Access Patterns Research Articles

Youth mental health care use during COVID-19: Evidence from administrative data in Alberta, Canada

Abstract Background The COVID-19 pandemic affected health care service delivery and accessibility. Our study examined how Canadian youth used mental health services before and during the COVID-19 pandemic, and whether youth access and use patterns differed for subgroups based on social determinants previously associated with health care access. Methods Cross-sectional population-based administrative health care data from the province of Alberta in Canada was used to examine youth (ages 15-24) mental health care use from 2018/19 to 2021/22. Data was analyzed using an interrupted time series design and segmented regression modeling on type of mental health care use. Outcome measures were mental health care use for: general physician visits, psychiatrist visits, emergency department, hospitalization, and different mental health diagnoses. We stratified by factors related to social determinants, including gender and socioeconomic status. Results The analysis indicates an overall increase in the proportion of youth that used mental health care from 2018/19 to 2021/22 (14.4% vs 17.5%, respectively). There was an immediate drop in use with the onset of the COVID-19 pandemic in Canada, followed by a steady rise during the pandemic years, which was largely due to an increase in general physician visits. This rise was seen for most mental health diagnoses of study (i.e., anxiety, adjustment, attention-deficit/hyperactivity disorder, schizophrenia, and self-harm disorders). Service use increased for young women/girls compared to young men/boys and for youth from wealthier neighborhoods. Conclusions This study provides evidence to support health services planning and delivery to respond to the mental health needs of youth and to prepare for future public health emergencies. Key messages • Our study findings indicate changes in health care use for mental health among Canadian youth (ages 15-24) during the COVID-19 pandemic, with use patterns differing for youth subgroups. • Administrative health data can provide evidence to support health services planning and delivery to respond to the mental health needs of youth and to prepare for future public health emergencies.

Understanding the complex chromatin dynamics in primary human neutrophils during PMA-induced NET formation

BackgroundPrimary human neutrophils play a pivotal role in innate immunity, mainly through the formation of neutrophil extracellular traps (NETs) in a process known as NETosis. This cell-death pathway is crucial for combating infections but is also implicated in many inflammatory diseases, such as sepsis, systemic lupus erythematosus, and rheumatoid arthritis.MethodsThe study presented here investigates chromatin dynamics during NET formation by stimulating primary human neutrophils with phorbol 12-myristate 13-acetate (PMA). We adapt the ATAC-Seq (assay for transposase-accessible chromatin using sequencing) method to isolated neutrophils and characterize a time-dependent chromatin response.ResultsWe found that chromatin accessibility patterns are consistent across individual donors and most chromatin changes occur within 30 min, with many continuing across the 90 min assessed in this study. Regulatory regions gaining accessibility were associated with the activity of pathways that have been implicated in NOX-dependent NET formation.ConclusionsOur findings increase the understanding of the chromatin changes underlying NET formation and also identify potential early-acting targets for modulating this process in inflammatory diseases.

Chronic interferon-stimulated gene transcription promotes oncogene-induced breast cancer.

The MRE11 complex (comprising MRE11, RAD50, and NBS1) is integral to the maintenance of genome stability. We previously showed that a hypomorphic Mre11 mutant mouse strain (Mre11 ATLD1/ATLD1 ) was highly susceptible to oncogene-induced breast cancer. Here we used a mammary organoid system to examine which MRE11-dependent responses are tumor-suppressive. We found that Mre11 ATLD1/ATLD1 organoids exhibited an elevated interferon-stimulated gene (ISG) signature and sustained changes in chromatin accessibility. This Mre11 ATLD1/ATLD1 phenotype depended on DNA binding of a nuclear innate immune sensor, IFI205. Ablation of Ifi205 in Mre11 ATLD1/ATLD1 organoids restored baseline and oncogene-induced chromatin accessibility patterns to those observed in WT. Implantation of Mre11 ATLD1/ATLD1 organoids and activation of the oncogene led to aggressive metastatic breast cancer. This outcome was reversed in implanted Ifi205 -/- Mre11 ATLD1/ATLD1 organoids. These data reveal a connection between innate immune signaling and tumor development in the mammary epithelium. Given the abundance of aberrant DNA structures that arise in the context of genome instability syndromes, the data further suggest that cancer predisposition in those contexts may be partially attributable to chronic innate immune transcriptional programs.

