Promoting fast MR imaging pipeline by full-stack AI.

Magnetic resonance imaging (MRI) is a widely used imaging modality in clinics for medical disease diagnosis, staging, and follow-up. Deep learning has been extensively used to accelerate k-space data acquisition, enhance MR image reconstruction, and automate tissue segmentation. However, these three tasks are usually treated as independent tasks and optimized for evaluation by radiologists, thus ignoring the strong dependencies among them; this may be suboptimal for downstream intelligent processing. Here, we present a novel paradigm, full-stack learning (FSL), which can simultaneously solve these three tasks by considering the overall imaging process and leverage the strong dependence among them to further improve each task, significantly boosting the efficiency and efficacy of practical MRI workflows. Experimental results obtained on multiple open MR datasets validate the superiority of FSL over existing state-of-the-art methods on each task. FSL has great potential to optimize the practical workflow of MRI for medical diagnosis and radiotherapy.

Evidence-based uncertainty-aware semi-supervised medical image segmentation.

Semi-Supervised Learning (SSL) has demonstrated great potential to reduce the dependence on a large set of annotated data, which is challenging to collect in clinical practice. One of the most important SSL methods is to generate pseudo labels from the unlabeled data using a network model trained with labeled data, which will inevitably introduce false pseudo labels into the training process and potentially jeopardize performance. To address this issue, uncertainty-aware methods have emerged as a promising solution and have gained considerable attention recently. However, current uncertainty-aware methods usually face the dilemma of balancing the additional computational cost, uncertainty estimation accuracy, and theoretical basis in a unified training paradigm. To address this issue, we propose to integrate the Dempster-Shafer Theory of Evidence (DST) into SSL-based medical image segmentation, dubbed EVidential Inference Learning (EVIL). EVIL performs as a novel consistency regularization-based training paradigm, which enforces consistency on predictions perturbed by two networks with different parameters to enhance generalization Additionally, EVIL provides a theoretically assured solution for precise uncertainty quantification within a single forward pass. By discarding highly unreliable pseudo labels after uncertainty estimation, trustworthy pseudo labels can be generated and incorporated into subsequent model training. The experimental results demonstrate that the proposed approach performs competitively when benchmarked against several state-of-the-art methods on public datasets, i.e., ACDC, MM-WHS, and MonuSeg. The code can be found at https://github.com/CYYukio/EVidential-Inference-Learning.

Laparoscopic Inguinal Hernia Repair for Female Patients: Experience from a High-volume Center in 20 years.

BACKGROUND: Although laparoscopic inguinal hernia repair (LIHR) is widely performed worldwide, few studies have focused on the procedure in female patients. This study investigated the characteristics and outcomes of female patients with inguinal hernias who underwent LIHR. MATERIALS AND METHODS: This study retrospectively analyzed the data of 7380 patients with inguinal hernia admitted to the General Surgery Department of Ruijin Hospital and underwent LIHR from January 2001 to December 2020. The clinical characteristics, surgical outcomes, and complications were assessed. RESULTS: In total, 572 female patients were enrolled in this study. The proportion of femoral hernias in female patients was higher in women than in male patients (17.4% vs. 0.3%, respectively). Mesothelial cysts of the round uterine ligament (MCURL) were noted in 74 patients. The mean age of patients with MCURL was lower than that of patients without MCURL (46.4 vs. 55.6, P =0.018). Seventy cases (93.3%) of MCURL were resected laparoscopically, and 5 cases were resected through an auxiliary small incision. The round ligament was cut off in 335 patients and preserved in 237. No significant differences were observed in the number of hospitalization days, recurrence rates, or complications between the transection and preservation groups. None of the cases were converted to laparotomy, and no recurrence was noted during follow-up. CONCLUSION: LIHR is safe and feasible in female patients. Treatment of femoral hernia, MCURL, and the round ligament of the uterus should be carefully considered during LIHR in female patients.

