cssi/SciSciGPT-SciSciNet huggingface dataset:
Abstract CT047: Phase I trial of intravesical Bacillus Calmette-Guérin combined with intravenous Pembrolizumab in high grade nonmuscle invasive bladder cancer

PURPOSE: A phase I trial of intravesical bacillus Calmette-Guerin (BCG) in combination with systemic pembrolizumab was conducted in patients with high grade non-muscle invasive bladder cancer who had persistent or recurrent disease after failing treatment with at least 2 courses of intravesical therapy (one of which had to contain BCG) or BCG followed by maintenance BCG. The primary objective was to determine the safety of this combination. Secondary end points included response to treatment at 19 weeks (end of treatment) and 3 months post treatment. MATERIALS AND METHODS: A total of 9 patients with recurrent/persistent high-grade non-muscle invasive bladder cancer after at least two courses of intravesical therapy or one course of BCG treatment followed by one course of maintenance BCG were enrolled in the study. Six doses of pembrolizumab were given every 3 weeks over 16 weeks given concurrently with 6 weekly doses of BCG beginning at week 7. Patient safety was evaluated during and for 30 days following pembrolizumab treatment. Preliminary combination efficacy was determined at 19 weeks using cystoscopy. Bladder biopsy was performed in patients with suspicious lesions. RESULTS: The combination of BCG and pembrolizumab was well tolerated at both 100mg and 200mg fixed doses. Fatigue and cystitis-type symptoms (burning, spasm, urgency, sensitivity, and frequency) were the most common adverse events and all cases were either grade 1 or 2. Two patients died during the trial period. One patient died due to progression of low grade upper urinary tract transitional cell carcinoma. The other patient died after cystectomy (for progressive disease) due to causes unrelated to the trial treatment. Of the 9 patients treated, 6 (78%) had no evidence of disease in the bladder and 1 had a mixed response (progression in the upper urinary tract only) at 19 weeks (end of treatment) while 5 (56%) remained disease-free at the 3 month follow up. CONCLUSIONS: The combination of BCG and pembrolizumab was well tolerated with subjects exhibiting the expected adverse effects associated with the use of both medications. Intravesical BCG and pembrolizumab may have clinical activity in non-muscle invasive bladder cancer recurring after repeated intravesical therapy. .A phase III trial is now open and enrolling in the United States and other countries (NCT03711032). Citation Format: Shaheen Alanee, Ahmed El Zawahry, Sherjeel Sana, Kevin McVary, Kathy Robinson, Krishna A. Rao. Phase I trial of intravesical Bacillus Calmette-Guerin combined with intravenous Pembrolizumab in high grade nonmuscle invasive bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT047.
Characterization of opioid consumption and disposal patterns after total knee arthroplasty.

Aims The aim of this study was to determine the general postoperative opioid consumption and rate of appropriate disposal of excess opioid prescriptions in patients undergoing primary unilateral to...
VULCAN: A “hammer” for high-temperature materials research

Understanding changes in chemistry, microstructure, and physical properties during synthesis, processing, testing, and even service is vital for materials design and performance. Compared to traditional postmortem material characterization tools, in situ crystallographic characterization can provide considerable data and information on evolution of chemistry, dislocations, twinning, texture, and strains when a material is under external stimuli. Neutrons especially are able to probe material bulk properties and behaviors in extreme environments, thanks to their deep penetrating power and unique sensitivity to differentiate elements from lightweight to transition-metal atoms. In this article, we introduce and describe a diffractometer named VULCAN, which is located at Oak Ridge National Laboratory. This represents a powerful tool to understand materials properties and behaviors under complex environments, in particular, at high temperatures.
Sustainable municipal solid waste disposal supply chain analysis under price-sensitive demand: A game theory approach.

The impacts of price and sustainability on municipal waste disposal demand have largely been ignored by waste management researchers. This paper considers a waste disposal supply chain that include...
The Crisis of the Black Worker, the U.S. Labor Movement, and Democracy for All:

This paper contextualizes the socioeconomic condition of the African-American working class in the American Labor Movement. As the union movement continues its steady decline, African-American soci...
Joint Manufacturing and Onsite Microgrid System Control using Markov Decision Process and Neural Network Integrated Reinforcement Learning

Abstract Onsite microgrid generation systems with renewable sources are considered a promising complementary energy supply system for manufacturing plant, especially when outage occurs during which the energy supplied from the grid is not available. Compared to the widely recognized benefits in terms of the resilience improvement when it is used as a backup energy system, the operation along with the electricity grid to support the manufacturing operations in non-emergent mode has been less investigated. In this paper, we propose a joint dynamic decision-making model for the optimal control for both manufacturing system and onsite generation system. Markov Decision Process (MDP) is used to formulate the decision-making model. A neural network integrated reinforcement learning algorithm is proposed to approximately estimate the value function given policy of MDP. A case study based on a manufacturing system as well as a typical onsite microgrid generation system is conducted to validate the proposed MDP model as well as the solution strategy.
Conservation of community functional structure across changes in composition in consumer-resource models.

