Loyola University Maryland
  • Baltimore, Maryland, United States
Recent publications
Researchers strategically assess youth mental health by soliciting reports from multiple informants. Typically, these informants (e.g., parents, teachers, youth themselves) vary in the social contexts where they observe youth. Decades of research reveal that the most common data conditions produced with this approach consist of discrepancies across informants’ reports (i.e., informant discrepancies). Researchers should arguably treat these informant discrepancies as domain-relevant information: data relevant to understanding youth mental health domains (e.g., anxiety, depression, aggression). Yet, historically, in youth mental health research as in many other research areas, one set of paradigms has guided interpretations of informant discrepancies: Converging Operations and the Multi-Trait Multi-Method Matrix (MTMM). These paradigms (a) emphasize shared or common variance observed in multivariate data, and (b) inspire research practices that treat unique variance (i.e., informant discrepancies) as measurement confounds, namely random error and/or rater biases. Several years ago, the Operations Triad Model emerged to address a conceptual problem that Converging Operations does not address: Some informant discrepancies might reflect measurement confounds, whereas others reflect domain-relevant information. However, addressing this problem requires more than a conceptual paradigm shift beyond Converging Operations. This problem necessitates a paradigm shift in measurement validation. We advance a paradigm (Classifying Observations Necessitates Theory, Epistemology, and Testing [CONTEXT]) that addresses problems with using the MTMM in youth mental health research. CONTEXT optimizes measurement validity by guiding researchers to leverage (a) informants that produce domain-relevant informant discrepancies, (b) analytic procedures that retain domain-relevant informant discrepancies, and (c) study designs that facilitate detecting domain-relevant informant discrepancies.
Purpose Mental health problems are proliferating, and access to mental health care is difficult due to barriers imposed by the COVID-19 pandemic in low-income countries such as Bangladesh. University students are susceptible to mental health concerns, given their unique stressors (i.e., academic pressure, new social environment). Mindfulness techniques can promote mental health , yet their acceptability has not been examined among Bangladeshi university students. These techniques can be used on a digital app, to decrease barriers to use.Qualitative methods were used to examine the acceptability of mindfulness among university students in Bangladesh. In-depth interviews (n = 12) were conducted to examine student reactions to linguistically (Bangla) and culturally adapted mindfulness exercises. Thematic analysis generated three themes (1) previous experience with mindfulness (2) positive responses to and (3) improvements to mindfulness exercises. Results The results showed favourable attitudes towards the mindfulness content; students expressed positive psychological and physiological reactions. Students welcomed the concept of using these exercises on an app and felt it could overcomepast barriers to help-seeking. Conclusions This evidence suggests the value of exploring the acceptability of an app with mindfulness exercises for mental health promotion through a larger-scale pilot study in university students in Bangladesh.
Background Chronic obstructive pulmonary disease (COPD) causes 3 million deaths each year, yet 38% of COPD patients continue to smoke. Despite proof of effectiveness and universal guideline recommendations, smoking cessation interventions are underused in practice. We sought to develop an infographic featuring personalized biomedical risk assessment through future lung function decline prediction (with vs without ongoing smoking) to both prompt and enhance clinician delivery of smoking cessation advice and pharmacotherapy, and augment patient motivation to quit. Methods We recruited patients with COPD and pulmonologists from a quaternary care center in Toronto, Canada. Infographic prototype content and design was based on best evidence. After face validation, the prototype was optimized through rapid-cycle design. Each cycle consisted of: (1) infographic testing in a moderated focus group and a clinician interview (recorded/transcribed) (with questionnaire completion); (2) review of transcripts for emergent/critical findings; and (3) infographic modifications to address findings (until no new critical findings emerged). We performed iterative transcript analysis after each cycle and a summative qualitative transcript analysis with quantitative (descriptive) questionnaire analysis. Results Stopping criteria were met after 4 cycles, involving 20 patients (58% male) and 4 pulmonologists (50% male). The following qualitative themes emerged: Tool content (infographic content preferences); Tool Design (infographic design preferences); Advantages of Infographic Messaging (benefits of an infographic over other approaches); Impact of Tool on Determinants of Smoking Cessation Advice Delivery (impact on barriers and enablers to delivery of smoking cessation advice in practice); and Barriers and Enablers to Quitting (impact on barriers and enablers to quitting). Patient Likert scale ratings of infographic content and format/usability were highly positive, with improvements in scores for 20/21 questions through the design process. Providers scored the infographic at 77.8% (“superior”) on the Suitability Assessment of Materials questionnaire. Conclusions We developed a user preference-based personalized biomedical risk assessment infographic to drive smoking cessation in patients with COPD. Our findings suggest that this tool could impact behavioural determinants of provider smoking-cessation advice delivery, while increasing patient quit motivation. Impacts of the tool on provider care, patient motivation to quit, and smoking cessation success should now be evaluated in real-world settings.
