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Abstract Background Colorectal cancer (CRC) is a prevalent malignancy with high mortality and morbidity rates. Although the significant efficacy of immunotherapy is well established, it is only beneficial for a limited number of individuals with CRC. Methods Differentially expressed immune-related genes (DE-IRGs) were retrieved from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and ImmPort databases. A prognostic signature comprising DE-IRGs was developed using univariate, LASSO, and multivariate Cox regression analyses. A nomogram integrating the independent prognostic factors was also developed. CIBERSORT was used to assess immune cell infiltration (ICI). Furthermore, wound-healing, colony formation, migration, and invasion assays were performed to study the involvement of ACTG1 in CRC. Results A signature including six DE-IRGs was developed. The overall survival (OS) rate was accurately estimated for TCGA and GSE38832 cohorts. The risk score (RS) of the signature was an independent factor for OS. Moreover, a nomogram encompassing age, RS, and pathological T stage accurately predicted the long-term OS probability of individuals with CRC. The high-risk group had an elevated proportion of patients treated with ICIs, including native B cells, relative to the low-risk group. Additionally, ACTG1 expression was upregulated, which supported the proliferation, migration, and invasion abilities of CRC cells. Conclusions An immune-related prognostic signature was developed for predicting OS and for determining the immune status of individuals with CRC. The present study provides new insights into accurate immunotherapy for individuals with CRC. Moreover, ACTG1 may serve as a new immune biomarker.

ABSTRACT Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by social communication deficiencies and stereotypic behaviors influenced by hereditary and/or environmental risk factors. There are currently no approved medications for treating the core symptoms of ASD. Human fecal microbiota transplantation (FMT) has emerged as a potential intervention to improve autistic symptoms, but the underlying mechanisms are not fully understood. In this study, we evaluated the effects of human-derived FMT on behavioral and multi-omics profiles of the BTBR mice, an established model for ASD. FMT effectively alleviated the social deficits in the BTBR mice and normalized their distinct plasma metabolic profile, notably reducing the elevated long-chain acylcarnitines. Integrative analysis linked these phenotypic changes to specific Bacteroides species and vitamin B6 metabolism. Indeed, vitamin B6 supplementation improved the social behaviors in BTBR mice. Collectively, these findings shed new light on the interplay between FMT and vitamin B6 metabolism and revealed a potential mechanism underlying the therapeutic role of FMT in ASD.IMPORTANCEAccumulating evidence supports the beneficial effects of human fecal microbiota transplantation (FMT) on symptoms associated with autism spectrum disorder (ASD). However, the precise mechanism by which FMT induces a shift in the microbiota and leads to symptom improvement remains incompletely understood. This study integrated data from colon-content metagenomics, colon-content metabolomics, and plasma metabolomics to investigate the effects of FMT treatment on the BTBR mouse model for ASD. The analysis linked the amelioration of social deficits following FMT treatment to the restoration of mitochondrial function and the modulation of vitamin B6 metabolism. Bacterial species and compounds with beneficial roles in vitamin B6 metabolism and mitochondrial function may further contribute to improving FMT products and designing novel therapies for ASD treatment.

Abstract Aqueous zinc‐ion batteries (ZIBs) have attracted extensive interest for the next‐generation batteries, which, however, are facing great challenges due to the poor reversibility of zinc (Zn) anodes and side reactions of water decomposition. Herein, we demonstrated a strategy that the solvation sheath of Zn ions could be facilely regulated by supramolecular coordination chemistry by adding small amounts of cyclodextrins (CDs) and, hence, inhibited the side reactions and side products, widened the electrochemical window, facilitated the homogenous deposition of Zn ions, refined the Zn grains, and enhanced the stability of Zn anodes. Importantly, we demonstrated that compared with α‐ and β‐CD, the γ‐CD showed the best regulation effect of the solvation sheath of Zn ions either at the same molar ratio or at the same mass concentration, which could be ascribed to their difference in supramolecular coordination chemistry and the strongest interaction of γ‐CD with Zn ions. As a result, with γ‐CD, the Zn//Zn symmetric cells showed ultrahigh stability with a cycling lifespan of over 2400 h at a current density of 1 mA/cm2. These results highlight the regulation of solvation sheath by supramolecular coordination chemistry for highly stable Zn anodes and pave a new way to realize high‐performance ZIBs.

