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Cell division cycle 20 (CDC20) and microRNAs (miRNAs) are differentially expressed in non-small cell lung cancer (NSCLC). The current study aimed to investigate the role of miR-1321 and miR-7515 regulation in CDC20 during NSCLC development. CDC20 expression in paracancerous and tumor tissues was assessed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The relationship between CDC20 expression and prognosis of patients was analyzed using the TCGA database. The expression profile of CDC20 in healthy lung cells and NSCLC cells was detected using qRT-PCR and western blotting. After the knockdown of CDC20 in NSCLC cells, the cell proliferation, apoptosis, migration, invasion, and cell cycle changes were investigated by CCK8, EdU, flow cytometry, wound healing, and Transwell assays. The miRNAs targeting CDC20 were predicted using two bioinformatics websites and validated using dual-luciferase assays. CDC20 was enhanced in NSCLC tissues and cells, thus predicting the poor prognosis in NSCLC patients. After CDC20 inhibition, the malignant phenotype of NSCLC cells was reverted. miR-1321 and miR-7515 targeted CDC20 and exhibited the same anti-tumor effects as CDC20 silencing. Functional rescue experiments showed that CDC20 overexpression averted the anti-tumor effects of miR-1321 and miR-7515 on NSCLC cells. miR-1321 and miR-7515 inhibited NSCLC development by targeting CDC20. Thus, the current study has implications in NSCLC treatment and provides novel insights into NSCLC management.

Introduction Plants containing aristolochic acid and its derivatives are nephrotoxic, mutagenic, and carcinogenic to humans; chronic diet poisoning caused by the aristolochic acid is the cause of endemic (Balkan) nephropathy and related cancers. Objective To develop a colloidal gold immunochromatographic test strip (ICS) based on the competitive format for the rapid detection of aristolochic acid A (AA-A) in herbal medicinal materials. Materials and methods For the ICS based on gold nanoparticles (AuNPs), the antigen [AA-A-bovine serum albumin (BSA)], and goat anti-mouse IgG were drawn on the nitrocellulose membrane as the test line (T line) and the control line (C line), respectively. Monoclonal antibody (MAb)-AuNP conjugates were sprayed onto the conjugate pad. The sensitivity of the ICS was 6 ng/mL, and the test was completed in 10 min. The analysis of AA-A in traditional Chinese medicine samples showed that the ICS results were in good agreement with those obtained by high-performance liquid chromatography methods. Conclusion These results demonstrated that the ICS test could be used as a reliable, rapid, cost-effective, and convenient qualitative tool for on-site screening techniques to detect AA-A in herbal medicinal materials without any special instrumentation.

Natural hydrogen (H2 ) has gained considerable attentions as a renewable energy resource to mitigate the globally increasing environmental concerns. Low-temperature serpentinization (

PURPOSE Propagation of contours from high-quality magnetic resonance (MR) images to treatment planning ultrasound (US) images with severe needle artifacts is a challenging task, which can greatly aid the organ contouring in high dose rate (HDR) prostate brachytherapy. In this study, a deep learning approach was developed to automatize this registration procedure for HDR brachytherapy practice. METHODS Because of the lack of training labels and difficulty of accurate registration from inferior image quality, a new segmentation-based registration framework was proposed for this multi-modality image registration problem. The framework consisted of two segmentation networks and a deformable registration network, based on the weakly -supervised registration strategy. Specifically, two 3D V-Nets were trained for the prostate segmentation on the MR and US images separately, to generate the weak supervision labels for the registration network training. Besides the image pair, the corresponding prostate probability maps from the segmentation were further fed to the registration network to predict the deformation matrix, and an augmentation method was designed to randomly scale the input and label probability maps during the registration network training. The overlap between the deformed and fixed prostate contours was analyzed to evaluate the registration accuracy. Three datasets were collected from our institution for the MR and US image segmentation networks, and the registration network learning, which contained 121, 104, and 63 patient cases, respectively. RESULTS The mean Dice similarity coefficient (DSC) results of the two prostate segmentation networks are 0.86 ± 0.05 and 0.90 ± 0.03, for MR images and the US images after the needle insertion, respectively. The mean DSC, center-of-mass (COM) distance, Hausdorff distance (HD), and averaged symmetric surface distance (ASSD) results for the registration of manual prostate contours were 0.87 ± 0.05, 1.70 ± 0.89 mm, 7.21 ± 2.07 mm, 1.61 ± 0.64 mm, respectively. By providing the prostate probability map from the segmentation to the registration network, as well as applying the random map augmentation method, the evaluation results of the four metrics were all improved, such as an increase in DSC from 0.83 ± 0.08 to 0.86 ± 0.06 and from 0.86 ± 0.06 to 0.87 ± 0.05, respectively. CONCLUSIONS A novel segmentation-based registration framework was proposed to automatically register prostate MR images to the treatment planning US images with metal artifacts, which not only largely saved the labor work on the data preparation, but also improved the registration accuracy. The evaluation results showed the potential of this approach in HDR prostate brachytherapy practice.

