Cadaveric Assessment of the Butterfly Graft in Rhinoplasty.

INTRODUCTION: The rhinoplasty butterfly graft is used to improve the internal nasal valve (INV), but post-operative visibility remains a concern. Intraoperative techniques have developed to thin the graft with unknown effect on functionality. OBJECTIVES: Improve understanding of how to modify the aesthetics of the butterfly graft without impacting patient outcomes. Determine how graft contouring affects its biomechanical properties. METHODS: Cadaveric cartilage grafts were used to examine the biomechanics in its native state and with progressive thinning. The force needed to stabilize the INV in an unaltered state and the resistance force provided by native (original), partially thinned, and fully thinned cartilage grafts were recorded. RESULTS: The mean thickness of grafts in their natural state was 1.64 mm, median 1.50 mm (SD 0.64 mm). The fully-thinned mean was 0.84 mm, median 0.8 mm (SD 0.18 mm). The mean force (N) of the native graft was 0.74 N and 0.60 N for fully thin (p = 0.016, 95%). The mean force (N) needed to stabilize the INV was 0.15 N (right) and 0.19 N (left). CONCLUSION: Butterfly grafts can be thinned by approximately 50% of their original thickness and retain the strength to stabilize the INV. LEVEL OF EVIDENCE: NA Laryngoscope, 134:1638-1641, 2024.

Tobacco Cessation Following Laryngeal Cancer Diagnosis Predicts Response to Treatment and Laryngectomy-Free Survival.

OBJECTIVE: To determine the effect of tobacco cessation following laryngeal cancer diagnosis on response to first-line therapy, laryngectomy-free survival, and overall survival in patients who were current smokers at the time of diagnosis. STUDY DESIGN: Retrospective, case-control study. SETTING: OU Stephenson Cancer Center, National Cancer Institute-Designated Cancer Center. METHODS: We included 140 patients diagnosed with laryngeal squamous cell carcinoma, who were current smokers at the time of diagnosis, and were treated with first-line definitive radiation or chemo/radiation with the intent to cure. The association between patient characteristics and treatment response was assessed using the χ2 test and logistic regression analysis. Survival outcomes were analyzed using Kaplan-Meier methods and Cox proportional-hazards models. RESULTS: Of the 140 current smokers, 61 patients (45%) quit smoking prior to treatment initiation. In adjusted logistic regression analysis, quitters had 3.7 times higher odds of achieving a complete response to first-line therapy than active smokers (odds ratio: 3.694 [1.575-8.661]; P = .003). In the adjusted Cox proportional-hazards model, quitters were 54% less likely to require salvage laryngectomy within 7 years of diagnosis than active smokers (hazard ratio: 0.456 [0.246-0.848]; P = .013). Quitters had a statistically significant increase in 7-year overall survival compared to active smokers (P = .02). CONCLUSION: This is the first study to show that in newly diagnosed laryngeal cancer patients who are current smokers at the time of diagnosis, tobacco cessation significantly increases therapy response, laryngectomy-free survival, and overall survival. These data stress the importance of systematically incorporating tobacco cessation programs into laryngeal cancer treatment plans.

Impact of Race and Age and their Interaction on Survival Outcomes in Patients With Diffuse Large B-Cell Lymphoma.

