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Abstract Background Squamous metaplasia (SM) is an irreversible form of airway epithelial remodeling. Hyperproliferation of basal cells was observed in squamous metaplastic epithelium of chronically inflamed airway. However, the association of such aberrant proliferation of basal cells with SM in the nasal epithelium after radiation damage remains unclear. The aim of this study was to investigate SM and accompanying levels of p63+Krt5+ (basal cell markers) cells in the nasal epithelium of patients with radiation-induced chronic rhinosinusitis (CRSr) and patients with chronic rhinosinusitis without nasal polyps (CRSsNP) compared to healthy controls. Methods We assessed the prevalence of SM and the expression of p63+, Krt5+, p63+Krt5+, and Ki67+ cells through immunofluorescence(IF) staining of the inferior turbinate (IT) tissues from patients with CRSr (n = 36), CRSsNP (n = 33) and controls (n = 28). Results The prevalence of SM and the number of p63+Krt5+ cells were both significantly increased in patients with CRSr compared to patients with CRSsNP and controls. The number of Ki67+ cells were both significantly increased in patients with CRSr and CRSsNP compared to controls, but the ratio of Ki67+ cells to p63+Krt5+ cells was significantly lower in patients with CRSr compared to patients with CRSsNP. In patients with CRSr, an increased number of p63+Krt5+ basal cells was observed in SM epithelium compared to non-SM epithelium. Conclusion SM is increased in the nasal epithelium of patients with CRSr, in which aberrant levels of p63+Krt5+ basal cells serves as an important pathologic feature in the squamous metaplastic epithelium.

Abstract Background Acute lymphoblastic leukemia (ALL) is an aggressive hematopoietic malignancy that is most commonly observed in children. Alantolactone (ALT) has been reported to exhibit anti-tumor activity in different types of cancer. The aim of the present study was to investigate the anti-tumor activity and molecular mechanism of ALT in ALL. Methods ALL cell lines were treated with 1, 5 and 10 μM ALT, and cell viability was assessed using an MTT assay and RNA sequencing. Flow cytometry, JC-1 staining and immunofluorescence staining assays were used to measure cell apoptosis and autophagy. Additionally, western blot analysis was used to detect expression of apoptosis and autophagy related proteins. Finally, the effects of ALT on tumor growth were assessed in a BV173 xenograft nude mouse model. Results ALT inhibited the proliferation of ALL cells in a dose-dependent manner. Additionally, it was demonstrated that ALT inhibited cell proliferation, colony formation, autophagy, induced apoptosis and reduced tumor growth in vivo through upregulating the expression of adaptor related protein complex 2 subunit mu 1 (AP2M1). Moreover, the autophagy activator rapamycin, attenuated the pro-apoptotic effects of ALT on BV173 and NALM6 cell lines. Overexpression of AP2M1 decreased the expression of Beclin1 and the LC3-II/LC3-1 ratio, and increased p62 expression. Knockdown of Beclin1 increased the levels of bax, cleaved caspase 3 and cytochrome C, and decreased bcl-2 expression. Conclusions The present study demonstrated that ALT exerts anti-tumor activity through inducing apoptosis and inhibiting autophagy by upregulating AP2M1 in ALL, highlighting a potential therapeutic strategy for treatment of ALL.

Abstract Background Among eukaryotic organisms, alternative splicing is an important process that can generate multiple transcripts from one same precursor messenger RNA, which greatly increase transcriptome and proteome diversity. This process is carried out by a super-protein complex defined as the spliceosome. Specifically, splicing factor 1/branchpoint binding protein (SF1/BBP) is a single protein that can bind to the intronic branchpoint sequence (BPS), connecting the 5′ and 3′ splice site binding complexes during early spliceosome assembly. The molecular function of this protein has been extensively investigated in yeast, metazoa and mammals. However, its counterpart in plants has been seldomly reported. Results To this end, we conducted a systematic characterization of the SF1 gene family across plant lineages. In this work, a total of 92 sequences from 59 plant species were identified. Phylogenetic relationships of these sequences were constructed, and subsequent bioinformatic analysis suggested that this family likely originated from an ancient gene transposition duplication event. Most plant species were shown to maintain a single copy of this gene. Furthermore, an additional RNA binding motif (RRM) existed in most members of this gene family in comparison to their animal and yeast counterparts, indicating that their potential role was preserved in the plant lineage. Conclusion Our analysis presents general features of the gene and protein structure of this splicing factor family and will provide fundamental information for further functional studies in plants.

