Intestinal Piezo1 aggravates intestinal barrier dysfunction during sepsis by mediating Ca2+ influx.

INTRODUCTION: Intestinal barrier dysfunction is a pivotal factor in sepsis progression. The mechanosensitive ion channel Piezo1 is associated with barrier function; however, its role in sepsis-induced intestinal barrier dysfunction remains poorly understood. METHODS: The application of cecal ligation and puncture (CLP) modeling was performed on both mice of the wild-type (WT) variety and those with Villin-Piezo1flox/flox genetic makeup to assess the barrier function using in vivo FITC-dextran permeability measurements and immunofluorescence microscopy analysis of tight junctions (TJs) and apoptosis levels. In vitro, Caco-2 monolayers were subjected to TNF-α incubation. Moreover, to modulate Piezo1 activation, GsMTx4 was applied to inhibit Piezo1 activation. The barrier function, intracellular calcium levels, and mitochondrial function were monitored using calcium imaging and immunofluorescence techniques. RESULTS: In the intestinal tissues of CLP-induced septic mice, Piezo1 protein levels were notably elevated compared with those in normal mice. Piezo1 has been implicated in the sepsis-mediated disruption of TJs, apoptosis of intestinal epithelial cells, elevated intestinal mucosal permeability, and systemic inflammation in WT mice, whereas these effects were absent in Villin-Piezo1flox/flox CLP mice. In Caco-2 cells, TNF-α prompted calcium influx, an effect reversed by GsMTx4 treatment. Elevated calcium concentrations are correlated with increased accumulation of reactive oxygen species, diminished mitochondrial membrane potential, and TJ disruption. CONCLUSIONS: Thus, Piezo1 is a potential contributor to sepsis-induced intestinal barrier dysfunction, influencing apoptosis and TJ modification through calcium influx-mediated mitochondrial dysfunction.

Non-volatile 2 × 2 optical switch using multimode interference in an Sb2Se3-loaded waveguide.

We propose a non-volatile 2 × 2 photonic switch based on multimode interference in an Sb2Se3-loaded waveguide. The different modal symmetries of the TE0 and TE1 modes supported in the multimode region change their propagation constants distinctly upon the Sb2Se3 phase transition. Through careful optical design and FDTD optimization of the multimode waveguide dimensions, efficient switching is achieved despite the modest index contrast of Sb2Se3 relative to Ge2Sb2Te5. The fabricated optical switch demonstrates favorable characteristics, including low insertion loss of ∼1 dB, a compact length of ∼27 µm, and small cross talk below -15 dB across a 35 nm bandwidth. Such non-volatile and broadband components will be critical for future high-density programmable photonic-integrated circuits for optical communications and signal processing.

Microbiome convergence enables siderophore-secreting-rhizobacteria to improve iron nutrition and yield of peanut intercropped with maize.

Intercropping has the potential to improve plant nutrition as well as crop yield. However, the exact mechanism promoting improved nutrient acquisition and the role the rhizosphere microbiome may play in this process remains poorly understood. Here, we use a peanut/maize intercropping system to investigate the role of root-associated microbiota in iron nutrition in these crops, combining microbiome profiling, strain and substance isolation and functional validation. We find that intercropping increases iron nutrition in peanut but not in maize plants and that the microbiota composition changes and converges between the two plants tested in intercropping experiments. We identify a Pseudomonas secreted siderophore, pyoverdine, that improves iron nutrition in glasshouse and field experiments. Our results suggest that the presence of siderophore-secreting Pseudomonas in peanut and maize intercropped plays an important role in iron nutrition. These findings could be used to envision future intercropping practices aiming to improve plant nutrition.

The efficacy of sorafenib against hepatocellular carcinoma is enhanced by 5-aza-mediated inhibition of ID1 promoter methylation.