BACKGROUND: Advances in treatment for patients with Diffuse Large B-Cell Lymphoma (DLBCL) have led to improved patient outcomes but the magnitude of these disparities remains understudied with regards to improved survival outcomes. We sought to describe changes in DLBCL survival trends over time and explore potential differential survival patterns by patients' race/ethnicity and age. METHODS: We utilized the Surveillance, Epidemiology, and End Results (SEER) database to identify patients diagnosed with DLBCL from 1980 to 009 and determined 5-year survival outcomes for all patients, categorizing patients by year of diagnosis. We used descriptive statistics and logistic regression, adjusting for stage and year of diagnosis, to describe changes in 5-year survival rates over time by race/ethnicity and age. RESULTS: We identified 43,564 patients with DLBCL eligible for this study. Median age was 67 years (ages: 18-64 = 44.2%, 65-79 = 37.1%, 80 + = 18.7%). Most patients were male (53.4%) and had advanced stage III/IV disease (40.0%). Most patients were White race (81.4%), followed by Asian/Pacific Islander (API) (6.3%), Black (6.3%), Hispanic (5.4%), and American Indian/Alaska Native (AIAN) (0.05%). Overall, the 5-year survival rate improved from 35.1% in 1980 to 52.4% in 2009 across all races and age groups (odds ratio [OR] for 5-year survival with increasing year of diagnosis = 1.05, P < .001). Patients in racial/ethnic minority groups (API: OR = 0.86, P < .0001; Black: OR = 0.57, P < .0001; AIAN: OR = 0.51, P = .008; Hispanic: 0.76, P = 0.291) and older adults (ages 65-79: OR = 0.43, P < .0001; ages 80+: OR = 0.13, P < .0001) had lower 5-year survival rates after adjusting for race, age, stage, and diagnosis year. We found consistent improvement in the odds of 5-year survival for year of diagnosis across all race and ethnicity groups (White: OR = 1.05, P < .001; API: OR = 1.04, P < .001; Black: OR = 1.06, p<.001; AIAN: OR = 1.05, P < .001; Hispanic: OR = 1.05, P < .005) and age groups (ages 18-64: OR = 1.06, P < .001; ages 65-79: OR = 1.04, P < .001; ages 80+: OR = 1.04, P < .001). CONCLUSION: Patients with DLBCL experienced improvements in 5-year survival rates from 1980 to 2009, despite persistently lower survival among patients in racial/ethnic minority groups and older adults.

Use of Aerosolized Prostacyclins in Critically Ill Patients and Association With Clinical Outcomes.

Aerosolized prostacyclins are frequently used in patients with severe acute respiratory distress syndrome and refractory hypoxia. Previous studies have shown improvement in oxygenation with use of pulmonary vasodilators such as iloprost and epoprostenol; however, there is no head-to-head comparison between these agents. OBJECTIVES: To compare the effects of inhaled epoprostenol and inhaled iloprost in critically ill patients with refractory hypoxia. DESIGN SETTING AND PARTICIPANTS: We performed a retrospective cohort analysis of patients admitted to the ICUs at the University of Oklahoma Health Sciences Center between 2015 and 2018. Adult patients who received aerosolized epoprostenol or iloprost for more than 4 hours were included in the analysis. MAIN OUTCOMES AND MEASURES: The primary endpoint measured was to compare the change in Pao2/Fio2 ratio between patients treated with iloprost compared with epoprostenol. Secondary outcomes measured were 90-day in-hospital mortality and improvement in vasopressor requirements. RESULTS: A total of 126 patients were included in the study, 95 of whom received iloprost (75%) and 31 patients (25%) received epoprostenol. There were significant improvements in Pao2/Fio2 ratio in both the iloprost and epoprostenol group. Patients in the epoprostenol group appeared to have a higher 90-day mortality compared with the iloprost group. However, our study was not powered to detect a mortality difference and this finding likely represents a sicker population in the epoprostenol group and prescription bias. The use of iloprost was associated with higher vasopressor requirements in the first 12 hours of administration, an association was not observed in the epoprostenol group. CONCLUSIONS AND RELEVANCE: In this retrospective cohort analysis, use of both pulmonary vasodilators was associated with similar improvement in gas exchange. The mortality difference observed likely represents difference in severity of illness. Further studies are needed to corroborate these findings.

Immediate weight loss before ovarian stimulation with intrauterine insemination is associated with a lower risk of preeclampsia in women with obesity and unexplained infertility.

