Prediction of shear wave velocity from petrophysical data utilizing intelligent systems: An example from a sandstone reservoir of Carnarvon Basin, Australia

Shear wave velocity associated with compressional wave velocity can provide the accurate data for geophysical study of a reservoir. These so called petroacoustic studies have important role in reservoir characterization such as lithology determination, identifying pore fluid type, and geophysical interpretation. In this study, a fuzzy logic, a neuro-fuzzy and an artificial neural network approaches were used as intelligent tools to predict shear wave velocity from petrophysical data. The petrophysical data of two wells were used for constructing intelligent models in a sandstone reservoir of Carnarvon Basin, NW Shelf of Australia. A third well of the field was used to evaluate the reliability of the models. The results show that intelligent models have been successful for prediction of shear wave velocity from conventional well log data

To Protect and to Preserve: Novel Preservation Strategies for Extracellular Vesicles

Extracellular vesicles (EVs)-based therapeutics are based on the premise that EVs shed by stem cells exert similar therapeutic effects and these have been proposed as an alternative to cell therapies. EV-mediated delivery is an effective and efficient system of cell-to-cell communication which can confer therapeutic benefits to their target cells. EVs have been shown to promote tissue repair and regeneration in various animal models such as, wound healing, cardiac ischemia, diabetes, lung fibrosis, kidney injury, and many others. Given the unique attributes of EVs, considerable thought must be given to the preservation, formulation and cold chain strategies in order to effectively translate exciting preclinical observations to clinical and commercial success. This review summarizes current understanding around EV preservation, challenges in maintaining EV quality, and also bioengineering advances aimed at enhancing the long-term stability of EVs

Modelowanie niezawodnościowe dwuwymiarowych danych dotyczących okresu eksploatacji z wykorzystaniem dwuwymiarowego rozkładu Weibulla z badań nad wywrotkami kopalnianymi

An engineering system can exhibit two- or multi-dimensions in its lifetime. As the classical univariate distribution cannot model this multi-dimensional characteristic, it is necessary to extend it to multivariate distribution in order to capture the multi-dimensional characteristics. This paper proposes a bivariate Weibull distribution that combines two classical Weibull models by a common exponent. The common exponent can represent the correlation between the two dimensions. A ratio likelihood test is proposed to test the significance of the correlation between the two dimensions. To solve the parameter estimation problem, this paper suggests a Bayesian method. Moreover, a goodness of fit test method is developed to visually check the fitness of the model. A case study considering mining trucks is presented to apply the bivariate Weibull distribution to model the two-dimensional life data.Systemy inżynieryjne można charakteryzować za pomocą dwóch lub więcej wymiarów dotyczących okresu ich eksploatacji (np. przebieg i czas pracy pojazdu). Ponieważ klasyczny rozkład jednowymiarowy nie wystarcza do zamodelowania tej wielowymiarowej charakterystyki, konieczne jest wykorzystanie rozkładu wielowymiarowego, który pozwala uchwycić wielowymiarowość cyklu życia systemu. W artykule zaproponowano dwuwymiarowy rozkład Weibulla, który łączy w sobie dwa klasyczne modele Weibulla za pomocą wspólnego wykładnika. Wspólny wykładnik może reprezentować korelację między dwoma wymiarami. Zaproponowano test ilorazu wiarygodności, który umożliwia badanie istotności korelacji pomiędzy dwoma wymiarami. Do rozwiązania problemu estymacji parametrów zastosowano metodę bayesowską. Ponadto opracowano metodę badania dopasowania modelu do danych empirycznych służącą do wizualizacji dopasowania modelu. Przedstawiono studium przypadku dotyczące wywrotek kopalnianych, w którym dwuwymiarowy rozkład Weibulla zastosowano do modelowania dwuwymiarowych danych dotyczących okresu eksploatacji tych pojazdów

High Expression of FOXP3 mRNA in Blood and Urine as a Predictive Marker in Kidney Transplantation

