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Due to acromegaly’s insidious onset and slow progression, its diagnosis is usually delayed, thus causing severe complications and treatment difficulty. A convenient screening method is imperative. Based on our previous work, we herein developed a new automatic diagnosis and severity-classification model for acromegaly using facial photographs by deep learning on the data of 2148 photographs at different severity levels. Each photograph was given a score reflecting its severity (range 1~3). Our developed model achieved a prediction accuracy of 90.7% on the internal test dataset and outperformed the performance of ten junior internal medicine physicians (89.0%). The prospect of applying this model to real clinical practices is promising due to its potential health economic benefits.

Additional file 1.. The materials, methods, results and limitations of this study in detail.

Additional file 2:. Table S1. Spearman correlation coefficient results and p-values measuring the rank correlation.

// Xiangyi Kong 1, 2, * , Shun Gong 3, 4, * , Lijuan Su 5, * , Xinqi Cheng 6 , Honglei Li 6 , Tingting You 6 and Yanguo Kong 1 1 Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China 2 Department of Breast Surgical Oncology, China National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyang District, Panjiayuan, Beijing 100021, P.R. China 3 Department of Neurosurgery, Shanghai Institute of Neurosurgery, PLA Institute of Neurosurgery, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai 200003, P.R. China 4 Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02215, United States of America 5 College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang 310027, P.R. China 6 Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China * These authors have contributed equally to this work Correspondence to: Yanguo Kong, email: kong0126@126.com Keywords: survivin; pituitary adenoma; invasiveness Received: February 21, 2017 Accepted: June 30, 2017 Published: November 10, 2017 ABSTRACT Background and objective: Survivin is an inhibitor of apoptosis. Its role in guiding the treatment of neoplasms, making diagnosis and predicting prognosis has been reported. However, there is little information on the implications and uses of survivin in predicting pituitary adenoma (PA) invasiveness. Existing information is unclear and controversial. We thus conducted this meta-analysis to explore whether the surviving expression levels in invasive PAs (IPA) and regular PAs are different or not. We considered both non-secreting and secreting tumors together. Methods: A global search strategy was systematically applied among five databases including Cochrane Library, Embase, PubMed, Web of Science, and Chinese National Knowledge Infrastructure (CNKI) up to June 18th, 2017. With a specially designed form including PAs’ invasive features, etc., data was collected. The included studies should present the data representing the surviving levels in IPA groups and regular PA groups, respectively. Differences were expressed as standard mean differences (SMDs) or odds ratios (ORs) with 95% confidence interval (CI). To estimate the heterogeneities, I 2 test, Cochran’s Q-test and Galbr figure were all conducted. A sensitivity-analysis and potential-publication bias were also performed. Results: In the present meta-analysis, 9 studies containing 489 patients were included. Seven studies with dichotomous-data showed that survivin over-expression in PA tissue was closely associated with a high invasive tendency (OR 6.226, 95% CI 3.970, 9.765; P

Triple‐negative breast cancer (TNBC) refers to the breast cancers that express little human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR) and oestrogen receptor (ER). When compared to other types of breast cancers, TNBC behaves more aggressively with relatively poorer prognosis. Moreover, except chemotherapy, no targeted treatments have been approved yet until now. Although the molecular‐biological mechanisms of the initiation and development of TNBC have been explored a lot, the exact details underlying its progressions are still not clear. Long non‐coding RNAs (lncRNAs), with the length greater than 200 nucleotides, are non‐protein coding transcripts. Previous researches have shown that lncRNAs are significantly involved in a variety of pathophysiological processes such as cell migration, invasion, proliferation, differentiation and development. lncRNAs’ dysregulated expressions have been observed in many types of tumours including TNBCs. This article will review the functional roles and dysregulations of lncRNAs in TNBCs. These lncRNAs are worthy of exploitation regarding their potential application values of TNBC's diagnosis and treatment.

The most common forms of oesophageal cancers are adenocarcinomas and squamous cell carcinoma (SCC). Although the incidence of SCC in the United States tends to be declining, the adenocarcinoma incidence caused by Barrett's oesophagus has been increasing. Oesophageal cancer is regarded as one of the most fatal malignancies with a short prognosis. Systemic manifestations of patients with PCNSL keep backward in spite of recent development of chemoradiotherapy. MicroRNAs are small non‐coding RNAs that can post‐transcriptionally down‐regulate the expression of genes by targeting mRNAs, causing their translational repression as well as degradation. MicroRNAs exert critical functions in many malignancy‐related biological processes, including cell apoptosis, metabolism, proliferation and differentiation. Many deregulated miRNAs have been identified in oesophageal adenocarcinomas, but their biological importance has not yet been fully elucidated. In this study, we review present evidence regarding the potential applications of oesophageal adenocarcinomas associated microRNAs for prognosis and diagnosis of this lethal disease.

