Predictors of social risk for post-ischemic stroke reintegration.

After stroke rehabilitation, patients need to reintegrate back into their daily life, workplace and society. Reintegration involves complex processes depending on age, sex, stroke severity, cognitive, physical, as well as socioeconomic factors that impact long-term outcomes post-stroke. Moreover, post-stroke quality of life can be impacted by social risks of inadequate family, social, economic, housing and other supports needed by the patients. Social risks and barriers to successful reintegration are poorly understood yet critical for informing clinical or social interventions. Therefore, the aim of this work is to predict social risk at rehabilitation discharge using sociodemographic and clinical variables at rehabilitation admission and identify factors that contribute to this risk. A Gradient Boosting modelling methodology based on decision trees was applied to a Catalan 217-patient cohort of mostly young (mean age 52.7), male (66.4%), ischemic stroke survivors. The modelling task was to predict an individual's social risk upon discharge from rehabilitation based on 16 different demographic, diagnostic and social risk variables (family support, social support, economic status, cohabitation and home accessibility at admission). To correct for imbalance in patient sample numbers with high and low-risk levels (prediction target), five different datasets were prepared by varying the data subsampling methodology. For each of the five datasets a prediction model was trained and the analysis involves a comparison across these models. The training and validation results indicated that the models corrected for prediction target imbalance have similarly good performance (AUC 0.831-0.843) and validation (AUC 0.881 - 0.909). Furthermore, predictor variable importance ranked social support and economic status as the most important variables with the greatest contribution to social risk prediction, however, sex and age had a lesser, but still important, contribution. Due to the complex and multifactorial nature of social risk, factors in combination, including social support and economic status, drive social risk for individuals.

Response Methodology Optimization and Artificial Neural Network Modeling for the Removal of Sulfamethoxazole Using an Ozone-Electrocoagulation Hybrid Process.

Removing antibiotics from water is critical to prevent the emergence and spread of antibiotic resistance, protect ecosystems, and maintain the effectiveness of these vital medications. The combination of ozone and electrocoagulation in wastewater treatment provides enhanced removal of contaminants, improved disinfection efficiency, and increased overall treatment effectiveness. In this work, the removal of sulfamethoxazole (SMX) from an aqueous solution using an ozone-electrocoagulation (O-EC) system was optimized and modeled. The experiments were designed according to the central composite design. The parameters, including current density, reaction time, pH, and ozone dose affecting the SMX removal efficiency of the OEC system, were optimized using a response surface methodology. The results show that the removal process was accurately predicted by the quadric model. The numerical optimization results show that the optimum conditions were a current density of 33.2 A/m2, a time of 37.8 min, pH of 8.4, and an ozone dose of 0.7 g/h. Under these conditions, the removal efficiency reached 99.65%. A three-layer artificial neural network (ANN) with logsig-purelin transfer functions was used to model the removal process. The data predicted by the ANN model matched well to the experimental data. The calculation of the relative importance showed that pH was the most influential factor, followed by current density, ozone dose, and time. The kinetics of the SMX removal process followed the first-order kinetic model with a rate constant of 0.12 (min-1). The removal mechanism involves various processes such as oxidation and reduction on the surface of electrodes, the reaction between ozone and ferrous ions, degradation of SMX molecules, formation of flocs, and adsorption of species on the flocs. The results obtained in this work indicate that the O-EC system is a potential approach for the removal of antibiotics from water.

SMES survival and knowledge in emerging economies: evidence from Vietnam.

This paper evaluates how knowledge affecting the survival of new private small and medium sized enterprises (SMEs) in an emerging economy like Vietnam. The panel data extracted from the national surveys allow for comprehensive analysis during the period 2005-2011 with the semi-parametric Cox proportional hazard model. The study examines knowledge factors under controlling firm-specific and industrial factors. The findings express strong evidence that Vietnamese SMEs benefit strongly from knowledge development. The findings suggest firms to foster labor productivity, value added, and computerization. There is evidence of market selection, based on efficiency of investment. Besides, firms should improve return on sales, especially in growing market. Start-up SMEs should prepare sufficient total assets, not basing on leverage to enter the market. Start-up in industries with high growth, especially at the early stages of the life cycle will require more government support. These findings provide the evidence for policy improvement to help SMEs in the development of knowledge economy.

Comparison of sample preparation methodologies towards optimisation of Raman spectroscopy for peripheral blood mononuclear cells.