Abstract Well water could be a stable source of drinking water. Recently, the use of well water as drinking water has been encouraged in developing countries. However, many kinds of disorders caused by toxic elements in well drinking water have been reported. It is our urgent task to resolve the global issue of element-originating diseases. In this review article, our multidisciplinary approaches focusing on oncogenic toxicities and disturbances of sensory organs (skin and ear) induced by arsenic and barium are introduced. First, our environmental monitoring in developing countries in Asia showed elevated concentrations of arsenic and barium in well drinking water. Then our experimental studies in mice and our epidemiological studies in humans showed arsenic-mediated increased risks of hyperpigmented skin and hearing loss with partial elucidation of their mechanisms. Our experimental studies using cultured cells with focus on the expression and activity levels of intracellular signal transduction molecules such as c-SRC, c-RET, and oncogenic RET showed risks for malignant transformation and/or progression arose from arsenic and barium. Finally, our original hydrotalcite-like compound was proposed as a novel remediation system to effectively remove arsenic and barium from well drinking water. Hopefully, comprehensive studies consisting of (1) environmental monitoring, (2) health risk assessments, and (3) remediation will be expanded in the field of environmental health to prevent various disorders caused by environmental factors including toxic elements in drinking water.

A dielectric barrier discharge plasma controlled diffusion flame experimental system was built based on the designed coaxial swirling plasma injector. The air plasma was generated within the annulus gap of the injector by alternating current dielectric barrier discharge. The discharge characteristics and power of plasma injector under different actuation intensities and air flowrates were measured. Through the measurement techniques, such as schlieren imaging, broadband chemiluminescence image and CH* chemiluminescence, the effect and mechanism of plasma on ethylene-air normal diffusive jet and flame was explored. The results showed that a large number of filamentary discharge channels are formed in air plasma. The increase of air flowrates weakened the intensity of discharge to a certain extent. The induced jet generated by the plasma can short the laminar length of the ethylene-air jet, accelerate the transition of the flow jet, enhance the turbulence and the mixing of the fuel and the oxidizer. The higher the actuation intensity, the shorter distance of the cold jet transition zone, the higher the jet turbulence. Depending on the aerodynamic and kinetic effects, plasma can improve the stability of ethylene-air diffusive flame and reduce the lift height between the flame root and injector. The plasma can also expand the flammability limit of ethylene-air flame and make the flame ignited under some conditions that could not be. In addition, the CH* chemiluminescence shows that, in a certain range of discharge voltage, the heat release distribution can be changed on both sides of the flame, and its representative length are generally reduced as the voltage rises. On the contrary, the overtop voltage could lead to a decrease of flame heat release.

Modular design is a widely used strategy that meets diverse customer requirements. Close relationships exist between parts inside a module and loose linkages between modules in the modular products. A change of one part or module may cause changes of other parts or modules, which in turn propagate through a product. This paper aims to present an approach to analyze the associations and change impacts between modules and identify influential modules in modular product design. The proposed framework explores all possible change propagation paths (CPPs), and measures change impact degrees between modules. In this article, a design structure matrix (DSM) is used to express dependence relationships between parts, and change propagation trees of affected parts within module are constructed. The influence of the affected part in the corresponding module is also analyzed, and a reachable matrix is employed to determine reachable parts of change propagation. The parallel breadth-first algorithm is used to search propagation paths. The influential modules are identified according to their comprehensive change impact degrees that are computed by the bat algorithm. Finally, a case study on the grab illustrates the impacts of design change in modular products.

