Predicting the risk of diabetic retinopathy using explainable machine learning algorithms.

BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is a global health concern among diabetic patients. The objective of this study was to propose an explainable machine learning (ML)-based system for predicting the risk of DR. MATERIALS AND METHODS: This study utilized publicly available cross-sectional data in a Chinese cohort of 6374 respondents. We employed boruta and least absolute shrinkage and selection operator (LASSO) based feature selection methods to identify the common predictors of DR. Using the identified predictors, we trained and optimized four widly applicable models (artificial neural network, support vector machine, random forest, and extreme gradient boosting (XGBoost) to predict patients with DR. Moreover, shapely additive explanation (SHAP) was adopted to show the contribution of each predictor of DR in the prediction. RESULTS: Combining Boruta and LASSO method revealed that community, TCTG, HDLC, BUN, FPG, HbAlc, weight, and duration were the most important predictors of DR. The XGBoost-based model outperformed the other models, with an accuracy of 90.01%, precision of 91.80%, recall of 97.91%, F1 score of 94.86%, and AUC of 0.850. Moreover, SHAP method showed that HbA1c, community, FPG, TCTG, duration, and UA1b were the influencing predictors of DR. CONCLUSION: The proposed integrating system will be helpful as a tool for selecting significant predictors, which can predict patients who are at high risk of DR at an early stage in China.

Histologic comparison of formocresol, platelet-rich fibrin, and hesperidin in pulpotomy: A randomized trial in dogs.

Aims: To histologically assess and compare formocresol (FC), platelet-rich fibrin (PRF), and hesperidin (HPN) as pulpotomy agents in dogs. Materials and Methods: Pulpotomy was attempted from the buccal surface (class V) of 48 teeth in three mongrel dogs (Canis Lupus). Cavities were randomly allocated for three groups (n = 16) according to the pulpotomy agent used; (group I: FC (control), group II: PRF, and group III: HPN). All cavities were then sealed with zinc oxide eugenol followed by resin-modified glass ionomer restoration. Two months later, dogs were euthanized; the specimens were obtained and prepared for histological assessment followed by statistical analysis. Results: HPN specimens showed the best dentin bridge formation and the least inflammatory signs and pulp disorganization. Followed without statistically significant difference by PRF (P ≥ 0.05). Both of HPN and PRF, however, showed a significant difference statistically (P ≤ 0.05) to FC that showed no dentin bridging with more pronounced inflammation, necrosis, and pulp disorganization. Conclusions: For pulpotomy, HPN and PRF seemed histologically to be good substitutes for FC in the dog model.

Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia.

BACKGROUND AND OBJECTIVES: Hypertension (HTN), a major global health concern, is a leading cause of cardiovascular disease, premature death and disability, worldwide. It is important to develop an automated system to diagnose HTN at an early stage. Therefore, this study devised a machine learning (ML) system for predicting patients with the risk of developing HTN in Ethiopia. MATERIALS AND METHODS: The HTN data was taken from Ethiopia, which included 612 respondents with 27 factors. We employed Boruta-based feature selection method to identify the important risk factors of HTN. The four well-known models [logistics regression, artificial neural network, random forest, and extreme gradient boosting (XGB)] were developed to predict HTN patients on the training set using the selected risk factors. The performances of the models were evaluated by accuracy, precision, recall, F1-score, and area under the curve (AUC) on the testing set. Additionally, the SHapley Additive exPlanations (SHAP) method is one of the explainable artificial intelligences (XAI) methods, was used to investigate the associated predictive risk factors of HTN. RESULTS: The overall prevalence of HTN patients is 21.2%. This study showed that XGB-based model was the most appropriate model for predicting patients with the risk of HTN and achieved the accuracy of 88.81%, precision of 89.62%, recall of 97.04%, F1-score of 93.18%, and AUC of 0. 894. The XBG with SHAP analysis reveal that age, weight, fat, income, body mass index, diabetes mulitas, salt, history of HTN, drinking, and smoking were the associated risk factors of developing HTN. CONCLUSIONS: The proposed framework provides an effective tool for accurately predicting individuals in Ethiopia who are at risk for developing HTN at an early stage and may help with early prevention and individualized treatment.

