TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8+ T cells, CD4+ helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4+ T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.

A nomogram for predicting choledochal cyst with perforation.

BACKGROUND: Choledochal cyst with perforation (CC with perforation) rarely occurs, early diagnosis and timely treatment plan are crucial for the treatment of CC with perforation. This study aims to forecast the occurrence of CC with perforation. METHODS: All 1111 patients were conducted, who underwent surgery for choledochal cyst at our hospital from January 2011 to October 2022. We conducted univariate and multivariate logistic regression analysis to screen for independent predictive factors for predicting CC with perforation, upon which established a nomogram. The predictive performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA) curves. RESULTS: The age of children with choledochal cyst perforation is mainly concentrated between 1 and 3 years old. Logistic regression analysis indicates that age, alanine aminotransferase, glutamyl transpeptidase, C-reactive protein, vomiting, jaundice, abdominal distension, and diarrhea are associated with predicting the occurrence of choledochal cyst perforation. ROC curves, calibration plots, and DCA curve analysis curves demonstrate that the nomogram has great discriminative ability and calibration, as well as significant clinical utility. CONCLUSION: The age of CC with perforation is mainly concentrated between 1 and 3 years old. A nomogram for predicting the perforation of choledochal cyst was established.

Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.

BACKGROUND: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation. METHODS: PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789). RESULTS: In 20,887 screened references, 79 articles (82.5% in 2017-2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5-52,000, median 21) and large-span sample size (range 80-3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as "recommended"; however, 281 and 187 were "not recommended" and "warning," respectively. CONCLUSION: AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems. The IVS we developed may contribute to independent external validation and the development of this field.

A Comparative Study of the Effects of Electronic Cigarette and Traditional Cigarette on the Pulmonary Functions of C57BL/6 Male Mice.

INTRODUCTION: Electronic cigarettes (E-cigs) are in a controversial state. Although E-cig aerosol generally contains fewer harmful substances than smoke from burned traditional cigarettes, aerosol along with other compounds of the E-cigs may also affect lung functions and promote the development of lung-related diseases. We investigated the effects of E-cig on the pulmonary functions of male C57BL/6 mice and reveal the potential underlying mechanisms. METHODS: A total of 60 male C57BL/6 mice were randomly divided into four groups. They were exposed to fresh-air, traditional cigarette smoke, E-cig vapor with 12 mg/mL of nicotine, and E-cig with no nicotine for 8 weeks. Lung functions were evaluated by using quantitative analysis of the whole body plethysmograph, FlexiVent system, lung tissue histological and morphometric analysis, and RT-PCR analysis of mRNA expression of inflammation-related genes. In addition, the effects of nicotine and acrolein on the survival rate and DNA damage were investigated using cultured human alveolar basal epithelial cells. RESULTS: Exposure to E-cig vapor led to significant changes in lung functions and structures including the rupture of the alveolar cavity and enlarged alveolar space. The pathological changes were also accompanied by increased expression of interleukin-6 and tumor necrosis factor-α. CONCLUSIONS: The findings of the present study indicate that the safety of E-cig should be further evaluated. IMPLICATIONS: Some people currently believe that using nicotine-free E-cigs is a safe way to smoke. However, our research shows that E-cigs can cause lung damage regardless of whether they contain nicotine.

Correlation between maximum heart distance and thoracic diameter changes and diaphragmatic descent in left-sided breast cancer patients during deep inspiration breath-hold (DIBH).

