In this study, predictive mathematical models were developed to predict the kinetics of Listeria monocytogenes growth in the mixed fresh-cut vegetables, which is the most popular ready-to-eat food in the world, as a function of temperature (4, 10, 20 and $30^{\circ}C$). At the specified storage temperatures, the primary growth curve fit well ($r^2$=0.916~0.981) with a Gompertz and Baranyi equation to determine the specific growth rate (SGR). The Polynomial model for natural logarithm transformation of the SGR as a function of temperature was obtained by nonlinear regression (Prism, version 4.0, GraphPad Software). As the storage temperature decreased from $30^{\circ}C$ to $4^{\circ}C$, the SGR decreased, respectively. Polynomial model was identified as appropriate secondary model for SGR on the basis of most statistical indices such as mean square error (MSE=0.002718 by Gompertz, 0.055186 by Baranyi), bias factor (Bf=1.050084 by Gompertz, 1.931472 by Baranyi) and accuracy factor (Af=1.160767 by Gompertz, 2.137181 by Baranyi). Results indicate L. monocytogenes growth was affected by temperature mainly, and equation was developed by Gompertz model (-0.1606+$0.0574^*Temp$+$0.0009^*Temp^*Temp$) was more effective than equation was developed by Baranyi model (0.3502-$0.0496^*Temp$+$0.0022^*Temp^*Temp$) for specific growth rate prediction of L.monocytogenes in the mixed fresh-cut vegetables.
Purpose: Diabetic foot ulcer with osteomyelitis is notorious with its complexity and healing difficulties. Bone biopsy is considered to be the gold standard method of guidance for antibiotic therapy. However, it is often replaced by cultures of ulcer swabs or by superficial samples because of the technical difficulties and possible adverse events. In this study, we compared microbiologic results of bone biopsy with those of superficial tissue biopsy or swab culture to investigate concordance and diagnostic value in bone involved diabetic foot ulcers. Methods: This study involved 106 patients with diabetic foot ulcers who showed positive results in bone probing test. Tissue samples for microbiologic tests were collected from all the patients by using superficial cotton swab, superficial tissue biopsy, and bone biopsy. The microbiologic results of bone biopsy were compared with swab culture and superficial tissue biopsy statistically. Results: The positive predictive value of bone probing test for underlying osteomyelitis was 82.1%. Microbiology of the bone biopsy showed same results with those of the swab culture and superficial tissue in 64% and 63%, respectively. Statistical analysis demonstrated that the microbiology of the swab culture or superficial tissue did not coincide with that of the bone biopsy. Conclusion: These results suggest that the microbiologic results of superficial tissue or swab culture do not coincide with those of bony tissue. To select appropriate antibiotic regimen for diabetic ulcer with bone involvement, the specimen for the microbiologic test should be obtained from involved bone.
Ouda, SM;Khairy, AM;Sorour, Ashraf E;Mikhail, Mikhail Nasr
Asian Pacific Journal of Cancer Prevention
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v.16
no.17
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pp.7825-7829
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2015
Background: Egypt has the highest prevalence of HCV infection in the world (~14.7%). Around 10-15% of HCV-infected persons will advance to cirrhosis within the first 20 years. The incidence of HCC is expected to grow in the next two decades, largely due to HCV related cirrhosis, and detection of HCC at an early stage is critical for a favorable clinical outcome. No simple reliable non-invasive marker has been available till now. B2M, a non-glycosylated polypeptide composed of 99 amino acids, is one of the components of HLA class I molecules on the surfaces of all nucleated cells. It has been reported that the level of serum B2M is elevated in patients with chronic hepatitis C and HCV-related HCC when compared to HCV-negative patients or healthy donors. Determining the clinical utility of serum B2M as a marker for disease progression in Egyptian patients with HCV related chronic hepatitis, cirrhosis and hepatocellular carcinoma was the aim of the present study. Materials and Methods: In this analytical cross sectional study 92 participants were included in 4 equal groups: Group (1) non cirrhotic chronic HCV; Group (2) HCV related liver cirrhosis; Group (3) HCC on top of HCV,; and Group (4) healthy controls. History taking, clinical examination, routine labs and