ACAP3 negatively regulated by HDAC2 inhibits the malignant development of papillary thyroid carcinoma cells.

ArfGAP with coiled-coil, ankyrin repeat and PH domains 3 (ACAP3) level has been confirmed to be downregulated in papillary thyroid carcinoma (PTC). Histone deacetylase inhibitors (HDACIs) have therapeutic effects on PTC. Accordingly, this study probed into the potential relation of histone deacetylase 2 (HDAC2) and ACAP3 in PTC. Expressions of ACAP3 and HDAC2 in PTC were investigated by quantitative real-time polymerase chain reaction (qRT-PCR). The relationship between HDAC2 and ACAP3 was predicted by Pearson analysis. Cell functional assays (cell counting kit-8, transwell, wound healing and flow cytometry assays) and rescue assay were carried out to determine the effects of HDAC2/ACAP3 axis on biological behaviors of PTC cells. Expressions of apoptosis-, epithelial-mesenchymal transition-, Protein Kinase B (AKT)-, and P53-related proteins were measured by Western blot. ACAP3 level was downregulated in PTC tissues and cells. ACAP3 overexpression (oe-ACAP3) suppressed viability, proliferation, migration and invasion of PTC cells, facilitated apoptosis, downregulated the expressions of Protein Kinase B (Bcl-2) and N-cadherin, upregulated the expressions of Bcl-2 associated protein X (Bax) and E-cadherin, diminished the p-AKT/AKT ratio and elevated the p-p53/p53 ratio; however, ACAP3 silencing or HDAC2 overexpression (oe-HDAC2) did the opposite. HDAC2 negatively correlated with ACAP3. The tumor-suppressing effect of oe-ACAP3 in PTC was reversed by oe-HDAC2. Collectively, ACAP3 negatively regulated by HDAC2 suppresses the proliferation and metastasis while facilitating apoptosis of PTC cells.

Frequency-Aware Divide-and-Conquer for Efficient Real Noise Removal.

Deep-learning-based approaches have achieved remarkable progress for complex real scenario denoising, yet their accuracy-efficiency tradeoff is still understudied, particularly critical for mobile devices. As real noise is unevenly distributed relative to underlay signals in different frequency bands, we introduce a frequency-aware divide-and-conquer strategy to develop a frequency-aware denoising network (FADN). FADN is materialized by stacking frequency-aware denoising blocks (FADBs), in which a denoised image is progressively predicted by a series of frequency-aware noise dividing and conquering operations. For noise dividing, FADBs decompose the noisy and clean image pairs into low-and high-frequency representations via a wavelet transform (WT) followed by an invertible network and recover the final denoised image by integrating the denoised information from different frequency bands. For noise conquering, the separated low-frequency representation of the noisy image is kept as clean as possible by the supervision of the clean counterpart, while the high-frequency representation combining the estimated residual from the successive FADB is purified under the corresponding accompanied supervision for residual compensation. Since our FADN progressively and pertinently denoises from frequency bands, the accuracy-efficiency tradeoff can be controlled as a requirement by the number of FADBs. Experimental results on the SIDD, DND, and NAM datasets show that our FADN outperforms the state-of-the-art methods by improving the peak signal-to-noise ratio (PSNR) and decreasing the model parameters. The code is released at https://github.com/NekoDaiSiki/FADN.

Two laser-assisted hatching methods of embryos in ART: a systematic review and meta-analysis.

