Use of compressed sensing to expedite high-throughput diagnostic testing for COVID-19 and beyond.

The rapid spread of SARS-CoV-2 has placed a significant burden on public health systems to provide swift and accurate diagnostic testing highlighting the critical need for innovative testing approaches for future pandemics. In this study, we present a novel sample pooling procedure based on compressed sensing theory to accurately identify virally infected patients at high prevalence rates utilizing an innovative viral RNA extraction process to minimize sample dilution. At prevalence rates ranging from 0-14.3%, the number of tests required to identify the infection status of all patients was reduced by 69.26% as compared to conventional testing in primary human SARS-CoV-2 nasopharyngeal swabs and a coronavirus model system. Our method provided quantification of individual sample viral load within a pool as well as a binary positive-negative result. Additionally, our modified pooling and RNA extraction process minimized sample dilution which remained constant as pool sizes increased. Compressed sensing can be adapted to a wide variety of diagnostic testing applications to increase throughput for routine laboratory testing as well as a means to increase testing capacity to combat future pandemics.

Globally optimal OCT surface segmentation using a constrained IPM optimization.

Segmentation of multiple surfaces in optical coherence tomography (OCT) images is a challenging problem, further complicated by the frequent presence of weak boundaries, varying layer thicknesses, and mutual influence between adjacent surfaces. The traditional graph-based optimal surface segmentation method has proven its effectiveness with its ability to capture various surface priors in a uniform graph model. However, its efficacy heavily relies on handcrafted features that are used to define the surface cost for the "goodness" of a surface. Recently, deep learning (DL) is emerging as a powerful tool for medical image segmentation thanks to its superior feature learning capability. Unfortunately, due to the scarcity of training data in medical imaging, it is nontrivial for DL networks to implicitly learn the global structure of the target surfaces, including surface interactions. This study proposes to parameterize the surface cost functions in the graph model and leverage DL to learn those parameters. The multiple optimal surfaces are then simultaneously detected by minimizing the total surface cost while explicitly enforcing the mutual surface interaction constraints. The optimization problem is solved by the primal-dual interior-point method (IPM), which can be implemented by a layer of neural networks, enabling efficient end-to-end training of the whole network. Experiments on spectral-domain optical coherence tomography (SD-OCT) retinal layer segmentation demonstrated promising segmentation results with sub-pixel accuracy.

The emerging roles of non-coding competing endogenous RNA in hepatocellular carcinoma.

Accumulating evidence has emerged revealing that noncoding RNAs (ncRNAs) play essential roles in the occurrence and development of hepatocellular carcinoma (HCC). However, the complicated regulatory interactions among various ncRNAs in the development of HCC are not entirely understood. The newly discovered mechanism of competing endogenous RNAs (ceRNAs) uncovered regulatory interactions among different varieties of RNAs. In recent years, a growing number of studies have suggested that ncRNAs, including long ncRNAs, circular RNAs and pseudogenes, play major roles in the biological functions of the ceRNA network in HCC. These ncRNAs can share microRNA response elements to affect microRNA affinity with target RNAs, thus regulating gene expression at the transcriptional level and both physiological and pathological processes. The ncRNAs that function as ceRNAs are involved in diverse biological processes in HCC cells, such as tumor cell proliferation, epithelial-mesenchymal transition, invasion, metastasis and chemoresistance. Based on these findings, ncRNAs that act as ceRNAs may be promising candidates for clinical diagnosis and treatments. In this review, we discuss the mechanisms and research methods of ceRNA networks. We also reviewed the recent advances in studying the roles of ncRNAs as ceRNAs in HCC and highlight possible directions and possibilities of ceRNAs as diagnostic biomarkers or therapeutic targets. Finally, the limitations, gaps in knowledge and opportunities for future research are also discussed.

Proton pump inhibitors and odds of cholangiocarcinoma: A retrospective case-control study.

