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Patients with biliary tract cancer (BTC) were associated with poor prognosis and limited therapeutic options after first-line therapy currently. In this study, we sought to evaluate the feasibility and tolerability of sintilimab plus anlotinib as the second-line treatment for patients with advanced BTC. Eligible patients had histologically confirmed locally advanced unresectable or metastatic BTC and failed after the first-line treatment were recruited. The primary endpoint was overall survival (OS). Simultaneously, association between clinical outcomes and genomic profiling and gut microbiome were explored to identify the potential biomarkers for this regimen. Twenty patients were consecutively enrolled and received study therapy. The trail met its primary endpoint with a median OS of 12.3 months (95% CI: 10.1-14.5). Only four (20%) patients were observed of the grade 3 treatment-related adverse events (TRAEs) and no grade 4 or 5 TRAEs were detected. Mutation of AGO2 was correlated with a significantly longer OS. Abundance of Proteobacteria was associated with inferior clinical response. Therefore, sintilimab plus anlotinib demonstrated encouraging anti-tumor activity with a tolerable safety profile and deserved to be investigated in larger randomized trials for patients with advanced BTC subsequently.

Background Pancreatic cancer (PC) is a highly malignant tumor which threatens human’s health. Long non-coding RNAs (lncRNAs) are implicated in many cancers, including PC, but their mechanisms in PC have not yet been entirely clarified. We focused on revealing the potential function of lncRNA SOX21-AS1 in PC. Methods Functional assays assessed SOX21-AS1 function on PC progression. Bioinformatics analysis, along with mechanism assays were taken to unmask the regulatory mechanism SOX21-AS1 may exert in PC cells. Results SOX21-AS1 possessed a high expression level in PC cells. SOX21-AS1 absence suppressed PC cell proliferation, migration, stemness and epithelial-mesenchymal transition (EMT) while elevated cell apoptosis. SOX21-AS1 positively regulated its nearby gene SRY-box transcription factor 21 (SOX21) at post-transcriptional level. Through mechanism assays, we uncovered that SOX21-AS1 sponged SOX21-AS1 to elevate SOX21 mRNA and recruited ubiquitin-specific peptidase 10 (USP10) to deubiquitinate and stabilize SOX21 protein. Moreover, signal transducer and activator of transcription 6 (STAT6) could transcriptionally activate SOX21-AS1 and SOX21 expression. Conclusions SOX21-AS1 aggravated the malignant development of PC, which might provide the utility value for PC treatment.

Yufei Gu, Fengyu Zheng, Yingxuan Zhang, Shishi Qiao Department of Hepatobiliary Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan Province, People’s Republic of ChinaCorrespondence: Shishi Qiao, Department of Hepatobiliary Surgery, The First Affiliated Hospital of Zhengzhou University, No. 50 Jianshe East Road, Erqi District, Zhengzhou City, Henan Province, People’s Republic of China, Tel +86 18595811956, Email qiaoshishiv@163.comPurpose: We aimed to develop and to validate a novel nomogram based on inflammatory markers to preoperatively predict microvascular invasion (MVI) in patients with solitary primary hepatocellular carcinoma (HCC).Patients and Methods: Data from 658 patients with solitary primary HCC who underwent hepatectomy at the First Affiliated Hospital of Zhengzhou University from June 2018 to October 2021 were retrospectively analyzed. Patients were divided into training (n=441) and validation (n=217) cohorts according to surgical data. Independent risk factors for MVI were identified via univariate and multivariate logistic regression analyses in the training cohort. A novel nomogram was developed based on the independent risk factors identified. Its accuracy was evaluated using a calibration curve and concordance index (C-index). The predictive value was evaluated using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA).Results: Preoperative alpha-fetoprotein > 969 μg/L (P< 0.001), tumor size (P=0.002), neutrophil > 1.8× 109/L (P=0.002), gamma-glutamyl transpeptidase-to-platelet ratio (GPR) > 0.32 (P=0.001), aspartate aminotransferase-to-platelet ratio (APR) > 0.18 (P< 0.001), gamma-glutamyl transpeptidase-to-albumin ratio (GAR) > 2.30 (P=0.001), and gamma-glutamyl transpeptidase-to-lymphocyte ratio > 29.58 (P< 0.001) were identified as preoperative independent risk factors for MVI and were used to establish the nomogram. The C-index of the training and validation cohorts were 0.788 (95% confidence interval [CI]: 0.744– 0.831) and 0.735 (95% CI: 0.668– 0.802), respectively. The calibration curve analysis revealed that the standard curve fit well with the predicted curve. ROC curve analysis demonstrated high efficiency of the nomogram. DCA verified that the nomogram had notable clinical value.Conclusion: Preoperative GPR > 0.32, APR > 0.18, and GAR > 2.30 were independent risk factors for MVI in patients with solitary primary HCC, suggesting their utility as preoperative predictors of MVI. The novel nomogram developed and validated in this study may aid in determining optimal therapeutic approaches for patients with solitary HCC at risk for MVI.Keywords: hepatocellular carcinoma, microvascular invasion, preoperative prediction, nomogram