LSTM-CRP: Algorithm-Hardware Co-Design and Implementation of Cache Replacement Policy Using Long Short-Term Memory

As deep learning has produced dramatic breakthroughs in many areas, it has motivated emerging studies on the combination between neural networks and cache replacement algorithms. However, deep learning is a poor fit for performing cache replacement in hardware implementation because its neural network models are impractically large and slow. Many studies have tried to use the guidance of the Belady algorithm to speed up the prediction of cache replacement. But it is still impractical to accurately predict the characteristics of future access addresses, introducing inaccuracy in the discrimination of complex access patterns. Therefore, this paper presents the LSTM-CRP algorithm as well as its efficient hardware implementation, which employs the long short-term memory (LSTM) for access pattern identification at run-time to guide cache replacement algorithm. LSTM-CRP first converts the address into a novel key according to the frequency of the access address and a virtual capacity of the cache, which has the advantages of low information redundancy and high timeliness. Using the key as the inputs of four offline-trained LSTM network-based predictors, LSTM-CRP can accurately classify different access patterns and identify current cache characteristics in a timely manner via an online set dueling mechanism on sampling caches. For efficient implementation, heterogeneous lightweight LSTM networks are dedicatedly constructed in LSTM-CRP to lower hardware overhead and inference delay. The experimental results show that LSTM-CRP was able to averagely improve the cache hit rate by 20.10%, 15.35%, 12.11% and 8.49% compared with LRU, RRIP, Hawkeye and Glider, respectively. Implemented on Xilinx XCVU9P FPGA at the cost of 15,973 LUTs and 1610 FF registers, LSTM-CRP was running at a 200 MHz frequency with 2.74 W power consumption.

CONTEXTUAL REANALYSIS OF THE ARCHITECTURAL FORM AND SOCIO-ECONOMIC STATUS OF THE PANAGIA HOUSES AT MYCENAE

The Panagia Houses, one of the building complexes at Mycenae, located to the south-west of the Citadel, were interpreted by the excavators as a group of three independent units. They were constructed and occupied during the Late Helladic (LH) IIIB phase, with two main phases distinguishable in the archaeological record, followed by a reoccupation phase. Careful analysis of the archaeological data published by Mylonas-Shear, which focused on the arrangement of individual units, formality of layout, access and movement patterns, and visibility, suggests that the group should be interpreted rather as a single complex, developed during the period of the maximum expansion of the settlement. The building was gradually expanded to form an extended household, with primary living space surrounded by a number of additional rooms for storage, work and habitation. It was composed of a rectangular main unit, surrounded by an extension formed around a small inner courtyard. The movement between the two levels was organised through a system of connected rooftops, with trapdoors and staircases ensuring access to the various rooms of the complex. During the LH IIIB2 Early phase, Mycenae was hit by a devastating earthquake. Much of the town was left in ruin, but the Panagia Houses were rebuilt, although in a smaller form, with the main unit abandoned and the courtyard inside the extension transformed into the main room of the complex. The status of the complex probably changed, but it was still inhabited by a middle-class family, who possessed a number of valuables and took part in the palatial mobilisation system. The household probably suffered in a widespread fire which destroyed Mycenae at the end of LH IIIB. Its remains were then used as two small dwellings by the survivors of the catastrophe. The history of the complex reflects the changing vicissitudes of the Lower Town of Mycenae.