To understand the differences in immune responses between early feathering (EF) and late feathering (LF) chickens after infection with avian leukosis virus, subgroup J (ALV-J), we monitored the levels of prolactin, growth hormone and the immunoglobulins IgG and IgM in the serum of LF and EF chickens for 8 weeks. Moreover, we analysed the expression of immune-related genes in the spleen and the expression of PRLR , SPEF2 and dPRLR in the immune organs and DF-1 cells by qRT–PCR. The results showed that ALV-J infection affected the expression of prolactin, growth hormone, IgG and IgM in the serum. Regardless of whether LF and EF chickens were infected with ALV-J, the serum levels of the two hormones and two immunoglobulins in EF chickens were higher than those in LF chickens ( P < 0.05). However, the expression of immune-related genes in the spleen of positive LF chickens was higher than that in the spleen of positive EF chickens. In the four immune organs, PRLR and SPEF2 expression was also higher in LF chickens than in EF chickens. Furthermore, the dPRLR expression of positive LF chickens was higher than that of negative LF chickens. After infection with ALV-J, the expression of PRLR in DF-1 cells significantly increased. In addition, overexpression of PRLR or dPRLR in DF-1 cells promoted replication of ALV-J. These results suggested that the susceptibility of LF chickens to ALV-J might be induced by dPRLR .
Background: The genetic disorder tuberous sclerosis complex (TSC) is frequently accompanied by the development of neuropsychiatric disorders, including autism spectrum disorder and intellectual disability, with varying degrees of impairment. These co-morbidities in TSC have been linked to the structural brain abnormalities, such as cortical tubers, and recurrent epileptic seizures (in 70-80% cases). Previous transcriptomic analysis of cortical tubers revealed dysregulation of genes involved in cell adhesion in the brain, which may be associated with the neurodevelopmental deficits in TSC. In this study we aimed to investigate the expression of one of these genes - cell-adhesion molecule contactin-3. Methods: Reverse transcription quantitative polymerase chain reaction for the contactin-3 gene (CNTN3) was performed in resected cortical tubers from TSC patients with drug-resistant epilepsy (n = 35, age range: 1-48 years) and compared to autopsy-derived cortical control tissue (n = 27, age range: 0-44 years), as well as by western blot analysis of contactin-3 (n = 7 vs n = 7, age range: 0-3 years for both TSC and controls) and immunohistochemistry (n = 5 TSC vs n = 4 controls). The expression of contactin-3 was further analyzed in fetal and postnatal control tissue by western blotting and in-situ hybridization, as well as in the SH-SY5Y neuroblastoma cell line differentiation model in vitro. Results: CNTN3 gene expression was lower in cortical tubers from patients across a wide range of ages (fold change = - 0.5, p < 0.001) as compared to controls. Contactin-3 protein expression was lower in the age range of 0-3 years old (fold change = - 3.8, p < 0.001) as compared to the age-matched controls. In control brain tissue, contactin-3 gene and protein expression could be detected during fetal development, peaked around birth and during infancy and declined in the adult brain. CNTN3 expression was induced in the differentiated SH-SY5Y neuroblastoma cells in vitro (fold change = 6.2, p < 0.01). Conclusions: Our data show a lower expression of contactin-3 in cortical tubers of TSC patients during early postnatal period as compared to controls, which may affect normal brain development and might contribute to neuropsychiatric co-morbidities observed in patients with TSC.