Sorafenib resistance greatly restricts its clinical application in patients with hepatocellular carcinoma (HCC). Numerous studies have reported that ID1 exerts a crucial effect in cancer initiation and development. Our previous research revealed an inhibitory role of ID1 in sorafenib resistance. However, the upstream regulatory mechanism of ID1 expression is unclear. Here, we discovered that ID1 expression is negatively correlated with promoter methylation, which is regulated by DNMT3B. Knockdown of DNMT3B significantly inhibited ID1 methylation status and resulted in an increase of ID1 expression. The demethylating agent 5-aza-2'-deoxycytidine (5-aza) remarkably upregulated ID1 expression. The combination of 5-aza with sorafenib showed a synergistic effect on the inhibition of cell viability.

Safe physical interaction with cobots: a multi-modal fusion approach for health monitoring.

Health monitoring is a critical aspect of personalized healthcare, enabling early detection, and intervention for various medical conditions. The emergence of cloud-based robot-assisted systems has opened new possibilities for efficient and remote health monitoring. In this paper, we present a Transformer-based Multi-modal Fusion approach for health monitoring, focusing on the effects of cognitive workload, assessment of cognitive workload in human-machine collaboration, and acceptability in human-machine interactions. Additionally, we investigate biomechanical strain measurement and evaluation, utilizing wearable devices to assess biomechanical risks in working environments. Furthermore, we study muscle fatigue assessment during collaborative tasks and propose methods for improving safe physical interaction with cobots. Our approach integrates multi-modal data, including visual, audio, and sensor- based inputs, enabling a holistic assessment of an individual's health status. The core of our method lies in leveraging the powerful Transformer model, known for its ability to capture complex relationships in sequential data. Through effective fusion and representation learning, our approach extracts meaningful features for accurate health monitoring. Experimental results on diverse datasets demonstrate the superiority of our Transformer-based multi- modal fusion approach, outperforming existing methods in capturing intricate patterns and predicting health conditions. The significance of our research lies in revolutionizing remote health monitoring, providing more accurate, and personalized healthcare services.

PD-L1 expression-related PI3K pathway correlates with immunotherapy efficacy in gastric cancer.

Background: The programed death ligand-1 combined positive score (PD-L1 CPS), the only FDA-approved biomarker for immune checkpoint inhibitor therapy in gastric cancer (GC) patients, is an important but imperfect predictive biomarker. The molecular characteristics of tumors that influence the PD-L1 CPS are largely unknown and would be helpful for screening patients who would benefit from immunotherapy. Methods: PD-L1 immunohistochemistry (IHC) and targeted next-generation sequencing techniques were used to compare genomic alterations in 492 GC patients in two groups (PD-L1 CPS ⩾ 1, positive; CPS < 1, negative). Screened PD-L1 expression-related factors were analyzed for immunotherapy efficacy in three distinct GC cohorts from public databases. Results: Positive PD-L1 expression occurred in 40% of GC patients and was associated with a higher proportion of phosphatidylinositol 3-kinase (PI3K), SWItch/Sucrose NonFermentable (SWI/SNF), lysine demethylase (KDM), and DNA (cytosine-5)-methyltransferase (DNMT) (all p < 0.01), pathway alterations. Compared to wild-type GC patients, those with PI3K pathway alterations had a higher response rate (p = 0.002) and durable clinical benefit rate with immunotherapy (p = 0.023, p = 0.038) as well as longer progression-free survival (p = 0.084, p = 0.0076) and overall survival (p = 0.2, p = 0.037) with immunotherapy. Conclusion: This study revealed PD-L1 expression-related factors in the tumor genome in a GC cohort. Alterations in the PI3K pathway associated with PD-L1 positivity were shown to be associated with better immunotherapy efficacy in three distinct GC cohorts from public databases. Our results provide a potential avenue for patient selection and rational immune combination development for GC patients.

Experimental Study on the Mechanical Properties and Influencing Factors of Glass Fiber-Reinforced Permeable Concrete.

