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After request completion, an I/O device must decide whether to minimize latency by immediately firing an interrupt or to optimize for throughput by delaying the interrupt, anticipating that more requests will complete soon and help amortize the interrupt cost. Devices employ adaptive interrupt coalescing heuristics that try to balance between these opposing goals. Unfortunately, because devices lack the semantic information about which I/O requests are latency-sensitive, these heuristics can sometimes lead to disastrous results. Instead, we propose addressing the root cause of the heuristics problem by allowing software to explicitly specify to the device if submitted requests are latency-sensitive. The device then “calibrates” its interrupts to completions of latency-sensitive requests. We focus on NVMe storage devices and show that it is natural to express these semantics in the kernel and the application and only requires a modest two-bit change to the device interface. Calibrated interrupts increase throughput by up to 35%, reduce CPU consumption by as much as 30%, and achieve up to 37% lower latency when interrupts are coalesced. [ABSTRACT FROM AUTHOR]

Introduction: This review aims to synthesise the literature on the efficacy, evolution, and challenges of implementing Clincian Decision Support Systems (CDSS) in the realm of mental health, addiction, and concurrent disorders., Methods: Following PRISMA guidelines, a systematic review and meta-analysis were performed. Searches conducted in databases such as MEDLINE, Embase, CINAHL, PsycINFO, and Web of Science through 25 May 2023, yielded 27,344 records. After necessary exclusions, 69 records were allocated for detailed synthesis. In the examination of patient outcomes with a focus on metrics such as therapeutic efficacy, patient satisfaction, and treatment acceptance, meta-analytic techniques were employed to synthesise data from randomised controlled trials., Results: A total of 69 studies were included, revealing a shift from knowledge-based models pre-2017 to a rise in data-driven models post-2017. The majority of models were found to be in Stage 2 or 4 of maturity. The meta-analysis showed an effect size of -0.11 for addiction-related outcomes and a stronger effect size of -0.50 for patient satisfaction and acceptance of CDSS., Discussion: The results indicate a shift from knowledge-based to data-driven CDSS approaches, aligned with advances in machine learning and big data. Although the immediate impact on addiction outcomes is modest, higher patient satisfaction suggests promise for wider CDSS use. Identified challenges include alert fatigue and opaque AI models., Conclusion: CDSS shows promise in mental health and addiction treatment but requires a nuanced approach for effective and ethical implementation. The results emphasise the need for continued research to ensure optimised and equitable use in healthcare settings., (© 2024 The Author(s). Journal of Evaluation in Clinical Practice published by John Wiley & Sons Ltd.)

The number of overdose-related fatalities continues to reach historic levels across Canada, despite ongoing efforts by authorities. To reduce mortality, a clinical trajectory ranging from preventative measures to crisis intervention, skill training to treatment, and risk assessment to risk management needs to be supported. The web-based Risk Assessment and Management Platform (RAMP) was developed to realize this concept and to empower people who use drugs through an integrated tool that allows them to better understand and manage their risk of overdose. This paper outlines the architecture and development of RAMP, which is built on the WordPress platform. WordPress components are mapped onto a 3-tier architecture that consists of presentation, application, and database layers. The architecture facilitates the development of a modular software that includes several features that are independent in functionality but interact with each other in an integrated platform. The relatively low coupling and high coherence of the features may reduce the cost of maintenance and increase flexibility of future developments. RAMP's architecture comprises a user interface, conceptual framework, and backend layers. The RAMP front end effectively uses some of the WordPress' features such as HTML5, CSS, and JavaScript to create a mobile, friendly, and scalable user interface. The RAMP backend uses several standard and custom WordPress plug-ins to support risk assessment and monitoring, with the goal of mitigating the impacts and eliminating risks together. A rule-based decision support system has been hard-coded to suggest relevant modules and goals to complement each user's lifestyle and goals based on their risk assessment. Finally, the backend uses the MySQL database management system and communicates with the RAMP framework layer via the data access layer to facilitate a timely and secure handling of information. Overall, RAMP is a modular system developed to identify and manage the risk of opioid overdose in the population of people who use drugs. Its modular design uses the WordPress architecture to efficiently communicate between layers and provide a base for external plug-ins. There is potential for the current system to adopt and address other related fields such as suicide, anxiety, and trauma. Broader implementation will support this concept and lead to the next level of functionality., (©Alireza Kazemi, Marisha Boyd, Fiona Choi, Andy Man Yeung Tai, Vivian WL Tsang, Tam To, Jane Kim, Kerry Jang, Farhud Shams, Stefanie Schreiter, Maurice Cabanis, Reinhard Michael Krausz. Originally published in JMIR Formative Research (https://formative.jmir.org), 11.03.2024.)