Abstract High-throughput sequencing techniques such as metagenomic and metatranscriptomic technologies allow cataloguing of functional characteristics of microbial community members as well as their phylogenetic identity. Such studies have found that a community’s makeup in terms of ecologically relevant functional traits or guilds can be conserved more strictly across varying settings than its composition is in terms of taxa. I use a standard ecological resource-consumer model to examine the dynamics of traits relevant to resource consumption, and analyze determinants of functional structure. This model demonstrates that interaction with essential resources can regulate the community-wide abundances of ecologically relevant traits, keeping them at consistent levels despite large changes in the abundances of the species housing those traits in response to changes in the environment, and across variation between communities in species composition. Functional structure is shown to be able to track differences in environmental conditions faithfully across differences in species composition. Mathematical conditions on consumers’ vital rates and functional responses necessary and sufficient to produce conservation of functional community structure across differences in species composition in these models are presented. These conditions imply a nongeneric relation between biochemical rates, and avenues for further research are discussed.
Evaluating the effects of nitrogen and sulfur deposition and ozone on tree growth and mortality in California using a spatially comprehensive forest inventory

Abstract Although nitrogen deposition and tropospheric ozone have impacted California forests for decades, broad scale studies of these impacts on forest growth and mortality are lacking. Because of the summer-dry climate over most of the state, forest responses to air pollution are expected to differ from more mesic climates. In this study, data from US Forest Service Forest Inventory and Analysis (FIA) permanent (remeasured) plots were combined with modelled atmospheric N and S deposition and an ozone exposure index to evaluate tree growth and mortality responses in California. Seven of 18 species exhibited significantly greater carbon increment (CI) in tree boles as N deposition increased, though the magnitude of the effect was quite small in most California forests. However, increases in CI were substantial in the coastal ecosections of central and northern California where precipitation and fog exposure are greatest. Redwood (Sequoia sempervirens (D. Don) Endl.) trees exhibited the strongest CI response to N deposition. Our model results imply a mean CI increase of 4.2 kg ha−1 yr−1 of C per kg ha−1 yr−1 of N deposition statewide versus 13.6 in the Central and Northern California Coast ecosections, where > 50% of the trees are redwood or tanoak (Lithocarpus densiflorus (Hook. & Arn.) Rehd.). Increased carbon sequestration rates in response to N deposition in these California coastal regions were similar to increases reported for Europe and global estimates. Nitrogen and S deposition significantly increased the odds of top damage and trees with crown damage exhibited higher mortality, although the effect was small. Elevated ozone exposure was associated with significantly larger rates of overall tree growth. However, for ozone-sensitive ponderosa pine at moderate ozone levels (ozone index values of ca. 20–30 ppb) and moderately-elevated N deposition (15–25 kg ha−1 hr−1), CI begins to decline, before increasing at higher pollution levels, presumably because of the fertilizing effect of N deposition; although data are limited for these more polluted conditions. Sulfur deposition in California forests was low, ranging from 0.3 to 3.1 kg ha−1 yr−1, but was associated with positive growth response in seven coniferous species. The combined effect of N and S deposition and ozone exposure statewide is a net increase in bole CI. However, aridity reduces the stimulatory growth effect of N deposition, and alters the threshold, capacity and sometimes the direction (e.g., S deposition) of the CI response to deposition, factors that need to be considered in global change models.
Mobile Assisted Chinese Learning as a Foreign Language: An Overview of Publications between 2007 and 2019

This paper presents a critical overview of studies on mobile assisted language learning (MALL) in teaching Chinese as a foreign language (CFL) during the period 2007–2019. In the review, keyword and reference searches were conducted to identify and select empirical studies during the review period. Thematic and frequency analyses were employed on the data. This identified methodological trends and research outcomes in the reviewed studies. As shown in the results, most of the reviewed studies used qualitative methods to examine the effect of mobile CFL learning on formal learning in higher education settings. These studies document the positive impact that mobile technology has on CFL learning. Their attention is primarily on the use of mobile learning in Chinese vocabulary acquisition, language skill development and mobile seamless learning. Suggestions are provided for further research to support continuous mobile assisted CFL teaching and learning.
Creating a browser-based virtual computer lab for classroom instruction

With laptops and tablets becoming more powerful and more ubiqui- tous in the classroom, traditional computer labs with rows of expensive desktop computers are slowly beginning to lose their relevance. An alternative approach for teaching Python is to use a browser-based virtual computer lab, with a notebook interface. The advantages of physical computer labs, such as face-to- face interaction, and the challenge of replicating them in a virtual environment are discussed. The need for collaborative features like terminal/notebook shar- ing and chatting is emphasized. A virtual computer lab is implemented using the GraphTerm server, with several experimental features including a virtual dashboard for monitoring tasks and progressively fillable notebooks for ensuring step-by-step completion of a sequence of tasks.
The Constitutional Emergency Powers of Federal Courts