Identification of the risk factors of type 2 diabetes and its prediction using machine learning techniques.

This study identified the risk factors for type 2 diabetes (T2D) and proposed a machine learning (ML) technique for predicting T2D. The risk factors for T2D were identified by multiple logistic regression (MLR) using p-value (p<0.05). Then, five ML-based techniques, including logistic regression, naïve Bayes, J48, multilayer perceptron, and random forest (RF) were employed to predict T2D. This study utilized two publicly available datasets, derived from the National Health and Nutrition Examination Survey, 2009-2010 and 2011-2012. About 4922 respondents with 387 T2D patients were included in 2009-2010 dataset, whereas 4936 respondents with 373 T2D patients were included in 2011-2012. This study identified six risk factors (age, education, marital status, SBP, smoking, and BMI) for 2009-2010 and nine risk factors (age, race, marital status, SBP, DBP, direct cholesterol, physical activity, smoking, and BMI) for 2011-2012. RF-based classifier obtained 95.9% accuracy, 95.7% sensitivity, 95.3% F-measure, and 0.946 area under the curve.

Socioeconomic inequality in the prevalence of low birth weight and its associated determinants in Bangladesh.

BACKGROUND AND OBJECTIVE: Low birth weight (LBW) is a major risk factor of child mortality and morbidity during infancy (0-3 years) and early childhood (3-8 years) in low and lower-middle-income countries, including Bangladesh. LBW is a vital public health concern in Bangladesh. The objective of the research was to investigate the socioeconomic inequality in the prevalence of LBW among singleton births and identify the significantly associated determinants of singleton LBW in Bangladesh. MATERIALS AND METHODS: The data utilized in this research was derived from the latest nationally representative Bangladesh Demographic and Health Survey, 2017-18, and included a total of 2327 respondents. The concentration index (C-index) and concentration curve were used to investigate the socioeconomic inequality in LBW among the singleton newborn babies. Additionally, an adjusted binary logistic regression model was utilized for calculating adjusted odds ratio and p-value (<0.05) to identify the significant determinants of LBW. RESULTS: The overall prevalence of LBW among singleton births in Bangladesh was 14.27%. We observed that LBW rates were inequitably distributed across the socioeconomic groups (C-index: -0.096, 95% confidence interval: [-0.175, -0.016], P = 0.029), with a higher concentration of LBW infants among mothers living in the lowest wealth quintile (poorest). Regression analysis revealed that maternal age, region, maternal education level, wealth index, height, age at 1st birth, and the child's aliveness (alive or died) at the time of the survey were significantly associated determinants of LBW in Bangladesh. CONCLUSION: In this study, socioeconomic disparity in the prevalence of singleton LBW was evident in Bangladesh. Incidence of LBW might be reduced by improving the socioeconomic status of poor families, paying special attention to mothers who have no education and live in low-income households in the eastern divisions (e.g., Sylhet, Chittagong). Governments, agencies, and non-governmental organizations should address the multifaceted issues and implement preventive programs and policies in Bangladesh to reduce LBW.

Investigate the risk factors of stunting, wasting, and underweight among under-five Bangladeshi children and its prediction based on machine learning approach.

AIMS: Malnutrition is a major health issue among Bangladeshi under-five (U5) children. Children are malnourished if the calories and proteins they take through their diet are not sufficient for their growth and maintenance. The goal of the research was to use machine learning (ML) algorithms to detect the risk factors of malnutrition (stunted, wasted, and underweight) as well as their prediction. METHODS: This work utilized malnutrition data that was derived from Bangladesh Demographic and Health Survey which was conducted in 2014. The selected dataset consisted of 7079 children with 13 factors. The potential risks of malnutrition have been identified by logistic regression (LR). Moreover, 3 ML classifiers (support vector machine (SVM), random forest (RF), and LR) have been implemented for predicting malnutrition and the performance of these ML algorithms were assessed on the basis of accuracy. RESULTS: The average prevalence of stunted, wasted, and underweight was 35.4%, 15.4%, and 32.8%, respectively. It was noted that LR identified five risk factors for stunting and underweight, as well as four factors for wasting. Results illustrated that RF can be accurately classified as stunted, wasted, and underweight children and obtained the highest accuracy of 88.3% for stunted, 87.7% for wasted, and 85.7% for underweight. CONCLUSION: This research focused on the identification and prediction of major risk factors for stunting, wasting, and underweight using ML algorithms which will aid policymakers in reducing malnutrition among Bangladesh's U5 children.