Objective: To determine whether successful weight loss before ovarian stimulation with intrauterine insemination (OS-IUI) affects the risk of future pregnancy complications among women with obesity and unexplained infertility after fertility treatment. Design: Secondary analysis of the randomized controlled clinical trial Improving Reproductive Fitness Through Pretreatment With Lifestyle Modification in Obese Women With Unexplained Infertility (FIT-PLESE). Setting: Multiple academic health centers in the United States. Patients: Three hundred seventy-nine women with obesity and unexplained infertility who underwent standard infertility treatment after a lifestyle intervention. Interventions: The FIT-PLESE trial evaluated whether prepregnancy lifestyle interventions (diet with weight loss medication and exercise vs. exercise alone) before OS-IUI improved the live birth rate among women with obesity and unexplained infertility. Although the primary outcome of FIT-PLESE was live birth rate, we compared the demographics and subsequent pregnancy complications of women who successfully lost some weight with those of women who did not lose any during the interventions. Main Outcome Measures: Obstetric complications by groups were compared using χ2 and Fisher's exact tests, and continuous variables were compared using Student's t-tests. Logistic regression was used to assess the odds of preeclampsia after adjustment for the randomized treatment arm in FIT-PLESE. Results: There was a nonsignificant trend toward a lower risk of intrauterine growth restriction (4% vs. 16%, P = .124) and preterm delivery (6% vs. 15%, P = .343) among patients who lost at least some weight. The risk of preeclampsia was significantly lower (6% vs.35%, P = .002) in the weight loss group (odds ratio, 0.09; 95% confidence interval, 0.016-0.505; P = .006) after adjustment for treatment assignment. Conclusions: Among women with obesity and unexplained infertility who had live births after fertility treatment, prepregnancy weight loss due to lifestyle interventions before OS-IUI was associated with a lower risk of preeclampsia.

Tobacco cessation after head and neck cancer diagnosis is an independent predictor of treatment response and long-term survival.

Head and neck squamous cell carcinoma (HNSCC) patients who are current smokers when diagnosed have inferior clinical outcomes compared to never-smokers or previous smokers. However, the impact of quitting after HNSCC diagnosis has not been quantified. In this retrospective, case-control study (n = 134), the odds of complete response to first-line therapy were 3.7 times higher among smokers at diagnosis who quit before treatment initiation (quitters; n = 55) than among those continuing to smoke (p = 0.03). Disease-free survival was also higher among quitters (aHR, 0.33; 95 % CI, 0.12-0.90; p = 0.029). Quitters were 67 % less likely to die of all causes than active smokers (aHR, 0.33; 95 % CI, 0.15-0.71; p = 0.004). These data show for the first time that, smoking cessation after HNSCC diagnosis is predictive of higher therapy efficacy and long-term survival.

An unsupervised machine learning approach using passive movement data to understand depression and schizophrenia.

INTRODUCTION: Schizophrenia and Major Depressive Disorder (MDD) are highly burdensome mental disorders, with significant cost to both individuals and society. Despite these disorders representing distinct clinical categories, they are each heterogenous in their symptom profiles, with considerable transdiagnostic features. Although movement and sleep abnormalities exist in both disorders, little is known of the precise nature of these changes longitudinally. Passively-collected longitudinal data from wearable sensors is well suited to characterize naturalistic features which may cross traditional diagnostic categories (e.g., highlighting behavioral markers not captured by self-report information). METHODS: The present analyses utilized raw minute-level actigraphy data from three diagnostic groups: individuals with schizophrenia (N = 23), individuals with depression (N = 22), and controls (N = 32), respectively, to interrogate naturalistic behavioral differences between groups. Subjects' week-long actigraphy data was processed without diagnostic labels via unsupervised machine learning clustering methods, in order to investigate the natural bounds of psychopathology. Further, actigraphic data was analyzed across time to determine timepoints influential in model outcomes. RESULTS: We find distinct actigraphic phenotypes, which differ between diagnostic groups, suggesting that unsupervised clustering of naturalistic data aligns with existing diagnostic constructs. Further, we found statistically significant inter-group differences, with depressed persons showing the highest behavioral variability. LIMITATIONS: However, diagnostic group differences only consider biobehavioral trends captured by raw actigraphy information. CONCLUSIONS: Passively-collected movement information combined with unsupervised deep learning algorithms shows promise in identifying naturalistic phenotypes in individuals with mental health disorders, specifically in discriminating between MDD and schizophrenia.

Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment naive. We uncovered recurrent expression programs across malignant cells and fibroblasts, including a newly identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities with distinct contributions from malignant, fibroblast and immune subtypes: classical, squamoid-basaloid and treatment enriched. Our refined molecular and cellular taxonomy can provide a framework for stratification in clinical trials and serve as a roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.

Evaluating the Response of Palbociclib on Progression-Free Survival in Hormone Receptor-Positive Metastatic Breast Cancer.

BACKGROUND: In patients with hormone receptor-positive metastatic breast cancer, palbociclib has been shown to improve overall survival and progression-free survival (PFS) when combined with endocrine therapy. Dose modification of palbociclib is effective in the management of adverse events. Despite variable clinical response, no predictive biomarkers of efficacy to palbociclib have been identified in metastatic breast cancer. In our study, we aimed to assess the PFS of metastatic breast cancer patients who received dose-reduced palbociclib and compare the results in the non-dose-reduced group. We also evaluated the clinical significance of progesterone receptor (PR) and Ki67 as predictive biomarkers of palbociclib. METHODS: Seventy-six palbociclib-treated metastatic breast cancer patients were included in our study. PFS was compared between dose-reduced and non-dose-reduced groups. PR expression and Ki67 status were assessed by immunohistochemistry. Kaplan-Meier method and log-rank test were used to analyze PFS. RESULTS: Of the 76 patients, 40 (52.6%) experienced dose reduction (DR). Statistical analysis of the results revealed that there were no statistically significant differences observed between dose-reduced (16.5 months) versus non-dose-reduced (17.7 months) patients in PFS (p = 0.5493). For patients with Ki67 ≥14%, PFS was 15.2 months (95% CI: 10.2-22.2 months; p = 0.3024). In patients with PR ≥20%, median PFS was 25.0 months (lower 95% CI: 16.8 months; p = 0.0069). CONCLUSION: Our study indicated that DR of palbociclib is frequently required but does not appear to affect PFS. PR expression was suggested to be a significant predictive factor for palbociclib responsiveness.

Prognostic impact of natural killer cell recovery on minimal residual disease after autologous stem cell transplantation in multiple myeloma.

INTRODUCTION: Natural killer cells are a potent effector lymphocyte subset that can induce cytotoxicity without the need for antigen sensitization or presentation. NK cells are a tempting target -for immune therapy, monoclonal antibody, or genetic engineering-to enhance immune surveillance mechanisms against myeloma cells. MATERIALS AND METHODS: We hypothesized an association between natural killer cell recovery after autologous stem cell transplantation (ASCT) and disease outcomes in multiple myeloma patients. We concluded a prospective study that started enrolling patients in January 2020 to identify the association between absolute NK cell count two to three after ASCT and disease outcomes after autologous stem cell transplantation in multiple myeloma using univariate and multivariate analysis. RESULTS: Natural killer cell recovery was evaluated during the third month after ASCT, day +60 to +90 post-ASCT. Our patients had a mean NK cell count of 90.53, ranging from 14 to 282 Cell/µL (Std Dev 84.64 Cell/µL). The odds of having a minimal residual disease (MRD-positivity) among patients with partial remission before transplantation is four times higher than patients with very good partial response or better (95% confidence interval 0.45-35.79). Our patients were classified into two groups based on MRD status after ASCT, an MRD-negative group of eight participants and an MRD-positive group of seven participants. The mean absolute NK cell count was significantly higher in the MRD-negative cohort, 131.38 Cell/µL, versus 43.86 Cell/µL in the MRD-positive group (p = 0.049). CONCLUSION: We conclude that for multiple myeloma patients treated with ASCT, high absolute NK cell counts two to three months after ASCT is an independent predictor for MRD negativity.

