Time points of outcome are often neglected in acupuncture meta-analyses: a methodological survey.

OBJECTIVES: To systematically understand the transparency of outcome measurement time point reporting in meta-analyses of acupuncture. STUDY DESIGN AND SETTING: We searched for meta-analyses of acupuncture published between 2013 and 2022 in PubMed, Embase, and Cochrane Library. A team of method-trained investigators screened studies for eligibility and collected data using pilot-tested standardized questionnaires. We documented in detail the reporting of outcome measurement time points in acupuncture meta-analyses. RESULTS: A total of 224 acupuncture meta-analyses were included. Of these, 98 (43.8%) studies did not specify the time points of primary outcome. Among 126 (56.3%) meta-analyses which reported the time points of primary outcome, only 22 (17.5%) meta-analyses specified time points in corresponding protocol. Among 48 (38.1%) meta-analyses that estimated treatment effects of multiple time points, 11 (22.9%) meta-analyses used inappropriate meta-analysis method (subgroup analysis) to pool effect size, and none of the meta-analyses used advanced methods for pooling effect sizes at different time points. CONCLUSION: Transparency in reporting outcome time points for acupuncture meta-analyses and appropriate methods to pool the effect size of multiple time points were lacking. For future systematic reviews, the transparency of outcome measurement time points should be emphasized in the protocols and final reports. Furthermore, advanced methods should be considered for pooling effect sizes at multiple time points.

Association of perceived social support and emotional regulation among college students / 中国学校卫生

Objective@#To understand the current situation of college students emotional regulation and its correlation with perceived social support, so as to provide a reference for improving emotional regulation ability among college students.@*Methods@#From September 15 to October 15, 2022, a total of 15 560 students from 27 colleges and universities in Guangdong, Jiangsu, Shandong, Shanghai, Anhui, Hebei, Yunnan, Shanxi and Gansu were enrolled by stratified random sampling method. The Perceived Social Support Scale (PSSS) and the Emotion Regulation Questionnaire (ERQ) were used to investigate, and multiple stepwise regression was used to explore the relationship between perceived social support and emotion regulation of college students.@*Results@#The scores of emotion regulation, cognitive reappraisal and expression inhibition were 44(40, 50), 24(20, 28) and 20(19, 24) respectively. There were significant differences in the scores of emotion regulation, cognitive reappraisal and expression inhibition by age, grade, household registration, only child status,cost of living, and sleep ( H/Z =77.72, 49.73, -5.10, -9.77, 7.68, 168.27 ; 204.55, 317.32, -5.96, -7.60, 131.20, 968.08; 82.18, 148.04, -2.30, -8.03, 64.82, 188.08, P <0.05). In addition, the multiple stepwise regression found that family support, friend support, and other support in perceived social support all had a positive impact on the emotional regulation state of college students ( β =0.137,0.207,0.090), and family support and friend support had a significant positive effect on expression inhibition( β =0.079,0.053) and cognitive reappraisal( β =0.153,0.296)( P <0.01).@*Conclusion@#The perceived social support can directly affect the emotional regulation of college students, and improving the emotional regulation ability has a positive significance to promote the mental health level among college students.

LncRNA H19 Influences Cellular Activities via the miR-454-3p/BHLHE40 Axis in Anaplastic Thyroid Carcinoma.

Anaplastic thyroid carcinoma (ATC) is an aggressive malignancy threatening patients' life quality. Our previous study has demonstrated that inhibition of long non-coding RNA H19 (lncRNA h19; H19) blocks ATC growth and metastasis. The current study aimed to further explore the potential mechanism of H19 in ATC. Expression of H19, miR-454-3p, and BHLHE40 mRNA was measured using RT-qPCR in tissue samples and cell lines. The dual-luciferase reporter assay and Pearson correlation analysis were used to explore the interaction among H19, miR-454-3p, and BHLHE40. The biological process of proliferation, migration, and invasion was determined using loss- or gain-function CCK-8 and Transwell assays. Western blot assay was used to evaluate the changes in protein levels. H19 was elevated in ATC tissues and cell lines. Based on online prediction database results, miR-454-3p might be a target of H19, and BHLHE40 might be a direct target of miR-454-3p. miR-454-3p expression was decreased in ATC and had a negative interaction with H19. BHLHE40 mRNA expression was increased and has a negative correlation with miR-454-3p and a positive correlation with H19. Downregulation of miR-454-3p and upregulation of BHLHE40 could reverse the decreased cellular activities caused by si-H19. Moreover, the silence of H19 modulates BHLHE40 to affect the PI3K/AKT protein levels and apoptotic-related protein levels. The current study provided a potential detailed mechanism of H19 in ATC, and lncRNA H19-miR-454-3p-BHLHE40 interaction may be a new experimental basis for prognosis and targeted therapy for ATC patients.