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-velocity tissue motion if motion compensation (MoCo) is not considered. While many studies have recently shown the interest of deep learning for the reconstruction of high-quality static images from PW or DW, its ability to achieve such performance while maintaining the capability of tracking cardiac motion has yet to be assessed. In this article, we addressed such issue by deploying a complex-weighted convolutional neural network (CNN) for image reconstruction and a state-of-the-art speckle-tracking method. The evaluation of this approach was first performed by designing an adapted simulation framework, which provides specific reference data, i.e., high-quality, motion artifact-free cardiac images. The obtained results showed that, while using only three DWs as input, the CNN-based approach yielded an image quality and a motion accuracy equivalent to those obtained by compounding 31 DWs free of motion artifacts. The performance was then further evaluated on nonsimulated, experimental in vitro data, using a spinning disk phantom. This experiment demonstrated that our approach yielded high-quality image reconstruction and motion estimation, under a large range of velocities and outperforms a state-of-the-art MoCo-based approach at high velocities. Our method was finally assessed on in vivo datasets and showed consistent improvement in image quality and motion estimation compared to standard compounding. This demonstrates the feasibility and effectiveness of deep learning reconstruction for ultrafast speckle-tracking echocardiography.

SemiMAR: Semi-Supervised Learning for CT Metal Artifact Reduction.

Metal artifacts lead to CT imaging quality degradation. With the success of deep learning (DL) in medical imaging, a number of DL-based supervised methods have been developed for metal artifact reduction (MAR). Nonetheless, fully-supervised MAR methods based on simulated data do not perform well on clinical data due to the domain gap. Although this problem can be avoided in an unsupervised way to a certain degree, severe artifacts cannot be well suppressed in clinical practice. Recently, semi-supervised metal artifact reduction (MAR) methods have gained wide attention due to their ability in narrowing the domain gap and improving MAR performance in clinical data. However, these methods typically require large model sizes, posing challenges for optimization. To address this issue, we propose a novel semi-supervised MAR framework. In our framework, only the artifact-free parts are learned, and the artifacts are inferred by subtracting these clean parts from the metal-corrupted CT images. Our approach leverages a single generator to execute all complex transformations, thereby reducing the model's scale and preventing overlap between clean part and artifacts. To recover more tissue details, we distill the knowledge from the advanced dual-domain MAR network into our model in both image domain and latent feature space. The latent space constraint is achieved via contrastive learning. We also evaluate the impact of different generator architectures by investigating several mainstream deep learning-based MAR backbones. Our experiments demonstrate that the proposed method competes favorably with several state-of-the-art semi-supervised MAR techniques in both qualitative and quantitative aspects.

Docetaxel-resistant triple-negative breast cancer cell-derived exosomal lncRNA LINC00667 reduces the chemosensitivity of breast cancer cells to docetaxel via targeting miR-200b-3p/Bcl-2 axis.

Development of docetaxel (TXT) resistance is a major obstacle for triple-negative breast cancer (TNBC) treatment. Additionally, chemoresistant cell-derived exosomes were able to change the chemo-response of chemosensitive recipient cells via transportation of lncRNAs. It has been shown that lncRNA LINC00667 level was significantly elevated in breast cancer tissues. Therefore, we explored whether LINC00667 level is increased in TXT-resistant TNBC cell-derived exosomes. In addition, whether exosomal LINC00667 derived from TXT-resistant TNBC cell could affect TXT sensitivity in TXT-sensitive TNBC cells was investigated as well. In the present study, exosomes were isolated from the TXT-resistant TNBC cells and from TXT-sensitive TNBC cells. Next, the level of LINC00667 in the isolated exosomes was detected with RT-qPCR. We found that LINC00667 expression was obviously elevated in TXT-resistant TNBC cell-derived exosomes compared to that in TXT-sensitive TNBC cell-derived exosomes. In addition, LINC00667 could be transferred from TXT-resistant TNBC cells to TNBC cells via exosomes. Moreover, TXT-resistant TNBC cell secreted exosomal LINC00667 markedly reduced the sensitivity of TNBC cells to TXT via upregulation of Bcl-2. Meanwhile, downregulation of LINC00667 notably enhanced the sensitivity of TXT-resistant TNBC cells to TXT through downregulation of Bcl-2. Additionally, LINC00667 was considered to be a ceRNA to sponge miR-200b-3p, thereby elevating Bcl-2 expression. Collectively, TXT-resistant TNBC cell-derived exosomal LINC00667 could decrease the chemosensitivity of TNBC cells to TXT via regulating miR-200b-3p/Bcl-2 axis. These findings suggested that LINC00667 might serve as a promising target for enhancing sensitivity of TNBC cells to TXT therapy.

Radiotherapy Combined With Concurrent Nedaplatin-Based Chemotherapy for Stage II-III Esophageal Squamous Cell Carcinoma.