The RefleXion X1 is a novel radiotherapy machine designed for image-guided radiotherapy (IGRT) and biology-guided radiotherapy (BgRT). Its treatment planning system (TPS) generates IMRT and SBRT plans for a 6MV-FFF beam delivered axially via 50 firing positions with the couch advancing every 2.1 mm. The purpose of this work is to report the TPS commissioning results for the first clinical installation of RefleXion™ X1.CT images of multiple phantoms were imported into the RefleXion TPS to evaluate the accuracy of data transfer, anatomical modeling, plan evaluation, and dose calculation. Comparisons were made between the X1, Eclipse™, and MIM™. Dosimetric parameters for open static fields were evaluated in water and heterogeneous slab phantoms. Representative clinical IMRT and SBRT cases were planned and verified with ion chamber, film, and ArcCHECKThe average difference between the TPS-reported and known HU values was -1.4 ± 6.0 HU. For static fields, the agreements between the TPS-calculated and measured PDDThe TPS commissioning results of the RefleXion X1 TPS were within the tolerances specified by AAPM TG 53, MPPG 5.a, TG 119, and TG 148. A subset of the commissioning tests has been identified as baseline data for an ongoing QA program.

Crop production is facing unprecedented challenges. Despite the fact that the food supply has significantly increased over the past half-century, ~8.9 and 14.3% people are still suffering from hunger and malnutrition, respectively. Agricultural environments are continuously threatened by a booming world population, a shortage of arable land, and rapid changes in climate. To ensure food and ecosystem security, there is a need to design future crops for sustainable agriculture development by maximizing net production and minimalizing undesirable effects on the environment. The future crops design projects, recently launched by the National Natural Science Foundation of China and Chinese Academy of Sciences (CAS), aim to develop a roadmap for rapid design of customized future crops using cutting-edge technologies in the Breeding 4.0 era. In this perspective, we first introduce the background and missions of these projects. We then outline strategies to design future crops, such as improvement of current well-cultivated crops, de novo domestication of wild species and redomestication of current cultivated crops. We further discuss how these ambitious goals can be achieved by the recent development of new integrative omics tools, advanced genome-editing tools and synthetic biology approaches. Finally, we summarize related opportunities and challenges in these projects.

Purpose Contouring intraprostatic lesions is a prerequisite for dose-escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning-based approach was developed for automatic intraprostatic lesion segmentation in multiparametric magnetic resonance imaging (mpMRI) images contributing to clinical practice. Methods Multiparametric magnetic resonance imaging images from 136 patient cases were collected from our institution, and all these cases contained suspicious lesions with Prostate Imaging Reporting and Data System (PI-RADS) score ≥ 4. The contours of the lesion and prostate were manually created on axial T2-weighted (T2W), apparent diffusion coefficient (ADC) and high b-value diffusion-weighted imaging (DWI) images to provide the ground truth data. Then a multiple branch UNet (MB-UNet) was proposed for the segmentation of an indistinct target in multi-modality MRI images. An encoder module was designed with three branches for the three MRI modalities separately, to fully extract the high-level features provided by different MRI modalities; an input module was added by using three sub-branches for three consecutive image slices, to consider the contour consistency among different image slices; deep supervision strategy was also integrated into the network to speed up the convergency of the network and improve the performance. The probability maps of the background, normal prostate and lesion were output by the network to generate the segmentation of the lesion, and the performance was evaluated using the dice similarity coefficient (DSC) as the main metric. Results A total of 162 lesions were contoured on 652 image slices, with 119 lesions in the peripheral zone, 38 in the transition zone, four in the central zone and one in the anterior fibromuscular stroma. All prostates were also contoured on 1,264 image slices. As for the segmentation of lesions in the testing set, MB-UNet achieved a per case DSC of 0.6333, specificity of 0.9993, sensitivity of 0.7056; and global DSC of 0.7205, specificity of 0.9993, sensitivity of 0.7409. All the three deep learning strategies adopted in this study contributed to the performance promotion of the MB-UNet. Missing the DWI modality would degrade the segmentation performance more markedly compared with the other two modalities. Conclusions A deep learning-based approach with proposed MB-UNet was developed to automatically segment suspicious lesions in mpMRI images. This study makes it feasible to adopt boosting intraprostatic lesions in clinical practice to achieve better outcomes.

