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Recrudescence

Recrudescence: The reappearance or relapse of a disease or symptom, especially after a period of improvement or remission.
This term is commonly used in the context of infectious diseases, where the pathogen may persist in the body and reemerge, causing a resurgence of symptoms.
Researchers and clinicians must be vigilant for signs of recrudescence when monitoring patient progress and designing effective treatment protocols.
Understanding the mechanisms and risk factors for recrudescence is crucial for optimizing disease management and improving patient outcomes.

Most cited protocols related to «Recrudescence»

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Publication 2007
Adult Anopheles Antimalarials artemisinine artenimol Child Chloroquine chrysarobin Coartem Coinfection Combined Modality Therapy Ethics Committees Ethics Committees, Research Hypersensitivity Infection Lumefantrine, Artemether Malaria Microscopy Mosquito Vectors Parasitemia Parasites Parent Patients Pharmaceutical Preparations piperaquine Recrudescence Transmission, Communicable Disease Visually Impaired Persons

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Publication 2016
Adult artenimol BLOOD Cambodians Child Ethics Committees Ethics Committees, Research Genetic Markers Genome Genome-Wide Association Study Infection Legal Guardians Malaria, Falciparum Merozoite Surface Protein 1 Parasites Parent Patients Pharmaceutical Preparations piperaquine Recrudescence Reproduction Short Tandem Repeat
We measured the efficacy of antimalarial compounds against P. yoelii or P. berghei in a ‘4-day test’ [60] as described previously [56] (link). We adapted this assay to measure the therapeutic efficacy against P. falciparum. Cohorts of age matched female (40 to 80, depending on the experiment) NODscid/β2m−/− were injected i.p. daily with hE throughout the experiment. When the mice reached ≥40% of chimerism in peripheral blood (7–9 days after initiation of injections), we infected them i.v. with 20·106 parasites obtained from infected donors and the mice were randomly distributed in groups of n = 3 mice·group−1 (day 0). Treatments were administered from day 3 until day 6 after infection. We measured the percentage of TER-119YOYO-1+ (or SYTO-16+) hE in peripheral blood at day 7 after infection and recrudescence up to day 35 if the parasitemias were below our detection limit (0.01%). We determined the minimum size of each experimental group (n = 3) to detect a reduction of 50% in parasitemia in peripheral blood assuming Type I error α = 0.05 (confidence level) and Type II error β = 0.2 (power of the assay). This sample size was calculated upon the distribution of the decimal logarithm of the mean percentage of TER-119YOYO-1+ parasitized hE, which is normally distributed (log parasitemia 0.334±0.01; n = 327 mice, P>0.2, Kolmogorov–Smirnov test of normality with Lilliefors' correction of significance) (Fig. 5D). The therapeutic efficacy of compounds was expressed as the effective dose (mg·Kg bodyweight−1) that reduces parasitemia by 90% with respect to vehicle treated groups (ED90). All compounds and corresponding vehicles were administered orally at 20 ml·Kg−1 or subcutaneously at 10 ml·Kg−1, as appropriate. Chloroquine is included as quality control for each in vivo assay.
Publication 2008
1,1'-((4,4,7,7-tetramethyl)-4,7-diazaundecamethylene)bis-4-(3-methyl-2,3-dihydro(benzo-1,3-oxazole)-2-methylidine)quinolinium, tetraiodide Antimalarials Biological Assay BLOOD Body Weight Chimerism Chloroquine Donors Females Grouping, Blood Infection Mus Parasitemia Parasites Recrudescence Therapeutics

