Marine fungus Aspergillus c1. sp metabolite activates the HSF1/PGC-1α axis, inducing a thermogenic program for treating obesity.

Background and aims: Obesity is one of the most prevalent diseases worldwide with less ideal approved agents in clinic. Activating the HSF1/PGC-1α axis in adipose tissues has been reported to induce thermogenesis in mice, which presents a promising therapeutic avenue for obesity treatment. The present study aimed to identified novel natural HSF1 activator and evaluated the therapeutic effects of the newly discovered compound on obesity-associated metabolic disorders and the molecular mechanisms of these effects. Methods: Our previous reported HSF1/PGC-1α activator screening system was used to identify novel natural HSF1 activator. The PGC-1α luciferase activity, immunoblot, protein nuclear-translocation, immunofluorescence, chromatin immunoprecipitation assays were used to evaluate the activity of compound HN-001 in activating HSF1. The experiments of mitochondrial number measurement, TG assay and imaging, cellular metabolic assay, gene assays, and CRISPR/Cas 9 were applied for investigating the metabolic effect of HN-001 in C3H10-T1/2 adipocytes. The in vivo anti-obesity efficacies and beneficial metabolic effects of HN-001 were evaluated by performing body and fat mass quantification, plasma chemical analysis, GTT, ITT, cold tolerance test, thermogenesis analysis. Results: HN-001 dose- and time-dependently activated HSF1 and induced HSF1 nuclear translocation, resulting in an enhancement in binding with the gene Pgc-1α. This improvement induced activation of adipose thermogenesis and enhancement of mitochondrial oxidation capacity, thus inhibiting adipocyte maturation. Deletion of HSF1 in adipocytes impaired mitochondrial oxidation and abolished the above beneficial metabolic effects of HN-001, including adipocyte browning induction, improvements in mitogenesis and oxidation capacity, and lipid-lowering ability. In mice, HN-001 treatment efficiently alleviated diet-induced obesity and metabolic disorders. These changes were associated with increased body temperature in mice and activation of the HSF1/PGC-1α axis in adipose tissues. UCP1 expression and mitochondrial biogenesis were increased in both white and brown adipose tissues of HN-001-treated mice. Conclusion: These data indicate that HN-001 may have therapeutic potential for obesity-related metabolic diseases by increasing the capacity of energy expenditure in adipose tissues through a mechanism involving the HSF1/PGC-1α axis, which shed new light on the development of novel anti-obesity agents derived from marine sources.

Identification of a natural PLA2 inhibitor from the marine fungus Aspergillus sp. c1 for MAFLD treatment that suppressed lipotoxicity by inhibiting the IRE-1α/XBP-1s axis and JNK signaling.

Lipotoxicity is a pivotal factor that initiates and exacerbates liver injury and is involved in the development of metabolic-associated fatty liver disease (MAFLD). However, there are few reported lipotoxicity inhibitors. Here, we identified a natural anti-lipotoxicity candidate, HN-001, from the marine fungus Aspergillus sp. C1. HN-001 dose- and time- dependently reversed palmitic acid (PA)-induced hepatocyte death. This protection was associated with IRE-1α-mediated XBP-1 splicing inhibition, which resulted in suppression of XBP-1s nuclear translocation and transcriptional regulation. Knockdown of XBP-1s attenuated lipotoxicity, but no additional ameliorative effect of HN-001 on lipotoxicity was observed in XBP-1s knockdown hepatocytes. Notably, the ER stress and lipotoxicity amelioration was associated with PLA2. Both HN-001 and the PLA2 inhibitor MAFP inhibited PLA2 activity, reduced lysophosphatidylcholine (LPC) level, subsequently ameliorated lipotoxicity. In contrast, overexpression of PLA2 caused exacerbation of lipotoxicity and weakened the anti-lipotoxic effects of HN-001. Additionally, HN-001 treatment suppressed the downstream pro-apoptotic JNK pathway. In vivo, chronic administration of HN-001 (i.p.) in mice alleviated all manifestations of MAFLD, including hepatic steatosis, liver injury, inflammation, and fibrogenesis. These effects were correlated with PLA2/IRE-1α/XBP-1s axis and JNK signaling suppression. These data indicate that HN-001 has therapeutic potential for MAFLD because it suppresses lipotoxicity, and provide a natural structural basis for developing anti-MAFLD candidates.