Discussions about whether governments in constitutional democracies possess emergency powers during exigent times focus exclusively on the political branches. But none of these discussions envision the judicial branch as an affirmative agent in designing government policies to deal with periods of crisis. When the judicial role during emergencies is considered, the courts are envisioned only as possible checking agents against potentially abusive uses of emergency powers that the political branches might invoke. The paradigmatic context for the judicial role is pictured as a response to a new government measure, which the emergency is said to necessitate, that impinges more than permitted in normal times on individual liberties (detention, surveillance, restrictions on freedom of movement, assembly, or worship). The courts are conceived as ex post checks on whether the political branches of the state have compelling enough interests to justify these extraordinary actions. As part of that inquiry, courts explore how much they should defer to the political branches’ claims of necessity for these emergency measures. In the American context, courts also determine whether the President can act on his own and whether Congress has endorsed the action at issue. But courts during emergencies remain ex post veto institutions over emergency policies the political branches adopt. In the current pandemic, however, we are witnessing the federal courts assuming the mantle of a different role, particularly around issues of voting and elections. The difference is subtle, but profound. In the domain of elections, federal courts are themselves becoming affirmative institutions of the state taking the initiative to create new policies that the pandemic crisis is thought to warrant. The courts are not engaging in an ex post checking function against new emergency measures the government has taken; instead, the courts are responding to the failure of governments to adopt new policies tailored to the extreme new circumstances of the pandemic. Courts in this arena are not negatively checking and vetoing government action, they are affirmatively requiring government to adopt certain policies. Courts are not issuing injunctions blocking coercive new emergency measures governments have adopted; instead, courts are mandating that governments exercise extraordinary powers that would not be required in normal times. In a fragmented way thus far, primarily across district courts scattered around the country, the federal courts are moving bit by bit toward building a new election code for pandemic-time elections. While we are not accustomed to viewing the Constitution as granting federal courts emergency powers, that is an apt overarching framework for synthesizing the various election-related decisions rapidly emerging -- with several new decisions weekly -- from the federal courts. This essay describes this framework and situates within it the actions of federal courts thus far.
Curriculum-Based Animal-Assisted Therapy in an Acute Outpatient Mental Health Setting

Rigor in animal-assisted therapy (AAT) research is growing, but AAT as an “evidence-based practice” is not yet clearly established. One methodological weakness in the current literature is the lack of a structured, manualized approach to AAT. The Mutt-i-grees Curriculum, founded on the principles of human-canine interaction, aims to enhance children’s resilience, social skills, and self-awareness. This study examined the utility of this manualized curriculum as a supplemental component of a pediatric intensive behavioral health treatment program for children with a range of psychiatric conditions. Patients, psychiatrists, and caregivers completed assessments of children’s (N = 22) symptoms before and after treatment, with analyses investigating the difference in symptoms for patients who received animal-assisted therapy (AAT) as a part of their treatment and patients who did not. Patients also completed mood scores before and after group sessions with and without a therapy dog present. Results indicate that AAT may be an effective adjunct to standard care in a pediatric setting. The success of AAT alongside behavioral treatment led to reduction in symptoms and improvement in mood for patients. These findings support previous research indicating the efficacy of using a manualized curriculum and the advantages of using dogs as part of treatment to supplement behavioral health services.
Transition preparation activities and expectations for the transition to adulthood among parents of autistic youth

Abstract Background Parents of autistic youth are highly involved in the transition preparation process, yet the role and influence of parental factors and perceptions is underexplored. In the current study, we aimed to expand understanding of transition preparation and the role and influence of parental factors for autistic youth including perceptions of the likelihood (i.e., parent expectations), importance, and parental influence over postsecondary outcomes as well as parental self-efficacy, parent stress, and parent concerns for the future. Method We surveyed 269 parents of autistic youth (ages 14–21, 78.2 % male) who did not have co-occurring intellectual disability. We used linear regression analyses to examine youth and parent predictors of the frequency of transition preparation activities, parents’ overall sense of preparation, and parental worry about the future. We also qualitatively analyzed open-ended responses about parent concerns. Results The most frequently endorsed transition preparation activities were discussions about the future and chores. Parental factors were associated with greater frequency of transition preparation activities, greater overall sense of preparation for the transition, and less overall worry. Key areas of parent concern were related to youth independence, social life, employment/finances, autism features, safety, happiness, and health. Conclusions The results of this study have implications for education and interventions focused on supporting autistic youth and their parents for the transition to adulthood. There is a need for transition-related interventions that focus on parents and on particular instruction for raising expectations, enhancing parent self-efficacy, and increasing parental sense of control over outcomes.
Prediction of severity and subtype of fibrosing disease using model informed by inflammation and extracellular matrix gene index

