DPCPX induces Bim-dependent apoptosis in nasopharyngeal carcinoma cells.

ADORA1 promotes tumor growth and development in multiple cancers. DPCPX (a selective adenosine A1 receptor antagonist), a specific ADORA1 antagonist, has shown antitumor effects in many cancer types. Nevertheless, the function of DPCPX in nasopharyngeal carcinoma (NPC) still remains to be unraveled. In this study, we investigated the functional role of DPCPX on NPC cells. We found that DPCPX promotes NPC cells growth inhibition. DPCPX induced Bim-dependent apoptosis in NPC cells irrespective of p53 status via the FoxO3a pathway following PI3K/AKT inhibition. Furthermore, DPCPX enhanced the antitumor effect of cisplatin, 5-FU and Paclitaxel in NPC. Xenograft experiment revealed that deficiency of Bim in vivo stalls apoptosis and antitumor activity of DPCPX. In conclusion, the PI3K/AKT/FoxO3a/Bim axis plays a critical role in the anticancer effects of DPCPX in NPC.

Technical note: Atlas-based Auto-segmentation of masticatory muscles for head and neck cancer radiotherapy.

PURPOSE: The study aimed to use quantitative geometric and dosimetric metrics to assess the accuracy of atlas-based auto-segmentation of masticatory muscles (MMs) compared to manual drawn contours for head and neck cancer (HNC) radiotherapy (RT). MATERIALS AND METHODS: Fifty-eight patients with HNC treated with RT were analyzed. Paired MMs (masseter, temporalis, and medial and lateral pterygoids) were manually delineated on planning computed tomography (CT) images for all patients. Twenty-nine patients were used to generate the MM atlas. Using this atlas, automatic segmentation of the MMs was performed for the remaining 29 patients without manual correction. Auto-segmentation accuracy for MMs was compared using dice similarity coefficients (DSCs), Hausdorff distance (HD), HD95, and variation in the center of mass (∆COM). The dosimetric impact on MMs was calculated (∆dose) using dosimetric parameters (D99%, D95%, D50%, and D1%), and compared with the geometric indices to test correlation. RESULTS: DSCmean ranges from 0.79 ± 0.04 to 0.85 ± 0.04, HDmean from 0.43 ± 0.08 to 0.82 ± 0.26 cm, HD95mean from 0.32 ± 0.08 to 0.42 ± 0.16 cm, and ∆COMmean from 0.18 ± 0.11 to 0.33 ± 0.23 cm. The mean MM volume difference was < 15%. The correlation coefficient (r) of geometric and dosimetric indices for the four MMs ranges between -0.456 and 0.300. CONCLUSIONS: Atlas-based auto-segmentation for masticatory muscles provides geometrically accurate contours compared to manual drawn contours. Dose obtained from those auto-segmented contours is comparable to that from manual drawn contours. Atlas-based auto-segmentation strategy for MM in HN radiotherapy is readily availalbe for clinical implementation.

Ethosomes as delivery system for transdermal administration of vinpocetine.

The purpose of the present study was to develop a novel transdermal vinpocetine patch containing a stable formulation and with good entrapment efficiency, and percutaneous absorption which via ethosome. Ethosome was found to be a more efficient delivery carrier with high encapsulation capacities (79.5% +/- 1.8%) and nanometric size (180.7 +/- 1.5 nm). In vitro percutaneous permeation experiments demonstrated that the permeation of vinpocetine through abdominal skin of Sprague Dawley was significantly increased when ethosome was used. The vinpocetine transdermal fluxes from ethosome gel (3.56 +/- 0.13 microg/cm2/h) were 6.72 and 3.10 times higher than that of vinpocetine gel solution and vinpocetine aueous solution, respectively. Furthermore, the AUC(0 --> infinity), and eliminiation half-life by the transdermal administration were significantly higher than those by the intragastric administration (P < 0.01). The study demonstrated that ethosome is a promising vesicular carrier for enhancing percutaneous absorption of vinpocetine.

Diverse Sample Generation: Pushing the Limit of Generative Data-Free Quantization.

Generative data-free quantization emerges as a practical compression approach that quantizes deep neural networks to low bit-width without accessing the real data. This approach generates data utilizing batch normalization (BN) statistics of the full-precision networks to quantize the networks. However, it always faces the serious challenges of accuracy degradation in practice. We first give a theoretical analysis that the diversity of synthetic samples is crucial for the data-free quantization, while in existing approaches, the synthetic data completely constrained by BN statistics experimentally exhibit severe homogenization at distribution and sample levels. This paper presents a generic Diverse Sample Generation (DSG) scheme for the generative data-free quantization, to mitigate detrimental homogenization. We first slack the statistics alignment for features in the BN layer to relax the distribution constraint. Then, we strengthen the loss impact of the specific BN layers for different samples and inhibit the correlation among samples in the generation process, to diversify samples from the statistical and spatial perspectives, respectively. Comprehensive experiments show that for large-scale image classification tasks, our DSG can consistently quantization performance on different neural architectures, especially under ultra-low bit-width. And data diversification caused by our DSG brings a general gain to various quantization-aware training and post-training quantization approaches, demonstrating its generality and effectiveness.

