Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank.

AIMS/HYPOTHESIS: The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. METHODS: From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. RESULTS: At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. CONCLUSIONS/INTERPRETATION: Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

Augmenting Polymer Datasets by Iterative Rearrangement.

One of the biggest obstacles to successful polymer property prediction is an effective representation that accurately captures the sequence of repeat units in a polymer. Motivated by the success of data augmentation in computer vision and natural language processing, we explore augmenting polymer data by iteratively rearranging the molecular representation while preserving the correct connectivity, revealing additional substructural information that is not present in a single representation. We evaluate the effects of this technique on the performance of machine learning models trained on three polymer datasets and compare them to common molecular representations. Data augmentation does not yield significant improvements in machine learning property prediction performance compared to equivalent (non-augmented) representations. In datasets where the target property is primarily influenced by the polymer sequence rather than experimental parameters, this data augmentation technique provides molecular embedding with more information to improve property prediction accuracy.

A case study on genomic imprinting facilitates student learning.

Problem-based learning encourages students to deepen their understanding of a concept by working through a real-world example of course content. Case studies represent a form of problem-based learning that engages students in realistic scenarios to achieve a deeper understanding of concepts. Case studies have been shown to facilitate the learning of challenging subject matter. We hypothesized that the use of a case study would help students better learn the topic of genomic imprinting, an abstract phenomenon in molecular biology and genetics. We wrote an interrupted case study that focused on genomic imprinting. The case study consists of three short popular news articles that relate to genomic imprinting. Each article is followed by a set of two to four questions. Students read each article and discuss its associated questions in small groups and then with the entire class before moving on to the next article. We deployed the case study in an intermediate-level molecular biology course at a small, liberal arts university. We assessed student learning and attitudes toward the case study (50 pre/postmatched pairs). In four true/false assessment questions, our results showed that the students' performance on the assessment after the case study was significantly higher than their performance before the case study. Students also self-reported increased knowledge of concepts related to genomic imprinting. Finally, students were likely to agree that the case study was beneficial to their learning and was an enjoyable classroom activity. We conclude that the case study is an effective way to instruct students about the topic of genomic imprinting.NEW & NOTEWORTHY Students often struggle with the concept of genomic imprinting, in part because it violates Mendelian rules of inheritance. Students learned about genomic imprinting, and enjoyed doing it when completing this case study.

Nonalbuminuric Diabetic Kidney Disease and Risk of All-Cause Mortality and Cardiovascular and Kidney Outcomes in Type 2 Diabetes: Findings From the Hong Kong Diabetes Biobank.

RATIONALE & OBJECTIVE: Nonalbuminuric diabetic kidney disease (DKD) has become the prevailing DKD phenotype. We compared the risks of adverse outcomes among patients with this phenotype compared with other DKD phenotypes. STUDY DESIGN: Multicenter prospective cohort study. SETTINGS & PARTICIPANTS: 19,025 Chinese adults with type 2 diabetes enrolled in the Hong Kong Diabetes Biobank. EXPOSURES: DKD phenotypes defined by baseline estimated glomerular filtration rate (eGFR) and albuminuria: no DKD (no decreased eGFR or albuminuria), albuminuria without decreased eGFR, decreased eGFR without albuminuria, and albuminuria with decreased eGFR. OUTCOMES: All-cause mortality, cardiovascular disease (CVD) events, hospitalization for heart failure (HF), and chronic kidney disease (CKD) progression (incident kidney failure or sustained eGFR reduction ≥40%). ANALYTICAL APPROACH: Multivariable Cox proportional or cause-specific hazards models to estimate the relative risks of death, CVD, hospitalization for HF, and CKD progression. Multiple imputation was used for missing covariates. RESULTS: Mean participant age was 61.1 years, 58.3% were male, and mean diabetes duration was 11.1 years. During 54,260 person-years of follow-up, 438 deaths, 1,076 CVD events, 298 hospitalizations for HF, and 1,161 episodes of CKD progression occurred. Compared with the no-DKD subgroup, the subgroup with decreased eGFR without albuminuria had higher risks of all-cause mortality (hazard ratio [HR], 1.59 [95% CI, 1.04-2.44]), hospitalization for HF (HR, 3.08 [95% CI, 1.82-5.21]), and CKD progression (HR, 2.37 [95% CI, 1.63-3.43]), but the risk of CVD was not significantly greater (HR, 1.14 [95% CI, 0.88-1.48]). The risks of death, CVD, hospitalization for HF, and CKD progression were higher in the setting of albuminuria with or without decreased eGFR. A sensitivity analysis that excluded participants with baseline eGFR <30 mL/min/1.73 m2 yielded similar findings. LIMITATIONS: Potential misclassification because of drug use. CONCLUSIONS: Nonalbuminuric DKD was associated with higher risks of hospitalization for HF and of CKD progression than no DKD, regardless of baseline eGFR.