Bodily expressed emotion understanding through integrating Laban movement analysis.

Bodily expressed emotion understanding (BEEU) aims to automatically recognize human emotional expressions from body movements. Psychological research has demonstrated that people often move using specific motor elements to convey emotions. This work takes three steps to integrate human motor elements to study BEEU. First, we introduce BoME (body motor elements), a highly precise dataset for human motor elements. Second, we apply baseline models to estimate these elements on BoME, showing that deep learning methods are capable of learning effective representations of human movement. Finally, we propose a dual-source solution to enhance the BEEU model with the BoME dataset, which trains with both motor element and emotion labels and simultaneously produces predictions for both. Through experiments on the BoLD in-the-wild emotion understanding benchmark, we showcase the significant benefit of our approach. These results may inspire further research utilizing human motor elements for emotion understanding and mental health analysis.

Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion: Drawing Insights From Psychology, Engineering, and the Arts, This Article Provides a Comprehensive Overview of the Field of Emotion Analysis in Visual Media and Discusses the Latest Research, Systems, Challenges, Ethical Implications, and Potential Impact of Artificial Emotional Intelligence on Society.

The emergence of artificial emotional intelligence technology is revolutionizing the fields of computers and robotics, allowing for a new level of communication and understanding of human behavior that was once thought impossible. While recent advancements in deep learning have transformed the field of computer vision, automated understanding of evoked or expressed emotions in visual media remains in its infancy. This foundering stems from the absence of a universally accepted definition of "emotion," coupled with the inherently subjective nature of emotions and their intricate nuances. In this article, we provide a comprehensive, multidisciplinary overview of the field of emotion analysis in visual media, drawing on insights from psychology, engineering, and the arts. We begin by exploring the psychological foundations of emotion and the computational principles that underpin the understanding of emotions from images and videos. We then review the latest research and systems within the field, accentuating the most promising approaches. We also discuss the current technological challenges and limitations of emotion analysis, underscoring the necessity for continued investigation and innovation. We contend that this represents a "Holy Grail" research problem in computing and delineate pivotal directions for future inquiry. Finally, we examine the ethical ramifications of emotion-understanding technologies and contemplate their potential societal impacts. Overall, this article endeavors to equip readers with a deeper understanding of the domain of emotion analysis in visual media and to inspire further research and development in this captivating and rapidly evolving field.

Single-cell transcriptomics reveals the identity and regulators of human mast cell progenitors.

Mast cell accumulation is a hallmark of a number of diseases, including allergic asthma and systemic mastocytosis. Immunoglobulin E-mediated crosslinking of the FcεRI receptors causes mast cell activation and contributes to disease pathogenesis. The mast cell lineage is one of the least studied among the hematopoietic cell lineages, and controversies remain about whether FcεRI expression appears during the mast cell progenitor stage or during terminal mast cell maturation. Here, we used single-cell transcriptomics analysis to reveal a temporal association between the appearance of FcεRI and the mast cell gene signature in CD34+ hematopoietic progenitors in adult peripheral blood. In agreement with these data, the FcεRI+ hematopoietic progenitors formed morphologically, phenotypically, and functionally mature mast cells in long-term culture assays. Single-cell transcriptomics analysis further revealed the expression patterns of prospective cytokine receptors regulating development of mast cell progenitors. Culture assays showed that interleukin-3 (IL-3) and IL-5 promoted disparate effects on progenitor cell proliferation and survival, respectively, whereas IL-33 caused robust FcεRI downregulation. Taken together, we showed that FcεRI expression appears at the progenitor stage of mast cell differentiation in peripheral blood. We also showed that external stimuli regulate FcεRI expression of mast cell progenitors, providing a possible explanation for the variable FcεRI expression levels during mast cell development.

Comparison of RNAscope and immunohistochemistry for evaluation of the UPK2 status in urothelial carcinoma tissues.