abdominal ultrasound were conducted for all patients, PCR and Metavir scores for group (1) patients, and triphasic CT abdomen and AFP for Group (3) patients. B2M levels were measured in serum with a fully-automated IMX system. Results: The mean serum B2M level of Group (1) was $4.25{\pm}1.48{\mu}g/ml$., Group (2) was $7.48{\pm}3.04$, Group (3) was $6.62{\pm}2.49$ and Group (4) was $1.62{\pm}0.63$. Serum B2M levels were significantly higher in diseased than control group (p<0.01) being significantly higher in cirrhosis ($7.48{\pm}3.04$) and HCC groups ($6.62{\pm}2.49$) than the HCV group ($4.25{\pm}1.48$) (p<0.01). There was a significant correlation between B2M Level and ALK, total and direct bilirubin and INR (p<0.05), and a significant inverse correlation between B2M level and albumin, total proteins, HB andWBCS values (p<0.05). There was no significant correlation between B2M level and viral load or Metavir score, largest tumour size or AFP (p>0.05). The best B2M cut-off for HCV diagnosis was 2.6 with a sensitivity of 100%, a specificity of 92%, a positive predictive value (PPV) of 97% and a negative predictive value (NPV) of 100%. The best B2M cut-off for HCC diagnosis was 4.55 which yielded sensitivity, specificity, positive predictive value, negative predictive values of 74%, 62%, 39.5, 87.8% respectively (p-value <0.01) while best cut-off for cirrhosis was 4.9, with sensitivity 74 % and specificity 74%.The sensitivity for HCC diagnosis increased upon B2M and AFP combined estimation to 91%, specificity to 79%, NPV to 95% and accuracy to 83%. Conclusions: Serum B2M level is elevated in HCV related chronic liver diseases and may be used as a marker for HCV disease progression towards cirrhosis and carcinoma.
The objective of this study is to estimate the shelf-life of Tteokgalbi containing dietary fiber extracted from rice bran by using the predictive microbiology. This Tteokgalbi was made with 0%, 1%, 2%, and 3% dietary fiber. The number of total viable cells, anaerobic, psychrotrophic, and heat-stable bacteria and coliforms was calculated during 15 days of storage under $4{\pm}1^{\circ}C$ and the obtained data was applied to Baranyi function. The evaluation of fitness between predicted and observed data showed that these were matched in a satisfactory way. Heat-stable bacteria was detected lower than <1 log CFU/g and coliforms were not detected during the storage. The changes of total viable cells and psychrotrophic bacteria in Tteokgalbi were increased gradually, but dramatically increased after 3 days of storage. The models of total viable cells and anaerobic bacteria showed very similar growth trends and values of growth parameters each other. The estimated shelf-life of each Tteokgalbi was calculated from the predictive model of total viable cells and the estimated shelf-life was 1.7, 2.3, 2.3, and 2.4 days, respectively. The results suggested that the prediction of bacteria growth could be used to evaluate the microbiological safety and determine the shelf-life of Tteokgalbi as ready-to-eat food in the local market.
The aim of this study was to investigate the growth of aerobic bacteria in fresh-cut salad during short-term temperature abuse ($4{\sim}30^{\circ}C$temperature for 1, 2, and 3 h) for 72 h and to develop predictive models for the growth of total viable cells (TVC) based on Predictive food microbiology (PFM). The tool that was used, Pathogen Modeling program (PMP 7.0), predicts the growth of Aeromonas hydrophila (broth Culture, aerobic) at pH 5.6, NaCl 2.5%, and sodium nitrite 150 ppm for 72 h. Linear models through linear regression analysis; DMFit program were created based on the results obtained at 5, 10, 20, and $30^{\circ}C$ for 72 h ($r^2$ >0.9). Secondary models for the growth rate and lag time, as a function of storage temperature, were developed using the polynomial model. The initial contamination level of fresh-cut salad was 5.6 log CFU/mL of TVC during 72 h storage, and the growth rate of TVC was shown to be 0.020~1.083 CFU/mL/h ($r^2$ >0.9). Also, the growth tendency of TVC was similar to that of PMP (grow rate: 0.017~0.235 CFU/mL/h; $r^2=0.994{\sim}1.000$). The predicted shelf life with PMP was 24.1~626.5 h, and the estimated shelf life of the fresh-cut salads with short-term temperature abuse was 15.6~31.1 h. The predicted shelf life was more than two times the observed one. This result indicates a 'fail safe' model. It can be taken to a ludicrous extreme by adopting a model that always predicts that a pathogenic microorganism will grow even under conditions so strict as to be actually impossible.