Competing Interests: Declaration of Conflicting InterestsMV has received consultation and speaker fees from Camurus. AP holds a US patent entitled “Tetrahydroprotoberbine Compounds and Uses Thereof “ in the Treatment of Neurological, Psychiatric and Neurodegenerative Diseases (United States, US20150306092) and holds shares in Resilience Biosciences Inc., Canada, focused on tetrahydroprotoberberine drug development. MI declares receiving honoraria for presenting (BCCSU, WCAF, Indivior), receiving VCHRI Team Grant (Fentanyl Cohort Study), receiving CSAM grant (Development of Stigma Series), being awarded the UBC/VGH Foundation BMO Capital Markets Innovators Challenge (Clinical Application of a Compact, Quantitative, and Inexpensive Opioid Detector), receiving research stipend (BCCfE The Hope to Health Research & Innovation Centre) and participating in a regional consult meeting for Otsuka and Lundbeck. The other authors declare no conflict of interest.

Background: Substance use disorders affect 36 million people globally, but only a small proportion of them receive the necessary treatment. E-health interventions have been developed to address this issue by improving access to substance use treatment. However, concerns about participant engagement and adherence to these interventions remain. This review aimed to evaluate adherence to e-health interventions targeting substance use and identify hypothesized predictors of adherence., Methods: A systematic review of literature published between 2009 and 2020 was conducted, and data on adherence measures and hypothesized predictors were extracted. Meta-analysis and meta-regression were used to analyze the data. The two adherence measures were (a) the mean proportion of modules completed across the intervention groups and (b) the proportion of participants that completed all modules. Four meta-regression models assessed each covariate including guidance, blended treatment, intervention duration and recruitment strategy., Results: The overall pooled adherence rate was 0.60 (95%-CI: 0.52-0.67) for the mean proportion of modules completed across 30 intervention arms and 0.47 (95%-CI: 0.35-0.59) for the proportion of participants that completed all modules across 9 intervention arms. Guidance, blended treatment, and recruitment were significant predictors of adherence, while treatment duration was not., Conclusion: The study suggests that more research is needed to identify predictors of adherence, in order to determine specific aspects that contribute to better exposure to intervention content. Reporting adherence and predictors in future studies can lead to improved meta-analyses and the development of more engaging interventions. Identifying predictors can aid in designing effective interventions for substance use disorders, with important implications for e-health interventions targeting substance use., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: In Egypt, the shortage of mental health services, particularly for adolescents and young adults, is apparent. Electronic mental health (EMH) has been proposed as a solution to bridge the gap and better address the needs of young people. However, EMH is new to Egypt and its acceptability among target populations is crucial to its implementation and success., Objective: The objective of this study is to explore the interest of Egyptian youth in EMH, identify perceived barriers to EMH, and inform the design of EMH tools to best address the needs of youth., Methods: A web-based cross-sectional survey was distributed among medical students at Tanta University in Egypt. Chi-square and one-way analysis of variance tests were performed for inferential analyses using a significance level of .05., Results: Of the 707 individuals who completed the survey (90.9% response rate), 60.5% (428) were female, 62% (438) lived in urban and suburban areas, and the mean age of the sample was 20.5 (SD 1.8) years. The vast majority of participants (522/707, 73.8%) had already used the internet to find information about mental health problems, but the information was unsatisfactory for about half of them (386/707, 54.6%). Almost all students reported that they would prefer web-based therapy if EMH were available through a trustworthy national web-based platform for youth mental health (601/707, 85%). Students believed that emotional difficulties, social support, and coping strategies were the main topics that EMH should help with. The most common perceived barriers for EMH use in Egypt were concerns about privacy (382/707, 54%) and a lack of technology literacy and unfamiliarity with EMH (352/707, 50%)., Conclusions: EMH is a promising strategy for addressing gaps in the mental health care for young people. To construct and implement a digital system of care that addresses the unique needs and preferences of youth, adolescents and young adults should be involved in the co-development and design., (©Mostafa Mamdouh, Andy Man Yeung Tai, Jean Nicolas Westenberg, Farhud Shams, Kerry Jang, Adel Badawy, Houssam Elsawi, Michael Krausz. Originally published in JMIR Formative Research (https://formative.jmir.org), 21.03.2022.)

Aim: First use of opioids often happens in adolescence and an increasing number of opioid overdoses are being reported among youth. The purpose of this narrative review was to present the treatment approaches for youth with high-risk opioid use, determine whether the literature supports the use of opioid agonist treatment among youth and identify evidence for better treatment outcomes in the younger population., Methods: A search of the literature on PubMed using MeSH terms specific to youth, opioid use and treatment approaches generated 1436 references. Following a screening process, 137 papers were found to be relevant to the treatment of high-risk opioid use among youth. After full-text review, 19 eligible studies were included: four randomized controlled trials, nine observational studies and six reviews., Results: Research for the different treatment options among youth is limited. The available evidence shows better outcomes in terms of retention in care and cost-effectiveness for opioid agonist treatment than abstinence-based comparisons. Integrating psychosocial interventions into the continuum of care for youth can be an effective way of addressing comorbid psychiatric conditions and emotional drivers of substance use, leading to improved treatment trajectories., Conclusions: From the limited findings, there is no evidence to deny youth with high-risk opioid use the same treatment options available to adults. A combination of pharmacological and youth-specific psychosocial interventions is required to maximize retention and survival. There is an urgent need for more research to inform clinical strategies toward appropriate treatment goals for such vulnerable individuals., (© 2021 John Wiley & Sons Australia, Ltd.)