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Publication 2004
Clone Cells Digestion Genetic Polymorphism Merozoite Surface Protein 1 Nested Polymerase Chain Reaction Oligonucleotide Primers Polymerase Chain Reaction Recrudescence Reinfection Restriction Fragment Length Polymorphism Single Nucleotide Polymorphism Strains
Blood samples were collected into acid-citrate-dextrose tubes (Becton-Dickinson, Franklin Lakes, NJ, USA) before treatment and sent to Institut Pasteur in Cambodia within 24 h. A subset of freshly collected samples was used to do the ex-vivo PSA.7 (link) All samples were cryopreserved in glycerolyte. Red cell pellets were stored at −20°C for molecular studies. Blood spots were prepared on day 0 and when applicable on the day of recrudescence.
Cryopreserved parasites were culture-adapted as described.12 (link) Susceptibility to piperaquine was investigated using in-vitro PSA for culture-adapted parasites and ex-vivo PSA for fresh isolates. Survival rates were assessed microscopically and parasites with a survival rate of at least 10% were considered piperaquine-resistant.7 (link)
msp1, msp2, and glurp polymorphisms were determined to distinguish recrudescent from new infections.13 Sequencing of the K13-propeller domain was used to screen for artemisinin resistance.1 (link) Whole-genome sequencing was done with Illumina paired-reads sequencing.1 (link) Data were integrated into the Whole-genome Data Manager database14 and exomes of piperaquine-resistant and piperaquine-sensitive lines were compared after excluding low-coverage positions (ie, lower than 25% of the genome-wide mean coverage). Genes from highly variable multigene families (var, rifin, phist, and stevor) were excluded.1 (link) SNPs and CNVs were investigated using PlasmoCNVScan and the Phen2gen software (appendix).14
Plasmepsin 2 and mdr1 copy number was determined by qPCR (appendix). Steady-state plasmepsin 2 mRNA concentrations were measured by RT-qPCR (appendix) and plasmepsin 2 protein expression by immunoblotting (appendix).
Publication 2017
acid citrate dextrose artemisinine BLOOD Erythrocytes Exanthema Exome Genes Genetic Polymorphism Genome Infection Merozoite Surface Protein 1 Multigene Family Parasites Pellets, Drug piperaquine plasmepsin Proteins Recrudescence RNA, Messenger Single Nucleotide Polymorphism Specimen Collection Susceptibility, Disease

Most recents protocols related to «Recrudescence»

To distinguish between recrudescence and re-infection, 4 drops of blood from malaria-positive patients were collected on filter paper on day zero before treatment, and on any day of recurrent P. falciparum malaria. Molecular analysis was conducted following the previously described method [19 (link)], with slight modifications. Briefly, blood spotted filter papers were soaked for 24 h in 1 mL of 0.5% saponin-1 phosphate buffered saline. The mixture was washed twice in 1-mL PBS and boiled for 8 min in 100 mL PCR-grade water to release DNA from the cells. To elute the extracted DNA, 150 µL Buffer AE was added to each well using a multichannel pipette and incubated for 1 min at room temperature. This setup was then centrifuged at 2608 RCF for 8 min. DNA was recovered and stored at -80 °C. Nested PCR was performed on the extracted DNA for subsequent genotyping of P. falciparum polymorphic gene loci encoding Merozoite surface protein 2 (MSP-2) using the method described by [20 (link)]. A master mix was prepared according to manufacturer instructions (New England Bio Labs, Massachusetts, USA). 24 µL of the Master Mix was added to the PCR 96 well plate and 25 µL of the master mix was also added to the negative PCR control. The plates were sealed using a thermo-seal plate sealer and placed in the PCR thermo-cycler. Amplification was then performed under the following conditions; denaturation (94 °C), annealing (55 °C), and extension (72 °C). Amplification was confirmed by running the nested PCR product together with a DNA ladder on the QIAxcel capillary electrophoresis. The result was classified as recrudescence if at least one identical MSP2 allele was detected in both ACT pre-treatment and ACT post-treatment blood samples. Blood samples where MSP2 alleles did not match ACT pre- and ACT post-treatment were classified as new infections. Any sample, which failed to amplify was classified as undetermined. Blood samples, which showed recrudescence of parasites during any follow up day were further genotyped for P. falciparum k13 resistance markers. The primers used in this protocol are shown in Table 1.