BACKGROUND & AIMS: Proton pump inhibitors (PPIs) have been reported to be associated with cholangitis and might possibly be carcinogenic. However, few studies have been conducted to investigate the association of PPIs with cholangiocarcinoma (CCA). Thus, a hospital-based case-control study was carried out in China to explore the association between PPIs and CCA. METHODS: In this study, 1468 CCA cases (826 intrahepatic cholangiocarcinoma (ICC) and 642 extrahepatic cholangiocarcinoma (ECC)) were included, which were observed at Beijing Friendship Hospital, from February 2002 to October 2018. We retrospectively extracted PPI use and other possible risk factors from clinical records, followed by an investigation of the relationship with CCA via calculation of odds ratios (ORs), adjusted odds ratios (AORs), and 95% confidence intervals (CIs) using logistic regression analysis. RESULTS: PPIs were used by 135 (9.2%) CCA cases and 173 (5.9%) controls. We found that PPI use was associated with a 1.61-fold elevated CCA odds (P < .001) (AOR = 1.61, 95% CI = 1.28-2.05; P < .001). After stratification by CCA subtypes, the AORs of PPIs were consistent for both CCA subtypes, with ORs of 1.36 (AOR = 1.36, 95% CI = 1.02-1.83; P = .003) and 1.95 (AOR = 1.95, 95% CI = 1.46-2.62; P < .001) for ICC and ECC respectively. Our results also showed that PPI use was slightly linked to the odds of CCA in a dose-dependent manner. CONCLUSION: PPI use was correlated with a significant 61% increased odds of CCA, particularly in the ECC. However, the retrospective design and observational nature cannot establish causation. Larger scale, multi-centre prospective studies are required for further validation.

A four-gene-based prognostic model predicts overall survival in patients with hepatocellular carcinoma.

With the development of new advances in hepatocellular carcinoma (HCC) management and noninvasive radiological techniques, high-risk patient groups such as those with hepatitis virus are closely monitored. HCC is increasingly diagnosed early, and treatment may be successful. In spite of this progress, most patients who undergo a hepatectomy will eventually relapse, and the outcomes of HCC patients remain unsatisfactory. In our study, we aimed to identify potential gene biomarkers based on RNA sequencing data to predict and improve HCC patient survival. The gene expression data and clinical information were acquired from The Cancer Genome Atlas (TCGA) database. A total of 339 differentially expressed genes (DEGs) were obtained between the HCC (n = 374) and normal tissues (n = 50). Four genes (CENPA, SPP1, MAGEB6 and HOXD9) were screened by univariate, Lasso and multivariate Cox regression analyses to develop the prognostic model. Further analysis revealed the independent prognostic capacity of the prognostic model in relation to other clinical characteristics. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model. Then, the prognostic model and the expression levels of the four genes were validated using the Gene Expression Omnibus (GEO) dataset. A nomogram comprising the prognostic model to predict the overall survival was established, and internal validation in the TCGA cohort was performed. The predictive model and the nomogram will enable patients with HCC to be more accurately managed in trials testing new drugs and in clinical practice.

All-Carbon Ultrafast Supercapacitor by Integrating Multidimensional Nanocarbons.

Ultrafast and high capacity all-carbon supercapacitors with 3D porous aerogel electrode are realized by combining carbon nanostructures of various dimensionalities, including 0D carbon onions, 1D carbon nanotubes, and 2D graphene oxide. The synergistic effects from the different forms of nanocarbons render this hybrid outstanding capacitance with excellent stability, even at ultrafast charge-discharge rates.

Quickest Sequential Multiband Spectrum Sensing with Mixed Observations.

Spectrum sensing is a key technology enabling the cognitive radio system. In this paper, the problem of how to quickly and accurately find an unoccupied channel from a large amount of potential channels is considered. The cognitive radio system under consideration is equipped with a narrow band sensor, hence it can only sense those potential channels in a sequential manner. In this scenario, we propose a novel two-stage mixed-observation sensing strategy. In the first stage, which is named as scanning stage, the sensor observes a linear combination of the signals from a pair of channels. The purpose of the scanning stage is to quickly identify a pair of channels such that at least one of them is highly likely to be unoccupied. In the second stage, which is called refinement stage, the sensor only observers the signal from one of those two channels identified from the first stage, and selects one of them as the unoccupied channel. The problem under this setup is an ordered two concatenated Markov stopping time problem. The optimal solution is solved using the tools from the multiple stopping time theory. It turns out that the optimal solution has a rather complex structure, hence a low complexity algorithm is proposed to facilitate the implementation. In the proposed low complexity algorithm, the cumulative sum test is adopted in the scanning stage and the sequential probability ratio test is adopted in the refinement stage. The performance of this low complexity algorithm is analyzed when the presence of unoccupied channels is rare. Numerical simulation results show that the proposed sensing strategy can significantly reduce the sensing time when the majority of potential channels are occupied.

Growing and Etching MoS2 on Carbon Nanotube Film for Enhanced Electrochemical Performance.

