A pre-S gene chip to detect pre-S deletions in hepatitis B virus large surface antigen as a predictive marker for hepatoma risk in chronic hepatitis B virus carriers

<p>Abstract</p> <p>Background</p> <p>Chronic hepatitis B virus (HBV) infection is an important cause of hepatocellular carcinoma (HCC) worldwide. The pre-S₁and -S₂mutant large HBV surface antigen (LHBS), in which the pre-S₁and -S₂regions of the LHBS gene are partially deleted, are highly associated with HBV-related HCC.</p> <p>Methods</p> <p>The pre-S region of the LHBS gene in two hundred and one HBV-positive serum samples was PCR-amplified and sequenced. A pre-S oligonucleotide gene chip was developed to efficiently detect pre-S deletions in chronic HBV carriers. Twenty serum samples from chronic HBV carriers were analyzed using the chip.</p> <p>Results</p> <p>The pre-S deletion rates were relatively low (7%) in the sera of patients with acute HBV infection. They gradually increased in periods of persistent HBV infection: pre-S mutation rates were 37% in chronic HBV carriers, and as high as 60% in HCC patients. The Pre-S Gene Chip offers a highly sensitive and specific method for pre-S deletion detection and is less expensive and more efficient (turnaround time 3 days) than DNA sequencing analysis.</p> <p>Conclusion</p> <p>The pre-S_1/2mutants may emerge during the long-term persistence of the HBV genome in carriers and facilitate HCC development. Combined detection of pre-S mutations, other markers of HBV replication, and viral titers, offers a reliable predictive method for HCC risks in chronic HBV carriers.</p

Enhancing diagnosis of T-cell lymphoma using non-recombined T-cell receptor sequences

Clonality assessment, which can detect neoplastic T cells by identifying the uniquely recombined T-cell receptor (TCR) genes, provides important support in the diagnosis of T-cell lymphoma (TCL). BIOMED-2 is the gold standard clonality assay and has proven to be effective in European TCL patients. However, we failed to prove its sensitivity in Taiwanese TCL patients, especially based on the TCRβ gene. To explore potential impact of genetic background in the BIOMED-2 test, we analyzed TCRβ sequences of 21 healthy individuals and two TCL patients. This analysis suggests that genetic variations in the BIOMED-2 primer sites could not explain the difference in sensitivity. The BIOMED-2 test results of the two TCL patients were positive and negative, respectively. Interestingly, a higher percentage (&gt;81%) of non-recombined TCRβ sequences was observed in the test-negative patient than those of the test-positive patient and all healthy individuals (13~66%). The result suggests a new TCR target for enhancing TCL diagnosis. To further explore the hypothesis, we proposed a cost-effective digital PCR assay that quantifies the relative abundance of non-recombined TCRβ sequences containing a J2-2P~J2-3 segment. With the digital PCR assay, bone marrow specimens from TCL patients (n=9) showed a positive outcome (i.e., the relative abundance of the J2-2P~J2-3 sequences ≧5%), whereas non-TCL patients (n=6) gave a negative result. As five of nine TCL patients had a negative BIOMED-2 test result, the J2-2P~J2-3 sequences may improve TCL detection. This is the first report showing the capability of characterizing non-recombined TCR sequences as a supplementary strategy for the BIOMED-2 clonality test

Pre-Treatment with Melatonin Enhances Therapeutic Efficacy of Cardiac Progenitor Cells for Myocardial Infarction

Background/Aims: Melatonin possesses many biological activities such as antioxidant and anti-aging. Cardiac progenitor cells (CPCs) have emerged as a promising therapeutic strategy for myocardial infarction (MI). However, the low survival of transplanted CPCs in infarcted myocardium limits the successful use in treating MI. In the present study, we aimed to investigate if melatonin protects against oxidative stress-induced CPCs damage and enhances its therapeutic efficacy for MI. Methods: TUNEL assay and EdU assay were used to detect the effects of melatonin and miR-98 on H2O2-induced apoptosis and proliferation. MI model was used to evaluate the potential cardioprotective effects of melatonin and miR-98. Results: Melatonin attenuated H2O2-induced the proliferation reduction and apoptosis of c-kit+ CPCs in vitro, and CPCs which pretreated with melatonin significantly improved the functions of post-infarct hearts compared with CPCs alone in vivo. Melatonin was capable to inhibit the increase of miR-98 level by H2O2 in CPCs. The proliferation reduction and apoptosis of CPCs induced by H2O2 was aggravated by miR-98. In vivo, transplantation of CPCs with miR-98 silencing caused the more significant improvement of cardiac functions in MI than CPCs. MiR-98 targets at the signal transducer and activator of the transcription 3 (STAT3), and thus aggravated H2O2-induced the reduction of Bcl-2 protein. Conclusions: Pre-treatment with melatonin protects c-kit+ CPCs against oxidative stress-induced damage via downregulation of miR-98 and thereby increasing STAT3, representing a potentially new strategy to improve CPC-based therapy for MI