In order to improve the mechanical properties and deformation characteristics of permeable concrete, glass fiber was added to this type of concrete. Based on an unconfined compressive strength test, non-contact full-field strain measurement system, and scanning electron microscopy test, the effects of aggregate particle composition, shaking time, fly ash content, fiber length, and fiber content on the strength and permeability of permeable concrete were studied. The results show that the strength and water permeability of permeable concrete are negatively correlated with an increase in shaking time. When the aggregate particle size is 5-10 mm, the permeable concrete has both good strength and permeability. Proper incorporation of fly ash improves the compactness inside the structure. The influence of different lengths of glass fiber on the strength of permeable concrete first increases and then decreases, and the permeable property decreases. With the same fiber length, the strength increases first and then decreases with an increase in the content, while the porosity and water permeability coefficient decrease. Under the test conditions, when the length of glass fiber is 6 mm, and the dosage is 2 kg/m3, the strength performance of permeable concrete is the best, and the permeability effect is good at the same time.

Integration of natural and deep artificial cognitive models in medical images: BERT-based NER and relation extraction for electronic medical records.

Introduction: Medical images and signals are important data sources in the medical field, and they contain key information such as patients' physiology, pathology, and genetics. However, due to the complexity and diversity of medical images and signals, resulting in difficulties in medical knowledge acquisition and decision support. Methods: In order to solve this problem, this paper proposes an end-to-end framework based on BERT for NER and RE tasks in electronic medical records. Our framework first integrates NER and RE tasks into a unified model, adopting an end-to-end processing manner, which removes the limitation and error propagation of multiple independent steps in traditional methods. Second, by pre-training and fine-tuning the BERT model on large-scale electronic medical record data, we enable the model to obtain rich semantic representation capabilities that adapt to the needs of medical fields and tasks. Finally, through multi-task learning, we enable the model to make full use of the correlation and complementarity between NER and RE tasks, and improve the generalization ability and effect of the model on different data sets. Results and discussion: We conduct experimental evaluation on four electronic medical record datasets, and the model significantly out performs other methods on different datasets in the NER task. In the RE task, the EMLB model also achieved advantages on different data sets, especially in the multi-task learning mode, its performance has been significantly improved, and the ETE and MTL modules performed well in terms of comprehensive precision and recall. Our research provides an innovative solution for medical image and signal data.

MBGA-Net: A multi-branch graph adaptive network for individualized motor imagery EEG classification.

BACKGROUND AND OBJECTIVE: The development of deep learning has led to significant improvements in the decoding accuracy of Motor Imagery (MI) EEG signal classification. However, current models are inadequate in ensuring high levels of classification accuracy for an individual. Since MI EEG data is primarily used in medical rehabilitation and intelligent control, it is crucial to ensure that each individual's EEG signal is recognized with precision. METHODS: We propose a multi-branch graph adaptive network (MBGA-Net), which matches each individual EEG signal with a suitable time-frequency domain processing method based on spatio-temporal domain features. We then feed the signal into the relevant model branch using an adaptive technique. Through an enhanced attention mechanism and deep convolutional method with residual connectivity, each model branch more effectively harvests the features of the related format data. RESULTS: We validate the proposed model using the BCI Competition IV dataset 2a and dataset 2b. On dataset 2a, the average accuracy and kappa values are 87.49% and 0.83, respectively. The standard deviation of individual kappa values is only 0.08. For dataset 2b, the average classification accuracies obtained by feeding the data into the three branches of MBGA-Net are 85.71%, 85.83%, and 86.99%, respectively. CONCLUSIONS: The experimental results demonstrate that MBGA-Net could effectively perform the classification task of motor imagery EEG signals, and it exhibits strong generalization performance. The proposed adaptive matching technique enhances the classification accuracy of each individual, which is beneficial for the practical application of EEG classification.

Role of magnetic resonance imaging in the diagnosis of placenta accreta.