BACKGROUND: Laser-assisted hatching (LAH) stands as the predominant technique for removing the zona pellucida (ZP) in embryos, primarily consisting of two methods: drilling laser-assisted hatching (D-LAH) and thinning laser-assisted hatching (T-LAH). Presently, both methods have limitations, and their comparative efficacy for embryo implantation and clinical pregnancy remains uncertain. AIM: Evaluate the impact of D-LAH and T-LAH on clinical pregnancy rates within assisted reproductive technology (ART). METHODS: We systematically searched electronic databases including PubMed, Web of Science, and Cochrane Library until July 20, 2022. This study encompassed observational studies and randomized controlled trials (RCTs). A 95% confidence interval (CI) was utilized for assessing the risk ratio (RR) of pregnancy outcomes. The level of heterogeneity was measured using I2 statistics, considering a value exceeding 50% as indicative of substantial heterogeneity. RESULTS: The meta-analysis scrutinized 9 studies involving 2405 clinical pregnancies from D-LAH and 2239 from T-LAH. Findings suggested no considerable variation in the clinical pregnancy rates between the two techniques (RR = 0.93, 95% CI: 0.79-1.10, I2 = 71%, P = 0.41). Subgroup analyses also revealed no substantial differences. However, D-LAH exhibited a notably higher occurrence of singleton pregnancies compared to T-LAH (RR = 2.28, 95% CI: 1.08-4.82, I2 = 89%, P = 0.03). There were no noteworthy distinctions observed in other secondary outcomes encompassing implantation rate, multiple pregnancies, ongoing pregnancy, miscarriage, premature birth, and live birth. CONCLUSION: Both the primary findings and subgroup analyses showed no marked variance in clinical pregnancy rates between D-LAH and T-LAH. Therefore, patients with varying conditions should select their preferred LAH technique after assessing their individual situation. However, due to the restricted number of studies involved, accurately gauging the influence of these laser techniques on clinical outcomes is challenging, necessitating further RCTs and high-quality studies to enhance the success rate of ART. TRIAL REGISTRATION: PROSPERO: CRD42022347066.

Multi-Classification and Tree-Based Ensemble Network for the Intrusion Detection System in the Internet of Vehicles.

The Internet of Vehicles(IoV) employs vehicle-to-everything (V2X) technology to establish intricate interconnections among the Internet, the IoT network, and the Vehicle Networks (IVNs), forming a complex vehicle communication network. However, the vehicle communication network is very vulnerable to attacks. The implementation of an intrusion detection system (IDS) emerges as an essential requisite to ensure the security of in-vehicle/inter-vehicle communication in IoV. Within this context, the imbalanced nature of network traffic data and the diversity of network attacks stand as pivotal factors in IDS performance. On the one hand, network traffic data often heavily suffer from data imbalance, which impairs the detection performance. To address this issue, this paper employs a hybrid approach combining the Synthetic Minority Over-sampling Technique (SMOTE) and RandomUnderSampler to achieve a balanced class distribution. On the other hand, the diversity of network attacks constitutes another significant factor contributing to poor intrusion detection model performance. Most current machine learning-based IDSs mainly perform binary classification, while poorly dealing with multiclass classification. This paper proposes an adaptive tree-based ensemble network as the intrusion detection engine for the IDS in IoV. This engine employs a deep-layer structure, wherein diverse ML models are stacked as layers and are interconnected in a cascading manner, which enables accurate and efficient multiclass classification, facilitating the precise identification of diverse network attacks. Moreover, a machine learning-based approach is used for feature selection to reduce feature dimensionality, substantially alleviating the computational overhead. Finally, we evaluate the proposed IDS performance on various cyber-attacks from the in-vehicle and external networks in IoV by using the network intrusion detection dataset CICIDS2017 and the vehicle security dataset Car-Hacking. The experimental results demonstrate remarkable performance, with an F1-score of 0.965 on the CICIDS2017 dataset and an F1-score of 0.9999 on the Car-Hacking dataset. These scores demonstrate that our IDS can achieve efficient and precise multiclass classification. This research provides a valuable reference for ensuring the cybersecurity of IoV.

A task-level emergency experience reuse method for freeway accidents onsite disposal with policy distilled reinforcement learning.