BACKGROUND: Cardioprotection is valued in radiotherapy for patients with left-sided breast cancer. Deep inspiration breath-hold (DIBH) technique can achieve cardioprotection well. However, during DIBH, the extent to which the heart enters the radiation field is affected by the movement of the thorax and diaphragm. The aim of this study was to analyze the correlation between the maximum distance of the heart entering the field (maximum heart distance, MHD) and thoracic diameter changes and diaphragmatic descent in left-sided breast cancer patients during DIBH. PATIENTS AND METHODS: Ninety-eight patients with left-sided breast cancer were included in this retrospective study. They performed simulation in Sentinel-guided DIBH, and two sets of CT images were collected under both free breathing (FB) and DIBH, and diaphragm positions, anteroposterior thoracic diameter (ATD), transverse thoracic diameter (TTD), gating window level (GWL), and MHD were measured, and the change (Δ) of each parameter in DIBH relative to that in FB were calculated. Pearson or Spearman test were used to analyze the correlation between ΔMHD and the changes in other parameters. RESULTS: For all patients with DIBH, the average of ΔMHD was -8.3 mm, and the average of ΔATD and ΔTTD were 11.0 and 8.6 mm, and the median of both left diaphragmatic descent (LDD) and right diaphragmatic descent (RDD) were 35.0 mm, and the median of GWL was 11.1 mm. The correlation coefficients between MHD decrease (ΔMHD) and LDD, RDD, and ΔTTD were -0.430 (p = 0.000), -0.592 (p = 0.000) and 0.208 (p = 0.040), respectively, but not significantly correlated with ΔATD or GWL. CONCLUSIONS: The MHD decrease showed a moderate correlation with diaphragmatic descent In Sentinel-guided DIBH for patients with left-sided breast cancer, while there was a weak or no correlation with thoracic diameter changes or GWL. Abdominal breathing can lower diaphragm more and may be more beneficial to the heart stay away from tangential field.

The medial preoptic area mediates depressive-like behaviors induced by ovarian hormone withdrawal through distinct GABAergic projections.

Fluctuations in reproductive hormone levels are associated with mood disruptions in women, such as in postpartum and perimenopausal depression. However, the neural circuit mechanisms remain unclear. Here we report that medial preoptic area (MPOA) GABAergic neurons mediate multifaceted depressive-like behaviors in female mice after ovarian hormone withdrawal (HW), which can be attributed to downregulation of activity in Esr1 (estrogen receptor-1)-expressing GABAergic neurons. Enhancing activity of these neurons ameliorates depressive-like behaviors in HW-treated mice, whereas reducing their activity results in expression of these behaviors. Two separate subpopulations mediate different symptoms: a subpopulation projecting to the ventral tegmental area (VTA) mediates anhedonia and another projecting to the periaqueductal gray mediates immobility. These projections enhance activity of dopaminergic neurons in the VTA and serotonergic neurons in the dorsal raphe, respectively, with increased release of dopamine and serotonin, possibly through disinhibition mechanisms. Thus, the MPOA is a hub that mediates depressive-like behaviors resulting from transitions in reproductive hormone levels.

Space Charge Characteristics and Breakdown Properties of Nanostructured SiO2/PP Composites.

Polypropylene (PP) has gained attention in the industry as an environmentally friendly material. However, its electrical properties are compromised due to space charge accumulation during operation, limiting its application in high-voltage DC cable insulation. This study investigates the effect and mechanism of SiO2 with a DDS surface hydrophobic treatment on space charge suppression and the electrical properties of PP composites. The PP matrix was doped with SiO2 nanostructures, both with a DDS surface hydrophobic treatment and untreated as a control group. The functional group structure and dispersion of nanostructured SiO2 in the matrix were characterized. The findings reveal that the incorporation of SiO2 nanostructures effectively mitigates charge accumulation in PP composites. However, a high concentration of unsurfaced nanostructures tends to agglomerate, resulting in inadequate space charge suppression and a diminished DC breakdown field strength. Nonetheless, surface treatment improves the dispersion of SiO2 within the matrix. Notably, the composite containing 1.0 wt% of surface hydrophobic SiO2 exhibits the least space charge accumulation. Compared to the base material PP, the average charge density is reduced by 83.9% after the 1800 s short-circuit discharges. Moreover, its DC breakdown field strength reaches 3.45 × 108 V/m, surpassing pure PP by 19.4% and untreated SiO2/PP composites of the same proportion by 24.0%.

Study on the potential risks under a hazardous gas leakage accident: effects of source characteristics and ambient wind velocities.

In this study, a full-scale storage tank was established to investigate the potential risks of leakage accident. We have developed a series of leak scenarios that close to real accidents and have divided the ambient areas according to relevant regulations. Considering the variety and complexity of real-life accident scenarios, the presented work revealed the combined effect of source release intensity and ambient wind speed on dispersion features by classifying leakage scenarios into active or passive release. The environmental hazards in each area is evaluated under various leak scenarios. The results show that when the approaching wind speed is low, the leakage on the windward side is the most dangerous release pattern. With the increase of the wind speed, the case with jet angle perpendicular to the incoming wind produces the largest cloud volume. Top release is the least dangerous way among the studied leak scenarios. However, the results illustrate that under some release angles, the cloud volume near the tank is not sensitive to wind speed. In leak accidents, quantitatively analysis reveals that the commonly used dimensionless concentrations ([Formula: see text]) cannot be used as a suitable parameter to discuss the concentration field except under top/leeward passive release conditions. This study will be beneficial to on-site rescue and decision-making when leakage accidents occur and provide reasonable suggestions for subsequent research on the environmental impact of container leakage and the diffusion of pollutants.