Objective: This study was conducted to explore the appropriate radical radiation dose in concurrent chemoradiotherapy (CCRT) for patients with inoperable stage II-III esophageal squamous cell carcinoma (ESCC). Methods: This retrospective study included patients with esophageal cancer (EC) from the database of patients treated at the Affiliated Zhangjiagang Hospital of Soochow University (1/2015-12/2019). Overall survival (OS), progression-free survival (PFS), objective remission rate (ORR), first failure pattern, and toxicities were collected. Results: 112 patients treated with intensity-modulated radiation therapy (IMRT) combined with concurrent chemotherapy of nedaplatin-based regimens were included. Fifty-eight (51.8%) and 54 (48.2%) patients received 60 (HD) and 50.4 (LD) Gy of radiotherapy, respectively. The HD group showed superior OS and a trend for longer PFS compared with the LD group (median OS: 25.5 vs 17.5 months, P = .021; median PFS: 14.0 vs 10.5 months, P = .076). There were more patients with a complete remission (CR) in the HD group than in the LD group (P=.016). The treatment-related toxicities were generally acceptable, but HD radiotherapy would increase the incidence of grade ≥3 late radiotoxicity (22.4% vs 5.6%, P = .011). Conclusion: In nedaplatin-based CCRT for stage II-III ESCC, the radiotherapy dose of 60 Gy achieved a better prognosis. Strengths and limitations of this study: A comparative study of 50.4 Gy and 60 Gy was conducted to evaluate whether 50.4 Gy can be used as a radical radiotherapy dose for inoperable stage II-III esophageal squamous cell carcinoma from a real-world perspective.The highly consistent selection criteria in our study make analysis results highly reliable and scientific.The existing research results support that nedaplatin can be used in concurrent chemoradiotherapy for esophageal squamous cell carcinoma, and this study focuses on the discovery of a better nedaplatin-based combination regimen.The findings of this study are limited to a single-center study with a non-large sample size.Inevitably, recall bias may exist in this retrospective study.Surgery was not involved in the follow-up treatment after concurrent chemoradiotherapy, which may worsen the prognosis of some patients.

Downregulation of PDGF-D Inhibits Proliferation and Invasion in Breast Cancer MDA-MB-231 Cells.

BACKGROUND: The platelet derived growth factor-D (PDGF-D) plays an important role in breast tumor aggressiveness. However, limited study has investigated the effect of silencing PDGF-D on the biological function of breast cancer. The purpose of this study is to clarify the potential value of PDGF-D as a target for breast cancer treatment. METHODS: Reverse transcription-polymerase chain reaction and western blot were used to detect PDGF-D expression in 5 different breast cancer cells. The lentiviral vector was usd to silence PDGF-D in MDA-MB-231 cells. Then, Methyl Thiazolyl Tetrazolium was used to detect cell viability, 5-Ethynyl-2'- deoxyuridine and a soft agar assay were used to detect cell proliferation and clonality. Additionally, cell apoptosis after PDGF-D knockdown was measured by Annexin V/ Prodium Iodide staining, and cell migration was detected by trans-well assay. Survival rate and tumor size were measured by nude mice transplantation. RESULTS: The MDA-MB-231 and SK-BR-3 cell lines showed higher PDGF-D expression than the MCF7 cell lines (P<.05). After the PDGF-D gene was silenced, the growth and colony forming abilitys ignificantly decreased (P<.05) together with the induction of apoptosis in MDA-MB-231 cells (P<.05). Moreover, MDA-MB-231 cells with PDGF-D silencing showed significantly diminished aggressive migration and invasion potential compared to other cells (P<.05). In vivo experiments also indicated that PDGF-D silencing inhibited tumor growth and improved the survival rate of tumor-bearing mice. CONCLUSION: Downregulation of PDGF-D had dramatic effects on breast cancer cell proliferation, apoptosis and migration, which indicates that it plays an important role in breast cancer development and progression.

Complex Convolutional Neural Networks for Ultrafast Ultrasound Imaging Reconstruction From In-Phase/Quadrature Signal.

