Cystoscopic removal of an intravesical gossypiboma mimicking a bladder mass: a case report

<p>Abstract</p> <p>Background</p> <p>Intravesical retained surgical sponges are very rare and only a few cases have been removed by minimally invasive techniques.</p> <p>Case presentation</p> <p>We report a case of an intravesical gossypiboma in a 71-year-old man from western Nepal, who presented with urinary retention and persistent lower urinary tract symptoms one year after open cystolithotomy. He was diagnosed with an intravesical mass using ultrasonography. The retained surgical sponge was found during cystoscopy and removed through endoscopy.</p> <p>Conclusion</p> <p>Intravesical gossypibomas are rare and can mimic a bladder mass. This is one of the few reported cases of cystoscopic removal.</p

Lessons from cholera response in Kathmandu Valley, Nepal

The first recorded cholera epidemic in Nepal took place in 1823, followed by a series of epidemics occurring in the Kathmandu Valley in 1831, 1843, 1856, 1862 and 1887. Kathmandu Valley still witnesses cholera and other water borne disease cases almost every year. In 2015 and 2016, cholera cases for the valley was highest with 76 and 150 confirmed cases respectively along is with huge caseload on Acute Watery Diarrhoea (AWD). WASH Situation of the Valley especially of City Centres comes with lots of challenges owing to the complexities of urban set-up and thus the city centres are the potential hotspots in context to outbreak vulnerabilities. Based on lesson learned in 2016 cholera response, this paper presents a way forward for minimizing the occurrence of cholera and AWD which includes developing a system for cholera prevention and outbreak response

Health and lifestyle of Nepalese migrants in the UK

Background: The health status and lifestyle of migrants is often poorer than that of the general population of their host countries. The Nepalese represent a relatively small, but growing, immigrant community in the UK, about whom very little is known in term of public health. Therefore, our study examined the health and lifestyle of Nepalese migrants in the UK. Methods: A cross-sectional survey of Nepalese migrants in UK was conducted in early 2007 using a postal, self-administered questionnaire in England and Scotland (n = 312), and telephone interviews in Wales (n = 15). The total response rate was 68% (327 out of 480). Data were analyzed to establish whether there are associations between socio-economic and lifestyle factors. A multivariate binary logistic regression was applied to find out independent effect of personal factors on health status. Results: The majority of respondents was male (75%), aged between 30 and 45 (66%), married or had a civil partner (83%), had university education (47%) and an annual family income (69%) ranging from £5,035 to £33,300. More than one third (39%) of the respondents have lived in the UK for 1 to 5 years and approximately half (46%) were longer-term residents. Most (95%) were registered with a family doctor, but only 38% with a dentist. A low proportion (14%) of respondents smoked but more than half (61%) consumed alcohol. More than half (57%) did not do regular exercises and nearly one fourth (23%) of respondents rated their health as poor. Self reported 'good' health status of the respondents was independently associated with immigration status and doing regular exercise Conclusion: The self reported health status and lifestyle, health seeking behaviour of Nepalese people who are residing in UK appears to be good. However, the overall regular exercise and dentist registration was rather poor. Health promotion, especially aimed at Nepalese migrants could help encourage them to exercise regularly and assist them to register with a dentist

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

Recession-based hydrological models for estimating low flows in ungauged catchments in the Himalayas

International audienceThe Himalayan region of Nepal and northern India experiences hydrological extremes from monsoonal floods during July to September, when most of the annual precipitation falls, to periods of very low flows during the dry season (December to February). While the monsoon floods cause acute disasters such as loss of human life and property, mudslides and infrastructure damage, the lack of water during the dry season has a chronic impact on the lives of local people. The management of water resources in the region is hampered by relatively sparse hydrometerological networks and consequently, many resource assessments are required in catchments where no measurements exist. A hydrological model for estimating dry season flows in ungauged catchments, based on recession curve behaviour, has been developed to address this problem. Observed flows were fitted to a second order storage model to enable average annual recession behaviour to be examined. Regionalised models were developed, using a calibration set of 26 catchments, to predict three recession curve parameters: the storage constant; the initial recession flow and the start date of the recession. Relationships were identified between: the storage constant and catchment area; the initial recession flow and elevation (acting as a surrogate for rainfall); and the start date of the recession and geographic location. An independent set of 13 catchments was used to evaluate the robustness of the models. The regional models predicted the average volume of water in an annual recession period (1st of October to the 1st of February) with an average error of 8%, while mid-January flows were predicted to within ±50% for 79% of the catchments in the data set. Keywords: Himalaya, recession curve, water resources, ungauged catchment, regionalisation, low flow

Local resection of gastrointestinal stromal tumor of the second part of duodenum

Gastrointestinal stromal tumors are relatively rare in the duodenum, representing 2-4% of Gastrointestinal stromal tumors of the gastrointestinal tract. We describe a huge Gastrointestinal stromal tumor arising from the second part of the duodenum invading the transverse colon which was removed successfully by local resection of the second part of the duodenum along with a segment of transverse colon. Keywords: duodenum, gastrointestinal stromal tumor, segmental resectio

Recession-based hydrological models for estimating low flows in ungauged catchments in the Himalayas

The Himalayan region of Nepal and northern India experiences hydrological extremes from monsoonal floods during July to September, when most of the annual precipitation falls, to periods of very low flows during the dry season (December to February). While the monsoon floods cause acute disasters such as loss of human life and property, mudslides and infrastructure damage, the lack of water during the dry season has a chronic impact on the lives of local people. The management of water resources in the region is hampered by relatively sparse hydrometerological networks and consequently, many resource assessments are required in catchments where no measurements exist. A hydrological model for estimating dry season flows in ungauged catchments, based on recession curve behaviour, has been developed to address this problem. Observed flows were fitted to a second order storage model to enable average annual recession behaviour to be examined. Regionalised models were developed, using a calibration set of 26 catchments, to predict three recession curve parameters: the storage constant; the initial recession flow and the start date of the recession. Relationships were identified between: the storage constant and catchment area; the initial recession flow and elevation (acting as a surrogate for rainfall); and the start date of the recession and geographic location. An independent set of 13 catchments was used to evaluate the robustness of the models. The regional models predicted the average volume of water in an annual recession period (1st of October to the 1st of February) with an average error of 8%, while mid-January flows were predicted to within ±50% for 79% of the catchments in the data set. Keywords: Himalaya, recession curve, water resources, ungauged catchment, regionalisation, low flow