The exquisite sensitivity of Raman spectroscopy to the molecular composition of biological samples has been a particular strength in its development towards clinical applicates. Its strength in this regard also presents challenges in the development of its diagnostic capabilities owing to its sensitivity, not only to the sample biochemistry, but also the preparation methodology employed prior to analysis. Here we have examined and optimised several approaches to the preparation of peripheral blood mononuclear cells (PBMCs), or immune cell subtypes of whole blood, for Raman spectroscopic analysis. Two approaches to the elimination of haemoglobin contamination, and two approaches to the purification of the lymphocyte portion of whole blood were investigated. It was found that a peroxide treatment of PBMCs prior to spectroscopic analysis was required for elimination of haemoglobin, while a negative selection approach involving magnetically labelled monoclonal antibodies was preferred for purification of individual leucocyte subpopulations in comparison to the plastic adherence method using an ex vivo culture. Further spectral fitting analysis has identified spectral features of interest which may be useful in the identification of individual leucocytes spectrally and warrant further investigation.

Discrimination of immune cell activation using Raman micro-spectroscopy in an in-vitro & ex-vivo model.

Activation and proliferation of immune cells such as lymphocytes and monocytes are appropriate inflammatory responses to invading pathogens and are key to overcoming an infection. In contrast, uncontrolled and prolonged activation of these cellular signalling pathways can be deleterious to the body and result in the development of autoimmune conditions. The understanding of cellular activatory status therefore plays a significant role in disease diagnosis and progression. Conventional automated approaches such as enzyme linked immunosorbent assays (ELISA) and immune-labelling techniques are time-consuming and expensive, relying on a commercially available and specific antibody to identify cell activation. Developing a label-free method for assessing molecular changes would therefore offer a quick and cost-efficient alternative in biomedical research. Here Raman spectroscopy is presented as an effective spectroscopic method for the identification of activated immune cells using both cell lines and primary cells (including purified monocyte and lymphocyte subgroups and mixed peripheral blood mononuclear cell (PBMC) populations) obtained from healthy donors. All cell lines and primary cells were exposed to different stimulants and cellular responses confirmed by flow cytometry or ELISA. Machine learning models of cell discrimination using Raman spectra were developed and compared to reference flow-cytometry, with spectral discrimination levels comparing favourably with the reference method. Spectral signatures of molecular expression after activation were also extracted with results demonstrating alignment with expected profiles. High performance classification models constructed in these in-vitro and ex-vivo studies enabled identification of the spectroscopic discrimination of immune cell subtypes in their resting and activated state. Further spectral fitting analysis identified a number of potential spectral biomarkers that elucidate the spectral classification.

Vibrational spectroscopy of liquid biopsies for prostate cancer diagnosis.

BACKGROUND: Screening for prostate cancer with prostate specific antigen and digital rectal examination allows early diagnosis of prostate malignancy but has been associated with poor sensitivity and specificity. There is also a considerable risk of over-diagnosis and over-treatment, which highlights the need for better tools for diagnosis of prostate cancer. This study investigates the potential of high throughput Raman and Fourier Transform Infrared (FTIR) spectroscopy of liquid biopsies for rapid and accurate diagnosis of prostate cancer. METHODS: Blood samples (plasma and lymphocytes) were obtained from healthy control subjects and prostate cancer patients. FTIR and Raman spectra were recorded from plasma samples, while Raman spectra were recorded from the lymphocytes. The acquired spectral data was analysed with various multivariate statistical methods, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and classical least squares (CLS) fitting analysis. RESULTS: Discrimination was observed between the infrared and Raman spectra of plasma and lymphocytes from healthy donors and prostate cancer patients using PCA. In addition, plasma and lymphocytes displayed differentiating signatures in patients exhibiting different Gleason scores. A PLS-DA model was able to discriminate these groups with sensitivity and specificity rates ranging from 90% to 99%. CLS fitting analysis identified key analytes that are involved in the development and progression of prostate cancer. CONCLUSIONS: This technology may have potential as an alternative first stage diagnostic triage for prostate cancer. This technology can be easily adaptable to many other bodily fluids and could be useful for translation of liquid biopsy-based diagnostics into the clinic.

Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies.