Situs inversus totalis (SIT) is a congenital disorder in which the thoracic and abdominal viscera organs are mirrored from their normal anatomical position. Thus, the presence of any cancerous mass in one of the visceral organs of patients with SIT represents a great challenge due to the anatomical variation. We report a 52-year-old male with SIT who presented with obstructive jaundice and pancreatic-head mass. After preoperative examinations, it was decided to perform a laparoscopic pancreaticoduodenectomy. In this case, we aim to demonstrate the diagnosis and management of pancreatic cancer in an SIT patient, in addition to presenting the advantages and difficulties of laparoscopic surgery in this case.

The aims of this study were to summarize the characteristics of insulinoma in central China and to present our experience with surgical management in the Department of Hepatobiliary and Pancreatic Surgery of The First Affiliated Hospital of Zhengzhou University. 617 patients were enrolled in this retrospective analysis, including 89 cases of insulinoma and 528 cases of other pancreatic tumors. All patients had been confirmed by histopathology reports and underwent surgical treatment. Medical data and operative notes were incorporated into the database. Among the 617 patients, 4 died during the perioperative period. In the insulinoma group, no deaths occurred. The average size of the insulinoma tumor was 1.4±0.8 cm. The ratio of open surgical procedure (57) to laparoscopic resection (32) was 1.8/1. The mean interoperation blood loss was significantly lower in the laparoscopic group (LA) (mean 35.2±17.4ml, range from 10 to 170ml) than that in the open surgical (OA) group (mean 64.7±38.6ml, range from 25 to 400ml). The mean postoperative hospital stay was also lower in the LA group (mean 8.1 ± 3.2days, range from 5 to 20 days) than that in the OA group (Mean 13.1±8.2days, range from 9 to 60 days). There was no significant difference for postoperative complications between the two groups (LA:37.5% vs OA:40.3% ). The rate of clinically significant postoperative-pancreatic-fistula (POPF) was 21.3 %, and there was only one case of C-degree-POPF. The average length of postoperative- gastrointestinal function recovery was 2.8 ± 0.9 days. And the average length of blood glucose fluctuation was 18±7.2 days. During the follow-up, 2 cases were found to be hypoglycemic again, and the rate of significant weight loss was 57.3% (51/89). Insulinoma was rare among patients who underwent surgical treatment at the Department. Their cases were benign, and their treatment was unproblematic. However, there was a small group of cases that could be associated with problematic clinical situations, and, therefore, treatment of patients with insulinoma should be conducted at specialist centers. Correct diagnostic and therapeutic management, involving close cooperation between multiple medical specialists, results in completely curing most patients.

Pancreatic cancer (PC) is a malignant tumour of the human digestive system that has a poor prognosis. Exosomes contain proteins and nucleic acids, and constitute a class of extracellular vesicles defined as membrane-bound nanovesicles of endocytic origin, with a diameter of 40-150 nm. Exosomes are potential diagnostic markers of PC; however, their roles in cancer initiation and progression remain unclear. Previous studies have focused on the molecular mechanisms and functions of exosomes that allow them to accelerate PC cell proliferation, migration and invasion. The present review discusses the interactions between exosomes and the pathophysiology of PC. The potential clinical applications of exosomes are also discussed.

Background: Hepatocellular carcinoma (HCC) is one of most common cancers with a high mortality rate. HBV/HCV infection is an important risk factor to trigger HCC. Therefore, developing serum biomarkers for early diagnosis is crucial to prolong survival in HCC patients. Methods: An antibody array technology was utilized to detect serum from 20 HBV-related HCC patients, 20 chronic hepatitis B patients and 20 normal population, whose results were further validated by ELISA. Results: Both antibody array and ELISA showed that ten growth factors (SCF R, GDF-15, HGF, FGF-4, IGFBP-1, PIGF, GH, GDNF, BDNF and IGF-1) were significantly differential in HCC patients when compared to the non-HCC population. Among these growth factors, the levels of SCF R, GDF-15, HGF, GH and IGF-1 showed significant correlation with hepatitis B and its severity, indicating that these growth factors may promote HCC progression by an HBV-specific mechanism. A therapy targeting these growth factors in hepatitis B patients may help to prevent the development of HCC. FGF4 and GH were found, for the first time, to be upregulated in HCC, suggesting that these two growth factors may serve as novel serum biomarkers for the early diagnosis of HCC. Conclusion: The combined detection of all the differential growth factors may improve the diagnostic accuracy of HCC.