BACKGROUND: UPK2 exhibits excellent specificity for urothelial carcinoma (UC). UPK2 evaluation can be useful in making the correct diagnosis of UC. However, UPK2 detection by immunohistochemistry (IHC) has relatively low sensitivity. This paper aimed to compare the diagnostic sensitivity of RNAscope and IHC for evaluation of the UPK2 status in UC. METHODS: Tissue blocks from 127 conventional bladder UCs, 45 variant bladder UCs, 24 upper tract UCs and 23 metastatic UCs were selected for this study. IHC and RNAscope were used to detect the UPK2 status in UCs. Then, comparisons of the two methods were undertaken. RESULTS: There was no significant difference between RNAscope and IHC for the evaluation of the UPK2 positivity rate in UC (68.0% vs. 62.6%, P = 0.141). Correlation analysis revealed a moderate positive correlation for detection of UPK2: RNAscope vs. IHC (P < 0.001, R = 0.441). Our results showed a trend toward a higher positive UPK2 rate detected by RNAscope (53.3%) than by IHC (35.6%) in variant bladder UCs. Disappointingly, the P value did not indicate a significant difference (P = 0.057). CONCLUSIONS: RNAscope for UPK2 appeared to perform similarly to IHC, with a marginally higher positive rate, suggesting it could be used as an alternative or adjunct to UPK2 IHC.

Synthesis and Antifungal Activity of Pyrimidine Derivatives Containing an Amide Moiety.

In this study, 17 novel pyrimidine derivatives containing an amide moiety were synthesized. Then their in vitro antifungal activities against Botryosphaeria dothidea (B. dothidea), Phomopsis sp., and Botrytis cinereal (B. cinereal) were determined. A preliminary biological test showed that compounds 5-bromo-2-fluoro-N-(2-((2-methyl-6-(trifluoromethyl)pyrimidin-4-yl)oxy)phenyl)benzamide (5f) and 5-bromo-2-fluoro-N-(3-((2-methyl-6-(trifluoromethyl)pyrimidin-4-yl)oxy)phenyl)benzamide (5o) exhibited higher antifungal activity against Phomopsis sp., with an inhibition rate of 100% compared to that of Pyrimethanil at 85.1%. In particular, compound 5o exhibited excellent antifungal activity against Phompsis sp., with the EC50 value of 10.5 µg/ml, which was even better than that of Pyrimethanil (32.1 µg/ml). As far as we know, this is the first report on the antifungal activities against B. dothidea, Phomopsis sp., and B. cinereal of this series of pyrimidine derivatives containing an amide moiety.

A Zic2/Runx2/NOLC1 signaling axis mediates tumor growth and metastasis in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies with rapid growth and high metastasis, but lacks effective therapeutic targets. Here, using public sequencing data analyses, quantitative real-time PCR assay, western blotting, and IHC staining, we characterized that runt-related transcription factor 2 (Runx2) was significantly upregulated in ccRCC tissues than that in normal renal tissues, which was associated with the worse survival of ccRCC patients. Overexpression of Runx2 promoted malignant proliferation and migration of ccRCC cells, and inversely, interfering Runx2 with siRNA attenuates its oncogenic ability. RNA sequencing and functional studies revealed that Runx2 enhanced ccRCC cell growth and metastasis via downregulation of tumor suppressor nucleolar and coiled-body phosphoprotein 1 (NOLC1). Moreover, increased Zic family member 2 (Zic2) was responsible for the upregulation of Runx2 and its oncogenic functions in ccRCC. Kaplan-Meier survival analyses indicated that ccRCC patients with high Zic2/Runx2 and low NOLC1 had the worst outcome. Therefore, our study demonstrates that Zic2/Runx2/NOLC1 signaling axis promotes ccRCC progression, providing a set of potential targets and prognostic indicators for patients with ccRCC.

Impact of immunohistochemistry-based molecular subtype on predicting chemotherapy response and survival in patients with T1 stage bladder cancer after bladder-preserving treatment.