High-density lipoprotein subclasses and cardiovascular disease and mortality in type 2 diabetes: analysis from the Hong Kong Diabetes Biobank.

OBJECTIVE: High-density lipoproteins (HDL) comprise particles of different size, density and composition and their vasoprotective functions may differ. Diabetes modifies the composition and function of HDL. We assessed associations of HDL size-based subclasses with incident cardiovascular disease (CVD) and mortality and their prognostic utility. RESEARCH DESIGN AND METHODS: HDL subclasses by nuclear magnetic resonance spectroscopy were determined in sera from 1991 fasted adults with type 2 diabetes (T2D) consecutively recruited from March 2014 to February 2015 in Hong Kong. HDL was divided into small, medium, large and very large subclasses. Associations (per SD increment) with outcomes were evaluated using multivariate Cox proportional hazards models. C-statistic, integrated discrimination index (IDI), and categorial and continuous net reclassification improvement (NRI) were used to assess predictive value. RESULTS: Over median (IQR) 5.2 (5.0-5.4) years, 125 participants developed incident CVD and 90 participants died. Small HDL particles (HDL-P) were inversely associated with incident CVD [hazard ratio (HR) 0.65 (95% CI 0.52, 0.81)] and all-cause mortality [0.47 (0.38, 0.59)] (false discovery rate < 0.05). Very large HDL-P were positively associated with all-cause mortality [1.75 (1.19, 2.58)]. Small HDL-P improved prediction of mortality [C-statistic 0.034 (0.013, 0.055), IDI 0.052 (0.014, 0.103), categorical NRI 0.156 (0.006, 0.252), and continuous NRI 0.571 (0.246, 0.851)] and CVD [IDI 0.017 (0.003, 0.038) and continuous NRI 0.282 (0.088, 0.486)] over the RECODe model. CONCLUSION: Small HDL-P were inversely associated with incident CVD and all-cause mortality and improved risk stratification for adverse outcomes in people with T2D. HDL-P may be used as markers for residual risk in people with T2D.

Obesity, clinical, and genetic predictors for glycemic progression in Chinese patients with type 2 diabetes: A cohort study using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank.

BACKGROUND: Type 2 diabetes (T2D) is a progressive disease whereby there is often deterioration in glucose control despite escalation in treatment. There is significant heterogeneity to this progression of glycemia after onset of diabetes, yet the factors that influence glycemic progression are not well understood. Given the tremendous burden of diabetes in the Chinese population, and limited knowledge on factors that influence glycemia, we aim to identify the clinical and genetic predictors for glycemic progression in Chinese patients with T2D. METHODS AND FINDINGS: In 1995-2007, 7,091 insulin-naïve Chinese patients (mean age 56.8 ± 13.3 [SD] years; mean age of T2D onset 51.1 ± 12.7 years; 47% men; 28.4% current or ex-smokers; median duration of diabetes 4 [IQR: 1-9] years; mean HbA1c 7.4% ± 1.7%; mean body mass index [BMI] 25.3 ± 4.0 kg/m2) were followed prospectively in the Hong Kong Diabetes Register. We examined associations of BMI and other clinical and genetic factors with glycemic progression defined as requirement of continuous insulin treatment, or 2 consecutive HbA1c ≥8.5% while on ≥2 oral glucose-lowering drugs (OGLDs), with validation in another multicenter cohort of Hong Kong Diabetes Biobank. During a median follow-up period of 8.8 (IQR: 4.8-13.3) years, incidence of glycemic progression was 48.0 (95% confidence interval [CI] 46.3-49.8) per 1,000 person-years with 2,519 patients started on insulin. Among the latter, 33.2% had a lag period of 1.3 years before insulin was initiated. Risk of progression was associated with extremes of BMI and high HbA1c. On multivariate Cox analysis, early age at diagnosis, microvascular complications, high triglyceride levels, and tobacco use were additional independent predictors for glycemic progression. A polygenic risk score (PRS) including 123 known risk variants for T2D also predicted rapid progression to insulin therapy (hazard ratio [HR]: 1.07 [95% CI 1.03-1.12] per SD; P = 0.001), with validation in the replication cohort (HR: 1.24 [95% CI 1.06-1.46] per SD; P = 0.008). A PRS using 63 BMI-related variants predicted BMI (beta [SE] = 0.312 [0.057] per SD; P = 5.84 × 10-8) but not glycemic progression (HR: 1.01 [95% CI 0.96-1.05] per SD; P = 0.747). Limitations of this study include potential misdiagnosis of T2D and lack of detailed data of drug use during follow-up in the replication cohort. CONCLUSIONS: Our results show that approximately 5% of patients with T2D failed OGLDs annually in this clinic-based cohort. The independent associations of modifiable and genetic risk factors allow more precise identification of high-risk patients for early intensive control of multiple risk factors to prevent glycemic progression.

