Carbonized wood fiber-supported S, N-codoped carbon layer-coated multinary metal sulfide nanoarchitecture for efficient oxygen evolution reaction at ampere-level current density.

Multinary metal sulfides (MMSs) are highly suitable candidates for the application of electrocatalysis as they offer numerous parameters for optimizing the electronic structure and catalytic sites. Herein, a stable nanoarchitecture consisting of MMSs ((NiCoCrMnFe)Sx) nanoparticles embedded in S, N-codoped carbon (SNC) layers derived from metal organic framework (MOF) and supported on carbonized wood fibers (CWF) was fabricated by directly carbonization. Benefiting from this carbon-coated configuration, along with the synergistic effects within multinary metal systems, (NiCoCrMnFe)Sx@SNC/CWF delivers an exceptionally low overpotential of 260 mV at a high current density of 1000 mA cm-2, a small Tafel slope of 48.5 mV dec-1, and robust electrocatalytic stability. Furthermore, the (NiCoCrMnFe)Sx@SNC/CWF used as the cathode of rechargeable Zn-air batteries demonstrates higher power density and remarkable durability, surpassing that of commercial RuO2. Thus, we showcase the feasibility and advantages of employing highly efficient and durable MMSs materials for low-cost and sustainable energy conversion.

Molecular subtypes and nomogram for predicting the prognosis of cervical cancer based on a matrix-immune signature.

Cervical cancer is a kind of tumor related to chronic HPV infection. Currently, the treatment of cervical cancer is guided mainly by clinicopathological factors. The role of tumor microenvironment in the prognosis and treatment of cervical cancer has been ignored. We aimed to use bioinformatics to identify the molecular subtypes in cervical cancer and construct a predictive nomogram combining a matrix-immune signature (MIS) and clinicopathological factors to support treatment decisions. Two cervical cancer subtypes with different prognoses were identified based on matrix- and immune-genes in TCGA-CESC. The MIS was developed using Cox regression and Lasso algorithm and verified in the Cancer Genome Characterization Initiative (CGCI) using time-dependent receiver operating characteristic (ROC) curve analysis. Multivariable analysis identified lymph node metastases, lymphovascular space invasion, and the MIS as independent prognostic factors, which were used to construct the predictive nomogram. The areas under the ROC curve of the model were 0.872, 0.879, and 0.803 for the 1-, 3-, and 5-year periods, respectively. The C-index was 0.845. Calibration curves confirmed the excellent prognosis prediction of the nomogram. The nomogram indicted a 3-year survival rate of > 90% in patients with a total score > 110.1. The constructed predictive nomogram has significant implications for prognostic assessment and treatment selection in cervical cancer.

Short-Term and Imminent Rainfall Prediction Model Based on ConvLSTM and SmaAT-UNet.

Short-term precipitation forecasting methods are mainly divided into statistical forecasting, numerical model-based forecasting, and radar image extrapolation techniques. The two methods based on statistical prediction and numerical model have the disadvantages of being unstable and generating large errors. Therefore, this study proposes the use of deep learning for radar image extrapolation for precipitation forecasting, in particular by developing algorithms for ConvLSTM and SmaAT-UNet. The ConvLSTM model is a fusion of a CNN (Convolutional Neural Network) and LSTM (Long Short-Term Memory network), which solves the challenge of processing spatial sequence data, which is a task that traditional LSTM models cannot accomplish. At the same time, SmaAT-UNet enhances the traditional UNet structure by incorporating the CBAM (Convolutional Block Attention Module) attention mechanism and replacing the standard convolutional layer with depthwise separable convolution. This innovative approach aims to improve the efficiency and accuracy of short-term precipitation forecasting by improving feature extraction and data processing techniques. Evaluation and analysis of experimental data show that both models exhibit good predictive ability, with the SmaAT-UNet model outperforming ConvLSTM in terms of accuracy. The results show that the performance indicators of precipitation prediction, especially detection probability (POD) and the Critical Success index (CSI), show a downward trend with the extension of the prediction time. This trend highlights the inherent challenges of maintaining predictive accuracy over longer periods of time and highlights the superior performance and resilience of the SmaAT-UNet model under these conditions. Compared with the statistical forecasting method and numerical model forecasting method, its accuracy in short-term rainfall forecasting is improved.