Ultrafast ultrasound imaging remains an active area of interest in the ultrasound community due to its ultrahigh frame rates. Recently, a wide variety of studies based on deep learning have sought to improve ultrafast ultrasound imaging. Most of these approaches have been performed on radio frequency (RF) signals. However, in- phase/quadrature (I/Q) digital beamformers are now widely used as low-cost strategies. In this work, we used complex convolutional neural networks for reconstruction of ultrasound images from I/Q signals. We recently described a convolutional neural network architecture called ID-Net, which exploited an inception layer designed for reconstruction of RF diverging-wave ultrasound images. In the present study, we derive the complex equivalent of this network, i.e., complex-valued inception for diverging-wave network (CID-Net) that operates on I/Q data. We provide experimental evidence that CID-Net provides the same image quality as that obtained from RF-trained convolutional neural networks, i.e., using only three I/Q images, CID-Net produces high-quality images that can compete with those obtained by coherently compounding 31 RF images. Moreover, we show that CID-Net outperforms the straightforward architecture that consists of processing real and imaginary parts of the I/Q signal separately, which thereby indicates the importance of consistently processing the I/Q signals using a network that exploits the complex nature of such signals.

Tripartite motif-containing protein 6 facilitates growth and migration of breast cancer through degradation of STUB1.

Proteins in the tripartite motif-containing protein (TRIM) family participates in carcinogenesis. However, little attention was focused on the role of TRIM6 on development of breast cancer. Expression level of TRIM6 was found to be markedly enhanced in breast cancer cells and tissues. Functional assays demonstrated that overexpression of TRIM6 promoted breast cancer progression through increase of YAP1 (Yes-associated Protein 1), while knockdown of TRIM6 suppressed in vitro breast cancer progression and in vivo tumor growth through decrease of YAP1. Co-Immunoprecipitation (co-IP) showed that TRIM6 interacted with STUB1 (stress induced phosphoprotein 1 homology and U-box containing protein 1). TRIM6 promoted ubiquitination-mediated degradation of STUB1 to promote YAP1 signaling. Overexpression of STUB1 attenuated TRIM6-induced promotion of breast cancer growth. In conclusion, TRIM6 contributed to breast cancer progression through ubiquitination-dependent proteasomal degradation of STUB1 and provocation of YAP1 pathway, providing potential therapeutic target for breast cancer.

DCAF13 promotes triple-negative breast cancer metastasis by mediating DTX3 mRNA degradation.

DCAF13 is firstly identified as a substrate receptor of CUL4-DDB1 E3 ligase complex. This study disclosed that DCAF13 acted as a novel RNA binding protein (RBP) that contributed to triple-negative breast cancer (TNBC) metastasis. Clinical data obtained from TCGA and our collection showed that DCAF13 was closely correlated with poor clinicopathological characteristics and overall survival, which indicated DCAF13 may serve as a diagnostic marker for TNBC metastasis. Functionally, DCAF13 overexpression or suppression was sufficient to enhance or decrease breast cancer cell migration and invasion. Mechanistically, DCAF13 functioned as an RBP by binding with the AU-rich element (ARE) of DTX3 mRNA 3'UTR to accelerate its degradation. Moreover, we identified that DTX3 promoted the ubiquitination and degradation of NOTCH4. Finally, increased DCAF13 expression led to post-transcriptional decay of DTX3 mRNA and consequently activated of NOTCH4 signaling pathway in TNBC. In conclusion, these results identified that DCAF13 as a diagnostic marker and therapeutic target for TNBC treatment. Abbreviation: DCAF13: DDB1 and CUL4-associated factor 13; DDB1: DNA-binding protein 1; CUL4: Cullin 4; CRL4, Cullin-ring finger ligase 4; RBP: RNA binding protein; TNBC: triple-negative breast cancer; ARE: AU-rich element; DTX3: Deltex E3 ubiquitin ligase 3; HER2: human epidermal growth factor receptor 2; ER: estrogen receptor; PR: progesterone receptor; PTEN: phosphatase and tensin homolog deleted on chromosome 10; EMT: epithelial-mesenchymal transition.

circFAT1(e2) Promotes Papillary Thyroid Cancer Proliferation, Migration, and Invasion via the miRNA-873/ZEB1 Axis.