Forecast of pain degree of lumbar disc herniation based on back propagation neural network.

To further explore the pathogenic mechanism of lumbar disc herniation (LDH) pain, this study screens important imaging features that are significantly correlated with the pain score of LDH. The features with significant correlation imaging were included into a back propagation (BP) neural network model for training, including Pfirrmann classification, Michigan State University (MSU) regional localization (MSU protrusion size classification and MSU protrusion location classification), sagittal diameter index, sagittal diameter/transverse diameter index, transverse diameter index, and AN angle (angle between nerve root and protrusion). The BP neural network training model results showed that the specificity was 95 ± 2%, sensitivity was 91 ± 2%, and accuracy was 91 ± 2% of the model. The results show that the degree of intraspinal occupation of the intervertebral disc herniation and the degree of intervertebral disc degeneration are related to LDH pain. The innovation of this study is that the BP neural network model constructed in this study shows good performance in the accuracy experiment and receiver operating characteristic experiment, which completes the prediction task of lumbar Magnetic Resonance Imaging features for the pain degree of LDH for the first time, and provides a basis for subsequent clinical diagnosis.

ResNet for recognition of Qi-deficiency constitution and balanced constitution based on voice.

Background: According to traditional Chinese medicine theory, a Qi-deficiency constitution is characterized by a lower voice frequency, shortness of breath, reluctance to speak, an introverted personality, emotional instability, and timidity. People with Qi-deficiency constitution are prone to repeated colds and have a higher probability of chronic diseases and depression. However, a person with a Balanced constitution is relatively healthy in all physical and psychological aspects. At present, the determination of whether one has a Qi-deficiency constitution or a Balanced constitution are mostly based on a scale, which is easily affected by subjective factors. As an objective method of diagnosis, the human voice is worthy of research. Therefore, the purpose of this study is to improve the objectivity of determining Qi-deficiency constitution and Balanced constitution through one's voice and to explore the feasibility of deep learning in TCM constitution recognition. Methods: The voices of 48 subjects were collected, and the constitution classification results were obtained from the classification and determination of TCM constitutions. Then, the constitution was classified according to the ResNet residual neural network model. Results: A total of 720 voice data points were collected from 48 subjects. The classification accuracy rate of the Qi-deficiency constitution and Balanced constitution was 81.5% according to ResNet. The loss values of the model training and test sets gradually decreased to 0, while the ACC values of the training and test sets tended to increase, and the ACC values of the training set approached 1. The ROC curve shows an AUC value of 0.85. Conclusion: The Qi-deficiency constitution and Balanced constitution determination method based on the ResNet residual neural network model proposed in this study can improve the efficiency of constitution recognition and provide decision support for clinical practice.

Automatic tongue image quality assessment using a multi-task deep learning model.