FSN: Joint Entity and Relation Extraction Based on Filter Separator Network.

Joint entity and relation extraction methods have attracted an increasing amount of attention recently due to their capacity to extract relational triples from intricate texts. However, most of the existing methods ignore the association and difference between the Named Entity Recognition (NER) subtask features and the Relation Extraction (RE) subtask features, which leads to an imbalance in the interaction between these two subtasks. To solve the above problems, we propose a new joint entity and relation extraction method, FSN. It contains a Filter Separator Network (FSN) module that employs a two-direction LSTM to filter and separate the information contained in a sentence and merges similar features through a splicing operation, thus solving the problem of the interaction imbalance between subtasks. In order to better extract the local feature information for each subtask, we designed a Named Entity Recognition Generation (NERG) module and a Relation Extraction Generation (REG) module by adopting the design idea of the decoder in Transformer and average pooling operations to better capture the entity boundary information in the sentence and the entity pair boundary information for each relation in the relational triple, respectively. Additionally, we propose a dynamic loss function that dynamically adjusts the learning weights of each subtask in each epoch according to the proportionality between each subtask, thus narrowing down the difference between the ideal and realistic results. We thoroughly evaluated our model on the SciERC dataset and the ACE2005 dataset. The experimental results demonstrate that our model achieves satisfactory results compared to the baseline model.

Structural Engineering of Co-Metal-Organic Frameworks via Ce Incorporation for Improved Oxygen Evolution.

The rational design of metal-organic framework (MOF)-based electrocatalysts plays a key role in achieving high-efficiency oxygen evolution reaction (OER). Herein, a synergetic morphology and electronic structure engineering strategy are proposed to design a Co-MOF nanoflower grown on carbon paper via rare-earth cerium doping (CoCe-MOF/CP). Compared with Co-MOF/CP, the developed CoCe-MOF/CP exhibited superior OER performance with a low overpotential of 267 mV at 10 mA cm-2 and outstanding long-term stability over 100 h. Theoretical calculations show that the unique 4f valence electron structure of Ce induced charge redistribution of the Co-MOF surface through the strong Co 3d-O 2p-Ce 4f orbital electronic coupling below the Fermi level. Ce-doped plays a key role in the engineering of the electronic states of the Co sites to endow them with the optimal free energy landscape for enhanced OER catalytic activity. This work provides new insights into comprehending the RE-enhanced mechanism of electrocatalysis and provides an effective strategy for the design of MOF-based electrocatalysts.

Synthesis of Hierarchical Layered Quasi-Triangular Ce(OH)CO3 and Its Thermal Conversion to Ceria with High Polishing Performance.

Layered quasi-triangular Ce(OH)CO3 assembled from primary nanoparticles was synthesized via a solvothermal method and converted into CeO2 abrasive particles by calcination at 800-1000 °C. With the increase of calcination temperature, the primary particle size increased and the microstructure, mechanical hardness, and chemical activity of the CeO2 particles changed, thus affecting the polishing performance. The calcined products obtained at 800, 850, and 900 °C maintained the layered edge structure of the Ce(OH)CO3 precursor and had a relatively high specific surface area and surface Ce3+ concentration. The samples calcined at 950 and 1000 °C lost the layered structure due to the large-scale melting of the primary particles, and their surface chemical activity decreased. The polishing experiments on K9 glass showed that, with the calcination temperature rising from 800 to 1000 °C, the material removal rate (MRR) first increased and then decreased sharply. The initial increase of MRR was attributed to the increase of mechanical hardness of the layered quasi-triangular CeO2, and the subsequent decrease of MRR was related to the decrease in surface chemical activity and disappearance of the layered edge structure. The product calcined at 900 °C had the highest MRR and best surface quality after polishing due to the layered edge structure and optimal match of chemical activity and mechanical hardness.