Molecular Evidence of Compound Kushen Injection Against Lung Cancer: A Network Pharmacology-Based Investigation from Western Medicine to Traditional Medicine.

BACKGROUND: Compound Kushen Injection (CKI) is used clinically for relieving cancer pain and treating various solid tumors, particularly lung cancer. However, the underlying mechanisms of CKI in lung cancer remain to be further elucidated. OBJECTIVE: This study aimed to obtain evidence regarding the potential efficacy of the active compounds and therapeutic targets of CKI at a molecular level by using Network Pharmacology (NP), which is an emerging technique for dealing with complex systems, such as those of herbal medicine. METHODS: The chemical and predicted target information of CKI was obtained from databases and computational prediction, respectively; lung-cancer drugs and their corresponding targets were retrieved from Drugbank and Drugcentral. The online tool, STRING, was used to gather target-pathway interactions for establishing a target-(pathway)-target network to identify the target group that was most relevant to cancer. Based on this module, a protein-protein interaction network was established for identifying the potential therapeutic targets and the potential active ingredients. RESULTS: CKI might affect lung cancer drug targets or their neighbor nodes to trigger anti-cancer effects. The compounds that were predicted to bind to the potential therapeutic targets were recommended as potential active ingredients of CKI, which included naringenin from Baituling, and kurarinone and isoxanthohumol from Kushen. CONCLUSION: This NP-based study might provide insights into understanding CKI from the perspective of modern science with reference to approved Western medicine for lung cancer. Moreover, network-based methods could also be further used with distinct advantages in dealing with complex information and systems of medicine.

The comparison of different drip cholangiography: a randomised trial.

BACKGROUND: This study investigated the advantages and disadvantages of contrast media administration by gravity drip and manual push injection during cholangiography. METHODS: A total of 100 patients who presented to the Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, for a cholangiography between June 2019 to June 2020 were enrolled in this study. Patients were randomly divided into 2 treatment groups. One group of patients with manual injection of contrast (the N group, n=50), received the contrast agent via the traditional manual injection method whereby the doctor injects 50 mL of prepared contrast agent into the right side of the patient while continuously observing the effects on the bile duct. The other group of patients with gravity drip administration of contrast media (the O group, n=50), received the contrast agent via gravity drip at a rate of 80 drops per minute, and both clinicians and radiologists monitored the entire cholangiography process from a safe distance. Patients were followed up and angiographic satisfaction was assessed after two weeks. RESULTS: All 100 patients completed cholangiography without allergic reaction to the contrast medium. In the traditional injection group (N group), nine patients experienced upper abdominal discomfort with nausea, abdominal pain, chills, high fever, and other symptoms, and residual gallstones were observed in 12 patients. In patients in the gravity drip group (O group), four patients felt upper abdominal discomfort accompanied by nausea, abdominal pain, chills, high fever, and other symptoms, with residual gallstones detected in six patients. CONCLUSIONS: Patients who underwent gravity drip cholangiography had significantly reduced adverse reactions compared to patients who underwent traditional manual infusion cholangiography. Furthermore, gravity drip cholangiography resulted in clearer images and reduced X-ray exposure for medical staff. Thus, increased implementation of gravity drip cholangiography in the clinical setting should be considered. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1800018202.

A Genotype Signature for Predicting Pathologic Complete Response in Locally Advanced Rectal Cancer.

PURPOSE: To construct and validate a predicting genotype signature for pathologic complete response (pCR) in locally advanced rectal cancer (PGS-LARC) after neoadjuvant chemoradiation. METHODS AND MATERIALS: Whole exome sequencing was performed in 15 LARC tissues. Mutation sites were selected according to the whole exome sequencing data and literature. Target sequencing was performed in a training cohort (n = 202) to build the PGS-LARC model using regression analysis, and internal (n = 76) and external validation cohorts (n = 69) were used for validating the results. Predictive performance of the PGS-LARC model was compared with clinical factors and between subgroups. The PGS-LARC model comprised 15 genes. RESULTS: The area under the curve (AUC) of the PGS model in the training, internal, and external validation cohorts was 0.776 (0.697-0.849), 0.760 (0.644-0.867), and 0.812 (0.690-0.915), respectively, and demonstrated higher AUC, accuracy, sensitivity, and specificity than cT stage, cN stage, carcinoembryonic antigen level, and CA19-9 level for pCR prediction. The predictive performance of the model was superior to clinical factors in all subgroups. For patients with clinical complete response (cCR), the positive prediction value was 94.7%. CONCLUSIONS: The PGS-LARC is a reliable predictive tool for pCR in patients with LARC and might be helpful to enable nonoperative management strategy in those patients who refuse surgery. It has the potential to guide treatment decisions for patients with different probability of tumor regression after neoadjuvant therapy, especially when combining cCR criteria and PGS-LARC.