Secular trends in blood lead concentrations of school-age children in Montevideo, Uruguay from 2009 to 2019.

Lead exposure continues to be a public health problem globally, yet very few countries perform systematic biomonitoring or surveillance of children's blood lead levels (BLLs). Secular trends in children's BLLs have not been well characterized outside North America and Europe. In 2009-19, we conducted a series of non-representative cross-sectional surveys in Montevideo, Uruguay, enrolling children living in areas of the city with known or suspected lead contamination. Lead was measured with atomic absorption spectrometry on fasting venous blood samples. Of the 856 children representing independent (non-sibling) observations, 759 had BLL measures. Other missing data were imputed. Using linear and logistic regression models, we estimated the covariate-adjusted year to year difference in mean BLL and the likelihood of having BLL ≥5 and BLL ≥3.5 µg/dL. At the start of the study, mean ± SD BLL was 4.8 ± 2.6 µg/dL, and at the end 1.4 ± 1.4 µg/dL. The prevalence of BLL ≥5 and BLL ≥3.5 µg/dL also differed markedly between 2009 and 2019 (30.8% vs. 2.7% and 53.8% vs. 5.8%). Similarly, where 80.8% of children had BLL ≥2 µg/dL in 2011, in 2019 that number was 19.3%. The estimated year to year difference in BLL was ∼0.3 µg/dL. Despite this progress, pediatric lead exposure remains a problem in Montevideo. In years 2015-19, between 19 and 48% of school children had BLL ≥2 µg/dL, a level at which adverse neurobehavioral outcomes continue to be reported in the literature. Continued prevention and risk-reduction efforts are needed in Montevideo, including systematic surveillance of BLLs in all children.

Reducing the complexity of high-dimensional environmental data: An analytical framework using LASSO with considerations of confounding for statistical inference.

PURPOSE: Frameworks for selecting exposures in high-dimensional environmental datasets, while considering confounding, are lacking. We present a two-step approach for exposure selection with subsequent confounder adjustment for statistical inference. METHODS: We measured cognitive ability in 338 children using the Woodcock-Muñoz General Intellectual Ability (GIA) score, and potential associated features across several environmental domains. Initially, 111 variables theoretically associated with GIA score were introduced into a Least Absolute Shrinkage and Selection Operator (LASSO) in a 50% feature selection subsample. Effect estimates for selected features were subsequently modeled in linear regressions in a 50% inference (hold out) subsample, first adjusting for sex and age and later for covariates selected via directed acyclic graphs (DAGs). All models were adjusted for clustering by school. RESULTS: Of the 15 LASSO selected variables, eleven were not associated with GIA score following our inference modeling approach. Four variables were associated with GIA scores, including: serum ferritin adjusted for inflammation (inversely), mother's IQ (positively), father's education (positively), and hours per day the child works on homework (positively). Serum ferritin was not in the expected direction. CONCLUSIONS: Our two-step approach moves high-dimensional feature selection a step further by incorporating DAG-based confounder adjustment for statistical inference.

Small Bowel Injury During Peritoneal Entry at Cesarean Section: A Five-Year Case Series.

Introduction Small bowel injury during peritoneal entry may occur unexpectedly at cesarean section (CS) and may present unexpected management problems and prolonged postoperative hospital stay. Methods This was an observational study of patients who sustained inadvertent injuries compared to those who did not. Both study and control patients had the same number of previous cesarean sections. Findings In this study population, the frequency of small bowel injury during peritoneal entry was 0.0003/10,000 cesarean sections. The majority comprised serosal trauma (7/10) and tended to occur in females who had had two or more CS. Compared to patients with a similar number of previous cesarean sections, patients who sustained small bowel injuries in the index cesarean section were twice as likely to have had adhesiolysis of flimsy or dense lesions in the immediate preceding procedure. Conclusion Bowel injury during peritoneal entry at cesarean section is rare but may be frequently encountered in maternity units with high-volume CS rates.

Does land use change, waterlogging, and salinity impact on sustainability of agriculture and food security? Evidence from southwestern coastal region of Bangladesh.