Xiangyi Kong,1,2 Yanguo Kong1 1Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Dongcheng District, Beijing, People’s Republic of China; 2Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Harvard University, Boston, MA, USA Abstract: The aim of this study was to summarize the findings of previous studies focusing on whether the risks of certain neurotoxicities are correlated to the programmed death 1 (PD-1) inhibitor nivolumab versus other chemotherapy or immunotherapy drugs. Six eligible studies, including 3,023 patients, were considered in the meta-analysis. The risk ratios (RRs) of fatigue, headache, dysgeusia, vertigo, paresthesia, anxiety or malaise and peripheral neuropathy were 0.908 (95% confidence interval [95% CI]: 0.724, 1.138; P=0.402), 0.841 (95% CI: 0.606, 1.168; P=0.302), 0.423 (95% CI: 0.132, 1.357; P=0.148), 0.762 (95% CI: 0.475, 1.223; P=0.261), 0.411 (95% CI: 0.232, 0.730; P=0.002), 1.049 (95% CI: 0.094, 11.752; P=0.969) and 0.192 (95% CI: 0.039, 0.935; P=0.041), respectively. Our analysis supported that the PD-1 inhibitor nivolumab did not cause increased or decreased risks of fatigue, headache, dysgeusia, vertigo and anxiety or malaise and was associated with decreased risks of paresthesia and peripheral neuropathy as compared with controls. These outcomes indicated that although clinicians should be attentive of the side effects of nivolumab, in terms of nervous system side effects, nivolumab is generally safe. Keywords: PD-1 inhibitor, nivolumab, neurotoxicity, cancer

Background: OPRM1-A118G polymorphism (A > G, rs1799971) is associated with interindividual variability in both response to postoperative pain and opioid treatment. The aim of this meta-analysis is to identify the predictive strength in the current literature of OPRM1-A118G polymorphism to postoperative anesthetic reactions, including nausea, vomiting, pruritus and dizziness. Methods: PubMed, EMBASE, Cochrane Library, Web of Knowledge, Google Scholar and CNKI database were searched to find gene-association researches exploring the impacts of OPRM1-A118G polymorphism on postoperative side effects (time: up to July 2016). Odd ratios (ORs) with 95% confidence intervals (95% CIs) were estimated in allele model, homozygote model, heterozygote model, dominant model and recessive model. Sensitivity analysis and potential bias were also assessed. Results: 137 articles were retrieved from databases. 17 eligible studies, including 4690 patients were considered in the meta-analysis. The ORs with 95% CIs of postoperative nausea, vomiting, nausea and vomiting (PONV), pruritus and dizziness in the five genetic models mentioned above were determined. Postoperative vomiting was significantly associated with OPRM1-A118G polymorphism in homozygote (OR: 0.422; 95% CI: 0.254, 0.701; P = 0.001), dominant (OR: 0.765; 95% CI: 0.592, 0.987; P = 0.040) and recessive (OR: 0.439; 95% CI: 0.268, 0.717; P = 0.001) models. The 118G allele was associated with a reduced risk of vomiting. No other associations were detected. There was no evidence of publication bias. Conclusions: OPRM1-A118G polymorphism (A > G) is associated with a reduced risk of postoperative vomiting, but not nausea, pruritus and dizziness. The results should be interpreted with caution due to limited sample and possible heterogeneity between the included studies. Well-designed and large-scale studies are necessary to confirm our results.

Background Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability. Methods In this study, several popular machine learning algorithms were used to train a retrospective development dataset consisting of 527 acromegaly patients and 596 normal subjects. We firstly used OpenCV to detect the face bounding rectangle box, and then cropped and resized it to the same pixel dimensions. From the detected faces, locations of facial landmarks which were the potential clinical indicators were extracted. Frontalization was then adopted to synthesize frontal facing views to improve the performance. Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. The trained models were evaluated using a separate dataset, of which half were diagnosed as acromegaly by growth hormone suppression test. Results The best result of our proposed methods showed a PPV of 96%, a NPV of 95%, a sensitivity of 96% and a specificity of 96%. Conclusions Artificial intelligence can automatically early detect acromegaly with a high sensitivity and specificity., Highlights • An automatic and handy diagnosis system for acromegaly was developed. • Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. • The algorithm allows medical practitioners and patients to proactively track face changes and detect acromegaly earlier and automatically, thus to facilitate cures and increase the likelihood of preventing irreversible complications of excessive secretion of growth hormone. We developed an automatic and handy diagnosis system for acromegaly, which can allow medical practitioners and patients to proactively track face changes and detect acromegaly earlier and automatically, thus to facilitate cures and increase the likelihood of preventing irreversible complications of excessive secretion of growth hormone.

