Well-posedness for a class of nonlinear degenerate parabolic equations

In this paper we obtain well-posedness for a class of semilinear weakly degenerate reaction-diffusion systems with Robin boundary conditions. This result is obtained through a Gagliardo-Nirenberg interpolation inequality and some embedding results for weighted Sobolev spaces

A Carleman estimate and an energy method for a first-order symmetric hyperbolic system

For a symmetric hyperbolic system of the first order, we prove a Carleman estimate under some positivity condition concerning the coefficient matrices. Next, applying the Carleman estimate, we prove an observability L2-estimate for initial values by boundary data

Inverse coefficient problems for a transport equation by local Carleman estimate

We consider the transport equation ∂tu(x,t)+(H(x) - ∇u(x,t))+p(x)u(x,t)=0 in Ω ×(0,t) where Ω ⊂ ℝn is a bounded domain, and discuss two inverse problems which consist of determining a vector-valued function p(x) or a real-valued function Ω by initial values and data on a subboundary of Ω. Our results are conditional stability of Hölder type in a subdomain D provided that the outward normal component of H(x) is positive on ∂D∩∂Ω. The proofs are based on a Carleman estimate where the weight function depends on H

Pregnancy Loss in Women with HIV is not Associated with HIV Markers: Data from a National Study in Italy, 2001-2018.

BACKGROUND: There is limited information on pregnancy loss in women with HIV, and it is still debated whether HIV-related markers may play a role.Objectives: To explore potential risk factors for pregnancy loss in women with HIV, with particular reference to modifiable risk factors and markers of HIV disease. METHODS: Multicenter observational study of HIV-positive pregnant women. The main outcome measure was pregnancy loss, including both miscarriage (<22 weeks) and stillbirth ( 6522 weeks). Possible associations of pregnancy loss were evaluated in univariate and multivariate analyses. RESULTS: Among 2696 eligible pregnancies reported between 2001 and 2018, 226 (8.4%) ended in pregnancy loss (miscarriage 198, 7.3%; stillbirth 28, 1.0%). In multivariate analyses, only older age (adjusted odds ratio [AOR] per additional year of age: 1.079, 95% confidence interval [CI] 1.046-1.113), HIV diagnosis before pregnancy (AOR: 2.533, 95%CI 1.407-4.561) and history of pregnancy loss (AOR: 1.625, 95%CI 1.178-2.243) were significantly associated with pregnancy loss. No significant association with pregnancy loss was found for parity, coinfections, sexually transmitted diseases, hypertension, smoking, alcohol and substance use, CD4 cell count, HIV-RNA viral load, and CDC HIV stage. CONCLUSIONS: Older women and those with a previous history of pregnancy loss should be considered at higher risk of pregnancy loss. The severity of HIV disease and potentially modifiable risk factors did not increase the risk of pregnancy loss

Learning about Actions and Events in Shared NeMuS

The categorization process of information from pure data or learned in unsuper- vised artificial neural networks is still manual, especially in the labeling phase. Such a process is fundamental to knowledge representation [6], especially for symbol-based systems like logic, natural language processing and textual infor- mation retrieval. Unfortunately, applying categorization theory in large volumes of data does not lead to good results mainly because there is no generic and systematic way of categorizing such data processed by artificial neural networks and joining investigated conceptual structures. Connectionist approaches are capable of extracting information from arti- ficial neural networks, but categorizing them as symbolic knowledge have been little explored. The obstacle lies on the difficulty to find logical justification from response patterns of these networks [2]. This gets worse when considering induc- tive learning from dynamic data which is very important to Cognitive Sciences that considers categorization as a mental operation of classifying objects, actions and events [1]. We shall address the discoveries of our on-going investigation on the problem of inductively learning (IL) from dynamic data by applying a novel framework for neural-symbolic representation and reasoning called share Neural Multi-Space (NeMuS) used in the Amao system[4]. Instead of woking like traditional ap- proaches for ILP, e.g. [5], Amao uses a shared NeMuS of a give background knowledge (BK) and uses inverse unification as the generalization mechanism of a set of logically connected expressions from the Herbrand Base (HB) of BK that defines positive examples

A novel genotype and first record of trypanosoma lainsoni in Argentina

Trypanosomes are a group of parasitic flagellates with medical and veterinary importance. Despite many species having been described in this genus, little is known about many of them. Here, we report a genetic and morphological characterization of trypanosomatids isolated from wild mammals from the Argentine Chaco region. Parasites were morphologically and ultrastructurally characterized by light microscopy and transmission electron microscopy. Additionally, 18s rRNA and gGAPDH genes were sequenced and analyzed using maximum likelihood and Bayesian inference. Morphological characterization showed clear characteristics associated with the Trypanosoma genus. The genetic characterization demonstrates that the studied isolates have identical sequences and a pairwise identity of 99% with Trypanosoma lainsoni, which belongs to the clade of lizards and snakes/rodents and marsupials. To date, this species had only been found in the Amazon region. Our finding represents the second report of T. lainsoni and the first record for the Chaco region. Furthermore, we ultrastructurally described for the first time the species. Finally, the host range of T. lainsoni was expanded (Leopardus geoffroyi, Carenivora, Felidae; and Calomys sp., Rodentia, Cricetidae), showing a wide host range for this species.Fil: Díaz, Anahí G.. Universidad Nacional de Salta; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Ragone, Paula Gabriela. Universidad Nacional de Salta; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Rusman, Fanny. Universidad Nacional de Salta; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Floridia Yapur, Noelia Aldana del Rosario. Universidad Nacional de Salta; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Barquez, Ruben Marcos. Universidad Nacional de Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Programa de Investigación de Biodiversidad Argentina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Díaz, María Mónica. Universidad Nacional de Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Programa de Investigación de Biodiversidad Argentina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Tomasini, Nicolás. Universidad Nacional de Salta; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Diosque, Patricio. Universidad Nacional de Salta; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; Argentin