The United Nation's sustainable development goal is to achieve zero hunger by 2030 and achieve food security throughout the world. In this context, we analyze the anthropogenic factors such as land use and land cover change, waterlogging, and soil salinity which combinedly affecting the agricultural sustainability and threatening the food security in the southwestern region of Bangladesh. Landsat satellite images from 1991 to 2021 were used to detect the changes and identify how anthropogenic activities have altered the land cover and land use and impede the sustainability of agriculture. Terra MODIS vegetation indices from 2000 to 2020 were used to detect waterlogging. Soil salinity was measured from the soil samples and vegetation soil salinity index (VSSI) from Landsat images. Findings of the study revealed that agricultural lands have decreased because of an increase in shrimp farming. Waterlogging and soil salinity are increasing due to increased shrimp farms also for poor drainage infrastructure and human modification. The area of agricultural land in 2011 was 19,657.12 acres,12,750.14 acres, and 38,774.70 acres in Keshabpur, Abhaynagar, and Manirampur, which changed to 12,668.70 acres (-36%), 7151.27 acres (-44%), and 32,809.30 acres (-16%) in 2021. Our hotspot analysis reveals that very high vulnerability to waterlogging due to floods was highest in Manirampur (15,464.09 acres). Finally, we proposed a new framework called IDCEM designed for monitoring land-use change, salinity, and waterlogging in the interior coast, which will indirectly help to promote food security and help in achieving sustainable development goal.

Do Neighborhood Factors Modify the Effects of Lead Exposure on Child Behavior?

Lead exposure and neighborhoods can affect children's behavior, but it is unclear if neighborhood characteristics modify the effects of lead on behavior. Understanding these modifications has important intervention implications. Blood lead levels (BLLs) in children (~7 years) from Montevideo, Uruguay, were categorized at 2 µg/dL. Teachers completed two behavior rating scales (n = 455). At one-year follow-up (n = 380), caregivers reported child tantrums and parenting conflicts. Multilevel generalized linear models tested associations between BLLs and behavior, with neighborhood disadvantage, normalized difference vegetation index (NDVI), and distance to nearest greenspace as effect modifiers. No effect modification was noted for neighborhood disadvantage or NDVI. Children living nearest to greenspace with BLLs < 2 µg/dL were lower on behavior problem scales compared to children with BLLs ≥ 2 µg/dL. When furthest from greenspace, children were similar on behavior problems regardless of BLL. The probability of daily tantrums and conflicts was ~20% among children with BLLs < 2 µg/dL compared to ~45% among children with BLLs ≥ 2 µg/dL when closest to greenspace. Furthest from greenspace, BLLs were not associated with tantrums and conflicts. Effect modification of BLL on child behavior by distance to greenspace suggests that interventions should consider both greenspace access and lead exposure prevention.

Fixed Dose Combination Tablets of Aripiprazole and Divalproex Sodium: a Pilot Pharmacokinetic Study in Human Volunteers.

A combination product of aripiprazole (antipsychotic) and divalproex sodium (mood stabilizer) was recently developed to establish their tolerability and safety in fixed dose combination (FDC). A pilot pharmacokinetic (PK) open-labeled parallel study on healthy human volunteers was carried out to assess the PK of FDC of aripiprazole/divalproex sodium in comparison with its individual components with a view to rationalize therapeutic regimen and potentially improve compliance of bipolar patients in future. A total of 24 volunteers were randomized to aripiprazole 5mg, divalproex sodium 500mg, and FDC (aripiprazole/divalproex sodium 5/500 mg) enteric-coated tablets. Peak plasma concentration (Cmax) and time to reach peak plasma concentration (Tmax) of aripiprazole increased, Cmax of valproic acid increased, and Tmax decreased. Half-life (t1/2) of both aripiprazole and valproic acid decreased. Area under the curve (AUC) of both aripiprazole and valproic acid increased while volume of distribution (Vd) and clearance (Cl) decreased when used in fixed combination. Increase in the AUC and decrease in the Vd of aripiprazole in the presence of valproic acid were found statistically significant while rest of the parameters were insignificant at level 0.05. Although not adequately powered, this pilot study gives an idea that FDC of aripiprazole and divalproex sodium has a PK profile comparable to its mono-component products. Thus, concomitant use of aripiprazole and valproate in FDC is possible which may prove to be a cost-effective and result-oriented substitute for conventional individual tablets to improve patients' compliance; however, further evaluation with positive control is required.

