Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers.

To identify cancer-associated gene regulatory changes, we generated single-cell chromatin accessibility landscapes across eight tumor types as part of The Cancer Genome Atlas. Tumor chromatin accessibility is strongly influenced by copy number alterations that can be used to identify subclones, yet underlying cis-regulatory landscapes retain cancer type-specific features. Using organ-matched healthy tissues, we identified the "nearest healthy" cell types in diverse cancers, demonstrating that the chromatin signature of basal-like-subtype breast cancer is most similar to secretory-type luminal epithelial cells. Neural network models trained to learn regulatory programs in cancer revealed enrichment of model-prioritized somatic noncoding mutations near cancer-associated genes, suggesting that dispersed, nonrecurrent, noncoding mutations in cancer are functional. Overall, these data and interpretable gene regulatory models for cancer and healthy tissue provide a framework for understanding cancer-specific gene regulation.

Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA.

Drug resistance is the major cause of therapeutic failure in high-grade serous ovarian cancer (HGSOC). Yet, the mechanisms by which tumors evolve to drug resistant states remains largely unknown. To address this, we aimed to exploit clone-specific genomic structural variations by combining scaled single-cell whole genome sequencing with longitudinally collected cell-free DNA (cfDNA), enabling clonal tracking before, during and after treatment. We developed a cfDNA hybrid capture, deep sequencing approach based on leveraging clone-specific structural variants as endogenous barcodes, with orders of magnitude lower error rates than single nucleotide variants in ctDNA (circulating tumor DNA) detection, demonstrated on 19 patients at baseline. We then applied this to monitor and model clonal evolution over several years in ten HGSOC patients treated with systemic therapy from diagnosis through recurrence. We found drug resistance to be polyclonal in most cases, but frequently dominated by a single high-fitness and expanding clone, reducing clonal diversity in the relapsed disease state in most patients. Drug-resistant clones frequently displayed notable genomic features, including high-level amplifications of oncogenes such as CCNE1 , RAB25 , NOTCH3 , and ERBB2 . Using a population genetics Wright-Fisher model, we found evolutionary trajectories of these features were consistent with drug-induced positive selection. In select cases, these alterations impacted selection of secondary lines of therapy with positive patient outcomes. For cases with matched single-cell RNA sequencing data, pre-existing and genomically encoded phenotypic states such as upregulation of EMT and VEGF were linked to drug resistance. Together, our findings indicate that drug resistant states in HGSOC pre-exist at diagnosis and lead to dramatic clonal expansions that alter clonal composition at the time of relapse. We suggest that combining tumor single cell sequencing with cfDNA enables clonal tracking in patients and harbors potential for evolution-informed adaptive treatment decisions.

Extending the gift-utilizing residual human anatomical materials for training Pathologists' Assistants in surgical pathology techniques.

This study investigates the effectiveness of using residual human anatomical materials, obtained from a gross anatomy course, for training Pathologists' Assistant (PathA) students in surgical pathology techniques. We utilized two surveys to assess the perceived efficacy of this approach: one survey targeted PathA students to evaluate their training experiences with both human and animal tissues, while the other assessed the impact of specimen collection on the educational experiences of gross anatomy course students.

Ongoing genome doubling promotes evolvability and immune dysregulation in ovarian cancer.

Whole-genome doubling (WGD) is a critical driver of tumor development and is linked to drug resistance and metastasis in solid malignancies. Here, we demonstrate that WGD is an ongoing mutational process in tumor evolution. Using single-cell whole-genome sequencing, we measured and modeled how WGD events are distributed across cellular populations within tumors and associated WGD dynamics with properties of genome diversification and phenotypic consequences of innate immunity. We studied WGD evolution in 65 high-grade serous ovarian cancer (HGSOC) tissue samples from 40 patients, yielding 29,481 tumor cell genomes. We found near-ubiquitous evidence of WGD as an ongoing mutational process promoting cell-cell diversity, high rates of chromosomal missegregation, and consequent micronucleation. Using a novel mutation-based WGD timing method, doubleTime , we delineated specific modes by which WGD can drive tumor evolution: (i) unitary evolutionary origin followed by significant diversification, (ii) independent WGD events on a pre-existing background of copy number diversity, and (iii) evolutionarily late clonal expansions of WGD populations. Additionally, through integrated single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signaling and cGAS-STING pathway activation result from ongoing chromosomal instability and are restricted to tumors that remain predominantly diploid. This contrasted with predominantly WGD tumors, which exhibited significant quiescent and immunosuppressive phenotypic states. Together, these findings establish WGD as an evolutionarily 'active' mutational process that promotes evolvability and dysregulated immunity in late stage ovarian cancer.