Survival Outcomes Associated With the Size of Opioid Prescriptions in the Management of Chronic Pain Related to Advanced Nasopharyngeal Carcinoma.

OBJECTIVE: Patients with advanced nasopharyngeal carcinoma (ANC) often experience chronic pain. Opioids are generally recommended to treat tumor-related pain, but increased opioid use may lead to detrimental aftereffects, particularly with respect to tumor progression, resulting in reduced quality of life and increased risk of death. Our objective was to investigate whether the high size of opioid prescriptions is associated with poor overall survival (OS) in patients with ANC. METHODS: A consecutive cohort of patients with newly diagnosed ANC who underwent high or low opioid prescription size treatment during 2012-2019 was retrospectively identified from our medical institutions. Survival was estimated with the Kaplan-Meier method with a log-rank test. Multivariate binary logistic regression was used to assess the association between opioid use and OS, adjusting for age, sex, body mass index (BMI), Eastern Collaborative Oncology Group performance status (ECOG PS), and ANC histology. The criterion to distinguish between the high opioid prescription size group [HD] and the low opioid prescription size group [LD] was 5 mg of oral morphine equivalents (OME) per 24 hours. RESULTS: The cohort consisted of 244 consecutive patients (HD: n = 120, median age = 66 years [range, 40-81 years]; LD: n = 124, median age = 65 years [40-82 years]. Patients who underwent treatment with a high opioid prescription size had a worse median OS than those who underwent treatment with a low opioid prescription size (5.1 vs 6.6 months), and the high opioid prescription size was associated with a remarkable 48% higher risk of death than the low opioid prescription size (HR 1.48, 95% CI 1.11-1.98; P = .005). The cumulative dose of opioids greater than or equal to 500 mg of OME was associated with a higher risk of death, adjusted for age, sex, BMI, ECOG PS, and ANC histology. CONCLUSIONS: In patients with newly diagnosed ANC experiencing palliative care, a high opioid prescription size may be associated with shorter OS than a low opioid prescription size.

TRIM27 is an adverse prognostic biomarker and associated with immune and molecular profiles in right-sided colon cancer.

Right-sided colon cancer (RCC), as an independent tumor entity, shows a poor prognosis. It is imperative to detect immune microenvironment-related genes for predicting RCC patient prognosis and study their function in RCC. Tripartite motif-containing 27 (TRIM27) was identified as a risk signature from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets by using weighted gene co-expression network analysis, differentially expressed analysis, and univariate Cox analysis. It predicted a poorer overall survival and increased lymph node metastasis, which were then validated in our 48 clinical samples. Using immunohistochemistry, TRIM27 was found to be highly expressed in both cancer cells and surrounding immunocytes, and its expression in tumor or immune cells both predicted a poorer prognosis. Thereafter, the functional mechanism, immune and molecular characteristics of TRIM27 were investigated using gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, and gene set variation analysis (GSVA) at the single-cell, somatic mutation, and RNA-seq level. Patients with highly expressed TRIM27 presented lower CD4+ T cell infiltration and activation of the mTORC1/glycolysis pathway. In addition, patients with highly expressed TRIM27 were characterized by hypermetabolism, higher tumor purity, more BRAF mutation, and more chromosomal instability. Collectively, TRIM27 is an important immune-related prognostic biomarker in patients with RCC. It may function via activating the mTORC1/glycolysis pathway and suppressing CD4+ T cells. These results indicated that TRIM27 could be a promising therapeutic target in RCC.

Rare pulmonary embolism in a pregnant patient: A primary diffused pulmonary artery myxofibrosarcoma case report.

A 37-year-old female patient presented with shortness of breath, cough, and chest pain complaints from the 12th week of her first pregnancy. At the 28th week, labor induction had to be performed because of severe dyspnea and hyoxemia. Thereafter, a diffused pulmonary embolism was detected by echocardiography and CT angiography, without histological diagnosis. Pulmonary endarterectomy was performed, and it was found during operation that a huge, lobular mass originated in the posterior wall and extended throughout the vasculature of both lungs, and a mucinous pellicle covered the entire pulmonary endothelium. Pathology revealed a low-grade myxofibrosarcoma with positive vimentin and SMA, partially positive CD-34.

