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Abstract Background Obesity is well-established as a significant contributor to the development of insulin resistance (IR) and diabetes, partially due to elevated plasma saturated free fatty acids like palmitic acid (PA). Grb10-interacting GYF Protein 2 (GIGYF2), an RNA-binding protein, is widely expressed in various tissues including the liver, and has been implicated in diabetes-induced cognitive impairment. Whereas, its role in obesity-related IR remains uninvestigated. Methods In this study, we employed palmitic acid (PA) exposure to establish an in vitro IR model in the human liver cancer cell line HepG2 with high-dose chronic PA treatment. The cells were stained with fluorescent dye 2-NBDG to evaluate cell glucose uptake. The mRNA expression levels of genes were determined by real-time qRT-PCR (RT-qPCR). Western blotting was employed to examine the protein expression levels. The RNA immunoprecipitation (RIP) was used to investigate the binding between protein and mRNA. Lentivirus-mediated gene knockdown and overexpression were employed for gene manipulation. In mice, an IR model induced by a high-fat diet (HFD) was established to validate the role and action mechanisms of GIGYF2 in the modulation of HFD-induced IR in vivo. Results In hepatocytes, high levels of PA exposure strongly trigger the occurrence of hepatic IR evidenced by reduced glucose uptake and elevated extracellular glucose content, which is remarkably accompanied by up-regulation of GIGYF2. Silencing GIGYF2 ameliorated PA-induced IR and enhanced glucose uptake. Conversely, GIGYF2 overexpression promoted IR, PTEN upregulation, and AKT inactivation. Additionally, PA-induced hepatic IR caused a notable increase in STAU1, which was prevented by depleting GIGYF2. Notably, silencing STAU1 prevented GIGYF2-induced PTEN upregulation, PI3K/AKT pathway inactivation, and IR. STAU1 was found to stabilize PTEN mRNA by binding to its 3’UTR. In liver cells, tocopherol treatment inhibits GIGYF2 expression and mitigates PA-induced IR. In the in vivo mice model, GIGYF2 knockdown and tocopherol administration alleviate high-fat diet (HFD)-induced glucose intolerance and IR, along with the suppression of STAU1/PTEN and restoration of PI3K/AKT signaling. Conclusions Our study discloses that GIGYF2 mediates obesity-related IR by disrupting the PI3K/AKT signaling axis through the up-regulation of STAU1/PTEN. Targeting GIGYF2 may offer a potential strategy for treating obesity-related metabolic diseases, including type 2 diabetes. Graphical Abstract

Background: Diabetes Mellitus (DM), a chronic metabolic disease characterized by elevated blood glucose, is caused by various degrees of insulin resistance and dysfunctional insulin secretion, resulting in hyperglycemia. The loss and failure of functional β-cells are key mechanisms resulting in type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Aim of review: Elucidating the underlying mechanisms of β-cell failure, and exploring approaches for β-cell neogenesis to reverse β-cell dysfunction may provide novel strategies for DM therapy. Key scientific concepts of review: Emerging studies reveal that genetic susceptibility, endoplasmic reticulum (ER) stress, oxidative stress, islet inflammation, and protein modification linked to multiple signaling pathways contribute to DM pathogenesis. Over the past few years, replenishing functional β-cell by β-cell neogenesis to restore the number and function of pancreatic β-cells has remarkably exhibited a promising therapeutic approach for DM therapy. In this review, we provide a comprehensive overview of the underlying mechanisms of β-cell failure in DM, highlight the effective approaches for β-cell neogenesis, as well as discuss the current clinical and preclinical agents research advances of β-cell neogenesis. Insights into the challenges of translating β-cell neogenesis into clinical application for DM treatment are also offered.