A Latent Dirichlet Allocation approach to understanding students' perceptions of Automated Writing Evaluation.

Automated writing evaluation (AWE) has shown promise in enhancing students' writing outcomes. However, further research is needed to understand how AWE is perceived by middle school students in the United States, as they have received less attention in this field. This study investigated U.S. middle school students' perceptions of the MI Write AWE system. Students reported their perceptions of MI Write's usefulness using Likert-scale items and an open-ended survey question. We used Latent Dirichlet Allocation (LDA) to identify latent topics in students' comments, followed by qualitative analysis to interpret the themes related to those topics. We then examined whether these themes differed among students who agreed or disagreed that MI Write was a useful learning tool. The LDA analysis revealed four latent topics: (1) students desire more in-depth feedback, (2) students desire an enhanced user experience, (3) students value MI Write as a learning tool but desire greater personalization, and (4) students desire increased fairness in automated scoring. The distribution of these topics varied based on students' ratings of MI Write's usefulness, with Topic 1 more prevalent among students who generally did not find MI Write useful and Topic 3 more prominent among those who found MI Write useful. Our findings contribute to the enhancement and implementation of AWE systems, guide future AWE technology development, and highlight the efficacy of LDA in uncovering latent topics and patterns within textual data to explore students' perspectives of AWE.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data.

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

Experiencing violence and other predictors of within-person same-day use of multiple substances in youth: a longitudinal study in emergency settings.

Background: Although experiencing violence is a risk factor for substance use among youth, its association with same-day use of multiple substances (a form of polysubstance use) and mitigating factors is less well understood.Objectives: To identify whether prosocial factors modified the effect of experiencing violence on the frequency of same-day use, and examine gender-specific risk/protective factors for same-day use.Methods: We analyzed longitudinal data from a cohort of youth who use drugs aged 14-24 (n = 599; 58% male) presenting to an urban emergency department between 2009-2011 and assessed biannually for two years. Using Poisson-generalized linear models with person-level fixed effects, we estimated within-person associations between self-reported experiencing violence and same-day use and analyzed gender and peer/parent support as effect modifiers. We adjusted for negative peer influence, parental drug and alcohol use, family conflict, anxiety and depression, and age.Results: Overall, positive parental support corresponded to lower rates of same-day use (rate ratio [RR]:0.93, 95% CI:0.87-0.99) and experiencing violence was associated with higher rates of same-day use (RR:1.25, 95% CI:1.10-1.41). Violence exposure was a risk factor among males (RR:1.42, 95% CI:1.21-1.66), while negative peer influences and parental substance use were risk factors among females (RR:1.63, 95% CI:1.36-1.97 and RR:1.58, 95% CI:1.35-1.83, respectively). Positive peer support reduced the association between violence exposure and same-day use among males (RR:0.69, 95% CI:0.57-0.84, p < .05).Conclusions: Tailored interventions may address gender differences in coping with experiencing violence - including interventions that promote parental support among males and reduce influence from parental substance use among females.

Predictors of middle school students' perceptions of automated writing evaluation.

This study examined middle school students' perceptions of an automated writing evaluation (AWE) system, MI Write. We summarize students' perceptions of MI Write's usability, usefulness, and desirability both quantitatively and qualitatively. We then estimate hierarchical entry regression models that account for district context, classroom climate, demographic factors (i.e., gender, special education status, limited English proficiency status, socioeconomic status, grade), students' writing-related beliefs and affect, and students' writing proficiency as predictors of students' perceptions. Controlling for districts, students reporting more optimal classroom climate also reported higher usability, usefulness, and desirability for MI Write. Also, model results revealed that eighth graders, students with limited English proficiency, and students of lower socioeconomic status perceived MI Write relatively more useable; students with lower socioeconomic status also perceived MI Write relatively more useful and desirable. Students who liked writing more and more strongly believed that writing is a recursive process viewed MI Write as more useable, useful, and desirable. Students with greater writing proficiency viewed MI Write as less useable and useful; writing proficiency was not related to desirability perceptions. We conclude with a discussion of implications and future directions.

Where Do Adults in the United States Obtain Cannabis? A Nationally Representative Study Examining the Relationships Between Sociodemographic Factors, Cannabis Use Characteristics and Sources of Cannabis.

