Cobbjain5012

The Latin American Federation of Endocrinology position statement on osteoporosis was developed by endocrinologists from 9 countries. It encompasses the definition, diagnosis, treatment, and follow-up of the disease, the identification of barriers to healthcare, and proposals to improve the disease care in the region.

There is a gap in the understanding of osteoporosis in Latin America. The objective of this work is to state the position of the Latin American Federation of Endocrinology on osteoporosis care in postmenopausal women to better bridge this gap.

An experts' panel was formed comprising of 11 endocrinologists from 9 countries. A data search was conducted with a conceptual approach and data selection was based on the hierarchy of the EBHC pyramid. Unpublished data was considered for local epidemiological data and expert opinion for the identification of barriers to healthcare. An expert consensus based on the Delphi methodology was carried out. Experts were asked to respond on a 5-point Likert Scad to identify knowledge gaps. There is great variability in the approach to osteoporosis in Latin America and barriers in all the stages of healthcare persist.COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly and affected most of the world since its outbreak in Wuhan, China, which presents a major challenge to the emergency response mechanism for sudden public health events and epidemic prevention and control in all countries. In the face of the severe situation of epidemic prevention and control and the arduous task of social management, the tremendous power of science and technology in prevention and control has emerged. The new generation of information technology, represented by big data and artificial intelligence (AI) technology, has been widely used in the prevention, diagnosis, treatment and management of COVID-19 as an important basic support. Although the technology has developed, there are still challenges with respect to epidemic surveillance, accurate prevention and control, effective diagnosis and treatment, and timely judgement. The prevention and control of sudden infectious diseases usually depend on t repeatability and universality, current studies in China have shown that the application of big data and AI is feasible in response to the COVID-19 pandemic. These studies concluded that the application of big data and AI technology can contribute to prevention, diagnosis, treatment and management decision making regarding sudden public health events in the future.The present analysis deals with the ability of Thermomyces lanuginosus to degrade pre-treated low-density polyethylene (LDPE). The synergistic effect of UV irradiation, heat, and acid pre-treatments on the biodegradability of the polymer was thoroughly assessed. Oxidative structural modifications such as the appearance of carboxylate and carbonyl groups in LDPE chains were recorded post the UV and heat treatments. Furthermore, the nitric acid treatment incorporated NO2 groups into the polymer matrix. Alterations in the polymer thermal stabilities and surface morphologies after each pre-treatment were analyzed using thermogravimetric analysis and scanning electron microscopy (SEM), respectively. The gravimetric analysis revealed a reduction in the weight of the pre-treated LDPE films by 9.21 ± 0.84% after 1 month of the incubation period with Thermomyces lanuginosus. An increase in the thermal stability, disappearance of the incorporated hydrophilic functional groups, and reduction in the carbon content of the polymer samples post the incubation period further justified the biodegradation process. SEM analysis showed modifications in the morphology and texture patterns in pre-treated LDPE after inoculation with Thermomyces lanuginosus. The findings suggest that Thermomyces lanuginosus could be efficient for the decomposition of pre-treated LDPE under laboratory conditions.

To assess the prevalence and severity of clinically significant symptoms (CSSs) for breast cancer, colon cancer, and leukemia patients undergoing chemotherapy.

A retrospective review of the Edmonton Symptom Assessment System scores reported by patients from the database ofour previous large-scale study, which was collected between May 2018 and January 2019. We described the prevalence of CSSs in proportion and severity in mean ± SD.

Of 546 cancer patients, 209 were breast cancer, 159 were colon cancer, and 178 were leukemia. The majority of participants were females 345 (63.2%), and the mean age of the entire study sample was 49.4 ± 13.93. Diminished feeling of well-being was the most prevalent CSS across the three cancers, with a statistically significant difference (p < 0.001). Fatigue (6.59 ± 2.07), pain (6.55 ± 2.01), and loss of appetite were the most distressing CSSs (6.49 ± 1.99) across the whole sample. Loss of appetite (6.34 ± 2.05) was the most distressing CSS in breast cancer, fatigue (6.9patients undergoing chemotherapy.

Few mortality-scoring models are available for solid tumor patients who are predisposed to develop Escherichia coli-caused bloodstream infection (ECBSI). We aimed to develop a mortality-scoring model by using information from blood culture time to positivity (TTP) and other clinical variables.

A cohort of solid tumor patients who were admitted to hospital with ECBSI and received empirical antimicrobial therapy was enrolled. Survivors and non-survivors were compared to identify the risk factors of in-hospital mortality. Univariable and multivariable regression analyses were adopted to identify the mortality-associated predictors. Bicuculline mouse Risk scores were assigned by weighting the regression coefficients with corresponding natural logarithm of the odds ratio for each predictor.

Solid tumor patients with ECBSI were distributed in the development and validation groups, respectively. Six mortality-associated predictors were identified and included in the scoring model acute respiratory distress (ARDS), TTP ≤ 8h, inascoring model was associated with improving capability in predicting ECBSI-related mortality. It can be a practical tool for clinicians to identify and manage bacteremic solid tumor patients with high risk of mortality.