Research on the Effect of Evidence-Based Intervention on Improving Students' Mental Health Literacy Led by Ordinary Teachers: A Meta-Analysis.

BACKGROUND: the purpose of this study was to systematically review the effects of intervention experiments led by ordinary teachers to improve students' mental health literacy and to provide evidence-based research and new ideas for improving students' mental health literacy. METHODS: A systematic search using 5 English (Web of Science, PubMed, ProQuest, EBSCO, Springer Link) and 3 Chinese (CNKI, WanFang, and VIP) databases was initiated to identify controlled trials assessing the immediate effect and delay effect of the intervention experiment led by ordinary teachers on improving students' mental health knowledge, anti-stigma, willingness, or behavior to seek-help. RESULTS: a total of 14 experiments with 7873 subjects were included. The results showed that the immediate effect of the intervention on promoting students' mental health knowledge [g = 0.622, 95% CI (0.395, 0.849)] and anti-stigma [g = 0.262, 95% CI (0.170, 0.354)] was significant, but the amount of delay effect is not significant. CONCLUSIONS: the results of this review show that ordinary classroom teachers can effectively participate in projects to improve students' mental health literacy, significantly improve students' mental health knowledge and attitudes towards psychological problems, and make up for the shortage of full-time mental health teachers in schools. In future, more attention should be paid to students' mental health literacy, and evidence-based intervention research should be strengthened. Furthermore, we can improve students' mental health literacy and avoid poor mental health by addressing delays in early intervention, as well as improve experimental design, prolong the intervention time, and improve the effectiveness of the intervention.

High-Throughput Fabrication of Size-Controlled Pickering Emulsions, Colloidosomes, and Air-Coated Particles via Clog-Free Jetting of Suspensions.

Microcapsules with a liquid core and a solid shell composed of hydrophobic nanoparticles are broadly applied in food, pharmaceutics, and biotechnologies. For example, Pickering emulsions, colloidosomes, or antibubbles (droplets surrounded by air layers in water) enable controlled release of active agents, biocompatibility, and contact-less liquid transportation. However, producing controlled nanoparticle- or polymer-laden hydrophobic shells at scale is highly challenging, since bulk methods are polydisperse and microfluidic chips are prone to clogging and slow. Here, clog-free coating of an aqueous jet with silica nanoparticle suspensions with concentrations up to 10% (w/v), as well as high concentrations of polymers (30% (w/v) poly(lactic acid) (PLA)), is demonstrated, enabling continuous generation of microcapsules at flow rates up to 4 mL min-1 . Pickering emulsions are converted into capsules, providing hydrophobic shells consisting of nanoparticles for controlled release. As a highlight, the scalable fabrication of air-coated capsules (antibubbles) in the sub-millimeter range is demonstrated. The shell contains an air film that protects the liquid core for days yet enables ultrasound-induced release within 3 min. By enabling rapid fabrication of controlled Pickering emulsions, colloidosomes, antibubbles, and biodegradable capsules, jetting through a liquid layer (JetALL) provides a versatile platform for advanced applications in food, pharmacy, and life science.

Effects of chronic heat stress on the immunophenotyping of lymphocytes in immune organs of growing pigs.

