Late-onset isolated cystic hygroma: The obstetrical significance,management, and outcome

We add two cases of prenatally diagnosed late-onset isolated cystic hygroma to the eight cases reported previously in the English literature. The obstetrical significance, management, and outcome of this entity are reviewed. A retrospective study of late-onset isolated cystic hygromas delivered in one medical centre between 1978 and 1992 was made. The medical records of these newborns served as the basis of the present report. A Medline search of the English literature was carried out. Over a period of 15 years, we observed 11 cases of late-onset congenital isolated cystic hygroma, two of whom had prenatal sonographic diagnosis. In one case, a Caesarean section was performed due to a huge lesion. All cases underwent surgical excision with a favourable outcome. Of the eight prenatally diagnosed cases reported previously, one died at birth due to inability to ventilate and two required a tracheostomy. Late-onset isolated cystic hygroma should be differentiated from the early-onset nuchal cystic hygroma. The differential diagnosis is important, as late-onset isolated cystic hygroma does not require any prenatal intervention, but special awareness during labour and Caesarean section in extreme cases. Transport to a perinatal centre with expert neonatal, respiratory, and paediatric surgical care is recommended. The prognosis in general is favourable.     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

Natural nutraceuticals for enhancing yogurt properties: a review

Environmental Chemistry Letters - Yogurt is a major fermented milk product providing probiotics, lactic acid bacteria, vitamins, calcium, and proteins, yet health-beneficial phenolics, flavonoids,...     

Methods to prepare biosorbents and magnetic sorbents for water treatment: a review

Access to drinkable water is becoming more and more challenging due to worldwide pollution and the cost of water treatments. Water and wastewater treatment by adsorption on solid materials is usually cheap and effective in removing contaminants, yet classical adsorbents are not sustainable because they are derived from fossil fuels, and they can induce secondary pollution. Therefore, biological sorbents made of modern biomass are increasingly studied as promising alternatives. Indeed, such biosorbents utilize biological waste that would otherwise pollute water systems, and they promote the circular economy. Here we review biosorbents, magnetic sorbents, and other cost-effective sorbents with emphasis on preparation methods, adsorbents types, adsorption mechanisms, and regeneration of spent adsorbents. Biosorbents are prepared from a wide range of materials, including wood, bacteria, algae, herbaceous materials, agricultural waste, and animal waste. Commonly removed contaminants comprise dyes, heavy metals, radionuclides, pharmaceuticals, and personal care products. Preparation methods include coprecipitation, thermal decomposition, microwave irradiation, chemical reduction, micro-emulsion, and arc discharge. Adsorbents can be classified into activated carbon, biochar, lignocellulosic waste, clays, zeolites, peat, and humic soils. We detail adsorption isotherms and kinetics. Regeneration methods comprise thermal and chemical regeneration and supercritical fluid desorption. We also discuss exhausted adsorbent management and disposal. We found that agro-waste biosorbents can remove up to 68–100% of dyes, while wooden, herbaceous, bacterial, and marine-based biosorbents can remove up to 55–99% of heavy metals. Animal waste-based biosorbents can remove 1–99% of heavy metals. The average removal efficiency of modified biosorbents is around 90–95%, but some treatments, such as cross-linked beads, may negatively affect their efficiency.

     

Biofuel production,hydrogen production and water remediation by photocatalysis,biocatalysis and electrocatalysis

The energy crisis and environmental pollution have recently fostered research on efficient methods such as environmental catalysis to produce biofuel and to clean water. Environmental catalysis refers to green catalysts used to breakdown pollutants or produce chemicals without generating undesirable by-products. For example, catalysts derived from waste or inexpensive materials are promising for the circular economy. Here we review environmental photocatalysis, biocatalysis, and electrocatalysis, with focus on catalyst synthesis, structure, and applications. Common catalysts include biomass-derived materials, metal–organic frameworks, non-noble metals nanoparticles, nanocomposites and enzymes. Structure characterization is done by Brunauer–Emmett–Teller isotherm, thermogravimetry, X-ray diffraction and photoelectron spectroscopy. We found that water pollutants can be degraded with an efficiency ranging from 71.7 to 100%, notably by heterogeneous Fenton catalysis. Photocatalysis produced dihydrogen (H₂) with generation rate higher than 100 μmol h⁻¹. Dihydrogen yields ranged from 27 to 88% by methane cracking. Biodiesel production reached 48.6 to 99%.