Video face retrieval (VFR) is an appealing and practical computer vision task, which aims to search particular character from masses of videos like in TV-Series. The challenges of this task mainly lie in two aspects, i.e. faces in such videos contain complex appearance variations with uncontrollable shooting environment and searching from big data usually requires high efficiency in both space and time. To fulfill this task, current works typically proceed in a learning to hash manner by fusing single-frame features within a video to obtain the video representation and further embedding it into Hamming space to yield video binary codes. The feature fusion stage has inevitably discarded too much frame information and leads to less discriminative video codes. In this paper, we propose Hybrid Video and Image Hashing (HVIH) to learn more effective binary codes for face videos. Specifically, we fully exploit the dense frame features rather than simply discarding them after the video level fusion and jointly optimize binary codes for the video and its composed frames in adapted supervised manners. To achieve more robust video representation, we introduce a module of video center alignment to ensure the binary codes location of the video and its frames to be as compact and consistent as possible in the Hamming space, which naturally facilitates both tasks of video-to-video retrieval and image-to-video retrieval. Extensive experiments on two challenging video face databases demonstrate the superiority of our approach over the state-of-the-art.

Preserving the semantic similarity is one of the most important goals of hashing. Most existing deep hashing methods employ pairs or triplets of samples in training stage, which only consider the semantic similarity within a minibatch and depict the local positional relationship in Hamming space, leading to intermittent semantic similarity preservation. In this paper, we propose Deep Position-Aware Hashing (DPAH) to ensure continuous semantic similarity in Hamming space by modeling global positional relationship. Specifically, we introduce a set of learnable class centers as the global proxies to represent the global information and generate discriminative binary codes by constraining the distance between data points and class centers. In addition, in order to reduce the information loss caused by relaxing the binary codes to real-values in optimization, we propose kurtosis loss (KT loss) to handle the distribution of real-valued features before thresholding to be double-peak, and then enable the real-valued features to be more binarylike. Comprehensive experiments on three datasets show that our DPAH outperforms state-of-the-art methods.

In this paper, we address one specific video retrieval problem in terms of human face. Given one query in forms of either a frame or a sequence from a person, we search the database and return the most relevant face videos, i.e., ones have the same class label with the query. Such problem is very challenging due to the large intra-class variations and the high request on the efficiency of video representations in terms of both time and space. To handle such challenges, this paper proposes a novel Deep Video Code (DVC) method which encodes video faces into compact binary codes. Specifically, we devise an end-to-end convolutional neural network (CNN) framework that takes face videos as training inputs, models each of them as a unified representation by temporal feature pooling operation, and finally projects the high-dimensional representations of both frames and videos into Hamming space to generate binary codes. In such Hamming space, distance of dissimilar pairs is larger than that of similar pairs by a margin. To this end, a novel bounded triplet hashing loss is elaborately designed, which takes all dissimilar pairs into consideration for each anchor point in a mini-batch, and the optimization of the loss function is smoother and more stable. Extensive experiments on challenging video face databases and general image/video datasets with comparison to the state-of-the-arts verify the effectiveness of our method in different kinds of retrieval scenarios.

Retrieving videos of a particular person with face image as a query via hashing technique has many important applications. While face images are typically represented as vectors in Euclidean space, characterizing face videos with some robust set modeling techniques (e.g. covariance matrices as exploited in this study, which reside on Riemannian manifold), has recently shown appealing advantages. This hence results in a thorny heterogeneous spaces matching problem. Moreover, hashing with handcrafted features as done in many existing works is clearly inadequate to achieve desirable performance for this task. To address such problems, we present an end-to-end Deep Heterogeneous Hashing (DHH) method that integrates three stages including image feature learning, video modeling, and heterogeneous hashing in a single framework, to learn unified binary codes for both face images and videos. To tackle the key challenge of hashing on the manifold, a well-studied Riemannian kernel mapping is employed to project data (i.e. covariance matrices) into Euclidean space and thus enables to embed the two heterogeneous representations into a common Hamming space, where both intra-space discriminability and inter-space compatibility are considered. To perform network optimization, the gradient of the kernel mapping is innovatively derived via structured matrix backpropagation in a theoretically principled way. Experiments on three challenging datasets show that our method achieves quite competitive performance compared with existing hashing methods., Comment: 14 pages, 17 figures, 4 tables, accepted by IEEE Transactions on Image Processing (TIP) 2019

