In-situ fluorescence spectroscopy indicates total bacterial abundance and dissolved organic carbon

We explore in-situ fluorescence spectroscopy as an instantaneous indicator of total bacterial abundance and faecal contamination in drinking water. Eighty-four samples were collected outside of the recharge season from groundwater-derived water sources in Dakar, Senegal. Samples were analysed for tryptophan-like (TLF) and humic-like (HLF) fluorescence in-situ, total bacterial cells by flow cytometry, and potential indicators of faecal contamination such as thermotolerant coliforms (TTCs), nitrate, and in a subset of 22 samples, dissolved organic carbon (DOC). Significant single-predictor linear regression models demonstrated that total bacterial cells were the most effective predictor of TLF, followed by on-site sanitation density; TTCs were not a significant predictor. An optimum multiple-predictor model of TLF incorporated total bacterial cells, nitrate, nitrite, on-site sanitation density, and sulphate (r2 0.68). HLF was similarly related to the same parameters as TLF, with total bacterial cells being the best correlated (ρs 0.64). In the subset of 22 sources, DOC clustered with TLF, HLF, and total bacterial cells, and a linear regression model demonstrated HLF was the best predictor of DOC (r2 0.84). The intergranular nature of the aquifer, timing of the study, and/or non-uniqueness of the signal to TTCs can explain the significant associations between TLF/HLF and indicators of faecal contamination such as on-site sanitation density and nutrients but not TTCs. The bacterial population that relates to TLF/HLF is likely to be a subsurface community that develops in-situ based on the availability of organic matter originating from faecal sources. In-situ fluorescence spectroscopy instantly indicates a drinking water source is impacted by faecal contamination but it remains unclear how that relates specifically to microbial risk in this setting

Non-alcoholic beverages and risk of bladder cancer in Uruguay

BACKGROUND: Bladder cancer is the fourth most frequent malignancy among Uruguayan men. A previous study from Uruguay suggested a high risk of bladder cancer associated with maté drinking. We conducted an additional case-control study in order to further explore the role of non-alcoholic beverages in bladder carcinogenesis. METHODS: In the time period 1996–2000, 255 incident cases with transitional cell carcinoma of the bladder and 501 patients treated in the same hospitals and in the same time period were frequency matched on age, sex, and residence. Both cases and controls were face-to-face interviewed on occupation, tobacco smoking, alcohol drinking and intake of maté, coffee, tea, and soft drinks. Statistical analysis was carried out by unconditional multiple logistic regression. RESULTS: Ever maté drinking was positively associated with bladder cancer (odds ratio [OR] 2.2, 95% confidence interval [CI] 1.2–3.9) and the risk increased for increasing duration and amount of maté drinking. Both coffee and tea were strongly associated with bladder cancer risk (OR for coffee drinking 1.6, 95% CI 1.2–2.3; OR for tea drinking 2.3, 95% CI 1.5–3.4). These results were confirmed in a separate analysis of never-smokers. CONCLUSION: Our results suggest that drinking of maté, coffee and tea may be risk factors for bladder carcinoma in Uruguay

Exploring and Implementing Agricultural Opportunities in Monwabisi Park, South Africa

The mission of the Gardens Team was to collaborate with the residents of Monwabisi Park to research and implement sustainable agricultural systems that could provide nutritional and aesthetic benefits. The team planted gardens and created educational materials to develop the community's agricultural capabilities. We proposed composting procedures that will be utilized in the Indlovu Water and Sanitation Facility. Through our achievements, we hope to provide a sustainable gardening plan and a base for future teams to build upon

Depression Speaks: Automatic Discrimination between Depressed and Non-Depressed Speakers Based on Nonverbal Speech Features

This article proposes an automatic approach-based on nonverbal speech features-aimed at the automatic discrimination between depressed and non-depressed speakers. The experiments have been performed over one of the largest corpora collected for such a task in the literature (62 patients diagnosed with depression and 54 healthy control subjects), especially when it comes to data where the depressed speakers have been diagnosed as such by professional psychiatrists. The results show that the discrimination can be performed with an accuracy of over 75% and the error analysis shows that the chances of correct classification do not change according to gender, depression-related pathology diagnosed by the psychiatrists or length of the pharmacological treatment (if any). Furthermore, for every depressed subject, the corpus includes a control subject that matches age, education level and gender. This ensures that the approach actually discriminates between depressed and non depressed speakers and does not simply capture differences resulting from other factors