Background: Diagnosis of allograft dysfunction by noninvasive biomarker tests is preferable to invasive allograft biopsies and has been extensively considered in recent years. This study aims to evaluate blood and urinary forkhead box P3 (FOXP3) messenger RNA (mRNA) expression in renal transplant recipients in an attempt to determine whether differential diagnosis of graft dysfunction is feasible using mRNA profiles. Methods: We analyzed FOXP3 mRNA expression in paired urinary and peripheral blood mononuclear cell (PBMC) samples. A total of 91 kidney transplant recipients enrolled in this study that were classified into 3 groups: biopsy-proven acute rejection (AR; n = 27), chronic allograft nephropathy (n = 19), and well-functioning graft (n = 45). The FOXP3 mRNA expression was quantified by TaqMan probe real-time polymerase chain reaction. Results: Acute rejection patients had a higher expression level of transcription factor FOXP3 compared to the chronic nephropathy and control groups. Analysis of receiver operating characteristic curves showed that rejection could be diagnosed with 100 sensitivity and 96 specificity in urine, and 92 sensitivity and 86 specificity in PBMC samples using the optimal FOXP3 mRNA cutoff value. We subdivided the AR group into progressive and nonprogressive patients, which showed a significant difference in FOXP3 mRNA expression. This result confirmed the role of FOXP3 as a diagnostic marker in predicting transplantation outcomes. Conclusion: Our results suggested that elevated expression of FOXP3 in blood and urine samples from kidney transplant recipients could be a useful noninvasive biomarker to diagnose graft dysfunction

Dynamic variation of kidney injury molecule-1 mRNA and protein expression in blood and urine of renal transplant recipients: a cohort study

BACKGROUND: Acute renal dysfunction still constitutes a highly significant obstacle to renal transplantation outcome. Kidney injury molecule-1 is highly upregulated in proximal tubular cells and shed into the urine and blood circulation following kidney injury. The aim of current cohort study was to evaluate the urine KIM-1 (uKIM-1) mRNA expression level and its protein concentration in blood and urine samples to determine whether sequential monitoring of KIM-1 in renal allograft recipients is a reliable biomarker for predicting the clinical status and outcome. METHODS: Both uKIM-1 mRNA expression level and the level of serum and uKIM-1 protein concentration in the 52 renal transplant recipients were respectively quantified using real-time PCR and ELISA methods at 2, 90 and 180 days after transplantation. RESULT: KIM-1 mRNA and protein expression level in the blood and urine samples of patients with graft dysfunction was significantly higher than patients with well-functioning graft on days 2, 90 and 180 after transplantation. Receiver-operating characteristic curve analysis of mRNA and protein expression levels showed that urinary and blood KIM-1 at months 3 and 6 could predict acute renal dysfunction at 6 months and 1 year after transplantation. CONCLUSION: Sequential monitoring of uKIM-1 mRNA expression level and its protein concentration in the serum and urine samples of renal transplant patients suggests that KIM-1 could be a sensitive and specific biomarker for early diagnosis and prognosis of kidney allograft injury

High expression of TIM-3 and KIM-1 in blood and urine of renal allograft rejection patients

Background-T cell immunoglobulin and mucin domain 3 (TIM-3) is involved in alloimmune and autoimmune responses, as well as tolerance induction in kidney transplantation. Kidney injury molecule-1 (KIM-1) is highly expressed in epithelial cells of the injured proximal tubule. In this study, we have investigated both urinary and blood TIM-3 mRNA expressions, urinary KIM-1 mRNA expression, and urinary and serum KIM-1 proteins in renal allograft recipients diagnosed with acute allograft rejection (AR) and chronic allograft dysfunction (CAD), as well as those with well-functioning transplants (WFG). Methods: We divided 85 patients into the following groups: AR (n = 24), CAD (n = 19), and WFG (n = 42). TIM-3 and KIM-1 mRNA expressions were quantified using real-time reverse-transcription TaqMan probe polymerase chain reaction (RT-PCR). An ELISA test was used to measure the amount of KIM-1 protein in serum and urine samples. Results: AR and CAD patients had significantly greater urinary and blood TIM-3 mRNA expressions, urinary KIM-1 mRNA expression, and urinary and serum KIM-1 proteins compared to WFG patients. Receiver operating characteristic (ROC) analysis showed that these molecules discriminated Allograft rejections from WFG. Conclusion: Quantification of TIM-3 and KIM-1 mRNA expressions, along with KIM-1 protein measurements in urine and blood could be employed as promising tools for noninvasive diagnosis of allograft dysfunction