Driving behavior analysis plays an important role in improving the human-like driving capability of the Advanced Driver Assistance System (ADAS) and autonomous driving technologies. In this study, 906 data of drivers stopping normally at urban intersections were extracted from natural driving data to study reaction characteristics and braking characteristics of drivers in real road traffic. The effects of traffic state and traffic density on approach speed and reaction distance were studied using one-way ANOVA, and the relationships between maximum deceleration, average deceleration, braking duration, and influencing factors were analyzed using hierarchical multiple regression. The main results indicate the following: (1) compare with free driving, the approach speed in the following state was lower, and following traffic also caused drivers with higher speeds to further increase reaction distance in high-density traffic. (2) Traffic density only affected the approach speed in the free-driving condition. High-density traffic caused drivers to reduce speed. (3) There was a clear correlation between approach speed and reaction distance: the greater the approach speed, the longer the reaction distance. (4) The braking characteristics were mainly affected by the self-vehicle motion state. Drivers braked to a stop with greater average deceleration and maximum deceleration in a shorter time when the approach speed was higher or the reaction distance was shorter. (5) Both traffic state and traffic density had an influence on the braking characteristics. Drivers reduced average deceleration and increased braking duration in the following state and high-density traffic. (6) When following a preceding vehicle to stop, the braking characteristics of drivers were no longer influenced by the traffic density but were related to the relative motion state with the preceding vehicle. In addition to the driving behavior analysis, the identification method of traffic participants and ranging method used in this study will also advance the development of autonomous driving technologies and driver assistance systems.

The covariance evaluation for neutron cross sections in CENDL is briefly introduced in this work. The methodology for evaluation contains the nuclear reaction theoretical model-dependent approach and the non-model dependent one according to the amount of experimental data. Both approaches are based on the Generalized Least-Squares (GLSQ) method. To obtain more reliable uncertainties from experimental measurement, the analysis of the sources of experimental uncertainties (ASEU) is used rigorously in the evaluation. Moreover, machine learning (ML) methods which can deal with the data mining with a more automatic way are employed to evaluate the cross sections in a large-scale nuclear mass region to compensate the uncertainties on some nuclides and reactions, lack of experimental data for, e.g., unstable nuclei and fission products. The covariance files for 70 fission product nuclei are obtained through the model-dependent method in CENDL-3.2, and the covariances for U and Pu isotopes have also been finished with high fidelity, which will be released as part of the next CENDL.

Microglial activation and subsequent pathological neuroinflammation contribute to diabetic retinopathy (DR). However, the underlying mechanisms of microgliosis, and means to effectively suppress pathological microgliosis, remain incompletely understood. Peroxisome proliferator-activated receptor alpha (PPARα) is a transcription factor that regulates lipid metabolism. The present study aimed to determine if PPARα affects pathological microgliosis in DR. In global Pparα mice, retinal microglia exhibited decreased structural complexity and enlarged cell bodies, suggesting microglial activation. Microglia-specific conditional Pparα−/− (PCKO) mice showed decreased retinal thickness as revealed by optical coherence tomography. Under streptozotocin (STZ)-induced diabetes, diabetic PCKO mice exhibited decreased electroretinography response, while diabetes-induced retinal dysfunction was alleviated in diabetic microglia-specific Pparα-transgenic (PCTG) mice. Additionally, diabetes-induced retinal pericyte loss was exacerbated in diabetic PCKO mice and alleviated in diabetic PCTG mice. In cultured microglial cells with the diabetic stressor 4-HNE, metabolic flux analysis demonstrated that Pparα ablation caused a metabolic shift from oxidative phosphorylation to glycolysis. Pparα deficiency also increased microglial STING and TNF-α expression. Taken together, these findings revealed a critical role for PPARα in pathological microgliosis, neurodegeneration, and vascular damage in DR, providing insight into the underlying molecular mechanisms of microgliosis in this context and suggesting microglial PPARα as a potential therapeutic target.