Background This study investigated the prognostic impact of (neo‐)adjuvant radiation therapies in early stage esophageal cancer. Methods A retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database was conducted from 2004 to 2016. Patients with pathologically staged T1‐4N0M0 esophageal cancer were divided into two treatment groups: (i) neoadjuvant radiotherapy followed by surgery; and (ii) upfront esophagectomy followed by adjuvant radiotherapy. Propensity scored match and Cox proportional hazards model were used to identify covariates associated with overall survival and cancer‐specific survival. Results There were 821 patients selected, of whom 588 (71.6%) received neoadjuvant radiotherapy and 233 (28.4%) received adjuvant radiotherapy. For the entire cohort, neoadjuvant radiotherapy was associated with a significantly benefit in five‐year survival outcomes compared with adjuvant radiotherapy (P, In this population‐based study, we indicated that the addition of neoadjuvant RT for pT3‐4N0 diseases followed by esophagectomy was associated with improved cancer‐specific survival in patients with tumor lengths 5 cm and squamous cell carcinoma. The identification of higher‐risk patients for neoadjuvant therapy would be expected to yield better results than taking a uniform approach to this population, to avoid unnecessary and possibly harmful treatment in node‐negative diseases.

Background The impact of neoadjuvant chemoradiotherapy (nCRT) on early stage esophageal cancer is unknown. Here, we compared the outcomes after esophagectomy alone or nCRT plus surgery for clinically staged node‐negative esophageal cancer. Methods We searched the Surveillance, Epidemiology, and End Results database for patients with clinically node‐negative (cN0) esophageal cancer from 2004 to 2016 who underwent surgery alone or nCRT plus surgery. Propensity score matching and Cox regression analysis were used to identify covariates associated with overall survival and cancer‐specific survival. Results A total of 1587 patients were retrospectively identified, of whom 49.8% (n = 791) received nCRT and 80.2% (n = 1273) were truly node‐negative diseases. For the entire cohort, surgery alone was associated with a statistically significant but modest absolute increase in survival outcomes (P, This study focuses on the use of neoadjuvant chemoradiotherapy to esophageal carcinoma patients with clinically staged node‐negative (cN0) status. Finally, compared with surgery alone, cN0 esophageal cancer with falsely node‐negative (pN+) or localized truly node‐negative (pT3‐4N0) gain a significant survival benefit from neoadjuvant chemoradiation. However, neoadjuvant chemoradiation plus surgery was associated with decreased survival for early‐staged true node‐negative (pT1‐2N0) patients. Despite the inherent limitations, this population‐based study allows for a robust analysis of patients with cN0 esophageal carcinoma and the benefits of neoadjuvant chemoradiation when stratified by nodal and tumor status, and this finding may have significant implications on the use of neoadjuvant chemoradiation in patients with cN0 disease.

PURPOSE High-Dose-Rate (HDR) brachytherapy is one of the most effective ways to treat the prostate cancer, which is the second most common cancer in men worldwide. This treatment delivers highly conformal dose through the transperineal needle implants and is guided by a real time ultrasound (US) imaging system. Currently, the brachytherapy needles in the US images are manually segmented by physicists during the treatment, which is time consuming and error prone. In this study, we propose a set of deep learning-based algorithms to accurately segment the brachytherapy needles and locate the needle tips from the US images. METHODS Two deep neural networks are developed to address this problem. First, a modified deep U-Net is used to segment the pixels belonging to the brachytherapy needles from the US images. Second, an additional VGG-16-based deep convolutional network is combined with the segmentation network to predict the locations of the needle tips. The networks are trained and evaluated on a clinical US images dataset with labeled needle trajectories collected in our hospital (Institutional Review Board approval (IRB 41755)). RESULTS The evaluation results show that our method can accurately extract the trajectories of the needles with a resolution of 0.668 mm and 0.319 mm in x and y direction, respectively. 95.4% of the x direction and 99.2% of the y direction have error ≤ 2 mm. Moreover, the position resolutions of the tips are 0.721, 0.369, and 1.877 mm in x, y, and z directions, respectively, while 94.2%, 98.3%, and 67.5% of the data have error ≤ 2 mm. CONCLUSIONS This paper proposed a neural network-based algorithm to segment the brachytherapy needles from the US images and locate the needle tip. It can be used in the HDR brachytherapy to help improve the efficiency and quality of the treatments.