A large number of freeway accident disposals are well-recorded by accident reports and surveillance videos, but it is not easy to get the emergency experience reused from past recorded accidents. To reuse emergency experience for better emergency decision-making, this paper proposed a knowledge-based experience transfer method to transfer task-level freeway accident disposal experience via multi-agent reinforcement learning algorithm with policy distillation. First, the Markov decision process is used to simulate the emergency decision-making process of multi-type freeway accident scene at the task level. Then, an adaptive knowledge transfer method named policy distilled multi-agent deep deterministic policy gradient (PD-MADDPG) algorithm is proposed to reuse experience from past freeway accident records to current accidents for fast decision-making and optimal onsite disposal. The performance of the proposed algorithm is evaluated on instantiated cases of freeway accidents that occurred on the freeway in Shaanxi Province, China. Aside from achieving better emergency decisions performance than various typical decision-making methods, the result shows decision maker with transferred knowledge owns 65.22%, 11.37%, 9.23%, 7.76% and 1.71% higher average reward than those without in the five studied cases, respectively. Indicating that the emergency experience transferred from past accidents contributes to fast emergency decision-making and optimal accident onsite disposal.

Reward-Adaptive Reinforcement Learning: Dynamic Policy Gradient Optimization for Bipedal Locomotion.

Controlling a non-statically bipedal robot is challenging due to the complex dynamics and multi-criterion optimization involved. Recent works have demonstrated the effectiveness of deep reinforcement learning (DRL) for simulation and physical robots. In these methods, the rewards from different criteria are normally summed to learn a scalar function. However, a scalar is less informative and may be insufficient to derive effective information for each reward channel from the complex hybrid rewards. In this work, we propose a novel reward-adaptive reinforcement learning method for biped locomotion, allowing the control policy to be simultaneously optimized by multiple criteria using a dynamic mechanism. The proposed method applies a multi-head critic to learn a separate value function for each reward component, leading to hybrid policy gradients. We further propose dynamic weight, allowing each component to optimize the policy with different priorities. This hybrid and dynamic policy gradient (HDPG) design makes the agent learn more efficiently. We show that the proposed method outperforms summed-up-reward approaches and is able to transfer to physical robots. The MuJoCo results further demonstrate the effectiveness and generalization of HDPG.

Multivariate genome-wide association study of depression, cognition, and memory phenotypes and validation analysis identify 12 cross-ethnic variants.

To date, little is known about the pleiotropic genetic variants among depression, cognition, and memory. The current research aimed to identify the potential pleiotropic single nucleotide polymorphisms (SNPs), genes, and pathways of the three phenotypes by conducting a multivariate genome-wide association study and an additional pleiotropy analysis among Chinese individuals and further validate the top variants in the UK Biobank (UKB). In the discovery phase, the participants were 139 pairs of dizygotic twins from the Qingdao Twins Registry. The genome-wide efficient mixed-model analysis identified 164 SNPs reaching suggestive significance (P < 1 × 10-5). Among them, rs3967317 (P = 1.21 × 10-8) exceeded the genome-wide significance level (P < 5 × 10-8) and was also demonstrated to be associated with depression and memory in pleiotropy analysis, followed by rs9863698, rs3967316, and rs9261381 (P = 7.80 × 10-8-5.68 × 10-7), which were associated with all three phenotypes. After imputation, a total of 457 SNPs reached suggestive significance. The top SNP chr6:24597173 was located in the KIAA0319 gene, which had biased expression in brain tissues. Genes and pathways related to metabolism, immunity, and neuronal systems demonstrated nominal significance (P < 0.05) in gene-based and pathway enrichment analyses. In the validation phase, 12 of the abovementioned SNPs reached the nominal significance level (P < 0.05) in the UKB. Among them, three SNPs were located in the KIAA0319 gene, and four SNPs were identified as significant expression quantitative trait loci in brain tissues. These findings may provide evidence for pleiotropic variants among depression, cognition, and memory and clues for further exploring the shared genetic pathogenesis of depression with Alzheimer's disease.

Global Bibliometric Developments on Solid Waste Recycling in Concrete Construction Engineering.

The precise and visual analysis of solid waste recycling in concrete construction engineering is critical for the development of ecological civilization and for the secure supply of resources. This research makes a bibliometric analysis of the solid waste application in concrete construction engineering from 2000 to 2021 based on the Web of Science. The global bibliometric status, current research focus and future directions were used to indicate the global development of solid waste recycling in concrete construction engineering. The most reused solid wastes and most solid waste productive regions were concluded with this bibliometric analysis. China is far ahead of other countries in solid waste recycling in all aspects and heavy metal is one of the most prominent solid waste themes in China. By analyzing the most studied solid waste, fly ash appears to be the most popular and is widely used; half of the top ten-cited papers are correlated with it.