Machine learning algorithm for characterizing risks of hypertension, at an early stage in Bangladesh.

BACKGROUND AND AIMS: Hypertension has become a major public health issue as the prevalence and risk of premature death and disability among adults due to hypertension has increased globally. The main objective is to characterize the risk factors of hypertension among adults in Bangladesh using machine learning (ML) algorithms. MATERIALS AND METHODS: The hypertension data was derived from Bangladesh demographic and health survey, 2017-18, which included 6965 people aged 35 and above. Two most promising risk factor identification methods, namely least absolute shrinkage operator (LASSO) and support vector machine recursive feature elimination (SVMRFE) are implemented to detect the critical risk factors of hypertension. Additionally, four well-known ML algorithms as artificial neural network, decision tree, random forest, and gradient boosting (GB) have been used to predict hypertension. Performance scores of these algorithms were evaluated by accuracy, precision, recall, F-measure, and area under the curve (AUC). RESULTS: The results clarify that age, BMI, wealth index, working status, and marital status for LASSO and age, BMI, marital status, diabetes and region for SVMRFE appear to be the top-most five significant risk factors for hypertension. Our findings reveal that the combination of SVMRFE-GB gives the maximum accuracy (66.98%), recall (97.92%), F-measure (78.99%), and AUC (0.669) compared to others. CONCLUSION: GB-based algorithm confirms the best performer for prediction of hypertension, at an early stage in Bangladesh. Therefore, this study highly suggests that the policymakers make proper judgments for controlling hypertension using SVMRFE-GB-based combination to save time and reduce cost for Bangladeshi adults.

Impact of miR-155 (rs767649 A>T) and miR-146a (rs57095329 A>G) polymorphisms in System Lupus Erythematosus susceptibility in an Egyptian cohort.

OBJECTIVE: Systemic Lupus Erythematosus (SLE) is an autoimmune inflammatory disease. miR-155 and miR-146a were expressed in many autoimmune diseases such as rheumatoid arthritis. The aim of this study was to examine miR-155 rs767649 and miR-146a rs57095329 polymorphisms in SLE susceptibility in an Egyptian cohort and to investigate the correlation between them and clinical data and disease activity. PATIENTS AND METHODS: The two SNPs were analyzed in 120 patients with SLE and 100 healthy controls using RT-PCR. RESULTS: The TT genotype and T allele of miR-155 rs767649 were associated with a significant increase in the risk of SLE, particularly in females. On the other hand, miR-146a (rs57095329) polymorphism was not associated with SLE risk. The AT/TT genotypes of miR-155 rs767649 showed higher distributions among patients with higher SLEDAI and nephritis. CONCLUSIONS: This study had demonstrated for the first time the association between miR-155 rs767649 and the risk of development of SLE in an Egyptian cohort, mostly in females.

Radiation-induced damage in the upper gastrointestinal tract: clinical presentation, diagnostic tests and treatment options.

Radiation-induced damage of the upper gastrointestinal (GI) tract results from radiation of GI tumors or structures adjacent to the GI tract. Radiation-induced damages of the upper GI tract may be acute or delayed, and ranges from lack of appetite, mucosal inflammation (i.e. esophagitis, gastritis, duodenitis) to ulcers, which may be complicated by perforation, penetration, bleeding and stenosis. Radiation-related factors as well as individual patient predisposing factors may increase susceptibility to post-radiation damage. High quality evidence for the treatment of radiation-induced GI damage is scarce and the management is often extrapolated from studies on GI lesions of different etiology. Treatment depends on severity and localization of the radiation-induced damage, and ranges from supportive and dietary measures to endoscopic interventions or surgery. Modern radiation techniques may decrease the incidence and severity of the radiation-induced upper gastrointestinal disease.