This study aimed to investigate the effects of chronic heat stress on the immunophenotyping of lymphocytes in immune organs of growing pigs. A single-factor randomized block design was used, and 15 healthy growing large white barrows (5 litters, 3 pigs/litter) with similar body weight (40.8 kg) were assigned into 3 groups (5 pigs in each group). Groups were: control group (Con, in 23 °C environmental control chamber, fed ad libitum), heat stress group (HS, in 33 °C environmental control chamber, fed ad libitum), and pair-fed group (PF, in 23 °C environmental control chamber, fed diets according to the feed intake of HS group). After a 7-d adaption, the experiment lasted for 21 d. The results showed as follows: (1) activated T cells in the thymus of HS pigs were higher than those in PF pigs (P < 0.05). Monocytes and dendritic cells in the thymus of HS pigs were significantly higher than that in Con and PF pigs (P < 0.05), while the proportions of these 2 lymphocytes in the thymus of Con pigs did not differ from PF pigs (P > 0.05). Compared with Con pigs, the proportion of CD4+ (P < 0.05) and CD8+ T cells (P < 0.10) in the thymus was increased in HS pigs, while the proportion of CD4+ and CD8+ T cells in PF pigs did not differ from Con pigs (P > 0.05). (2) Compared with Con pigs, significantly decreased T cells, increased B cells and monocytes were found in the spleen of pigs exposed to heat stress (P < 0.05); the proportions of these 3 types of lymphocytes were not significantly different between Con and PF pigs (P > 0.05). The proportions of CD4+ T cells and Treg cells in the spleen of pigs exposed to heat stress tended to be lower than those in the Con pigs (P < 0.10). (3) The proportion of lymphocytes in the tonsils of pigs exposed to heat stress did not differ from Con pigs (P > 0.05); compared with PF pigs, the proportion of Treg cells was significantly decreased in HS pigs (P < 0.05). In conclusion, chronic heat stress stimulates the development and maturation of T cells in the pig thymus toward CD4+ and CD8+ T cells and increases the proportion of monocytes and dendritic cells; under the condition of chronic heat stress, the immune response process in the spleen of pigs is enhanced, but chronic heat stress impairs the survival of CD4+ T cells in the spleen.

Chronic heat stress (HS) has become a common hazard to livestock and poultry as global warming intensifies and breeding densities increase, which undoubtedly causes enormous economic losses to animal husbandry annually. Furthermore, it could also negatively impact the immune function of poultry and vaccines, resulting in various animal diseases. Until now, very few studies have focused on how HS affects the immune system of growing pigs, especially the immunophenotyping of lymphocytes in their immune organs (thymus, spleen and tonsils). In this study, the spleen and thymus are more severely affected by chronic HS than tonsils in growing pigs. Chronic HS stimulates the development and maturation of CD4+ and CD8+ T lymphocytes in the thymus. Under chronic HS, the immune response process in the spleen is enhanced, that is, the proportion of monocytes and B lymphocytes supporting immune responses increased, while the proportion of Treg cells decreased; yet long-term HS damaged the survival of CD4+ T lymphocytes in spleen.

Recognition of the Multi-class Schizophrenia Based on the Resting-State EEG Network Topology.

The clinical therapy of schizophrenia (SCZ) replies on the corresponding accurate and reliable recognition. Although efforts have been paid, the diagnosis of SCZ is still roughly subjective, it is thus urgent to search for related objective physiological parameters. Motivated by the great potential of resting-state networks in underling the brain deficits among different SCZ groups, in this study, we then developed a multi-class feature extraction approach that could effectively extract the spatial network topology and facilitate the recognition of the SCZ, by combining a network structure based supervised learning with an ensemble co-decision strategy. The results demonstrated that the multi-class spatial pattern of the network (MSPN) features outperformed the other conventional electrophysiological features, such as relative power spectrums and network properties, and achieved the highest classification accuracy of 71.58% in the alpha band. These findings did validate that the resting-state MSPN is a promising tool for the clinical assessment of the SCZ.

The complete mitochondrial genome of a marine triclad Miroplana shenzhensis (Platyhelminthes, Tricladida, Maricola).

The complete mitochondrial genome (mitogenome) of Miroplana shenzhensis Yu & Wang, 2013 is reported in the present study, representing the second mitogenome recorded in the suborder Maricola. The circular mitogenome is 14,344 bp in length, containing 12 protein-coding genes, 2 ribosomal RNAs and 22 transfer RNAs. Comparative analysis on mitochondrial gene order reveals a rearrangement in the suborder Maricola, indicating that mitochondrial gene order is conserved only in Continenticola, and is divergent across Tricladida. Phylogenetic analysis shows M. shenzhensis is clustered with an another marine triclad, forming a well-supported monophyletic group of Maricloan.

Altered temporal variability in brain functional connectivity identified by fuzzy entropy underlines schizophrenia deficits.