Checkpoint kinase inhibition has been studied as a way of enhancing the effectiveness of DNA-damaging agents. More recently, histone deacetylase inhibitors have shown efficacy in several cancers, including non-Hodgkin lymphoma. To evaluate the effectiveness of this combination for the treatment of lymphoma, we examined the combination of AR42, a histone deacetylase inhibitor, and checkpoint kinase 2 (CHEK2) inhibitor II in vitro and in vivo. The combination resulted in up to 10-fold increase in potency in five Burkitt lymphoma cell lines when compared with either drug alone. Both drugs inhibited tumor progression in xenograft models, but the combination was more effective than either agent alone, resulting in regression of established tumors. No toxicity was observed. These results suggest that the combination of histone deacetylase inhibition and checkpoint kinase inhibition represent an effective and nontoxic treatment option that should be further explored in preclinical and clinical studies.

Background Studies have sought associations of the opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with alcohol-dependence, but findings are inconsistent. We summarize the information as to associations of rs1799971 (A > G) and the alcohol-dependence. Methods Systematically, we reviewed related literatures using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Embase, PubMed, Web of Knowledge, and Chinese National Knowledge Infrastructure (CNKI) databases were searched using select medical subject heading (MeSH) terms to identify all researches focusing on the present topic up to September 2016. Odds ratios (ORs) along with the 95% confidence interval (95% CI) were estimated in allele model, homozygote model, heterozygote model, dominant model and recessive model. Ethnicity-specific subgroup-analysis, sensitivity analysis, heterogeneity description, and publication-bias assessment were also analyzed. Results There were 17 studies, including 9613 patients in the present meta-analysis. The ORs in the 5 genetic-models were 1.037 (95% CI: 0.890, 1.210; p = 0.64), 1.074 (95% CI: 0.831, 1.387; p = 0.586), 1.155 (95% CI: 0.935, 1.427; p = 0.181), 1.261 (95% CI: 1.008, 1.578; p = 0.042), 0.968 (95% CI: 0.758, 1.236; p = 0.793), respectively. An association is significant in the dominant model, but there is no statistical significance upon ethnicity-specific subgroup analysis. Conclusion The rs1799971 (A > G) is not strongly associated with alcohol-dependence. However, there are study heterogeneities and limited sample sizes.

// Xiangyi Kong 1, 2, * , Hao Deng 2, * , Theodore Alston 2 , Yanguo Kong 1 and Jingping Wang 2 1 Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Dongcheng District, Beijing 100730, P. R. China 2 Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Harvard University, Boston, Massachusetts 02114-3117, United States of America * These authors have contributed equally to this work Correspondence to: Jingping Wang, email: JWANG23@mgh.harvard.edu Yanguo Kong, email: ygkong@pumch.cams.cn Keywords: OPRM1-A118G, rs1799971, polymorphism, nicotine dependence, meta-analysis Received: April 12, 2017 Accepted: July 26, 2017 Published: September 15, 2017 ABSTRACT Background and Object: Whether opioid-receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) is associated with nicotine dependence is controversial. We analyzed the combined results from published studies of this possibility. Methods: Literature reviews were performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Web of Science, Chinese National Science Infrastructure (CNKI), PubMed, Embase and Google Scholar database searches using MeSH terms were conducted to find all relevant researches up to October 2016. Odds ratios (ORs) and their 95% confidence intervals (95% CIs) were calculated in allele, homozygote, heterozygote, dominant and recessive models. Ethnicity-specific subgroup meta-analysis, heterogeneity, sensitivity analysis and publication bias were considered. Results: Seven eligible studies with 3313 patients were included. The ORs in the five genetic models mentioned above were 1.000 (95% CI: 0.906, 1.104; p = 0.999), 1.032 (95% CI: 0.771, 1.381; p = 0.834), 0.963 (95% CI: 0.799, 1.162; p = 0.696), 1.006 (95% CI: 0.916, 1.104; p = 0.907), 0.967 (95% CI: 0.715, 1.309; p = 0.830), respectively. Only in dominant model is the association significant. Upon ethnicity-specific subgroup analysis, there is no statistical significance. Conclusion: OPRM1-A118G polymorphism (A>G) is not associated with nicotine dependence.