Determinants of depressive symptoms among older people in Bangladesh.

BACKGROUND: Depressive symptoms are common among older people which are associated with disability, morbidity and mortality. The aim of this study was to determine the associated risk factors for depressive symptoms among older people in Bangladesh. METHODS: A cross-sectional survey was conducted among 400 people aged ≥65 years from the Meherpur district in Bangladesh. Depressive symptoms were measured by the 15-item Geriatric Depression Scale and categorized into: no depressive symptoms, mild, moderate and severe depressive symptoms. Information was also collected on socio-economic and demographic characteristics, health problems, feeling of loneliness, history of falls and concern about falling. Chi-square test of association and multinomial logistic regression was performed to reveal the determinants of depressive symptoms. RESULTS: Just over half of the sample were female, aged 70+ years, and lived in rural areas. The prevalence of depressive symptoms was 55.5%, and 23.0% mild, 19.0% moderate, and 13.5% having severe levels of depressive symptoms. Older age, sex, residence, marital status, presence of co-morbidities, visual impairment, previous falls, loneliness, and fear of falling were the significant determinants for developing depressive symptoms. LIMITATIONS: A convenience sampling method was used for data collection among older people from selected communities in a district of Bangladesh. The results do not represent the entire population of Bangladesh. Besides, it was a cross-sectional study, and causality cannot be determined. CONCLUSION: Depressive symptoms among older people in Bangladesh is prevalent, and needs to be addressed. Public health programs and strategies are needed to reduce depressive symptoms among older adults in Bangladesh.

Determinants of tobacco cultivation in Bangladesh.

BACKGROUND: Tobacco production continues to increase in low-income and middle-income countries including in Bangladesh. It has spreads to different parts of Bangladesh and is now threatening food cultivation, the environment and health. The aim of this study is to determine the factors those are influenced farmers' decisions to grow tobacco. METHODS: We surveyed 371 tobacco farmers using a simple random sampling in the Meherpur district of Bangladesh. Binary logistic regression was used to examine the variables affecting farmers' decision to cultivate tobacco. RESULTS: Approximately 87.0% of the respondents were contract farmers with different tobacco companies. Almost 83.3% of the farmers had intentions to continue tobacco farming. Binary logistic regression results suggest that company's incentives to farmers, farmers' profitability, a guaranteed market for the tobacco crop and economic viability were the variables most affecting the decision to cultivate tobacco. CONCLUSIONS: Governments seeking to shift farmers away from tobacco will need to consider how to address the dynamics revealed in this research.

Prevalence of erectile dysfunction among Saudi type 2 diabetic patients.

OBJECTIVES: The present study aimed to determine the prevalence and etiology of erectile dysfunction in Saudi type 2 diabetic patients. PATIENTS AND METHODS: 429 Saudi type 2 diabetic male patients aged more than 30 years were recruited. Total and bio-available serum testosterone, sex hormone binding globulin and free testosterone levels were measured by ELISA-IBL GMBH Germany. RESULTS: 47 (12.6%) subjects had hypogonadism with total testosterone < 8 nmol/l and 109 (29.3%) had possible hypogonadism with a total testosterone between 8 and 12 nmol/l. Similarly, using bioavailable levels, 30 (8%) men had overt hypogonadism with bioavailable testosterone < 2.5 nmol/l and 89 (33.9%) men had possible hypogonadism with bioavailable testosterone between 2.5-4 nmol/l; while 266 (71.6%) patients with free testosterone < 0.255 nmol/l had hypogonadism. BMI and waist circumference were both significantly negatively correlated with testosterone levels in Saudi type 2 diabetic men. CONCLUSIONS: Testosterone levels are frequently low in Saudi men with type 2 diabetes and majority of these patients have symptoms of hypogonadism. The prevalence of erectile dysfunction (ED) was 86.7% in diabetic men with low testosterone level of 8-12 nmol/L. Obesity is an associated factor with low testosterone levels and ED in Saudi type 2 diabetic patients.

