Peanut allergen characterization and allergenicity throughout development.

Introduction: Peanut allergy (PA) in children is a major concern. There is a need for better biological material for both diagnosis and oral immunotherapy (OIT) treatments. The unique state of seeds at early reproductive stages may affect the allergenicity of storage proteins, and impact clinical diagnostic and OIT protocols. The objective of this study was to evaluate the major allergen content in sequential seed developmental stages and monitor allergenicity via specific IgE binding quantification and skin prick testing. Methods: Seeds were collected from peanut plants and sorted into five developmental stages: initial (S1), developing (S2), full-size without coloration (S3), full-size with coloration (S4), and fully mature (S5) seeds. Samples were characterized by RNA-Seq, ELISA, and immunohistochemistry. Lyophilized, ground preparations were used for evaluation of skin test responses in sixty challenge-proven PA children. Results: Gene expression, protein content, and specific IgE binding of allergenic proteins increased throughout seed maturation and development. An expression bias towards the less allergenic A-genome copy of the major allergen Ara h 2 was found in earlier stages, especially in stage S2. Immunohistochemical staining showed that Ara h 2 is more dispersed in the cell and less accumulated within organized bodies at stage S2 versus stage S4. Significant differences were found in mean wheal responses between the commercial peanut extract (equivalent to stage S5) and stages S1 and S2, but not with stage S4, upon skin prick testing in subjects with PA. Discussion: The observed decrease in peanut-specific IgE binding of immature peanut seeds may be a result not only of decreased amounts of allergenic proteins, but also of profound changes in seed composition and conformation. This may be significant for developing a safer and more effective peanut OIT protocol.

Peanut oral immunotherapy using an extensively heated and baked novel composition of peanuts.

BACKGROUND: Oral immunotherapy (OIT) is an increasingly acceptable therapeutic option for peanut-allergic (PA) children, despite significant side effects. Major peanut allergenic proteins are heat-resistant and are not rendered hypoallergenic after baking or cooking. Lyophilized peanut protein-MH (LPP-MH) is a novel composition from developing peanuts, enabling cooking-induced reduction in allergenicity. We aimed to explore the safety and efficacy of OIT, with extensively heated and baked (EHEB) LPP-MH in PA children. METHODS: In a single-arm, single-center, pilot study, PA children with a single highest tolerated dose of <100 mg peanut protein were placed on a 40-week OIT protocol with 300 mg daily of heat-treated LPP-MH. A repeat open peanut food challenge was performed after 40 weeks of treatment and at a 6-12 months of follow-up visit. RESULTS: Thirty-three children with PA were enrolled, with a mean cumulative tolerated dose (MCTD) of 71.2 mg PP (95% CI 45-100 mg). After 40 weeks, 32/33 patients were able to consume more than 300 mg of natural PP, with MCTD of 1709 mg (CI 365-3675 mg). There were no severe allergic reactions requiring epinephrine, during any of the observed LPP-MH challenges or any treatment related doses at home. After 6-12 months on daily maintenance, the MCTD was 8821 mg (95% CI 1930-13,500 mg). This enabled most children age-appropriate dietary inclusion of peanuts. CONCLUSION: An OIT protocol with heat-treated LPP-MH, a novel composition from developing peanuts, seems a potentially safe and efficacious OIT modality for PA children, enabling the introduction of dietary levels of peanut proteins in highly allergic PA children. Validation in randomized controlled studies is mandated.

Clinical evaluation and determinants of response to HBI0101 (BCMA CART) therapy in relapsed/refractory multiple myeloma.

ABSTRACT: HBI0101 is an academic chimeric antigen receptor T-cell (CART)-targeted to B-cell maturation antigen (BCMA) for the treatment of relapsed and refractory multiple myeloma (R/RMM) and light chain amyloidosis. Herein, we present the phase 1b/2 results of 50 heavily pretreated patients with R/RMM dosed with 800 × 106 CART cells. Inclusion criteria were relatively permissive (i.e., performance status and baseline organ function) and consequently, approximately half of the enrolled patients would have been ineligible for pivotal clinical trials. The median time elapsed from patient enrollment until CART delivery was 25 days (range, 14-65). HBI0101-related toxicities included grade 1 to 3 cytokine release syndrome, grade 3 to 4 hematologic toxicities, and grade 1 to 2 immune effector cell-associated neurotoxicity syndrome. Responses were achieved in 90% of the patients, 56% achieved stringent and complete response, and 70% reached a minimal residual disease negativity. Within a median follow-up of 12.3 months, the median progression-free survival (PFS) was 11.0 months (95% confidence interval [CI], 6.2-14.6), and the overall survival was not reached (95% CI, 13.3 to not reached). Multivariable analysis on patient/disease and CART-related characteristics revealed that high-risk cytogenetic, extramedullary disease, and increased number of effector-memory T cells in CART products were independently associated with inferior PFS. In conclusion, comprehensive analyses of the parameters affecting the response to CART therapy are essential for improving patients' outcome. This trial was registered at www.ClinicalTrials.gov as #NCT04720313.