OBJECTIVE: Characterization of population subgroups based on where they acquire cannabis is unexplored. We examine relationships between sociodemographic characteristics, cannabis use modality, risky cannabis use, and source of cannabis. METHOD: Analyzing a representative sample (unweighted n = 8,089) of U.S. adults living in medical cannabis-permitting states with past-year cannabis use from the 2021 National Survey on Drug Use and Health, we determined source of last cannabis used. Outcome groups were purchased from a dispensary, purchased from another source, or nonpurchased source. Incorporating the complex survey design, descriptive statistics and adjusted multinomial logistic regressions evaluated associations between sociodemographic, individual cannabis use characteristics, and source of cannabis. Secondary analyses described cannabis purchasing characteristics among the subsample who last purchased cannabis. RESULTS: Purchasing from a dispensary was the most common source of cannabis (42.5%). Significant relationships between sociodemographic characteristics, cannabis use modality, risky cannabis use, and source of cannabis were found. Recent cannabis initiates and those with cannabis vaporizer use had an increased likelihood of purchasing cannabis from a dispensary. Purchasing from a nondispensary source was most likely among those with daily cannabis use, past-month blunt use, past-year driving under the influence, cannabis use disorder, and cannabis and alcohol co-use. Among those purchasing cannabis, joints and other forms of cannabis were more likely to be purchased from a dispensary than purchased from other sources. CONCLUSIONS: We identified key sociodemographic and cannabis use characteristics that may influence where individuals obtain cannabis, which are important for cannabis behavior surveillance and cannabis use prevention and intervention strategies to consider.

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement.

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.

Comparison of homemade mask designs based on calculated infection risk, using actual COVID-19 infection scenarios.

During pandemics such as COVID-19, shortages of approved respirators necessitate the use of alternative masks, including homemade designs. The effectiveness of the masks is often quantified in terms of the ability to filter particles. However, to formulate public policy the efficacy of the mask in reducing the risk of infection for a given population is considerably more useful than its filtration efficiency (FE). The effect of the mask on the infection profile is complicated to estimate as it depends strongly upon the behavior of the affected population. A recently introduced tool known as the dynamic-spread model is well suited for performing population-specific risk assessment. The dynamic-spread model was used to simulate the performance of a variety of mask designs (all used for source control only) in different COVID-19 scenarios. The efficacy of different masks was found to be highly scenario dependent. Switching from a cotton T-shirt of 8% FE to a 3-layer cotton-gauze-cotton mask of 44% FE resulted in a decrease in number of new infections of about 30% in the New York State scenario and 60% in the Harris County, Texas scenario. The results are valuable to policy makers for quantifying the impact upon the infection rate for different intervention strategies, e.g., investing resources to provide the community with higher-filtration masks.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data.

Multi-region DNA sequencing of primary tumors and metastases from individual patients helps identify somatic aberrations driving cancer development. However, most methods to infer copy-number aberrations (CNAs) analyze individual samples. We introduce HATCHet2 to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 introduces a novel statistic, the mirrored haplotype B-allele frequency (mhBAF), to identify mirrored-subclonal CNAs having different numbers of copies of parental haplotypes in different tumor clones. HATCHet2 also has high accuracy in identifying focal CNAs and extends the earlier HATCHet method in several directions. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 50 prostate cancer samples from 10 patients reveals previously-unreported mirrored-subclonal CNAs affecting cancer genes.

Writing motivation and ability profiles and transition during a technology-based writing intervention.

Students exhibit heterogeneity in writing motivation and ability. Profiles based on measures of motivation and ability might help to describe this heterogeneity and better understand the effects of interventions aimed at improving students' writing outcomes. We aimed to identify writing motivation and ability profiles in U.S. middle-school students participating in an automated writing evaluation (AWE) intervention using MI Write, and to identify transition paths between profiles as a result of the intervention. We identified profiles and transition paths of 2,487 students using latent profile and latent transition analysis. Four motivation and ability profiles emerged from a latent transition analysis with self-reported writing self-efficacy, attitudes toward writing, and a measure of writing writing: Low, Low/Mid, Mid/High, and High. Most students started the school year in the Low/Mid (38%) and Mid/High (30%) profiles. Only 11% of students started the school year in the High profile. Between 50 and 70% of students maintained the same profile in the Spring. Approximately 30% of students were likely to move one profile higher in the Spring. Fewer than 1% of students exhibited steeper transitions (e.g., from High to Low profile). Random assignment to treatment did not significantly influence transition paths. Likewise, gender, being a member of a priority population, or receiving special education services did not significantly influence transition paths. Results provide a promising profiling strategy focused on students' attitudes, motivations, and ability and show students' likeliness to belong to each profile based on their demographic characteristics. Finally, despite previous research indicating positive effects of AWE on writing motivation, results indicate that simply providing access to AWE in schools serving priority populations is insufficient to produce meaningful changes in students' writing motivation profiles or writing outcomes. Therefore, interventions targeting writing motivation, in conjunction with AWE, could improve results.

