Postoperative nomogram for disease-specific survival after an R0 resection for gastric carcinoma.

PURPOSE: Few published studies have addressed individual patient risk after R0 resection for gastric cancer. We developed and internally validated a nomogram that combines these factors to predict the probability of 5-year gastric cancer-specific survival on the basis of 1,039 patients treated at a single institution. METHODS: Nomogram predictor variables included age, sex, primary site (distal one-third, middle one-third, gastroesophageal junction, and proximal one-third), Lauren histotype (diffuse, intestinal, mixed), number of positive lymph nodes resected, number of negative lymph nodes resected, and depth of invasion. Death as a result of gastric cancer was the predicted end point. The concordance index was used as an accuracy measure, with bootstrapping to correct for optimistic bias. Calibration plots were constructed. RESULTS: Gastric cancer-specific survival at 5 years was 50%. A nomogram was constructed on the basis of a Cox regression model. The bootstrap-corrected concordance index was 0.80. When compared with the predictive ability of American Joint Committee on Cancer stage, the nomogram discrimination was superior (P <.001). Nomogram calibration appeared to be excellent. CONCLUSION: A nomogram was developed to predict 5-year disease-specific survival after R0 resection for gastric cancer. This tool should be useful for patient counseling, follow-up scheduling, and clinical trial eligibility determination.     

Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy.

PURPOSE: A postoperative nomogram for prostate cancer recurrence after radical prostatectomy (RP) has been independently validated as accurate and discriminating. We have updated the nomogram by extending the predictions to 10 years after RP and have enabled the nomogram predictions to be adjusted for the disease-free interval that a patient has maintained after RP. METHODS: Cox regression analysis was used to model the clinical information for 1,881 patients who underwent RP for clinically-localized prostate cancer by two high-volume surgeons. The model was externally validated separately on two independent cohorts of 1,782 patients and 1,357 patients, respectively. Disease progression was defined as a rising prostate-specific antigen (PSA) level, clinical progression, radiotherapy more than 12 months postoperatively, or initiation of systemic therapy. RESULTS: The 10-year progression-free probability for the modeling set was 79% (95% CI, 75% to 82%). Significant variables in the multivariable model included PSA (P = .002), primary (P < .0001) and secondary Gleason grade (P = .0006), extracapsular extension (P < .0001), positive surgical margins (P = .028), seminal vesicle invasion (P < .0001), lymph node involvement (P = .030), treatment year (P = .008), and adjuvant radiotherapy (P = .046). The concordance index of the nomogram when applied to the independent validation sets was 0.81 and 0.79. CONCLUSION: We have developed and validated as a robust predictive model an enhanced postoperative nomogram for prostate cancer recurrence after RP. Unique to predictive models, the nomogram predictions can be adjusted for the disease-free interval that a patient has achieved after RP.     

硫酸多糖对体外人脐静脉内皮细胞损伤的保护作用

研究表明,硫酸多糖体外对多聚阳离子和氧自由基损伤的人脐静脉内皮细胞有保护作用。肝素、硫酸软骨素A抗多聚阳离子损伤作用比同浓度低分子肝素和甘糖酯强。肝素、硫酸软骨素A、甘糖酯抗氧自由基损伤作用优于同浓度低分子肝素。结果显示硫酸多糖有保护血管内皮的作用,其作用可能与所带阴离子基团有关。     

Human ovarian granulosa cells and follicular fluid indices: the relationship to oocyte maturity and fertilization in vitro

The study investigates the correlation between oocyte maturity and fertilization and a variety of hormonal parameters in follicular fluid and ovarian granulosa cells. A methodology for purification of granulosa cells from contaminating blood cells is also established. A total of 63 follicular aspirates were collected at oocyte retrieval from 30 women superovulated using the long luteinizing hormone- releasing hormone (LHRH analogue)/human menopausal gonadotrophin regimen. Oestradiol, progesterone, testosterone and human chorionic gonadotrophin (HCG) were quantified in follicular fluid and granulosa cells were immunostained for human chorionic gonadotrophin. Immunopurification of granulosa cells from contaminating blood cells was performed. HCG in follicular fluid was significantly high in follicles yielding immature (grade 3) oocytes (P=0.002); there was no correlation with fertilization. Aspirates from follicles containing mature (grade 1) oocytes and oocytes that subsequently fertilized had significantly more granulosa cells immunobound to HCG (P < 0.001, P=0.02). Moreover, the immunomagnetic purification technique provided >98% pure population of granulosa cells. The data demonstrate that HCG in follicular fluid and on granulosa cells may help to predict oocyte maturity and fertilization. Furthermore, immunomagnetic beads provide a reliable procedure for the purification of ovarian granulosa cells.      

