription pills and illicit street drug mixtures due to their ease of synthesis and exceedingly high potency. The ongoing epidemic of fatal overdoses fueled by F/FA continues to highlight the need for longer-acting therapies than naloxone (NLX), the current gold-standard for reversing opioid overdoses, which shows limited efficacy to prevent renarcotization associated with F/FA toxicity. A novel opioid reversal agent based on covalent naloxone nanoparticles (cNLX-NP) has been shown to blunt fentanyl-induced respiratory depression out to 48 hr, demonstrating its potential therapeutic utility. The purpose of this study was to characterize how rapidly cNLX-NP reverses fentanyl-induced respiratory effects as well as the duration of its protective effects. Methods: Sprague Dawley male rats (n=6/group) were tested on an oximeter for baseline percent arterial oxygen saturation (%SaO2) challenged with 0.1 mg/kg SC fentanyl and 15 min later given 10 mg/kg IM doses of NLX, nalmefene (NLMF), or cNLX-NP and continuously monitored via oximetry for 10 minutes. One week later the experiment was repeated using a 1:1 mixture of NLX:cNLX-NP as the reversal agent in the rats that previously received NLX alone. Results: While both NLX and NLMF rapidly reversed %SaO2 to baseline within 1 min, rats that received cNLX-NP did not return to >90% SaO2 levels until 9 min after administration. Similarly, heart and breath rates returned to baseline within 1 min of treatment with NLX and NLMF but did not return to baseline until 10 minutes after cNLX-NP administration. In contrast, NLX:cNLX-NP reversed all fentanyl-induced respiratory depressive effects within one minute. Discussion: While cNLX-NP alone may not sufficiently reverse F/FA overdose in a timely manner, mixing free NLX with cNLX-NP can provide a mechanism to both rapidly reverse fentanyl-related effects and maintain extended protection against synthetic opioid toxicity. These data support further development of cNLX-NP as a fast-acting and long-lasting antidote to treat F/FA-induced respiratory depression and overdose, and potentially prevent renarcotization in humans.

Distribution and removal mechanism of microplastics in urban wastewater plants systems via different processes.

Microplastic pollution threatens water systems worldwide. As one of the most important parts of city wastewater treatment, wastewater treatment plants are not only microplastics interception barriers but also emission sources. Water samples were collected from each sewage treatment plant stage and sludge from the sludge dewatering room. Microplastics were extracted using wet peroxide oxidation and flotation, and the abundance, size, shape, and polymer type of microplastics were detected. Basis on the results, the influence of each process on the removal rate and characteristics of microplastics under the same influent source was analysed. The influent microplastic concentration in this study was 32.5 ± 1.0 n/L, which rapidly decreased after treatment. The removal rates of the sequencing batch reactor activated sludge, cyclic activated sludge, and anaerobic anoxic oxic technologies were 73.0%, 75.6%, and 83.9%, respectively. Most microplastics were transported to the sludge, and the concentration of microplastics in dehydrated sludge was 27.2 ± 3.1 n/g. Microplastics removal occurred primarily during the primary and secondary stages. Disposal processes, settling time, and process design affected wastewater treatment plant microplastic removal rates at each stage. Significant differences in microplastic characteristics were observed at each stage, with the most abundant being fragment shaped, particle sizes of 30-100 µm, and black in colour. Sixteen polymer types were identified using a Raman spectrometer. The predominant polymers are polypropylene, polyethylene, and polyethylene terephthalate. This study demonstrates that optimising the process design of existing wastewater treatment plants is crucial for the prevention and control of microplastic pollution. It is suggested that the process settings of contemporary wastewater treatment plants should be studied in depth to develop a scientific foundation for avoiding and managing microplastic pollution in urban areas.

Prediction of Impulsive Aggression Based on Video Images.

In response to the subjectivity, low accuracy, and high concealment of existing attack behavior prediction methods, a video-based impulsive aggression prediction method that integrates physiological parameters and facial expression information is proposed. This method uses imaging equipment to capture video and facial expression information containing the subject's face and uses imaging photoplethysmography (IPPG) technology to obtain the subject's heart rate variability parameters. Meanwhile, the ResNet-34 expression recognition model was constructed to obtain the subject's facial expression information. Based on the random forest classification model, the physiological parameters and facial expression information obtained are used to predict individual impulsive aggression. Finally, an impulsive aggression induction experiment was designed to verify the method. The experimental results show that the accuracy of this method for predicting the presence or absence of impulsive aggression was 89.39%. This method proves the feasibility of applying physiological parameters and facial expression information to predict impulsive aggression. This article has important theoretical and practical value for exploring new impulsive aggression prediction methods. It also has significance in safety monitoring in special and public places such as prisons and rehabilitation centers.

