Youth-Reported School Connection and Experiences of a Middle SchooleBased Screening, Brief Intervention, and Referral to Treatment Initiative: Preliminary Results From a Program Evaluation

Purpose This study aimed (1) to evaluate the feasibility of a school-based Screening, Brief Intervention, and Referral to Treatment (SBIRT) program that expands on traditional SBIRT to support the mental health and well-being of middle school students and (2) to assess its effects on students’ connection with adults at school. Methods Focus group discussions were conducted with 26 students in grades 6–8 to understand student perspectives about an innovative school-based SBIRT program. A subset of middle school students from the SBIRT program who received a brief intervention (BI) after screening (n = 116) were asked to rate their experience meeting with the interventionist in terms of feeling comfortable, feeling listened to, and talking about their goals. Additionally, these students’ ratings of connection to adults at school was compared from the time of screening (baseline) to following BI using two-sided paired t-tests. Results Students who participated in focus groups expressed favorable opinions about universal screening and this school-based SBIRT model and noted that relationship building with adults at school was an important factor for open communication and motivating behavior change for students. Nearly all students who completed the post-BI survey rated their experiences with interventionists during BI as “Excellent,” “Very Good,” or “Good” in all categories (98%). Students’ reported mean school connection scores significantly higher after participation in school-based SBIRT than at baseline (5.9/8 vs. 7.0/8, p \u3c .001). Discussion Middle school students were satisfied with the school-based SBIRT model and participation in the program resulted in increased student connection with adults at school. These findings improve our understanding of the experience of SBIRT intervention with middle school students and on school connection in particular

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Screentime Screening, Berwick Film and Media Arts Festival

Screening of three short video works by young filmmakers in Berwick, made collaboratively with artists Kimberley O’Neill and Kathryn Elkin. Applying techniques of digital filmmaking and documentary storytelling, the films explore entangled relationships between people, technology and the local environment. Berwick Film & Media Arts Festival (BFMAF) is an artistically ambitious and inclusive organisation for new cinema and artists’ moving image. Based in North Northumberland, the Festival leads through collaboration and research. With a resolute commitment to peer support, artistic production and community development, the Film Festival is recognised for its innovative programming and critical engagement

Gene expression profile testing for breast cancer and the use of chemotherapy, serious adverse effects, and costs of care

As gene expression profile (GEP) testing for breast cancer may provide additional prognostic information to guide the use of adjuvant chemotherapy, we examined the association between GEP testing and use of chemotherapy, serious chemotherapy-related adverse effects, and total charges during the 12 months following diagnosis. Medical record review was conducted for women age 30-64 years, with incident, non-metastatic, invasive breast cancer diagnosed 2006-2008 in a large, national health plan. Of 534 patients, 25.8% received GEP testing, 68.2% received chemotherapy, and 10.5% experienced a serious chemotherapy-related adverse effect. GEP testing was most commonly used in women at moderate clinical risk of recurrence (52.0 vs. 25.0% of low-risk women and 5.5% of high-risk). Controlling for the propensity to receive GEP testing, women who had GEP were less likely to receive chemotherapy (propensity adjusted odds ratio, 95% confidence interval 0.62, 0.39-0.99). Use of GEP was associated with more chemotherapy use among women at low risk based on clinical characteristics (OR = 42.19; CI 2.50-711.82), but less use among women with a high risk based on clinical characteristics (OR = 0.12; CI 0.03-0.47). Use of GEP was not associated with chemotherapy for the moderate risk group. There was no significant relationship between GEP use and either serious chemotherapy-associated adverse effects or total charges. While GEP testing was associated with an overall decrease in adjuvant chemotherapy, we did not find differences in serious chemotherapy-associated adverse events or charges during the 12 months following diagnosis

An Independent Assessment of a Commercial Clinical Interpretation Software Indicates That Software Can Mitigate Variation in Human Assessment

Comprehensive next-generation sequencing (NGS) panels for cancer diagnostics create a bottleneck for interpretation. QIAGEN Clinical Insights Interpret One (QCI) is a clinical decision support software that supports molecular pathologists in the classification of oncology-related variants. This study compares variant assessments by QCI to assessments utilizing current laboratory methods. Eight laboratories were recruited by the external quality assessment organization GenQA. The laboratories submitted VCFs from sequencing studies performed on both hematological disorders and solid tumors for analysis by QCI and an independent laboratory. Results were compared and conflicts were resolved using a panel of experts. In total, 14/149 variants (9%) reported as Tier 1 or Tier 2 by either QCI or the submitting laboratory were found to be discordant after expert panel review. In contrast, 41/149 variants (28%) reflected discrepancy among human reviewers. The expert panel was unable to reach resolution on eight variants. QCI demonstrates high concordance in the classification of actionable mutations with independent laboratory methods and expert assessment. The rate of disagreement among laboratories and the expert panel was greater than the disagreement between QCI and expert assessment. Disagreement among experts highlights the subjectivity of classifying variants. The study demonstrates that QCI interpretation supports streamlining and standardization of NGS variant interpretation

Clinical practice patterns and cost effectiveness of human epidermal growth receptor 2 testing strategies in breast cancer patients

BACKGROUND: Testing technologies are increasingly used to target cancer therapies. Human epidermal growth factor receptor 2 (HER2) testing to target trastuzumab for patients with breast cancer provides insights into the evidence needed for emerging testing technologies. METHODS: The authors reviewed literature on HER2 test utilization and cost effectiveness of HER2 testing for patients with breast cancer. They examined available evidence on: percentage of eligible patients tested for HER2; test methods used; concordance of test results between community and central/reference laboratories; use of trastuzumab by HER2 test result; and cost effectiveness of testing strategies. RESULTS: Little evidence was available to determine whether all eligible patients are tested, how many are retested to confirm results, and how many with negative HER2 test results still receive trastuzumab. Studies suggested that up to 66% of eligible patients had no documentation of testing in claims records, up to 20% of patients receiving trastuzumab were not tested or had no documentation of a positive test, and 20% of HER2 results may be incorrect. Few cost-effectiveness analyses of trastuzumab explicitly considered the economic implications of various testing strategies. CONCLUSIONS: There was little information about the actual use of HER2 testing in clinical practice, but evidence suggested important variations in testing practices and key gaps in knowledge exist. Given the increasing use of targeted therapies, it is critical to build an evidence base that supports informed decision making on emerging testing technologies in cancer care