In this work we directly synthesized molybdenum disulfide (MoS2) nanosheets on carbon nanotube film (MoS2@CNT) via a two-step chemical vapor deposition method (CVD). By etching the obtained MoS2@CNT into 10% wt HNO3, the morphology of MoS2 decorated on CNT bundles was modulated, resulting in more catalytic active MoS2 edges being exposed for significantly enhanced electrochemical performance. Our results revealed that an 8 h acid etching sample exhibited the best performance for the oxygen evolution reaction, i.e., the current density reached 10 mA/cm² under 375 mV over-potential, and the tafel slope was as low as 94 mV/dec. The enhanced behavior was mainly originated from the more catalytic sites in MoS2 induced by the acid etching treatment and the higher conductivity from the supporting CNT films. Our study provides a new route to produce two-dimensional layers on CNT films with tunable morphology, and thus may open a window for exploring its promising applications in the fields of catalytic-, electronic-, and electrochemical-related fields.

Deep learning network with differentiable dynamic programming for retina OCT surface segmentation.

Multiple-surface segmentation in optical coherence tomography (OCT) images is a challenging problem, further complicated by the frequent presence of weak image boundaries. Recently, many deep learning-based methods have been developed for this task and yield remarkable performance. Unfortunately, due to the scarcity of training data in medical imaging, it is challenging for deep learning networks to learn the global structure of the target surfaces, including surface smoothness. To bridge this gap, this study proposes to seamlessly unify a U-Net for feature learning with a constrained differentiable dynamic programming module to achieve end-to-end learning for retina OCT surface segmentation to explicitly enforce surface smoothness. It effectively utilizes the feedback from the downstream model optimization module to guide feature learning, yielding better enforcement of global structures of the target surfaces. Experiments on Duke AMD (age-related macular degeneration) and JHU MS (multiple sclerosis) OCT data sets for retinal layer segmentation demonstrated that the proposed method was able to achieve subvoxel accuracy on both datasets, with the mean absolute surface distance (MASD) errors of 1.88 ± 1.96µm and 2.75 ± 0.94µm, respectively, over all the segmented surfaces.

The population percentile allowance method for determining systematic spatial error tolerances for temporary intensity modulated brachytherapy.

BACKGROUND: Multiple approaches are under development for delivering temporary intensity modulated brachytherapy (IMBT) using partially shielded applicators wherein the delivered dose distributions are sensitive to spatial uncertainties in both the applicator position and shield orientation, rather than only applicator position as with conventional high-dose-rate brachytherapy (HDR-BT). Sensitivity analyses to spatial uncertainties have been reported as components of publications on these emerging technologies, however, a generalized framework for the rigorous determination of the spatial uncertainty tolerances of dose-volume parameters is needed. PURPOSE: To derive and present the population percentile allowance (PPA) method, a generalized mathematical and statistical framework to evaluate the tolerance of temporary IMBT approaches to spatial uncertainties in applicator position and shield orientation. METHODS: A mathematical formalism describing geometric applicator position and shield orientation shifts was derived that supports straight and curved applicators and applies to serial and helical rotating shield brachytherapy (RSBT) and direction modulated brachytherapy (DMBT). The PPA method entails defining the percentage of a patient population receiving a given therapy that is, allowed to receive dose-volume errors in the target volume and specified organs at risk of a defined percentage or less, then determining what combinations of applicator position and shield orientation systematic errors would be expected to produce that outcome in the population. The PPA method was applied to the use case of multi-shield helical 169 Yb-based RSBT for cervical cancer, with 45° and 180° shield emission angles. A total of 37 cervical cancer patients were considered in the population, with average (± 1 standard deviation) HR-CTV volumes of 79 cm3  ± 37 cm3 and optimized baseline treatment plans (no spatial uncertainties applied) created for each patient to meet dose-volume requirements of 85 GyEQD2 (equivalent uniform dose in 2 Gy fraction), with D2cc tolerance doses of 90 GyEQD2 , 75 GyEQD2 , and 75 GyEQD2 for bladder, rectum, and sigmoid colon, respectively. RESULTS: For the PPA requirement that 90% of cervical cancer patients receiving multi-shield helical RSBT could have a maximum dose-volume uncertainty of 10% for high-risk clinical target volume (HR-CTV) D90 (minimum dose to hottest 90%) and bladder, rectum, and sigmoid colon D2cc (minimum dose to hottest 2 cm3 ), the tolerance systematic applicator position and shield orientation uncertainties were approximately ± 1.0 mm and ± 4.25°, respectively. For ± 1.5 mm and ± 5° systematic applicator position and shield orientation tolerances, 90% of the patients considered would have a maximum dose-volume uncertainty of 12.8% or less. CONCLUSION: The PPA method was formalized to determine the temporary IMBT spatial uncertainty tolerances that would be expected to result in an allowed percentage of a population of patients receiving relative dose-volume errors above a defined percentage. Multi-shield, helical 169 Yb-based RSBT for cervical cancer was evaluated and tolerances determined, which, if applied on each treatment fraction, would represent an extreme situation. The PPA method is applicable to a variety of temporary IMBT approaches and can be used to rigorously determine the design parameters for the delivery systems such as mechanical driver motor accuracy, shield angle backlash, applicator rotation, and applicator fixation stability.

Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma.

Background: Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC. Methods: We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic. Results: Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group. Conclusion: The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.

The Systemic Inflammation-Based Prognostic Score Predicts Postoperative Complications in Patients Undergoing Pancreaticoduodenectomy.

BACKGROUND: Although many studies have confirmed the correlation between inflammation-based or nutritional markers and postoperative complications in patients undergoing colorectal cancer surgery, their correlation after undergoing pancreaticoduodenectomy (PD) remains unclear. METHODS: We retrospectively reviewed the clinical data of patients who underwent PD in Beijing Friendship hospital between 2018 and 2020. Univariate analysis, multivariate analysis, and receiver operating characteristic curve (ROC) were performed. We assessed the preoperative modified Glasgow Prognostic Score (mGPS), C-reactive protein/albumin ratio (CAR), C-reactive protein (CRP), postoperative Glasgow Prognostic Score (poGPS), CRP on postoperative day 3 (POD3) and CAR on POD3. The optimal cut-off values were determined by performing logistic regression analysis. RESULTS: Of the 172 patients who underwent PD, 74 (43.0%) developed complications, of whom 27 (15.7%) had clinically relevant postoperative pancreatic fistulas (CR-POPF) and 36 (20.9%) had positive drainage fluid cultures. Elevated levels of preoperative mGPS (P<0.001), poGPS (P<0.001), CRP (P<0.001) and CAR on POD3 were associated with postoperative complications. CRP on POD3 (OR=1.028, 95% CI=1.017-1.039, P<0.001) was an independent risk factor associated with postoperative complications in both univariate and multivariate analyses. CAR on POD 3 showed the largest area under the curve (AUC=0.883, P<0.001). Compared with CAR<4.86, CAR ≥4.86 on POD3 was associated with a higher probability of complications (85.5% vs 14.6%, P<0.001), especially CR-POPF (33.3% vs 4.9%, P<0.001), intra-abdominal infection (36.2% vs 10.7%, P<0.001) with a positive drainage fluid culture. CONCLUSION: CAR, an inflammatory response-based marker, can effectively predict early postoperative complications in patients undergone PD.

Use of compressed sensing to expedite high-throughput diagnostic testing for COVID-19 and beyond.

The rapid spread of SARS-CoV-2 has placed a significant burden on public health systems to provide rapid and accurate diagnostic testing highlighting the critical need for innovative testing approaches for future pandemics. In this study, we present a novel sample pooling procedure based on compressed sensing theory to accurately identify virally infected patients at high prevalence rates utilizing an innovative viral RNA extraction process to minimize sample dilution. At prevalence rates ranging from 0-14.3%, the number of tests required to identify the infection status of all patients was reduced by 75.6% as compared to conventional testing in primary human SARS-CoV-2 nasopharyngeal swabs and a coronavirus model system. Additionally, our modified pooling and RNA extraction process minimized sample dilution which remained constant as pool sizes increased. Our use of compressed sensing can be adapted to a wide variety of diagnostic testing applications to increase throughput for routine laboratory testing as well as a means to increase testing throughput to combat future pandemics.

CeRNA regulatory network-based analysis to study the roles of noncoding RNAs in the pathogenesis of intrahepatic cholangiocellular carcinoma.