Effect of Cyberlindnera jadinii supplementation on growth performance, serum immunity, antioxidant status, and intestinal health in winter fur-growing raccoon dogs (Nyctereutes procyonoides).

Introduction: This study aimed to investigate the effects of Cyberlindnera jadinii supplementation on the growth performance, nutrient utilization, serum biochemistry, immunity, antioxidant status, and intestinal microbiota of raccoon dogs during the winter fur-growing period. Methods: Forty-five 135 (±5) day-old male raccoon dogs were randomly assigned to three dietary groups supplemented with 0 (group N), 1 × 109 (group L) and 5 × 109 CFU/g (group H) Cyberlindnera jadinii, with 15 raccoon dogs per group. Results: The results showed that Cyberlindnera jadinii in groups L and H improved average daily gain (ADG) and decreased feed-to-weight ratio (F/G) (P < 0.05). No significant difference was found in nutrient digestibility and nitrogen metabolism among the three groups (P > 0.05). Compared with group N, serum glucose levels were lower in groups L and H (P < 0.05). The levels of serum immunoglobulins A and G in group L were higher than those in the other two groups (P < 0.05), and the levels of serum immunoglobulins A and M in group H were higher than those in group N (P < 0.05). Supplementation with Cyberlindnera jadinii in groups L and H increased serum superoxide dismutase activity, and the total antioxidant capacity in group H increased compared with group N (P < 0.05). The phyla Bacteroidetes and Firmicutes were dominant in raccoon dogs. The results of principal coordinate analysis (PCoA) showed that the composition of microbiota in the three groups changed significantly (P < 0.05). The relative abundance of Campylobacterota was increased in the H group compared to the N and L groups (P < 0.05). The relative abundance of Sarcina was increased in group L compared with the other two groups (P < 0.05), while the relative abundance of Subdoligranulum and Blautia were decreased in group H compared with the other two groups (P < 0.05). Also, the relative abundance of Prevotella, Sutterella and Catenibacterium was higher in group L (P < 0.05) compared with group H. Discussion: In conclusion, dietary supplementation with Cyberlindnera jadinii improved growth performance, antioxidant activity, immune status, and improved intestinal microbiota in winter fur-growing raccoon dogs. Among the concentrations tested, 1 × 109 CFU/g was the most effective level of supplementation.

Characterization of Dissolved Organic Matter from Agricultural and Livestock Effluents: Implications for Water Quality Monitoring.

There is growing concern about the impact of agricultural practices on water quality. The loss of nutrients such as nitrogen and phosphorous through agricultural runoff poses a potential risk of water quality degradation. However, it is unclear how dissolved organic matter (DOM) composition is associated with pollution levels in water bodies. To address this, we conducted a cross-year investigation to reveal the nature of DOM and its relationship to water quality in agricultural effluents (AEs) and livestock effluents (LEs). We discovered that DOM fluorescence components of AEs were mainly from autochthonous and terrestrial sources, while in LEs it was primarily from autochthonous sources. LEs showed a higher ß:α and biological index (BIX) than AEs, indicating that LEs had higher biological activity. Compared to the LEs, DOM in AEs exhibited a higher humification index (HIX), illustrating that DOM was more humic and aromatic. Overall, our results suggest that the BIX and fluorescence index (FI) were best suited for the characterization of water bodies impacted by LEs and AEs. Excitation-emission matrix spectroscopy and parallel factor (EEMs-PARAFAC) analysis showed that DOM in AEs was mainly a humic-like material (~64%) and in LEs was mainly protein-like (~68%). Tryptophan-like compounds (C1) were made more abundant in AEs because of the breakdown of aquatic vegetation. The microbial activity enhanced protein-like substances (C1 and C2) in LEs. Our study revealed a positive correlation between five-day biochemical oxygen demand (BOD5) concentrations and tyrosine-like substance components, suggesting that fluorescence peak B may be a good predictor of water quality affected by anthropogenic activities. For both LEs and AEs, our results suggest that peak D may be a reliable water quality surrogate for total phosphorus (TP).