Methodology to define a static allocation mapping based on memory access patterns and the Signature of MPI applications in HPC systems

Tools to identify problems and improve MPI applications performance running on an HPC system require information from the application and the system. In this work we will focus on defining a methodology to analyze how memory usage affects an MPI application performance running on this HPC system. This methodology will obtain valid and comparable data based on different memory access patterns that will allow defining key performance values used to characterize the HPC system behavior in front of these access patterns and to characterize the Application Signature behavior, (PAS2P Signature that obtains the representative phases of the MPI application) in front of these same access patterns. With these key performance values, we will be able to detect memory access application problems, suggest improvements and define a mapping policy for this application in this HPC system to improve its performance and to determine limits to these improvements.

HybridSA: GPU Acceleration of Multi-pattern Regex Matching using Bit Parallelism

Multi-pattern matching is widely used in modern software for applications requiring high throughput such as protein search, network traffic inspection, virus or spam detection. Graphics Processor Units (GPUs) excel at executing massively parallel workloads. Regular expression (regex) matching is typically performed by simulating the execution of deterministic finite automata (DFAs) or nondeterministic finite automata (NFAs). The natural implementations of these automata simulation algorithms on GPUs are highly inefficient because they give rise to irregular memory access patterns. This paper presents HybridSA, a heterogeneous CPU-GPU parallel engine for multi-pattern matching. HybridSA uses bit parallelism to efficiently simulate NFAs on GPUs, thus reducing the number of memory accesses and increasing the throughput. Our bit-parallel algorithms extend the classical shift-and algorithm for string matching to a large class of regular expressions and reduce automata simulation to a small number of bitwise operations. We have developed a compiler to translate regular expressions into bit masks, perform optimizations, and choose the best algorithms to run on the GPU. The majority of the regular expressions are accelerated on the GPU, while the patterns that exhibit random memory accesses are executed on the CPU in parallel. We evaluate HybridSA against state-of-the-art CPU and GPU engines, as well as a hybrid combination of the two. HybridSA achieves between 4 and 60 times higher throughput than the state-of-the-art CPU engine and between 4 and 233 times better than the state-of-the-art GPU engine across a collection of real-world benchmarks.

Multidimensional patterns of early care and education access through a family centered lens

Despite evidence of the benefits of early care and education (ECE) for child development and family employment, the supply of providers is scarce and variable; leading many families with young children to experience limited and inequitable access. To examine the multidetermined nature of access, this study leverages a multidimensional, family-centered definition and a nationally representative sample of families of preschoolers from the Early Childhood Longitudinal Study – Birth Cohort to examine (1) patterns of access-related features present in preschool-age children's ECE arrangements, and (2) child characteristics, household circumstances, and care setting type that may be related to patterns of access. Latent class analysis model enumeration revealed five latent classes of children's nonparental care arrangements along features of accessibility: High Across Most Access Features (26.4 %), Single, Long-Term Provider (30.1 %), Limited Across Most Access Features (11.6 %), Low Affordability, Multiple Providers (10.1 %), and High Affordability, Recent Transition (21.8 %). These results suggested many children were in ECE that met multiple dimensions of access, with others in care arrangements that reflected trade-offs. Children were also differentially classified into types of ECE arrangements in relation to care setting type, race/ethnicity, income, household urbanicity, and parental employment. The implications of investigating ECE access as a multidimensional construct, and recommendations for how ECE providers and policy can more closely align with family needs are discussed.

Trends in Epidemiologic Characteristics and Clinical Patterns of Vascular Access of Incident Hemodialysis Patients: Nationwide Cohort Study (2006-2019) in Korea

Trends in Epidemiologic Characteristics and Clinical Patterns of Vascular Access of Incident Hemodialysis Patients: Nationwide Cohort Study (2006-2019) in Korea

Definition of regulatory elements and transcription factors controlling porcine immune cell gene expression at single cell resolution using single nucleus ATAC-seq

