The relationship between Cho/NAA and glioma metabolism: implementation for margin delineation of cerebral gliomas

BACKGROUND: The marginal delineation of gliomas cannot be defined by conventional imaging due to their infiltrative growth pattern. Here we investigate the relationship between changes in glioma metabolism by proton magnetic resonance spectroscopic imaging ((1)H-MRSI) and histopathological findings in order to determine an optimal threshold value of choline/N-acetyl-aspartate (Cho/NAA) that can be used to define the extent of glioma spread. METHOD: Eighteen patients with different grades of glioma were examined using (1)H-MRSI. Needle biopsies were performed under the guidance of neuronavigation prior to craniotomy. Intraoperative magnetic resonance imaging (MRI) was performed to evaluate the accuracy of sampling. Haematoxylin and eosin, and immunohistochemical staining with IDH1, MIB-1, p53, CD34 and glial fibrillary acidic protein (GFAP) antibodies were performed on all samples. Logistic regression analysis was used to determine the relationship between Cho/NAA and MIB-1, p53, CD34, and the degree of tumour infiltration. The clinical threshold ratio distinguishing tumour tissue in high-grade (grades III and IV) glioma (HGG) and low-grade (grade II) glioma (LGG) was calculated. RESULTS: In HGG, higher Cho/NAA ratios were associated with a greater probability of higher MIB-1 counts, stronger CD34 expression, and tumour infiltration. Ratio threshold values of 0.5, 1.0, 1.5 and 2.0 appeared to predict the specimens containing the tumour with respective probabilities of 0.38, 0.60, 0.79, 0.90 in HGG and 0.16, 0.39, 0.67, 0.87 in LGG. CONCLUSIONS: HGG and LGG exhibit different spectroscopic patterns. Using (1)H-MRSI to guide the extent of resection has the potential to improve the clinical outcome of glioma surgery

Thyroid volume, goiter prevalence, and selenium levels in an iodine-sufficient area: a cross-sectional study

Abstract Background Selenium (Se) is a necessary element for the biosynthesis of thyroid hormones. We investigated the relationship between selenium status, thyroid volume, and goiter in a cross-sectional study in an iodine-sufficient area. Methods We selected residents of Chengdu (over 18 years old and living in the city for more than 5 years) using a stratified cluster sampling technique. Fifteen hundred subjects were selected for the study, which involved a questionnaire survey, physical examination, thyroid ultrasound, serum thyroid function test, and determination of serum selenium level. Thyroid volume was calculated from the thickness, width, length, and a corrective factor for each lobe. Ultimately, 1,205 subjects completed the investigation and were included in our study. Additionally, 80 school-age children were selected to provide urine samples for urinary iodine analysis. We analyzed the data using appropriate nonparametric and parametric statistical tests. Results The median urinary iodine value was 184 μg/L in school-age children, indicating iodine sufficiency. The median serum selenium level of the 1,205 subjects was 52.63 (interquartile range [IQR] : 40.40-67.00) μg/L. The median thyroid volume was 9.93 (IQR: 7.71-12.57) mL; both log-transformed serum selenium and log-transformed thyroid volume were Gaussian distributions (P = .638 and P = .046, respectively). The prevalences of goiter and thyroid nodules were 8.8% and 18.6%. The prevalences of positive thyroid autoantibodies, thyroperoxidase autoantibodies and thyroglobulin autoantibodies were 16.7%, 12.0%, and 11.1%, respectively. In the general linear regression model, there were positive associations between serum selenium and age, and body mass index. We found no association between serum selenium and thyroid-stimulating hormone. In simple linear regression analyses, we found no association between thyroid volume and serum selenium. There were no significant differences in serum selenium between persons with or without goiter. Serum selenium was not a risk factor for goiter. Conclusion In our study population, serum selenium was neither associated with thyroid volume nor with goiter in an iodine-sufficient area. More studies should be conducted by following non-goitrous persons over time and monitoring their selenium status. </jats:sec

FAN: Fatigue-Aware Network for Click-Through Rate Prediction in E-commerce Recommendation

Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely on explicit negative user behaviors (e.g., dislikes) or simply treat non-clicks as negative feedback, failing to learn negative user interests comprehensively. In such situations, users may experience fatigue because of seeing too many similar recommendations. In this paper, we propose Fatigue-Aware Network (FAN), a novel CTR model that directly perceives user fatigue from non-clicks. Specifically, we first apply Fourier Transformation to the time series generated from non-clicks, obtaining its frequency spectrum which contains comprehensive information about user fatigue. Then the frequency spectrum is modulated by category information of the target item to model the bias that both the upper bound of fatigue and users' patience is different for different categories. Moreover, a gating network is adopted to model the confidence of user fatigue and an auxiliary task is designed to guide the learning of user fatigue, so we can obtain a well-learned fatigue representation and combine it with user interests for the final CTR prediction. Experimental results on real-world datasets validate the superiority of FAN and online A/B tests also show FAN outperforms representative CTR models significantly

Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction

Promotions are becoming more important and prevalent in e-commerce to attract customers and boost sales, leading to frequent changes of occasions, which drives users to behave differently. In such situations, most existing Click-Through Rate (CTR) models can't generalize well to online serving due to distribution uncertainty of the upcoming occasion. In this paper, we propose a novel CTR model named MOEF for recommendations under frequent changes of occasions. Firstly, we design a time series that consists of occasion signals generated from the online business scenario. Since occasion signals are more discriminative in the frequency domain, we apply Fourier Transformation to sliding time windows upon the time series, obtaining a sequence of frequency spectrum which is then processed by Occasion Evolution Layer (OEL). In this way, a high-order occasion representation can be learned to handle the online distribution uncertainty. Moreover, we adopt multiple experts to learn feature representations from multiple aspects, which are guided by the occasion representation via an attention mechanism. Accordingly, a mixture of feature representations is obtained adaptively for different occasions to predict the final CTR. Experimental results on real-world datasets validate the superiority of MOEF and online A/B tests also show MOEF outperforms representative CTR models significantly

Candida haemulonii Species Complex: Emerging Fungal Pathogens of the Metschnikowiaceae Clade

Candida species, the most common fungal pathogens affecting humans, cause not only superficial infections but also life-threatening invasive infections, particularly in immunocompromised individuals. Although Candida albicans remains the most frequent cause of candidiasis, infections caused by non- albicans Candida species have been increasingly reported in clinical settings over the past two decades. Recently, species of the Metschnikowiaceae clade including the “superbug” Candida auris and other members of the Candida haemulonii species complex have attracted substantial attention for their multidrug resistance and high rates of transmission in clinical settings. In this review, we summarize the epidemiology, biology, virulence, and drug resistance of the C. haemulonii species complex and discuss potential reasons for the recent increase in the prevalence of infections caused by non- albicans species in clinical settings

An electromagnetic coupling treatment for improving the cutting performance of cemented carbide-coated tools

To improve the cutting performance and prolong the service life of a carbide-coated tool in the process of ductile iron machining, an electromagnetic coupling treatment (EMCT) was carried out. The cutting experiments show that the cutting force and cutting temperature are reduced after EMCT, and the roughness of the machined surface is reduced. It is found that after EMCT with optimal parameters the dislocation density, microscopic strain, microhardness and bonding strength of an alumina coating increase by 109.2%, 28.2%, 28.3% and 26.6%, respectively. Using the actual machining of a differential housing to verify the tool life, it is found that after EMCT, a single tool can process 18.4 more workpieces or in other words, the tool life increased by 44%. EMCT can promote element diffusion, optimize coating properties and have great potential in coating tool life extension

Raman photostability of off-resonant gap-enhanced Raman tags

Surface-enhanced Raman scattering (SERS) nanoprobes show promising potential for biosensing and bioimaging applications due to advantageous features of ultrahigh sensitivity and specificity. However, very limited research has been reported on the SERS photostability of nanoprobes upon continuous laser irradiation, which is critical for high-speed and time-lapse microscopy. The core-shell off-resonant gap-enhanced Raman tags (GERTs) with built-in Raman reporters, excited at near-infrared (NIR) region but with a plasmon resonance at visible region, allow decoupling the plasmon resonance behaviors with the SERS performance and therefore show ultrahigh Raman photostability during continuous laser irradiation. In this work, we have synthesized five types of off-resonant GERTs with different embedded Raman reporters, numbers of shell layer, or nanoparticle shapes. Via thorough examination of time-resolved SERS trajectories and quantitative analysis of photobleaching behaviors, we have demonstrated that double metallic-shell GERTs embedded with 1,4-benzenedithiol molecules show the best photostability performance, to the best of our knowledge, among all SERS nanoprobes reported before, with a photobleaching time constant up to 4.8 x 10(5) under a laser power density of 4.7 x 10(5) W cm(-2). Numerical calculations additionally support that the local plasmonic heating effect in fact can be greatly minimized using the off-resonance strategy. Moreover, double-shell BDT-GERTs are highly potential for high-speed and high-resolution Raman-based cell bioimaging