INTRODUCTION: To analyze the value of magnetic resonance imaging (MRI) in suspicious cases for prenatal detection of placenta accreta (PA). MATERIALS AND METHODS: A total of 50 placental MRI exams performed on a 1.5T scanner were retrospectively reviewed by two radiologists in consensus.HASTE(half-Fourier acquisition single-shot turbo spin echo)and True-FISP (true fast imaging with steady-state precession) sequences were acquired. Findings from MRI were compared with the final diagnosis, which was determined by clinical findings at delivery and pathological examination of specimens. RESULTS: Of 50 pregnant women in the analysis, 33 required cesarean hysterectomy, and 17 underwent cesarean delivery.MRI signs such as myometrial thinning, loss of T2 hypointense interface(loss of retroplacental clear space on US), heterogenous intraplacental sign, and intraplacental T2 dark bands were more likely to be seen in this group. In this group, the cases that were finally clinically and pathologically confirmed were 12, 16, and 22 cases of placenta accreta vera, placenta increta, and placenta percreta respectively. CONCLUSION: MRI is particularly useful in cases where US is inconclusive and to assess the extent to which the placenta penetrates the uterine serosa and invades outward into surrounding tissues.MRI has become a routine examination for patients with suspected PA in clinical practice.

Insights into the Electronic Structure Effect of SnMnOx Nanorod Catalysts for Low-Temperature Catalytic Combustion of o-Dichlorobenzene.

For the catalytic combustion reaction of chlorinated volatile organic compounds (CVOCs), the redox properties and acid sites of the catalyst surface are key factors in determining the activity, selectivity, and chlorine-resistance stability. Herein, a series of SnMnOx catalysts for the catalytic combustion of CVOCs were prepared by the changing of Sn-doping way to regulate the electron valance state of Mn element, including reflux (R-SnMnOx ), co-precipitation (C-SnMnOx ) and impregnation (I-SnMnOx ). It was discovered that the R-SnMnOx catalyst had better activity and chlorine resistance than the R-MnOx , C-SnMnOx and I-SnMnOx catalyst, and we discovered that the doping ways of Sn in MnOx catalyst could regulate greatly the surface acidity, active oxygen species, the chemical state of Mnn+ species, and redox ability. Especially, the R-SnMnOx catalysts exhibit excellent water resistance, and the reasons were related to the strong interaction of Snn+ and Mnn+ , which could promote obviously the dispersion of active Mn species, form a large number of acid sites, provide the abundant lattice oxygen species, and own the excellent redox ability, which accelerate the rate of charge transfer between Snn+ and Mnn+ (Sn4+ +Mn2+ →Sn2+ +Mn4+ ) to produce the abundant active species and accelerate the rapid conversion of benzene and intermediates conversion.

Compact nonvolatile polarization switch using an asymmetric Sb2Se3-loaded silicon waveguide.

We propose and simulate a compact (∼29.5 µm-long) nonvolatile polarization switch based on an asymmetric Sb2Se3-clad silicon photonic waveguide. The polarization state is switched between TM0 and TE0 mode by modifying the phase of nonvolatile Sb2Se3 between amorphous and crystalline. When the Sb2Se3 is amorphous, two-mode interference happens in the polarization-rotation section resulting in efficient TE0-TM0 conversion. On the other hand, when the material is in the crystalline state, there is little polarization conversion because the interference between the two hybridized modes is significantly suppressed, and both TE0 and TM0 modes go through the device without any change. The designed polarization switch has a high polarization extinction ratio of > 20 dB and an ultra-low excess loss of < 0.22 dB in the wavelength range of 1520-1585 nm for both TE0 and TM0 modes.

A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations.

Background: TP53 is one of the most frequent mutated genes in colon cancer. Although colon cancer with TP53 mutations has a high risk of metastasis and worse prognosis generally, it showed high heterogeneity clinically. Methods: A total of 1,412 colon adenocarcinoma (COAD) samples were obtained from two RNA-seq cohorts and three microarray cohorts, including the TCGA-COAD (N = 408), the CPTAC-COAD (N = 106), GSE39582 (N = 541), GSE17536 (N = 171) and GSE41258 (N = 186). The LASSO-Cox method was used to establish the prognostic signature based on the expression data. The patients were divided into high-risk and low-risk groups based on the median risk score. The efficiency of the prognostic signature was validated in various cohorts, including TP53-mutant and TP53 wild-type. The exploration of potential therapeutic targets and agents was performed by using the expression data of TP53-mutant COAD cell lines obtained from the CCLE database and the corresponding drug sensitivity data obtained from the GDSC database. Results: A 16-gene prognostic signature was established in TP53-mutant COAD. The high-risk group had significantly inferior survival time compared to the low-risk group in all TP53-mutant datasets, while the prognostic signature failed to classify the prognosis of COAD with TP53 wild-type properly. Besides, the risk score was the independent poor factor for the prognosis in TP53-mutant COAD and the nomogram based on the risk score was also shown good predictive efficiency in TP53-mutant COAD. Moreover, we identified SGPP1, RHOQ, and PDGFRB as potential targets for TP53-mutant COAD, and illuminated that the high-risk patients might benefit from IGFR-3801, Staurosporine, and Sabutoclax. Conclusion: A novel prognostic signature with great efficiency was established especially for COAD patients with TP53 mutations. Besides, we identified novel therapeutic targets and potential sensitive agents for TP53-mutant COAD with high risk. Our findings provided not only a new strategy for prognosis management but also new clues for drug application and precision treatment in COAD with TP53 mutations.