OBJECTIVE: To explore the immunohistochemistry-based molecular subtypes of bladder cancer, and their impact on the prognosis and the chemotherapy response between gemcitabine plus cisplatin intra-arterial chemotherapy and epirubicin-inducted intravesical chemotherapy, in patients with T1 stage bladder cancer after bladder-preserving treatment. METHODS: One hundred and seventy-six patients with T1 stage bladder cancer were selected for this study. Thirty-three patients underwent radical cystectomy, 43 received gemcitabine plus cisplatin intra-arterial chemotherapy and 100 received intravesical chemotherapy. The markers labeled with luminal (GATA3, Uroplakin II, CK20) and basal (CK5/6, CK14, CD44) phenotypes were chosen as candidate markers. RESULTS: One hundred and seventy-six patients were divided into 76 patients as basal/squamous (BASQ), 45 as the luminal A and 55 as the luminal B. Compared with the luminal B and BASQ tumors, the luminal A tumors showed a trend for better recurrence-free survival (P = 0.105) and progression-free survival (P = 0.093). The combination of CK20 and GATA3 was practical to identify the molecular phenotypes with total 84.9% accuracy and significantly associated with recurrence-free survival (P = 0.025) and progression-free survival (P = 0.004). The patient with BASQ tumors who received intravesical chemotherapy showed a trend for worse progression-free survival than the patient who received gemcitabine plus cisplatin intra-arterial chemotherapy or radical cystectomy. Furthermore, the patients with BASQ tumors experienced a significant improvement in progression-free survival after gemcitabine plus cisplatin intra-arterial chemotherapy compared with the patients who received intravesical chemotherapy (P = 0.011). CONCLUSIONS: The immunohistochemistry-based molecular subtypes could predict the patient's prognosis and clinically different chemotherapeutic survival outcomes in patients with T1 stage bladder cancer after bladder-preserving treatment.

Multi-region saliency-aware learning for cross-domain placenta image segmentation.

We propose a multi-region saliency-aware learning (MSL) method for cross-domain placenta image segmentation. Unlike most existing image-level transfer learning methods that fail to preserve the semantics of paired regions, our MSL incorporates the attention mechanism and a saliency constraint into the adversarial translation process, which can realize multi-region mappings in the semantic level. Specifically, the built-in attention module serves to detect the most discriminative semantic regions that the generator should focus on. Then we use the attention consistency as another guidance for retaining semantics after translation. Furthermore, we exploit the specially designed saliency-consistent constraint to enforce the semantic consistency by requiring the saliency regions unchanged. We conduct experiments using two real-world placenta datasets we have collected. We examine the efficacy of this approach in (1) segmentation and (2) prediction of the placental diagnoses of fetal and maternal inflammatory response (FIR, MIR). Experimental results show the superiority of the proposed approach over the state of the art.

AI-PLAX: AI-based placental assessment and examination using photos.

Post-delivery analysis of the placenta is useful for evaluating health risks of both the mother and baby. In the U.S., however, only about 20% of placentas are assessed by pathology exams, and placental data is often missed in pregnancy research because of the additional time, cost, and expertise needed. A computer-based tool that can be used in any delivery setting at the time of birth to provide an immediate and comprehensive placental assessment would have the potential to not only to improve health care, but also to radically improve medical knowledge. In this paper, we tackle the problem of automatic placental assessment and examination using photos. More concretely, we first address morphological characterization, which includes the tasks of placental image segmentation, umbilical cord insertion point localization, and maternal/fetal side classification. We also tackle clinically meaningful feature analysis of placentas, which comprises detection of retained placenta (i.e., incomplete placenta), umbilical cord knot, meconium, abruption, chorioamnionitis, and hypercoiled cord, and categorization of umbilical cord insertion type. We curated a dataset consisting of approximately 1300 placenta images taken at Northwestern Memorial Hospital, with hand-labeled pixel-level segmentation map, cord insertion point and other information extracted from the associated pathology reports. We developed the AI-based Placental Assessment and Examination system (AI-PLAX), which is a novel two-stage photograph-based pipeline for fully automated analysis. In the first stage, we use three encoder-decoder convolutional neural networks with a shared encoder to address morphological characterization tasks by employing a transfer-learning training strategy. In the second stage, we employ distinct sub-models to solve different feature analysis tasks by using both the photograph and the output of the first stage. We evaluated the effectiveness of our pipeline by using the curated dataset as well as the pathology reports in the medical record. Through extensive experiments, we demonstrate our system is able to produce accurate morphological characterization and very promising performance on aforementioned feature analysis tasks, all of which may possess clinical impact and contribute to future pregnancy research. This work is the first for comprehensive, automated, computer-based placental analysis and will serve as a launchpad for potentially multiple future innovations.

CM-supplement network model for reducing the memory consumption during multilabel image annotation.