Adenohypophysis spindle cell oncocytoma (ASCO) is a rare tumor recently reported by Roncaroli et al in 2002. This tumor is considered a grade I tumor by the World Health Organization. We report a rare case of malignant ASCO with repeating recurrences and a high Ki-67 index—a challenging diagnosis guided by clinical presentations, radiological signs, and postoperative pathological tests. We represent a 30-year-old man who had suffered from headaches, diplopia, and impaired visual field and acuity. His magnetic resonance imaging revealed an abnormal sellar mass and was originally misdiagnosed as a pituitary macroadenoma. We present detailed analysis of the patient's disease course and review relevant literature. When surgically treated, the specimen revealed a typical histopathology pattern of ASCO. The tumor recurred for several times and the patient underwent 3 surgeries and 1 γ-knife treatment, which was accompanied by a continuously increasing Ki-67 index. This is the first reported case of malignant ASCO (WHO III–IV grade). Despite its rarity, ASCO should be considered in the differential diagnosis of sellar lesions that mimic pituitary adenomas.

Object: We performed a meta-analysis of the risk of selected musculoskeletal toxicities associated with the PD-1 inhibitor Nivolumab versus other drugs. Methods: Several databases were searched. We assess the relevant articles and relative risks (RRs) with 95% confidence intervals (95% CIs) were estimated regarding the risk of arthralgia, asthenia, myalgia and extremity pain and Nivolumab versus control. Heterogeneity, sensitivity analysis and publication bias of the included studies were also analyzed. Results: There were 5 eligible studies, including 2220 patients that were considered in the present metaanalysis. The RRs of arthralgia, asthenia, myalgia and extremity pain were 1.116 (95% CI: 0.669, 1.860; p=0.675), 0.846 (95% CI: 0.657, 1.090; p=0.197), 0.658 (95% CI: 0.141, 3.062; p=0.593), 1.037 (95% CI: 0.647, 1.662; p=0.882), respectively. Conclusion: Our results suggested that PD-1 inhibitor Nivolumab was not associated with an increased risk of musculoskeletal toxicities including arthralgia, asthenia, and myalgia and extremity pain compared with control.

HB22.7, an anti-CD22 monoclonal antibody has shown consistent preclinical activity against non-Hodgkin lymphoma (NHL). Histone deacetylase inhibitors (HDACi) have demonstrated efficacy in lymphoma and can modulate cell surface receptor expression. To augment the lymphomacidal activity of HB22.7 we examined the combination of AR42 (an HDACi) and HB22.7 in vitro and in vivo. The combination resulted in 10-fold increased potency in 6 NHL cell lines when compared to either drug alone. Both drugs reduced tumor progression in xenografts, but the combination was significantly more efficacious and resulted in regression of established tumors, without toxicity. AR42 inhibited HB22.7-mediated CD22 internalization, suggesting that increased efficacy could be due to higher availability of CD22. Overall, the synergistic effects of HB22.7 and AR42 on in vitro cytotoxicity and in vivo anti-tumor activity make this combination an attractive option for further pre-clinical and clinical evaluation.

To investigate the correlation between preoperative serum epidermal growth factor receptor (EGF-R) level and proliferation of pituitary adenoma.ELISA was used to determine the levels of EGF-R in preoperative serum from 137 patients with pituitary diseases: 5 cases of pituitary Rathke's pouch, 13 cases of pituitary hyperplasia, and 119 cases of pituitary adenomas including 17 cases of microadenoma, 64 cases of macroadenoma, and 38 cases of giant adenoma. Twenty-eight healthy blood donors were used as controls.The level of serum EGF-R was (194 +/- 38) fmol/L in patients with pituitary hyperplasia, and was (219 +/- 37) fmol/L in patients with pituitary microadenoma, 322 +/- 66 fmol/L in patients with pituitary macroadenoma and (428 +/- 62) fmol/L in patients with pituitary giant adenoma. The levels of serum EGF-R in patients with different kinds of pituitary hyperplasia and pituitary adenoma were significantly higher than the level in patients with pituitary Rathke's pouch (152 +/- 17) fmol/L, all P0.0001, and were significantly higher than that in healthy control group (159 +/- 41) fmol/L, all P0.05. The serum level of EGF-R was positively correlated to the size of pituitary adenoma (r = 0.998). Furthermore, significant difference in the level of serum EGF-R was observed among patients with different kinds of pituitary adenoma (P0.0001).EGF-R level in preoperative serum of patients with pituitary adenoma reflexes the proliferative status of pituitary adenoma and helps differentiate pituitary adenoma from pituitary Rathke's pouch. It is suggested that serum EGF-R be used as a referable marker of proliferative status of pituitary adenoma.