Investigation of the temporal variability of resting-state brain networks informs our understanding of how neural connectivity aggregates and disassociates over time, further shedding light on the aberrant neural interactions that underlie symptomatology and psychosis development. In the current work, an electroencephalogram-based sliding window analysis was utilized for the first time to measure the nonlinear complexity of dynamic resting-state brain networks of schizophrenia (SZ) patients by applying fuzzy entropy. The results of this study demonstrated the attenuated temporal variability among multiple electrodes that were distributed in the frontal and right parietal lobes for SZ patients when compared with healthy controls (HCs). Meanwhile, a concomitant strengthening of the posterior and peripheral flexible connections that may be attributed to the excessive alertness or sensitivity of SZ patients to the external environment was also revealed. These temporal fluctuation distortions combined reflect an abnormality in the coordination of functional network switching in SZ, which is further the source of worse task performance (i.e., P300 amplitude) and the negative relationship between individual complexity metrics and P300 amplitude. Notably, when using the network metrics as features, multiple linear regressions of P300 amplitudes were also exactly achieved for both the SZ and HC groups. These findings shed light on the pathophysiological mechanisms of SZ from a temporal variability perspective and provide potential biomarkers for quantifying SZ's progressive neurophysiological deterioration.

A millisecond passive micromixer with low flow rate, low sample consumption and easy fabrication.

Fast mixing of small volumes of solutions in microfluidic devices is essential for an accurate control and observation of the dynamics of a reaction in biological or chemical studies. It is often, however, a challenging task, as the Reynolds number (Re) in microscopic devices is typically < 100. In this report, we detail a novel mixer based on the "staggered herring bone" (SHB) pattern and "split-recombination" strategies with an optimized geometry, the periodic rotation of the flow structure can be controlled and recombined in a way that the vortices and phase shifts of the flow induce intertwined lamellar structures, thus increasing the contact surface and enhancing mixing. The optimization improves the mixing while using a low flow rate, hence a small volume for mixing and moderate pressure drops. The performances of the patterns were first simulated using COMSOL Multiphysics under different operating conditions. The simulation indicates that at very low flow rate (1-12 µL·min-1) and Re (3.3-40), as well as a very small working volume (~ 3 nL), a very good mixing (~ 98%) can be achieved in the ms time range (4.5-78 ms). The most promising design was then visualized experimentally, showing results that are consistent with the outcomes of the simulations. Importantly, the devices were fabricated using a classical soft-lithography method, as opposed to additive manufacturing often used to generate complex mixing structures. This new device minimizes the sample consumption and could therefore be applied for studies using precious samples.

Janus Photothermal Membrane as an Energy Generator and a Mass-Transfer Accelerator for High-Efficiency Solar-Driven Membrane Distillation.

Membrane distillation (MD) is an emerging membrane-based evaporation technology with great promise for the desalination and separation industries. However, its widespread application still depends on substantial development to increase the distillation flux, reduce the energy consumption, and extend the lifespan of the membrane. Herein, we report for the first time the integration of multiple functions, that is, energy-saving, flux-enhancing, and anti-fouling properties, into a single membrane. Such a membrane was fabricated by coating the top surface of a poly(vinylidene fluoride)-co-hexafluoropropylene (PVDF-HFP) nanofibrous mat with photothermal and hydrophobic graphitic carbon spheres and subsequently coating the bottom surface with a hydrophilic polydopamine layer, yielding a novel Janus photothermal membrane (JPTM). Owing to the high photothermal efficiency and accelerated mass transport across the membrane, the JPTM demonstrated an excellent desalination performance when assembled into a solar-driven MD system, with a distillation flux of 1.29 kg m-2 h-1, which is 10 times higher than that of the conventional un-modified PVDF-HFP membrane, requiring only 1 kW m-2 solar illumination as the energy input.

Brain variability in dynamic resting-state networks identified by fuzzy entropy: a scalp EEG study.