The transcriptome of porcine peripheral blood mononuclear cells (PBMC) at single cell (sc) resolution is well described, but little is understood about the cis-regulatory mechanism behind scPBMC gene expression. Here, we profiled the open chromatin landscape of porcine PBMC that define cis-regulatory elements and mechanism contributing to the transcription using single nucleus ATAC sequencing (snATAC-seq). Approximately 22 % of the identified peaks overlapped with annotated transcription start sites (TSS). Using clustering based on open chromatin pattern similarity, we demonstrate that cell type annotations using snATAC-seq are highly concordant to that reported for sc RNA sequencing (scRNA-seq). The differentially accessible peaks (DAPs) for each cell type were characterized and the pattern of accessibility of the DAPs near cell type markers across cell types was similar to that of the average gene expression level of corresponding marker genes. Additionally, we found that peaks identified in snATAC-seq have the potential power to predict the cell type specific transcription starting site (TSS). We identified both transcription factors (TFs) whose binding motif were enriched in cell type DAPs of multiple cell types and cell type specific TFs by conducting transcription factor binding motif (TFBM) analysis. Furthermore, we identified the putative enhancer or promoter regions bound by TFs for each differentially expressed gene (DEG) with a DAP that overlapped with its TSS by generating cis-co-accessibility networks (CCAN). To predict the regulators of such DEGs, TFBM analysis was performed for each CCAN. The regulator TF-target DEG pairs predicted in this way were largely consistent with the results reported in the ENCODE Transcription Factor Targets Dataset (TFTD). This snATAC-seq approach provides insights into the regulation of chromatin accessibility landscape of porcine PBMCs and enables discovery of TFs predicted to control DEG through binding regulatory elements whose chromatin accessibility correlates with the DEG promoter region.

Gender Dimensions of Vulnerabilities, Adaptations and Alternative Livelihoods of the Closed Season in Elmina – Ghana: A Qualitative Study

A closed season policy has emerged as an ocean governance strategy aimed at protecting and conserving fish stocks across countries and coastal areas. Its implementation has produced traces of vulnerabilities, and forms of livelihood adaptations and alternative livelihood opportunities. However, little is known about how these occur among gender groups. This paper therefore focuses on the gender dimensions of vulnerabilities, adaptations and alternative livelihoods during the closed season in Elmina, Ghana, within the feminist political ecology framework. It employed Focus Group Discussions (FGDs) from purposively selected fishermen and fish processors. The study found significant differences in the vulnerability patterns among the gender groups, albeit some similarities. We further observed more fluid roles among the women than the men because the women were ready to undertake alternative livelihood options that were traditionally male-based during the closed season. Based on these results, we contend that political decisions toward environmental sustainability may create vulnerability and fluid adaptation patterns which may vary among gender groups in the light of their differential patterns of access, control and positionalities within the fishing industry.

Geosites of Northern Mountainous Adygeya (Southwestern Russia): A Novel Vision

Territorial inventories of geosites remain on the international agenda, and they can help in acquiring information for solving pure geological research tasks. New field investigations in the northern part of Mountainous Adygeya (geoheritage-rich territory in the western Greater Caucasus) permitted us to extend our knowledge of its geosites. Five geosites were described qualitatively and assessed semi-quantitatively, namely the Polkovnitskaya River Valley (ammonite-bearing concretions of Aptian glauconitic sandstones), the Little Khadzhokh River Valley (Aptian glauconitic sandstones with fossils and trace fossils), the Shakhan and Middle Khadzhokh River Valley (Upper Jurassic variegated siliciclastics, Hauterivian fluvial and deltaic sandstones, mixed ancient and modern clastic material), the Big Khadzhoh Waterfall (splendid waterfall and exposures of locally folded Oxfordian–Kimmeridgian limestones), and the Verblyud Mountain (small, camel-shaped cuesta’s remnant). They were ranked nationally (one geosite), regionally (three geosites), and locally (one geosite). Close examination of the considered geosites permitted to register pure geological peculiarities (changes in the dip direction between sedimentary packages), which indicate the tectonic activity across the Jurassic–Cretaceous transition. Additionally, complex accessibility patterns were established in some geosites, and these patterns should be addressed in further refinements of the semi-quantitative approaches to geosite assessment.