With the rapid development of the Internet and the increasing popularity of mobile devices, the availability of digital image resources is increasing exponentially. How to rapidly and effectively retrieve and organize image information has been a hot issue that urgently must be solved. In the field of image retrieval, image auto-annotation remains a basic and challenging task. Targeting the drawbacks of the low accuracy rate and high memory resource consumption of current multilabel annotation methods, this study proposed a CM-supplement network model. This model combines the merits of cavity convolutions, Inception modules and a supplement network. The replacement of common convolutions with cavity convolutions enlarged the receptive field without increasing the number of parameters. The incorporation of Inception modules enables the model to extract image features at different scales with less memory consumption than before. The adoption of the supplement network enables the model to obtain the negative features of images. After 100 training iterations on the PASCAL VOC 2012 dataset, the proposed model achieved an overall annotation accuracy rate of 94.5%, which increased by 10.0 and 1.1 percentage points compared with the traditional convolution neural network (CNN) and double-channel CNN (DCCNN). After stabilization, this model achieved an accuracy of up to 96.4%. Moreover, the number of parameters in the DCCNN was more than 1.5 times that of the CM-supplement network. Without increasing the amount of memory resources consumed, the proposed CM-supplement network can achieve comparable or even better annotation effects than a DCCNN.

Live attenuated pertussis vaccine BPZE1 induces a broad antibody response in humans.

BACKGROUNDThe live attenuated BPZE1 vaccine candidate induces protection against B. pertussis and prevents nasal colonization in animal models. Here we report on the responses in humans receiving a single intranasal administration of BPZE1.METHODSWe performed multiple assays to dissect the immune responses induced in humans (n = 12) receiving BPZE1, with particular emphasis on the magnitude and characteristics of the antibody responses. Such responses were benchmarked to adolescents (n = 12) receiving the complete vaccination program of the currently used acellular pertussis vaccine (aPV). Using immunoproteomics analysis, potentially novel immunogenic B. pertussis antigens were identified.RESULTSAll BPZE1 vaccinees showed robust B. pertussis-specific antibody responses with regard to significant increase in 1 or more of the following parameters: IgG, IgA, and memory B cells to B. pertussis antigens. BPZE1-specific T cells showed a Th1 phenotype, and the IgG exclusively consisted of IgG1 and IgG3. In contrast, all aPV vaccines showed a Th2-biased response. Immunoproteomics profiling revealed that BPZE1 elicited broader and different antibody specificities to B. pertussis antigens as compared with the aPV that primarily induced antibodies to the vaccine antigens. Moreover, BPZE1 was superior at inducing opsonizing antibodies that stimulated ROS production in neutrophils and enhanced bactericidal function, which was in line with the finding that antibodies against adenylate cyclase toxin were only elicited by BPZE1.CONCLUSIONThe breadth of the antibodies, the Th1-type cellular response, and killing mechanisms elicited by BPZE1 may hold prospects of improving vaccine efficacy and protection against B. pertussis transmission.TRIAL REGISTRATIONClinicalTrials.gov NCT02453048, NCT00870350.FUNDINGILiAD Biotechnologies, Swedish Research Council (Vetenskapsrådet), Swedish Heart-Lung Foundation.

Expression of P63 and its correlation with prognosis in diffuse large B-cell lymphoma: a single center experience.

BACKGROUND: Large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin's lymphoma among adults. In some cases, DLBCL may seem similar to carcinoma cells, presenting a round, oval, or polygonal shape and clear nuclei. We found that the expression of P63 accounted for a considerable proportion of DLBCL cases. Under the circumstances, P63 expression may lead to a misdiagnosis, especially with a small biopsy. We aim to investigate the expression status and prognostic significance of P63 in a cohort of Chinese DLBCL patients. METHODS: P63, ΔNP63(P40), P53 and Ki67 were detected by immunohistochemistry (IHC). A ROC curve was adopted to find the best cut-off value for positive P63/P53 expression and high Ki67 expression. We defined P53 as positive when ≥50% of the tumor cells showed staining. The relationship between P63 and P53/Ki67 expression was examined. Time-to-event endpoints were estimated according to the Kaplan-Meier method. Moreover, multivariate analyses were conducted to evaluate the prognostic factors in DLBCL. RESULTS: Out of all the 159 DLBCL cases, 76 (47.8%) expressed P63 in the nuclei, while 41 (25.8%) were determined to have high expression by using a ROC cut-off value "≥6". Examination of the different P63 isoforms revealed that the ΔNP63(P40) was unclearly and weakly expressed in only 3 cases, showing a fuzzy yellow cytoplasm. P63 expression was not correlated with subtype (GCB or non-GCB) or P53 but was correlated with a high proliferative index (Ki67). Kaplan-Meier analyses revealed that P63 expression was correlated with overall survival, and P63 positive cases showed poor survival outcomes (P<0.05) in our cohort. CONCLUSIONS: ΔNP63(P40) is a useful marker in the differential diagnosis of poorly differentiated squamous cell carcinoma versus DLBCL in small needle biopsy. P63 may be involved in DLBCL tumor progression, and it is an unfavorable prognostic marker in DLBCL. A subgroup of P63 and P53 coexpression DLBCL patients with an extremely poor prognosis should be noted.