Accelerated urbanization has exacerbated the urban heat island phenomenon, and urban forests have been recognized as an effective strategy for modulating thermal environments. Nevertheless, there remains a dearth of systematic investigations into the nonlinear associations between the detailed spatial configurations of urban forests and thermal conditions. We proposed a deep learning-based approach to extract forest data, utilizing multisource high-resolution remote sensing data with relative radiometric correction. Subsequently, we employed deep neural networks (DNNs) to quantify the linkages between urban forest landscape patterns and land surface temperature (LST) in summer and winter across Fuzhou, Xiamen, and Zhangzhou in Fujian Province, China. Our findings indicate the following: (1) Our extraction approach outperforms DeepLabv3+, FCN_8S, and SegNet in terms of extraction precision and adaptability, achieving an overall accuracy (OA) of 87.57%; furthermore, the implementation of relative radiometric correction enhances both the extraction precision and model generalizability, improving OA by 0.05%. (2) Geographic and seasonal differences influence the urban forests’ cooling effects, with more pronounced cooling in summer, particularly in Zhangzhou. (3) The significance of forest landscape composition and configuration in affecting the thermal environment varies seasonally; landscape configuration plays a more pivotal role in modulating surface temperatures across the three cities, with a more critical role in winter than in summer. (4) Seasonal and city-specific variations in forest spatial patterns influence LST. Adopting the appropriate forest structures tailored to specific seasons, cities, and scales can optimize cooling effects. These results offer quantitative insights into urban heat island dynamics and carry significant implications for urban planning strategies.

In this article, a distributed charging strategy problem for plug-in electric vehicles (PEVs) with feeder constraints based on generalized Nash equilibria (GNE) in a novel smart charging station (SCS) is investigated. The purpose is to coordinate the charging strategies of all PEVs in SCS to minimize the energy cost of SCS. Therefore, we build a non-cooperative game framework and propose a new price-driven charging control game by considering the overload constraint of the assigned feeder, where each PEV minimizes the fees it pays to satisfy its optimal charging strategy. On this basis, the existence of GNE is given. Furthermore, we employ a distributed algorithm based on forward–backward operator splitting methods to find the GNE. The effectiveness of the employed algorithm is verified by the final simulation results.

Abstract Background Neck pain is widespread among students in healthcare-related fields. Although neck pain is more prevalent in females, since most research involves mixed-sex samples we know very little about sex differences in contributors to neck pain. Thus, this study sought to explore sex differences in the risk factors for neck pain in this high-risk population. Methods This cross-sectional study was conducted in China in 2021 and included a sample of 1921 undergraduate healthcare students (693 males, 1228 females) from 7 health professional schools at Fujian Medical University. We collected data on neck pain symptoms, demographics, behavioral and psychological factors. Multiple regression analysis was conducted to examine sex differences in the risk factors of neck pain. Results The overall prevalence of neck pain was 41.6% with female students having a higher prevalence than male students (44.4% vs. 36.7%, respectively). The adjusted analyses showed that self-study time ≥ 6 h/day (OR = 1.44, 95% CI:1.13-1.83), flexed neck posture >20 degrees (OR = 2.19, 95% CI: 1.28-3.74), static duration posture >2 h (OR = 1.42, 95% CI: 1.02-1.97), and psychological distress (high: OR = 2.04, 95% CI:1.42-2.94; very high: OR = 2.50, 95% CI:1.57-3.74; respectively) were independent factors for neck pain in females. Among males, self-study time ≥ 6 h/day (OR = 1.43, 95% CI: 1.02-2.01) and psychological distress (moderate: OR = 2.04, 95% CI:1.28-3.25; high: OR = 2.37, 95% CI:1.49-3.79; very high: OR = 2.97, 95% CI:1.75-5.02; respectively) were significant risk factors for neck pain. Conclusions These findings suggest that the risk profiles of neck pain differ between females and males. The modifiable risk factors for neck pain, such as prolonged self-study time and elevated psychological distress, as well as poor posture among females, could be targeted through health promotion interventions in university settings.

BackgroundSmoking in patients with Schizophrenia is more common than in the general population. Varenicline, a partial agonist at α4β2 nicotinic acetylcholine receptors, is an effective smoking cessation pharmacotherapy in patients with Schizophrenia. However, its effects on the serum levels of antipsychotics in Schizophrenia are understudied. This study investigated the impact of smoking cessation with varenicline on the serum concentration of olanzapine in patients with Schizophrenia.MethodsAdult smokers with Schizophrenia were enrolled in a 12-week course of varenicline and placebo for smoking cessation. The serum concentration of olanzapine was measured at baseline and weeks 1, 2, 4, 8, and 12. Data were analyzed with the generalized additive mixed model.ResultsDuring the 12-week study, the results indicated that olanzapine concentrations increased nonlinearly in the varenicline and placebo groups. Threshold effect analysis suggested that the olanzapine concentrations increased over time until the turning point (week 4). However, there was no significant difference between the two treatment groups.ConclusionVarenicline showed safety and efficacy in smoking cessation in people with Schizophrenia.