The effect of pulsed electromagnetic radiation from mobile phone on the levels of monoamine neurotransmitters in four different areas of rat brain.

BACKGROUND: The use of mobile phones is rapidly increasing all over the world. Few studies deal with the effect of electromagnetic radiation (EMR) on monoamine neurotransmitters in the different brain areas of adult rat. AIM: The aim of the present study was to investigate the effect of EMR on the concentrations of dopamine (DA), norepinephrine (NE) and serotonin (5-HT) in the hippocampus, hypothalamus, midbrain and medulla oblongata of adult rats. MATERIALS AND METHODS: Adult rats were exposed daily to EMR (frequency 1800 MHz, specific absorption rate 0.843 W/kg, power density 0.02 mW/cm2, modulated at 217 Hz) and sacrificed after 1, 2 and 4 months of daily EMR exposure as well as after stopping EMR for 1 month (after 4 months of daily EMR exposure). Monoamines were determined by high performance liquid chromatography coupled with fluorescence detection (HPLC-FD) using their native properties. RESULTS: The exposure to EMR resulted in significant changes in DA, NE and 5-HT in the four selected areas of adult rat brain. CONCLUSIONS: The exposure of adult rats to EMR may cause disturbances in monoamine neurotransmitters and this may underlie many of the adverse effects reported after EMR including memory, learning, and stress.

Patient safety in developing countries: retrospective estimation of scale and nature of harm to patients in hospital.

OBJECTIVE: To assess the frequency and nature of adverse events to patients in selected hospitals in developing or transitional economies. DESIGN: Retrospective medical record review of hospital admissions during 2005 in eight countries. SETTING: Ministries of Health of Egypt, Jordan, Kenya, Morocco, Tunisia, Sudan, South Africa and Yemen; the World Health Organisation (WHO) Eastern Mediterranean and African Regions (EMRO and AFRO), and WHO Patient Safety. PARTICIPANTS: Convenience sample of 26 hospitals from which 15,548 patient records were randomly sampled. MAIN OUTCOME MEASURES: Two stage screening. Initial screening based on 18 explicit criteria. Records that screened positive were then reviewed by a senior physician for determination of adverse event, its preventability, and the resulting disability. RESULTS: Of the 15,548 records reviewed, 8.2% showed at least one adverse event, with a range of 2.5% to 18.4% per country. Of these events, 83% were judged to be preventable, while about 30% were associated with death of the patient. About 34% adverse events were from therapeutic errors in relatively non-complex clinical situations. Inadequate training and supervision of clinical staff or the failure to follow policies or protocols contributed to most events. CONCLUSIONS: Unsafe patient care represents a serious and considerable danger to patients in the hospitals that were studied, and hence should be a high priority public health problem. Many other developing and transitional economies will probably share similar rates of harm and similar contributory factors. The convenience sampling of hospitals might limit the interpretation of results, but the identified adverse event rates show an estimate that should stimulate and facilitate the urgent institution of appropriate remedial action and also to trigger more research. Prevention of these adverse events will be complex and involves improving basic clinical processes and does not simply depend on the provision of more resources.

Studies on the effects of aspartame on memory and oxidative stress in brain of mice.

