RHA™ anti-progesterone monoclonal antibody, clone p (HMABPY023)

RHA™ mouse anti-progesterone monoclonal antibody, clone p for ELISA, LFIA

Specifications


Host Species
Mouse
Antibody Isotype
IgG
Clone
p
Species Reactivity
N/A
Immunogen
Progesterone [KLH]
Conjugate
Unconjugated

Applications


Application Notes
Indirect ELISA IC50: 0.5 ppb
Matched pair conjugate available for Progesterone antibody:
Progesterone-11 [BSA] (Catalog # DAG3019)
Progesterone-11 [BSA](Catalog # DAG1278)
*Suggested working dilutions are given as a guide only. It is recommended that the user titrates the product for use in their own experiment using appropriate negative and positive controls.

Target


Alternative Names
progesterone; Pregnenedione

Citations


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References


Modeling the release of food bioactive ingredients from carriers/nanocarriers by the empirical, semiempirical, and mechanistic models

COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY

Authors: Malekjani, Narjes; Jafari, Seid Mahdi

The encapsulation process has been utilized in the field of food technology to enhance the technofunctional properties of food products and the delivery of nutraceutical ingredients via food into the human body. The latter application is very similar to drug delivery systems. The inherent sophisticated nature of release mechanisms requires the utilization of mathematical equations and statistics to predict the release behavior during the time. The science of mathematical modeling of controlled release has gained a tremendous advancement in drug delivery in recent years. Many of these modeling methods could be transferred to food. In order to develop and design enhanced food controlled/targeted bioactive release systems, understanding of the underlying physiological and chemical processes, mechanisms, and principles of release and applying the knowledge gained in the pharmaceutical field to food products is a big challenge. Ideally, by using an appropriate mathematical model, the formulation parameters could be predicted to achieve a specific release behavior. So, designing new products could be optimized. Many papers are dealing with encapsulation approaches and evaluation of the impact of process and the utilized system on release characteristics of encapsulated food bioactives, but still, there is no deep insight into the mathematical release modeling of encapsulated food materials. In this study, information gained from the pharmaceutical field is collected and discussed to investigate the probable application in the food industry.

External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study

BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY

Authors: Christodoulou, E.; Bobdiwala, S.; Kyriacou, C.; Farren, J.; Mitchell-Jones, N.; Ayim, F.; Chohan, B.; Abughazza, O.; Guruwadahyarhalli, B.; Al-Memar, M.; Guha, S.; Vathanan, V.; Gould, D.; Stalder, C.; Wynants, L.; Timmerman, D.; Bourne, T.; Van Calster, B.

Objective To validate externally five approaches to predict ectopic pregnancy (EP) in pregnancies of unknown location (PUL): the M6P and M6NP risk models, the two-step triage strategy (2ST, which incorporates M6P), the M4 risk model, and beta human chorionic gonadotropin ratio cut-offs (BhCG-RC). Design Secondary analysis of a prospective cohort study. Setting Eight UK early pregnancy assessment units. Population Women presenting with a PUL and BhCG >25 IU/l. Methods Women were managed using the 2ST protocol: PUL were classified as low risk of EP if presenting progesterone <= 2 nmol/l; the remaining cases returned 2 days later for triage based on M6P. EP risk >= 5% was used to classify PUL as high risk. Missing values were imputed, and predictions for the five approaches were calculated post hoc. We meta-analysed centre-specific results. Main outcome measures Discrimination, calibration and clinical utility (decision curve analysis) for predicting EP. Results Of 2899 eligible women, the primary analysis excluded 297 (10%) women who were lost to follow up. The area under the ROC curve for EP was 0.89 (95% CI 0.86-0.91) for M6P, 0.88 (0.86-0.90) for 2ST, 0.86 (0.83-0.88) for M6NP and 0.82 (0.78-0.85) for M4. Sensitivities for EP were 96% (M6P), 94% (2ST), 92% (N6NP), 80% (M4) and 58% (BhCG-RC); false-positive rates were 35%, 33%, 39%, 24% and 13%. M6P and 2ST had the best clinical utility and good overall calibration, with modest variability between centres. Conclusions 2ST and M6P performed best for prediction and triage in PUL. Tweetable abstract The M6 model, as part of a two-step triage strategy, is the best approach to characterise and triage PULs.

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