Does anthropogenic upstream water withdrawal impact on downstream land use and livelihood changes of Teesta transboundary river basin in Bangladesh?

This article evaluates the impact of upstream water withdrawal on downstream land use and livelihood changes in the Teesta River basin, using a combination of geospatial and social data. Results show that water bodies gradually decreased, indicating a low volume of water discharge from upstream of the Teesta River basin due to the construction of several barrages. During the study period, a significant change in the area of water bodies was observed between 2012 and 2016, from 881 to 1123 Ha, respectively. The cropland area increased because farmers changed their cropping practice due to water scarcity and floods. Trend analyses of riverbank erosion and accretion patterns suggest an increase in accretion rates compared to the rate of riverbank erosion. A household survey was conducted using a self-administered questionnaire where 450 respondents have participated (farmers: 200 and fishermen: 250). Survey results show that most of the farmers (65.5%) and fishermen (76.8%) think that the construction of upstream barrages caused harm to them. The majority of farmers and fishermen feel water scarcity, mainly in the dry season. We found that a large number of participants in the study area are willing to change their occupations. Furthermore, participants observed that many local people are migrating or willing to migrate to other places nowadays. Our study also found that farmers who face water scarcity in their area are more likely to change their location than their counterparts, while those who face problems in their cultivation are less likely to move. On the other hand, upstream barrages, fishing effects, and getting support in crisis significantly predict fishermen's occupation changes. We believe our results provide essential information on the significance of transboundary water-sharing treaties, sustainable water resource management, and planning.

Explainable artificial intelligence (XAI) for exploring spatial variability of lung and bronchus cancer (LBC) mortality rates in the contiguous USA.

Machine learning (ML) has demonstrated promise in predicting mortality; however, understanding spatial variation in risk factor contributions to mortality rate requires explainability. We applied explainable artificial intelligence (XAI) on a stack-ensemble machine learning model framework to explore and visualize the spatial distribution of the contributions of known risk factors to lung and bronchus cancer (LBC) mortality rates in the conterminous United States. We used five base-learners-generalized linear model (GLM), random forest (RF), Gradient boosting machine (GBM), extreme Gradient boosting machine (XGBoost), and Deep Neural Network (DNN) for developing stack-ensemble models. Then we applied several model-agnostic approaches to interpret and visualize the stack ensemble model's output in global and local scales (at the county level). The stack ensemble generally performs better than all the base learners and three spatial regression models. A permutation-based feature importance technique ranked smoking prevalence as the most important predictor, followed by poverty and elevation. However, the impact of these risk factors on LBC mortality rates varies spatially. This is the first study to use ensemble machine learning with explainable algorithms to explore and visualize the spatial heterogeneity of the relationships between LBC mortality and risk factors in the contiguous USA.

Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA.

Type 2 diabetes mellitus (T2D) prevalence in the United States varies substantially across spatial and temporal scales, attributable to variations of socioeconomic and lifestyle risk factors. Understanding these variations in risk factors contributions to T2D would be of great benefit to intervention and treatment approaches to reduce or prevent T2D. Geographically-weighted random forest (GW-RF), a tree-based non-parametric machine learning model, may help explore and visualize the relationships between T2D and risk factors at the county-level. GW-RF outputs are compared to global (RF and OLS) and local (GW-OLS) models between the years of 2013-2017 using low education, poverty, obesity, physical inactivity, access to exercise, and food environment as inputs. Our results indicate that a non-parametric GW-RF model shows a high potential for explaining spatial heterogeneity of, and predicting, T2D prevalence over traditional local and global models when inputting six major risk factors. Some of these predictions, however, are marginal. These findings of spatial heterogeneity using GW-RF demonstrate the need to consider local factors in prevention approaches. Spatial analysis of T2D and associated risk factor prevalence offers useful information for targeting the geographic area for prevention and disease interventions.