Involvement of the fatty acid-binding protein in the growth of Schistosoma japonicum schistosomula.

This study aimed to explore the effect and mechanism underlying the role of the Schistosoma japonicum antigen of fatty acid-binding protein (SjFABP) on the growth of the schistosomula. SjFABP levels were evaluated by quantitative real-time polymerase chain reaction of samples of mice infected with S. japonicum; SjFABP was expressed and its levels gradually increased during all stages of S. japonicum schistosomula, including on 3, 10, 14, and 21 days of the growth process. Immunohistochemistry results demonstrated that SjFABP was distributed in the parenchyma, especially in the digestive tract of the S. japonicum schistosomula. RNA interference resulted in more than 60% knockdown of SjFABP leading to a reduction in length, volume, width, and area of the schistosomula as compared to control samples, as determined by light microscopy. Terminal deoxynucleotidyl transferase dUTP nick-end labeling detection further suggested that SjFABP knockdown resulted in increased apoptosis of schistosomes. Taken together, these results suggest that SjFABP may be related to the growth and survival of S. japonicum schistosomula, thereby representing a potential target for the treatment of schistosomiasis.

The effect of regulatory T cells in Schistosoma-mediated protection against type 2 diabetes.

In western societies, the prevalence of type 2 diabetes (T2D) is related to the hygiene hypothesis, which implies that reduced exposure to infectious factors results in a loss of the immune stimulation necessary to form the immune system during development. In fact, it has been reported that parasites, such as Schistosoma, can improve or prevent the development of T2D, which may be related to the activity of immune cells, including regulatory T cells (Tregs). Hence, Schistosoma, Tregs, and T2D share a close relationship. Schistosoma infection and the molecules released can lead to an increase in Tregs, which play an important role in the suppression of T2D. In this review, we provide an overview of the role of Tregs in the response to Schistosoma infection and the protective mechanism of Schistosoma-related molecular products against T2D.

Device-Free Human Identification Using Behavior Signatures in WiFi Sensing.

Wireless sensing can be used for human identification by mining and quantifying individual behavior effects on wireless signal propagation. This work proposes a novel device-free biometric (DFB) system, WirelessID, that explores the joint human fine-grained behavior and body physical signatures embedded in channel state information (CSI) by extracting spatiotemporal features. In addition, the signal fluctuations corresponding to different parts of the body contribute differently to the identification performance. Inspired by the success of the attention mechanism in computer vision (CV), thus, to extract more robust features, we introduce the spatiotemporal attention function into our system. To evaluate the performance, commercial WiFi devices are used for prototyping WirelessID in a real laboratory environment with an average accuracy of 93.14% and a best accuracy of 97.72% for five individuals.

Deductive Reinforcement Learning for Visual Autonomous Urban Driving Navigation.

Existing deep reinforcement learning (RL) are devoted to research applications on video games, e.g., The Open Racing Car Simulator (TORCS) and Atari games. However, it remains under-explored for vision-based autonomous urban driving navigation (VB-AUDN). VB-AUDN requires a sophisticated agent working safely in structured, changing, and unpredictable environments; otherwise, inappropriate operations may lead to irreversible or catastrophic damages. In this work, we propose a deductive RL (DeRL) to address this challenge. A deduction reasoner (DR) is introduced to endow the agent with ability to foresee the future and to promote policy learning. Specifically, DR first predicts future transitions through a parameterized environment model. Then, DR conducts self-assessment at the predicted trajectory to perceive the consequences of current policy resulting in a more reliable decision-making process. Additionally, a semantic encoder module (SEM) is designed to extract compact driving representation from the raw images, which is robust to the changes of the environment. Extensive experimental results demonstrate that DeRL outperforms the state-of-the-art model-free RL approaches on the public CAR Learning to Act (CARLA) benchmark and presents a superior performance on success rate and driving safety for goal-directed navigation.

