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The metabolic switch from oxidative phosphorylation to glycolysis is required for tumorigenesis in order to provide cancer cells with energy and substrates of biosynthesis. Therefore, it is important to elucidate mechanisms controlling the cancer metabolic switch. MTR4 is a RNA helicase associated with a nuclear exosome that plays key roles in RNA processing and surveillance. We demonstrate that MTR4 is frequently overexpressed in hepatocellular carcinoma (HCC) and is an independent diagnostic marker predicting the poor prognosis of HCC patients. MTR4 drives cancer metabolism by ensuring correct alternative splicing of pre-mRNAs of critical glycolytic genes such as GLUT1 and PKM2 . c-Myc binds to the promoter of the MTR4 gene and is important for MTR4 expression in HCC cells, indicating that MTR4 is a mediator of the functions of c-Myc in cancer metabolism. These findings reveal important roles of MTR4 in the cancer metabolic switch and present MTR4 as a promising therapeutic target for treating HCC. Aberrant alternative splicing has been shown to contribute to the tumorigenic processes. Here, the authors show that MTR4 is overexpressed in hepatocellular carcinoma and has a role in tumorigenesis through the modulation of the splicing of glycolytic genes PKM2 and GLUT1 .

Gene therapy is a technique involving the modification of an individual’s genes for treating a particular disease. The key to effective gene therapy is an efficient carrier delivery system. Viral vectors that have been artificially modified to lose their pathogenicity are used widely as a delivery system, with the key advantages of their natural high transduction efficiency and stable expression. With decades of development, viral vector-based gene therapies have achieved promising clinical outcomes. Currently, the three key vector strategies are based on adeno-associated viruses, adenoviruses, and lentiviruses. However, certain challenges, such as immunotoxicity and “off-target”, continue to exist. In the present review, the above three viral vectors are discussed along with their respective therapeutic applications. In addition, the major translational challenges encountered in viral vector-based gene therapies are summarized, and the possible strategies to address these challenges are also discussed.

Subtropical reservoirs are an important source of atmospheric methane (CH 4 ). This study investigated the spatiotemporal variability of bubble and diffusive CH 4 emissions from a subtropical reservoir, including its upstream and downstream rivers, in eastern China. There was no obvious seasonal variation in CH 4 emissions from the main reservoir, which increased slightly from the first half year to the next half year. In the upstream river, CH 4 emissions were low from February to June and fluctuated widely from July to January due to bubble activity. In the downstream river, CH 4 emissions were lowest in February, which was possibly influenced by the low streamflow rate from the reservoir (275 m 3 s −1 ) and a short period of mixing. There was spatial variability in CH 4 emissions, where fluxes were highest from the upstream river (3.65 ± 3.24 mg CH 4 m −2 h −1 ) and lowest from the main reservoir (0.082 ± 0.061 mg CH 4 m −2 h −1 ), and emissions from the downstream river were 0.49 ± 0.20 mg CH 4 m −2 h −1 . Inflow rivers are hot spots in bubble CH 4 emissions that should be examined using field-sampling strategies. This study will improve the accuracy of current and future estimations of CH 4 emissions from hydroelectric systems and will help guide mitigation strategies for greenhouse gas emissions.

Kidney fibrosis is the hallmark of chronic kidney disease (CKD) progression, whereas no effective anti-fibrotic therapies exist. Recent evidence has shown that tubular ferroptosis contributes to the pathogenesis of CKD with persistent proinflammatory and profibrotic responses. We previously reported that natural flavonol fisetin alleviated septic acute kidney injury and protected against hyperuricemic nephropathy in mice. In this study, we investigated the therapeutic effects of fisetin against fibrotic kidney disease and the underlying mechanisms. We established adenine diet-induced and unilateral ureteral obstruction (UUO)-induced CKD models in adult male mice. The two types of mice were administered fisetin (50 or 100 mg·kg −1 ·d −1 , i.g.) for 3 weeks or 7 days, respectively. At the end of the experiments, the mice were euthanized, and blood and kidneys were gathered for analyzes. We showed that fisetin administration significantly ameliorated tubular injury, inflammation, and tubulointerstitial fibrosis in the two types of CKD mice. In mouse renal tubular epithelial (TCMK-1) cells, treatment with fisetin (20 μM) significantly suppressed adenine- or TGF-β1-induced inflammatory responses and fibrogenesis, and improved cell viability. By quantitative real-time PCR analysis of ferroptosis-related genes, we demonstrated that fisetin treatment inhibited ferroptosis in the kidneys of CKD mice as well as in injured TCMK-1 cells, as evidenced by decreased ACSL4, COX2, and HMGB1, and increased GPX4. Fisetin treatment effectively restored ultrastructural abnormalities of mitochondrial morphology and restored the elevated iron, the reduced GSH and GSH/GSSG as well as the increased lipid peroxide MDA in the kidneys of CKD mice. Notably, abnormally high expression of the ferroptosis key marker ACSL4 was verified in the renal tubules of CKD patients (IgAN, MN, FSGS, LN, and DN) as well as adenine- or UUO-induced CKD mice, and in injured TCMK-1 cells. In adenine- and TGF-β1-treated TCMK-1 cells, ACSL4 knockdown inhibited tubular ferroptosis, while ACSL4 overexpression blocked the anti-ferroptotic effect of fisetin and reversed the cytoprotective, anti-inflammatory, and anti-fibrotic effects of fisetin. In summary, we reveal a novel aspect of the nephroprotective effect of fisetin, i.e. inhibiting ACSL4-mediated tubular ferroptosis against fibrotic kidney diseases.