A Multivariate Meta-Analysis for Optimizing Cell Counts When Using the Mechanical Processing of Lipoaspirate for Regenerative Applications.

Lipoaspirate has become the preferred source for regenerative cells. The mechanical processing of lipoaspirate has advantages over enzymatic processing but has a lower yield of regenerative cells. A review of the literature shows different techniques of extraction, but the ideal method or combination has not been determined. METHODS: A comprehensive literature search was focused on the mechanical processing of lipoaspirate, without the use of enzymes. Data from the articles were integrated by utilizing a multivariate meta-analysis approach and used to create a statistical-based predictive model for a combination of multiple variables. RESULTS: Starting with 10,000 titles, 159 articles were reviewed, and 6 met the criteria for inclusion and exclusion. The six studies included data on 117 patients. Sixteen factors were analyzed and six were identified as significant. The predictive profilers indicated that the optimal combination to maximize the cell yield was: a centrifuge force of 2000× g, a centrifuge time of 10 min, a cannula diameter of 2 mm, and an intra-syringe number of passes of 30. The optimal patient factors were a higher BMI and younger age. CONCLUSIONS: The novelty of the method used here was in combining data across different studies to understand the effect of the individual factors and in the optimization of their combination for mechanical lipoaspirate processing.

Development of an Operational Digital Twin of a Locomotive Parking Brake for Fault Diagnosis.

In recent years, a growing role in digital technologies has been filled by model-based digital twinning. A digital twin produces a one-to-one mapping of a physical structure, operating in the digital domain. Combined with sensor technology and analytics, a digital twin can provide enhanced monitoring, diagnostic, and optimization capabilities. This research harnesses the significant capabilities of digital twining for the unmitigated challenge of fault type classification of a locomotive parking brake. We develop a digital twin of the locomotive parking brake and suggest a method for fault type classification based on the digital twin. The diagnostic ability of the method is demonstrated on a large experimental dataset.

Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective.

In Industry 4.0, smart manufacturing is facing its next stage, cybermanufacturing, founded upon advanced communication, computation, and control infrastructure. Cybermanufacturing will unleash the potential of multi-modal manufacturing data, and provide a new perspective called computation service, as a part of service-oriented architecture (SOA), where on-demand computation requests throughout manufacturing operations are seamlessly satisfied by data analytics and machine learning. However, the complexity of information technology infrastructure leads to fundamental challenges in modeling and analysis under cybermanufacturing, ranging from information-poor datasets to a lack of reproducibility of analytical studies. Nevertheless, existing reviews have focused on the overall architecture of cybermanufacturing/SOA or its technical components (e.g., communication protocol), rather than the potential bottleneck of computation service with respect to modeling and analysis. In this paper, we review the fundamental challenges with respect to modeling and analysis in cybermanufacturing. Then, we introduce the existing efforts in computation pipeline recommendation, which aims at identifying an optimal sequence of method options for data analytics/machine learning without time-consuming trial-and-error. We envision computation pipeline recommendation as a promising research field to address the fundamental challenges in cybermanufacturing. We also expect that computation pipeline recommendation can be a driving force to flexible and resilient manufacturing operations in the post-COVID-19 industry.

A clinical pathway for the diagnosis of sesame allergy in children.