Fibrosis is a chronic disease with heterogeneous clinical presentation, rate of progression, and occurrence of comorbidities. Systemic sclerosis (scleroderma, SSc) is a rare rheumatic autoimmune disease that encompasses several aspects of fibrosis, including highly variable fibrotic manifestation and rate of progression. The development of effective treatments is limited by these variabilities. The fibrotic response is characterized by both chronic inflammation and extracellular remodeling. Therefore, there is a need for improved understanding of which inflammation-related genes contribute to the ongoing turnover of extracellular matrix that accompanies disease. We have developed a multi-tiered method using Naive Bayes modeling that is capable of predicting level of disease and clinical assessment of patients based on expression of a curated 60-gene panel that profiles inflammation and extracellular matrix production in the fibrotic disease state. Our novel modeling design, incorporating global and parametric-based methods, was highly accurate in distinguishing between severity groups, highlighting the importance of these genes in disease. We refined this gene set to a 12-gene index that can accurately identify SSc patient disease state subsets and informs knowledge of the central regulatory pathways in disease progression.
Mg II & C IV Kinematics vs. Stellar Kinematics in Galaxies

Comparisons of the kinematics of Mg II absorbing gas and the stellar rotation curves in 0.5 < z < 1.0 spiral galaxies suggests that, at least in some cases, the extended gaseous envelopes may be dynamically coupled to the stellar matter. A strong correlation exists between the overall kinematic spread of Mg II absorbing gas and C IV absorption strength, and therefore kinematics of the higher-ionization gas. Taken together, the data may suggest a "halo/disk connection" between z~1 galaxies and their extended gaseous envelopes. Though the number of galaxies in our sample are few, there are no clear examples that suggest the gas is accreting/infalling isotropically about the galaxies from the intergalactic medium.
Understanding the Lived Experiences: A Post-structuralist Interpretation

From a post-structuralist standpoint, this chapter interprets the meaning of the narratives embedded in the lived experiences of these L2 learners and users after describing and uncovering the social variables that affect the participating Chinese graduate students’ learning process and learning outcomes described in the previous chapters. Section one offers a composite portrait of the participating Chinese students growing from L2 learners to L2 users, then moves to interpret the departmental cultures and the challenges Blue Fountain University faces and analyzes the university services offered to international students. This chapter also discusses the perceptions of Chinese students on English language teaching in China. Their authentic voice publicizes the aspects that they thought were ineffective and/or ought to be reformed. The last two sections of this chapter explore the participating Chinese international students’ ecological second language acquisition and language socialization, as well as identity negotiations along the way of pursuing a graduate degree in the United States.
A role for aldehyde dehydrogenase (ALDH) 2 in angiotensin II-mediated decrease in angiogenesis of coronary endothelial cells.

Abstract Diabetes-induced coronary endothelial cell (CEC) dysfunction contributes to diabetic heart diseases. Angiotensin II (Ang II), a vasoactive hormone, is upregulated in diabetes, and is reported to increase oxidative stress in CECs. 4-hydroxy-2-nonenal (4HNE), a key lipid peroxidation product, causes cellular dysfunction by forming adducts with proteins. By detoxifying 4HNE, aldehyde dehydrogenase (ALDH) 2 reduces 4HNE mediated proteotoxicity and confers cytoprotection. Thus, we hypothesize that ALDH2 improves Ang II-mediated defective CEC angiogenesis by decreasing 4HNE-mediated cytotoxicity. To test our hypothesis, we treated the cultured mouse CECs (MCECs) with Ang II (0.1, 1 and 10 μM) for 2, 4 and 6 h. Next, we treated MCECs with Alda-1 (10 μM), an ALDH2 activator or disulfiram (2.5 μM)/ALDH2 siRNA (1.25 nM), the ALDH2 inhibitors, or blockers of angiotensin II type-1 and 2 receptors i.e. Losartan and PD0123319 respectively before challenging MCECs with 10 μM Ang II. We found that 10 μM Ang II decreased tube formation in MCECs with in vitro angiogenesis assay (P
Toll-like Receptor 9 Agonists as Adjuvants for Nanoparticle-Based Nicotine Vaccine

Nicotine vaccine was considered a promising therapy against smoking addiction. The level of immune response that a nicotine vaccine can induce is pivotal to its efficacy. In this study, Toll-like receptor 9 agonists, namely, CpG ODN 1555 and CpG ODN 1826, were incorporated into a nanoparticle-based nicotine vaccine (NanoNicVac) to enhance its immunogenicity. The results showed that NanoNicVac containing either CpG ODN 1555 or CpG ODN 1826 could be rapidly internalized by dendritic cells. In mice trials, it was found that NanoNicVac with CpG ODN 1555 and CpG ODN 1826 induced 3.3- and 3.2-fold higher anti-nicotine antibody titer than that by the native NanoNicVac after two injections, respectively. Instead of enhancing the immunogenicity of the vaccine, however, mixtures of the two CpG ODNs were observed to exert an immune-suppressing effect on NanoNicVac. Finally, the histopathological examination on major organs of the mice immunized with the NanoNicVacs proved that NanoNicVac with either CpG ODN 1555 or CpG ODN 1826 as adjuvants did not cause detectable toxicity to the mice.
A Review of Multilevel Modeling using R (2nd edition)

