Neglected diseases of neglected populations: Thinking to reshape the determinants of health in Latin America and the Caribbean

BACKGROUND: People living in poverty throughout the developing world are heavily burdened with neglected communicable diseases and often marginalized by the health sector. These diseases are currently referred to as Neglected Diseases of Neglected Populations. The neglected diseases create social and financial burdens to the individual, the family, the community, and the nation. DISCUSSION: Numerous studies of successful individual interventions to manage communicable disease determinants in various types of communities have been published, but few have applied multiple interventions in an integrated, coordinated manner. We have identified a series of successful interventions and developed three hypothetical scenarios where such interventions could be applied in an integrated, multi-disease, inter-programmatic, and/or inter-sectoral approach for prevention and control of neglected diseases in three different populations: a slum, an indigenous community, and a city with a mix of populations. SUMMARY: The objective of this paper is to identify new opportunities to address neglected diseases, improve community health and promote sustainable development in neglected populations by highlighting examples of key risk and protective factors for neglected diseases which can be managed and implemented through multi-disease-based, integrated, inter-programmatic, and/or inter-sectoral approaches. Based on a literature review, analysis and development of scenarios we visualize how multiple interventions could manage multiple disease problems and propose these as possible strategies to be tested. We seek to stimulate intra- and inter-sectoral dialogue which will help in the construction of new strategies for neglected diseases (particularly for the parasitic diseases) which could benefit the poor and marginalized based on the principle of sustainability and understanding of key determinants of health, and lead to the establishment of pilot projects and activities which can contribute to the achievement of the Millennium Development Goals

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

World Journal of Gastroenterology ISSN 1007-9327

doi:10.3748/wjg.14.496

Prediction of bone mass gain by bone turnover parameters after parathyroidectomy for primary hyperparathyroidism: neural network software statistical analysis.

Background: Primary hyperparathyroidism (pHPT) is the most frequent endocrine hypersecretion disease, and parathyroidectomy is the only curative option, since pharmacologic therapy reduces hypercalcemia but does not impede parathyroid hormone hypersecretion. According to guidelines from the National Institutes of Health, parathyroidectomy is associated with bone mass increase in some asymptomatic patients, while in others bone mass is not changed after surgery. Therefore, we performed the present study in an attempt to elucidate whether a preoperative biochemical bone parameter can be predictive of a significant vertebral bone mass increase in patients with pHPT. Methods: For each patient we analyzed the following preoperative parameters: parathyroid hormone, urinary calcium excretion, urinary type I collagen cross-linked N-telopeptide (NTX), osteocalcin, and vertebral computerized bone mineralography. All patients underwent vertebral computerized bone mineralography 12 months after the operation. Statistical analysis was carried out by a neural network program, an event-predicting software modeled on human brain neuronal connections, which is able to examine independent statistical parameters. Results: The patients presenting with high preoperative bone turnover (especially high NTX levels) will have a 5% vertebral bone mass gain in 83.33% of cases after surgery, independently of the National Institutes of Health guidelines. Conclusions: A high preoperative NTX level seems to be the best predictor parameter for postoperative vertebral bone mass gain in patients with pHPT. Our study also illustrates that neural network software may be a valuable method to help elucidate which pHPT patients should undergo surgical treatmen

Classification of pseudohypoparathyroidism and differential diagnosis

Pseudohypoparathyroidism (PHP) exemplifies a quite unusual form of hormone resistance as the underlying molecular defect is a partial deficiency of the \u3b1 subunit of the stimulatory G protein (Gs\u3b1), a key regulator of cAMP signaling pathway, rather than the hormone receptor itself. PHP, together with Albright hereditary osteodystrophy (AHO), is a rare disorder encompassing heterogeneous features, such as brachydactyly, ectopic ossifications, short stature, mental retardation, and endocrine deficiencies due to resistance to the action of different hormones, primarily PTH. The two main subtypes of PHP are caused by mutations and/or methylation defects within the imprinted GNAS cluster, whose main transcript is Gs\u3b1. Moreover, mutations in the PRKAR1A and PDE4D genes, both crucial as GNAS for cAMP-mediated signaling, have been demonstrated in patients with acrodysostosis, a disease of bone formation with characteristics similar to AHO, while small deletions of chromosome 2 may also lead to the AHO phenotype. The clinical and molecular overlap among these different but related disorders represents a challenge for endocrinologists as to differential diagnosis and genetic counselin