The quality of tongue images has a significant influence on the performance of tongue diagnosis in Chinese medicine. During the acquisition process, the quality of the tongue image is easily affected by factors such as the illumination, camera parameters, and tongue extension of the subject. To ensure that the quality of the collected images meet the diagnostic criteria of traditional Chinese Medicine practitioners, we propose a deep learning model to evaluate the quality of tongue images. First, we acquired the tongue images of the patients under different lighting conditions, exposures, and tongue extension conditions using the inspection instrument, and experienced Chinese physicians manually screened them into high-quality and unqualified tongue datasets. We then designed a multi-task deep learning network to classify and evaluate the quality of tongue images by adding tongue segmentation as an auxiliary task, as the two tasks are related and can promote each other. Finally, we adaptively designed different task weight coefficients of a multi-task network to obtain better tongue image quality assessment (IQA) performance, as the two tasks have relatively different contributions in the loss weighting scheme. Experimental results show that the proposed method is superior to the traditional deep learning tongue IQA method, and as an additional task of the network, it can output the tongue segmentation area, which provides convenience for follow-up clinical tongue diagnosis. In addition, we used network visualization to verify the effectiveness of the proposed method qualitatively.

Biological effective dose in analysis of rectal dose in prostate cancer patients who underwent a combination therapy of VMAT and LDR with hydrogel spacer insertion.

This study aimed to evaluate rectal dose reduction in prostate cancer patients who underwent a combination of volumetric modulated arc therapy (VMAT) and low-dose-rate (LDR) brachytherapy with insertion of hydrogel spacer (SpaceOAR). For this study, 35 patients receiving hydrogel spacer and 30 patients receiving no spacer were retrospectively enrolled. Patient was treated to doses of 45 Gy to the primary tumor site and nodal regions over 25 fractions using VMAT and 100 Gy to the prostate using prostate seed implant (PSI). In VMAT plans of patients with no spacer, mean doses of rectal wall were 43.6, 42.4, 40.1, and 28.8 Gy to the volume of 0.5, 1, 2, and 5 cm3 , respectively. In patients with SpaceOAR, average rectal wall doses decreased to 39.0, 36.9, 33.5, and 23.9 Gy to the volume of 0.5, 1, 2, and 5 cm3 , respectively (p < 0.01). In PSI plans, rectal wall doses were on average 78.5, 60.9, 41.8, and 14.8 Gy to the volume of 0.5, 1, 2, and 5 cm3 , respectively, in patients without spacer. In contrast, the doses decreased to 34.5, 28.4, 20.6 (p < 0.01), and 8.5 Gy (p < 0.05) to rectal wall volume of 0.5, 1, 2, and 5 cm3 , respectively, in patient with SpaceOAR. To demonstrate rectal sum dose sparing, dose-biological effective dose (BED) calculation was accomplished in those patients who showed >60% overlap of rectal volumetric doses between VMAT and PSI. In patients with SpaceOAR, average BEDsum was decreased up to 34%, which was 90.1, 78.9, 65.9, and 40.8 Gy to rectal volume of 0.5, 1, 2, and 5 cm3 , respectively, in comparison to 137.4, 116.7, 93.0, and 50.2 Gy to the volume of 0.5, 1, 2, and 5 cm3 , respectively, in those with no spacer. Our result suggested a significant reduction of rectal doses in those patients who underwent a combination of VMAT and LDR with hydrogel spacer placement.

Retracted: The MEK1/2 Inhibitor AZD6244 Sensitizes BRAF-Mutant Thyroid Cancer to Vemurafenib.

This publication has been retracted by the Editor due to the identification of falsified figure images and manuscript content that raise concerns regarding the credibility of the study and the manuscript. Reference: Vemurafenib Hao Song, Jinna Zhang, Liang Ning, Honglai Zhang, Dong Chen, Xuelong Jiao, Kejun Zhang. The MEK1/2 Inhibitor AZD6244 Sensitizes BRAF-Mutant Thyroid Cancer to Vemurafenib. Med Sci Monit, 2018; 24: 3002-3010. DOI: 10.12659/MSM.910084.

Applied Research on the Combination of Weighted Network and Supervised Learning in Acupoints Compatibility.