To explore and understand the competitive mechanism of ceRNAs in intrahepatic cholangiocarcinoma (ICC), we used bioinformatics analysis methods to construct an ICC-related ceRNA regulatory network (ceRNET), which contained 340 lncRNA-miRNA-mRNA regulatory relationships based on the RNA expression datasets in the NCBI GEO database. We identified the core regulatory pathway RP11-328K4.1-hsa-miR-27a-3p-PROS1, which is related to ICC, for further validation by molecular biology assays. GO analysis of 44 differentially expressed mRNAs in ceRNET revealed that they were mainly enriched in biological processes including "negative regulation of epithelial cell proliferation" and "positive regulation of activated T lymphocyte proliferation." KEGG analysis showed that they were mainly enriched in the "complement and coagulation cascade" pathway. The molecular biology assay showed that lncRNA RP11-328K4.1 expression was significantly lower in the cancerous tissues and peripheral plasma of ICC patients than in normal controls (p<0.05). In addition, hsa-miR-27a-3p was found to be significantly upregulated in the cancer tissues and peripheral plasma of ICC patients (p<0.05). Compared to normal controls, the expression of PROS1 mRNA was significantly downregulated in ICC patient cancer tissues (p<0.05) but not in peripheral plasma (p>0.05). Furthermore, ROC analysis revealed that RP11-328K4.1, hsa-miR-27a-3p, and PROS1 had significant diagnostic value in ICC. We concluded that the upregulation of lncRNA RP11-328K4.1, which might act as a miRNA sponge, exerts an antitumor effect in ICC by eliminating the inhibition of PROS1 mRNA expression by oncogenic miRNA hsa-miR-27a.

Prognostic value and underlying mechanism of KIAA0101 in hepatocellular carcinoma: database mining and co-expression analysis.

Although KIAA0101 is involved in many diseases, its expression and prognostic value in HCC remain undefined. According to CCLE, KIAA0101 is highly expressed in HCC, with a weak positive correlation between copy number and gene expression. Four studies involving 760 samples in ONCOMINE report elevated KIAA0101 expression in HCC (p=3.11E-22). The KM plotter revealed high KIAA0101 expression to be associated with worse overall survival in HCC (HR=2.09, p=4.1e-05); this prognostic power was stronger for male than female, early-stage than advanced-stage, and Asian than Caucasian patients. RNA sequencing data for 8 pairs of HCC and adjacent tissue samples validated the significantly high KIAA0101 level (p=0.00497). Moreover, functional annotations of 31 KIAA0101-coexpressed genes show enrichment of terms associated with mitosis, cytoskeleton construction, and chromosome segregation. Among 9 genes having STRING-validated protein-protein interactions with KIAA0101, two are involved in virus-related pathways. Alternative splicing analysis indicated higher expression of variant 1 and variant 2 in HCC and no significant differences in exon usage of KIAA0101 between cancer and normal tissues. These findings support that KIAA0101 is a potential prognostic biomarker for HCC and highlight the association between virus infection and the mechanism underlying the process by which KIAA0101 contributes to poor prognosis of patients.

Needle-free cervical cancer treatment using helical multishield intracavitary rotating shield brachytherapy with the 169 Yb Isotope.

PURPOSE: To assess the capability of an intracavitary 169 Yb-based helical multishield rotating shield brachytherapy (RSBT) delivery system to treat cervical cancer. The proposed RSBT delivery system contains a pair of 1.25 mm thick platinum partial shields with 45° and 180° emission angles, which travel in a helical pattern within the applicator. METHODS: A helically threaded tandem applicator with a 45° tandem curvature containing a helically threaded catheter was designed. A 0.6 mm diameter 169 Yb source with a length of 10.5 mm was simulated. A 37-patient treatment planning study, based on Monte Carlo dose calculations using MCNP5, was conducted with high-risk clinical target volumes (HR-CTVs) of 41.2-192.8 cm3 (average ± standard deviation of 79.9 ± 35.8 cm3 ). All patients were assumed to receive 25 fractions of 1.8 Gy of external beam radiation therapy (EBRT) before receiving 5 fractions of high-dose-rate brachytherapy (HDR-BT). For each patient, 192 Ir-based intracavitary (IC) HDR-BT, 192 Ir-based intracavitary/interstitial (IC/IS) HDR-BT using a hybrid applicator with eight IS needles, and 169 Yb-based RSBT plans were generated. RESULTS: For the IC, IC/IS, and RSBT treatment plans, 38%, 84%, and 86% of the plans, respectively, met the planning goal of an HR-CTV D90 (minimum dose to hottest 90%) of 85 GyEQD2 (α/ß = 10 Gy). Median (25th percentile, 75th percentile) treatment times for IC, IC/IS, and RSBT were 11.71 (6.62, 15.40) min, 68.00 (45.02, 80.02) min, and 25.30 (13.87, 35.39) min, respectively. 192 Ir activities ranging from 159.1-370 GBq (4.3-10 Ci) and 169 Yb activities ranging from 429.2-999 GBq (11.6-27 Ci) were used, which correspond to the same clinical ranges of dose rates at 1 cm off-source-axis in water. Extra needle insertion and planning time beyond that needed for intracavitary-only approaches was accounted for in the IC/IS treatment time calculations. CONCLUSION: 169 Yb-based RSBT for cervical cancer met the HR-CTV D90 goal of 85 Gy in a greater percentage of the patients considered than IC/IS (86% vs 84%, respectively) and can reduce overall treatment time relative to IC/IS. 169 Yb-based RSBT could be used to replace IC/IS in instances where IC/IS treatment is not available, especially in instances when HR-CTV volumes are ≥30 cm3 .