Summary: N-type voltage-gated calcium (CaV) channels mediate Ca2+ influx at presynaptic terminals in response to action potentials and play vital roles in synaptogenesis, release of neurotransmitters, and nociceptive transmission. Here, we elucidate a cryo-electron microscopy (cryo-EM) structure of the human CaV2.2 complex in apo, ziconotide-bound, and two CaV2.2-specific pore blockers-bound states. The second voltage-sensing domain (VSD) is captured in a resting-state conformation, trapped by a phosphatidylinositol 4,5-bisphosphate (PIP2) molecule, which is distinct from the other three VSDs of CaV2.2, as well as activated VSDs observed in previous structures of CaV channels. This structure reveals the molecular basis for the unique inactivation process of CaV2.2 channels, in which the intracellular gate formed by S6 helices is closed and a W-helix from the domain II–III linker stabilizes closed-state inactivation. The structures of this inactivated, drug-bound complex lay a solid foundation for developing new state-dependent blockers for treatment of chronic pain.

Intermittent fasting (IF) has been shown beneficial in reducing metabolic diseases. Here, using a multi-omics approach in a T2D mouse model, the authors report that IF alters the composition of the gut microbiota and improves metabolic phenotypes that correlate with cognitive behavior.

Early detection and diagnosis of breast cancer are crucial to improve the survival rates of patients. Hence, pathologists and radiologists need a computer-aided diagnosis system to assist their clinical diagnoses effectively and efficiently. However, most breast cancer recognition models are faced with the sample scarcity problem, which results in serious overfitting and lowers recognition performance. To alleviate the sample scarcity problem, a simple, effective model called “refinement, correlation, adaptive” (RCA) for breast cancer recognition is proposed from the perspective of fine-grained feature selection. An innovative multiview efficient range-based gene selection algorithm is proposed to complete the first-layer feature “refinement,” which contributes to suppressing the noisy information in the original feature space. Then, more-discriminant but low-dimensional information among heterogeneous features is mined through the second-layer cross-modal “correlation” mining. Feature dimensions are reduced to a reasonable value that fits the sample size well and alleviates the overfitting problem. Finally, the last-layer decision-tree-guided “adaptive” feature selection is completed using the gradient boosting decision tree algorithm. The RCA model was validated on two well-known datasets. The experimental results demonstrate that the proposed RCA model can address the sample scarcity problem well. It outperforms state-of-the-art baselines, especially in terms of accuracy and the area of the Kiviat diagram. The largest performance improvements of the metrics are 2.39% and 1121, respectively. Moreover, an online diagnosis system based on the RCA model is proposed. It provides rapid and effective breast cancer recognition, which should make clinical diagnoses more convenient and narrow the gap between theoretical research and practical application.

Driving intention identification is a key technology which can improve the adaptability of the intelligent driver assistance systems and the energy efficiency of electric vehicles. This article proposes a novel method for identifying the driver braking intention. In order to improve the identification accuracy of driving intention, a braking intention identification model based on Long Short-Term Memory (LSTM) Network is constructed. The data of slight braking, normal braking and hard braking that can use for offline training are obtained through tests on real vehicle at Chang'an University vehicle performance testing ground. Support vector machine - recursive feature elimination (SVM-RFE) algorithm is used to select the characteristic parameter of braking intention identification model. The random search is subsequently used to optimize the hyper-parameters of LSTM. LSTM-based and Gaussian Hidden Markov Model (GHMM)-based model under different time window are used to identify braking intention of slight braking, normal braking and hard braking respectively. The results show that the Precision, Recall, F-measure, Accuracy of the braking intention identification model which propose in this paper based on LSTM are better than that of the braking intention identification model based on GHMM. Moreover, the Recall and Accuracy of the LSTM-based braking intention identification models are above 0.95, indicating the good ability of intention identification.

Image sentiment analysis is a hot research topic in the field of computer vision. However, two key issues need to be addressed. First, high-quality training samples are scarce. There are numerous ambiguous images in the original datasets owing to diverse subjective cognitions from different annotators. Second, the cross-modal sentimental semantics among heterogeneous image features has not been fully explored. To alleviate these problems, we propose a novel model called multidimensional extra evidence mining (ME2M) for image sentiment analysis, it involves sample-refinement and cross-modal sentimental semantics mining. A new soft voting-based sample-refinement strategy is designed to address the former problem, whereas the state-of-the-art discriminant correlation analysis (DCA) model is used to completely mine the cross-modal sentimental semantics among diverse image features. Image sentiment analysis is conducted based on the cross-modal sentimental semantics and a general classifier. The experimental results verify that the ME2M model is effective and robust and that it outperforms the most competitive baselines on two well-known datasets. Furthermore, it is versatile owing to its flexible structure.