     

Solar photo-oxidation of recalcitrant industrial wastewater: a review

Conventional methods to clean wastewater actually lead to incomplete treatments, calling for advanced technologies to degrade recalcitrant pollutants. Herein we review solar photo-oxidation to degrade the recalcitrant contaminants in industrial wastewater, with focus on photocatalysts, reactor design and the photo-Fenton process. We discuss limitations due to low visible-light absorption, catalyst collection and reusability, and production of toxic by-products. Photodegradation of refractory organics by solar light is controlled by pH, photocatalyst composition and bandgap, pollutant properties and concentration, irradiation type and intensity, catalyst loading, and the water matrix.

     

Advanced physico-chemical treatment experiences on young municipal landfill leachates

In this study, Membrane Filtration (UF+RO), Struvite (MAP) precipitation and ammonia stripping alternatives were studied on biologically pre-treated Landfill Leachate. The results indicated that the system including the Upflow Anaerobic Sludge Blanket Reactor (UASBR) and Membrane Reactors (UF+RO) has been offered as an appropriate treatment alternative for young landfill leachates. This system provided high removals of COD, colour and conductivity (>98-99%). For ammonia removal, struvite precipitation was applied at the stoichiometric ratio (Mg:NH4:PO4=1:1:1) to anaerobically pre-treated raw landfill leachate effluent having an influent ammonium concentration of 2240 mg/l. Maximum ammonium nitrogen removal was observed as 85% at pH of 9.2. In ammonia stripping following 2 h of aeration, the removal was 72% at pH=12 while the removals were around 20% at pH=10 and pH=11. When membrane reactor, and struvite precipitation or ammonia stripping was applied to anaerobically pre-treated effluents, the results indicated that each system could be used as an appropriate post-treatment option for young landfill leachates. In economic aspect, ammonia stripping was found as the cheapest alternative with high ammonium removal. However, when both high COD and ammonium removals were to be achieved membrane technology such as UF+RO (SW) could be considered as the most appropriate system due to the fact that COD removal could be obtained very low by ammonia stripping.     

Stronger predation in the tropics shapes species richness patterns in marine communities

Species interactions are widely assumed to be stronger at lower latitudes, but surprisingly few experimental studies test this hypothesis, and none ties these processes to observed patterns of species richness across latitude. We report here the first experimental field test that predation is both stronger and has a disproportionate effect on species richness in the tropics relative to the temperate zone. We conducted predator-exclusion experiments on communities of sessile marine invertebrates in four regions, which span 32 degrees latitude, in the western Atlantic Ocean and Caribbean Sea. Over a three-month timescale, predation had no effect on species richness in the temperate zone. In the tropics, however, communities were from two to over ten times more species-rich in the absence of predators than when predators were present. While micro-and macro-predators likely compete for the limited prey resource in the tropics, micropredators alone were able to exert as much pressure on the invertebrate communities as the full predator community. This result highlights the extent to which exposure to even a subset of the predator guild can significantly impact species richness in the tropics. Patterns were consistent in analyses that included relative and total species abundances. Higher species richness in the absence of predators in the tropics was also observed when species occurrences were pooled across two larger spatial scales, site and region, demonstrating a consistent scaling relationship. These experimental results show that predation can both limit local species abundances and shape patterns of regional coexistence in the tropics. When preestablished diverse tropical communities were then exposed to predation for different durations, ranging from one to several days, species richness was always reduced. These findings confirmed that impacts of predation in the tropics are strong and consistent, even in more established communities. Our results offer empirical support for the long-held prediction that predation pressure is stronger at lower latitudes. Furthermore, we demonstrate the magnitude to which variation in predation pressure can contribute to the maintenance of tropical species diversity.