Materials and Methods: A model of ATR-FTIR-PLSR was developed using ATR-FTIR spectra of mixed aflatoxin standards in 100% acetonitrile (112 samples) and 75% methanol (112 samples), validated by testing its prediction on 125 feed/food samples spiked with variable concentrations of aflatoxins, and applied to screen 660 samples of commercial chicken feeds and food grains from Nigerian and Malaysian markets for total aflatoxins, for which the dietary exposure risks to aflatoxins (DERA) and associated hepatocellular carcinoma (HCC) risks were evaluated for both countries.
Results: The ATR-FTIR-PLSR model demonstrated excellent prediction power [R 2 = 99.59%, p = 0.001, root mean square error of calibration (RMSEC) = 1.69, RMSE p = 1.98, bias = -0.26], sensitivity (limit of quantitation and limit of the method < 5.0 ng/gm), precision (coefficient of variation = 0.97-1.72), and accuracy (% recovery of 88%-106%) in all the spiked samples. The model's prediction was statistically reliable (R 2 = 99.8%, p < 0.05) when compared with a high-performance liquid chromatography method. Levels of aflatoxins in the commercial samples signify high DERA (0.92-138.2 ng of aflatoxins/kg BW/day) and HCC risk (1.07%-159.91% of HCC/100,000 people/year) in the exposed populations.
Conclusions: Results feature the conceivable implementation of the proposed ATR-FTIR-PLSR model for rapid, accurate determination and monitoring of aflatoxins in commercial chicken feeds and food grains; and the need to strengthen aflatoxin control/prevention strategies in the study populations.
MATERIALS AND METHODS: This cross-sectional study was conducted in a PO mill located in Mukah, Sarawak, Malaysia. Thirty-one workers from the four workstations (sterilizer, boiler, oil, and engine rooms) were selected as the respondents in this study. Wet Bulb Globe Thermometer was used in this study to measure the environmental temperature (WBGTin). Body core temperature (BCT), blood pressure (BP), and heart rate (HR) were recorded both before and after working in order to assess the physiological effects of heat stress on workers. A set of questionnaires were used to determine sociodemographic characteristics of the respondents and their symptoms related to heat stress. Data were then analyzed using SPSS Ver28.
RESULTS: The WBGTin was found to be above the ACGIH threshold limit value of heat stress exposure in the engine room, sterilizer, and boiler workstations (>28.0°C). Additionally, there was a significant difference in the worker's BCT in these three workstations before and after work (p<0.05). Only the systolic BP and HR of those working at the boiler workstation showed significant difference between before and after work (p<0.05). The most typical symptoms that workers experience as a result of being exposed to heat at work include headache and fatigue. However, statistical analysis using Spearman Rho's test showed that there is no correlation between heat stress level with physiological changes and health-related symptoms among study respondents (p>0.05).
CONCLUSION: Results of the present study confirmed that workers in PO mill were exposed to high temperatures while at work. Although the evidence indicates the physiological parameters in general are not significantly affected while working, it also demonstrated that worker's body adapts and acclimates to the level of heat. Even so, precautions should still be taken to reduce future heat exposure. It is recommended that a physiological study be carried out that focuses on cognitive function impairment to support the evidence regarding the effects of heat stress on PO mill workers.
MATERIALS AND METHODS: To obtain the optimal mobile phase, samples were extracted with methanol/water (3:1) + 5% sodium chloride and partitioned using several solvent systems using preparative TLC. Camag TLC scanner 3 was used to scan the TLC plates at 366 nm and quantify them using JustTLC software. The method was tested for linearity, specificity, accuracy, precision, sensitivity, and robustness in accordance with ICH recommendations, and then utilized to screen 132 Nigerian poultry/food samples for total aflatoxins (TAFs).
RESULTS: The best separation of aflatoxins was achieved using acetonitrile and dichloromethane (3:17) mobile phase over an average run time of 45 min, resulting in linear calibration curves (R2 > 0.99) in the concentration range limit of quantitation (LoQ) to 50 ng/spot with a limit of detection of <2.0 ng/g and a LoQ of <4.0 ng/gm for all aflatoxins in all spiked samples. When the proposed TLC method was compared to an optimized high-performance liquid chromatography method, an excellent linear regression was obtained (R2 > 95%). Seventy seven (58.33%) of the 132 samples examined were positive for aflatoxins, with mean values ranging from 3.57 ± 2.55 to 37.31 ± 34.06 ng/gm for aflatoxin B1 and 6.67 ± 0.00 to 38.02 ± 31.52 ng/gm for TAFs, respectively.
CONCLUSIONS: The results demonstrate the feasibility of using the suggested TLC method in conjunction with a novel solvent solution (free of carcinogenic chloroform) for the rapid and accurate measurement of TAFs in foods/feeds.
METHODS: This was a retrospective cross-sectional study conducted on specialist medical reports written from 2009 to 2019, involving patients who survived after TBI from RTA. The functional outcome was assessed using the Glasgow Outcome Scale-Extended (GOSE). Factors associated with good outcome were analysed via logistic regression analysis. Multivariate logistic regression analysis was used to derive the best fitting Prediction Model and split-sample cross-validation was performed to develop a prediction model.
RESULTS: A total of 1939 reports were evaluated. The mean age of the study participants was 32.4 ± 13.7 years. Most patients were male, less than 40, and with average post RTA of two years. Good outcome (GOSE score 7 & 8) was reported in 30.3% of the patients. Factors significantly affecting functional outcome include age, gender, ethnicity, marital status, education level, severity of brain injury, neurosurgical intervention, ICU admission, presence of inpatient complications, cognitive impairment, post-traumatic headache, post traumatic seizures, presence of significant behavioural issue; and residence post discharge (p<0.05). After adjusting for confounding factors, prediction model identified age less than 40, mild TBI, absence of post traumatic seizure, absence of behaviour issue, absence of cognitive impairment and independent living post TBI as significant predictors of good functional outcome post trauma. Discrimination of the model was acceptable (C-statistic, 0.67; p<0.001, 95% CI: 0.62-0.73).
CONCLUSION: Good functional outcome following TBI due to RTA in this study population is comparable to other low to middle income countries but lower than high income countries. Factors influencing outcome such as seizure, cognitive and behavioural issues, and independent living post injury should be addressed early to achieve favourable long-term outcomes.