Longitudinal outcomes of high-risk human papillomavirus (HPV) infections as competing-risks events following cervical HPV test at baseline visit in the *NIS-LAMS** cohort

Background: The complex natural history of human papillomavirus (HPV) infections following a single HPV test can be modeled as competing-risks events (i.e., no-, transient- or persistent infection) in a longitudinal setting. The covariates associated with these compet ng events have not been previously assessed using competing-risks regression models. Objectives: To gain further insights in the outcomes of cervical HPV infections, we used univariate- and multivariate competing-risks regression models to assess the covariaies associated with these competing events. Study Design and Methods: Covariates associated with three competing outcomes (no-, transient- or persistent HR-HPV infection) were analysed in a sub-cohort of 1,865 women prospectively followed-up in the NIS (n = 3,187) and LAMS Study (n = 12,114). Results: In multivariate competing-risks models (with two other outcomes as competing events), permanently HR-HPV negative outcome was significantly predicted only by the clearance of ASCUS+Pap during FU, while three independent covariates predicted transient HR-HPV infections: i) number of recent (< 12 months) sexual partners (risk increased), ii) previous Pap screening history (protective), and history of previous CIN (increased risk). The two most powerful predictors of persistent HR-HPV infections were persistent ASCUS+Pap (risk increased), and previous Pap screening history (protective). In pair-wise comparisons, number of recent sexual partners and previous CIN history increase the probability of transient HR-HPV infection against the HR-HPV negative competing event, while previous Pap screening history is protective. Persistent ASCUS+Pap during FU and no previous Pap screening history are significantly associated with the persistent HR-HPV outcome (compared both with i) always negative, and ii) transient events), whereas multiparity is protective. Conclusions: Different covariates are associated with the three main outcomes of cervical HPV infections. The most significant covariates of each competing events are probably distinct enough to enable constructing of a risk-profile for each main outcome.

Covariates of high-risk human papillomavirus (HPV) infections are distinct for incident CIN1, CIN2 and CIN3 as disclosed by competing-risks regression models

Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1, CIN2 and CIN3. This emphasises true biological differences between the three grades of GIN, which revisits the concept of combining CIN2 with CIN3 or with CIN1 in histological classification or used as a common end-point, e.g., in HPV vaccine trials.

Risks, Benefits, and Therapeutic Potential of Hematopoietic Stem Cell Transplantation for Autoimmune Diabetes

Type 1 diabetes mellitus is a chronic disease that results from the autoimmune response against pancreatic insulin producing beta cells. Apart of several insulin regimens, since the decade of 80s various immunomodulatory regimens were tested aiming at blocking some steps of the autoimmune process against beta cell mass and at promoting beta cell preservation. In the last years, some independent research groups tried to cure type 1 diabetes with an "immunologic reset" provided by autologous hematopoietic stem cell transplantation in newly diagnosed patients, and the majority of patients became free form insulin with increasing levels of C-peptide along the time. In this review, we discuss the biology of hematopoietic stem cells and the possible advantages and disadvantages related to the high dose immunosuppression followed by autologous hematopoietic stem cell transplantation.

The dengue virus non-structural 1 protein: risks and benefits

The dengue virus (DENV) non-structural 1 (NS1) protein plays a critical role in viral RNA replication and has a central position in DENV pathogenesis. DENV NS1 is a glycoprotein expressed in infected mammalian cells as soluble monomers that dimerize in the lumen of the endoplasmic reticulum; NS1 is subsequently transported to the cell surface, where it remains membrane associated or is secreted into the extracellular milieu as a hexameric complex. During the last three decades, the DENV NS1 protein has also been intensively investigated as a potential target for vaccines and antiviral drugs. In addition, NS1 is the major diagnostic marker for dengue infection. This review highlights some important issues regarding the role of NS1 in DENV pathogenesis and its biotechnological applications, both as a target for the development of safe and effective vaccines and antiviral drugs and as a tool for the generation of accurate diagnostic methods