Timely and remote biomarker detection is highly desired in personalized medicine and health protection but presents great challenges in the devices reported so far. Here, we present a cost-effective, flexible and self-powered sensing device for H 2 S biomarker analysis in various application scenarios based on the structure of galvanic cells. The sensing mechanism is attributed to the change in electrode potential resulting from the chemical adsorption of gas molecules on the electrode surfaces. Intrinsically stretchable organohydrogels are used as solid-state electrolytes to enable stable and long-term operation of devices under stretching deformation or in various environments. The resulting open-circuit sensing device exhibits high sensitivity, low detection limit, and excellent selectivity for H 2 S. Its application in the non-invasive halitosis diagnosis and identification of meat spoilage is demonstrated, emerging great commercial value in portable medical electronics and food security. A wireless sensory system has also been developed for remote H 2 S monitoring with the participation of Bluetooth and cloud technologies. This work breaks through the shortcomings in the traditional chemiresistive sensors, offering a direction and theoretical foundation for designing wearable sensors catering to other stimulus detection requirements. Biomarker detection, including for H 2 S, is desirable but challenging to achieve. Here, the authors report the development of a device for H 2 S sensing across a range of applications.

In recent years, the widespread adoption of wireless sensor networks (WSN) has resulted in the growing integration of the internet of things (IoT). However, WSN encounters limitations related to energy and sensor node lifespan, making the development of an efficient routing protocol a critical concern. Cluster technology offers a promising solution to this challenge. This study introduces a novel cluster routing protocol for WSN. The system selects cluster heads and relay nodes utilizing the multi-strategy fusion snake optimizer (MSSO) and employs the minimum spanning tree algorithm for inter-cluster routing planning, thereby extending the system’s lifecycle and conserving network energy. In pursuit of an optimal clustering scheme, the paper also introduces tactics involving dynamic parameter updating, adaptive alpha mutation, and bi-directional search optimization within MSSO. These techniques significantly increase the algorithm convergence speed and expand the available search space. Furthermore, a novel efficient clustering routing model for WSN is presented. The model generates different objective functions for selecting cluster heads and relay nodes, considering factors such as location, energy, base station distance, intra-cluster compactness, inter-cluster separation, and other relevant criteria. When selecting cluster heads, the fuzzy c-means (FCM) algorithm is integrated into MSSO to improve the optimization performance of the algorithm. When planning inter-cluster routing, the next hop node is selected for the relay node based on distance, residual energy, and direction.The experimental results demonstrate that the proposed protocol reduces energy consumption by at least 26.64% compared to other cluster routing protocols including LEACH, ESO, EEWC, GWO, and EECHS-ISSADE. Additionally, it increases the network lifetime of WSN by at least 25.84%, extends the stable period by at least 52.43%, and boosts the network throughput by at least 40.99%.