Material recognition is a fundamental problem in the field of computer vision. Material recognition is still challenging because of varying camera perspectives, light conditions, and illuminations. Feature learning or feature engineering helps build an important foundation for effective material recognition. Most traditional and deep learning-based features usually point to the same or similar material semantics from diverse visual perspectives, indicating the implicit complementary information (or cross-modal semantics) among these heterogeneous features. However, only a few studies focus on mining the cross-modal semantics among heterogeneous image features, which can be used to boost the final recognition performance. To address this issue, we first improve the well-known multiset discriminant correlation analysis model to fully mine the cross-modal semantics among heterogeneous image features. Then, we propose a novel hierarchical multi-feature fusion (HMF2) model to gather effective information and create novel yet more effective and robust features. Finally, a general classifier is employed to train a new material recognition model. Experimental results demonstrate the simplicity, effectiveness, robustness, and efficiency of the HMF2 model on two benchmark datasets. Furthermore, based on the HMF2 model, we design an end-to-end online system for real-time material recognition.

Background & Aims: Psychological stress is a trigger for the development of irritable bowel syndrome and associated symptoms including abdominal pain. Although irritable bowel syndrome patients show increased activation in the limbic brain, including the amygdala, the underlying molecular and cellular mechanisms regulating visceral nociception in the central nervous system are incompletely understood. In a rodent model of chronic stress, we explored the role of microglia in the central nucleus of the amygdala (CeA) in controlling visceral sensitivity. Microglia are activated by environmental challenges such as stress, and are able to modify neuronal activity via synaptic remodeling and inflammatory cytokine release. Inflammatory gene expression and microglial activity are regulated negatively by nuclear glucocorticoid receptors (GR), which are suppressed by the stress-activated pain mediator p38 mitogen-activated protein kinases (MAPK). Methods: Fisher-344 male rats were exposed to water avoidance stress (WAS) for 1 hour per day for 7 days. Microglia morphology and the expression of phospho-p38 MAPK and GR were analyzed via immunofluorescence. Microglia-mediated synaptic remodeling was investigated by quantifying the number of postsynaptic density protein 95–positive puncta. Cytokine expression levels in the CeA were assessed via quantitative polymerase chain reaction and a Luminex assay (Bio-Rad, Hercules, CA). Stereotaxic infusion into the CeA of minocycline to inhibit, or fractalkine to activate, microglia was followed by colonic sensitivity measurement via a visceromotor behavioral response to isobaric graded pressures of tonic colorectal distension. Results: WAS induced microglial deramification in the CeA. Moreover, WAS induced a 3-fold increase in the expression of phospho-p38 and decreased the ratio of nuclear GR in the microglia. The number of microglia-engulfed postsynaptic density protein 95–positive puncta in the CeA was increased 3-fold by WAS, while cytokine levels were unchanged. WAS-induced changes in microglial morphology, microglia-mediated synaptic engulfment in the CeA, and visceral hypersensitivity were reversed by minocycline whereas in stress-naïve rats, fractalkine induced microglial deramification and visceral hypersensitivity. Conclusions: Our data show that chronic stress induces visceral hypersensitivity in male rats and is associated with microglial p38 MAPK activation, GR dysfunction, and neuronal remodeling in the CeA.

Aiming at problems of poor environmental adaptability of photoelectric navigation and low accuracy of long-term positioning of inertial navigation adopted in roadheader positioning, an inertial navigation positioning method of roadheader based on zero-velocity update was put forward based on analysis of movement characteristics of roadheader. In short stopping time interval of roadheader, velocity error curve of inertial navigation system is fitted by quadratic curve, and position error curve is obtained by integration, so as to correct position measurement value of inertial navigation system. The test results show that the inertial navigation positioning accuracy of roadheader based on zero-speed update can reach centimeter-level, fluctuation range of positioning error is small, and accumulated positioning error has no obvious increasing trend with the increase of time, which meets positioning requirements of roadheader.