This study was conducted to assess the relationship between occurrence of gastric cancer and peptic ulcer, and the presence of H. pylori cagA gene and anti-CagA IgG, and to estimate the value of these antibodies in detecting infection by cagA gene-positive H. pylori strains in Saudi patients. The study included 180 patients who were subjected to upper gastrointestinal endoscopy in Taif province and Western region of Saudi Arabia (60 gastric cancer, 60 peptic ulcer, and 60 with non-ulcer dyspepsia). Gastric biopsy specimens were obtained and tested for H. pylori infection by rapid urease test and culture. PCR was performed on the isolated strains and biopsy specimens for detection of the cagA gene. Blood samples were collected and tested for CagA IgG by ELISA. H. pylori infection was detected among 72.8% of patients. The cagA gene and anti-CagA IgG were found in 63.4% and 61.8% of H. pylori-infected patients, respectively. They were significantly (p < 0.01) higher in patients with gastric cancer and peptic ulcer compared with those with non-ulcer dyspepsia. Detection of the CagA IgG was 91.6% sensitive, 89.6% specific, and 90.8% accurate compared with detection of the cagA gene. Its positive and negative predictive values were 93.8% and 86%, respectively. The study showed a significant association between the presence of the cagA gene and gastric cancer and peptic ulcer disease, and between anti-CagA IgG and the cagA gene in Saudi patients. However, a further larger study is required to confirm this finding.
Tariq, Muhammad Usman;Haroon, Saroona;Kayani, Naila
Asian Pacific Journal of Cancer Prevention
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v.16
no.8
/
pp.3147-3152
/
2015
Background: Phylloides tumors are rare breast neoplasms with a variable clinical course depending on the tumor category. Along with histologic features, the role of immunohistochemical staining has been studied in predicting their behavior. Objectives: Our aim was to evaluate the role of CD 10 immunohistochemical staining in predicting survival, recurrence and metastasis in phylloides tumor. We also evaluated correlations of other clinicopathological features with overall and disease-free survival. Materials and Methods: CD10 expression was studied in 82 phylloides tumors divided into recurrent/metastatic and non-recurrent/non-metastatic cohorts. The Chi-square test was applied to determine the significance of differences in CD10 expression between outcome cohorts. Uni and multivariate survival analyses were also performed using log-rank test and Cox regression hazard models. Results: All 3 metastatic cases, 5 out of 6 (83.3%) recurrent cases and 37out of 73 (50.7%) non-recurrent and non-metastatic cases expressed significant (2+ or 3+) staining for CD10. This expression significantly varied between outcome cohorts (p<0.03). Tumor category and histological features including mitotic count and necrosis correlated significantly with recurrence and metastasis. A significant decrease in overall and disease free survival was seen with CD10 positivity, malignant category, increased mitoses and necrosis. Neither CD10 expression nor any other clinicopathologic feature proved to be an independent prognostic indicator in multivariate analysis. Conclusions: CD10 immunohistochemical staining can be used as a predictive tool for phylloides tumor but this expression should be interpreted in conjunction with tumor category.