OBJECTIVE: The dipeptide aspartame (N-L-alpha-aspartyl-Lphenylalanine, 1-methyl ester; alpha-APM) is one of the most widely used artificial sweeteners. The present study aimed to investigate the effect of repeated administration of aspartame in the working memory version of Morris water maze test, on oxidative stress and brain monoamines in brain of mice. MATERIALS AND METHODS: Aspartame (0.625, 1.875 or 5.625 mg/kg) was administered once daily subcutaneously for 2 weeks and mice were examined four times a week for their ability to locate a submerged plate. Malondialdehyde (MDA), reduced glutathione (GSH), nitric oxide levels (the concentrations of nitrite/nitrate) and glucose were determined in brain. RESULTS: Only at the highest dose of 5.625 mg/kg, did aspartame significantly impaired water maze performance. The mean time taken to find the escape platform (latency) over 2 weeks was significantly delayed by aspartame 5.625 mg/kg, compared with the saline-treated control group. Significant differences occurred only on the first trial to find the escape platform. Significant increase in brain MDA by 16.5% and nitric oxide by 16.2% and a decrease in GSH by 25.1% and glucose by 22.5% occurred after treatment with aspartame at 1.875 mg/kg. Aspartame administered at 5.625 mg/kg significantly increased brain MDA by 43.8%, nitric oxide by 18.6% and decreased GSH by 32.7% and glucose by 25.8%. Aspartame caused dose-dependent inhibition of brain serotonin, noradrenaline and dopamine. CONCLUSIONS: These findings suggest impaired memory performance and increased brain oxidative stress by repeated aspartame administration. The impaired memory performance is likely to involve increased oxidative stress as well as decreased brain glucose availability.

Variations in amino acid neurotransmitters in some brain areas of adult and young male albino rats due to exposure to mobile phone radiation.

BACKGROUND AND OBJECTIVES: Mobile phone radiation and health concerns have been raised, especially following the enormous increase in the use of wireless mobile telephony throughout the world. The present study aims to investigate the effect of one hour daily exposure to electromagnetic radiation (EMR) with frequency of 900 Mz (SAR 1.165 w/kg, power density 0.02 mW/cm2) on the levels of amino acid neurotransmitters in the midbrain, cerebellum and medulla of adult and young male albino rats. MATERIALS AND METHODS: Adult and young rats were divided into two main groups (treated and control). The treated group of both adult and young rats was exposed to EMR for 1 hour daily. The other group of both adult and young animals was served as control. The determination of amino acid levels was carried out after 1 hour, 1 month, 2 months and 4 months of EMR exposure as well as after stopping radiation. RESULTS: Data of the present study showed a significant increase in both excitatory and inhibitory amino acids in the cerebellum of adult and young rats and midbrain of adult animals after 1 hour of EMR exposure. In the midbrain of adult animals, there was a significant increase in glycine level after 1 month followed by significant increase in GABA after 4 months. Young rats showed significant decreases in the midbrain excitatory amino acids. In the medulla, the equilibrium ratio percent (ER%) calculations showed a state of neurochemical inhibition after 4 months in case of adult animals, whereas in young animals, the neurochemical inhibitory state was observed after 1 month of exposure due to significant decrease in glutamate and aspartate levels. This state was converted to excitation after 4 months due to the increase in glutamate level. CONCLUSION: The present changes in amino acid concentrations may underlie the reported adverse effects of using mobile phones.

Paediatric CT examinations in 19 developing countries: frequency and radiation dose.

The aims of this study were to investigate the frequency of computed tomography (CT) examinations for paediatric patients below 15 y of age in 128 CT facilities in 28 developing countries of Africa, Asia and Eastern Europe and to assess the magnitude of CT doses. Radiation dose data were available from 101 CT facilities in 19 countries. The dose assessment was performed in terms of weighted CT dose index (CTDI(w)), volume CT index and dose length product (DLP) for chest, chest (high resolution), lumbar spine, abdomen and pelvis CT examinations using standard methods. The results show that on average the frequency of paediatric CT examinations was 20, 16 and 5 % of all CT examinations in participating centres in Africa, Asia and Eastern Europe, respectively. Eleven CT facilities in six countries were found to use adult CT exposure parameters for paediatric patients, thus indicating limited awareness and the need for optimisation. CT images were of adequate quality for diagnosis. The CTDI(w) variations ranged up to a factor of 55 (Africa), 16.3 (Asia) and 6.6 (Eastern Europe). The corresponding DLP variations ranged by a factor of 10, 20 and 8, respectively. Generally, the CTDI(w) and DLP values in Japan are lower than the corresponding values in the three regions in this study. The study has indicated a stronger need in many developing countries to justify CT examinations in children and their optimisation. Awareness, training and monitoring of radiation doses is needed as a way forwards.