Background: Sesame allergy (SA) is a common cause of life-threatening, persistent food allergy, not only in the Middle East and Asia, but increasingly worldwide. Commercially available tests such as extracts for skin testing or specific IgE for sesame or its components in serum, have very limited predictive values. Therefore the diagnosis is dependent on the performance of oral food challenges (OFC), frequently avoided in children, due to time and resource constraints, as well as the risk of anaphylaxis. In the current study we aimed to develop a simple, readily available, clinical tool, able to predict sesame OFC outcomes in children. Methods: Children with a history of SA were evaluated in the outpatient allergy clinic. All children underwent natural sesame OFC, with an additional baked-sesame challenge offered to children with SA. Clinical data were compared between the sesame tolerant (ST) and SA groups. Machine-learning tools were applied, to create a simple, clinically driven, decision tree analysis (DTA), predicting the outcome of sesame OFCs and the diagnosis of SA. Results: One hundred four children, mean age 47.2 months, 58% boys were included, with a high prevalence of additional food allergies, atopic dermatitis, asthma, and rhinitis. Following OFC, 56 (54%) were diagnosed as ST and 48 (46%) SA. Among SA children, 85% were able to consume baked-sesame in equal or higher protein amounts compared to natural sesame paste. Compared to ST, SA children had a tendency towards a higher incidence of allergic rhinitis (5% Vs 17%, p = 0.062), multiple food allergies (3.6% vs 12.5%, p = 0.09) and requiring medical treatment after the initial SA reaction (27% vs 41%, p = 0.022). As a group, skin tests with both commercial and natural tahini paste differed significantly between ST and SA (mean wheal in mm, for extract 4.2 vs 13.4, p < 0.001 and for natural sesame paste 6.7 vs 24.4, p < 0.001), However, the PPV of any individual test was only between 60%-85%. Our exploratory, clinical DTA, predicted OFC outcomes and the presence or absence of Sesame Allergy, with ≥96% positive (PPV) and negative (NPV) predictive values. Conclusion: OFCs remain the gold standard for the diagnosis of Sesame Allergy and are indicated to define ST/SA status even in highly atopic patients with previous immediate allergic reactions to sesame. A decision-tree analysis based on clinical parameters easily available in every allergy clinic, can predict the outcome of sesame OFC in the vast majority of children, increasing the safety and availability of such diagnostic procedures.

Your best day: An interactive app to translate how time reallocations within a 24-hour day are associated with health measures.

Reallocations of time between daily activities such as sleep, sedentary behavior and physical activity are differentially associated with markers of physical, mental and social health. An individual's most desirable allocation of time may differ depending on which outcomes they value most, with these outcomes potentially competing with each other for reallocations. We aimed to develop an interactive app that translates how self-selected time reallocations are associated with multiple health measures. We used data from the Australian Child Health CheckPoint study (n = 1685, 48% female, 11-12 y), with time spent in daily activities derived from a validated 24-h recall instrument, %body fat from bioelectric impedance, psychosocial health from the Pediatric Quality of Life Inventory and academic performance (writing) from national standardized tests. We created a user-interface to the compositional isotemporal substitution model with interactive sliders that can be manipulated to self-select time reallocations between activities. The time-use composition was significantly associated with body fat percentage (F = 2.66, P < .001), psychosocial health (F = 4.02, P < .001), and academic performance (F = 2.76, P < .001). Dragging the sliders on the app shows how self-selected time reallocations are associated with the health measures. For example, reallocating 60 minutes from screen time to physical activity was associated with -0.8 [95% CI -1.0 to -0.5] %body fat, +1.9 [1.4 to 2.5] psychosocial score and +4.5 [1.8 to 7.2] academic performance. Our app allows the health associations of time reallocations to be compared against each other. Interactive interfaces provide flexibility in selecting which time reallocations to investigate, and may transform how research findings are disseminated.

Oral immunotherapy for children with a high-threshold peanut allergy.

BACKGROUND: Between 25% and 30% of children with peanut allergy (PA) have a relatively high-threshold peanut allergy (HTPA), with a single maximal tolerated dose (SMTD) higher than 100 mg of peanut protein (PP). However, this threshold may decrease with time, age, exercise, illness, sleep deprivation, and other covariates. OBJECTIVE: To explore the feasibility of a simplified oral immunotherapy (OIT) protocol in a group of children with HTPA. METHODS: Children with PA with an SMTD higher than 100 mg were placed on a 40-week OIT protocol of either 300 mg/d of PP or 100 mg/d for 20 weeks followed by 300 mg/d for 20 weeks. A repeat open peanut food challenge was performed after 40 weeks of treatment and at a 6-month follow-up visit. After the 40-week challenge, all children received a maintenance dosage of 2 gPP 3 times a week. RESULTS: A total of 28 children with HTPA were enrolled, with 56% boys, 89% younger than 6 years old, and a mean SMTD of 304 mg (95% confidence interval 229-378). All were placed on the described OIT protocol. Overall, 2 children were not compliant and 3 had allergic reactions at home on the dose previously tolerated in clinic, 23 completed the 40-week protocol, and all were able to consume 2 g of PP. The mean tolerated dosage at the 6-month follow-up was 8 g. This enabled most children age-appropriate dietary inclusion of peanut-containing products. CONCLUSION: In children with HTPA, a simple, fixed-dose OIT can be both safe and efficacious.

Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models.

The response to the COVID-19 pandemic has been highly variable. Governments have applied different mitigation policies with varying effect on social and economic measures, over time. This article presents a methodology for examining the effect of mobility restriction measures and the association between health and population activity data. As case studies, we refer to the pre-vaccination experience in Italy and Israel. Facing the pandemic, Israel and Italy implemented different policy measures and experienced different population behavioral patterns. Data from these countries are used to demonstrate the proposed methodology. The analysis we introduce in this paper is a staged approach using Bayesian Networks and Structural Equations Models. The goal is to assess the impact of pandemic management and mitigation policies on pandemic spread and population activity. The proposed methodology models data from health registries and Google mobility data and then shows how decision makers can conduct scenario analyses to help design adequate pandemic management policies.

The role of statisticians in the response to COVID-19 in Israel: a holistic point of view.

The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. Statisticians in Israel were involved in these processes early in the pandemic in some silos as an ad-hoc unorganized effort. Informal discussions within the statistical community culminated in a roundtable, organized by three past presidents of the Israel Statistical Association, and hosted by the Samuel Neaman Institute in April 2021. The meeting was designed to provide a forum for exchange of views on the profession's role during the COVID-19 pandemic, and more generally, on its influence in promoting evidence-based public policy. This paper builds on the insights and discussions that emerged during the roundtable meeting and presents a general framework, with recommendations, for involving statisticians and statistics in decision-making.

The reproducibility of COVID-19 data analysis: paradoxes, pitfalls, and future challenges.

In the midst of the COVID-19 experience, we learned an important scientific lesson: knowledge acquisition and information quality in medicine depends more on "data quality" rather than "data quantity." The large number of COVID-19 reports, published in a very short time, demonstrated that the most advanced statistical and computational tools cannot properly overcome the poor quality of acquired data. The main evidence for this observation comes from the poor reproducibility of results. Indeed, understanding the data generation process is fundamental when investigating scientific questions such as prevalence, immunity, transmissibility, and susceptibility. Most of COVID-19 studies are case reports based on "non probability" sampling and do not adhere to the general principles of controlled experimental designs. Such collected data suffers from many limitations when used to derive clinical conclusions. These include confounding factors, measurement errors and bias selection effects. Each of these elements represents a source of uncertainty, which is often ignored or assumed to provide an unbiased random contribution. Inference retrieved from large data in medicine is also affected by data protection policies that, while protecting patients' privacy, are likely to reduce consistently usefulness of big data in achieving fundamental goals such as effective and efficient data-integration. This limits the degree of generalizability of scientific studies and leads to paradoxical and conflicting conclusions. We provide such examples from assessing the role of risks factors. In conclusion, new paradigms and new designs schemes are needed in order to reach inferential conclusions that are meaningful and informative when dealing with data collected during emergencies like COVID-19.

Helping reviewers assess statistical analysis: A case study from analytic methods.

Analytic methods development, like many other disciplines, relies on experimentation and data analysis. Determining the contribution of a paper or report on a study incorporating data analysis is typically left to the reviewer's experience and good sense, without reliance on structured guidelines. This is amplified by the growing role of machine learning driven analysis, where results are based on computer intensive algorithm applications. The evaluation of a predictive model where cross validation was used to fit its parameters adds challenges to the evaluation of regression models, where the estimates can be easily reproduced. This lack of structure to support reviews increases uncertainty and variability in reviews. In this paper, aspects of statistical assessment are considered. We provide checklists for reviewers of applied statistics work with a focus on analytic method development. The checklist covers six aspects relevant to a review of statistical analysis, namely: (1) study design, (2) algorithmic and inferential methods in frequentism analysis, (3) Bayesian methods in Bayesian analysis (if relevant), (4) selective inference aspects, (5) severe testing properties and (6) presentation of findings. We provide a brief overview of these elements providing references for a more elaborate treatment. The robustness analysis of an analytical method is used to illustrate how an improvement can be achieved in response to questions in the checklist. The paper is aimed at both engineers and seasoned researchers.

Diagnosis of Peanut Allergy in Preschool Children: The Impact of Skin Testing With a Novel Composition of Peanuts.