A bridging model for persistence of a polycomb group protein complex through DNA replication in vitro.

Epigenetic regulation may involve heritable chromatin states, but how chromatin features can be inherited through DNA replication is incompletely understood. We address this question using cell-free replication of chromatin. Previously, we showed that a Polycomb group complex, PRC1, remains continuously associated with chromatin through DNA replication. Here we investigate the mechanism of persistence. We find that a single PRC1 subunit, Posterior sex combs (PSC), can reconstitute persistence through DNA replication. PSC binds nucleosomes and self-interacts, bridging nucleosomes into a stable, oligomeric structure. Within these structures, individual PSC-chromatin contacts are dynamic. Stable association of PSC with chromatin, including through DNA replication, depends on PSC-PSC interactions. Our data suggest that labile individual PSC-chromatin contacts allow passage of the DNA replication machinery while PSC-PSC interactions prevent PSC from dissociating, allowing it to rebind to replicated chromatin. This mechanism may allow inheritance of chromatin proteins including PRC1 through DNA replication to maintain chromatin states.

Advances in the Diagnosis and Management of Cystic Fibrosis in the Genomic Era.

BACKGROUND: Cystic fibrosis (CF) is a complex autosomal recessive disease that continues to present unique diagnostic challenges. Because CF was first described in 1938, there has been a substantial growth of genetic and phenotypic information about the disorder. During the past few years, as more evidence has become available, a consortium of international experts determined that the 2008 guidelines from the CF Foundation needed to be reviewed and updated. CONTENT: The goal of this review is to highlight the latest advances in CF multidisciplinary care, together with the recent updates to the 2017 CF Foundation diagnostic guidelines. SUMMARY: Data from newborn screening programs, patient registries, clinical databases, and functional research have led to a better understanding of the CF transmembrane conductance regulator (CFTR) gene. Recent consensus guidelines have provided recommendations for clinicians and laboratorians to better assist with interpretation of disease status and related CF mutations. The highly recommended Clinical and Functional Translation of CFTR project should be the first resource in the evaluation of disease severity for CF mutations. Screen-positive newborns and patients with high clinical suspicion for CF are always recommended to undergo confirmatory sweat chloride testing with interpretations based on updated reference intervals. Every patient diagnosed with CF should receive genotyping, as novel molecular therapies are becoming standard of practice. The future of CF management must consider healthcare system disparities as CF transitions from a historically childhood disease to a predominantly adult epidemic.

Bloch mode selection in silicon photonic crystal microring resonators.

A novel method of selecting a subset of Bloch modes in silicon-based photonic crystal microring resonators (PhCR)s is demonstrated. Bloch modes in the PhCR are calculated, and their intensity beating patterns are analyzed. Based on the different spatial intensity distribution for each resonance, a subset of resonances is out-coupled using an output coupler waveguide (CWG) which is positioned at an angle θ=90° with respect to the input CWG. As shown in theory and experiment, resonances with an even mode number are selected, while resonances with an odd mode number are rejected. The highest contrast between mode selection and mode rejection is ∼9 dB in the experiments. This approach opens another design freedom for ring resonator-based devices and could potentially reduce the footprint of microring resonator-based multiplexers and add-drop filters.