Multilevel modeling is an excellent tool among researchers with nested data. As statistical software improves, the ease of conducting these models has become more accessible. In particular, the sec...
Investigating Transfer Learning of Smartphone-Sensed Stress in University Populations

Stress has become a significant public health problem worldwide. Prior work has proposed methods for inferring stress from smartphone sensed data. However, in many cases subjects are reluctant to participate and annotate data in mobile sensing studies. In this work, we explored a transfer learning approach to mitigate this issue. We investigated whether a smartphone-based stress model learned from Dartmouth college students could be transferred and used to accurately predict the stress of students at Worcester Polytechnic Institute (WPI). While these two colleges have similar size, differences exist including the length of their academic terms. To validate our approach, B.stress, a smartphone app was developed, which used the transferred model to infer the stress levels of WPI subjects. To validate this approach, the students were prompted to agree or disagree with the transferred model’s inference, which was compared to a stress model trained from scratch for WPI students. Our results were encouraging, demonstrating that transfer learning can quickly and autonomously achieve a stress inference accuracy of 78.9% for all stress levels. In comparison, a model learned from users directly from scratch is personalizable and achieves an accuracy of 87% as the classifier learns a specific model for each student. However, training the model from scratch without transferring learning requires weeks of manual labeling beforehand. These results are encouraging and suggest that a hybrid approach might be an optimal middle ground. A transfer learning could be used to generate an initial stress sensing model, which is then fine-tuned using feedback from the user.
Past, present, and future barriers to digital transformation in manufacturing: A review

Abstract Research in digital transformation (DT) is burgeoning. Meanwhile, the COVID-19 pandemic has not only influenced both day-to-day functions of firms dramatically, but also their efforts to become more digitally mature. In this review paper, we discuss the barriers to DT before, during, and what may well continue after the COVID-19 pandemic and offer a new strategy discipline—Strategic Doing—that may be useful to manufacturing firms in achieving successful DT. We discuss the divergent definitions and drivers of DT diving deep into the barriers for manufacturing firms to mature digitally. We briefly describe digital readiness and current efforts of DT in manufacturing while describing the impact of COVID-19 on DT initiatives. We conclude by describing Strategic Doing and suggesting new paths for research in this area.
Sulvanites: The Promise at the Nanoscale

The class of ternary copper chalcogenides Cu3MX4 (M = V, Nb, Ta; X = S, Se, Te), also known as the sulvanite family, has attracted attention in the past decade as featuring promising materials for optoelectronic devices, including solar photovoltaics. Experimental and theoretical studies of these semiconductors have provided much insight into their properties, both in bulk and at the nanoscale. The recent realization of sulvanites at the nanoscale opens new avenues for the compounds toward printable electronics. This review is aimed at the consideration of synthesis methods, relevant properties and the recent developments of the most important sulvanites.
How to Compute the Largest Number of Rationalizable Choices

When checking revealed preference conditions on experimental or field data, a commonly reported measure of choice consistency is a function of the largest number of rationalizable choices. While there are known methods to compute the largest number of rationalizable choices for the standard consumer problem with linear budgets, computation of this object is unknown for general budget sets. In this paper, I provide a mixed-integer linear program that facilitates computation of the largest number of rationalizable choices for general budget sets.
ACT for Life: Why Psychiatrists Pound the Pavement to Provide Care

To better understand the experience of psychiatrists working on assertive community treatment (ACT) teams and the factors that may draw them to this work, the authors created a survey and distributed it through e-mail groups of the American Association of Community Psychiatrists, the Columbia University Public Psychiatry Fellowship Alumni, and the New York State Center for Practice Innovations ACT Institute. A second survey, with questions primarily regarding safety concerns for ACT providers, was distributed to respondents of the first survey. Responses suggested that ACT leaders should foster teamwork, fieldwork, creativity, flexibility, safety, and leadership opportunities on ACT teams if they wish to engage psychiatrists in this work.
The GSDMB rs7216389 SNP is associated with chronic rhinosinusitis in a multi-institutional cohort