Patient doses in CT examinations in 18 countries: initial results from International Atomic Energy Agency projects.

The purpose of this prospective study at 73 facilities in 18 countries in Africa, Asia and Eastern Europe was to investigate if the CT doses to adult patients in developing countries are higher than international standards. The dose assessment was performed in terms of weighted computed tomography dose index (CTDIw) and dose length product (DLP) for chest, chest (high resolution), lumbar spine, abdomen and pelvis CT examinations using standard methods. Except in one case, the mean CTDIw values were below diagnostic reference level (DRL) while for DLP, 17 % of situations were above DRLs. The resulting CT images were of adequate quality for diagnosis. The CTDIw and DLP data presented herein are largely similar to those from two recent national surveys. The study has shown a stronger need to create awareness and training of radiology personnel as well as monitoring of radiation doses in many developing countries so as to conform to the ALARA principle.

Biofilm formation and autoinducer-2 signaling in Streptococcus intermedius: role of thermal and pH factors.

BACKGROUND/AIM: Bacteria sense their population density using autoinducer (AI) signaling systems. The AI-2 signal is thought to mediate communication among and within bacterial species. Streptococcus intermedius is a commensal organism frequently associated with periodontitis and purulent infections. We investigated the role of AI-2 signaling in S. intermedius biofilm formation under temperatures and pH levels relevant to human physiology. METHODS: Bioluminescence was used to monitor the change in AI-2 levels at various temperatures. Growth and biofilm formation in S. intermedius and its luxS mutant SI006 were measured at 35, 37, 39, and 41 degrees C and in pH ranging from 5.7 to 7.5. To confirm the role of AI-2 signals in biofilm formation, the AI-2 precursor (S)-4,5-dihydroxy-2,3-pentanedione (DPD) was used to complement SI006 biofilm formation. RESULTS: S. intermedius AI-2 signals were detected at all growth temperatures but reached the highest levels at 37 degrees C. SI006 displayed significantly less biofilm formation than S. intermedius wild-type (WT); however, the role of AI-2 on biofilm formation was confined to 37 degrees C. DPD supplementation significantly increased SI006 biofilm formation to the S. intermedius WT level. The role of AI-2 in S. intermedius biofilm formation was not influenced by pH. High temperatures and low pH enhanced biofilm formation in both S. intermedius and its luxS mutant. CONCLUSIONS: High temperature and acidic conditions may favor biofilm formation by S. intermedius. The role of AI-2 in biofilm formation by S. intermedius, however, varies with physiological temperature changes. These results may assist in understanding possible behavior relative to health and disease.

Validated liquid chromatographic-ultraviolet method for the quantitation of tadalafil in human plasma using liquid-liquid extraction.

A highly selective, sensitive and rapid HPLC method has been developed and validated to quantify tadalafil in human plasma. The tadalafil and internal standard (loratadine, I.S.) were extracted by liquid-liquid extraction technique followed by an aqueous back-extraction allowing injection of an aqueous solvent in the HPLC system. The chromatographic separation was performed on a reverse phase BDS Hypersil C-18 column (250 mm x 4.6 mm, 5 microm, Thermo Separation Co., USA) with a mobile phase of acetonitrile and aqueous solution containing 0.012 M triethylamine+0.020 M orthophosphoric acid (50/50, v/v). The analytes were detected at 225 nm. The assay exhibited a linear range of 5-600 ng/mL for tadalafil in human plasma. The lower limit of quantitation (LLOQ) was 5 ng/mL. The within- and between batch precision (expressed as coefficient of variation, C.V.) did not exceed 10.3% and the accuracy was within -7.6% deviation of the nominal concentration. The recovery of tadalafil from plasma was greater than 66.1%. Stability of tadalafil in plasma was excellent with no evidence of degradation during sample processing (auto-sampler) and 30 days storage in a freezer. This validated method is applied for the clinical study of the tadalafil in human volunteers.