Environmental sustainability assessment due to stone quarrying and crushing activities in Jaflong, Sylhet.

Quarrying and crushing activities constitute a major threat to the environment and occupational health of the workers in Jaflong, Sylhet. This study aims to determine the environmental sustainability of stone quarrying and crushing activities considering four dominant environmental components, viz. physicochemical parameters of water, PM2.5 and PM10, sound, and land use land cover (LULC). Water quality was measured in a seasonal variation, and air and sound data were collected in an 8-h period of every weekday of 2 months while LULC data were also collected from 1999 to 2019 with 5 years of interval. Water quality index (WQI) and cluster analysis were applied to classify the pollution sources while inverse distance weighting (IDW) and weighted overlay were used to show the vulnerable zone. All the parameters were considered with the established limit of WHO. WQI detects that the sampling stations located near the quarrying site were responsible for the deterioration of the water quality. Cluster analysis identified that the S8 and S10 sites were heavily susceptible to air and sound pollution. IDW and WO ranked the south-western lower stream and tribal village located at the north-western side as moderately to highly polluted. Correlation analysis illustrated that the values of air and sound parameters were concentrated above the permissible limit. Besides, LULC change revealed the significant lowering trend of vegetation and water bodies whereas it shows the upward trend of barren land and settlement. Finally, the extensive quarrying and crushing activities without any safety measure lead to breaking the environmental sustainability as well as workers and nearby dwellers were exposed to several respiratory diseases.

Detecting functional field units from satellite images in smallholder farming systems using a deep learning based computer vision approach: A case study from Bangladesh.

Improving agricultural productivity of smallholder farms (which are typically less than 2 ha) is key to food security for millions of people in developing nations. Knowledge of the size and location of crop fields forms the basis for crop statistics, yield forecasting, resource allocation, economic planning, and for monitoring the effectiveness of development interventions and investments. We evaluated three different full convolutional neural network (F-CNN) models (U-Net, SegNet, and DenseNet) with deep neural architecture to detect functional field boundaries from the very high resolution (VHR) WorldView-3 satellite imagery from Southern Bangladesh. The precision of the three F-CNN was up to 0.8, and among the three F-CNN models, the highest precision, recalls, and F-1 score was obtained using a DenseNet model. This architecture provided the highest area under the receiver operating characteristic (ROC) curve (AUC) when tested with independent images. We also found that 4-channel images (blue, green, red, and near-infrared) provided small gains in performance when compared to 3-channel images (blue, green, and red). Our results indicate the potential of using CNN based computer vision techniques to detect field boundaries of small, irregularly shaped agricultural fields.

Mapping U.S. Food System Localization Potential: The Impact of Diet on Foodsheds.

In the long term, food systems must heed natural resource limits. Localized production and dietary changes are often suggested as potential solutions. However, no U.S. analyses fully evaluate the feasibility to scale localization across a range of diets. We therefore modeled the biophysical capacity for regional food systems based on agricultural land area and productivity, population, and 7 diet scenarios ranging in meat-intensity, from current consumption to vegan. We estimated foodshed size, colloquially known as "food miles" for 378 U.S. metropolitan centers, in a hypothetical nationwide closed system that prioritizes localized food. We found that foodshed size (weighted average distance traveled) for three land types ranged from 351-428 km (cultivated cropland), 80-492 km (perennial forage cropland), and 117-799 km (grazing land). Localized potential varies regionally: foodsheds are generally larger in the populous Northeast, Southeast, and Southwest than in the Northwest and the center of the country. However, depending on consumption of animal-based foods, a sizable proportion of the population could meet its food needs within 250km: from 35%-53% (cultivated cropland), 39%-94% (perennial forage cropland, 100% for vegan), and 26%-88% (grazing land, 100% for ovolacto-vegetarian and vegan). All seven scenarios leave some land unused. This reserve capacity might be used to supply food to the global market, grow bioenergy crops, or for conservation.

Farming on the fringe: Shallow groundwater dynamics and irrigation scheduling for maize and wheat in Bangladesh's coastal delta.