Predicting clinically significant prostate cancer with a deep learning approach: a multicentre retrospective study.

PURPOSE: This study aimed to develop deep learning (DL) models based on multicentre biparametric magnetic resonance imaging (bpMRI) for the diagnosis of clinically significant prostate cancer (csPCa) and compare the performance of these models with that of the Prostate Imaging and Reporting and Data System (PI-RADS) assessment by expert radiologists based on multiparametric MRI (mpMRI). METHODS: We included 1861 consecutive male patients who underwent radical prostatectomy or biopsy at seven hospitals with mpMRI. These patients were divided into the training (1216 patients in three hospitals) and external validation cohorts (645 patients in four hospitals). PI-RADS assessment was performed by expert radiologists. We developed DL models for the classification between benign and malignant lesions (DL-BM) and that between csPCa and non-csPCa (DL-CS). An integrated model combining PI-RADS and the DL-CS model, abbreviated as PIDL-CS, was developed. The performances of the DL models and PIDL-CS were compared with that of PI-RADS. RESULTS: In each external validation cohort, the area under the receiver operating characteristic curve (AUC) values of the DL-BM and DL-CS models were not significantly different from that of PI-RADS (P > 0.05), whereas the AUC of PIDL-CS was superior to that of PI-RADS (P < 0.05), except for one external validation cohort (P > 0.05). The specificity of PIDL-CS for the detection of csPCa was much higher than that of PI-RADS (P < 0.05). CONCLUSION: Our proposed DL models can be a potential non-invasive auxiliary tool for predicting csPCa. Furthermore, PIDL-CS greatly increased the specificity of csPCa detection compared with PI-RADS assessment by expert radiologists, greatly reducing unnecessary biopsies and helping radiologists achieve a precise diagnosis of csPCa.

The active Fe chelator proline-2'-deoxymugineic acid enhances peanut yield by improving soil Fe availability and plant Fe status.

Iron (Fe) deficiency restricts crop yields in calcareous soil. Thus, a novel Fe chelator, proline-2'-deoxymugineic acid (PDMA), based on the natural phytosiderophore 2'-deoxymugineic acid (DMA), was developed to solve the Fe deficiency problem. However, the effects and mechanisms of PDMA relevant to the Fe nutrition and yield of dicots grown under field conditions require further exploration. In this study, pot and field experiments with calcareous soil were conducted to investigate the effects of PDMA on the Fe nutrition and yield of peanuts. The results demonstrated that PDMA could dissolve insoluble Fe in the rhizosphere and up-regulate the expression of the yellow stripe-like family gene AhYSL1 to improve the Fe nutrition of peanut plants. Moreover, the chlorosis and growth inhibition caused by Fe deficiency were significantly diminished. Notably, under field conditions, the peanut yield and kernel micronutrient contents were promoted by PDMA application. Our results indicate that PDMA promotes the dissolution of insoluble Fe and a rich supply of Fe in the rhizosphere, increasing yields through integrated improvements in soil-plant Fe nutrition at the molecular and ecological levels. In conclusion, the efficacy of PDMA for improving the Fe nutrition and yield of peanut indicates its outstanding potential for agricultural applications.