To enhance the depth of excavation and promote the intelligence of acupoint compatibility, a method of constructing weighted network, which combines the attributes of acupoints and supervised learning, is proposed for link prediction. Medical cases of cervical spondylosis with acupuncture treatment are standardized, and a weighted network is constructed according to acupoint attributes. Multiple similarity features are extracted from the network and input into a supervised learning model for prediction. And, the performance of the algorithm is evaluated through evaluation indicators. The experiment finally screened 67 eligible medical cases, and the network model involved 141 acupoint nodes with 1048 edge. Except for the Preferential Attachment similarity index and the Decision Tree model, all other similarity indexes performed well in the model, among which the combination of PI index and Multilayer Perception model had the best prediction effect with an AUC value of 0.9351, confirming the feasibility of weighted networks combined with supervised learning for link prediction, also as a strong support for clinical point selection.

Which of the acupuncture treatment regimen for lumbar disc herniation is more effective and safer: A protocol for systematic review and network meta-analysis.

INTRODUCTION: Lumbar disc herniation (LDH) is the most common cause of low back pain and severely affects people's quality of life and ability to work. Although many clinical trials and medical reports conducted over the years have shown that acupuncture treatments are effective for LDH, the comparative effectiveness of these different acupuncture therapies is still unclear. This protocol of a network meta-analysis was designed to compare the effects and safety of acupuncture treatment regimens on LDH using both direct and indirect evidence. METHODS AND ANALYSIS: This protocol is reported according to the 2015 PRISMA-P and PRISMA guidelines for acupuncture. Eight databases and two platforms will be searched for articles published from their establishment to 1 December 2020 with medical subject heading terms and keywords. Three reviewers will verify the eligible randomized controlled trials independently. NoteExpress (3.2.0) software will be utilized to manage the literature. The overall quality of evidence will be evaluated by Confidence In Network Meta-Analysis (CINeMA). Additionally, we will conduct a meta-analysis of the effectiveness, recurrence rate, and symptom score of acupuncture in treating LDH using Review Manager (RevManV.5.4.1) and R4.0.2 software (The R Foundation for Statistical Computing). RESULTS: The results of the study will be published in journals or relevant conferences. CONCLUSION: This proposed systematic review will evaluate the comparative efficacy and safety of various acupuncture methods and combination protocols for LDH.

Phase I trial of dose-escalated stereotactic radiosurgery (SRS) boost for unfavorable locally advanced oropharyngeal cancer.

BACKGROUND AND PURPOSE: Patients with locally advanced oropharynx squamous cell carcinoma have suboptimal outcomes with standard chemoradiation. Here, we evaluated toxicity and oncologic outcomes of dose escalation using radiosurgical boost for patients with unfavorable oropharynx squamous cell carcinoma. MATERIALS AND METHODS: Between 2010-2017, Thirty four patients with intermediate- or high-risk oropharynx squamous cell carcinoma were enrolled onto this prospective phase I trial. Each patient received concurrent cisplatin and fractionated radiotherapy totaling 60 Gy or 66 Gy followed by radiosurgery boost to areas of residual gross tumor: single fraction of 8 Gy or 10 Gy, or two fractions of 5 Gy each. Primary endpoint was treatment toxicity. Secondary endpoints were local, regional, and distant disease control. RESULTS: Eleven, sixteen and seven patients received radiosurgery boost with 8 Gy in 1 fraction, 10 Gy in 1 fraction, and 10 Gy in 2 fractions respectively. Acute toxicities include 4 patients with tumor necrosis causing grade 3 dysphagia, of which 3 developed grade 4 pharyngeal hemorrhage requiring surgical intervention. At 24 months after treatment, 7%, 9%, and 15% had grade 2 dysgeusia, xerostomia, and dysphagia, respectively, and two patients remained feeding tube dependent. No grade 5 toxicities occurred secondary to treatment. Local, regional, and distant control at a median follow up of 4.2 years were 85.3%, 85.3% and 88.2%, respectively. Five patients died resulting in overall survival of 85.3%. CONCLUSIONS: This study is the first to report the use of radiosurgery boost dose escalation in patients with unfavorable oropharynx squamous cell carcinoma. Longer follow-up, larger cohorts, and further refinement of boost methodology are needed prior to implementation in routine clinical practice. TRIAL REGISTRATION: Northwell Health Protocol #09-309A (NCT02703493) ( https://clinicaltrials.gov/ct2/show/NCT02703493 ).