Further efforts are needed to combat poverty and agricultural productivity problems in the delta region of Bangladesh. Sustainable intensification of crop production through irrigation and production of cash crops such as maize and wheat might be a promising option to increase income and diversify food production. Only limited research has however been conducted on the potential of using surface water from canals as an irrigation source for maize and wheat production in the delta region. To better understand the contribution of shallow groundwater to crop production and number of irrigations needed for maize and wheat in this unique coastal environment, we conducted multi-locational trials on farmers' fields over three rabi seasons. In addition to soil moisture and salinity, we recorded the depth and salinity of the shallow water table throughout these experiments. Maize in particular requires considerable capital investment for seeds, fertilizer, irrigation and labor. Although farmers express wide interest in maize - which can be sold as a profitable cash crop into Bangladesh's expanding poultry feed industry - many of them are reluctant to invest in fertilizer because of the high entry costs. We therefore also investigated the profitability of growing maize under low and high (recommended) fertilizer regimens. Volumetric soil moisture at sowing and during the grain filling phase or at maturity indicated that there is ample supply of water in the profile. Most measurements were above the drained upper limit (DUL). We attributed this to the generally shallow water table depths, which never exceeded 2.75 m at any location, but generally stayed between 1-2 m depth throughout the season. The region's soil texture classes (clay loams, silt loams and silty clay loams) are all conducive for capillary rise of water into the rooting zone. Consequently, irrigation had a significant effect on maize yield in the driest winter only, whereas for wheat, it had no effect. The key for a successful maize and wheat production in the delta region of Bangladesh is to ensure a good crop establishment, which can be achieved with a starter and an additional irrigation at crown root initiation for wheat and at V6-8 for maize. Maize however is not always profitable. Compared to low fertilizer rates, higher rates reduced losses in low yielding site-years and increased profits in high-yielding site years. This indicates that it is advisable for farmers not to reduce fertilizer rates. Low-risk financial credit with rationally structured interest rates that allow farmers to invest in maize could potentially offset these constraints.

Stability Studies and Characterization of Glutathione-Loaded Nanoemulsion.

Glutathione reduced (GSH) is the mother of all the antioxidants and has an antimelanogenic effect. It is extremely vulnerable to oxidation in the solution form which limits its use. The GSH in nano-oil droplets present a potential solution to this problem. The aim of this study was to formulate glutathione-loaded nanoemulsion and assess its stability studies over a 90-day testing period. To formulate GSH-loaded nanoemulsion pseudo-ternary phase diagram, it was built with various concentrations of water, liquid paraffin oil, and surfactant mixture (Tween 80 and Span 80). The oily phase was prepared by dissolving the GSH (450 mg) in liquid paraffin oil through stirring. High-energy homogenization was used to prepare the nanoemulsion. From preformulation stability studies of the 28-day testing period, nanoemulsion (NE-19) with oil and surfactant mixture ratio (1:1) of hydrophilic lipophilic balance (HLB) value 10 was selected. The samples of NE-19 and its respective base (B-19) were kept at four different storage conditions for a period of 90 days and evaluated for physical characteristics, droplet size and distribution analysis, zeta potential analysis, electrical conductivity, mobility, polydispersity, pH, phase separation, and flow analysis at different time intervals. Glutathione in nano-oil droplets with nonionic surfactants produced oil-in-water nanoemulsions that were thermodynamically stable over the 90-day testing period at different storage conditions. NE-19 was formulated having non-Newtonian flow and pseudo-plastic behavior. pH was found in the range of 5-6. Polydispersity was less than 0.3. The droplet size of fresh nanoemulsion was 96.05 nm, whereas the zeta potential was -37.1. Mobility and electrical conductivity were -2.726 µm cm/Vs and 0.0141 mS/cm, respectively. Glutathione-loaded nanoemulsions have excellent stability, promising the solution in nano-oil droplets and are suggested for in-vivo release studies for oxidative skin related diseases.

Sustainable crop intensification through surface water irrigation in Bangladesh? A geospatial assessment of landscape-scale production potential.