The IceCube Neutrino Observatory is a cubic kilometer neutrino detector located at the geographic South Pole designed to detect high-energy astrophysical neutrinos. To thoroughly understand the detected neutrinos and their properties, the detector response to signal and background has to be modeled using Monte Carlo techniques. An integral part of these studies are the optical properties of the ice the observatory is built into. The simulated propagation of individual photons from particles produced by neutrino interactions in the ice can be greatly accelerated using graphics processing units (GPUs). In this paper, we (a collaboration between NVIDIA and IceCube) reduced the propagation time per photon by a factor of up to 3 on the same GPU. We achieved this by porting the OpenCL parts of the program to CUDA and optimizing the performance. This involved careful analysis and multiple changes to the algorithm. We also ported the code to NVIDIA OptiX to handle the collision detection. The hand-tuned CUDA algorithm turned out to be faster than OptiX. It exploits detector geometry and only a small fraction of photons ever travel close to one of the detectors.
Epigenetic posttranslational modifications are critical for fine-tuning gene expression in various biological processes. SETD8 is so far the only known lysyl methyltransferase in mammalian cells to produce mono-methylation of histone H4 at lysine 20 (H4K20me1), a prerequisite for di- and tri-methylation. Importantly, SETD8 is related to a number of cellular activities, impinging upon tissue development, senescence and tumorigenesis. The double-strand breaks (DSBs) are cytotoxic DNA damages with deleterious consequences, such as genomic instability and cancer origin, if unrepaired. The homology-directed repair and canonical nonhomologous end-joining are two most prominent DSB repair pathways evolved to eliminate such aberrations. Emerging evidence implies that SETD8 and its corresponding H4K20 methylation are relevant to establishment of DSB repair pathway choice. Understanding how SETD8 functions in DSB repair pathway choice will shed light on the molecular basis of SETD8-deficiency related disorders and will be valuable for the development of new treatments. In this review, we discuss the progress made to date in roles for the lysine mono-methyltransferase SETD8 in DNA damage repair and its therapeutic relevance, in particular illuminating its involvement in establishment of DSB repair pathway choice, which is crucial for the timely elimination of DSBs.
This study highlighted how particular intersections of personal characteristics were related to Motivation to Learn (MtL) among adults. MtL is a prerequisite for adult education and training participation. However, little is known about MtL across subpopulations due to several methodological limitations. This study developed a national profile of MtL by key subpopulations that are defined by combinations of age, gender, education level, and literacy proficiency in the United States. Data were obtained from 2012/2014/2017 Program for International Assessment of Adult Competencies (PIAAC) restricted use file ( N = 8400). The alignment optimization (AO) method was employed to estimate subpopulation means of a PIAAC-based latent MtL construct. Subpopulations with younger age, greater educational attainment, and higher literacy proficiency showed significantly greater MtL.