Autosomal glycogenosis of liver and muscle due to phosphorylase kinase deficiency is caused by mutations in the phosphorylase kinase beta subunit (PHKB)

Glycogen storage disease due to phosphorylase kinase deficiency occurs in several variants that differ in mode of inheritance and tissue- specificity. This heterogeneity is suspected to be largely due to mutations affecting different subunits and isoforms of phosphorylase kinase. The gene of the ubiquitously expressed beta subunit, PHKB, was a candidate for involvement in autosomally transmitted phosphorylase kinase deficiency of liver and muscle. To identify such mutations, the complete PHKB coding sequence was amplified by RT-PCR of RNA isolated from blood samples of patients and analyzed by direct sequencing of PCR products. The characterization of mutations was complemented by PCR of genomic DNA. In one female and four male patients, we identified five independent nonsense mutations (Y418ter; R428ter; Y974H+E975ter; Q656ter in two cases), one single-base insertion in codon N421, one splice-site mutation affecting exon 31, and a large deletion involving the loss of exon 8. Although these severe translation-disrupting mutations occur in constitutively expressed sequences of the only known beta subunit gene of phosphorylase kinase, PHKB, they are associated with a surprisingly mild clinical phenotype, affecting virtually only the liver, and relatively high residual enzyme activity of approximately 10%.      

Delivery of a hammerhead ribozyme specifically down-regulates the production of fibrillin-1 by cultured dermal fibroblasts

The hammerhead ribozyme is a small catalytic RNA molecule. Potential hammerhead ribozymes that possess a catalytic domain and flanking sequence complementary to a target mRNA can cleave in trans at a putative cleavage site within the target molecule. We have investigated the potential of hammerhead ribozymes to down-regulate the product of the fibrillin-1 gene (FBN1). Fibrillin is a 347 kDa glycoprotein that is a major constituent of the elastin-associated microfibrils. Mutations in the FBN1 gene are responsible for Marfan syndrome (MFS), a common systemic disorder of the connective tissue. Many FBN1 mutations responsible for MFS appear to act in a dominant-negative fashion, raising the possibility that reduction of the amount of product from the mutant FBN1 allele might be a valid therapeutic approach for MFS. A trans-acting hammerhead ribozyme (FBN1-RZ1) targeted to the 5' end of the human FBN1 mRNA has been designed and synthesized, and shown to cleave its target efficiently in vitro. FBN1-RZ1 cleavage is magnesium dependent and efficient at both 37 and 50 degrees C. Delivery of the FBN1-RZ1 ribozyme into cultured dermal fibroblasts, by receptor- mediated endocytosis of a ribozyme-transferrin-polylysine complex, specifically reduces both cellular FBN1 mRNA and the deposition of fibrillin in the extracellular matrix. These results suggest that the use of hammerhead ribozymes is a valid approach to the study of fibrillin gene expression and possibly to the development of a therapeutic approach to MFS.      

Protective cytotoxic T lymphocyte responses against paramyxoviruses induced by epitope-based DNA vaccines: involvement of IFN-gamma

Plasmid DNA vectors have been constructed with minigenes encoding a single cytotoxic T lymphocyte (CTL) epitope from either the M2 protein of respiratory syncytial virus (RSV) or from the nucleoprotein of measles virus (MV) with or without a signal sequence (also called secretory or leader sequence). Following intradermal immunization, plasmids in which the CTL epitopes were expressed in-frame with the signal sequence were more effective at inducing peptide- and virus- specific CTL responses than plasmids expressing CTL epitopes without the signal sequence. This immunization resulted in protection against MV-induced encephalitis and a significant reduction in viral load following RSV challenge. The reduction of viral load following RSV challenge was abrogated by prior injection with anti-IFN-gamma antibodies. These results highlight the ability of epitope-based DNA immunization to induce protective immune responses to well-defined epitopes and indicate the potential of this approach for the development of vaccines against infectious diseases.      

Machine learning for survival analysis: a case study on recurrence of prostate cancer

Machine learning techniques have recently received considerable attention, especially when used for the construction of prediction models from data. Despite their potential advantages over standard statistical methods, like their ability to model non-linear relationships and construct symbolic and interpretable models, their applications to survival analysis are at best rare, primarily because of the difficulty to appropriately handle censored data. In this paper we propose a schema that enables the use of classification methods--including machine learning classifiers--for survival analysis. To appropriately consider the follow-up time and censoring, we propose a technique that, for the patients for which the event did not occur and have short follow-up times, estimates their probability of event and assigns them a distribution of outcome accordingly. Since most machine learning techniques do not deal with outcome distributions, the schema is implemented using weighted examples. To show the utility of the proposed technique, we investigate a particular problem of building prognostic models for prostate cancer recurrence, where the sole prediction of the probability of event (and not its probability dependency on time) is of interest. A case study on preoperative and postoperative prostate cancer recurrence prediction shows that by incorporating this weighting technique the machine learning tools stand beside modern statistical methods and may, by inducing symbolic recurrence models, provide further insight to relationships within the modeled data.