Clonal Mutations Activate the NF-κB Pathway to Promote Recurrence of Nasopharyngeal Carcinoma.

The genetic events occurring in recurrent nasopharyngeal carcinoma (rNPC) are poorly understood. Here, we performed whole-genome and whole-exome sequencing in 55 patients with rNPC and 44 primarily diagnosed NPC (pNPC), with 7 patients having paired rNPC and pNPC samples. Previously published pNPC exome data were integrated for analysis. rNPC and pNPC tissues had similar mutational burdens, however, the number of clonal mutations was increased in rNPC samples. TP53 and three NF-κB pathway components (TRAF3, CYLD, and NFKBIA) were significantly mutated in both pNPC and rNPC. Notably, mutations in TRAF3, CYLD, and NFKBIA were all clonal in rNPC, however, 55.6% to 57.9% of them were clonal in pNPC. In general, the number of clonal mutations in NF-κB pathway-associated genes was significantly higher in rNPC than in pNPC. The NF-κB mutational clonality was selected and/or enriched during NPC recurrence. The amount of NF-κB translocated to the nucleus in samples with clonal NF-κB mutants was significantly higher than that in samples with subclonal NF-κB mutants. Moreover, the nuclear abundance of NF-κB protein was significantly greater in pNPC samples with locoregional relapse than in those without relapse. Furthermore, high nuclear NF-κB levels were an independent negative prognostic marker for locoregional relapse-free survival in pNPC. Finally, inhibition of NF-κB enhanced both radiosensitivity and chemosensitivity in vitro and in vivo. In conclusion, NF-κB pathway activation by clonal mutations plays an important role in promoting the recurrence of NPC. Moreover, nuclear accumulation of NF-κB is a prominent biomarker for predicting locoregional relapse-free survival. SIGNIFICANCE: This study uncovers genetic events that promote the progression and recurrence of nasopharyngeal carcinoma and has potential prognostic and therapeutic implications.See related commentary by Sehgal and Barbie, p. 5915.

An Improved Convolutional Neural Network Algorithm and Its Application in Multilabel Image Labeling.

In today's society, image resources are everywhere, and the number of available images can be overwhelming. Determining how to rapidly and effectively query, retrieve, and organize image information has become a popular research topic, and automatic image annotation is the key to text-based image retrieval. If the semantic images with annotations are not balanced among the training samples, the low-frequency labeling accuracy can be poor. In this study, a dual-channel convolution neural network (DCCNN) was designed to improve the accuracy of automatic labeling. The model integrates two convolutional neural network (CNN) channels with different structures. One channel is used for training based on the low-frequency samples and increases the proportion of low-frequency samples in the model, and the other is used for training based on all training sets. In the labeling process, the outputs of the two channels are fused to obtain a labeling decision. We verified the proposed model on the Caltech-256, Pascal VOC 2007, and Pascal VOC 2012 standard datasets. On the Pascal VOC 2012 dataset, the proposed DCCNN model achieves an overall labeling accuracy of up to 93.4% after 100 training iterations: 8.9% higher than the CNN and 15% higher than the traditional method. A similar accuracy can be achieved by the CNN only after 2,500 training iterations. On the 50,000-image dataset from Caltech-256 and Pascal VOC 2012, the performance of the DCCNN is relatively stable; it achieves an average labeling accuracy above 93%. In contrast, the CNN reaches an accuracy of only 91% even after extended training. Furthermore, the proposed DCCNN achieves a labeling accuracy for low-frequency words approximately 10% higher than that of the CNN, which further verifies the reliability of the proposed model in this study.