Changing dietary preferences and population growth in South Asia have resulted in increasing demand for wheat and maize, along side high and sustained demand for rice. In the highly productive northwestern Indo-Gangetic Plains of South Asia, farmers utilize groundwater irrigation to assure that at least two of these crops are sequenced on the same field within the same year. Such double cropping has had a significant and positive influence on regional agricultural productivity. But in the risk-prone and food insecure lower Eastern Indo-Gangetic Plains (EIGP), cropping is less intensive. During the dryer winter months, arable land is frequently fallowed or devoted to lower yielding rainfed legumes. Seeing opportunity to boost cereals production, particularly for rice, donors and land use policy makers have consequently reprioritized agricultural development investments in this impoverished region. Tapping groundwater for irrigation and intensified double cropping, however, is unlikely to be economically viable or environmentally sound in the EIGP. Constraints include saline shallow water tables and the prohibitively high installation and energetic extraction costs from deeper freshwater aquifers. The network of largely underutilized rivers and natural canals in the EIGP could conversely be tapped to provide less energetically and economically costly surface water irrigation (SWI). This approach is now championed by the Government of Bangladesh, which has requested USD 500 million from donors to implement land and water use policies to facilitate SWI and double cropping. Precise geospatial assessment of where freshwater flows are most prominent, or where viable fallow or low production intensity cropland is most common, however remains lacking. In response, we used remotely sensed data to identify agricultural land, detect the temporal availability of freshwater in rivers and canals, and assess crop production intensity over a three-year study period in a 33,750 km2 case study area in southwestern Bangladesh. We combined these data with georeferenced and temporally explicitly soil and water salinity information, in addition to relative elevation classifications, in order to examine the extent of winter fallows and low productivity rainfed cropland that could be irrigated by small-scale surface water pumps. Applying observations of irrigated crop sowing dates and yields from 510 wheat, 550 maize, and 553 rice farmers, we also modeled crop intensification production scenarios within the case study area. We conservatively estimate that at least 20,800 and 103,000 ha of fallow and rainfed cropland, respectively, could be brought into intensified double cropping using SWI. Scenario analysis indicates that if 25%-75% of the fallow or low-intensity land were converted to irrigated maize, national aggregate production could increase by 10-14% or 29-42%, respectively. Conversion to wheat would conversely boost national production by 9-10% or 26-31%. Irrigated rice is however unlikely to contribute >3%. In aggregate, these actions could generate between USD 36-108 million of revenue annually among farmers. Intensification therefore has important land use policy and food and income security implications, helping to rationalizei SWI investments. Crop choice, water resource allocation, and water governance will however remain crucial considerations for irrigation planners.

Development of fixed dose combination tablets of aripiprazole plus divalproex sodium and their simultaneous determination using HPLC-UV.

A vast majority of psychiatric patients are effectively treated with combination of drugs to improve efficacy and adherence, but due to limited research and development in fixed dose combination (FDC) in psychiatry, these products are not commonly available. The aim of this study is to prepare cost effective FDC tablets containing aripiprazole and divalproex sodium. Two batches of fixed dose combination tablets, FDC1 and FDC2, were successfully prepared using wet granulation technique. Furthermore, aripiprazole tablets A1 and A2 and divalproex tablets D1 were also formulated as reference to compare the in vitro availability profile. An accurate and simple isocratic HPLC method was established and validated for the simultaneous quantification of aripiprazole and valproic acid in the FDC tablets. A reversed-phase C18 (250 × 4.6 mm) column in isocratic mode was used. The mobile phase consisted of acetonitrile and 0.32% KH2PO4 (60:40, v/v), flow rate was set at 1.0 mL/min and the detection was performed at 210 nm. Average percent recoveries of aripiprazole and valproic acid were 96.0 and 95.5%, respectively, meeting the official requirements. The newly developed FDC product may be used for the better therapeutic outcomes of combined use of aripiprazole and valproic acid, which may improve patient adherence.

Effect of fasting on serum lithium levels: an experimental study in animal models.