Background Neurogenesis in the hippocampus endures across the lifespan but is particularly prolific during the first postnatal week in the developing rodent brain. The majority of new born neurons are in the dentate gyrus (DG). The number of new neurons born during the first postnatal week in the DG of male rat pups is about double the number in females. In other systems, the rate of cell proliferation is controlled by epigenetic modifications in stem cells. We, therefore, explored the potential impact of DNA methylation and histone acetylation on cell genesis in the developing DG of male and female rats. Methods Cell genesis was assessed by quantification of BrdU + cells in the DG of neonatal rats following injections on multiple days. Methylation and acetylation were manipulated pharmacologically by injection of well vetted drugs. DNA methylation, histone acetylation and associated enzyme activity were measured using commercially available colorimetric assays. mRNA was quantified by PCR. Multiple group comparisons were made by one- or two-way ANOVA followed by post-hoc tests controlling for multiple comparisons. Two groups were compared by t test. Results We found higher levels of DNA methylation in male DG and treatment with the DNA methylating enzyme inhibitor zebularine reduced the methylation and correspondingly reduced cell genesis. The same treatment had no impact on either measure in females. By contrast, treatment with a histone deacetylase inhibitor, trichostatin-A, increased histone acetylation in the DG of both sexes but increased cell genesis only in females. Females had higher baseline histone deacetylase activity and greater inhibition in response to trichostatin-A treatment. The mRNA levels of the proproliferative gene brain-derived neurotrophic factor were greater in males and reduced by inhibiting both DNA methylation and histone deacetylation only in males. Conclusions These data reveal a sexually dimorphic epigenetically based regulation of neurogenesis in the DG but the mechanisms establishing the distinct regulation involving DNA methylation in males and histone acetylation in females is unknown.
A recent article (JED 10:23, 2022) proposed defining terminal anorexia to improve access to palliative and hospice care, and to medical aid in dying for a minority of patients with severe and enduring anorexia nervosa (SE-AN). The authors presented three cases and, for two, the first author participated in their death. Anorexia nervosa is a treatable psychiatric condition for which recovery may be uncertain. We are greatly concerned however regarding implications of applying the label “terminal” to anorexia nervosa and the risk it will lead to unjustified deaths in individuals whose mental illness impairs their capacity to make a reasoned treatment decision.
Stroke is a leading cause of neurological injury characterized by impairments in multiple neurological domains including cognition, language, sensory and motor functions. Clinical recovery in these domains is tracked using a wide range of measures that may be continuous, ordinal, interval or categorical in nature, which can present challenges for multivariate regression approaches. This has hindered stroke researchers’ ability to achieve an integrated picture of the complex time-evolving interactions among symptoms. Here, we use tools from network science and machine learning that are particularly well-suited to extracting underlying patterns in such data, and may assist in prediction of recovery patterns. To demonstrate the utility of this approach, we analyzed data from the NINDS tPA trial using the Trajectory Profile Clustering (TPC) method to identify distinct stroke recovery patterns for 11 different neurological domains at 5 discrete time points. Our analysis identified 3 distinct stroke trajectory profiles that align with clinically relevant stroke syndromes, characterized both by distinct clusters of symptoms, as well as differing degrees of symptom severity. We then validated our approach using graph neural networks to determine how well our model performed predictively for stratifying patients into these trajectory profiles at early vs. later time points post-stroke. We demonstrate that trajectory profile clustering is an effective method for identifying clinically relevant recovery subtypes in multidimensional longitudinal datasets, and for early prediction of symptom progression subtypes in individual patients. This paper is the first work introducing network trajectory approaches for stroke recovery phenotyping, and is aimed at enhancing the translation of such novel computational approaches for practical clinical application.
The next two decades are expected to open the door to the first coincident detections of electromagnetic (EM) and gravitational-wave (GW) signatures associated with massive black-hole (MBH) binaries heading for coalescence. These detections will launch a new era of multimessenger astrophysics by expanding this growing field to the low-frequency GW regime and will provide an unprecedented understanding of the evolution of MBHs and galaxies. They will also constitute fundamentally new probes of cosmology and would enable unique tests of gravity. The aim of this Living Review is to provide an introduction to this research topic by presenting a summary of key findings, physical processes and ideas pertaining to EM counterparts to MBH mergers as they are known at the time of this writing. We review current observational evidence for close MBH binaries, discuss relevant physical processes and timescales, and summarize the possible EM counterparts to GWs in the precursor, coalescence, and afterglow stages of a MBH merger. We also describe open questions and discuss future prospects in this dynamic and quick-paced research area.
