RESUMO
River systems in developing and emerging countries are often fragmented relative to land and waste management in their catchment. The impact of inconsistent waste management and releases is a major challenge in water quality management. To examine how anthropogenic activities and estuarine effects impact water quality, we characterised water conditions, in-situ microbiomes, profiles of faecal pollution indicator, pathogenic and antibiotic resistant bacteria in the River Melayu, Southern Malaysia. Overall, upstream sampling locations were distinguished from those closer to the coastline by physicochemical parameters and bacterial communities. The abundances of bacterial DNA, total E. coli marker genes, culturable bacteria as well as antibiotic resistance ESBL-producing bacteria were elevated at upstream sampling locations especially near discharge of a wastewater oxidation pond. Furthermore, 85.7% of E. faecalis was multidrug-resistant (MDR), whereas 100% of E. cloacae, E. coli, K. pneumoniae were MDR. Overall, this work demonstrates how pollution in river estuaries does not monotonically change from inland towards the coast but varies according to local waste releases and tidal mixing. We also show that surrogate markers, such dissolved oxygen, Bacteroides and Prevotella abundances, and the rodA qPCR assay for total E. coli, can identify locations on a river that deserve immediate attention to mitigate AMR spread through improved waste management.
Assuntos
Microbiota , Gerenciamento de Resíduos , Antibacterianos/análise , Antibacterianos/farmacologia , Bactérias/genética , Escherichia coli , Estuários , Rios , Águas ResiduáriasRESUMO
Parkinson's disease (PD) is a chronic neurodegenerative disease with complex motor and non-motor symptoms often leading to significant caregiver burden. An integrated, multidisciplinary care setup involving different healthcare professionals is the mainstay in the holistic management of PD. Many challenges in delivering multidisciplinary team (MDT) care exist, such as insufficient expertise among different healthcare professionals, poor interdisciplinary collaboration, and communication. The need to attend different clinics, incurring additional traveling and waiting time for allied health therapies can also make MDT care more burdensome. By shifting MDT care to local community settings and into patients' homes, patient-centered care can be achieved. In Singapore, the National Neuroscience Institute created the Community Care Partners Programme in 2007 to bring the allied MDT team to the community and nurse-led Integrated Community Care Programme for Parkinson's Disease in 2012 to provide care in community and at patient's home. However, attaining MDT care in the community setting is difficult to achieve where there is a shortage of PD-trained professionals. As such, interdisciplinary and transdisciplinary management would be other best practice options to deliver patient-centric care in PD. Telemedicine could be another viable option to bring the MDT closer to the patient.
RESUMO
PURPOSE: Left ventricular assist devices (LVAD) are associated with an increased aerobic capacity in patients with chronic heart failure (CHF). However, studies evaluating the impact of LVAD implantation on physical activity (PA) are lacking. The aim of this study was to compare daily PA levels in participants with LVAD with well-matched CHF participants. METHODS: Sixteen participants with an LVAD (age, 59.1 ± 10.8 yr) were case-matched to 16 participants with advanced CHF (age, 58.3 ± 8.7 yr), who were listed or being considered for cardiac transplantation. Participants underwent a cardiopulmonary exercise test to determine peak oxygen consumption (VËO2 peak). Physical activity was monitored continuously for seven consecutive days with an Actiheart monitor. RESULTS: VËO2 peak in the CHF group (12.3 ± 3.5 mL·kg·min) was not significantly different to the LVAD group before LVAD implantation (10.4 ± 2.1 mL·kg·min), but was lower than in the LVAD group after implantation (15.8 ± 4.3 mL·kg·min; P < 0.05). Physical activity was higher in the LVAD (19.7 ± 6.4 kJ·kg·d) compared with the CHF group (11.6 ± 6.9 kJ·kg·d; P = 0.001). The LVAD participants spent more time performing moderate-intensity PA than their CHF counterparts (median, 26 min·d; interquartile range, 24-40 min·d vs median, 12 min·d; interquartile range, 9-16 min·d; P < 0.001). Physical activity was correlated with VËO2 peak (r = 0.582; P = 0.001) across participants in the CHF and LVAD groups. CONCLUSIONS: Higher levels of PA were observed in participants with LVAD compared with patients with advanced CHF. This may be due to a higher VËO2 peak, resulting in an improved capacity to perform activities of daily living with less symptoms.
Assuntos
Tolerância ao Exercício , Insuficiência Cardíaca/fisiopatologia , Insuficiência Cardíaca/terapia , Coração Auxiliar , Atividades Cotidianas , Idoso , Estudos de Casos e Controles , Teste de Esforço , Feminino , Insuficiência Cardíaca/psicologia , Humanos , Masculino , Pessoa de Meia-Idade , Consumo de Oxigênio/fisiologia , Qualidade de Vida , AutoeficáciaRESUMO
BACKGROUND: Deviation in gait performance from normative data of healthy cohorts is used to quantify gait ability. However, normative data is influenced by anthropometry and such differences among subjects impede accurate assessment. De-correlation of anthropometry from gait parameters and mobility measures is therefore desirable. METHODS: 87 (42 male) healthy subjects varying form 21 to 84 years of age were assessed on gait parameters (cadence, ankle velocity, stride time, stride length) and mobility measures (the 3-meter/7-meter Timed Up-and-Go, 10-meter Walk Test). Multiple linear regression models were derived for each gait parameter and mobility measure, with anthropometric measurements (age, height, body mass, gender) and self-selected walking speed as independent variables. The resulting models were used to normalize the gait parameters and mobility measures. The normalization's capability in de-correlating data and reducing data dispersion were evaluated. RESULTS: Gait parameters were predominantly influenced by height and walking speed, while mobility measures were affected by age and walking speed. Normalization de-correlated data from anthropometric measurements from |rs| < 0.74 to |rs| < 0.23, and reduced data dispersion by up to 69%. CONCLUSION: Normalization of gait parameters and mobility measures through linear regression models augment the capability to compare subjects with varying anthropometric measurements.