Juvenile Injustice: Disproportionate Minority Contact in Oklahoma\u27s Juvenile Justice System

Statistics show that minority overrepresentation in the juvenile justice system is not a new phenomenon. The problem, however, is not going away and might even be getting worse. In 2008, the FBI\u27s Uniform Crime Report showed that 52% of juvenile Violent Crime Index arrests, and 33% of juvenile Property Crime Index arrests, are black youths. This occurring while black youth only accounted for 16% of the youth population. These statistics illustrate disproportionate minority contact. The question is whether disproportionate minority contact has improved, and what is influencing minority overrepresentation. In this dissertation, I examine whether minorities are overrepresented in Oklahoma\u27s Juvenile Justice System. I explore this by using quantitative data collected by the University of Oklahoma\u27s research study on DMC using the Juvenile-On-line Tracking System, law enforcement data, and municipal court data. Once DMC is found existing in the juvenile justice system, I examine the relationship between covert racism, on the part of juvenile justice officials, and minority overrepresentation. This is done through 81 interviews with juvenile justice officials from Oklahoma City including: police, district attorneys, public defenders, judges, and juvenile specialists. Finally, I examine whether minority juvenile justice officials are similar to white juvenile justice officials in the use of color-blind racism. I do this by an analysis of the interviews, and comparing minority to white juvenile justice officials. I argue that disproportionate minority contact exists, and that color-blind racism is present in juvenile justice officials, which has an adverse effect on the overrepresentation of minorities in the juvenile justice system. White juvenile justice officials are more likely to use color-blind rhetoric. Minorities use color-blind racism to a lesser degree than whites, but this can be explained through social identity theory. This dissertation might offer an explanation to research that supports differential treatment of minorities by the juvenile justice system, as a cause of minority overrepresentation. The difference between those studies, and this dissertation, is identifying that the ideology of juvenile justice officials could influence DMC. The implication of this dissertation then, is changing the beliefs of juvenile justice officials might be important in reducing DMC

Genome-wide association study identifies _FUT8_ and _ESR2_ as co-regulators of a bi-antennary N-linked glycan A2 (GlcNAc~2~Man~3~GlcNAc~2~) in human plasma proteins

HPLC analysis of N-glycans quantified levels of the biantennary glycan (A2) in plasma proteins of 924 individuals. Subsequent genome-wide association study (GWAS) using 317,503 single nucleotide polymorphysms (SNP) identified two genetic loci influencing variation in A2: FUT 8 and ESR2. We demonstrate that human glycans are amenable to GWAS and their genetic regulation shows sex-specific effects with _FUT 8_ variants explaining 17.3% of the variance in pre-menopausal women, while _ESR2_ variants explained 6.0% of the variance in post-menopausal women

A phase I trial of SON-1010, a tumor-targeted, interleukin-12-linked, albumin-binding cytokine, shows favorable pharmacokinetics, pharmacodynamics, and safety in healthy volunteers

BackgroundThe benefits of recombinant interleukin-12 (rIL-12) as a multifunctional cytokine and potential immunotherapy for cancer have been sought for decades based on its efficacy in multiple mouse models. Unexpected toxicity in the first phase 2 study required careful attention to revised dosing strategies. Despite some signs of efficacy since then, most rIL-12 clinical trials have encountered hurdles such as short terminal elimination half-life (T½), limited tumor microenvironment targeting, and substantial systemic toxicity. We developed a strategy to extend the rIL-12 T½ that depends on binding albumin in vivo to target tumor tissue, using single-chain rIL-12 linked to a fully human albumin binding (FHAB) domain (SON-1010). After initiating a dose-escalation trial in patients with cancer (SB101), a randomized, double-blind, placebo-controlled, single-ascending dose (SAD) phase 1 trial in healthy volunteers (SB102) was conducted.MethodsSB102 (NCT05408572) focused on safety, tolerability, pharmacokinetic (PK), and pharmacodynamic (PD) endpoints. SON-1010 at 50-300 ng/kg or placebo administered subcutaneously on day 1 was studied at a ratio of 6:2, starting with two sentinels; participants were followed through day 29. Safety was reviewed after day 22, before enrolling the next cohort. A non-compartmental analysis of PK was performed and correlations with the PD results were explored, along with a comparison of the SON-1010 PK profile in SB101.ResultsParticipants receiving SON-1010 at 100 ng/kg or higher tolerated the injection but generally experienced more treatment-emergent adverse effects (TEAEs) than those receiving the lowest dose. All TEAEs were transient and no other dose relationship was noted. As expected with rIL-12, initial decreases in neutrophils and lymphocytes returned to baseline by days 9-11. PK analysis showed two-compartment elimination in SB102 with mean T½ of 104 h, compared with one-compartment elimination in SB101, which correlated with prolonged but controlled and dose-related increases in interferon-gamma (IFNγ). There was no evidence of cytokine release syndrome based on minimal participant symptoms and responses observed with other cytokines.ConclusionSON-1010, a novel presentation for rIL-12, was safe and well-tolerated in healthy volunteers up to 300 ng/kg. Its extended half-life leads to a prolonged but controlled IFNγ response, which may be important for tumor control in patients.Clinical trial registrationhttps://clinicaltrials.gov/study/NCT05408572, identifier NCT05408572