Background Chronic rhinosinusitis (CRS) is a multifactorial disease with a high co-occurrence with asthma. In this multicohort study, we tested whether single nucleotide polymorphisms (SNPs) associated with childhood asthma and rhinovirus (RV)-associated disease are related to an increased susceptibility to adult CRS in a multicohort retrospective case-control study. Methods Participants at two tertiary academic rhinology centers, University of Arizona (UofA) and University of Pennsylvania (UPenn) were recruited. Cases were defined as those with physician diagnosed CRS (UofA, n = 149; UPenn, n = 250), and healthy controls were those without CRS (UofA, n = 66; UPenn, n = 275). Genomic DNA was screened for the GSDMB rs7216389 SNP and CDHR3 rs6967330 SNP. Gene dosage, or the number of combined risk alleles in a single subject was calculated. Meta-analysis of the association between GSDMB or CDHR3 genotypes and CRS was performed and additive gene dosage effect for each population calculated using p for trend. Results A meta-analysis revealed a combined increased risk for CRS in subjects with the GSDMB rs7216389 SNP (odds ratio [OR] 1.40; 95% confidence interval [CI], 1.16-1.76; p = 0.004). Both the UofA (OR 1.73; 95% CI, 1.23-2.43; p = 0.002) and UPenn (OR 1.27; 95% CI, 1.02-1.58; p = 0.035) populations showed a significant positive association between the number of combined risk alleles of GSDMB rs7216389 SNP and CDHR3 rs6967330 SNP and risk for CRS. Conclusion Carriers of the GSDMB rs7216389 SNP and CDHR3 rs6967330 SNP are at increased susceptibility for CRS. These data suggest that therapeutic approaches to target aberrant responses to RV infection may play a role in the treatment of unified airway disease.
Integration of an enhanced recovery after surgery program for patients undergoing pituitary surgery

Abstract Evidence-based enhanced recovery after surgery (ERAS) programs aim to improve patient outcomes and shorten hospital stays. The objective of this study is to describe the development, implementation, and evolution of an ERAS protocol to optimize the perioperative management for patients undergoing endoscopic skull base surgery for pituitary tumors. A systematic review of the literature was performed, best practices were discussed with stakeholders, and institutional guidelines were established and implemented. Key performance indicators (KPI) were measured and patient-reported outcome surveys were collected. The ERAS protocol was introduced successfully at our institution. We describe the process of initiation of the program and the perioperative management of our patients. We demonstrated the feasibility of integration of ERAS protocols for pituitary tumors with multidisciplinary engagement, with a particular emphasis on the use of data informatics and metrics to monitor outcomes. We expect that this approach will translate to improved quality of care for these often-complex patients.
The Tadros Theory of Change with Incarcerated Populations

An estimated 2.3 million individuals were incarcerated in the U.S. in 2018. This paper displays how The Tadros Theory of Change can be utilized to work with incarcerated individuals and their famil...
Determinants of pyelonephritis onset in patients with obstructive urolithiasis

Background:Acute obstructive pyelonephritis due to urolithiasis represents a medico-surgical emergency that can lead to life-threatening complications. There are still no established factors that r...
Multi-cyclone analysis and machine learning model implications of cyclone effects on forests

Abstract Past studies of cyclones (hurricanes, typhoons, tropical cyclones) disturbance showed that meteorological, topographical, and biological factors affect the patterns of forest disturbance intensity but left open the extent to which these findings were representative across different global cyclone regions. Using remote sensing data and machine learning models, we examined how these factors change over spatial scales and assessed their consistency across four major cyclones: Katrina (August 2005), Rita (September 2005), Yasi (February 2011), and Maria (September 2017). Our results revealed that the factors which best explained forest disturbance intensity pattern varied across these regions. Wind speed and precipitation were the dominant factors contributing to the variation in impacts of Katrina; terrain features, especially elevation, explained most of the variation in disturbance intensity of Rita; pre-disturbance vegetation condition was significant predictors of effects of Yasi; these factors played equal roles in explaining the disturbance intensity variation of Maria. A 40 m/s (144 km/h) wind speed threshold was proposed to split low- and high-level forest disturbance intensity. Other than wind speed, few generalizations can be made on features across multiple regions. We built several generalized hurricane impact models, which worked well with the test data from cyclones used for model development (R2 = 0.89). However, these models did not have good predictions on other cyclones, such as Michael (October 2018) and Laura (August 2020). This study showed that each cyclone interacted with the landscape in a unique way and the challenges remained in building a generalized cyclone impact model.
Quantitative flood risk evaluation to improve drivers’ route choice decisions during disruptive precipitation

Abstract This article describes a data-driven approach to flood risk exposure evaluation and route delineation during heavy rainfall events. We cross-referenced diverse geospatial and drainage infrastructure datasets with the street network of Hoboken to uncover the factors that increase flood risk. Elevation, slope, precipitation level, imperviousness, and distance to the drainage system’s outlets were the most significant predictors to link flooding. We used the link flood risk patterns found in the data to train a reinforcement learning model that generates routes that avoid flood-prone areas. We benchmarked the route assistance model with shortest path and most reliable path algorithms, demonstrating our model has balanced path length and path reliability. We provided the flood risk model outputs at the link-level, which city authorities can use to plan road closures ahead of heavy precipitation events. The route assistance model can be used by drivers to better navigate flood-prone environments by detouring around riskier areas or canceling trips altogether.
Abstract 19: Using the Heckman Selection Model to Assess Selection Bias in Ischemic Stroke Patients with Documented NIHSS