Lipid profile during pregnancy in HIV-infected women

Purpose: We investigated the evolution of serum lipid levels in HIV-infected pregnant women and the potential effect of antiretroviral treatment during pregnancy using data from a national surveillance study. Method: Fasting lipid measurements collected during routine care in pregnancy were used, analyzing longitudinal changes and differences in lipid values at each trimester by protease inhibitors (Pls) and stavudine use. Multivariate analyses were used to control for simultaneous factors potentially leading to hyperlipidemia. Study population included 248 women. Results: Lipid values increased progressively and significantly during pregnancy: mean increases between the first and third trimesters were 141.6 mg/dL for triglycerides (p <.001), 60.8 mg/dL for total cholesterol (p <.001), 13.7 mg/dL for HDL cholesterol (p <.001), and 17.8 mg/dL for LDL cholesterol (p =.001). At all trimesters, women on PIs had significantly higher triglyceride values compared to women not on Pis. The effect of Pls on cholesterol levels was less consistent. Stavudine showed a dyslipidemic effect at first trimester only. Multivariate analyses confirmed these observations and suggested a potential role of other cofactors in the development of hyperlipidemia during pregnancy. Conclusion: The changes observed point to the need to further explore the causes and the clinical correlates of hyperlipidemia during pregnancy in women with HIV

Improving diagnosis for rare diseases: the experience of the Italian undiagnosed Rare diseases network

Background For a number of persons with rare diseases (RDs) a definite diagnosis remains undiscovered with relevant physical, psychological and social consequences. Undiagnosed RDs (URDs) require other than specialised clinical centres, outstanding molecular investigations, common protocols and dedicated actions at national and international levels; thus, many "Undiagnosed RDs programs" have been gradually developed on the grounds of a well-structured multidisciplinary approach. Methods The Italian Undiagnosed Rare Diseases Network (IURDN) was established in 2016 to improve the level of diagnosis of persons with URD living in Italy. Six Italian Centres of Expertise represented the network. The National Centre for Rare Diseases at the Istituto Superiore di Sanita coordinates the whole project. The software PhenoTips was used to collect the information of the clinical cases. Results One hundred and ten cases were analysed between March 2016 and June 2019. The age of onset of the diseases ranged from prenatal age to 51 years. Conditions were predominantly sporadic; almost all patients had multiple organs involvements. A total of 13/71 family cases were characterized by WES; in some families more than one individual was affected, so leading to 20/71 individuals investigated. Disease causing variants were identified in two cases and were associated to previously undescribed phenotypes. In 5 cases, new candidate genes were identified, although confirmatory tests are pending. In three families, investigations were not completed due to the scarce compliance of members and molecular investigations were temporary suspended. Finally, three cases (one familial) remain still unsolved. Twelve undiagnosed clinical cases were then selected to be shared at International level through PhenomeCentral in accordance to the UDNI statement. Conclusions Our results showed a molecular diagnostic yield of 53,8%; this value is comparable to the diagnostic rates reported in other international studies. Cases collected were also pooled with those collected by UDNI International Network. This represents a unique example of global initiative aimed at sharing and validating knowledge and experience in this field. IURDN is a multidisciplinary and useful initiative linking National and International efforts aimed at making timely and appropriate diagnoses in RD patients who still do not have a confirmed diagnosis even after a long time

High Levels of Receptor Tyrosine Kinases in CCM3-Deficient Cells Increase Their Susceptibility to Tyrosine Kinase Inhibition

Cerebral cavernous malformations (CCMs) are vascular malformations that can be the result of the deficiency of one of the CCM genes. Their only present treatment is surgical removal, which is not always possible, and an alternative pharmacological strategy to eliminate them is actively sought. We have studied the effect of the lack of one of the CCM genes, CCM3, in endothelial and non-endothelial cells. By comparing protein expression in control and CCM3-silenced cells, we found that the levels of the Epidermal Growth Factor Receptor (EGFR) are higher in CCM3-deficient cells, which adds to the known upregulation of Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) in these cells. Whereas VEGFR2 is upregulated at the mRNA level, EGFR has a prolonged half-life. Inhibition of EGFR family members in CCM3-deficient cells does not revert the known cellular effects of lack of CCM genes, but it induces significantly more apoptosis in CCM3-deficient cells than in control cells. We propose that the susceptibility to tyrosine kinase inhibitors of CCM3-deficient cells can be harnessed to kill the abnormal cells of these lesions and thus treat CCMs pharmacologically