Electron Capture Dissociation Mass Spectrometry of Tyrosine Nitrated Peptides

In vivo protein nitration is associated with many disease conditions that involve oxidative stress and inflammatory response. The modification involves addition of a nitro group at the position ortho to the phenol group of tyrosine to give 3-nitrotyrosine. To understand the mechanisms and consequences of protein nitration, it is necessary to develop methods for identification of nitrotyrosine-containing proteins and localization of the sites of modification.Here, we have investigated the electron capture dissociation (ECD) and collision-induced association (CID) behavior of 3-nitrotyrosine-containing peptides. The presence of nitration did not affect the CID behavior of the peptides. For the doubly-charged peptides, addition of nitration severely inhibited the production of ECD sequence fragments. However, ECD of the triply-charged nitrated peptides resulted in some singly-charged sequence fragments. ECD of the nitrated peptides is characterized by multiple losses of small neutral species including hydroxyl radicals, water and ammonia. The origin of the neutral losses has been investigated by use of activated ion (AI) ECD. Loss of ammonia appears to be the result of non-covalent interactions between the nitro group and protonated lysine side-chains

Impact of the pre-examination phase on multicenter metabolomic studies

The development of metabolomics in clinical applications has been limited by the lack of validation in large multicenter studies. Large population cohorts and their biobanks are a valuable resource for acquiring insights into molecular disease mechanisms. Nevertheless, most of their collections are not tailored for metabolomics and have been created without specific attention to the pre-analytical requirements for high-quality metabolome assessment. Thus, comparing samples obtained by different pre-analytical procedures remains a major challenge. Here, H-1 NMR-based analyses are used to demonstrate how human serum and plasma samples collected with different operating procedures within several large European cohort studies from the Biobanking and Biomolecular Resources Infrastructure - Large Prospective Cohorts (BBMRI-LPC) consortium can be easily revealed by supervised multivariate statistical analyses at the initial stages of the process, to avoid biases in the downstream analysis. The inter-biobank differences are discussed in terms of deviations from the validated CEN/TS 16945:2016 / ISO 23118:2021 norms. It clearly emerges that biobanks must adhere to the evidence-based guidelines in order to support wider-scale application of metabolomics in biomedicine, and that NMR spectroscopy is informative in comparing the quality of different sample sources in multi cohort/center studies.Peer reviewe

Metabolomic Fingerprints in Large Population Cohorts : Impact of Preanalytical Heterogeneity

Non peer reviewe

BICEPP: an example-based statistical text mining method for predicting the binary characteristics of drugs

<p>Abstract</p> <p>Background</p> <p>The identification of drug characteristics is a clinically important task, but it requires much expert knowledge and consumes substantial resources. We have developed a statistical text-mining approach (BInary Characteristics Extractor and biomedical Properties Predictor: BICEPP) to help experts screen drugs that may have important clinical characteristics of interest.</p> <p>Results</p> <p>BICEPP first retrieves MEDLINE abstracts containing drug names, then selects tokens that best predict the list of drugs which represents the characteristic of interest. Machine learning is then used to classify drugs using a document frequency-based measure. Evaluation experiments were performed to validate BICEPP's performance on 484 characteristics of 857 drugs, identified from the Australian Medicines Handbook (AMH) and the PharmacoKinetic Interaction Screening (PKIS) database. Stratified cross-validations revealed that BICEPP was able to classify drugs into all 20 major therapeutic classes (100%) and 157 (of 197) minor drug classes (80%) with areas under the receiver operating characteristic curve (AUC) > 0.80. Similarly, AUC > 0.80 could be obtained in the classification of 173 (of 238) adverse events (73%), up to 12 (of 15) groups of clinically significant cytochrome P450 enzyme (CYP) inducers or inhibitors (80%), and up to 11 (of 14) groups of narrow therapeutic index drugs (79%). Interestingly, it was observed that the keywords used to describe a drug characteristic were not necessarily the most predictive ones for the classification task.</p> <p>Conclusions</p> <p>BICEPP has sufficient classification power to automatically distinguish a wide range of clinical properties of drugs. This may be used in pharmacovigilance applications to assist with rapid screening of large drug databases to identify important characteristics for further evaluation.</p