Radiation therapy (RT) is used to treat approximately 50% of all cancer patients. However, RT causes a wide range of adverse late effects that can affect a patient's quality of life. There are currently no predictive assays in clinical use to identify patients at risk of normal tissue radiation toxicity. This study aimed to investigate the potential of Fourier transform infrared (FTIR) spectroscopy for monitoring radiotherapeutic response. Blood plasma was acquired from 53 prostate cancer patients at five different time points: prior to treatment, after hormone treatment, at the end of radiotherapy, two months post radiotherapy and eight months post radiotherapy. FTIR spectra were recorded from plasma samples at all time points and the data was analysed using MATLAB software. Discrimination was observed between spectra recorded at baseline versus follow up time points, as well as between spectra from patients showing minimal and severe acute and late toxicity using principal component analysis. A partial least squares discriminant analysis model achieved sensitivity and specificity rates ranging from 80% to 99%. This technology may have potential to monitor radiotherapeutic response in prostate cancer patients using non-invasive blood plasma samples and could lead to individualised patient radiotherapy.

Correction: Discrimination of breast cancer from benign tumours using Raman spectroscopy.

[This corrects the article DOI: 10.1371/journal.pone.0212376.].

Discrimination of breast cancer from benign tumours using Raman spectroscopy.

Breast cancer is the most common cancer among women worldwide, with an estimated 1.7 million cases and 522,000 deaths in 2012. Breast cancer is diagnosed by histopathological examination of breast biopsy material but this is subjective and relies on morphological changes in the tissue. Raman spectroscopy uses incident radiation to induce vibrations in the molecules of a sample and the scattered radiation can be used to characterise the sample. This technique is rapid and non-destructive and is sensitive to subtle biochemical changes occurring at the molecular level. This allows spectral variations corresponding to disease onset to be detected. The aim of this work was to use Raman spectroscopy to discriminate between benign lesions (fibrocystic, fibroadenoma, intraductal papilloma) and cancer (invasive ductal carcinoma and lobular carcinoma) using formalin fixed paraffin preserved (FFPP) tissue. Haematoxylin and Eosin stained sections from the patient biopsies were marked by a pathologist. Raman maps were recorded from parallel unstained tissue sections. Immunohistochemical staining for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2/neu) was performed on a further set of parallel sections. Both benign and cancer cases were positive for ER while only the cancer cases were positive for HER2. Significant spectral differences were observed between the benign and cancer cases and the benign cases could be differentiated from the cancer cases with good sensitivity and specificity. This study has shown the potential of Raman spectroscopy as an aid to histopathological diagnosis of breast cancer, in particular in the discrimination between benign and malignant tumours.

Development of a memetic clustering algorithm for optimal spectral histology: application to FTIR images of normal human colon.

The coupling between Fourier-transform infrared (FTIR) imaging and unsupervised classification is effective in revealing the different structures of human tissues based on their specific biomolecular IR signatures; thus the spectral histology of the studied samples is achieved. However, the most widely applied clustering methods in spectral histology are local search algorithms, which converge to a local optimum, depending on initialization. Multiple runs of the techniques estimate multiple different solutions. Here, we propose a memetic algorithm, based on a genetic algorithm and a k-means clustering refinement, to perform optimal clustering. In addition, this approach was applied to the acquired FTIR images of normal human colon tissues originating from five patients. The results show the efficiency of the proposed memetic algorithm to achieve the optimal spectral histology of these samples, contrary to k-means.

Fully unsupervised inter-individual IR spectral histology of paraffinized tissue sections of normal colon.

In label-free Fourier-transform infrared histology, spectral images are individually recorded from tissue sections, pre-processed and clustered. Each single resulting color-coded image is annotated by a pathologist to obtain the best possible match with tissue structures revealed after Hematoxylin-Eosin staining. However, the main limitations of this approach are the empirical choice of the number of clusters in unsupervised classification, and the marked color heterogeneity between the clustered spectral images. Here, using normal murine and human colon tissues, we developed an automatic multi-image spectral histology to simultaneously analyze a set of spectral images (8 images mice samples and 72 images human ones). This procedure consisted of a joint Extended Multiplicative Signal Correction (EMSC) to numerically deparaffinize the tissue sections, followed by an automated joint K-Means (KM) clustering using the hierarchical double application of Pakhira-Bandyopadhyay-Maulik (PBM) validity index. Using this procedure, the main murine and human colon histological structures were correctly identified at both the intra- and the inter-individual levels, especially the crypts, secreted mucus, lamina propria and submucosa. Here, we show that batched multi-image spectral histology procedure is insensitive to the reference spectrum but highly sensitive to the paraffin model of joint EMSC. In conclusion, combining joint EMSC and joint KM clustering by double PBM application allows to achieve objective and automated batched multi-image spectral histology.