Objective: Complete documentation in large scale datasets such as administrative data or disease registries is often difficult. Given that the subset of patients with complete data documentation are most likely not a random sample of patients, selection bias threatens the validity of results if a complete case analysis is used. To demonstrate, we will assess the presence and magnitude of selection bias in ischemic stroke patients with documented National Institute of Health Stroke Scale (NIHSS) [[Unable to Display Character: –]] which is often incomplete [[Unable to Display Character: –]] using the Heckman Selection Model. Methods: Patient level variables including demographics, comorbidities, clinical EMS and admission variables, and medical history/comorbidities were obtained from 10,717 ischemic stroke patients aged 65 and older in the Michigan Stroke Registry in 2009-2012. The Heckman Selection Model assesses the presence and magnitude of selection bias by estimating a correlation coefficient between error components of a linear regression model predicting patient NIHSS score [[Unable to Display Character: –]] the outcome model [[Unable to Display Character: –]] and a binary probit model predicting NIHSS documentation [[Unable to Display Character: –]] the selection model [[Unable to Display Character: –]] conditional on patient and hospital predictors. The outcome model predicting NIHSS score was specified using a backward selection process with stepwise deletion of non-significant predictors. The selection model included all variables in the outcome model, plus additional significant predictors of NIHHS documentation. Quasi-maximum likelihood estimation was used to produce robust standard errors. All analyses were done using PROC QLIM procedure in SAS. Results: 7,956 cases (74.2%) of cases had NIHSS documented. Significant predictors in the outcome and selection models are shown in the Table. The Heckman Selection Model found a statistically significant but modest correlation coefficient of ρ =0.1089 (SE=0.0119, p<0.0001). The positive correlation indicates that NIHSS was more likely to be documented in patients with higher NIHSS scores, i.e., more severe strokes. Conclusions: We found statistically significant albeit weak selection bias in the documentation of NIHSS in stroke patients. The Heckman Selection Model is a novel method that can be used to assess the presence and magnitude of selection bias when missing data is common. ![][1] [1]: /embed/graphic-1.gif
Alcoholic liver injury in baboons: transformation of lipocytes to transitional cells.

Abstract Ultrastructure of the lipocytes (the main perisinusoidal cells) and their alterations in the progression of hepatic fibrosis were studied in liver biopsy specimens of baboons pair-fed with diets containing alcohol, or isocaloric carbohydrate, for up to 112 mo. In control baboons, 97% of the cells in the Disse space were lipocytes characterized by a volume density of lipid droplets occupying > 20% of the cell volume and by the presence of microfilament bundles with associated dense bodies and pinocytic vesicles. Intercellular junctions of the adherens type were present between lipocytes and hepatocytes. After alcohol consumption, the number of lipocytes (as assessed by light microscopy) was significantly decreased in fatty livers and at various stages of hepatic fibrosis; this was associated with a decreased hepatic vitamin A content. In baboons fed alcohol, only 48% of cells were lipocytes, whereas 52% were transitional cells defined by a volume of lipid droplets
Ischemic preconditioning in isolated perfused mouse heart: reduction in infarct size without improvement of post-ischemic ventricular function.

Genetically engineered mice provide an excellent tool to study the role of a particular gene in biological systems and will be increasingly used as models to understand the signal transduction mechanisms involved in ischemic preconditioning (IP). However, the phenomenon of IP has not been well characterized in this species. We therefore attempted to examine whether IP could protect isolated mouse heart against global ischemia/reperfusion (GI/R) injury. Thirty adult mice hearts were perfused at constant pressure of 55 mmHg in Langendorff mode. Following 20 min equilibration, the hearts were randomized into three groups (n = 10/each): (1) Control Group; (2) IP2.5 Group: IP with two cycles of 2.5 min GI + 2.5 min R; (3) IP5 Group: IP with 5 min GI + 5 min R. All hearts were then subjected to 20 min of GI and 30 min R (37°C). Ventricular developed force was measured by a force transducer attached to the apex. Leakage of CK and LDH was measured in coronary efflux. Infarct size was determined by tetrazolium staining. Following sustained GI/R, infarct size was significantly reduced in IP2.5 (13.8 ± 2.3%), but not in IP5 (20.1 ± 4.0%), when compared with non-preconditioned control (23.6 ± 3.8%) hearts. CK & LDH release was also reduced in both IP2.5 and IP5 groups. No significant improvement in post-ischemic ventricular contractile function was observed in either IP groups. We conclude that IP with repetitive cycles of brief GI/R is able to reduce myocardial infarct size and intracellular enzyme leakage caused by a sustained GI/R in the isolated perfused mouse heart. This anti-necrosis cardioprotection induced by IP was not associated with the amelioration of post-ischemic ventricular dysfunction. (Mol Cell Biochem 186: 69-77, 1998)
Axial-Stereo 3D Optical Metrology of Internally Machined Parts Using High-Quality Imaging from a Scanning Laser Endoscope