DeepPSE: Prediction of polypharmacy side effects by fusing deep representation of drug pairs and attention mechanism.

Polypharmacy (multiple use of drugs) is an effective strategy for combating complex or co-existing diseases. However, a major consequence of polypharmacy is a higher risk of adverse side effects due to drug-drug interactions, which are rare and observed in relatively small clinical testing. Thus, identification of polypharmacy side effects remains challenging. Here, we propose a deep learning-based method, DeepPSE, to predict polypharmacy side effects in an end-to-end way. DeepPSE is composed of two main modules. First, multiple types of neural networks are constructed and fused to learn the deep representation of a drug pair. Second, the encoder block of transformer that includes self-attention mechanism is built to get latent features, which are further fed into the fully connected layer to predict polypharmacy side effects of drug pairs. Further, DeepPSE is compared with five baseline or state-of-the-art methods on a benchmark dataset of 964 types of polypharmacy side effects across 63473 drug pairs. Experimental results demonstrate that DeepPSE achieves better performance than that of all five methods. The source codes and data are available at https://github.com/ShenggengLin/DeepPSE.

Targeting the immune checkpoint B7-H3 for next-generation cancer immunotherapy.

Immune checkpoint inhibitors (ICIs) for programmed death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) have become preferred treatment strategies for several advanced cancers. However, response rates for these treatments are limited, which encourages the search for new ICI candidates. Recent reports have underscored significant roles of B7 homolog 3 protein (B7-H3) in tumor immunity and disease progression. While its multifaceted roles are being elucidated, B7-H3 has already entered clinical trials as a therapeutic target. In this review, we overview the recent results of clinical trials evaluating the antitumor activity and safety of B7-H3 targeting drugs. On this basis, we also discuss the challenges and opportunities arising from the application of these drugs. Finally, we point out current gaps to address in the understanding of B7-H3 function and regulation in order to fully unleash the future clinical utility of B7-H3-based therapies for the treatment of cancer.

Artificial intelligence-based bone-enhanced magnetic resonance image-a computed tomography/magnetic resonance image composite image modality in nasopharyngeal carcinoma radiotherapy.

BACKGROUND: In the radiotherapy of nasopharyngeal carcinoma (NPC), magnetic resonance imaging (MRI) is widely used to delineate tumor area more accurately. While MRI offers the higher soft tissue contrast, patient positioning and couch correction based on bony image fusion of computed tomography (CT) is also necessary. There is thus an urgent need to obtain a high image contrast between bone and soft tissue to facilitate target delineation and patient positioning for NPC radiotherapy. In this paper, our aim is to develop a novel image conversion between the CT and MRI modalities to obtain clear bone and soft tissue images simultaneously, here called bone-enhanced MRI (BeMRI). METHODS: Thirty-five patients were retrospectively selected for this study. All patients underwent clinical CT simulation and 1.5T MRI within the same week in Shenzhen Second People's Hospital. To synthesize BeMRI, two deep learning networks, U-Net and CycleGAN, were constructed to transform MRI to synthetic CT (sCT) images. Each network used 28 patients' images as the training set, while the remaining 7 patients were used as the test set (~1/5 of all datasets). The bone structure from the sCT was then extracted by the threshold-based method and embedded in the corresponding part of the MRI image to generate the BeMRI image. To evaluate the performance of these networks, the following metrics were applied: mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). RESULTS: In our experiments, both deep learning models achieved good performance and were able to effectively extract bone structure from MRI. Specifically, the supervised U-Net model achieved the best results with the lowest overall average MAE of 125.55 (P<0.05) and produced the highest SSIM of 0.89 and PSNR of 23.84. These results indicate that BeMRI can display bone structure in higher contrast than conventional MRI. CONCLUSIONS: A new image modality BeMRI, which is a composite image of CT and MRI, was proposed. With high image contrast of both bone structure and soft tissues, BeMRI will facilitate tumor localization and patient positioning and eliminate the need to frequently check between separate MRI and CT images during NPC radiotherapy.

Circular RNA_0001495 increases Robo1 expression by sponging microRNA-527 to promote the proliferation, migration and invasion of bladder cancer cells.