Eukaryotic translation initiation factor 5A in the pathogenesis of cancers.

Cancer is the leading cause of death worldwide. The absence of obvious symptoms and insufficiently sensitive biomarkers in early stages of carcinoma limits early diagnosis. Cancer therapy agents and targeted therapy have been used extensively against tissues or organs of specific cancers. However, the intrinsic and/or acquired resistance to the agents or targeted drugs as well as the serious toxic side effects of the drugs would limit their use. Therefore, identifying biomarkers involved in tumorigenesis and progression represents a challenge for cancer diagnosis and therapeutic strategy development. The eukaryotic translation factor 5A (eIF5A), originally identified as an initiation factor, was later shown to promote translation elongation of iterated proline sequences. There are two eIF5A isoforms (eIF5A1 and eIF5A2). eIF5A2 protein consists of 153 residues, and shares 84% amino acid identity with eIF5A1. However, the biological functions of these two isoforms may be significantly different. Recently, it was demonstrated that eIF5Ais widely involved in the pathogenesis of a number of diseases, including cancers. In particular, eIF5A plays an important role in regulating tumor growth, invasion, metastasis and tumor microenvironment. It was also shown to serve as a potential biomarker and target for the diagnosis and treatment of cancers. The present review briefly discusses the latest findings of eIF5A in the pathogenesis of certain malignant cancers and evolving clinical applications.

[Acupoint selection rules of acupuncture for cervical spondylotic radiculopathy based on data mining].

OBJECTIVE: To analyze the rules of acupoint selection in the acupuncture treatment of cervical spondylotic radiculopathy by data mining. METHODS: The randomized controlled trials (RCTs) regarding acupuncture for cervical spondylotic radiculopathy published from July 15 of 2009 to July 15 of 2019 were retrieved from databases of CNKI, VIP, Wanfang, SinoMed, PubMed and EMbase. A database was established with Microsoft Excel 2016. The frequency and total effective rate of high-frequency acupoints, meridians and acupoint combinations were analyzed, and the association rules of acupoints and meridians were analyzed by Apriori algorithm. RESULTS: A total of 87 RCTs were included, involving 104 acupoints with a total frequency of 921. Among them, the high-frequency acupoints were cervical Jiaji (EX-B 2, 87 times), Fengchi (GB 20, 70 times), Houxi (SI 3, 54 times), etc. The frequently-used acupoints were mainly distributed in the hand yangming large intestine meridian, the foot shaoyang gallbladder meridian and hand taiyang small intestine meridian. The frequently-used acupoint combination was Fengchi (GB 20)-cervical Jiaji (EX-B 2), and most of the combinations were acupoints at the proximal end and acupoints at the far and near end. With the analysis of association rules, 15 groups of acupoint association rules and meridian association rules were obtained. CONCLUSION: It is feasible to explore the acupoint selection and compatibility rules of acupuncture for cervical spondylotic radiculopathy by data mining. This study could provide corresponding reference for clinical treatment.

A Model-Based Method for Assessment of Salivary Gland and Planning Target Volume Dosimetry in Volumetric-Modulated Arc Therapy Planning on Head-and-Neck Cancer.

