Implementation of a re-linkage to care strategy in patients with chronic hepatitis C who were lost to follow-up in Latin America

To achieve WHO's goal of eliminating hepatitis C virus (HCV), innovative strategies must be designed to diagnose and treat more patients. Therefore, we aimed to describe an implementation strategy to identify patients with HCV who were lost to follow-up (LTFU) and offer them re-linkage to HCV care. We conducted an implementation study utilizing a strategy to contact patients with HCV who were not under regular follow-up in 13 countries from Latin America. Patients with HCV were identified by the international classification of diseases (ICD-9/10) or equivalent. Medical records were then reviewed to confirm the diagnosis of chronic HCV infection defined by anti-HCV+ and detectable HCV-RNA. Identified patients who were not under follow-up by a liver specialist were contacted by telephone or email, and offered a medical reevaluation. A total of 10,364 patients were classified to have HCV. After reviewing their medical charts, 1349 (13%) had undetectable HCV-RNA or were wrongly coded. Overall, 9015 (86.9%) individuals were identified with chronic HCV infection. A total of 5096 (56.5%) patients were under routine HCV care and 3919 (43.5%) had been LTFU. We were able to contact 1617 (41.3%) of the 3919 patients who were LTFU at the primary medical institution, of which 427 (26.4%) were cured at a different institutions or were dead. Of the remaining patients, 906 (76.1%) were candidates for retrieval. In our cohort, about one out of four patients with chronic HCV who were LTFU were candidates to receive treatment. This strategy has the potential to be effective, accessible and significantly impacts on the HCV care cascade.

A model for the emergence of adaptive subsystems

We investigate the interaction of learning and evolution in a changing environment. A stable learning capability is regarded as an emergent adaptive system evolved by natural selection of genetic variants. We consider the evolution of an asexual population. Each genotype can have 'fixed' and 'flexible' alleles. The former express themselves as synaptic connections that remain unchanged during ontogeny and the latter as synapses that can be adjusted through a learning algorithm. Evolution is modelled using genetic algorithms and the changing environment is represented by two optimal synaptic patterns that alternate a fixed number of times during the 'life' of the individuals. The amplitude of the change is related to the Hamming distance between the two optimal patterns and the rate of change to the frequency with which both exchange roles. This model is an extension of that of Hinton and Nowlan in which the fitness is given by a probabilistic measure of the Hamming distance to the optimum. We find that two types of evolutionary pathways are possible depending upon how difficult (costly) it is to cope with the changes of the environment. In one case the population loses the learning ability, and the individuals inherit fixed synapses that are optimal in only one of the environmental states. In the other case a flexible subsystem emerges that allows the individuals to adapt to the changes of the environment. The model helps us to understand how an adaptive subsystem can emerge as the result of the tradeoff between the exploitation of a congenital structure and the exploration of the adaptive capabilities practised by learning.

A model for the interaction of learning and evolution

We present a simple model in order to discuss the interaction of the genetic and behavioral systems throughout evolution. This considers a set of adaptive perceptrons in which some of their synapses can be updated through a learning process. This framework provides an extension of the well-known Hinton and Nowlan model by blending together some learning capability and other (rigid) genetic effects that contribute to the fitness. We find a halting effect in the evolutionary dynamics, in which the transcription of environmental data into genetic information is hindered by learning, instead of stimulated as is usually understood by the so-called Baldwin effect. The present results are discussed and compared with those reported in the literature. An interpretation is provided of the halting effect.

Fault tolerance in noise-enhanced propagation

As a mock-up of synaptic transmission between neurons, we revisit a problem that has recently risen the interest of several authors: the propagation of a low-frequency periodic signal through a chain of one-way coupled bistable oscillators, subject to uncorrelated additive noise. On a numerical study performed in the optimal range of noise intensity for which essentially undamped transmission along the chain has been reported, we focus on the outcome of feeding with noise all the nodes but the central one. A (moderate) critical value of the coupling between oscillators is found such that whereas below it the propagation can be considered to be interrupted at the "dead neuron," it is reestablished above it. Thus, one of the distinguishing features of synaptic transmission, namely, a fault-tolerant behavior that enhances reliability at the expense of efficiency, arises here as an emergent property of the system.

[Neuroendocrine cell tumor of the stomach (carcinoid). Clinico-pathological experience with 4 patients and demonstration of its ultrastructure]

Neuroendocrine cell tumours of the stomach (carcinoid) are uncommon, low potential for malignancy, lesions grow slowly and produce hormonal substances in contrast with others malignant neoplasias of the gastrointestinal tract. Early diagnosis is important because the curative treatment could not be done in advanced stage with disseminated metastases. In small lesions less than 2 cm without invasion to lymph node, the local wedge resection is reasonable and definitive curative treatment. Neuroendocrine differentiation, in doubtful cases, becomes established by a characteristic silver affinity, by the ultrastructurally observed presence of "endocrine" secretion granules, and by immunohistochemically detectable biogenic amines, neurohormonal peptides and "panNE markers".