Development of a hierarchical double application of crisp cluster validity indices: a proof-of-concept study for automated FTIR spectral histology.

Fourier-transform infrared (FTIR) spectral imaging is currently used as a non-destructive and label-free method for analyzing biological specimens. However, to highlight the different tissue regions, unsupervised clustering methods are commonly used leading to a subjective choice of the number of clusters. Here, we develop a hierarchical double application of 9 selected crisp cluster validity indices (CCVIs) using K-Means clustering. This approach when tested first on an artificial dataset showed that the indices Pakhira-Bandyopadhyay-Maulik (PBM) and Sym-Index (SI) perfectly estimated the expected 9 sub-clusters. Then, the concept was applied to a real dataset consisting of FTIR spectral images of normal human colon tissue samples originating from 5 patients. PBM and SI were revealed to be the most efficient indices that correctly identified the different colon histological components including crypts, lamina propria, muscularis mucosae, submucosa, and lymphoid aggregates. In conclusion, these results strongly suggest that the hierarchical double CCVI application is a promising method for automated and informative spectral histology.

Urinary amino acid alterations in 3-year-old children with neurodevelopmental effects due to perinatal dioxin exposure in Vietnam: a nested case-control study for neurobiomarker discovery.

In our previous study of 3-year-old children in a dioxin contamination hot spot in Vietnam, the high total dioxin toxic equivalent (TEQ-PCDDs/Fs)-exposed group during the perinatal period displayed lower Bayley III neurodevelopmental scores, whereas the high 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-exposed group displayed increased autistic traits. In autistic children, urinary amino acid profiles have revealed metabolic alterations in the amino acids that serve as neurotransmitters in the developing brain. Therefore, our present study aimed to investigate the use of alterations in urinary amino acid excretion as biomarkers of dioxin exposure-induced neurodevelopmental deficits in highly exposed 3-year-old children in Vietnam. A nested case-control study of urinary analyses was performed for 26 children who were selected from 111 3-year-old children whose perinatal dioxin exposure levels and neurodevelopmental status were examined in follow-up surveys conducted in a dioxin contaminated hot spot. We compared urinary amino acid levels between the following 4 groups: (1) a high TEQ-PCDDs/Fs and high TCDD-exposed group; (2) a high TEQ-PCDDs/Fs but low TCDD-exposed group; (3) a low TEQ-PCDDs/Fs exposed and poorly developed group; and (4) a low TEQ-PCDDs/Fs exposed and well-developed group. Urinary levels of histidine and tryptophan were significantly decreased in the high TEQ-PCDDs/Fs and high TCDD group, as well as in the high TEQ-PCDDs/Fs but low TCDD group, compared with the low TEQ-PCDDs/Fs and well-developed group. However, the ratio of histidine to glycine was significantly lower only in the high TEQ-PCDDs/Fs and high TCDD group. Furthermore, urinary histidine levels and the ratio of histidine to glycine were significantly correlated with neurodevelopmental scores, particularly for language and fine motor skills. These results indicate that urinary histidine is specifically associated with dioxin exposure-induced neurodevelopmental deficits, suggesting that urinary histidine may be a useful marker of dioxin-induced neurodevelopmental deficits and that histaminergic neurotransmission may be an important pathological contributor to dioxin-mediated neurotoxicity.

Randomised pharmacokinetic trial of rifabutin with lopinavir/ritonavir-antiretroviral therapy in patients with HIV-associated tuberculosis in Vietnam.