Peanut allergy is an increasing concern in younger children. Available bedside diagnostic tools, i.e., prick tests with commercial extracts or peanut-containing foods have only limited predictive values. In a cohort of preschoolers with both a history of allergic reactions and sensitization to peanut proteins, we aimed to characterize the impact of skin tests with a novel composition of peanuts LPP-MH. Almost one quarter (27/110) of preschool children, with a history of allergic reactions to peanuts and positive standard IgE-mediated tests for peanut allergy, can tolerate the reintroduction of peanut proteins into their diet after resolving their allergy and, thus, can avoid adverse health outcomes associated with the false diagnosis. In the younger age group, a quarter of peanut allergic children, display a relatively high threshold, potentially enabling an easier and safer oral immunotherapy protocol in this window of opportunity in childhood. The use of the novel diagnostic skin test, LPP-MH, significantly improves the predictive value of outpatient evaluation for the outcomes of peanut challenge as well as the expected threshold at which the PA child will react, thus, making for a better informed decision of how, when, and where to challenge.

Guided Bone Regeneration with Ammoniomethacrylate-Based Barrier Membranes in a Radial Defect Model.

Large bone defects pose an unsolved challenge for orthopedic surgeons. Our group has previously reported the construction of a barrier membrane made of ammoniomethacrylate copolymer USP (AMCA), which supports the adhesion, proliferation, and osteoblastic differentiation of human mesenchymal stem cells (hMSCs). In this study, we report the use of AMCA membranes to seclude critical segmental defect (~1.0 cm) created in the middle third of rabbit radius and test the efficiency of bone regeneration. Bone regeneration was assessed by radiography, biweekly for 8 weeks. The results were verified by histology and micro-CT at the end of the follow-up. The AMCA membranes were found superior to no treatment in terms of new bone formation in the defect, bone volume, callus surface area normalized to total volume, and the number of bone trabeculae, after eight weeks. Additional factors were then assessed, and these included the addition of simvastatin to the membrane, coating the membrane with human MSC, and a combination of those. The addition of simvastatin to the membranes demonstrated a stronger effect at a similar radiological follow-up. We conclude that AMCA barrier membranes per se and simvastatin delivered in a controlled manner improve bone regeneration outcome.

Implementing Personal Mentoring in an Obstetrics and Gynecology Residency Program-3-Year Evaluation.

OBJECTIVE: To empower residents-in-training through personal mentorship from a senior physician who dedicates time and guidance to their personal development and provides professional and emotional support. METHODS: A structured model of personal mentoring for residents was designed and implemented in the Department of Obstetrics & Gynecology. The process was assessed by a special-purpose survey constructed and reviewed by established medical mentors. The survey examined residents' attitudes towards personal aspects associated with their residency. The questionnaires were filled out anonymously before launching and 1 and 3 years after initiating the personal mentoring process. RESULTS: The residents' reports showed a distinct trend of increased positive attitudes towards the personal mentoring throughout the process. The residents reported on an improvement in the mentors' availability to address personal aspects within the mentoring relationship (empathy, emotional support in deliberations, career guidance, etc.). The general satisfaction with the residency program improved as well. CONCLUSIONS: Mentoring is a significant element in a comprehensive, multi-dimensional process. Integrating personal mentoring into a residency program, with the focus on interpersonal relational characteristics as empathy, availability, open communication, and guidance, led to improvements in residents' professional development and skills. They also received optimal support and guidance in their professional careers and personal deliberations.

A structured graduated protocol with heat denatured eggs in the treatment of egg allergy.

BACKGROUND: Most children with egg allergy (EA) can tolerate extensively heated and baked egg (EHBE). Consumption of EHBE may promote faster resolution of EA; however, no consensus exists as to the required amounts and treatment protocols. OBJECTIVE: To evaluate the efficacy and safety of a structured graduated exposure protocol (SGEP) with EHBE in promoting tolerance to eggs in EA children under 2 years of age. METHODS: In a case-control study, EA children aged < 2 years who were treated with SGEP including EHBE were compared to children treated with strict avoidance. Data were collected from records and telephone questionnaires. Analysis was performed using non-parametric Kaplan-Meier and Cox proportional hazard regression models. RESULTS: Thirty-nine egg-allergic children with a median age at intervention of 16 months (interquartile range: 13-19) were treated with SGEP and followed to a median age of 39 months (26.8-50.0). The median age at resolution of EA was compared to a matched group of 80 children treated with strict avoidance at least until 2 years of age or earlier natural resolution and followed to a median age of 69 months (46-104). The median estimated age at EA resolution in the SGEP group was 24 months (95% CI, 19.5-28.5 months), compared to 78 months (95% CI, 53-102) in the control group, P < .001. At last follow-up, 82% of treated children were tolerant to lightly cooked eggs vs 54% of controls, P = .001. CONCLUSION: A structured protocol with EHBE appears to promote faster resolution of EA.