Abstract C089: Characterization of the breast tumor immune microenvironment in women of African descent using single-nucleus RNA- and ATAC-sequencing

Abstract Women of African descent are at an increased risk of developing and dying from aggressive subtypes of breast cancer. A connection between aggressive disease and Western Sub-Saharan African ancestry has been postulated, but it remains largely unknown to what extent breast cancer in Africa is reminiscent of breast cancer in U.S. African American (AA) women who experience disproportionately high mortality rates. We performed ATAC- and RNA-sequencing on 9 human triple-negative breast cancer cell lines of U.S. origin and discovered that African ancestry influences the chromatin landscape, leading to disparate transcription factor (TF) activity and downstream gene expression patterns indicative of an aggressive tumor biology. Here, we describe an ambitious study that employs single-nucleus (sn) ATAC- and RNA-sequencing (snMultiome) of frozen breast tumors to characterize chromatin accessibility and gene expression patterns with single-cell resolution in AA (n=33), Kenyan (n=25), and European American (EA, n=24) women in relation to genetic ancestry, risk factor exposures, clinical characteristics, and 5-year survival. To achieve this, we successfully isolated intact, high-quality single nuclei from archival frozen breast tumor tissue through an optimized combination of enzymatic digestion and automated tissue homogenization. We performed snMultiome sequencing of 82 tumors using the 10x Genomics platform. Following filtering, normalization (SCT for snRNA; LSI for snATAC), peak calling (MACS2), and integration (Harmony), our dataset includes a total of 296,557 nuclei. Cancerous (163,419 nuclei) and non-cancerous (133,138 nuclei) cells were distinguished based on DNA copy number (CopyKat). Within the microenvironment, 11 major immune, epithelial, and stromal cell types were successfully annotated, exhibiting distinct patterns by population group (e.g. AA tumors showed markedly increased abundance of myeloid and T-cells, while Kenyan tumors showed increased abundance of pericytes and fibroblasts, relative to EA). A large number of enriched TFs within each cell type varied significantly by population group, suggesting distinct chromatin accessibility patterns related to genetic ancestry. CD45+, EPCAM- cells were further extracted, clustered, and manually annotated for subpopulations based on known marker genes. We detected 26 distinct immune subpopulations across our samples, including 2 inflammatory macrophage, 6 immunosuppressive macrophage, 1 fibronectin+/thrombospondin+ monocyte, 6 T-cell, 1 natural killer cell, 2 B-cell, 1 mast cell, and 4 dendritic cell subpopulations. Differential gene expression analyses of each immune cell subpopulation, adjusted for age, BMI, and tumor subtype, revealed ancestry-specific gene expression patterns, which could provide novel insights into functional differences that may impact tumor immune response. Current efforts focus on in-depth molecular characterization of ancestry-related differences in the tumor immune environment and distinct signatures present in lethal disease. Citation Format: Alexandra R. Harris, Huaitian Liu, Brittany D. Jenkins, Tiffany H. Dorsey, Francis Makokha, Shahin Sayed, Gretchen Gierach, Stefan Ambs. Characterization of the breast tumor immune microenvironment in women of African descent using single-nucleus RNA- and ATAC-sequencing [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C089.

Assessing spatial configuration of barrier-free facilities from the perspective of age-friendliness: A case Study of Beijing, China

Enhancing urban inclusivity is a crucial task for sustainable urban development. One key challenge is to create seamless and accessible urban space that caters to the mobility needs of people, especially the elderly. Addressing this pressing challenge requires a comprehensive overview of barrier-free facilities (BFFs) configuration within cities. In this study, we propose an integrated framework for assessing the BFFs in Beijing by leveraging open BFFs data and mobile phone data. The proposed framework encompasses considerations of spatial distribution, accessibility, and supply-demand patterns of BFFs. Our findings reveal the significant agglomeration and heterogeneity of BFFs in Beijing, as well as serious spatial and social inequalities. Furthermore, the supply-demand relationship of BBFs in Beijing is relatively good, with 77.8% of supply-demand balanced areas. Overall, our study provides a holistic understanding of the BFFs within Beijing, offering valuable insights for informed decision-making in inclusive city planning and development.