As the rapid progress in the development of optoelectronic components and computational power, 3D optical metrology becomes more and more popular in manufacturing and quality control due to its flexibility and high speed. However, most of the optical metrology methods are limited to external surface. This paper proposed a new approach to measure tiny internal 3D surfaces with a scanning fiber endoscope and axial-stereo vision algorithm. A dense, accurate point cloud of internally machined threads was generated to compare with its corresponding X-ray 3D data as ground truth, and the quantification was analyzed by iterative closest points (ICP) algorithm.
Crime or punishment?: Enforcement of the NCAA football cartel

Abstract This paper presents theoretical and empirical evidence on the methods that the National Collegiate Athletic Association (NCAA) and its member schools use to detect violations of its cartel agreement. Because it is difficult to find direct evidence of cheating we suggest that the volatility of a school's winning percentage is used as a proxy by the NCAA rules has a detect violations. Empirical evidence also suggests that the enforcement of the NCAA rules has a redistributive effect that benefits consistent winners at the expense of up-and-coming schools.
Penalized classification using Fisher's linear discriminant

We consider the supervised classification setting, in which the data consist of p features measured on n observations, each of which belongs to one of K classes. Linear discriminant analysis (LDA) is a classical method for this problem. However, in the high-dimensional setting where p ≫ n, LDA is not appropriate for two reasons. First, the standard estimate for the within-class covariance matrix is singular, and so the usual discriminant rule cannot be applied. Second, when p is large, it is difficult to interpret the classification rule obtained from LDA, since it involves all p features. We propose penalized LDA, a general approach for penalizing the discriminant vectors in Fisher's discriminant problem in a way that leads to greater interpretability. The discriminant problem is not convex, so we use a minorization-maximization approach in order to efficiently optimize it when convex penalties are applied to the discriminant vectors. In particular, we consider the use of L(1) and fused lasso penalties. Our proposal is equivalent to recasting Fisher's discriminant problem as a biconvex problem. We evaluate the performances of the resulting methods on a simulation study, and on three gene expression data sets. We also survey past methods for extending LDA to the high-dimensional setting, and explore their relationships with our proposal.
Prediction of fetal macrosomia using sonographically measured abdominal subcutaneous tissue thickness

Purpose We assessed the usefulness of sonographic measurement of abdominal subcutaneous tissue thickness in predicting fetal macrosomia (weight > 4,000 g). Methods Abdominal subcutaneous tissue thickness was measured sonographically in 133 term fetuses. All studied fetuses were delivered within 72 hours after the measurements were taken. Results One hundred thirteen fetuses were normal size, and 20 were macrosomic. The fetal abdominal subcutaneous tissue thickness ranged between 3 and 18 mm in all fetuses, with a mean measurement of 8.4 ± 2.7 mm (standard deviation). The mean tissue thickness differed significantly between normal and macrosomic fetuses (7.0 mm versus 12.4 mm, respectively; p < 0.0001). There was a significant positive correlation between the abdominal subcutaneous tissue thickness and the birth weight (r = 0.67, p < 0.0001). The negative predictive value for a range of cut-off points between 8 and 13 mm varied between 84.3% and 100% (for prevalence rates of macrosomia of 5–25%). However, the positive predictive value was less than 50% for cut-off values below 11 mm. Conclusions Sonographic measurement of the subcutaneous tissue thickness of the fetal abdomen is useful for ruling out macrosomia. © 1997 John Wiley & Sons, Inc. J Clin Ultrasound25: 378–382, 1997.
Underinsurance in children with special health care needs: The impact of definition on findings

To identify differences in groups of children with special healthcare needs (CSHCN) identified as underinsured by two alternate definitions and discuss implications for policy decisions based on using one definition over another. Secondary data from the National Survey of CSHCN 2005/2006 were analyzed. Only CSHCN who were continuously-insured for 12 months were included in analyses. We identified groups of underinsured CSHCN using two general definitions (“economic” and “attitudinal”) and three mutually-exclusive groups (identified by both definitions, identified by attitudinal but not economic, and identified by economic but not attitudinal). Key variables included demographics and condition characteristics. Different underinsurance rates were identified [attitudinal = 30.9 % (n = 11,470); economic = 22.7 % (n = 8,447)] with fair agreement by kappa score (κ = 0.3194; Z = 65.91; p > 0.0001). Differences across mutually-exclusive groups included family income ≥400 % FPL (attitudinal only = 34.2 %, economic only = 16.3 %, both = 18.4 %; p < 0.001) and high severity (attitudinal only = 42.5 %, economic only = 68.5 %, both = 69.9 %; p < 0.001). CSHCN who needed equipment/supplies/home health (OR = 1.31, p < 0.001) had increased odds of being identified as underinsured by the economic, but not attitudinal definition. CSHCN with private insurance had increased odds of being identified by attitudinal only or both definitions, but not by economic only (AO: OR = 1.41, p < 0.001; BOTH: OR = 2.36, p < 0.001). Despite overlap between the two definitions, choosing either one excludes some CSHCN, potentially underestimating the extent of underinsurance and masking important findings related to specific conditions characteristics. A definition that comprehensively identifies and describes underinsurance is vital to translating health insurance coverage expansion into benefit packages that meet complex health and service needs.