Association of Dietary Vitamin D Intake, Serum 25(OH)D3, 25(OH)D2 with Cognitive Performance in the Elderly.

BACKGROUND: As life expectancy increases, cognitive performance decline in the elderly has become one of the major global challenges. We aimed to evaluate the association of dietary vitamin D (VD), serum 25-hydroxyvitamin D3 (25(OH)D3), 25-hydroxyvitamin D2 (25(OH)D2), and total 25-hydroxyvitamin (25(OH)D) concentration with cognitive performance in older Americans. METHODS: The data from the National Health and Nutrition Examination Survey (NHANES), 2011-2014 was used. The cognitive performance was assessed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning sub-test, Animal Fluency test, and Digit Symbol Substitution Test (DSST). A binary logistic regression model was applied to evaluate the association between VD and cognitive performance, and restricted cubic spline model was adopted to evaluate the dose-response relationship. RESULTS: While comparing to the lowest dietary VD intake group, the multivariate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of the highest dietary VD intake group were 0.51 (0.36-0.72) for the Animal Fluency test score and 0.45 (0.31-0.66) for DSST score, respectively; and those of serum total 25(OH)D and 25(OH)D3 concentration were 0.68 (0.47-0.97) and 0.62 (0.44-0.86) for DSST score. L-shaped relationships were identified for dietary VD intake, serum total 25(OH)D and 25(OH)D3 concentration with cognition performance. The associations between dietary VD intake, serum total 25(OH)D and cognitive performance were non-significant when stratified by gender. CONCLUSIONS: The study indicates that dietary VD intake, serum total 25(OH)D and 25(OH)D3 concentration were positively associated with cognitive performance. Further studies are needed to clarify the possible effects of dietary VD intake and serum 25(OH)D2, 25(OH)D3 on cognitive performance.

EFFECT OF ADENYLATE KINASE 1 ON THE GROWTH AND DEVELOPMENT OF SCHISTOSOMA JAPONICUM SCHISTOSOMULUM.

We investigated the effect of Schistosoma japonicum adenylate kinase 1 (Sjak1) on the growth and development of schistosomula. Quantitative real-time PCR showed that Sjak1 mRNA was expressed in 3-, 10-, 14-, 18-, and 21-day-old schistosomula, and its levels increased gradually with the development of S. japonicum. Using immunohistochemical techniques, ak1 protein was found to be mainly distributed in the tegument and some parenchymal tissues of the schistosomula. Double-stranded RNA-mediated knockdowns of ak1 decreased ak1 mRNA transcripts by more than 90%, and western blot results showed that expression of ak1 protein was decreased by 66%. Scanning electron microscopy following the RNA-mediated ak1 knockdown showed that the sensory papillae did not develop. Transmission electron microscopy showed a lower mean thickness of the tegument in the Sjak1 interference group than in the negative control group. Terminal deoxynucleotidyl transferase dUTP nick-end labeling suggested higher apoptosis in the interference group than the negative control group. These results showed that ak1 may be involved in the growth and development of S. japonicum schistosomula and especially in the development of the integument. Consequently, ak1 may be a potential target in developing prevention methods for schistosomiasis in the future.

Association between milk and dairy product intake and the risk of dental caries in children and adolescents: NHANES 2011-2016.

BACKGROUND AND OBJECTIVES: To date, few studies have comprehensively explored the associations between milk and dairy product intake and dental caries. Therefore, this study aimed to simultaneously assess the associations between whole milk, low-fat milk, skim milk, yogurt, milk desserts, cheese, creams, and total fluid milk intake and the risk of dental caries in children and adolescents. METHODS AND STUDY DESIGN: Data were from the National Health and Nutrition Examination Survey (NHANES) 2011-2016. Two 24-hour dietary recall interviews measured dietary milk and dairy product intake. Primary teeth caries was diagnosed by the dfs (decayed or filled primary tooth surfaces) index, and permanent teeth caries was diagnosed by the DMFS (decayed, missing, or filled permanent tooth surfaces) index. We used logistic regression to explore the associations between milk and dairy product intake and the risk of dental caries. RESULTS: A total of 6885 individuals aged 2-17 years were included in this study. In the fully adjusted model, the odds ratios (95% confidence intervals) of dental caries were 0.66 (0.47-0.93) for intake ≥123 g/day of yogurt and 0.82 (0.69-0.98) for intake <22.6 g/day of cheese, as compared with non-consumers. CONCLUSIONS: Our study indicates that high yogurt and low cheese intake were associated with a decreased risk of dental caries among American children and adolescents. These findings may be applied to update and supplement the evidence that informs public health policies on milk and dairy products and the prevention of dental caries.