Objective.Exploring the temporal variability in spatial topology during the resting state attracts growing interest and becomes increasingly useful to tackle the cognitive process of brain networks. In particular, the temporal brain dynamics during the resting state may be delineated and quantified aligning with cognitive performance, but few studies investigated the temporal variability in the electroencephalogram (EEG) network as well as its relationship with cognitive performance.Approach.In this study, we proposed an EEG-based protocol to measure the nonlinear complexity of the dynamic resting-state network by applying the fuzzy entropy. To further validate its applicability, the fuzzy entropy was applied into simulated and two independent datasets (i.e. decision-making and P300).Main results.The simulation study first proved that compared to the existing methods, this approach could not only exactly capture the pattern dynamics in time series but also overcame the magnitude effect of time series. Concerning the two EEG datasets, the flexible and robust network architectures of the brain cortex at rest were identified and distributed at the bilateral temporal lobe and frontal/occipital lobe, respectively, whose variability metrics were found to accurately classify different groups. Moreover, the temporal variability of resting-state network property was also either positively or negatively related to individual cognitive performance.Significance.This outcome suggested the potential of fuzzy entropy for evaluating the temporal variability of the dynamic resting-state brain networks, and the fuzzy entropy is also helpful for uncovering the fluctuating network variability that accounts for the individual decision differences.

Short-Term Impact of Sleep Apnea/Hypopnea on the Interaction Between Various Cortical Areas.

INTRODUCTION: Sleep apnea/hypopnea syndrome (SAHS) can change brain structure and function. These alterations are related to respiratory event-induced abnormal sleep, however, how brain activity changes during these events is less well understood. METHODS: To study information content and interaction among various cortical regions, we analyzed the variations of permutation entropy (PeEn) and symbolic transfer entropy (STE) of electroencephalography (EEG) activity during respiratory events. In this study, 57 patients with moderate SAHS were enrolled, including 2804 respiratory events. The events terminated with cortical arousal were independently researched. RESULTS: PeEn and STE were lower during apnea/hypopnea, and most of the brain interaction was higher after apnea/hypopnea termination than that before apnea in N2 stage. As indicated by STE, the respiratory events also affected the stability of information transmission mode. In N1, N2, and rapid eye movement (REM) stages, the information flow direction was posterior-to-anterior, but the anterior-to-posterior increased relatively during apnea/hypopnea. The above EEG activity trends maintained in events with cortical arousal. CONCLUSIONS: These results may be related to the intermittent hypoxia during apnea and the cortical response. Furthermore, increased frontal information outflow, which was related to the compensatory activation of frontal neurons, may associate with cognitive function.

Combining Dual-Light Emissions to Achieve Efficient Broadband Yellowish-Green Luminescence in One-Dimensional Hybrid Lead Halides.

In recent years, low-dimensional lead halides have emerged as some of most attractive photoelectric materials due to their intrinsic broadband emissions with a potential application in white-light emitting diodes. To achieve the desired performance, tremendous research has emphasized the modulation of inorganic components as optical centers; however, less work has paid attention to the direct contribution of the organic components. Herein, we successfully assembled two new hybrid lead halides of [H2BPP]Pb2X6 (X = Br, 1, and Cl, 2) containing one-dimensional double [Pb2X6]2- chains using optically active 1,3-bis(4-pyridyl)-propane (BPP) as an organic cation. Under UV-light excitation, compounds 1 and 2 exhibit broadband yellowish-green emissions, which were verified by promising photoluminescence quantum efficiencies (PLQEs) of 8.10% and 4.84%, respectively. The broadband light emissions are derived from the combination of dual higher-energy blue and lower-energy yellow light spectra, which can be attributed to the individual contributions of the organic and inorganic components, respectively, according to the time-resolved and temperature-dependent emission spectra as well as theoretical calculations. This work proves the great contribution of organic components to the photophysical properties and provides a new design strategy to realize broadband light emission by rationally combining the dual-emitting properties of different assembly blocks.

Discrimination of Tourette Syndrome Based on the Spatial Patterns of the Resting-State EEG Network.