Circular RNAs (circRNAs) play an extremely important regulatory role in the occurrence and development of various malignant tumors including papillary thyroid cancer (PTC). circFAT1(e2) is a new type of circRNA derived from exon 2 of the FAT1 gene, which is distributed in the cytoplasm and nucleus of PTC cells. However, so far, the role of circFAT1(e2) in PTC is still unclear. In this study, circFAT1(e2) was found to be highly expressed in PTC cell lines and tissues. circFAT1(e2) knockdown suppressed PTC cell growth, migration, and invasion. Also, circFAT1(e2) acted as a sponge for potential microRNAs (miRNAs) to modulate cancer progression. A potential miRNA target was discovered to be miR-873 which was targeted by circFAT1(e2) in PTC. The dual-luciferase assay conducted later also confirmed that there was indeed a direct interaction between circFAT1(e2) and miR-873. This study also confirmed that circFAT1(e2) inhibited the miR-873 expression and thus promoted the ZEB1 expression, thus affecting the proliferation, metastasis, and invasion of PTC cells. In conclusion, the results of this study indicated that circFAT1(e2) played a carcinogenic role by targeting the miR-873/ZEB1 axis to promote PTC invasion and metastasis, which might become a potential novel target for therapy of PTC.

Hypermethylation of lncRNA MEG3 impairs chemosensitivity of breast cancer cells.

BACKGROUND: Chemoresistance posed a barrier to successful treatment of breast cancer (BC), and lncRNA MEG3 has been documented to implicate in BC development. However, whether MEG3 methylation, which led to low MEG3 expression, was relevant to BC progression and chemoresistance remained uncertain. METHODS: In the aggregate, 374 pairs of tumor tissues and adjacent normal tissues were collected from pathologically confirmed BC patients, and four BC cell lines, including MDA-MB-231, Bcap-37, MCF-7, and SK-BR-3, were purchased. Moreover, methylation-specific polymerase chain reaction (PCR) was adopted to evaluate the methylation status of BC tissues and cell lines, and chemo-tolerance of BC cell lines was assessed by performing MTT assay. Concurrently, transwell assay and scratch assay were carried out to estimate the migratory and invasive capability of BC cell lines. RESULTS: Methylated MEG3, lowly expressed MEG3, large tumor size (≥2 cm), advanced TNM grade and lymphatic metastasis were potentially symbolic of poor prognosis among BC patients (P < .05). Besides, MDA-MB-231 cell line exhibited the strongest resistance against paclitaxel, adriamycin, and vinorelbine (P < .05), while MCF-7 cell line seemed more sensitive against these drugs than any other BC cell line (P < .05). Furthermore, pcDNA3.1-MEG3 and 5-Aza-dC markedly sensitized MDA-MB-231 and MCF-7 cell lines against the drug treatments (P < .05). Simultaneously, proliferation and metastasis of the BC cell lines were slowed down under the force of pcDNA3.1-MEG3 and 5-Aza-dC (P < .05). CONCLUSION: Preventing methylation of MEG3 might matter in lessening BC chemoresistance, owing to its hindering proliferation and metastasis of BC cells.

Reconstruction for Diverging-Wave Imaging Using Deep Convolutional Neural Networks.

In recent years, diverging wave (DW) ultrasound imaging has become a very promising methodology for cardiovascular imaging due to its high temporal resolution. However, if they are limited in number, DW transmits provide lower image quality compared with classical focused schemes. A conventional reconstruction approach consists in summing series of ultrasound signals coherently, at the expense of frame rate, data volume, and computation time. To deal with this limitation, we propose a convolutional neural network (CNN) architecture, Inception for DW Network (IDNet), for high-quality reconstruction of DW ultrasound images using a small number of transmissions. In order to cope with the specificities induced by the sectorial geometry associated with DW imaging, we adopted the inception model composed of the concatenation of multiscale convolution kernels. Incorporating inception modules aims at capturing different image features with multiscale receptive fields. A mapping between low-quality images and corresponding high-quality compounded reconstruction was learned by training the network using in vitro and in vivo samples. The performance of the proposed approach was evaluated in terms of contrast ratio (CR), contrast-to-noise ratio (CNR), and lateral resolution (LR), and compared with standard compounding method and conventional CNN methods. The results demonstrated that our method could produce high-quality images using only 3 DWs, yielding an image quality equivalent to that obtained with compounding of 31 DWs and outperforming more conventional CNN architectures in terms of complexity, inference time, and image quality.

Circular RNA hsa_circ_0061825 (circ-TFF1) contributes to breast cancer progression through targeting miR-326/TFF1 signalling.