Disparities in Spatial Access to Sleep Health Care in the United States: A Population-Based Geospatial Analysis

ObjectivesTo examine spatial access to sleep health care in the United States and investigate associations with demographic and socioeconomic characteristics, thereby identifying high-risk communities with limited spatial access to sleep health service. DesignA cross-sectional population-based geospatial analysis. Settings and ParticipantsResidents in US Census tracts across the 48 contiguous states, Alaska, and Hawaii. MethodsThe 2020 American Community Survey 5-year estimates, 2010 rural-urban commuting area codes, 2020 Area Deprivation Index, and sleep care provider locations from the National Provider Identifier file were used to assess the spatial access and related demographic/socioeconomic characteristics. Spatial access was measured by spatial access ratio using enhanced 2-step floating catchment area methods. The associations were investigated using logistic regression analysis and multivariate linear regression analysis. ResultsA total of 45.8 million residents experienced low spatial access to sleep health care. Spatial access decreased in rural and high Area Deprivation Index areas, and in areas characterized by higher population with uninsured status, vehicle unavailability, internet unavailability, cognitive difficulties, and hearing difficulties. With a 10% increase in the percentage of the racial minority (non-white) population, metropolitan census tracts experienced an increase in spatial access (3.268%), whereas micropolitan (−1.526%) and rural (−4.493%) areas experienced a decrease in spatial access. Similar findings were observed within the ethnic minority (Hispanic or Latino) population. Conclusions and ImplicationsDisparities exist in spatial access to sleep health care across the United States, especially for disadvantaged individuals. Racial/ethnic minorities exhibit contrasting spatial access patterns in urban and rural areas, with those in rural areas facing more challenges in spatial access to sleep health care.

TEE-MR: Developer-friendly data oblivious programming for trusted execution environments

Trusted execution environments (TEEs) enable efficient protection of integrity and confidentiality for applications running on untrusted platforms. They have been deployed in cloud servers to attract users who have concerns on exporting data and computation. However, recent studies show that TEEs’ side channels, including memory, cache, and micro-architectural features, are still vulnerable to adversarial exploitation. As many such attacks utilize program access patterns to infer secret information, data oblivious programs have been considered a practical defensive solution. However, they are often difficult to develop and optimize via either manual or automated approaches. We present the oblivious TEE with MapReduce (TEE-MR) approach that uses application frameworks, an approach between fully manual and fully automated, to hide the details of access-pattern protection to significantly minimize developers’ efforts. We have implemented the approach with the MapReduce application framework for data-intensive applications. It can regulate application dataflows and hide application-agnostic access-pattern protection measures from developers. Compared to manual composition approaches, it demands much less effort for developers to identify access patterns and to write code. Our approach is also easy to implement, less complicated than fully automated approaches, for which we have not seen a working prototype yet. Our experimental results show that TEE-MR-based applications have good performance, comparable to those carefully developed with time-consuming manual composition approaches.

Node and relevant data selection in distributed predictive analytics: A query-centric approach

Distributed Predictive Analytics (DPA) refers to constructing predictive models based on data distributed across nodes. DPA reduces the need for data centralization, thus, alleviating concerns about data privacy, decreasing the load on central servers, and minimizing communication overhead. However, data collected by nodes are inherently different; each node can have different distributions, volumes, access patterns, and features space. This heterogeneity hinders the development of accurate models in a distributed fashion. Many state-of-the-art methods adopt random node selection as a straightforward approach. Such method is particularly ineffective when dealing with data and access pattern heterogeneity, as it increases the likelihood of selecting nodes with low-quality or irrelevant data for DPA. Consequently, it is only after training models over randomly selected nodes that the most suitable ones can be identified based on the predictive performance. This results in more time and resource consumption, and increased network load. In this work, holistic knowledge of nodes’ data characteristics and access patterns is crucial. Such knowledge enables the successful selection of a subset of suitable nodes for each DPA task (query) before model training. Our method engages the most suitable nodes by predicting their relevant distributed data and learning predictive models per query. We introduce a novel DPA query-centric mechanism for node and relevant data selection. We contribute with (i) predictive selection mechanisms based on the availability and relevance of data per DPA query and (ii) various distributed machine learning mechanisms that engage the most suitable nodes for model training. We evaluate the efficiency of our mechanism and provide a comparative assessment with other methods found in the literature. Our experiments showcase that our mechanism significantly outperforms other approaches being applicable in DPA.