Tourette syndrome (TS) is a neuropsychiatric disorder with childhood onset characterized by chronic motor and vocal tics; however, the current diagnosis of TS patients is subjective, as it is mainly assessed based on the parents' description alongside specific evaluations. The early and accurate diagnosis of TS based on its potential symptoms in children would be of benefit in their future therapy, but reliable diagnoses are difficult due to the lack of objective knowledge of the etiology and pathogenesis of TS. In this study, resting-state electroencephalograms were first collected from 36 patients and 21 healthy controls (HCs); the corresponding resting-state functional networks were then constructed, and the potential differences in network topology between the two groups were extracted by using the topology of the spatial pattern of the network (SPN). Compared to the HCs, the TS patients exhibited decreased frontotemporal/occipital/parietal connectivity. When classifying the two groups, compared to the network properties, the derived SPN features achieved a much higher accuracy of 92.31%. The intrinsic long-range connectivity between the frontal and the temporal/occipital/parietal lobes was damaged in the patient group, and this dysfunctional network pattern might serve as a reliable biomarker to differentiate TS patients from HCs as well as to assess the severity of tic symptoms.

Peritumoral activated hepatic stellate cells are associated with hepatic recurrence for resectable colorectal adenocarcinoma liver metastasis following resection.

The formation of the pre-metastatic niche (PMN), which precedes the establishment of tumor lesions, plays a critical role in cancer recurrence and metastasis. Hepatic stellate cells (HSCs), a critical liver stromal cell component, can be induced to facilitate metastasis by modeling liver PMN formation. In the present study, activated HSCs were observed in the peritumor non-cancerous liver tissues (PNLT) colorectal adenocarcinoma liver metastasis (CRALM), and the density of activated HSCs was higher in PNLT compared with that in normal liver tissues (NLT). High density of activated HSC in the PNLT was positively associated with the number of tumor liver metastases (P=0.036), maximum diameter of liver metastases (P=0.002), and recurrence following synchronous radical resection (P=0.003). High density of activated HSCs in the PNLT was identified as a significant and independent prognostic factor for disease-free survival (HR, 2.083; 95% CI, 1.504-2.885; P=0.016) and overall survival (HR, 2.039; 95% CI, 1.312-3.169; P=0.019). Functionally, in vitro assays revealed that activated HSCs facilitated colorectal adenocarcinoma (CRA) cells to colonize the liver. Molecularly, it was demonstrated that the pro-recurrence of activated HSCs depended on paracrine hepatic growth factor. Taken together, the present results showed that high density of activated HSCs in the PNLT was an independent predictor for CRALM recurrence following resection, and they exerted their roles via their effect on CRA cell recruitment and proliferation by paracrine HGF.

miR-5188 augments glioma growth, migration and invasion through an SP1-modulated FOXO1-PI3K/AKT-c-JUN-positive feedback circuit.

The biological effect and molecular mechanism of miR-5188 have not been thoroughly investigated. The study aims at elucidating the role of miR-5188 in glioma progression. Human glioma cell lines and tissues were used for functional and expression analysis. Cellular and molecular techniques were performed to explore the functions and mechanisms of miR-5188 in glioma. In our investigation, we demonstrated that miR-5188 promoted cell proliferation, the G1/S transition of the cell cycle, migration and invasion in glioma and reduced the lifespan of glioma-bearing mice. miR-5188 directly targeted FOXO1 and activated PI3K/AKT-c-JUN signalling, which enhanced miR-5188 expression. Moreover, the c-JUN transcription factor functionally bound to the miR-5188 promoter region, forming the positive feedback loop. The feedback loop promoted glioma progression through activating the PI3K/AKT signalling, and this loop is augmented by the interaction between SP1 and c-JUN. Moreover, it was also found that the miR-5188/FOXO1 axis is facilitated by SP1-activated PI3K/AKT/c-JUN signalling. In glioma samples, miR-5188 expression was found to be an unfavourable factor and was positively associated with the mRNA levels of SP1 and c-JUN, whereas negatively associated with the mRNA levels of FOXO1. Our investigation demonstrates that miR-5188 could function as a tumour promoter by directly targeting FOXO1 and participating in SP1-mediated promotion of cell growth and tumorigenesis in glioma.