Photonic crystal microring resonator for label-free biosensing.

A label-free optical biosensor based on a one-dimensional photonic crystal microring resonator with enhanced light-matter interaction is demonstrated. More than a 2-fold improvement in volumetric and surface sensing sensitivity is achieved compared to conventional microring sensors. The experimental bulk detection sensitivity is ~248nm/RIU and label-free detection of DNA and proteins is reported at the nanomolar scale. With a minimum feature size greater than 100nm, the photonic crystal microring resonator biosensor can be fabricated with the same standard lithographic techniques used to mass fabricate conventional microring resonators.

Dried Blood Spot Reference Intervals for Steroids and Amino Acids in a Neonatal Cohort of the National Children's Study.

BACKGROUND: Reference intervals from children are limited by access to healthy children and their limited blood volumes. In this study we set out to fill gaps in pediatric reference intervals for amino acids and steroid hormones using dried blood spots (DBS) from a cohort of the National Children's Study. METHODS: Deidentified DBS annotated with age, birthweight, sex, and geographic location were obtained from 310 newborns aged 0-4 days and analyzed for 25 amino acids and 4 steroid hormones using LC-MS/MS. Nonparametric statistical approaches were used to generate the 2.5th-97.5th percentile distributions for newborns. Paired plasma/DBS specimens were used to mathematically transform DBS reference intervals to corresponding plasma intervals. RESULTS: 10 of 25 DBS amino acid distributions were dependent on sex. There was little correlation with age, birthweight, or geographic location over the first 4 days of life. In most cases, transformation of DBS distributions to plasma distributions faithfully reflected independent studies of newborn plasma amino acid distributions. In general newborn steroid distributions were negatively correlated with age and birthweight over the first 4 days of life. Data distributions for the 4 steroids were not found related to geographic location, but testosterone concentrations displayed sex dependence. Transformation of DBS distributions to plasma intervals did not faithfully replicate other neonate steroid reference intervals determined directly with plasma. CONCLUSIONS: These data demonstrate the feasibility and utility of deriving newborn reference intervals from large numbers of archived DBS samples such as those obtained from the National Children's Study biobank.

Mentorship for Transfer Student Success in STEM Research: Mentor Approaches and Reflections.

Mentorship has been widely recognized as an effective means to promote student learning and engagement in undergraduate research experiences. However, little work exists for understanding different mentors' perceived approaches to mentorship, including mentorship of students from backgrounds and educational trajectories not well represented in science, technology, engineering, and mathematics (STEM). Transfer students, in particular, face unique trajectories in their pursuit of research opportunities, yet few studies investigate how mentors describe their approaches to supporting these students. Using semistructured interviews, this study examines how mentors approach mentoring students from diverse backgrounds as research trainees, with an emphasis on transfer students. First, using phenomenography as an analytical approach, we identified four categories describing variations in how mentors reflected upon or accounted for the transfer student identity in their approaches. We find that research mentors vary in their understanding and exposure to the transfer student identity and may have preconceived notions of the transfer student experience. Second, we present vignettes to illustrate how mentors' approaches to the transfer student identity may relate or diverge from their general approaches to mentoring students from different backgrounds and identities. The emerging findings have implications for developing effective mentorship strategies and training mentors to support transfer students.

Variations in Student Approaches to Problem Solving in Undergraduate Biology Education.

Existing research has investigated student problem-solving strategies across science, technology, engineering, and mathematics; however, there is limited work in undergraduate biology education on how various aspects that influence learning combine to generate holistic approaches to problem solving. Through the lens of situated cognition, we consider problem solving as a learning phenomenon that involves the interactions between internal cognition of the learner and the external learning environment. Using phenomenography as a methodology, we investigated undergraduate student approaches to problem solving in biology through interviews. We identified five aspects of problem solving (including knowledge, strategy, intention, metacognition, and mindset) that define three qualitatively different approaches to problem solving; each approach is distinguishable by variations across the aspects. Variations in the knowledge and strategy aspects largely aligned with previous work on how the use or avoidance of biological knowledge informed both concept-based and nonconcept-based strategies. Variations in the other aspects revealed intentions spanning complete disengagement to deep interest with the course material, different degrees of metacognitive reflections, and a continuum of fixed to growth mindsets. We discuss implications for how these characterizations can improve instruction and efforts to support development of problem-solving skills.