Vascular endothelial cells (ECs) senescence plays a crucial role in vascular aging that promotes the initiation and progression of cardiovascular disease. The mutation of Grb10-interacting GYF protein 2 (GIGYF2) is strongly associated with the pathogenesis of aging-related diseases, whereas its role in regulating ECs senescence and dysfunction still remains elusive. In this study, we found aberrant hyperexpression of GIGYF2 in senescent human ECs and aortas of old mice. Silencing GIGYF2 in senescent ECs suppressed eNOS-uncoupling, senescence, and endothelial dysfunction. Conversely, in nonsenescent cells, overexpressing GIGYF2 promoted eNOS-uncoupling, cellular senescence, endothelial dysfunction, and activation of the mTORC1-SK61 pathway, which were ablated by rapamycin or antioxidant N-Acetyl-l-cysteine (NAC). Transcriptome analysis revealed that staufen double-stranded RNA binding protein 1 (STAU1) is remarkably downregulated in the GIGYF2-depleted ECs. STAU1 depletion significantly attenuated GIGYF2-induced cellular senescence, dysfunction, and inflammation in young ECs. Furthermore, we disclosed that GIGYF2 acting as an RNA binding protein (RBP) enhances STAU1 mRNA stability, and that the intron region of the late endosomal/lysosomal adaptor MAPK and mTOR activator 4 (LAMTOR4) could bind to STAU1 protein to upregulate LAMTOR4 expression. Immunofluorescence staining showed that GIGYF2 overexpression promoted the translocation of mTORC1 to lysosome. In the mice model, GIGYF2flox/flox Cdh-Cre+ mice protected aged mice from aging-associated vascular endothelium-dependent relaxation and arterial stiffness. Our work discloses that GIGYF2 serving as an RBP enhances the mRNA stability of STAU1 that upregulates LAMTOR4 expression through binding with its intron region, which activates the mTORC1-S6K1 signaling via recruitment of mTORC1 to the lysosomal membrane, ultimately leading to ECs senescence, dysfunction, and vascular aging. Disrupting the GIGYF2-STAU1-mTORC1 signaling cascade may represent a promising therapeutic approach against vascular aging and aging-related cardiovascular diseases.

In wireless communication wiretap channel, for the eavesdropper to obtain the legitimate receiver decoding rules situation, this paper proposes a LT-SLT fountain code anti-eavesdropping channel coding design. This method targets the Luby Transform (LT) code transmission for some of the original symbols of the Shifted LT (SLT) code and utilizes the fountain code to receive the correct symbols in different noise channels with differential characteristics so that the decoding process of the eavesdropper changes and cannot be decoded in synchronization with the legitimate receivers, and then the partial symbols of the recovered source are different from those of the legitimate receivers. When these symbols continue to participate in SLT decoding, increasing the untranslated rate of the eavesdropper. Experimental results show that although the method proposed in this paper increases the number of decoded symbols by a small amount, the eavesdropper untranslated rate of this scheme gets improved by about 15% when the main channel or the wiretap channel is varied individually, compared with LT code and SLT code. When both the main channel and the wiretap channel are varied simultaneously, the untranslated rate of the eavesdropper in this scheme gets approximately 30% higher compared to LT code and SLT code, and the untranslated rate of the eavesdropper in this scheme gets approximately 14% higher compared to SLT-LT fountain code. When the main channel is worse or slightly better than the wiretap channel, the untranslated rate of eavesdroppers of this scheme is better than that of SLT-LT fountain code, which effectively ensures secure transmission of information.

Fountain code can significantly increase eavesdroppers’ untranslated efficiency in the wireless communication eavesdropping channel. The secondary LT coding anti-eavesdropping scheme with fountain code degree-1 is the subject of a theoretical investigation in this paper. The fact that its channel security capacity is greater than that of traditional LT code is first deduced from an information-theoretic standpoint, and the impact of source symbol length on decoding complexity and decoding overhead is then examined. The experimental results show that, compared with the traditional anti-eavesdropping twice fountain code, selecting long source symbols for double LT coding, when the main channel is better than the eavesdropping channel, can ensure that the eavesdropper has a higher untranslated efficiency, and can effectively reduce the fountain code decoding complexity and the number of encoded symbols sent by the source to improve the efficiency of information transmission.

The prediction of pause fillers plays a crucial role in enhancing the naturalness of synthesized speech. In recent years, neural networks, including LSTM, BERT, and XLNet, have been employed for pause fillers prediction modules. However, these methods have exhibited relatively lower accuracy in predicting pause fillers. This paper introduces the utilization of the RoBERTa model for predicting Chinese pause fillers and presents a novel approach to training the RoBERTa model, effectively enhancing the accuracy of Chinese pause fillers prediction. Our proposed approach involves categorizing text from different speakers into four distinct style groups based on the frequency and position of Chinese pause fillers. The RoBERTa model is trained on these four groups of data, which incorporate different styles of fillers, thereby ensuring a more natural synthesis of speech. The Chinese pause fillers prediction module is evaluated on systems such as Parallel Tacotron2, FastPitch, and Deep Voice3, achieving a notable 26.7% improvement in word-level prediction accuracy compared to the BERT model, along with a 14% enhancement in position-level prediction accuracy. This substantial improvement results in a significant enhancement of the naturalness of the generated speech.