Short-Chain Fatty Acids Reduce Oligodendrocyte Precursor Cells Loss by Inhibiting the Activation of Astrocytes via the SGK1/IL-6 Signalling Pathway.

Short-chain fatty acids (SCFAs) are known to be actively involved in neurological diseases, but their roles in hypoxic-ischaemic brain injury (HIBI) are unclear. In this study, a rat model of HIBI was established, and this study measured the changes in IL-6 and NOD-like receptor thermal protein domain associated protein 3 (NLRP3), in addition to proliferation and apoptosis indicators of oligodendrocyte precursor cells (OPCs). The mechanism of action of SCFA on astrocytes was also investigated. Astrocytes were subjected to hypoxia in vitro, and OPCs were treated with IL-6. The results showed that SCFAs significantly alleviated HIBI-induced activation of astrocytes and loss of OPCs. SCFA pretreatment (1) downregulated the expression of NLRP3, IL-6, CCL2, and IP-10; (2) had no effect on the proliferation of OPCs; (3) ameliorated the abnormal expression of Bax and Bcl-2; and (4) regulated IL-6 expression via the SGK1-related pathway in astrocytes. Our findings revealed that SCFAs alleviated the loss of OPCs by regulating astrocyte activation through the SGK1/IL-6 signalling pathway.

Radiographic analysis of dynamic lumbar motion during the five-repetition sit-to-stand test in degenerative lumbar spondylolisthesis.

BACKGROUND: To investigate the mechanisms of low back pain triggered by the five-repetition sit-to-stand test (5R-STS test) in degenerative lumbar spondylolisthesis (DLS) from radiographic perspective, as well as to determine the most useful diagnostic modalities in the evaluation of segmental instability. METHODS: We retrospectively performed a study of 78 patients (23 men and 55 women) with symptomatic DLS at L4/5 in our institution between April 2020 and December 2021. Each patient was assessed by using the 5R-STS test and received a series of radiographs including the upright standing, normal sitting, standing flexion-extension radiographs, and supine sagittal MR images. Enrolled patients were divided into two groups based on the 5R-STS test score: severe group and mild group. Translational and angular motion was determined by comparing normal sitting radiograph (N) with upright standing radiograph (U) (Combined, NU), flexion/extension radiographs (FE) as well as normal sitting radiograph (N) with a supine sagittal MR image (sMR) (Combined, N-sMR). RESULTS: Overall, 78 patients were enrolled, and there were 31(39.7%) patients in group S and 47(60.3%) patients in group M, with an average age of 60.7 ± 8.4 years. The normal sitting radiograph demonstrated the maximum slip percentage (SP) and the highest kyphotic angle both in group S and group M. Compared with group M, group S revealed significantly higher SP in the normal sitting position (24.1 vs 19.6; p = 0.002). The lumbar slip angular in group S with a sitting position was significantly higher than that in group M (-5.2 vs -1.3; p < 0.001). All patients in group S had objective functional impairment (OFI) and 28 patients of them were diagnosed with lumbar instability by using the combination of normal sitting radiograph (N) and supine sagittal MR image (sMR) (Combined, N-sMR). CONCLUSION: DLS patients with positive sign of the 5R-STS test is a distinct subgroup associated with lumbar instability. The modality of the combination of normal sitting radiograph (N) and supine sagittal MR image (sMR) had a significant advantage in terms of the ability to identify segmental instability.

Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography.

Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this work, we used unmanned aerial vehicle infrared thermal imaging technology to monitor the construction work. By analyzing the temperature distribution at the paving site, and conducting laboratory tests, the relationship between the melt temperature, high-temperature stability, and water stability of the asphalt mix was assessed. The results showed that the optimal temperature measurement height for an unmanned aerial vehicle (UAV) with an infrared thermal imager was 7-8 m. By coring the representative temperature points on the construction site and then conducting a Hamburg wheel tracking (HWT) test, the test results were verified through the laboratory test results in order to establish a prediction model for the melt temperature and high-temperature stability of y = 10.73e0.03x + 1415.78, where the predictive model for the melt temperature and water was y = -19.18e-0.02x + 98.03. The results showed that using laboratory tests combined with UAV infrared thermography could quickly and accurately predict the road performance of asphalt mixtures during paving. We hope that more extensive evaluations of the roadworthiness of asphalt mixtures using paving temperatures will provide reference recommendations in the future.