OBJECTIVES: Circular RNAs (circRNAs) are RNA transcripts that belong to non-coding RNAs (ncRNAs), whose implication in human cancers has been recently demonstrated. However, the specific role of multiple circRNAs in breast cancer remains unidentified. MATERIALS AND METHODS: Microarray analysis and bioinformatics analysis were applied to select circRNA and miRNA, respectively. The loop structure of circ-TFF1 was confirmed using RNase R treatment, divergent primer PCR and Sanger sequencing. qRT-PCR and Western blot were employed for gene expressions. In vitro and in vivo experiments were conducted to assess the function of circ-TFF1 in biological processes in breast cancer cells. FISH and subcellular separation indicated circ-TFF1 cellular distribution. Luciferase reporter and RIP assays and Pearson's correlation analysis were performed to evaluate relationships between genes. RESULTS: Circ-TFF1 and TFF1 were both upregulated and positively associated with each other in breast cancer. Knockdown of circ-TFF1 hindered breast cancer cell proliferation, migration, invasion and EMT in vitro and controlled tumour growth in vivo. Circ-TFF1 acted as a ceRNA of TFF1 by sponging miR-326, and its contribution to breast cancer progression was mediated by miR-326/TFF1 axis. CONCLUSIONS: Circ-TFF1 is a facilitator in breast cancer relying on TFF1 by absorbing miR-326, providing a novel promising target for BC treatment.

Discovery of N-Phenyl-4-(1H-pyrrol-3-yl)pyrimidin-2-amine Derivatives as Potent Mnk2 Inhibitors: Design, Synthesis, SAR Analysis, and Evaluation of in vitro Anti-leukaemic Activity.

BACKGROUND: Aberrant expression of eukaryotic translation initiation factor 4E (eIF4E) is common in many types of cancer including acute myeloid leukaemia (AML). Phosphorylation of eIF4E by MAPK-interacting kinases (Mnks) is essential for the eIF4E-mediated oncogenic activity. As such, the pharmacological inhibition of Mnks can be an effective strategy for the treatment of cancer. METHODS: A series of N-phenyl-4-(1H-pyrrol-3-yl)pyrimidin-2-amine derivatives was designed and synthesised. The Mnk inhibitory activity of these derivatives as well as their anti-proliferative activity against MV4-11 AML cells was determined. RESULTS: These compounds were identified as potent Mnk2 inhibitors. Most of them demonstrated potent anti-proliferative activity against MV4-11 AML cells. The cellular mechanistic studies of the representative inhibitors revealed that they reduced the level of phosphorylated eIF4E and induced apoptosis by down-regulating the anti-apoptotic protein myeloid cell leukaemia 1 (Mcl-1) and by cleaving poly(ADP-ribose)polymerase (PARP). The lead compound 7k possessed desirable pharmacokinetic properties and oral bioavailability. CONCLUSION: This work proposes that exploration of the structural diversity in the context of Nphenyl- 4-(1H-pyrrol-3-yl)pyrimidin-2-amine would offer potent and selective Mnk inhibitors.

Clinical significance of prognostic score based on age, tumor size, and grade in gastric cancer after gastrectomy.

BACKGROUND: Postoperative management and survival of gastric cancer is mainly determined by pathologic TNM stage. However, gastric cancer is a heterogeneity group, and the survival is quite different even when they are in the same TNM stage. Moreover, TNM stage system does not grasp other important clinicopathologic factors to determine the survival. The aim of the present study is to propose and validate prognostic score based on age, tumor size, and grade. MATERIALS AND METHODS: Patients diagnosed with gastric cancer in the Surveillance, Epidemiology, and End Results database from 1988 to 2012 were included in the present study. Kaplan-Meier methods were adopted and multivariable Cox regression models were built for the analysis of long-term survival outcomes and risk factors. RESULTS: A total of 26,091 eligible patients diagnosed with noncardia gastric cancer were included in the study. In the univariate and multivariate survival analysis, age at diagnosis, tumor grade, and tumor size were validated as independent prognostic factors (P<0.05). Then, we proposed a prognostic score calculated from the number of risk factors, with 0, 1, and 2 points each given for favorable, intermediate, and poor prognostic categories of age (≤50, 50-70, and >70), grade (well, moderate, and poor differentiation), and size (≤3, 3-6, ≥7 cm). The prognostic score was verified as independent predictor in both univariate and multivariate survival analyses (P<0.001). In addition, nomograms on cause-specific survival were established according to prognostic factor and all other significant factors, and c-index was 0.715 (95% CI: 0.706-0.725). CONCLUSION: Prognostic score based on age, tumor size, and grade is an independent predictor of survival after gastrectomy. The novel prognostic score can improve the accuracy of prediction for current TNM stage system. Patients who are with a high prognostic score should undergo extensive follow-up after surgery.