Identification of platelet-related subtypes and diagnostic markers in pediatric Crohn’s disease based on WGCNA and machine learning

BackgroundThe incidence of pediatric Crohn’s disease (PCD) is increasing worldwide every year. The challenges in early diagnosis and treatment of PCD persist due to its inherent heterogeneity. This study’s objective was to discover novel diagnostic markers and molecular subtypes aimed at enhancing the prognosis for patients suffering from PCD.MethodsCandidate genes were obtained from the GSE117993 dataset and the GSE93624 dataset by weighted gene co-expression network analysis (WGCNA) and differential analysis, followed by intersection with platelet-related genes. Based on this, diagnostic markers were screened by five machine learning algorithms. We constructed predictive models and molecular subtypes based on key markers. The models were evaluated using the GSE101794 dataset as the validation set, combined with receiver operating characteristic curves, decision curve analysis, clinical impact curves, and calibration curves. In addition, we performed pathway enrichment analysis and immune infiltration analysis for different molecular subtypes to assess their differences.ResultsThrough WGCNA and differential analysis, we successfully identified 44 candidate genes. Following this, employing five machine learning algorithms, we ultimately narrowed it down to five pivotal markers: GNA15, PIK3R3, PLEK, SERPINE1, and STAT1. Using these five key markers as a foundation, we developed a nomogram exhibiting exceptional performance. Furthermore, we distinguished two platelet-related subtypes of PCD through consensus clustering analysis. Subsequent analyses involving pathway enrichment and immune infiltration unveiled notable disparities in gene expression patterns, enrichment pathways, and immune infiltration landscapes between these subtypes.ConclusionIn this study, we have successfully identified five promising diagnostic markers and developed a robust nomogram with high predictive efficacy. Furthermore, the recognition of distinct PCD subtypes enhances our comprehension of potential pathogenic mechanisms and paves the way for future prospects in early diagnosis and personalized treatment

A replicative recombinant HPV16 E7 expression virus upregulates CD36 in C33A cells

ObjectiveIn past decades, the role of high-risk HPV (HR-HPV) infection in cancer pathogenesis has been extensively studied. The viral E7 protein expressed in pre-malignant cells has been identified as an ideal target for immunological intervention. However, the cultivation of HPV in vitro remains a significant challenge, as well as the lack of methods for expressing the HPV E7 protein and generating replication-competent recombinant viral particles, which posed a major obstacle to further exploration of the function and carcinogenic mechanisms of the E7 oncoprotein. Therefore, it is imperative to investigate novel methodologies to construct replication-competent recombinant viral particles that express the HPV E7 protein to facilitate the study of its function.MethodsWe initiated the construction of recombinant viral particles by utilizing the ccdB-Kan forward/reverse screening system in conjunction with the Red/ExoCET recombinant system. We followed the infection of C33A cells with the obtained recombinant virus to enable the continuous expression of HPV16 E7. Afterwards, the total RNA was extracted and performed transcriptome sequencing using RNA-Seq technology to identify differentially expressed genes associated with HPV-induced oncogenicity.ResultsWe successfully established replicative recombinant viral particles expressing HPV16 E7 stably and continuously. The C33A cells were infected with recombinant viral particles to achieve overexpression of the E7 protein. Subsequently, RNA-Seq analysis was conducted to assess the changes in host cell gene expression. The results revealed an upregulation of the CD36 gene, which is associated with the HPV-induced oncogenic pathways, including PI3K-Akt and p53 signaling pathway. qRT-PCR analysis further identified that the upregulation of the CD36 gene due to the expression of HPV16 E7.ConclusionThe successful expression of HPV16 E7 in cells demonstrates that the replicated recombinant virus retains the replication and infection abilities of Ad4, while also upregulating the CD36 gene involved in the PI3K-Akt signaling and p53 pathways, thereby promoting cell proliferation. The outcome of this study provides a novel perspective and serves as a solid foundation for further exploration of HPV-related carcinogenesis and the development of replicative HPV recombinant vaccines capable of inducing protective immunity against HPV