Assessing the diagnostic utility of the Cannabis Use Disorder Identification Test - Revised (CUDIT-R) among veterans with medical and non-medical cannabis use.

BACKGROUND: Few studies examine the utility of the Cannabis Use Disorder Identification Test - Revised (CUDIT-R) in relation to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, (DSM-5) criteria for cannabis use disorder (CUD). This study assesses the performance of the CUDIT-R among a sample of Veterans with and without medical cannabis use. METHODS: We approached and consented primary care patients presenting to one of three Department of Veterans Affairs (VA) Medical Centers. Veterans with at least monthly cannabis use and complete CUD data at baseline were included in this analysis (n=234). CUDIT-R scores were compared against Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (DSM-5) CUD as the standard to calculate measures of validity (sensitivity, specificity), identify optimal CUDIT-R cutoff values, and assess the diagnostic proficiency of the CUDIT-R using receiver operating characteristic (ROC) curves. We further stratified analyses by active medical cannabis card holder status and DSM-5 CUD severity (any, moderate, and severe). RESULTS: Among the entire sample, 38.9% qualified for any DSM-5 CUD, with 10.7% and 3.0% meeting criteria for moderate and severe CUD, respectively. We identified optimal CUDIT-R scores at 10 for any DSM-5 CUD (sensitivity=0.58; specificity=0.80), at 12 for moderate CUD (sensitivity=0.72; specificity=0.82), and at 14 for severe CUD (sensitivity=0.71; specificity=0.87). ROC curves showed higher CUDIT-R validity among non-card holders compared with medical cannabis card holders. CONCLUSION: The present study identified optimal CUDIT-R cutoff scores for Veterans who use cannabis. Varying DSM-5 validity measures inform the need for population-specific CUDIT-R cutoff values.

Firearms Availability Among High-School Age Youth With Recent Depression or Suicidality.

BACKGROUND AND OBJECTIVES: Limiting firearm access is essential to decreasing teen suicide. Previous efforts have focused on household firearms; however, less is known about firearm access and possession among teens at increased suicide risk. Our objective was to estimate prevalence of firearm possession and access among high school-aged teens with recent depression and/or lifetime history of suicidality (DLHS). METHODS: We conducted a probability-based, cross-sectional Web survey of 1914 parent-teen dyads between June 24, 2020, and July 22, 2020, with data weighted to generate a nationally representative sample of US teenagers (aged 14-18). Logistic regression analyses examined the difference between teens with and without DLHS for: (1) personal firearm possession, (2) perceived firearm access, and (3) method of firearm attainment. RESULTS: Among high school-aged teens, 22.6% (95% confidence interval [CI], 19.4-25.8) reported DLHS, 11.5% (95% CI, 8.7-14.3) reported personal firearm possession, and 44.2% (95% CI, 40.2-48.2) endorsed firearm access. Teens experiencing DLHS had increased perceived access (adjusted odds ratio, 1.56; 95% CI, 1.07-2.28) compared with non-DLHS peers. There was no association between DLHS and personal firearm possession (adjusted odds ratio, 0.97; 95% CI, 0.47-2.00). Among teens reporting firearm possession, those with DLHS were more likely to have acquired it by buying/trading for it (odds ratio, 5.66; 95% CI, 1.17-27.37) and less likely receiving it as a gift (odds ratio, 0.06; 95% CI, 0.01-0.36). CONCLUSIONS: High school-aged teens experiencing DLHS have higher perceived firearm access compared with lower-risk peers. Providers should speak directly to high school-aged teens at increased suicide risk about firearm access, in addition to counseling parents.

Development and characterization of a sorghum multi-parent advanced generation intercross (MAGIC) population for capturing diversity among seed parent gene pool.