The effects of helminth infections against type 2 diabetes.

Type 2 diabetes mellitus (T2D) is a prevalent inflammation-related disease characterized by insulin resistance and elevated blood glucose levels. The high incidence rate of T2D in Western societies may be due to environmental conditions, including reduced worm exposure. In human and animal models, some helminths, such as Schistosoma, Nippostrongylus, Strongyloides, and Heligmosomoides, and their products reportedly ameliorate or prevent T2D progression. T2D induces adaptive immune pathways involved in the inhibition of type 1 immune responses, promotion of type 2 immune responses, and expansion of regulatory T cells and innate immune cells, such as macrophages, eosinophils, and group 2 innate lymphoid cells. Among immune cells expanded in T2DM, type 2 immune cells and macrophages are the most important and may have synergistic effects. The stimulation of host immunity by helminth infections also promotes interactions between the innate and adaptive immune systems. In this paper, we provide a comprehensive review of intestinal helminths' protective effects against T2D.

Schisandrin B Protects against Acute Ethanol-Induced Cardiac Injury by Downregulating Autophagy via the NOX4/ROS Pathway.

INTRODUCTION: Although oxidative stress has been demonstrated to mediate acute ethanol-induced changes in autophagy in the heart, the precise mechanism behind redox regulation in acute ethanol heart disease remains largely unknown. METHODS: Wild-type C57BL/6 mice were intraperitoneally injected with ethanol (3 g/kg/day) for 3 consecutive days. The effects of ethanol on cultured primary cardiomyocytes and H9c2 myoblasts were also studied in vitro. Levels of autophagic flux, cardiac apoptosis and function, reactive oxygen species (ROS) accumulation, NOX4, and NOX2 were examined. The NOX4 gene was knocked down with NOX4 siRNA. RESULTS: In this study, we demonstrated that schisandrin B inhibited acute ethanol-induced autophagy and sequent apoptosis. In addition, schisandrin B treatment improved cardiac function in ethanol-treated mice. Furthermore, NOX4 protein expression was increased during acute ethanol exposure, and the upregulation of NOX4 was significantly inhibited by schisandrin B treatment. The knockdown of NOX4 prevented ROS accumulation, cell autophagy, and apoptosis. CONCLUSION: These results highlight that NOX4 is a critical mediator of ROS and elaborate the role of the NOX4/ROS axis in the effect of schisandrin B on autophagy and autophagy-mediated apoptosis in acute ethanol exposure, which suggests a therapeutic strategy for acute alcoholic cardiomyopathy.

Cooperative Adaptive Cruise Control and exhaust emission evaluation under heterogeneous connected vehicle network environment in urban city.

With the development of information communication and artificial intelligence, the ICV (intelligent connected vehicle) will inevitably play an important part in future urban transport system. In this paper, we study the car following behaviour under the heterogeneous ICV environment. The time to receive information varies from vehicle to vehicle, since the manual vehicles and autonomous vehicles co-exist on the road. By introducing time-varying lags function, a new car following model is proposed, and the cooperative control strategy of this model is studied. Based on Lyapunov function theory and linear matrix inequality (LMI) approach, the sufficient condition that the existence of the feedback controller is given, which makes the closed-loop system asymptotically stable under mixed traffic flow environment. That is to say, traffic congestion phenomenon under heterogeneous traffic flow can be effectively suppressed, and the feedback controller gain matrix can be obtained via solving linear matrix inequality. Finally, by simulation the method is verified effective in alleviating traffic congestions and reducing fuel consumption and exhaust emissions. It could be a useful reference to Cooperative Vehicle Infrastructure System and Smart City.