Induction of Bcl-2 Expression by Hepatitis B Virus Pre-S2 Mutant Large Surface Protein Resistance to 5-Fluorouracil Treatment in Huh-7 Cells

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide with poor prognosis due to resistance to conventional chemotherapy and limited efficacy of radiotherapy. Our previous studies have indicated that expression of Hepatitis B virus pre-S2 large mutant surface antigen (HBV pre-S2Δ) is associated with a significant risk of developing HCC. However, the relationship between HBV pre-S2Δ protein and the resistance of chemotherapeutic drug treatment is still unclear. METHODOLOGY/PRINCIPAL FINDINGS: Here, we show that the expression of HBV pre-S2Δ mutant surface protein in Huh-7 cell significantly promoted cell growth and colony formation. Furthermore, HBV pre-S2Δ protein increased both mRNA (2.7±0.5-fold vs. vehicle, p=0.05) and protein (3.2±0.3-fold vs. vehicle, p=0.01) levels of Bcl-2 in Huh-7 cells. HBV pre-S2Δ protein also enhances Bcl-2 family, Bcl-xL and Mcl-1, expression in Huh-7 cells. Meanwhile, induction of NF-κB p65, ERK, and Akt phosphorylation, and GRP78 expression, an unfolded protein response chaperone, were observed in HBV pre-S2Δ and HBV pre-S-expressing cells. Induction of Bcl-2 expression by HBV pre-S2Δ protein resulted in resistance to 5-fluorouracil treatment in colony formation, caspase-3 assay, and cell apoptosis, and can enhance cell death by co-incubation with Bcl-2 inhibitor. Similarly, transgenic mice showed higher expression of Bcl-2 in liver tissue expressing HBV pre-S2Δ large surface protein in vivo. CONCLUSION/SIGNIFICANCE: Our result demonstrates that HBV pre-S2Δ increased Bcl-2 expression which plays an important role in resistance to 5-fluorouracil-caused cell death. Therefore, these data provide an important chemotherapeutic strategy in HBV pre-S2Δ-associated tumor

Automatic assessment of glioma burden: A deep learning algorithm for fully automated volumetric and bi-dimensional measurement

Background Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO). Methods Two cohorts of patients were used for this study. One consisted of 843 preoperative MRIs from 843 patients with low- or high-grade gliomas from 4 institutions and the second consisted of 713 longitudinal postoperative MRI visits from 54 patients with newly diagnosed glioblastomas (each with 2 pretreatment “baseline” MRIs) from 1 institution. Results The automatically generated FLAIR hyperintensity volume, contrast-enhancing tumor volume, and AutoRANO were highly repeatable for the double-baseline visits, with an intraclass correlation coefficient (ICC) of 0.986, 0.991, and 0.977, respectively, on the cohort of postoperative GBM patients. Furthermore, there was high agreement between manually and automatically measured tumor volumes, with ICC values of 0.915, 0.924, and 0.965 for preoperative FLAIR hyperintensity, postoperative FLAIR hyperintensity, and postoperative contrast-enhancing tumor volumes, respectively. Lastly, the ICCs for comparing manually and automatically derived longitudinal changes in tumor burden were 0.917, 0.966, and 0.850 for FLAIR hyperintensity volume, contrast-enhancing tumor volume, and RANO measures, respectively. Conclusions Our automated algorithm demonstrates potential utility for evaluating tumor burden in complex posttreatment settings, although further validation in multicenter clinical trials will be needed prior to widespread implementation

DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management

Abstract Background Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma. Methods DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts. Results The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03–0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8–7.2, P &lt; 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22–0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3–11.1, P &lt; 0.001) with clinical implications. Conclusions The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone. </jats:sec