Young Ju Kim;Kyung Na Rho;Saei Jeong;Gil-Woo Lee;Hee-Ok Kim;Hyun-Ju Cho;Woo Kyun Bae;In-Jae Oh;Sung-Woo Lee;Jae-Ho Cho
IMMUNE NETWORK
/
v.23
no.4
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pp.35.1-35.16
/
2023
Defining the molecular dynamics associated with T cell differentiation enhances our understanding of T cell biology and opens up new possibilities for clinical implications. In this study, we investigated the dynamics of CD5 expression in CD8+ T cell differentiation and explored its potential clinical uses. Using PBMCs from 29 healthy donors, we observed a stepwise decrease in CD5 expression as CD8+ T cells progressed through the differentiation stages. Interestingly, we found that CD5 expression was initially upregulated in response to T cell receptor stimulation, but diminished as the cells underwent proliferation, potentially explaining the differentiation-associated CD5 downregulation. Based on the proliferation-dependent downregulation of CD5, we hypothesized that relative CD5 expression could serve as a marker to distinguish the heterogeneous CD8+ T cell population based on their proliferation history. In support of this, we demonstrated that effector memory CD8+ T cells with higher CD5 expression exhibited phenotypic and functional characteristics resembling less differentiated cells compared to those with lower CD5 expression. Furthermore, in the retrospective analysis of PBMCs from 30 non-small cell lung cancer patients, we found that patients with higher CD5 expression in effector memory T cells displayed CD8+ T cells with a phenotype closer to the less differentiated cells, leading to favorable clinical outcomes in response to immune checkpoint inhibitor (ICI) therapy. These findings highlight the dynamics of CD5 expression as an indicator of CD8+ T cell differentiation status, and have implications for the development of predictive biomarker for ICI therapy.
Jiang, Li Juan;Wu, Wen Juan;Wu, Hai;Ryang, Son Sik;Zhou, Jian;Wu, Wei;Li, Tao;Guo, Jian;Wang, Hong Hai;Lu, Shui Hua;Li, Yao
Journal of Microbiology and Biotechnology
/
v.22
no.9
/
pp.1301-1306
/
2012
We combined real-time RT-PCR and real-time PCR (R/P) assays using a hydrolysis probe to detect Mycobacterium tuberculosis complex (MTBC)-specific 16S rRNA and its rRNA gene (rDNA). The assay was applied to 28 non-respiratory and 207 respiratory specimens from 218 patients. Total nucleic acids (including RNA and DNA) were extracted from samples, and results were considered positive if the repeat RT-PCR threshold cycle was ${\leq}35$ and the ratio of real-time RT-PCR and real-time PCR load was ${\geq}1.51$. The results were compared with those from existing methods, including smear, culture, and real-time PCR. Following resolution of the discrepant results between R/P assay and culture, the overall sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) of all samples (including non-respiratory and respiratory specimens) were 98.2%, 97.2%, 91.7%, and 99.4%, respectively, for R/P assay, and 83.9%, 89.9%, 72.3%, and 94.7%, respectively, for real-time PCR. Furthermore, the R/P assay of four patient samples showed a higher ratio before treatment than after several days of treatment. We conclude that the R/P assay is a rapid and accurate method for direct detection of MTBC, which can distinguish viable and nonviable MTBC, and thus may guide patient therapy and public health decisions.
The objective of this study was to develop software to predict the kinetic behavior and the probability of foodborne bacterial growth on processed meat products. It is designed for rapid application by non-specialists in predictive microbiology. The software, named Foodborne bacteria Animal product Modeling Equipment (FAME), was developed using Javascript and HTML. FAME consists of a kinetic model and a probabilistic model, and it can be used to predict bacterial growth pattern and probability. In addition, validation and editing of model equation are available in FAME. The data used by the software were constructed with 5,400 frankfurter samples for the kinetic model and 345,600 samples for the probabilistic model using a variety of combinations including atmospheric conditions, temperature, NaCl concentrations and $NaNO_2$ concentrations. Using FAME, users can select the concentrations of NaCl and $NaNO_2$ meat products as well as storage conditions (atmosphere and temperature). The software displays bacterial growth patterns and growth probabilities, which facilitate the determination of optimal safety conditions for meat products. FAME is useful in predicting bacterial kinetic behavior and growth probability, especially for quick application, and is designed for use by non-specialists in predictive microbiology.
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