Integrative Analysis of the Expression Levels and Prognostic Values for NEK Family Members in Breast Cancer.

Background: In the latest rankings, breast cancer ranks first in incidence and fifth in mortality among female malignancies worldwide. Early diagnosis and treatment can improve the prognosis and prolong the survival of breast cancer (BC) patients. The NIMA-related kinase (NEK), a group of serine/threonine kinase, is a large and conserved gene family that includes NEK1-NEK11. The NEK plays a pivotal role in the cell cycle and microtubule formation. However, an integrative analysis of the effect and prognosis value of NEK family members on BC patients is still lacking. Methods: In this study, the expression profiles of NEK family members in BC and its subgroups were analyzed using UALCAN, GEPIA2, and Human Protein Atlas datasets. The prognostic values of NEK family members in BC were evaluated using the Kaplan-Meier plotter. Co-expression profiles and genetic alterations of NEK family members were analyzed using the cBioPortal database. The function and pathway enrichment analysis of the NEK family were performed using the WebGestalt database. The correlation analysis of the NEK family and immune cell infiltration in BC was conducted using the TIMER 2.0 database. Results: In this study, we compared and analyzed the prognosis values of the NEKs. We found that NEK9 was highly expressed in normal breast tissues than BC, and NEK2, NEK6, and NEK11 were significantly highly expressed in BC than adjacent normal tissues. Interestingly, the expression levels of NEK2, NEK6, and NEK10 were not only remarkably correlated with the tumor stage but also with the molecular subtype. Through multilevel research, we found that high expression levels of NEK1, NEK3, NEK8, NEK9, NEK10, and NEK11 suggested a better prognosis value in BC, while high expression levels of NEK2 and NEK6 suggested a poor prognosis value in BC. Conclusion: Our studies show the prognosis values of the NEKs in BC. Thus, we suggest that NEKs may be regarded as novel biomarkers for predicting potential prognosis values and potential therapeutic targets of BC patients.

Hsa_circ_0006677 regulates special AT-rich binding protein-2-mediated tumor-suppressive effect via functioning as a miR-1245a sponge in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is still one of the most challenging malignant tumors. Deregulation of circular RNAs (circRNAs) is associated with NSCLC progression. However, the regulatory mechanism of circRNAs in NSCLC still needs to be studied. We selected a differentially expressed hsa_circ_0006677 (circ_0006677) in NSCLC through analyzing the GSE158695 and GSE112214 datasets. Expression of circ_0006677 was evaluated by real-time quantitative polymerase-chain reaction (RT-qPCR). Effects of circ_0006677 overexpression on NSCLC cell proliferation, apoptosis, migration, invasion, and stemness were determined by clonogenic, 5-ethynyl-2'-deoxyuridine (EdU), flow cytometry, transwell, and sphere formation assays. The regulatory mechanism of circ_0006677 was predicted by bioinformatics analysis and verified by dual-luciferase reporter and RIP assays. Animal experiments were carried out to validate the function of circ_0006677 in vivo. We observed the downregulation of circ_0006677 in NSCLC samples and cells. Functionally, circ_0006677 overexpression decreased xenograft tumor growth and restrained NSCLC cell proliferation, invasion, migration, stemness, and induced NSCLC cell apoptosis in vitro. Molecular mechanism experiments exhibited that circ_0006677 functioned as a miR-1245a sponge and mediated SATB2 expression through adsorbing miR-1245a. Either miR-1245a overexpression or SATB2 knockdown weakened circ_0006677 overexpression-mediated repression on proliferation, invasion, migration, and stemness. In conclusion, circ_0006677 regulated SATB2-mediated tumor-suppressive effect via acting as a miR-1245a sponge in NSCLC, providing a new mechanism for understanding the progression of NSCLC.