Young children’s math learning opportunities in families appear to relate to long-term math achievement and attitudes. While there is growing interest in promoting families’ support of children’s math learning, existing family math models do not fully capture sources of variation in how families support early math learning. We propose an expanded conceptual framework incorporating macrosystem and mesosystem dimensions, along with developmental considerations, that may influence family math engagement and children’s math learning. We use this framework to guide a systematic review on family math engagement from birth through early elementary school. Reviewing 194 articles from peer-reviewed journals, we asked three questions: 1) How do different aspects of family engagement relate to math outcomes? 2) What accounts for variation in family math engagement? and 3) What evidence is there for effective intervention approaches to support family math engagement? Building on prior models, we identify five facets of family engagement associated with children’s math learning, including math attitudes and expectations, math activities, math talk, the general home learning environment, and school involvement. We also identified sociocultural differences in family math engagement linked to race, ethnicity, socioeconomic status, and gender. Finally, family math intervention studies showed some short-term, but limited long-term, benefits to math engagement and children’s math learning. Our review also identified gaps in the family math engagement literature, particularly in understanding family math engagement across contexts and development. We use our expanded framework to propose future research considering sociocultural, community, and developmental dimensions of family math engagement.
The first statewide wildland-urban interface (WUI) maps were created for Alaska in 2000 and 2010. • Alaska experienced expanding WUI area and rapid housing growth within WUI from 2000 to 2010. • Housing density was the dominant contributor to WUI change. • As the distance from WUI increased, both human and lightning ignition density decreased but the percentage of fire perimeters increased within 30 km from WUI. A B S T R A C T Climate change is exacerbating the fire activity in Alaska, which exposes lives and properties to great risk, especially residents living in Wildland-Urban Interface (WUI). Therefore, it is crucial to characterize the spatial distribution and temporal dynamics of WUI and assess its impacts on fire activity. However, existing WUI delineations in Alaska do not cover all communities and apply different mapping approaches, making it difficult to examine the WUI distribution and dynamics across the state. This study created the first statewide WUI map using census data and National Land Cover Database, and characterized the dynamics of WUI from 2000 to 2010. Furthermore, the relationship between WUI and fire was identified using fire ignition and fire perimeter datasets from Alaska Interagency Coordination Center. The findings showed WUI that only covered 0.22 % of the total area in Alaska contained 73.45 % of the housing units. Nearly 85 % of newly added WUI housing units were found in WUI, and the growth rates in WUI housing units far exceeded that in non-WUI. As the distance from WUI increased, both human and lightning ignition density decreased but the percentage of fire perimeters increased within 30 km from WUI. Our results demonstrated the importance of tracking the dynamics of WUI and characterizing the social change behind the pattern to strengthen wildfire preparedness and facilitate community-adapted management.
Some test amplification tools extend a manually created test suite with additional test cases to increase the code coverage. The technique is effective, in the sense that it suggests strong and understandable test cases, generally adopted by software engineers. Unfortunately, the current state-of-the-art for test amplification heavily relies on program analysis techniques which benefit a lot from explicit type declarations present in statically typed languages. In dynamically typed languages, such type declarations are not available and as a consequence test amplification has yet to find its way to programming languages like Smalltalk, Python, Ruby and Javascript. We propose to exploit profiling information —readily obtainable by executing the associated test suite— to infer the necessary type information creating special test inputs with corresponding assertions. We evaluated this approach on 52 selected test classes from 13 mature projects in the Pharo ecosystem containing approximately 400 test methods. We show the improvement in killing new mutants and mutation coverage at least in 28 out of 52 test classes (≈ 53%). Moreover, these generated tests are understandable by humans: 8 out of 11 pull-requests submitted were merged into the main code base (≈ 72%). These results are comparable to the state-of-the-art, hence we conclude that test amplification is feasible for dynamically typed languages.