Diet can protect from autoimmune disease; however, whether diet acts via the host and/or microbiome remains unclear. Here, we use a ketogenic diet (KD) as a model to dissect these complex interactions. A KD rescued the experimental autoimmune encephalomyelitis (EAE) mouse model of multiple sclerosis in a microbiota-dependent fashion. Dietary supplementation with a single KD-dependent host metabolite (β-hydroxybutyrate [βHB]) rescued EAE, whereas transgenic mice unable to produce βHB in the intestine developed more severe disease. Transplantation of the βHB-shaped gut microbiota was protective. Lactobacillus sequence variants were associated with decreased T helper 17 cell activation in vitro. Finally, we isolated an L. murinus strain that protected from EAE, which was phenocopied by a Lactobacillus metabolite enriched by βHB supplementation, indole lactate. Thus, diet alters the immunomodulatory potential of the gut microbiota by shifting host metabolism, emphasizing the utility of taking a more integrative approach to study diet-host-microbiome interactions.

BackgroundNasal inverted papilloma (NIP) is a common benign tumor. Yes-associated protein (YAP) is the core effector molecule of the Hippo pathway, which regulates the proliferation and differentiation of airway epithelium. While its role in proliferation may be connected to NIP formation, no definitive association has been made between them.MethodsWe compared the difference of YAP expression and proliferation level between the control inferior turbinate, NP (nasal polyps), and NIP groups. In addition, we further used PCR, immunofluorescence, and immunohistochemistry to investigate YAP’s role in the proliferation and differentiation of the nasal epithelium and inflammatory cell infiltration, correlating them with different grades of epithelial remodeling. We further used an IL-13 remodeling condition to investigate YAP’s role in differentiation in an in vitro air-liquid interface (ALI) human nasal epithelial cell (hNECs) model. Finally, we also explored the correlation between YAP expression and clinical indicators of NIP.ResultsThe expression of YAP/active YAP in the NIP group was significantly higher than that in the NP group and control group. Moreover, within the NIP group, the higher grade of epithelial remodeling was associated with higher YAP induced proliferation, leading to reduced ciliated cells and goblet cells. The finding was further verified using an IL-13 remodeling condition in differentiating ALI hNECs. Furthermore, YAP expression was positively correlated with proliferation and neutrophil infiltration in NIP. YAP expression was also significantly increased in NIP patients with adverse outcomes.ConclusionAbnormal expression of YAP/active YAP is associated with proliferation, differentiation, neutrophil infiltration, and adverse outcome in NIP and may present a novel target for diagnosis and intervention in NIP.

Glioblastoma (GBM) is the most common and aggressive brain tumor in adults. The aberrant activation of STAT3 commonly occurs in GBM and is a key player in GBM tumorigenesis. Yet, the aberrant activation of STAT3 signaling is not fully understood. Here, we report that SH2B adaptor protein 3 (SH2B3) is highly expressed in GBM and preferentially expressed in GBM stem cells (GSCs). Moreover, SH2B3 high expression predicts worse survival of GBM patients. Targeting SH2B3 considerably impairs GBM cell proliferation, migration, and GSCs’ self-renewal in vitro as well as xenograft tumors growth in vivo. Additionally, we provide evidence suggesting that STAT1 directly binds to the promoter of SH2B3 and activates SH2B3 expression in the transcriptional level. Functionally, SH2B3 facilitates GBM progression via physically interacting with gp130 and acting as an adaptor protein to transduce IL-6/gp130/STAT3 signaling. Together, our work firstly uncovers that the STAT1/SH2B3/gp130/STAT3 signaling axis plays critical roles in promoting GBM progression and provides insight into new prognosis marker and therapeutic target in GBM.