Bladder cancer (BCa) is a heterogeneous disease that poses great threats on public health. Increasing studies have identified the vital functions of circular RNAs (circRNAs) in BCa treatment. Hence, this current study set out to explore the modulatory role of circ_0001495 in BCa development. First, the expression of circ_0001495 was determined by reverse transcription quantitative polymerase chain reaction. Cell biological processes were then analyzed after altering the circ_0001495 expression in T24 cells. Next, interactions among circ_0001495, microRNA-527 (miR-527) and roundabout guidance receptor 1 (Robo1) were investigated by dual luciferase reporter gene assay, RNA pull down assay and FISH assay. Lastly, xenograft tumors in nude mice were established to explore the effect of circ_0001495 in vivo. It was found that circ_0001495 was highly expressed in BCa tissues and cells, and was further correlated with poor prognosis in BCa patients. In addition, circ_0001495 inhibited the activity of miR-527 by acting as a sponge to sponge miR-527, which further elevated the Robo1 expression. Lastly, circ_0001495 was found to promote the proliferation, migration and invasion of BCa cells in vitro through the miR-527/Robo1 axis and promote the growth and metastasis of BCa tumors in vivo. Altogether, findings in our study highlight the promoting role of circ_0001495 in the progression of BCa by increasing Robo1 via sponging miR-527, representing a promising target for BCa management.

A Prognostic Nomogram of Colon Cancer With Liver Metastasis: A Study of the US SEER Database and a Chinese Cohort.

BACKGROUND: Among colon cancer patients, liver metastasis is a commonly deadly phenomenon, but there are few prognostic models for these patients. METHODS: The clinicopathologic data of colon cancer with liver metastasis (CCLM) patients were downloaded from the Surveillance, Epidemiology and End Results (SEER) database. All patients were randomly divided into training and internal validation sets based on the ratio of 7:3. A prognostic nomogram was established with Cox analysis in the training set, which was validated by two independent validation sets. RESULTS: A total of 5,700 CCLM patients were included. Age, race, tumor size, tumor site, histological type, grade, AJCC N status, carcinoembryonic antigen (CEA), lung metastasis, bone metastasis, surgery, and chemotherapy were independently associated with the overall survival (OS) of CCLM in the training set, which were used to establish a nomogram. The AUCs of 1-, 2- and 3-year were higher than or equal to 0.700 in the training, internal validation, and external validation sets, indicating the favorable effects of our nomogram. Besides, whether in overall or subgroup analysis, the risk score calculated by this nomogram can divide CCLM patients into high-, middle- and low-risk groups, which suggested that the nomogram can significantly determine patients with different prognosis and is suitable for different patients. CONCLUSION: Higher age, the race of black, larger tumor size, higher grade, histological type of mucinous adenocarcinoma and signet ring cell carcinoma, higher N stage, RCC, lung metastasis, bone metastasis, without surgery, without chemotherapy, and elevated CEA were independently associated with poor prognosis of CCLM patients. A nomogram incorporating the above variables could accurately predict the prognosis of CCLM.

Green Synthesis of Metallic Nanoparticles and Their Potential Applications to Treat Cancer.

Nanoparticle synthesis using microorganisms and plants by green synthesis technology is biologically safe, cost-effective, and environment-friendly. Plants and microorganisms have established the power to devour and accumulate inorganic metal ions from their neighboring niche. The biological entities are known to synthesize nanoparticles both extra and intracellularly. The capability of a living system to utilize its intrinsic organic chemistry processes in remodeling inorganic metal ions into nanoparticles has opened up an undiscovered area of biochemical analysis. Nanotechnology in conjunction with biology gives rise to an advanced area of nanobiotechnology that involves living entities of both prokaryotic and eukaryotic origin, such as algae, cyanobacteria, actinomycetes, bacteria, viruses, yeasts, fungi, and plants. Every biological system varies in its capabilities to supply metallic nanoparticles. However, not all biological organisms can produce nanoparticles due to their enzymatic activities and intrinsic metabolic processes. Therefore, biological entities or their extracts are used for the green synthesis of metallic nanoparticles through bio-reduction of metallic particles leading to the synthesis of nanoparticles. These biosynthesized metallic nanoparticles have a range of unlimited pharmaceutical applications including delivery of drugs or genes, detection of pathogens or proteins, and tissue engineering. The effective delivery of drugs and tissue engineering through the use of nanotechnology exhibited vital contributions in translational research related to the pharmaceutical products and their applications. Collectively, this review covers the green synthesis of nanoparticles by using various biological systems as well as their applications.