Removal of hexavalent chromium from water by modified sponge iron particles and insights into mechanism.

Sponge iron particles modified with expanded graphite and Cu were used to purify solutions contaminated with aqueous Cr(VI). A removal mechanism that involved physical adsorption and a redox reaction is proposed. The reaction, which consisted of rapid adsorption, a desorption stage, and an adsorption-desorption equilibrium stage, corresponded to a first-order kinetic model. The properties of the adsorption materials before and after use were investigated by X-ray diffraction, scanning electron microscopy-energy-dispersive spectroscopy, Fourier-transform infrared spectroscopy, energy-dispersive X-ray fluorescence spectroscopy, and surface area measurements. Changes in the surface properties, e.g., attachment of material to the surface and filling of pores with Cr, were clearly observed. The Langmuir model best described Cr(VI) adsorption on the sponge iron and its modified particles. Removal efficiencies of 98.7, 98.8, and 100% were achieved in 7 h at a Cr(VI) dosage of 10 mg/L. Sponge iron particles are therefore potential adsorbents and after modification give good removal of Cr(VI) ions from contaminated water.

Gastric Neuroendocrine Tumors (G-Nets): Incidence, Prognosis and Recent Trend Toward Improved Survival.

BACKGROUND/AIMS: Gastric neuroendocrine tumors (G-NETs) are uncommon neoplasms that can present with or without clinical symptoms. In this study, we evaluated the incidence, prognosis, and temporal trends of G-NETs. METHODS: We analyzed all cases of G-NETs registered in the Surveillance, Epidemiology, and End Results (SEER) database from 1973 to 2014. Incidence was estimated by age and joinpoint analyses. Survival rates were calculated and survival trends over time were evaluated. RESULTS: A total of 3740 eligible patients were enrolled in the study. G-NETs incidence increased from 0.31 per 1 000 000 patients in 1975 to 4.85 in 2014, with an annual percentage changes (APCs) of 8.9% (95% confidence interval [CI] = 7.7% to 10.21%, P < 0.001, t test (29) from 1975 to 2001 and 3.6% from 2002 to 2014 (95% CI= 2.3% to 4.9%, P < 0.001). For cases diagnosed between 1973 and 1982, five-year survival was 62.8% ± 7.0% (Standard error, SE) and increased to 86.7% ± 0.7% for cases diagnosed between 2003 and 2012 (P < 0.001). Years of diagnosis, gender, age at diagnosis, marital status, grade, tumor size, tumor stage, and surgery performed or not were the strongest predictors of worse survival in both univariate and multivariate analysis (P<0.05). CONCLUSION: G-NETs are uncommon neoplasms but the incidence is growing. Survival has improved in the past decades. Years of diagnosis, gender, age at diagnosis, marital status, grade, tumor size, tumor stage, and surgery status predict survival in patients with G-NETs.

Dual Inhibition of Mnk2 and FLT3 for potential treatment of acute myeloid leukaemia.

The discovery of novel anti-AML therapeutic agents is urgently needed, but the complex heterogeneity of the disease has so far hampered the development of a curative treatment. FLT3 inhibitors have shown therapeutic potential in clinical trials; but a monotherapy regimen has been associated with resistance mediated by the activation of parallel signalling circuitry, including MAPK and mTOR. Therefore, inhibiting a nexus of the two signalling pathways along with inhibition of FLT3 might be advantageous. Herein, we propose that a dual inhibition of FLT3 and Mnk would provide a better clinical option for AML patients compared to targeting FLT3 alone. Thus, a series of N-phenyl-4-(thiazol-5-yl)pyrimidin-2-amines and 4-(indol-3-yl)-N-phenylpyrimidin-2-amines were prepared. Potent Mnk2 inhibitors, FLT3 inhibitors, and dual inhibitors of Mnk2 and FLT3 were identified and their anti-proliferative activities assessed against MV4-11 AML cell lines. Dual inhibition of FLT3 and Mnk2 caused the increased apoptotic cell death of MV4-11 cells compared to inhibition of FLT3 or Mnk2 alone.