Variability in Celiac Serology Testing by Provider Type: A Single-Center Experience.

To evaluate the ordering practices of celiac disease (CD) serologies by providers at a tertiary, academic, Children's Hospital and compare them to guidelines and best practices. Methods: We analyzed celiac serologies ordered in 2018 by provider type (pediatric gastrointestinal (GI) specialists, primary care providers (PCPs), and nonpediatric GI specialists), and identified causes for variability and nonadherence. Results: The antitissue transglutaminase antibody (tTG) IgA was ordered (n = 2504) most frequently by gastroenterologists (43%), endocrinologists (22%), and other (35%). Total IgA was ordered with tTG IgA for screening purposes in 81% of overall cases, but endocrinologists ordered it only 49% of the time. The tTG IgG was ordered infrequently (1.9%) compared with tTG IgA. Antideaminated gliadin peptide (DGP) IgA/IgG levels were also infrequently ordered (5.4%) compared with tTG IgA. The antiendomysial antibody was ordered sparingly (0.9%) compared with tTG IgA, but appropriately by providers with expertise in CD, similar to ordering for celiac genetics (0.8%). Of the celiac genetic tests, 15% were ordered in error. The positivity rate of the tTG IgA ordered by PCPs was 4.4%. Conclusions: The tTG IgA was appropriately ordered by all types of providers. Endocrinologists inconsistently ordered total IgA levels with screening labs. DGP IgA/IgG tests were not commonly ordered but were inappropriately ordered by one provider. The low number of ordered antiendomysial antibody and celiac genetic tests suggests under-utilization of the nonbiopsy approach. The positive yield of tTG IgA ordered by PCPs was higher compared with previous studies.

Overview of Pediatric Procalcitonin Testing Patterns in a Tertiary Care Children's Hospital.

The use of procalcitonin (PCT) has grown over the past decade with increasing reliance on the test to rule out bacterial infection. We retrospectively reviewed the medical records of children <18 years old hospitalized at a tertiary care children's hospital from 2017 to 2019 who had PCT testing performed during their admission. Of 4135 PCT levels collected on 1530 children, 982 (23.7%) were diagnostically low and 1993 (48.1%) were diagnostically elevated. Pediatric intensive care, with 6% of total hospital patients, obtained 41.4% of tests. Thirty-one (2%) patients had an average of 27 PCT levels per patient, accounting for 20% of all tests. Many children had symptoms for which testing is not indicated (eg, skin complaints). The differences in PCT testing by service, inappropriate patterns of repeat testing, and testing performed in patients for whom it is not indicated may identify targets for diagnostic stewardship.

Consensus Statements from the Diabetologists & Endocrinologists Alliance for the Management of People with Hypertension and Type 2 Diabetes Mellitus.

Hypertension and type 2 diabetes mellitus (T2DM) are important, intertwined public health issues. People with both conditions face significantly elevated risks of cardiovascular (CV) and renal complications. To optimize patient care, a multidisciplinary expert panel met to review recent evidence on optimal blood pressure (BP) targets, implications of albuminuria, and treatment regimens for hypertensive patients with T2DM, with the aim of providing recommendations for physicians in Hong Kong. The panel reviewed the relevant literature, obtained by searching PubMed for the publication period from January 2015 to June 2021, to address five discussion areas: (i) BP targets based on CV/renal benefits; (ii) management of isolated systolic or diastolic hypertension; (iii) roles of angiotensin II receptor blockers; (iv) implications of albuminuria for CV/renal events and treatment choices; and (v) roles and tools of screening for microalbuminuria. The panel held three virtual meetings using a modified Delphi method to address the discussion areas. After each meeting, consensus statements were derived and anonymously voted on by every panelist. A total of 17 consensus statements were formulated based on recent evidence and expert insights regarding cardioprotection and renoprotection for hypertensive patients with T2DM.