Associations of n-3, n-6 Fatty Acids Intakes and n-6:n-3 Ratio with the Risk of Depressive Symptoms: NHANES 2009-2016.

Many studies have explored the association between n-3 fatty acids and depression, but research on the associations of n-6 fatty acids and n-6:n-3 ratio with depression is more scarce, and the results are controversial. Therefore, we conducted this cross-sectional study to explore the associations of n-3 and n-6 fatty acid intakes and n-6:n-3 ratio with the risk of depressive symptoms using data from National Health and Nutrition Examination Survey (NHANES) 2009-2016. Dietary data on n-3 and n-6 fatty acids were obtained through two 24-h dietary recall interviews, and were adjusted by energy. Depressive symptoms were measured by PHQ-9 (nine-item Patient Health Questionnaire). We applied logistic regression and restricted cubic spline models to assess the relationships of n-3 and n-6 fatty acids intake and n-6:n-3 ratio with the risk of depressive symptoms. A total of 17,431 individuals over 18 years old were enrolled in this study. In the multivariate-adjusted model 2, compared with the lowest category, the highest odd ratios (ORs) with 95% confidence intervals (CIs) for n-3 fatty acid intake and n-6:n-3 ratio were 0.71 (0.55-0.92) and 1.66 (1.10-2.50), and middle OR (95% CI) for n-6 fatty acid intake was 0.72 (0.56-0.92), respectively. Our study suggests that n-3 and n-6 fatty acids intake were inversely associated with the risk of depressive symptoms, while the n-6:n-3 ratio was positively associated with the risk of depressive symptoms.

[Effect of Metformin on Proliferation Capacity, Apoptosis and Glycolysis in K562 Cells].

OBJECTIVE: To investigate the effect of metformin on the proliferation, apoptosis and energy metabolism of acute myeloid leukemia (AML) K562 cells and the possible mechanism. METHODS: Different doses (0, 5, 10, 20 and 30 mmol/L) of metformin was added into the K562 cells, which were cultivated for 24 h, 48 h and 72 h. The inverted optical microscope was used to observe the cell growth, CCK 8 was used to detect the cell vitality. The appropriate metformin doses (0, 10, 20 and 30 mmol/L) and the best time (48 h) were selected for subsequent experiments. The flow cytometer with Annexin V-FITC /PI doulde staining was used to detect apoptosis; the glucose detection kit and lactate detection kit were used to detect glucose consumption and lactate production; fluorescence quantitative PCR was used to detect glycolysis-related gene expression, and Western blot was used to detect protein expression. RESULTS: Metformin inhibited the proliferation of K562 cells in a dose-dependent manner (r=0.92), and the relative survival in the 30 mmol/L group was as low as 19.84% at 72 h. When treated with metformin for 48 h, the apoptosis rates of 0, 10, 20 and 30 mmol/L groups were 5.14%, 12.19%, 26.29% and 35.5%, respectively. Compared with the control group, the glucose consumption and lactate secretion of K562 cells treated with metformin were significantly reduced (P<0.05), and showed a dose-dependent effect(r=0.94,r=0.93,respectively). Metformin inhibited the expression of GLUT1, LDHA, ALDOA, PDK1, and PGK1 genes of K562 cells (P<0.05) showing a dose-dependent manner(r=0.83，r=0.80，r=0.72，r=0.76，r=0.73,respectively). Metformin inhibited the expression of P-Akt, P-S6, GLUT1, LDHA proteins of K562 cells(P<0.05), showing a dose-dependent relationship(r=0.80，r=0.92，r=0.83，r=0.92,respectively). CONCLUSION: Metformin can inhibit the growth and proliferation of K562 cells and promote the apoptosis of K562 cells by inhibiting glycolysis energy metabolism. PI3K/Akt/mTOR signaling pathway may be one of the molecular mechanisms of metformin on k562 cells.