Background Myocardial infarction in the absence of obstructive coronary artery disease (MINOCA) accounts for approximately 5% ‐ 6% of acute myocardial infarction (AMI) patients. Anxiety symptoms are common in patients with coronary artery disease (CAD), and are associated with a poor prognosis. However, the association between anxiety and MINOCA outcomes is less clear. Hypothesis Anxiety will be associated with clinical outcomes in patients with MINOCA. Methods and Results Between November 2014 and December 2016, 620 hospitalized patients with MINOCA were recruited from a single center. Within 7 days of coronary angiography, anxiety was assessed using the Zung Self‐Rating Anxiety Scale. The primary endpoint was all‐cause mortality; secondary endpoint was any major adverse cardiovascular event (MACE). After 3 years, 87 deaths and 151 MACE had occurred. Kaplan‐Meier curves indicated the unadjusted rates of all‐cause mortality (log‐rank P = .045) and MACE (log‐rank P = .023) were significantly higher in the anxiety group compared with the control group of patients without anxiety. Multivariate Cox regression analysis showed that clinically significant anxiety was an independent prognostic factor for all‐cause mortality as well as MACE (hazard ratio [HR] = 1.547; 95% confidence interval [CI], 1.006‐2.380; P = .047; HR = 1.460; 95% CI, 1.049‐2.031; P = .025; respectively). Conclusions Anxiety is significantly and independently associated with an increased risk of all‐cause mortality and MACE in patients with MINOCA.

Background Anastomosis is one of the important factors affecting anastomotic complications after esophagectomy, and multiple reports have compared anastomotic complications among various techniques. However, there is insufficient evidence in the literature to definitively recommend one anastomotic technique over another. Method We retrospectively evaluated 34 consecutive patients who underwent an improved totally mechanical side-to-side: posterior-to-posterior linear stapled (TM-STS) technique for minimally invasive Ivor Lewis esophagogastric anastomosis, performed by a single surgeon between February 2015 to November 2017. The operative techniques and short-term outcomes are analyzed in this study. Results There were no conversions to an open approach and a complete resection was achieved in all patients undergoing this improved procedure. During the first half of the series, the median operation time was 355 minutes, ranging from 257 to 480 minutes. Over the second half of this series, the median operation time was reduced to 256 minutes. There were no mortalities or serious postoperative complications. Only one patient (2.9%) had an anastomotic leak, which resolved without intervention. Another patient (2.9%) experienced transient, delayed conduit emptying which upper gastrointestinal radiography determined was due to a mechanical obstruction caused by an abnormally long gastric tube in the chest cavity. Conclusions The results of our study suggest that this improved TM-STS technique is safe and effective for minimally invasive Ivor Lewis esophagectomy, and can be considered as one of the alternative procedure for patients with lower esophageal as well as Siewert types I/II gastroesophageal junction carcinoma.

Medicinal phytochemicals, such as artemisinin and taxol, have impacted the world, and hypericin might do so if its availability issue could be addressed. Hypericin is the hallmark component of Saint John's wort (Hypericum perforatum L.), an approved depression alleviator documented in the US, European, and British pharmacopoeias with its additional effectiveness against diverse cancers and viruses. However, the academia-to-industry transition of hypericin remain hampered by its low in planta abundance, unfeasible bulk chemical synthesis, and unclear biosynthetic mechanism. Here, we present a strategy consisting of the hypericin-structure-centered modification and reorganization of microbial biosynthetic steps in the repurposed cells that have been tamed to enable the designed consecutive reactions to afford hypericin (43.1 mg L