This paper proposes a charging strategy for plug-in electric vehicles (PEVs) in a smart charging station (SCS) that considers load constraints and time anxieties. Due to the rapidly growing load demand of PEVs and the load capacity investments in infrastructure, PEV charging needs to be subject to overload limits, beyond which failures can occur. The time anxiety is presented to address some of the uncertainties that may arise while charging PEVs. Under an aggregative game framework, this paper constructs a price-driven charging model to minimize costs by choosing the optimal charging strategy. Meanwhile, since the driver information is an aggregated item in the PEV cost function, the drivers’ privacy can be protected. Then, a distributed reflected forward–backward (RFB) splitting method is developed to search for the generalized Nash equilibria (GNE) of the game. The convergence of the proposed algorithm and the effectiveness of the charging strategy are verified by the detailed simulation and results.

Abstract Background LINC00426 is a newly identified long non-coding RNA (lncRNA) with unacknowledged biological roles. Here we set out to characterize the expression status of LINC00426 in osteosarcoma and understand its mechanistic involvement in incidence of doxorubicin (Dox) resistance. Methods The relative expression of LINC00426 and miR-4319 was determined by real-time PCR. Cell viability and proliferation in response to LINC00426 silencing or miR-4319 over-expression was measured with CCK-8 kit and colony formation assay, respectively. The direct association between LINC00426 and miR-4319 was analyzed by pulldown assay with biotin-labelled probes. Results LINC00426 was significantly up-regulated in Dox-resistant osteosarcoma (OS) both in vitro and in vivo, which intimately associated with unfavorable prognosis. SiRNA-mediated knockdown of LINC00426 remarkably compromised cell viability and proliferation in Dox-resistant OS cells, which accompanied with decrease of IC50 and activation of caspase-3. We further predicted and validated the regulatory effects of miR-4319 on LINC00426 expression. Simultaneously, we provided evidences in support of direct binding between LINC00426 and miR-4319 by pulldown assay. Reciprocally negative regulation was observed between LINC00426 and miR-4319 each other. Conclusion Ectopic introduction of miR-4319 significantly surmounted the Dox resistance in OS cells, while miR-4319 inhibition in LINC00426-deficient cells greatly restore this phenotype. We uncovered the important contribution of LINC00426/miR-4319 to Dox resistance in osteosarcoma. Reviewers This article was reviewed by Bo Liang and Sinan Zhu.

Brain ischemia has been associated with deficits in neural oscillations. Here in an animal model, the authors show that modulation of low-gamma oscillations using a light flicker can restore low gamma oscillations and protect ischemic neurons.

As plug-in electric vehicles (PEVs) become more and more popular, there is a growing interest in the management of their charging power. Many models exist nowadays to manage the charging of plug-in electric vehicles, and it is important that these models are implemented in a better way. This paper investigates a price-driven charging management model in which all plug-in electric vehicles are informed of the charging strategies of neighboring plug-in electric vehicles and adjust their own strategies to minimize the cost, while an aggregator determines the unit price based on overall electricity consumption to coordinate the charging strategies of the plug-in electric vehicles. In this article, we used an asynchronous distributed generalized Nash game algorithm to investigate a charging management model for plug-in electric vehicles in a smart charging station (SCS). In a charging management model, we need to consider constraints on the charge and discharge rates of plug-in electric vehicles, the battery capacity, the amount of charge per plug-in electric vehicle, and the maximum electrical load that the whole system can allow. Meeting the constraints of plug-in electric vehicles and smart charging stations, the model coordinates the charging strategy of each plug-in electric vehicle to ultimately reduce the cost of smart charging stations, which is the cost that the smart charging station should pay to the higher-level power supply facility. To the best of our knowledge, this algorithm used in this paper has not been used to solve this model, and it has better performance than the generalized Nash equilibria (GNE) seeking algorithm originally used for this model, which is called a fast alternating direction multiplier method (Fast-ADMM). In the simulation results, the asynchronous algorithm we used showed a correlation error of 0.0076 at the 713th iteration, compared to 0.0087 for the synchronous algorithm used for comparison, and the cost of the smart charging station was reduced to USD 4800.951 after coordination using the asynchronous algorithm, which was also satisfactory. We used an asynchronous algorithm to better implement a plug-in electric vehicle charging management model; this also demonstrates the potential advantages of using an asynchronous algorithm for solving the charging management model for plug-in electric vehicles.