BACKGROUND: Rifampicin and protease inhibitors are difficult to use concomitantly in patients with HIV-associated tuberculosis because of drug-drug interactions. Rifabutin has been proposed as an alternative rifamycin, but there is concern that the current recommended dose is suboptimal. The principal aim of this study was to compare bioavailability of two doses of rifabutin (150 mg three times per week and 150 mg daily) in patients with HIV-associated tuberculosis who initiated lopinavir/ritonavir-based antiretroviral therapy in Vietnam. Concentrations of lopinavir/ritonavir were also measured. METHODS: This was a randomized, open-label, multi-dose, two-arm, cross-over trial, conducted in Vietnamese adults with HIV-associated tuberculosis in Ho Chi Minh City (Clinical trial registry number NCT00651066). Rifabutin pharmacokinetics were evaluated before and after the introduction of lopinavir/ritonavir -based antiretroviral therapy using patient randomization lists. Serial rifabutin and 25-O-desacetyl rifabutin concentrations were measured during a dose interval after 2 weeks of rifabutin 300 mg daily, after 3 weeks of rifabutin 150 mg daily with lopinavir/ritonavir and after 3 weeks of rifabutin 150 mg three times per week with lopinavir/ritonavir. RESULTS: Sixteen and seventeen patients were respectively randomized to the two arms, and pharmacokinetic analysis carried out in 12 and 13 respectively. Rifabutin 150 mg daily with lopinavir/ritonavir was associated with a 32% mean increase in rifabutin average steady state concentration compared with rifabutin 300 mg alone. In contrast, the rifabutin average steady state concentration decreased by 44% when rifabutin was given at 150 mg three times per week with lopinavir/ritonavir. With both dosing regimens, 2 - 5 fold increases of the 25-O-desacetyl- rifabutin metabolite were observed when rifabutin was given with lopinavir/ritonavir compared with rifabutin alone. The different doses of rifabutin had no significant effect on lopinavir/ritonavir plasma concentrations. CONCLUSIONS: Based on these findings, rifabutin 150 mg daily may be preferred when co-administered with lopinavir/ritonavir in patients with HIV-associated tuberculosis. TRIAL REGISTRATION: ClinicalTrials.gov NCT00651066.

Maternal risk factors associated with increased dioxin concentrations in breast milk in a hot spot of dioxin contamination in Vietnam.

This study looked to identify determinants of exposure to dioxin in breast milk from breast-feeding women in a hot spot of dioxin exposure in Vietnam. Breast milk was collected from 140 mothers 1 month after delivery. The risk factors investigated included length of residency, drinking of well water and the frequency of animal food consumption. Cluster analysis was performed to identify dietary patterns of fish and meat portions, fish variety and egg variety. Residency, age and parity were clearly associated with increased dioxin levels. Drinking well water and the consumption of marine crab and shrimps were related to higher levels of furans in breast milk. The consumption of quail eggs also appeared to be associated with increased levels of some dioxin isomers in this area. Some mothers who ate no or less meat than fish and mothers who consumed more freshwater fish than marine fish had lower levels of dioxins in their breast milk. However, the type of water and the eating habits of mothers contributed only partly to the increased dioxin levels in their breast milk; the length of residency was the most important risk factor associated with increased dioxin body burdens of mothers.

Dioxin exposure in breast milk and infant neurodevelopment in Vietnam.

OBJECTIVES: Dioxin levels in the breast milk of mothers residing near hot spots of dioxin contamination areas in South Vietnam remain much higher than in unsprayed areas, suggesting that fetuses and breast-fed infants may be exposed to high levels of dioxins. The present study investigated the association of infant neurodevelopment in early infancy and dioxin exposure during the perinatal period. METHODS: The study involved 216 mother-infant pairs living near the Da Nang airbase, a dioxin contaminated area in Vietnam. Mothers and infants were followed from birth until infants were 4 months old. Dioxin levels in breast milk were measured to estimate the perinatal dioxin exposure, including the infant daily dioxin intake (DDI) via breastfeeding. Infant neurodevelopmental parameters, including cognitive, language and motor domains were assessed at approximately 4 months using the Bayley Scales of Infant and Toddler Development, third edition (Bayley-III). RESULTS: The level of 2,3,7,8-tetrachlorodibenzo-p-dioxin and polychlorinated dibenzo-p-dioxins/furans-toxic equivalents in breast milk and the infant DDI showed significant inverse correlations with neurodevelopmental scores. When the subjects were divided into four groups according to dioxin levels in breast milk, the moderate and high DDI groups had significantly lower cognitive, composite motor and fine motor scores, and the high polychlorinated dibenzo-p-dioxins/furans-toxic equivalents group had significantly lower fine motor score than the low exposure group. For all domains, neurodevelopmental scores were decreased with increase in the level of 2,3,7,8-tetrachlorodibenzo-p-dioxin. CONCLUSION: The present study demonstrates a considerable impact of perinatal dioxin exposure on neurodevelopment in 4-month-old infants living in contaminated areas in Vietnam.

Impact of perinatal dioxin exposure on infant growth: a cross-sectional and longitudinal studies in dioxin-contaminated areas in Vietnam.