Do acute and chronic physical activity interventions affect the cognitive function of preschool children? A meta-analysis.

This meta-analysis aims to investigate the effects of acute and chronic physical activity (PA) interventions on multiple domains of cognitive function (CF) in preschool children. Electronic databases (PsycINFO, PubMed, SPORTDiscus, Embase, Web of Science, MEDLINE, and ERIC) were searched for relevant studies between January 2000 and February 2022. Studies that examined the effects of acute or chronic physical activity interventions on CF in preschool children aged 2-6 years were included. A total of 16 articles were eligible for this meta-analysis. Results showed that there was no effect of acute PA interventions on CF (Hedges' g = 0.04; 95% CI = -0.12, 0.19). Chronic PA interventions had a moderate and positive effect on overall CF (Hedges' g = 0.49; 95% CI = 0.29, 0.69), a large effect on perception (Hedges' g = 1.19; 95% CI = 0.64, 1.75), and a moderate effect on inhibitory control (Hedges' g = 0.73; 95% CI = 0.22, 1.24). The moderator analyses showed that overall CF performance was significantly moderated by intervention modality and assessment of cognitive outcomes, and no other moderator (study design, sample size, frequency, duration, and session length) was found to have an effect. Chronic PA intervention might be a promising way to promote multiple aspects of CF, especially executive function and perception. Future studies should explore the effect of different intensities of PA on the CF of preschool children to discern the most effective PA prescription to, in turn, enhance the CF of preschool children.

Lycium barbarum (Wolfberry) glycopeptide prevents stress-induced anxiety disorders by regulating oxidative stress and ferroptosis in the medial prefrontal cortex.

BACKGROUND: Lycium barbarum (Wolfberry) extract has been shown to be effective in neuroprotection against aging or neural injury. Knowledge of its potential roles and biological mechanisms in relieving mental disorders, however, remains limited. PURPOSE: To investigate the potency of Lycium barbarum glycopeptide (LbGp) in alleviating anxiety disorders and the related biological mechanisms. METHODS: LbGp was administrated to mice subjected to 14 days of chronic restrain stress (CRS) via the intragastric route. The anxiolytic effect was evaluated by a battery of behavioral assays. The morphology of neurons and glial cells was evaluated, and cortical neuronal calcium transients were recorded in vivo. The molecular mechanism of LbGp was also investigated. RESULTS: LbGp effectively relieved anxiety-like and depressive behaviors under CRS. Mechanistic studies further showed that LbGp treatment relieved oxidative stress and lipid peroxidation in the medial prefrontal cortex (mPFC). In particular, the ferroptosis pathway was inhibited by LbGp, revealing a previously unrecognized mechanism of the anxiolytic role of wolfberry extract. CONCLUSION: In summary, our results supported the future development of LbGp to prevent or ameliorate stress-induced anxiety disorders. Our work provides a promising strategy for early intervention for pateitents with mental disorders by applying natural plant extracts.

Fabrication of ROS-responsive nanoparticles by modifying the interior pore-wall of mesoporous silica for smart delivery of azoxystrobin.

The suboptimal efficiency in pesticide utilization may elevate residues, posing safety risks to human food and non-target organisms. To address this challenge, delivery systems, such as pathogen infection stimuli-responsive carriers, can be employed to augment the efficiency of fungicide utilization. The bursting of reactive oxygen species (ROS) is a common defense response of host plants to pathogenic infections. In this study, ROS-responsive mesoporous silica nanoparticles (MSN) modified with phenyl sulfide (PHS) as azoxystrobin (AZOX) carrier (MSN-PHS-AZOX) were fabricated. Results demonstrated that MSN-PHS-AZOX exhibited fungicide release kinetics dependent on ROS. In vitro inhibition experiments confirmed the fungicidal effect of MSN-PHS-AZOX on Botrytis cinerea, relying on external ROS. In vivo leaf experiments showcased the superior persistence of MSN-PHS-AZOX in compared to AZOX SC. Furthermore, MSN-PHS-AZOX exhibits favorable biosafety and lower toxicity to aquatic zebrafish compared to AZOX SC, with no adverse impact on cucumber leaf growth. These findings suggest the potential application of this ROS-responsive nano fungicide in managing plant disease in agricultural fields.