Alzheimer's disease (AD) treatment represents one of the largest unmet medical needs. Developing small molecules targeting Aβ aggregation is an effective approach to prevent and treat AD. Here, we show that gallic acid (GA), a naturally occurring polyphenolic small molecule rich in grape seeds and fruits, has the capacity to alleviate cognitive decline of APP/PS1 transgenic mouse through reduction of Aβ1–42 aggregation and neurotoxicity. Oral administration of GA not only improved the spatial reference memory and spatial working memory of 4-month-old APP/PS1 mice, but also significantly reduced the more severe deficits developed in the 9-month-old APP/PS1 mice in terms of spatial learning, reference memory, short-term recognition and spatial working memory. The hippocampal long-term-potentiation (LTP) was also significantly elevated in the GA-treated 9-month-old APP/PS1 mice with increased expression of synaptic marker proteins. Evidence from atomic force microscopy (AFM), dynamic light scattering (DLS) and thioflavin T (ThT) fluorescence densitometry analyses showed that GA significantly reduces Aβ1–42 aggregation both in vitro and in vivo. Further, pre-incubating GA with oligomeric Aβ1–42 reduced Aβ1–42-mediated intracellular calcium influx and neurotoxicity. Molecular docking studies identified that the 3,4,5-hydroxyle groups of GA were essential in noncovalently stabilizing GA binding to the Lys28-Ala42 salt bridge and the –COOH group is critical for disrupting the salt bridge of Aβ1–42. The predicated covalent interaction through Schiff-base formation between the carbonyl group of the oxidized product and ε-amino group of Lys16 is also critical for the disruption of Aβ1–42 S-shaped triple-β-motif and toxicity. Together, these studies demonstrated that GA can be further developed as a drug to treat AD through disrupting the formation of Aβ1–42 aggregation.

The mixed Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), Masson’s pine (Pinus massoniana Lamb.), and hardwood forest is a major forest type in China and of national and international importance in terms of its provision of both timber and ecosystem services. However, over-harvesting has threatened its long-term productivity and sustainability. We examined the impacts of timber harvesting intensity on soil physical and chemical properties 10 and 15 years after cutting using the research plots established with a randomized block design. We considered five treatments, including clear cutting and low (13.0% removal of growing stock volume), medium (29.1%), high (45.8%), and extra-high (67.1) intensities of selective cutting with non-cutting as the control. The impact on overall soil properties derived from principal component analysis showed increasing with a rise in cutting intensity, and the most critical impact was on soil nutrients, P and K in particular. Soil nutrient loss associated with timber harvesting even at a low cutting intensity could lead to nutrient deficits in this forest although most of the soil physical properties could be recovered under the low and medium intensities of cutting. These results indicate that clear cutting and the selective cutting of extra-high and high intensities should be avoided in this type of forest in the region.

Background: Patients with schizophrenia frequently experience issues such as poor sleep quality, anxiety, and depression. White sound has been identified as a potential therapeutic strategy to enhance sleep quality and alleviate negative emotions. This study aimed to investigate the effectiveness of white sound in improving sleep quality, anxiety, and depression among patients with schizophrenia. Materials and Methods: This retrospective analysis included clinical data from 212 patients with schizophrenia divided into two groups based on their treatment approach. Group C (control, without white sound, n =106) received standard pharmacological treatments, while group W (white sound, n =106) was exposed to white sound (40-50 dB) for 2 hours nightly at 9:00 pm. All patients were assessed using the Pittsburgh Sleep Quality Index (PSQI), Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), and Positive and Negative Syndrome Scale (PANSS) before and after 12 weeks of intervention. Results: After 12 weeks, group W showed significant improvements in sleep latency, sleep efficiency, and overall PSQI scores compared to group C (P < 0.05). Furthermore, the HAMD and HAMA scores were significantly lower in group W (P < 0.05), indicating reduced levels of anxiety and depression. The negative symptoms score was significantly lower in group W (P < 0.05) after treatment. Conclusion: White sound shows promise in improving sleep quality, and alleviating anxiety and depression in patients with schizophrenia. [ABSTRACT FROM AUTHOR]