Dioxin exposure levels remain elevated in residents living around former US Air Force bases in Vietnam, indicating potential adverse impacts on infant growth. In this study, 210 mother-infant pairs in dioxin-contaminated areas in Vietnam were recruited at the infants' birth and followed up for 4 months. Perinatal dioxin exposure levels were estimated by measurement of polychlorinated dibenzo-p-dioxins/furans toxic equivalent (PCDDs/Fs-TEQ) in breast milk. The infants' size was measured at birth and 1 and 4 months after birth, and neurodevelopment was evaluated using the Bayley Scales III at 4 months of age. Among 4 dioxin groups (<25, 25-50, 50-75, ≥75 percentile of PCDDs/Fs-TEQ), cross-sectional comparisons of body size and neurodevelopment scales and comparisons of longitudinally assessed body size were performed respectively. At birth, head circumference of girls in the ≥75 percentile group was significantly larger than those in the <25 and 50-75 percentile groups. At 4 months of age, the weight and body mass index (BMI) of boys in the ≥75 percentile group were significantly lower than those in the other groups. Increase in weight was significantly lower in the ≥75 percentile group in both sexes from birth to 1 month but only in boys at 1-4 months of age. Estimated marginal mean values in a mixed model of weight and BMI during the first 4 months of life were significantly lower in the ≥75 percentile group in boys. In girls, marginal mean values for head circumference were increased with increase in dioxin levels. Only in boys, cognitive, language, and fine motor scores in the ≥75 percentile group were significantly lower than those in the other groups. These results suggested a considerable impact of perinatal dioxin exposure on infant growth, particularly in boys exposed to dioxins at high level of PCDDs/Fs-TEQ.

Genome-wide association study identifies susceptibility loci for dengue shock syndrome at MICB and PLCE1.

Hypovolemic shock (dengue shock syndrome (DSS)) is the most common life-threatening complication of dengue. We conducted a genome-wide association study of 2,008 pediatric cases treated for DSS and 2,018 controls from Vietnam. Replication of the most significantly associated markers was carried out in an independent Vietnamese sample of 1,737 cases and 2,934 controls. SNPs at two loci showed genome-wide significant association with DSS. We identified a susceptibility locus at MICB (major histocompatibility complex (MHC) class I polypeptide-related sequence B), which was within the broad MHC region on chromosome 6 but outside the class I and class II HLA loci (rs3132468, P(meta) = 4.41 × 10(-11), per-allele odds ratio (OR) = 1.34 (95% confidence interval: 1.23-1.46)). We identified associated variants within PLCE1 (phospholipase C, epsilon 1) on chromosome 10 (rs3765524, P(meta) = 3.08 × 10(-10), per-allele OR = 0.80 (95% confidence interval: 0.75-0.86)). We identify two loci associated with susceptibility to DSS in people with dengue, suggesting possible mechanisms for this severe complication of dengue.

Dioxin concentrations in breast milk of Vietnamese nursing mothers: a survey four decades after the herbicide spraying.

In an operation by United States Armed Forces during 1961 to 1971, large quantities of herbicides were sprayed in South Vietnam. These herbicides contained 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-tetraCDD), the most toxic congener of dioxins. Several decades after the herbicide spraying ceased, dioxin concentrations in the environment and human remained elevated in the sprayed areas. Breast milk samples from 520 nursing mothers residing in areas including the hot spots as well as the sprayed and unsprayed areas were collected to quantify the levels of dioxins. The total toxic equivalents of 2,3,7,8-substitued PCDDs/PCDFs in breast milk of mothers living in the hot spots, and the sprayed and unsprayed areas were 14.10 pg/g lipid, 10.89 pg/g lipid, and 4.09 pg/g lipid for primiparae and 11.48 pg/g lipid, 7.56 pg/g lipid, and 2.84 pg/g lipid for multiparae, respectively, with significant differences in the values among the three areas. In the hot spots, dioxin levels were highly correlated with the residency of mothers after adjustment for their age and parity.

Sensitivity and specificity of the two sets of PCR primers TH1 and TH2 designed for detecting Helicobacter pylori

Two sets of PCR primers, named TH1 and TH2, were designed to detect Helicobacter pylori. While TH2 primer can detect the bacteria in 97% of cases, TH1 primer can detect only the bacteria in 42% of cases. The specificity of both primers was 100%. Therefore, TH2 primer was proved more sensitivity than TH1 primer and had promise in use to detect Helicobacter pylori