TPLAD: Template-Parsed Log Anomaly Detection for Electrical Database Systems

In recent years, with the increasing complexity of software systems, logs have become crucial for system maintenance. Log-based anomaly detection plays a vital role in automatically detecting system anomalies through log analysis. However, current log-based anomaly detection approaches encounter significant practical challenges. Supervised methods often require a large amount of manually labeled training data, which can be time-consuming and costly to obtain. On the other hand, unsupervised and semi-supervised approaches may suffer from subpar performance, as they do not leverage historical anomalies to improve their detection capabilities. These challenges underscore the necessity for the development of more efficient and effective log-based anomaly detection methods. Database anomaly access detection is critical for ensuring the stability and security of database systems. We present a survey of existing log anomaly detection models and propose a novel approach, Template-Parsed Log Anomaly Detection (TPLAD) model, for automated anomaly detection in massive database log files. The proposed model combines the original log template with template parsing using code and text semantic representation. Experimental results demonstrate the effectiveness of the proposed approach in detecting abnormal database access patterns, including runtime errors, unauthorized access, and data leaks. The findings indicate that TPLAD model shows promise in enhancing database security and stability in business systems.

Patterns of Alcohol Access Among Brazilian Adolescents: A Latent Class Analysis

Patterns of Alcohol Access Among Brazilian Adolescents: A Latent Class Analysis

A Scoping Review of the Utilization of Opioid Use Treatment, Harm Reduction, and Culturally Tailored Interventions Among Racial/Ethnic Minorities in the United States

AbstractAs part of a multilayered scoping review, we assessed literature on prevention and management interventions for racial/ethnic minorities in the United States (US) who non-medically use prescription opioids and/or who use illicit opioids such as heroin. The review specifically focused on access to and uptake of medications for opioid use disorder (MOUD) and harm reduction resources. We conducted a scoping review of peer-reviewed literature and governmental reports published between January 2000 and August 2024 on patterns of access to, and acceptability and utilization of, overdose prevention and opioid use management resources among racial/ethnic minorities in the US. Searches were conducted on Cochrane, PubMed, Embase, and Google Scholar, with us examining studies on the uptake of MOUD, such as buprenorphine and methadone, syringe services programs (SSPs), safe consumption sites, and harm reduction resources like naloxone (used to reverse overdoses) and fentanyl test strips (used to test for the presence of fentanyl in drug supplies). Additionally, we sought to identify and describe existing interventions for opioid use prevention and management that have expressly incorporated cultural adaptations related to racial/ethnic minorities’ specific needs and preferences in an effort to improve participants' sense of salience and acceptability and thus enhance utilization. We further endeavored to leverage this scoping review towards the development of research and intervention guidelines contoured to improve future scholarship and programming with these populations. The existing evidence suggests that racial/ethnic minorities in the US, specifically Black individuals, have diminished access to and/or utilization of preventive and management resources and amenities such as buprenorphine and naloxone, owing to structural deficits, provider bias, socioeconomic obstacles, geographic barriers, and communal stigma and distrust. Black individuals, relative to White individuals, also appear less likely to report using SSPs to obtain syringes and related resources, but across racial groups, those who used SSPs were more likely to be trained in, possess, and/or use naloxone. Further, there have been very few culturally tailored interventions for harm reduction or MOUD; there were limited data across the reviewed works on Native American/Indigenous or Asian populations; and the broader body of literature lacks methodological rigor. We close by proposing a cultural humility-focused model for better meeting the complex needs of these populations through research and primary and secondary intervention.