One task of nonparallel speech conversion is to convert the source speaker’s speech samples to the target speaker’s speech samples, keeping the content unchanged. In view of the advantages of MaskCycleGAN-VC in nonparallel speech conversion, such as small model size and superior performance, our paper uses the basic structure of MaskCycleGAN-VC to improve it and proposes a cyclic boundary method filling in the frame MaskCycleGAN-VC (CBFMCycleGAN-VC) model, which predicts the voice of a person as he ages by using voice samples of his younger self. First, this paper adds speech preprocessing modules, including the Chebyshev low-pass filter and adaptive filter, which increases the robustness of the system. Second, our paper considers the time-domain difference in the weight parameters, which makes it easier to grasp the mapping law of the time-domain structure, with a faster convergence speed. Last, the circular boundary method is introduced to avoid the ringing effect, to enhance the connection between the filled frame and the adjacent frame, and to obtain a better generator. The simulation results show that the CBFMCycleGAN-VC model is more suitable for the speech conversion task of predicting the voices of elderly people, and the convergence speed is faster. The converted voice is also closer to the voice of the target speaker in the time domain and frequency domain. Under the condition that the accuracy rate is similar to that of MaskCycleGAN-VC, the MOS score is 17.5% higher than that of MaskCycleGAN-VC.

In recent years, physical layer security technology has provided a new way to solve the problem of secure transmissions in wireless communications from an information theory perspective by using physical layer security coding and the inherent characteristics of the channel. As a nonsystematic code, Luby transform (LT) code has the characteristics of random coding and rateless, therefore, eavesdroppers cannot directly obtain useful information from leaked code symbols. As a shifted LT (SLT) code, the SLT codes can efficiently recover information, with a smaller decoding overhead. Therefore, we propose an SLT-LT joint code anti-eavesdropping scheme based on random symbol sets. Based on the environment of the main channel, the sender selects a set of random symbols to send to legitimate receivers as known symbols and uses these random symbols and message symbols to form source symbols for the SLT-LT concatenated coding to increase the bit error rate (BER) of the eavesdroppers. The experimental results show that, compared with other anti-eavesdropping LT schemes, our proposed scheme only adds a small amount of decoding overhead but has a better security performance.

Arginase is a key hydrolase in the urea cycle that hydrolyses L-arginine to urea and L-ornithine. Increasing number of studies in recent years demonstrate that two mammalian arginase isoforms, arginase 1 (ARG1) and arginase 2 (ARG2), were aberrantly upregulated in various types of cancers, and played crucial roles in the regulation of tumor growth and metastasis through various mechanisms such as regulating L-arginine metabolism, influencing tumor immune microenvironment, etc. Thus, arginase receives increasing focus as an attractive target for cancer therapy. In this review, we provide a comprehensive overview of the physiological and biological roles of arginase in a variety of cancers, and shed light on the underlying mechanisms of arginase mediating cancer cells growth and development, as well as summarize the recent clinical research advances of targeting arginase for cancer therapy.

The existing physical layer security technology based on fountain codes needs to ensure that the legal channel is superior to the eavesdropping channel; when the quality of the legal channel and the eavesdropping channel are close, the information security cannot be guaranteed. Aiming at this problem, this paper proposes a shifted Luby transform (SLT) code security scheme for partial information encryption, which is mainly divided into two stages, partial information encryption transfer and degree distribution adjustment. The main idea is that the source randomly extracts part of the information symbols, and performs XOR encryption with the random sequence containing the main channel noise sent by the legitimate receiver. Afterward, the degree distribution is adjusted using the number of transfer information symbols received by the legitimate receiver to improve the average degree of the encoded codewords. Since the eavesdropper can only obtain fewer information symbols in the initial stage, it is difficult to decode the generated coded symbols after the degree distribution adjustment, thereby ensuring the safe transmission of information. The experimental results show that, compared with other LT anti-eavesdropping schemes, even if the legitimate channel is not dominant, the proposed scheme still has better security performance and less decoding overhead.