The performance of heat pumps in electric vehicles drops significantly at low ambient temperatures due to low suction density and high-pressure ratios. To resolve this issue, we proposed the kangaroo heat pump cycle (KC). It is an enhanced flash tank-based vapor injection heat pump cycle (FT-VIC) that adds a sub-cycle before the refrigerant enters the flash tank, which increases the injection mass flow rate and leads to a higher heating capacity. Thermodynamic cycle models were developed for the basic heat pump cycle, FT-VIC, and KC. Furthermore, their heating performances, the annual energy consumption, and life cycle climate performance (LCCP) were evaluated and compared while using R-1234yf as the refrigerant. Results show that as compared to the FT-VIC, the KC increases the heating capacity by 25.7% and 20.1% and reduces the coefficient of performance by 25.8% and 18.9% when the ambient temperature is −5 °C and −15 °C, respectively. Due to the additional weight of the sub-cycle, the LCCP of KC is on average 4.6% higher than that of FT-VIC. In conclusion, the KC can provide more heating capacity in extremely cold conditions with additional energy consumption but is still more efficient than relying on the low-efficient PTC heater to meet the target heating capacity.
Dual-metal single-atom catalysts (DACs) with an intrinsic synergy and multiple coordination structures are flourishing for oxygen reduction reaction (ORR), on the basis of optimization and regulation of the electron configuration for active centers. Herein, a two-step strategy consisting of cavity confinement and post-adsorption is developed to prepare a nitrogen-doped carbon catalyst co-supported by high-density ZnN4 and CoN4 sites (denoted as ZnCo-NC-II) through metal-organic framework (MOF) engineering. Structural characterization incorporated with density functional theory (DFT) calculation demonstrates that electrons are transferred from Zn (donors) to nearby Co (acceptors) through the conjugated graphene π-bond. The optimized Co d-band center achieves a moderate adsorption strength between O2 and CoN4 active sites. So, the rate-determining step (RDS) for the *OOH formation is accelerated. Therefore, ZnCo-NC-II exhibits a distinguished ORR activity with a half-wave potential (E1/2) of 0.86 and 0.79 V (vs RHE) in alkaline and acid media, respectively. The zinc-air battery built with the ZnCo-NC-II catalyst shows excellent electrochemical performance for an immediate practical application. Our work is conducive to an atomic-level clarification on both the composition and design and thereof the synergistic catalytic mechanism with dual-metal sites.
This paper provides an example of the successful incorporation of a virtual project-based learning (PBL) assignment as a significant component of two business courses during the COVID-19 pandemic. In these courses, undergraduate accounting and global business students worked with local nonprofits to solve real-world business problems in a virtual environment. This collaboration afforded students the opportunity to practice professional competency skills while growing in their understanding of business and of nonprofits. This paper discusses the challenges and successes that occurred during the implementation of the virtual project, encourages the use of PBL and other innovative teaching projects when teaching online, and facilitates faculty design and implementation of virtual learning programs.
Language switch costs have been explored less in receptive tasks than in productive tasks, and previous studies have produced mixed findings with regard to switch cost symmetry and the relationship of switch costs to executive function. To address these unresolved gaps, one hundred Chinese–English bilingual adults completed a bilingual lexical decision task and three tasks measuring executive function, and we used mixed effects models and correlational analyses to answer the two research questions. The results showed asymmetry with larger costs into the second language, but this was qualified by interactions with response sequence effects. No evidence was found for a relationship between switch costs and inhibition or shifting. Together, rather than supporting a model involving top-down control mechanisms as has been suggested to account for switch cost patterns in productive tasks, these findings support a bottom-up, activation-based model of bilingual word recognition and receptive language switching.
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Gloria Phillips-Wren
  • Department of Information Systems/ Operations Management
Bahram Roughani
  • Department of Physics
Christopher Morrell
  • Department of Mathematics and Statistics
Inge Heyer
  • Department of Physics
Martin F Sherman
  • Department of Psychology
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