Prognostic Significance of the Preoperative Lymphocyte to Monocyte Ratio in Patients with Gallbladder Carcinoma.

BACKGROUND: This study was designed to investigate the prognostic value of the lymphocyte to monocyte ratio (LMR) in patients with gallbladder carcinoma (GBC). PATIENTS AND METHODS: We retrospectively enrolled 154 consecutive GBC patients from 2005 to 2017 in this study. The LMR of preoperative blood samples was calculated by dividing the lymphocyte count by the monocyte count. A receiver operating characteristic (ROC) curve was employed to identify the optimal cut-off value of the LMR in the determination of overall survival (OS). The Kaplan-Meier method was utilized to assess OS, and the Log rank test was employed to compare survival differences. Univariate and multivariate Cox regression analyses were conducted to detect independent prognostic indicators. RESULTS: The optimal cut-off point for the LMR was 4.76 according to the ROC curve. Patients ≤60 years old with an LMR ≤4.76 experienced significantly worse OS than those with an LMR >4.76 (hazard ratio (HR): 0.399, 95% confidence interval (CI): 0.265-0.602, P<0.001); however, the prognostic value of the LMR was not determined in patients >60 years old or among the entire study cohort (both P>0.05). Significantly poorer OS was observed in patients >60 years with an LMR ≤4.21 compared to those with an LMR >4.21 (HR: 1.830, 95% CI: 1.129-2.967, P=0.014). Multivariate Cox regression analysis indicated that both the high and low LMR cut-off values were independent risk factors for OS (HR: 0.272, 95% CI: 0.105-0.704, P=0.007; HR: 0.544, 95% CI: 0.330-0.895, P=0.017). CONCLUSION: The LMR is an independent prognostic indicator for GBC patients, the cut-off value of which is age dependent.

CK20 and lymph node involvement predict adverse outcome of malignant intraductal papillary neoplasm of the bile duct.

OBJECTIVES: To identify prognostic factors of malignant intraductal papillary neoplasm of the bile duct (m-IPNB). MATERIALS AND METHODS: We included 38 consecutive cases which underwent surgical resection and diagnosed as IPNB with malignant component from January 2003 to January 2017. Clinicopathological variables were collected to conduct survival analysis and identify prognostic factors. RESULTS: The median overall survival (OS) of m-IPNB was 76.0 months, with 1-, 3-, and 5-year survival rates of 97.2%, 73.5%, and 59.8%, respectively. The median RFS was 48.0 months with 1-, 3-, and 5-year recurrence-free survival (RFS) rate was 83.2%, 59.8%, and 44.6%, respectively. Univariate analysis showed that elevation of carcinoembryonic antigen CEA, lymph node involvement, resection margin status, degree of periductal invasion, and positive expression of CK20 were associated with both OS and RFS of m-IPNB. After multivariate Cox models analysis, lymph node involvement and positive expression of CK20 were identified as independent prognostic factors for OS, while lymph node involvement and resection margin status were independent prognostic factors for RFS. The median OS of patients with m-IPNB involving lymphatic metastases and positive expression of CK20 was 27.0±8.8 months and 51.0±12.4 months, respectively. The median RFS of cases with lymph node involvement and R1 resection was 10.0±3.3 months and 25.0±6.9 months, respectively. However, there was no significant difference in OS or RFS between cases of pancreaticobiliary and intestinal subtype. CONCLUSIONS: Lymph node involvement and positive expression of CK20 are independent prognostic factors for shorter OS of m-IPNB, while patients with lymph node involvement and positive resection margin are at higher risk of tumor recurrence.