It’s us or them: a study of social value orientation and type of salient group culture in intergroup conflict

As one of the biggest problems of the century, intergroup conflict has drawn much attention in social psychology. Achieving intra- and intergroup cooperation is valuable in promoting cohesive societies, but oftentimes unattainable. The present study aimed to disentangle motives for behaviours in intergroup conflict as well as possible factors that could promote ingroup welfare without the expense of outgroup welfare. The study examined the influence of the dispositional trait Social Value Orientation (SVO; Prosocial vs. Proself), the type of salient group culture (ingroup vs. outgroup vs. neutral), and their combined effect on behaviours in intergroup conflict, specifically expression of ingroup love and outgroup hate. 111 participants responded to the Slider Measure of SVO, underwent a priming procedure to increase the salience of ingroup culture, outgroup culture or no culture, and the Intergroup Prisoner’s Dilemma-Maximising Difference game as a model of intergroup conflict. Results indicate that (1) ingroup love increased with prosociality but not outgroup hate, (2) salient group culture, both ingroup and outgroup culture, increased outgroup hate, (3) the type of salient group culture did not moderate the effect of SVO on ingroup love and outgroup hate. Possible explanations, limitations, future direction, societal and policy implications were discussed.Bachelor of Social Sciences in Psycholog

A New Method of Pedestrian Abnormal Behavior Detection Based on Attention Guidance

In public places, some behavior that violates public order and endangers public safety is defined as abnormal behavior. Moreover, it is a necessary auxiliary means to maintain public order and safety by detecting abnormal behavior in a large number of surveillance videos. However, due to the small proportion of abnormal behavior in video data, the extreme imbalance of data seriously restricts the effectiveness of detection. So, weakly supervised learning has become the most suitable and effective detection method. However, existing weakly supervised methods rarely take the locality and slightness of abnormal behavior into account and ignore the details of extracted features. Based on this, an attention-directed abnormal behavior detection model is proposed. In the two common prediction and reconstruction abnormal behavior detection methods based on weak supervision, suitable attention mechanisms are introduced, respectively, and two corresponding attention-directed networks are proposed. In addition, aiming at the problem of inaccurate thresholds for abnormal behavior division, the loss function of the model is improved and a new abnormal behavior evaluation method is proposed. Experiments were carried out on three classical datasets (the USCD Ped1, USCD Ped2, and CUHK Avenue dataset) for abnormal behavior detection. The best results for the area under the curve (AUC) indicator reached 82.7%, 94.5%, and 87.3%, respectively, which are better than many existing literature results

Adaptive finite-time synchronization of fractional-order memristor chaotic system based on sliding-mode control

In this paper, based on sliding-mode control, a finite-time adaptive synchronization method is introduced to realize the generalized projective synchronization of fractional-order memristor chaotic systems with unknown parameters. First, a class of memristor chaotic system is extended to fractional order, and the chaos characteristics of the system are studied. Then a new fractional-order integral sliding-mode surface with faster convergence speed is designed, which can make the error system converge to zero in finite time. Next the controller with adjustable parameters and the adaptive laws are designed, and the sufficient condition for the sliding-mode surface can be reached by the synchronization error system in finite time and the unknown parameters can be identified in finite time is obtained. Finally, the numerical simulations show that the generalized projection synchronization and unknown parameter identification of fractional-order memristor chaotic system can be realized in a short time under the proposed synchronization strategy

Discrete Optimization Model and Algorithm for Driver Planning in Periodic Driver Routing Problem

Workforce planning is an operation management problem in the delivery industry to improve service quality and reliability, and the working attitude and passion of drivers, as the direct implementors of delivery service, affect the service level. Consequently, assigning equal workload for drivers so as to improve drivers’ acceptance is a reasonable and efficient workforce plan for managers. This paper investigates a periodic driver routing problem to explore the relationship between workload differential among drivers and total workload; the objective of the optimization problem is to minimize the total workload. To tackle this problem, we first propose a mixed-integer linear programming model, which can be solved by an off-the-shelf mixed-integer linear programming solver, and use the local branching based method to solve larger instances of the problem. Numerical experiments are conducted to validate the effectiveness and efficiency of the proposed model and solution method, as well as the effect of small workload differential among drivers on the total workload