Showing Merozoite Surface Proteins-2 (MSP-2) Amplification primers

Primer nameSequence (5′ → 3′)Purpose
MSP-2(1)ATGAAGGTAATTAAAACATTGTCTATTATAExternal forward primer
MSP-2(4)ATATGGCAAAAGATAAAACAAGTGTTGCTGExternal reverse primer
MSP-2(A1)CAGAAAGTAAGCCTTCTACTGGInternal forward primer (IC3D7)
MSP-2(A2)GATTTGTTTCGGCATTATTATGAInternal reverse primer (IC3D7)
MSP-2(B1)CAAATGAAGGTTCTAATACTAExternal forward primer (FC27)
MSP-2(B2)GCTTTGGGTCCTTCTTCAGTTGATTCInternal reverse primer (FC27)
Publication 2023
Alleles BLOOD Buffers Cells Electrophoresis, Capillary Genetic Loci Infection Malaria Malaria, Falciparum Membrane Proteins Merozoites Nested Polymerase Chain Reaction Neutrophil Oligonucleotide Primers Parasites Patients Phocidae Phosphates Recrudescence Reinfection Saline Solution Saponin
In this retrospective case-control study, all patients with KD were enrolled between August 2017 and August 2022 at Wuhan Children's Hospital. The diagnosis criteria for KD were based on the guideline issued by the Japan Kawasaki Disease Research Committee in 2020 (16 (link)). MAS diagnosis was made according to the MAS-sJIA-2016 criteria (17 (link)).
Inclusion criteria: (1) individuals younger than 18 years (2); complete or incomplete KD was diagnosed (3); MAS was diagnosed based on the diagnostic criteria. Exclusion criteria: (1) individuals without complete medical records (2); hospitalization for less than 24 h and referral to other hospitals (3); treatment with IVIG or steroids in other hospitals before admission.
Individuals were divided into two groups based on their clinical outcome: KD and KD-MAS groups. In total, 28 cases satisfied the KD-MAS criteria. In the KD group, 4 control cases were chosen for each patient and matched to its control by admission time (±1 week) as the matching factor to control for the effect of seasonal factor (18 (link), 19 (link)). This study was approved by the Ethics Committee of Wuhan Children's Hospital.
Our primary objective was to investigate the early predictor factors for KD-MAS, and the secondary objective was to evaluate the evolution of KD-MAS during medical treatment. IVIG resistance, as a potential predictor factor, was defined as persistent or recrudescent fever at least 36 h and <7 days after the completion of the first IVIG infusion (1 (link)).
Publication 2023
Biological Evolution Diagnosis Ethics Committees, Clinical Fever Hospitalization Hospital Referral Intravenous Immunoglobulins Patients Recrudescence Steroids Youth
We used a data-model assimilation technique based on the Bayesian Melding (BM) algorithm to calibrate and identify locality-specific LF transmission models based on the baseline mf prevalence and vector biting intensity data observed in each of our study sites9 (link). This is done by “melding” the observed baseline data from each site (Supplementary Table 2) with model-generated outputs in order to learn or parameterize models for describing the localized parasite transmission dynamics. The fitted models from each site were then used to quantify the various quantities of interest to this study, viz. estimations of mf thresholds and threshold biting rates, predictions of the impact of various MDA interventions with and without vector control on mf prevalence, and calculations of the probabilities of transmission interruption and recrudescence from using the WHO-set TAS thresholds versus model-derived threshold values once mf prevalences are forecast to cross below these thresholds in each study site.
The BM procedure begins by first specifying a range of plausible parameter values to generate distributions of parameter priors. We then randomly sample from those prior distributions to generate 200,000 parameter vectors, which are then used with the observed ABR in a site to generate predictions of baseline age-specific prevalences. The Sampling Importance Resampling (SIR) algorithm is then used to select N (typically N = 500) parameter vectors, θ, or models applicable to a site based on their likelihoods for describing the observed local baseline prevalence data. This BM fitting procedure normally relies on observed baseline age profiles of mf prevalence9 (link), but, in the present analysis, these data were available only for DoakanTofa and Piapung, while overall community-level mf prevalences were available for the other sites (Mossasso, Kirare, Peneng, Dozanso). In this scenario, the observed overall prevalences from these sites were transformed into theoretical age-infection profiles using: (1) the national demographic profile applicable to the site in question, and (2) by conversion of the community-level mf prevalence to reflect either a plateau, concave or linear age-infection profile known typically to occur in LF endemic regions15 (link). The derived age-prevalence infection data were then used in the model fitting procedures described above, which also effectively allowed the integration of partially observed data into the present LF model.
Publication 2023
Cloning Vectors Infection Parasites Recrudescence Transmission, Communicable Disease
Interventions were modeled by using the SIR-selected parameter vectors/models for simulating the impacts of both currently used as well as proposed MDA-based intervention strategies in reducing the observed baseline LF prevalence in each site to below either the global TAS (1% mf prevalence) or site-specific 95% EP thresholds. When simulating these interventions, the observed MDA regimens and coverages followed in each site were used (Supplementary Table 2), while MDA was assumed to target all residents aged 5 years and above. While the drug-induced mf kill rate and the duration of adult worm sterilization were fixed among the models (Supplementary Table 1), the worm kill rate was left as a free parameter to be estimated from the post-intervention data to account for uncertainty in this drug efficacy parameter. For making mf prevalence forecasts beyond the observations made in each site, predictions arising from the impacts of MDA simulated with and without vector control were carried out for 5 years and 20 years after the stoppage of MDA in each site. Three different MDA regimens: (i) annual MDA with ivermectin and albendazole (IVM+ALB) or diethylcarbamazine and ivermectin (IVM+DEC) as applied in each site, (ii) biannual MDA with the above regimens, and (iii) annual triple drug MDA (IDA: combined ivermectin, diethylcarbamazine and albendazole) were modeled with and without vector control in this study to provide a comparison of the effectiveness of these drug regimens for affecting LF elimination. In these simulations, MDAs are stopped after achieving either the 1% mf TAS threshold or the model-predicted 95% EP threshold in each modeled site but simulations of subsequent changes in mf prevalence with or without VC for the next 20 years were continued to evaluate the probability of LF elimination and the risk of recrudescence of the infection respectively over both the shorter 5-year TAS period and over the longer-term 20 years period (using the assessment methods for calculating the occurrence of either of these events described above). VC is modeled in terms of the impact of long-lasting insecticidal nets (LLINs) with 65% coverage following the equation given in ref. 9 (link). The specific details concerning the different MDA-based scenarios investigated are as listed in Tables 1 and 2.
Note that the estimated 95% EP mf prevalence threshold at ABR was used when carrying out simulations of durations or timelines to break transmission by MDA alone strategies while the corresponding and comparatively higher 95% EP thresholds (obtaining at TBR) for this indicator was employed when modeling the impact of including VC into MDA programs9 (link). The MDA plus MDA and vector control model formulations, parameters and functions used to carry out these simulations are as described previously and provided in Supplementary Information.
Publication 2023
Adult Albendazole Cloning Vectors Diethylcarbamazine Helminthiasis Infection Insecticides Ivermectin Pharmaceutical Preparations Recrudescence SLC6A2 protein, human Sterilization TimeLine Transmission, Communicable Disease Treatment Protocols
We calculated the probability that LF extinction has been achieved in each study site due to the applied intervention by quantifying the proportion of the best-fit SIR model prevalences that were declining or declined to zero (ie. models giving rise to mf prevalence curves with significant negative slopes) by the end of the 5 or 20-year simulation period following crossing of either the pre-TAS threshold of 1% mf or the predicted site-specific 95% EP threshold values, respectively. The recrudescence probability for a given study site was similarly calculated as the proportion of the total SIR-selected model runs that managed to revive and generate positive increases in mf prevalence (i.e., give rise to mf curves with significant positive slopes) by the end of each of the above simulation periods once MDAs are stopped. Finally, the curves having non-significant and fluctuating positive or negative slopes are considered as those exhibiting transient behavior.
Publication 2023
3,4-Methylenedioxyamphetamine Extinction, Psychological Recrudescence Transients