This study examined the relationship of achievable mean dose and percent volumetric overlap of salivary gland with the planning target volume (PTV) in volumetric-modulated arc therapy (VMAT) plan in radiotherapy for a patient with head-and-neck cancer. The aim was to develop a model to predict the viability of planning objectives for both PTV coverage and organs-at-risk (OAR) sparing based on overlap volumes between PTVs and OARs, before the planning process. Forty patients with head-and-neck cancer were selected for this retrospective plan analysis. The patients were treated using 6 MV photons with 2-arc VMAT plan in prescriptions with simultaneous integrated boost in dose of 70 Gy, 63 Gy, and 58.1 Gy to primary tumor sites, high-risk nodal regions, and low-risk nodal regions, respectively, over 35 fractions. A VMAT plan was generated using Varian Eclipse (V13.6), in optimization with biological-based generalized equivalent uniform dose (gEUD) objective for OARs and targets. Target dose coverage (D 95, D max, conformity index) and salivary gland dose (D mean and D max) were evaluated in those plans. With a range of volume overlaps between salivary glands and PTVs and dose constraints applied, results showed that dose D 95 for each PTV was adequate to satisfy D 95 >95% of the prescription. Mean dose to parotid <26 Gy could be achieved with <20% volumetric overlap with PTV58 (parotid-PTV58). On an average, the D mean was seen at 15.6 Gy, 21.1 Gy, and 24.2 Gy for the parotid-PTV58 volume at <5%, <10%, and <20%, respectively. For submandibular glands (SMGs), an average D mean of 27.6 Gy was achieved in patients having <10% overlap with PTV58, and 36.1 Gy when <20% overlap. Mean doses on parotid and SMG were linearly correlated with overlap volume (regression R 2 = 0.95 and 0.98, respectively), which were statistically significant (P < 0.0001). This linear relationship suggests that the assessment of the structural overlap might provide prospective for achievable planning objectives in the head-and-neck plan.

Targeted inhibition of long non-coding RNA H19 blocks anaplastic thyroid carcinoma growth and metastasis.

Long non-coding RNA H19 (H19) is highly expressed in cancers and is considered to highly correlate with the extent of malignant degree. The present study was performed to determine the expression levels of H19 in anaplastic thyroid carcinoma (ATC) tissues and the role of H19 in ATC 8505C cells in vitro and in vivo. Expression of H19 was detected in 19 ATC and 19 normal thyroid tissues by real-time quantitative polymerase chain reaction. Utilizing the siRNA or short hairpin RNA (shRNA) directed against human H19 (H19 siRNA or shRNA H19) depleted H19 in ATC 8505C cells and characterized the outcomes. The results showed that H19 was overexpressed in ATC tissues. Targeting H19 inhibited proliferation, migration, and invasion and induced apoptosis in 8505C cells in vitro and inhibited tumorigenesis and metastasis in vivo. Therefore, the H19 might be an effective target for ATC molecular therapy.

Improving the malignancy characterization of hepatocellular carcinoma using deeply supervised cross modal transfer learning for non-enhanced MR.

The malignancy characterization of hepatocellular carcinoma (HCC) is remarkably significant in clinical practice. In this work, we propose a deeply supervised cross modal transfer learning method to remarkably improve the malignancy characterization of HCC based on non-enhanced MR. First, we use samples of non-enhanced and contrast-enhanced MR for pre-training a deep learning network to learn the cross modal relationship between the non-enhanced modal and enhanced modal. Then, the parameters of the pre-trained across modal representation are transferred to a second deep learning model for fine-tuning based only on non-enhanced MR for malignancy characterization of HCC. Specifically, a deeply supervised network is designed to enhance the stability of the second deep learning model and further improve the performance of lesion characterization. Importantly, only non-enhanced MR of HCC is required for the malignancy characterization in the training and test phase of the second deep learning model. Experiments of one hundred and fifteen clinical HCCs demonstrate that the proposed deeply supervised cross modal transfer learning method can significantly improve the malignancy characterization of HCC based on non-enhanced MR.

Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.

BACKGROUND: Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospital information systems and disease surveillance systems, provides abundant data for CAMDM. However, the complexity of EMR data with abstract medical knowledge makes the conventional model incompetent for the analysis. Thus a deep belief networks (DBN) based model is proposed to simulate the information analysis and decision-making procedure in medical practice. The purpose of this paper is to evaluate a deep learning architecture as an effective solution for CAMDM. METHODS: A two-step model is applied in our study. At the first step, an optimized seven-layer deep belief network (DBN) is applied as an unsupervised learning algorithm to perform model training to acquire feature representation. Then a support vector machine model is adopted to DBN at the second step of the supervised learning. There are two data sets used in the experiments. One is a plain text data set indexed by medical experts. The other is a structured dataset on primary hypertension. The data are randomly divided to generate the training set for the unsupervised learning and the testing set for the supervised learning. The model performance is evaluated by the statistics of mean and variance, the average precision and coverage on the data sets. Two conventional shallow models (support vector machine / SVM and decision tree / DT) are applied as the comparisons to show the superiority of our proposed approach. RESULTS: The deep learning (DBN + SVM) model outperforms simple SVM and DT on two data sets in terms of all the evaluation measures, which confirms our motivation that the deep model is good at capturing the key features with less dependence when the index is built up by manpower. CONCLUSIONS: Our study shows the two-step deep learning model achieves high performance for medical information retrieval over the conventional shallow models. It is able to capture the features of both plain text and the highly-structured database of EMR data. The performance of the deep model is superior to the conventional shallow learning models such as SVM and DT. It is an appropriate knowledge-learning model for information retrieval of EMR system. Therefore, deep learning provides a good solution to improve the performance of CAMDM systems.