Introduction: Machine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learning/Artificial Intelligence (AI) may instantiate such capabilities, as well as provide rationale for its application to psychiatry in both research and clinical ecosystems., Methods: Databases PubMed and PsycINFO were searched from 1966 to June 2016 for keywords:Big Data, Machine Learning, Precision Medicine, Artificial Intelligence, Mental Health, Mental Disease, Psychiatry, Data Mining, RDoC, and Research Domain Criteria. Articles selected for review were those that were determined to be aligned with the objective of this particular paper., Results: Results indicate that AI is a viable option to build useful predictors of outcome while offering objective and comparable accuracy metrics, a unique opportunity, particularly in mental health research. The approach has also consistently brought notable insight into disease models through processing the vast amount of already available multi-domain, semi-structured medical data. The opportunity for AI in psychiatry, in addition to disease-model refinement, is in characterizing those at risk, and it is likely also relevant to personalizing and discovering therapeutics., Conclusions: Machine learning currently provides an opportunity to parse disease models in complex, multi-factorial disease states (e.g. mental disorders) and could possibly inform treatment selection with existing therapies and provide bases for domain-based therapeutic discovery., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Loss of DNA copy number at the short arm of chromosome 3 is one of the most common genetic changes in human lung cancer, suggesting the existence of one or more tumor suppressor genes (TSG) at 3p. To identify most frequently deleted regions and candidate TSGs within these regions, a recently developed single-nucleotide polymorphism (SNP)-mass spectrometry-genotyping (SMSG) technology was applied to investigate the loss of heterozygosity (LOH) in 30 primary non-small-cell lung cancers. A total of 386 SNP markers that spanned a region of 70 Mb at 3p, from 3pter to 3p14.1, were selected for LOH analysis. The average intermarker distance in the present study is approximately 180 kb. Several frequently deleted regions, including 3p26.3, 3p25.3, 3p24.1, 3p23, and 3p21.1, were found. Several candidate TSGs within these frequently detected LOH regions have been found, including APG7L at 3p25.3, CLASP2 at 3p23, and CACNA2D3 at 3p21.1. This study also showed that SMSG technology is a very useful approach to rapidly define the minimal deleted region and to identify target TSGs in a given cancer.

Lung cancer is one of the most common causes of cancer death worldwide. Although many efforts have been made to explore the mechanisms involved in the development of lung cancer, the genetic events involved in the pathogenesis of lung cancer are still unclear. For a better mechanistic scope of study, a well-established cellular model is essential. We report the establishment of a squamous cell carcinoma (SCC) cell line of human lung, SCC-37. Chromosomal abnormalities and global genomic alterations of SCC-37 were studied by spectral karyotyping (SKY) and comparative genomic hybridization (CGH), respectively. Results showed that SCC-37 was a hypodiploid with complex chromosomal rearrangements. Some of the alterations, such as the gain of 1q25-qter in SCC-37, have been correlated to the tumor recurrence of non-small cell lung cancer (NSCLC). Other interesting findings include the amplification of 3q25-qter and 12q13, suggesting the existence of important oncogenes in the amplicons. This cell line may thus provide a useful cellular resource for studying the pathogenesis of SCC of the lung in the future.

Background: Lung carcinoma is a leading cause of cancer deaths worldwide. To better understand this disease, the authors studied genetic alterations in nonsmall cell lung carcinoma (NSCLC) and the association between genetic changes and clinical features., Methods: Genetic alterations in 30 patients with adenocarcinoma (AC) and 39 patients with squamous cell carcinoma (SCC) were analyzed by comparative genomic hybridization. The genetic changes in patients with AC and SCC were compared and the associations of these changes with clinical features were studied., Results: A gain of 3q with a minimal amplified region at 3q25.3-qter was significantly higher in patients with SCC compared with patients with AC (72% vs. 27%; P < 0.001). A gain of 20q and loss of chromosome 9 were detected more frequently in patients with AC compared with patients with SCC (P < 0.05). Gains of 5p and 20q and loss of 5q were significantly correlated with an advanced stage of NSCLC (P < 0.05). Amplification of 1q was significantly associated with NSCLC recurrence (P = 0.04)., Conclusions: The results of the current study suggested that different chromosomal aberrations may contribute to the types and pathologic stages of NSCLC., (Copyright 2004 American Cancer Society.)