A Structured Gradual Exposure Protocol to Baked and Heated Milk in the Treatment of Milk Allergy.

OBJECTIVE: To evaluate the efficacy and safety of a structured gradual exposure protocol (SGEP) with extensively heated and baked milk in promoting allergy resolution in children with cow milk allergy (CMA). STUDY DESIGN: In a case control study, children with CMA aged 1-4 years who were treated with SGEP including extensively heated and baked milk, were compared with children treated with strict avoidance. Data were collected from medical records and from validated telephone questionnaires. Data analysis was performed using a nonparametric Kaplan-Meier and proportional hazard Cox regression model, after evaluation of the adequacy of the case control matching. RESULTS: There were 43 children with milk allergy-26 (62%) males with a mean age at intervention of 21 months (range, 12-47 months)-who were treated with SGEP and followed to a mean age of 40 months (range, 20-82 months). The median age at resolution of CMA was compared with a matched group of 67 children treated with strict avoidance at least until 4 years of age or followed until earlier resolution, with a mean age at follow-up of 71 months (range, 11-176 months). The median estimated age at CMA resolution in the SGEP group was 36 months (95% CI, 34.5-49.7) compared with 98 months (95% CI, 82.4-114.1) in controls (P < .001). At last follow-up, 86% of treated children were tolerant to unheated milk proteins vs 52% of controls (P = .003). CONCLUSION: A structured protocol with extensively heated and baked milk seems to promote faster resolution of CMA.

Synchronizing the release rates of salicylate and indomethacin from degradable chitosan hydrogel and its optimization by definitive screening design.

Three types of ionically crosslinked (with citric acid) chitosan discs were loaded with the highly water- soluble drug, sodium salicylate (SS) and the poorly water-soluble drug, indomethacin (Ind). In separate experiments the hydrated discs were immersed in a de-crosslinking solution comprising of different concentrations of calcium chloride, which induced a controlled erosion of the discs, a process which was optimized to synchronize the release rates of the two drugs over a predetermined period of time. The optimization was accomplished by manipulating six factors: chitosan MW, its amount in the formulation, the concentration of the crosslinker agent, the concentration of the de-crosslinking agent in the dissolution medium, its pH and its temperature. A computerized multifactorial definitive screening design analysis assisted in minimizing the number of experiments. The quotient of the SS to Ind release rates, the difference factor f1, the similarity factor f2 and the combination of f1 and f2 were determined as the experimental responses. The computerized prediction profilers that were used to simulate the contribution of the experimental factors and their effect on the experimental responses led to a successful erodible formulation with a concomitant release of the two drugs over 150 min.

Salivary Neutrophil Gelatinase-Associated Lipocalin Sampling Feasibility in Acute Renal Colic.

PURPOSE: Neutrophil gelatinase-associated lipocalin (NGAL) levels in the serum and urine are predictive biomarkers of acute kidney injury with correlation to complication and survival in major surgery. Salivary levels of NGAL during acute renal colic may reflect the degree of renal injury as it appears in different compartments encompassing body response in time perspective. Our aim is to evaluate and examine the feasibility and correlation of salivary NGAL with serum and urine levels in acute renal colic event. MATERIALS AND METHODS: A prospective controlled study of all patients presenting to the emergency room with acute renal colic event diagnosed with single ureteral stone obstruction by noncontrast CT. Saliva, urine, and blood samples were collected in patients and a control group during the first morning of admission. RESULTS: The study groups consisted of 44 patients and 13 controls, mean age 47 ± 15 years, body mass index 29 ± 6, mean stone size 6 ± 4 mm, mean creatinine levels 1.3 ± 0.7 mg/dL, mean white blood count 10,900 ± 3100 counts per field, and C-reactive protein 29 ± 55. Serum (190 ± 120 ng/mL vs 81 ± 24; p < 0.001) and predominantly salivary (474 ± 185 vs 328 ± 134 ng/mL; p < 0.05) NGAL levels were significantly elevated in patients compared with controls. CONCLUSIONS: Salivary NGAL sampling is feasible during the acute phase of renal colic. High levels of salivary NGAL are observed in a single sampling during acute ureteral stone obstruction and may advance clinical decision-making.