Synergistic inhibition of MEK/ERK and BRAF V600E with PD98059 and PLX4032 induces sodium/iodide symporter (NIS) expression and radioiodine uptake in BRAF mutated papillary thyroid cancer cells.

BACKGROUND AND AIMS: The activating mutation BRAFV600E is a frequent genetic event in papillary thyroid carcinomas (PTC). Mutation BRAFV600E is associated with the loss of a sodium/iodine symporter (NIS), and subsequent radioiodide-refractory (RAI) metastatic disease. Use of BRAF V600E inhibitors could partly restore NIS expression and Iodide uptake by inhibition of mitogen-activated protein kinase (MAPK) pathway. Previous study has reported that the BRAF V600E inhibitors could re-activate MAPK signals. In the present study, we investigated whether the combination treatment of BRAF V600E inhibitor and MAPK signal inhibitor could more effectively increase NIS expression and RAI uptake, and explore the mechanisms. METHODS: BCPAP and K1 cells were exposed to increasing concentrations of BRAF V600E inhibitor PLX4032 (0.01 µM, 0.1 µM, 1 µM) or MEK/ERK inhibitor PD98059 (0.01 µM, 0.1 µM, 1 µM) or with their association or/and in the presence of 3 mM perchlorate (ClO- 4) for 0-72 h. Iodide uptake and expression of BRAF, phosphorylated (p) ERK1/2, NIS were detected. RESULTS: PLX4032 or PD98059 alone did not induce NIS expression and increase Iodide uptake in BCPAP and K1 cells. But combined treatment of PLX4032 and PD98059 significantly induce NIS expression and increase Iodide uptake in BCPAP and K1 cells. PLX4032 alone inhibited p-ERK expression at early time, and re-activated p-ERK expression at late time. However, combined treatment of PLX4032 and PD98059 completely inhibited p-ERK expression. CONCLUSION: Simultaneously suppressing BRAF V600E and p-ERK restored NIS expression and increase Iodide uptake in PTC cells, which was associated the inhibition of p-ERK expression. The results warrants clinical trials to confirm.

Loss of AMPKα2 Impairs Hedgehog-Driven Medulloblastoma Tumorigenesis.

The AMP-activated protein kinase (AMPK) is a sensor of cellular energy status that has a dual role in cancer, i.e., pro- or anti-tumorigenic, depending on the context. In medulloblastoma, the most frequent malignant pediatric brain tumor, several in vitro studies previously showed that AMPK suppresses tumor cell growth. The role of AMPK in this disease context remains to be tested in vivo. Here, we investigate loss of AMPKα2 in a genetically engineered mouse model of sonic hedgehog (SHH)-medulloblastoma. In contrast to previous reports, our study reveals that AMPKα2 KO impairs SHH medulloblastoma tumorigenesis. Moreover, we performed complementary molecular and genomic analyses that support the hypothesis of a pro-tumorigenic SHH/AMPK/CNBP axis in medulloblastoma. In conclusion, our observations further underline the context-dependent role of AMPK in cancer, and caution is warranted for the previously proposed hypothesis that AMPK agonists may have therapeutic benefits in medulloblastoma patients. Note: an abstract describing the project was previously submitted to the American Society for Investigative Pathology PISA 2018 conference and appears in The American Journal of Pathology (Volume 188, Issue 10, October 2018, Page 2433).