Expression and significance of Cystatin-C in clear cell renal cell carcinoma.

PURPOSE: Cystatin-C (Cys-C) has been studied as a valuable prognostic indicator in several malignancies. The goal of this study is to explore the expression and prognostic significance of Cys-C in clear cell renal cell carcinoma (CCRCC). METHODS: Immunohistochemistry and western blot assays were performed to evaluate the level of Cys-C expression in CCRCC tissue. Expression levels of Cys-C in CCRCC tissue samples in relation to clinicopathological characteristics of the tumors were assessed. Their prognostic significance was analyzed by univariate and multivariate analyses. In addition, the expression of Cys-C in 786-O cell lines was inhibited by using CRISPR/Case9 and the effects of Cys-C knockout on 786-O cells in vitro were evaluated using MTT method, colony formation assay, cell cycle assay, and cell migration and invasive assay. RESULTS: The expression level of Cys-C was lower in CCRCC tissues (n = 253) than in paired adjacent non-cancerous tissues (n = 164) by immunohistochemistry (P < 0.001). Among the 253 patients, the results showed that patients with low Cys-C expression level in cancer tissue has longer overall survival (OS) than that with high Cys-C level. Furthermore, knockout of Cys-C in 786-O cell line has ability to suppress cell proliferation, induce G0/G1 phase arrest, inhibited cell invasion, decreased phosphorylation of ERK1/2, STAT-3 and enhanced phosphorylated JNK expression. CONCLUSIONS: A decrease in serum Cys-C is a favorable prognostic indicator for CCRCC patients. Inhibition of Cys-C suppressed RCC 786-O cell proliferation and invasion. These results indicated that Cys-C could serve as an ideal prognostic biomarker in patients with CCRCC.

A novel efficient g-C3N4@BiOI p-n heterojunction photocatalyst constructed through the assembly of g-C3N4 nanoparticles.

An efficient and facile method to fabricate a surficial dispersive heterojunction based on the assembly of g-C3N4 nanoparticles was proposed. A p-n nano heterojunction composed of BiOI and g-C3N4 was constructed by simply loading g-C3N4 nanoparticles on flower-like BiOI nanosheets. The structure-dependent optical, electronic and photoelectric properties were investigated, and the structure-property relationship was discussed. The results show that the g-C3N4 nanoparticles are uniformly loaded on the surface of BiOI nanosheets and thus form a p-n heterojunction with an intimate interface. The as-prepared samples exhibit enhanced photocatalytic degradation ability towards MO under visible-light irradiation. With the unique structure and morphology, enhanced visible-light photocatalytic activities are achieved owing to the synergistic effect of light harvesting, high transfer efficiency and enhanced separation efficiency of photo-generated carriers.

Loss of CD15 expression in clear cell renal cell carcinoma is correlated with worse prognosis in Chinese patients.

PURPOSE: To explore the role of CD15 expression in the prognosis of clear cell renal cell carcinoma (ccRCC) in Chinese patients. METHODS: The study included 301 patients who had undergone surgery for localized ccRCC. All paraffin-embedded tumor sections were collected to make a set of tissue microarrays. CD15 expression was assessed by immunohistochemistry. The relationship between CD15 expression and survival parameters, clinicopathology features was assessed. Kaplan-Meier and Cox proportional hazards model were utilized to determine the correlation between CD15 expression and overall survival (OS). RESULTS: The median follow-up time was 54.6 months (range, 3-121 months). The positive rate of CD15 expression was 81.7% (246/301). The cut-off value of CD15 expression was defined as the maximum for Youden index by plotting the receiver operating characteristic curve for survival status. As the threshold was 0.5, all cases were divided into two groups: positive expression group and negative expression group. In correlation analysis, loss of CD15 expression was correlated with female gender, higher Fuhrman nuclear grade, with sarcomatoid differentiation, with necrosis, and with vascular invasion. Kaplan-Meier analysis indicated that the OS time of patients with loss of CD15 expression was shorter than that of patients with positive CD15 expression (P = 0.013). CONCLUSION: CD15 is a significant prognostic factor in clear cell renal cell carcinoma.