Intestinal microbial metabolites have been increasingly recognized as important regulators of enteric viral infection. However, very little information is available about which specific microbiota-derived metabolites are crucial for swine enteric coronavirus (SECoV) infection in vivo . Using swine acute diarrhea syndrome (SADS)-CoV as a model, we were able to identify a greatly altered bile acid (BA) profile in the small intestine of infected piglets by untargeted metabolomic analysis. Using a newly established ex vivo model–the stem cell-derived porcine intestinal enteroid (PIE) culture–we demonstrated that certain BAs, cholic acid (CA) in particular, enhance SADS-CoV replication by acting on PIEs at the early phase of infection. We ruled out the possibility that CA exerts an augmenting effect on viral replication through classic farnesoid X receptor or Takeda G protein-coupled receptor 5 signaling, innate immune suppression or viral attachment. BA induced multiple cellular responses including rapid changes in caveolae-mediated endocytosis, endosomal acidification and dynamics of the endosomal/lysosomal system that are critical for SADS-CoV replication. Thus, our findings shed light on how SECoVs exploit microbiome-derived metabolite BAs to swiftly establish viral infection and accelerate replication within the intestinal microenvironment.

Human skin is a self-healing mechanosensory system that detects various mechanical contact forces efficiently through three-dimensional innervations. Here, we propose a biomimetic artificially innervated foam by embedding three-dimensional electrodes within a new low-modulus self-healing foam material. The foam material is synthesized from a one-step self-foaming process. By tuning the concentration of conductive metal particles in the foam at near-percolation, we demonstrate that it can operate as a piezo-impedance sensor in both piezoresistive and piezocapacitive sensing modes without the need for an encapsulation layer. The sensor is sensitive to an object’s contact force directions as well as to human proximity. Moreover, the foam material self-heals autonomously with immediate function restoration despite mechanical damage. It further recovers from mechanical bifurcations with gentle heating (70 °C). We anticipate that this material will be useful as damage robust human-machine interfaces. Designing mechanosensory system that detects mechanical contact forces like human skin remains a challenge. Here, the authors present artificially innervated self-healing foams by embedding 3D electrodes for piezo-impedance sensors that can operate in both piezoresistive and piezocapacitive sensing modes to address various proximity and mechanical interactions efficiently.

Background Depression is one of the most common mental health problems in older adults. Community social capital and depressive symptoms in older adults have been discussed in previous studies but remain limited. This study aims to explore the association between community social capital and depressive symptoms among older adults relocated for poverty alleviation in China. Methods Through the multi-stage stratified sampling, 1882 relocated older adults (≥ 60) were surveyed in 24 resettlement sites in Shanxi Province, China. Community social capital was measured in civic participation, social cohesion, and reciprocity. Depressive symptoms were assessed by the 10-item CES-D scale. Results There were 49.5% of relocated older adults reported significant depressive symptoms. We found that the relocated older adults who did not participate in leisure-time activities showed higher odds of reporting significant depressive symptoms compared to those who participated [Adjusted Odds Ratio ( AOR ) 1.360, 95% CI : 1.060 ~ 1.745], the relocated older adults who gave negative responses in community trust were more likely to report significant depressive symptoms compared to those who gave positive responses ( AOR : 1.461, 95% CI : 1.126 ~ 1.896), and those who did not receive emotional support in their community showed 33.6% higher odds of reporting significant depressive symptoms ( AOR : 1.336, 95% CI : 1.015 ~ 1.757) after controlling for all potential confounders. Conclusions Leisure-time activity participation, community trust, and receiving emotional support were associated with depressive symptoms of older adults relocated for poverty alleviation in Shanxi, China. Targeted interventions on community social capital for relocated older adults are needed for mental health promotion.

Human behaviors are extremely sophisticated, relying on the adaptive, plastic and event-driven network of sensory neurons. Such neuronal system analyzes multiple sensory cues efficiently to establish accurate depiction of the environment. Here, we develop a bimodal artificial sensory neuron to implement the sensory fusion processes. Such a bimodal artificial sensory neuron collects optic and pressure information from the photodetector and pressure sensors respectively, transmits the bimodal information through an ionic cable, and integrates them into post-synaptic currents by a synaptic transistor. The sensory neuron can be excited in multiple levels by synchronizing the two sensory cues, which enables the manipulating of skeletal myotubes and a robotic hand. Furthermore, enhanced recognition capability achieved on fused visual/haptic cues is confirmed by simulation of a multi-transparency pattern recognition task. Our biomimetic design has the potential to advance technologies in cyborg and neuromorphic systems by endowing them with supramodal perceptual capabilities. Designing bioinspired perceptual system remains a challenge. Here, the authors report a bimodal artificial sensory neuron, integrating a resistive pressure sensor, a perovskite-based photodetector, a hydrogel-based ionic cable, and a synaptic transistor, to implement the visual-haptic fusion for motion control and patterns recognition.