This work implements first-principles simulations in order to investigate the Ni-decorating property on the ZnO monolayer and the sensing property of the Ni-decorated ZnO (Ni–ZnO) monolayer upon CO and HCHO molecules formed in the dry-type transformers. The results reveal that the Ni dopant is stably anchored on the TO site of the ZnO surface forming the Ni–Zn and Ni–O bonds with the binding energy (Eb) of −1.75 eV. Based on the adsorption energy (Ead) of −1.49 and −2.22 eV for CO and HCHO on the Ni–ZnO monolayer, we determined the chemisorption for two such systems. The band structure (BS) and atomic density of state (DOS) of the gas adsorbed systems are analyzed to comprehend the electronic property of the Ni–ZnO monolayer in the gas adsorptions. Besides, the change of bandgap and work function uncover the sensing potential of Ni–ZnO monolayer upon CO and HCHO detections, with admirable electrical response (15,394.9% and −84.6%). The findings in this work manifest the potential of Ni–ZnO monolayer for CO and HCHO sensing to evaluate the operation condition of the dry-type transformers.

Glioblastoma (GBM) is the most common and aggressive brain tumor in adults. Overexpression or activation of epidermal growth factor receptor (EGFR) occurs commonly in multiple human cancers and promotes tumorigenesis. However, the underlying molecular mechanism of EGFR aberrant activation and the downstream signaling pathways remains largely unknown. In this study, we report that both SH3-domain kinase binding protein 1 (SH3KBP1) mRNA and protein levels are highly expressed in GBM and its high expression is associated with worse survival of glioma patients. In addition, we provide evidence that SH3KBP1 is prominently expressed in GBM stem cells (GSCs) and have potential to serve as a novel GSCs marker. Moreover, silencing SH3KBP1 dramatically impairs GBM cell proliferation, migration and GSCs self-renewal ability in vitro and xenograft tumors growth in vivo. Most importantly, we found that SH3KBP1 directly interacts with EGFR and may act as an adaptor protein to transduce EGFR signaling. Together, our work uncovers SH3KBP1 as a novel regulator of oncogenic EGFR signaling and also as a potential therapeutic target for GBM patients with EGFR activation.

Hepatocellular carcinoma (HCC) is one of the primary types of cancer that claims many lives worldwide, and its incidence continues to increase. Conventional therapies against liver cancer are inadequate, and the pathogenesis of HCC remains unclear. Thus, not only are more effective therapies to treat HCC required but also identification of the key genes involved in its pathogenesis is important for developing such therapies. This study found that olfactomedin 4 (OLFM4) level is higher in HCC patients than in healthy individuals. Furthermore, HCC patients also have higher messenger ribonucleic acid (mRNA) expression level in HCC tissues than in liver paracancerous tissues. OLFM4 has high predictive capacity as a biomarker for HCC and closely correlates to tumor size. It is confirmed that OLFM4 contributes to cancer cell proliferation, and HIF1α is involved in this process. Thus, the OLFM4/HIF-1α axis might be a target signaling pathway for developing novel drugs to treat HCC.

Tight junctions (TJs) are intercellular structures which are essential for epithelial barrier function and play an important role in antimicrobial defense. Epithelium dysfunction and type-2-skewed inflammation are two main pathological phenomena of chronic rhinosinusitis with nasal polyps (CRSwNP). However, the effect of pro-inflammatory type-2 cytokine IL-13 on TJs in CRSwNP is poorly understood. Nasal biopsies of CRSwNP patients and in vitro IL-13-matured human nasal epithelial cells (hNECs) were used to analyze epithelial markers and TJ proteins. Epithelium permeability, transepithelial electrical resistance (TEER), expression of TJs were quantified for IL-13-matured hNECs and that with RV infection. The expression of occludin, claudin-3, and ZO-1 were significantly decreased in CRSwNP biopsies and in hNECs after IL-13 treatment. IL-13 treatment increased epithelium permeability, decreased TEER and altered hNECs composition resulting in lesser ciliated cells and mucus over-secretion. Interestingly, claudin-3 is selectively expressed on ciliated cells. While RV infection induced minimal changes to TJs, the IL-13-matured hNECs has reduced capacity for upregulation of IFN-λ1 and CXCL10 but further increased the expression of TSLP upon RV infection. These findings suggested that IL-13-mediated dysfunction of TJs and compromised epithelial barrier. IL-13-induced cilia loss conferred lowered viral replication and impaired antiviral responses of nasal epithelium against RV infection.