Merkel cell carcinoma: treatment and outcomes over a 10-year period at a high-volume academic center.

BACKGROUND: Merkel cell carcinoma (MCC) is a rare, highly aggressive malignancy which lacks high-level evidence-based treatment guidelines. METHODS: To determine outcomes of MCC patients and assess the role of radiation in treatment, we performed a retrospective chart review of patients treated for MCC between 2006 and 2016 at a single high-volume academic medical center. The primary outcome was overall survival (OS) for the entire population and for those populations receiving specific therapies. RESULTS: Forty-two patients were evaluable. OS for all patients was not reached since most remain alive at time of analysis. OS for the American Joint Committee on Cancer (AJCC) stage I was not reached. OS for stages II, III, and IV was 37.3 months (6.8, -), 49.5 months (14.2, 49.5), and 14.5 months (10.8, -), respectively. OS could not be reached in the high radiotherapy (RT) dose group (biologically equivalent dose [BED] ≥ 60) and was 49.5 months (10.8, -) in the low-dose group (BED < 60). For surgical margin status, OS was 14.9158 months (6.8008, -) for positive margins and 37.3 months (10.8, -) for negative margins. CONCLUSIONS: No conclusive findings for OS were identified; however, trends for improved OS were associated with lower AJCC staging, negative surgical margins, and high RT doses.

HLA-A∗02:01 restricted T cell receptors against the highly conserved SARS-CoV-2 polymerase cross-react with human coronaviruses.

Cross-reactivity and direct killing of target cells remain underexplored for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-specific CD8+ T cells. Isolation of T cell receptors (TCRs) and overexpression in allogeneic cells allows for extensive T cell reactivity profiling. We identify SARS-CoV-2 RNA-dependent RNA polymerase (RdRp/NSP12) as highly conserved, likely due to its critical role in the virus life cycle. We perform single-cell TCRαß sequencing in human leukocyte antigen (HLA)-A∗02:01-restricted, RdRp-specific T cells from SARS-CoV-2-unexposed individuals. Human T cells expressing these TCRαß constructs kill target cell lines engineered to express full-length RdRp. Three TCR constructs recognize homologous epitopes from common cold coronaviruses, indicating CD8+ T cells can recognize evolutionarily diverse coronaviruses. Analysis of individual TCR clones may help define vaccine epitopes that can induce long-term immunity against SARS-CoV-2 and other coronaviruses.

Pan-Cancer Survival Classification With Clinicopathological and Targeted Gene Expression Features.

Prognostication for patients with cancer is important for clinical planning and management, but remains challenging given the large number of factors that can influence outcomes. As such, there is a need to identify features that can robustly predict patient outcomes. We evaluated 8608 patient tumor samples across 16 cancer types from The Cancer Genome Atlas and generated distinct survival classifiers for each using clinical and histopathological data accessible to standard oncology workflows. For cancers that had poor model performance, we deployed a random-forest-embedded sequential forward selection approach that began with an initial subset of the 15 most predictive clinicopathological features before sequentially appending the next most informative gene as an additional feature. With classifiers derived from clinical and histopathological features alone, we observed cancer-type-dependent model performance and an area under the receiver operating curve (AUROC) range of 0.65 to 0.91 across all 16 cancer types for 1- and 3-year survival prediction, with some classifiers consistently outperforming those for others. As such, for cancers that had poor model performance, we posited that the addition of more complex biomolecular features could enhance our ability to prognose patients where clinicopathological features were insufficient. With the inclusion of gene expression data, model performance for 3 select cancers (glioblastoma, stomach/gastric adenocarcinoma, ovarian serous carcinoma) markedly increased from initial AUROC scores of 0.66, 0.69, and 0.67 to 0.76, 0.77, and 0.77, respectively. As a whole, this study provides a thorough examination of the relative contributions of clinical, pathological, and gene expression data in predicting overall survival and reveals cancer types for which clinical features are already strong predictors and those where additional biomolecular information is needed.