Muslims throughout the world observe dawn to dusk fast in the month of Holy Ramadan. This study aims to investigate the effect of fasting on serum lithium levels in an animal model under typical conditions of Ramadan. Animals were categorized into oral and intraperitoneal groups. Each group was divided into fasting and non fasting groups along with their controls having six animals each. Mean serum lithium levels of non-fasting and fasting rats were assessed. Mean serum lithium levels of oral non-fasting rats was 0.23±0.004 mequiv/L, (n=6) compared to oral fasting rats 0.20+0.002 mequiv/L, (n=6) mean difference=0.003. The mean difference between mean serum lithium level of intraperitoneal non fasting (0.246±0.015 mequiv/L, n = 6) and intraperitoneal fasting rats (0.206±0.020 mequiv/L, n = 6) was 0.02. These differences were statistically non significant (P>0.05). The mean serum lithium is not grossly affected by fasting in rats under 25ºC and fasting for almost 12 hours which is consistent with a previous clinical study. Lithium can be used by fasting bipolar patients but, will require careful supervision.

Operability and early outcome in 48 Irish patients with peritoneal malignancy treated by surgery and intraperitoneal chemotherapy in a specialized centre.

BACKGROUND: In selected cases of peritoneal malignancy a novel approach of complete macroscopic tumour removal by extensive surgical cytoreduction, combined with intraperitoneal chemotherapy, provides a possibility of cure. The experience with 48 consecutive Irish cases undergoing laparotomy in a specialized centre is reported. PATIENTS AND METHODS: A subset of 48 Irish patients out of a total of 120 cases with peritoneal malignancy underwent surgery between September 1999 and March 2011 in an English National referral centre. Overall 37/48 (77%) had appendiceal mucinous tumours with pseudomyxoma peritonei type syndrome. The treatment strategy involved macroscopic complete tumour removal (complete cytoreduction) combined with intra-operative, intraperitoneal chemotherapy. RESULTS: Overall 30/48 (62.5%) had complete cytoreduction, 15/48 (31.3%) had major debulking and 3 (4.2%) had laparotomy and biopsy only. The median (range) operating time in hours was 9.8 (4.8-16) in the 30 who had complete cytoreduction compared with 6.3 (4.5-11) in the 15 who had debulking (p = 0.019). There was no post-operative mortality. Overall five year survival for the complete tumour removal group was 66% compared with 12% for those only amenable to major debulking. CONCLUSION: This novel strategy of cytoreduction combined with intraperitoneal chemotherapy is effective in selected patients with peritoneal malignancy. The complex surgery is particularly effective for appendiceal tumours and provides the only possibility of cure in this challenging disease.

Factors affecting paddy soil arsenic concentration in Bangladesh: prediction and uncertainty of geostatistical risk mapping.

Knowledge of the spatial correlation of soil arsenic (As) concentrations with environmental variables is needed to assess the nature and extent of the risk of As contamination from irrigation water in Bangladesh. We analyzed 263 paired groundwater and paddy soil samples covering highland (HL) and medium highland-1 (MHL-1) land types for geostatistical mapping of soil As and delineation of As contaminated areas in Tala Upazilla, Satkhira district. We also collected 74 non-rice soil samples to assess the baseline concentration of soil As for this area. The mean soil As concentrations (mg/kg) for different land types under rice and non-rice crops were: rice-MHL-1 (21.2)>rice-HL (14.1)>non-rice-MHL-1 (11.9)>non-rice-HL (7.2). Multiple regression analyses showed that irrigation water As, Fe, land elevation and years of tubewell operation are the important factors affecting the concentrations of As in HL paddy soils. Only years of tubewell operation affected As concentration in the MHL-1 paddy soils. Quantitatively similar increases in soil As above the estimated baseline-As concentration were observed for rice soils on HL and MHL-1 after 6-8 years of groundwater irrigation, implying strong retention of As added in irrigation water in both land types. Application of single geostatistical methods with secondary variables such as regression kriging (RK) and ordinary co-kriging (OCK) gave little improvement in prediction of soil As over ordinary kriging (OK). Comparing single prediction methods, kriging within strata (KWS), the combination of RK for HL and OCK for MHL-1, gave more accurate soil As predictions and showed the lowest misclassification of declaring a location "contaminated" with respect to 14.8 mg As/kg, the highest value obtained for the baseline soil As concentration. Prediction of soil As buildup over time indicated that 75% or the soils cropped to rice would contain at least 30 mg/L As by the year 2020.