Identification of a Common Variant for Coronary Heart Disease at PDE1A Contributes to Individualized Treatment Goals and Risk Stratification of Cardiovascular Complications in Chinese Patients With Type 2 Diabetes.

OBJECTIVE: In this study we aim to unravel genetic determinants of coronary heart disease (CHD) in type 2 diabetes (T2D) and explore their applications. RESEARCH DESIGN AND METHODS: We performed a two-stage genome-wide association study for CHD in Chinese patients with T2D (3,596 case and 8,898 control subjects), followed by replications in European patients with T2D (764 case and 4,276 control subjects) and general populations (n = 51,442-547,261). Each identified variant was examined for its association with a wide range of phenotypes and its interactions with glycemic, blood pressure (BP), and lipid controls in incident cardiovascular diseases. RESULTS: We identified a novel variant (rs10171703) for CHD (odds ratio 1.21 [95% CI 1.13-1.30]; P = 2.4 × 10-8) and BP (ß ± SE 0.130 ± 0.017; P = 4.1 × 10-14) at PDE1A in Chinese T2D patients but found only a modest association with CHD in general populations. This variant modulated the effects of BP goal attainment (130/80 mmHg) on CHD (Pinteraction = 0.0155) and myocardial infarction (MI) (Pinteraction = 5.1 × 10-4). Patients with CC genotype of rs10171703 had >40% reduction in either cardiovascular events in response to BP control (2.9 × 10-8 < P < 3.6 × 10-5), those with CT genotype had no difference (0.0726 < P < 0.2614), and those with TT genotype had a threefold increase in MI risk (P = 6.7 × 10-3). CONCLUSIONS: We discovered a novel CHD- and BP-related variant at PDE1A that interacted with BP goal attainment with divergent effects on CHD risk in Chinese patients with T2D. Incorporating this information may facilitate individualized treatment strategies for precision care in diabetes, only when our findings are validated.

Examining the Variations in Undergraduate Students' Conceptions of Successful Researchers: A Phenomenographic Study.

Undergraduate education represents an important transitional stage in which students make career decisions, and undergraduate research experiences (UREs) play a critical role in training the next generation of science, technology, engineering, and mathematics researchers. Extensive studies have identified the different ways in which researchers and graduate students understand their profession, but little work has focused on undergraduate students. To contribute to this gap in literature, this study examines how undergraduate students conceptualize successful researchers. Data were collected using semistructured interviews with transfer students at a research-intensive university, in which participants articulated how they perceive a successful researcher and how their conception had changed based on their undergraduate experiences. Using phenomenography as the research approach, three conceptions of successful researchers were identified based on variations within the following aspects: process of research, interactions with other researchers, and scope of contribution. Retrospective conceptions were more simplistic, with little appreciation for the complex methodological processes and collaborations needed to meaningfully contribute to the research community. After UREs, participants reported conceptions with more nuanced understanding that successful researchers demonstrate proactive engagement, collaboration, and contribution. These findings can be applied to facilitate meaningful research experiences and target undergraduates' professional development as they are enculturated into the research community.

Identification of Urine Organic Acids for the Detection of Inborn Errors of Metabolism Using Urease and Gas Chromatography-Mass Spectrometry (GC/MS).

A patient suspected of an inborn error of metabolism will commonly have urine organic acid analysis performed as part of their workup. The traditional urine organic acid method involves extraction of the acidic fraction from urine samples using an organic solvent, derivatization of extracted compounds, and identification using gas chromatography-mass spectrometry (GC/MS). Unfortunately, the extraction step results in the loss of many neutral and positively charged compounds which may be of interest to metabolic physicians and biochemical geneticists. By replacing the traditional extraction step with an enzymatic treatment of the sample with urease, an abundance of organic molecules is available for separation and quantification by GC/MS. The urease method is a useful adjunct to newborn screening follow-up, and it has the additional benefit of being able to identify many classes of biochemical compounds, such as amino acids, acylglycines, neurotransmitters, and carbohydrates. This method describes the urease treatment, derivatization, and the organic acids and other biochemical metabolites that can be identified.