Multiparent advanced eneration inter-cross (MAGIC) populations improve the precision of quantitative trait loci (QTL) mapping over biparental populations by incorporating increased diversity and opportunities to reduce linkage disequilibrium among variants. Here, we describe the development of a MAGIC B-Line (MBL) population from an inter-cross among 4 diverse founders of grain sorghum [Sorghum bicolor (L.) Moench] across different races (kafir, guinea, durra, and caudatum). These founders were selected based on genetic uniqueness and several distinct qualitative features including panicle architecture, plant color, seed color, endosperm texture, and awns. A whole set of MBL (708 F6) recombinant inbred lines along with their founders were genotyped using Diversity Arrays Technology (DArTseq) and 5,683 single-nucleotide polymorphisms (SNPs) were generated. A genetic linkage map was constructed using a set of polymorphic, quality-filtered markers (2,728 SNPs) for QTL interval-mapping. For population validation, 3 traits (seed color, plant color, and awns) were used for QTL mapping and genome-wide association study (GWAS). QTL mapping and GWAS identified 4 major genomic regions located across 3 chromosomes (Chr1, Chr3, and Chr6) that correspond to known genetic loci for the targeted traits. Founders of this population consist of the fertility maintainer (A/B line) gene pool and derived MBL lines could serve as female/seed parents in the cytoplasmic male sterility breeding system. The MBL population will serve as a unique genetic and genomic resource to better characterize the genetics of complex traits and potentially identify superior alleles for crop improvement efforts to enrich the seed parent gene pool.

Driving under the influence of cannabis, alcohol, and illicit drugs among adults in the United States from 2016 to 2020.

OBJECTIVE: Driving under the influence (DUI) of substances increases motor vehicle crash risk. Understanding current national trends of driving under the influence of alcohol (DUIA), cannabis (DUIC), and drugs other than cannabis (DUID) can inform public health efforts. Herein, we provide updated trends among United States (US) adults regarding DUIA, DUIC, DUID, and DUI of any substance. METHOD: We used nationally-representative National Survey on Drug Use and Health (2016-2020) data to derive prevalence estimates of past-year DUIC, DUIA, DUID, and DUI of any substance among non-institutionalized US adults and among those reporting respective past-year  substance use. Prevalence estimates and adjusted logistic regressions characterized temporal trends of these behaviors among US adults, among those with respective past-year substance use, and among stratified demographic subpopulations. RESULTS: Over 1 in 10 US adults reported DUI of any substance annually from 2016 to 2020.DUIA was most prevalent among all US adults (8.7% in 2017); however, this behavior is decreasing (AOR:0.96; 95%CI:0.94,0.98). No change in DUIC among the US adult population was found, but a decrease was found among those with past-year cannabis use (AOR:0.95; 95%CI:0.93,0.98), which coincided with a 29.1% increase in past-year cannabis use. There were no significant changes in overall DUID; however, females, those ages 26-34 and 65 or older with past-year use displayed increasing trends. DUI of any substance decreased among the US adult population. CONCLUSIONS: DUI remains a salient public health concern in the US and results indicate population subgroups who may benefit from impaired driving prevention interventions.

Vessel Rupture Thresholds for Vessel-Bubble Interactions Using an Earthworm Vasculature Model.

OBJECTIVE: Intravenous microbubble oscillation in the presence of ultrasound has the potential to yield a wide range of therapeutic benefits. However, the likelihood of vessel damage caused by mechanical effects has not been quantified as a function of the numerous important parameters in therapeutic ultrasound procedures. In this study, we examined the effects of microbubbles injected into the vasculature of the earthworm. It was found that the elastic properties of earthworm blood vessels are similar to those of arteries in older humans, and that earthworms are well suited to the large number of experiments necessary to investigate safety of procedures involving microbubble oscillation in sonicated vessels. METHODS: Microbubbles were infused into earthworm vessels, and the rupture time during sonication was recorded as a function of ultrasound frequency, pulse repetition frequency and acoustic pressure. DISCUSSION: A modified mechanical index (MMI) was defined that successfully captured the trends in rupture probability and rupture time for the different parameter values, creating a database of vessel rupture thresholds. In the absence of bubbles, the product of MMI squared and rupture time was approximately constant, indicating a possible radiation-force effect. CONCLUSION: The MMI was an effective correlating parameter in the presence of bubbles, though the mathematical dependence is not yet apparent. The results of the study are expected to be valuable in designing more refined studies in vertebrate models, as well as informing computational models.