307 Background: Gemcitabine combined with cisplatin (GP) has been established as the standard first-line treatment in patients with unresectable biliary tract cancers (BTC), a heterogeneous group of rare and aggressive malignancies arising from the epithelium of the biliary duct system. Nevertheless, there has been no approved standard of care for second-line treatment. In this study, we explored the efficacy and safety of the combination of anlotinib and sintlimab as a novel second-line regimen in BTC. Methods: In this phase II trial, patients with advanced BCT, who experienced progression after first-line chemotherapy, received anlotinib (12 mg, PO, D1-14, Q3W) combined with sintlimab (200 mg, iv, D1, Q3W) until disease progression or unacceptable toxicity. The primary endpoint was OS, and the secondary endpoints included ORR, PFS, DCR, and safety. The exploratory endpoint was the correlation of clinical outcomes with biomarkers. Results: From Aug 2019 to Sep 2020, 17 patients were enrolled. 9(52.9%) were men, and the median age was 59(43-69) years. Nine patients were diagnosed with ICC, 2 with ECC, and 6 with GBC. 15 patients were assessable for response. At a median follow-up of 8.76 months (95%CI: 3.60-13.94 months), the primary endpoint OS has not been reached, the median PFS was 6.50 months (95%CI: 3.60-9.40 months). ORR was 40.00%, and DCR was 86.67%. The incidence of treatment-related adverse events (TRAEs) was 70.60%, and the most common grade 1-2 AEs were hypertension (70.60%), diarrhea (17.65%), and hypothyroidism (17.65%). Conclusions: Anlotinib plus sintlimab demonstrates significant clinical activity and acceptable toxicity in patients with advanced BTC who failed first-line chemotherapy. Clinical trial information: ChiCTR1900022003.

In this paper, we address the problem of face video retrieval. Given one face video of a person as query, we search the database and return the most relevant face videos, i.e., ones have same class label with the query. Such problem is of great challenge. For one thing, faces in videos have large intra-class variations. For another, it is a retrieval task which has high request on efficiency of space and time. To handle such challenges, this paper proposes a novel Deep Video Code (DVC) method which encodes face videos into compact binary codes. Specifically, we devise a multi-branch CNN architecture that takes face videos as training inputs, models each of them as a unified representation by temporal feature pooling operation, and finally projects the high-dimensional representations into Hamming space to generate a single binary code for each video as output, where distance of dissimilar pairs is larger than that of similar pairs by a margin. To this end, a smooth upper bound on triplet loss function which can avoid bad local optimal solution is elaborately designed to preserve relative similarity among face videos in the output space. Extensive experiments with comparison to the state-of-the-arts verify the effectiveness of our method.

Hepatocellular carcinoma (HCC) is one of the most frequent malignant tumors in the world. The only serological marker widely used for the diagnosis of HCC is alpha-fetoprotein (AFP). Despite that AFP is widely used for the diagnosis of HCC, it has a limit as a serological marker due to its low sensitivity and specificity. The human cervical cancer proto-oncogene 1 (HCCR-1) was previously reported as a new biomarker for HCC. To further evaluate the HCCR-1 as a biomarker for HCC, we conducted the prospective cohort study. We evaluated the significance of simultaneous measurement of 2 tumor markers in the diagnosis of HCC in China, Japan and Korea. Two markers for HCC, AFP and HCCR-1, were measured in the sera obtained from 1,338 patients at the time of initial diagnosis of HCC. Of the 1338 HCC patients, 616 (46%) and 686 (51.3%) were sero-positive for AFP and HCCR-1, respectively. The positive rate for HCC was increased up to 74.1% in combined use of AFP and HCCR-1. Many cases (54%) for AFP-negative HCC were positive for HCCR-1 and vice versa. More importantly, the diagnostic rate for small HCC (< 2 cm) was significantly improved in the combined analysis of AFP and HCCR-1 to 56.9% although it was only 40.1% and 23.4% in the single analysis of HCCR-1 and AFP, respectively. Our result suggests that the HCCR-1 could be an useful biomarker for HCC while the diagnostic rate could be significantly improved in the combined use of HCCR-1 and AFP.