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More about "Recrudescence"

Recrudescence, also known as relapse or resurgence, refers to the reappearance or return of a disease or symptom after a period of improvement or remission.
This phenomenon is commonly observed in the context of infectious diseases, where the causative pathogen may persist in the body and reemerge, leading to a resurgence of symptoms.
Understanding the mechanisms and risk factors for recrudescence is crucial for optimizing disease management and improving patient outcomes.
Researchers and clinicians must be vigilant for signs of recrudescence when monitoring patient progress and designing effective treatment protocols.
Factors such as host immune response, pathogen persistence, and environmental conditions can all contribute to the risk of recrudescence.
In the field of molecular biology, tools like the QIAamp DNA Mini Kit and QIAamp DNA Blood Midi Kit can be used to extract high-quality DNA samples from various sources, which is essential for detecting and monitoring the presence of pathogens that may lead to recrudescence.
Gel Doc systems can be used to visualize and analyze DNA samples, while FTA® Whatman paper can be used for convenient sample collection and storage.
Statistical software like Stata can be used to analyze data and identify risk factors for recrudescence, while the use of antimalarial drugs like Coartem and the anesthetic MS-222 can be important in the management of recrudescent diseases.
Additionally, Feature Extraction software can be utilized to analyze and interpret complex data, potentially aiding in the identification of biomarkers or patterns associated with recrudescence.
By leveraging these tools and techniques, researchers and clinicians can gain a deeper understanding of the mechanisms and risk factors for recrudescence, ultimately leading to more effective disease management strategies and improved patient outcomes.