Long-Noncoding RNA CASC9 Promotes Progression of Non-Small Cell Lung Cancer by Promoting the Expression of CDC6 Through Binding to HuR.

OBJECTIVE: The long-noncoding RNAs (lncRNAs) have been identified as key players in diverse cellular processes in non-small cell lung cancer (NSCLC). However, the understanding of biological functions and detailed mechanisms of lncRNAs is still limited. Herein, the lncRNA cancer susceptibility candidate 9 (CASC9) on NSCLC progression is investigated. MATERIALS AND METHODS: Expressions of CASC9, HuR and cell division cycle 6 (CDC6) in NSCLC tissues were detected with quantitative real-time polymerase chain reaction (qRT-PCR). The cell counting kit-8, transwell assays, and flow cytometry were used to examine cell proliferation, migration, and the cell cycle. Tumor growth in vivo was evaluated by xenograft tumor experiments and immunohistochemistry. RNA-binding protein immunoprecipitation (RIP) was used to identify the interaction between HuR and CDC6, and CASC9 and HuR. RESULTS: CASC9, CDC6 and HuR expression were found significantly upregulated in NSCLC tissues, which predicted poorer 5-year overall survival in NSCLC patients. Inhibition of CASC9 significantly reduced the malignancy of NSCLC cells, such as proliferation, migration and cell cycle. In vivo experiments further demonstrated that CASC9 knockdown reduced the tumor growth and the Ki-67 expression. Moreover, CASC9 knockdown inhibited the expression of CDC6 which was detected overexpressed in NSCLC tumor tissues. Then, up-regulation of CDC6 could partly reverse the negative effects of CASC9 on cell proliferation, migration and cell cycle. RIP assay and rescue experiment showed that CASC9 regulated CDC via binding to HuR. CONCLUSION: Our results indicate that CASC9 conferred an aggressive phenotype in NSCLC and might be a pivotal target for this disease.

Electronic cigarette exposure on insulin sensitivity of ApoE gene knockout mice.

INTRODUCTION: The current study aimed to investigate the effects of electronic cigarettes on insulin sensibility in ApoE gene knockout mice. METHODS: In total, 48 male ApoE gene knockout mice were randomly divided into four exposure groups: 1) electronic cigarette (e-cigarette) containing 12 mg/mL of nicotine, 2) e-cigarette without nicotine (0mg), 3) traditional cigarette (cigarette), and 4) fresh air (control). The first three groups were exposed to the associated smoke for 18 weeks. The body weight was recorded regularly in the four groups. After the last exposure, the concentrations of lipids, hs-CRP and TNF-α in serum were detected and the effect of electronic cigarettes on insulin tolerance was measured. RESULTS: The levels of serum lipid, hs-CRP and TNF-α in the e-cigarette, 0mg and cigarette groups were significantly increased compared with those in the control group (p<0.05). Also, the insulin tolerance in the e-cigarette, 0mg and cigarette groups was significantly decreased compared to that in the control group (p<0.05). CONCLUSIONS: Electronic cigarettes showed comparable effects to traditional cigarettes in influencing the metabolic functions in ApoE gene knockout mice.

Application of rare earth-doped nanoparticles in biological imaging and tumor treatment.

Rare earth-doped nanoparticles have been widely used in disease diagnosis, drug delivery, tumor therapy, and bioimaging. Among various bioimaging methods, the fluorescence imaging technology based on the rare earth-doped nanoparticles can visually display the cell activity and lesion evolution in living animals, which is a powerful tool in biological technology and has being widely applied in medical and biological fields. Especially in the band of near infrared (700-1700 nm), the emissions show the characteristics of deep penetration due to low absorption, low photon scattering, and low autofluorescence interference. Furthermore, the rare earth-doped nanoparticles can be endowed with the water solubility, biocompatibility, drug-loading ability, and the targeting ability for different tumors by surface functionalization. This confirms its potential in the cancer diagnosis and treatment. In this review, we summarized the recent progress in the application of rare earth-doped nanoparticles in the field of bioimaging and tumor treatment. The luminescent mechanism, properties, and structure design were also discussed.