Pan-cancer Transcriptomic Predictors of Perineural Invasion Improve Occult Histopathologic Detection.

PURPOSE: Perineural invasion (PNI) is associated with aggressive tumor behavior, recurrence, and metastasis, and can influence the administration of adjuvant treatment. However, standard histopathologic examination has limited sensitivity in detecting PNI and does not provide insights into its mechanistic underpinnings. EXPERIMENTAL DESIGN: A multivariate Cox regression was performed to validate associations between PNI and survival in 2,029 patients across 12 cancer types. Differential expression and gene set enrichment analysis were used to learn PNI-associated programs. Machine learning models were applied to build a PNI gene expression classifier. A blinded re-review of hematoxylin and eosin (H&E) slides by a board-certified pathologist helped determine whether the classifier could improve occult histopathologic detection of PNI. RESULTS: PNI associated with both poor overall survival [HR, 1.73; 95% confidence interval (CI), 1.27-2.36; P < 0.001] and disease-free survival (HR, 1.79; 95% CI, 1.38-2.32; P < 0.001). Neural-like, prosurvival, and invasive programs were enriched in PNI-positive tumors (P adj < 0.001). Although PNI-associated features likely reflect in part the increased presence of nerves, many differentially expressed genes mapped specifically to malignant cells from single-cell atlases. A PNI gene expression classifier was derived using random forest and evaluated as a tool for occult histopathologic detection. On a blinded H&E re-review of sections initially described as PNI negative, more specimens were reannotated as PNI positive in the high classifier score cohort compared with the low-scoring cohort (P = 0.03, Fisher exact test). CONCLUSIONS: This study provides salient biological insights regarding PNI and demonstrates a role for gene expression classifiers to augment detection of histopathologic features.

Electronic cigarette aerosols alter the expression of cisplatin transporters and increase drug resistance in oral cancer cells.

Tobacco smoking is the leading preventable cause of cancer. Moreover, continued smoking during cancer therapy reduces overall survival. Aware of the negative consequences of tobacco smoking and the challenges of smoking cessation, cancer patients are inquiring whether they should switch to electronic cigarettes (e-cigarettes). To obtain evidence-based data to inform this decision, we examined the effects of e-cigarette aerosol exposure on cisplatin resistance in head and neck cancer cells. Our results show that cancer cells exposed to e-cigarette aerosol extracts and treated with cisplatin have a significant decrease in cell death, increase in viability, and increase in clonogenic survival when compared to non-exposed cells. Moreover, exposure to e-cigarette aerosol extracts increased the concentration of cisplatin needed to induce a 50% reduction in cell growth (IC50) in a nicotine-independent manner. Tobacco smoke extracts induced similar increases in cisplatin resistance. Changes in the expression of drug influx and efflux transporters, rather than activation of cell growth-promoting pathways or DNA damage repair, contribute to e-cigarette induced cisplatin resistance. These results suggest that like combustible tobacco, e-cigarette use might increase chemotherapy resistance, and emphasize the urgent need for rigorous evaluation of e-cigarettes health effects to ensure evidence-based public health policies.

The impact of the Federal Pandemic Unemployment Compensation on job search and vacancy creation.

During the COVID-19 pandemic, the Federal Pandemic Unemployment Compensation (FPUC) increased US unemployment benefits by $600 a week. Theory predicts that FPUC should decrease job applications, while the effect on vacancy creation is ambiguous. We estimate the effect of FPUC on job applications and vacancy creation week by week, from March to July 2020, using granular data from the online jobs platform Glassdoor. We exploit variation in the proportional increase in benefits across local labor markets. To isolate the effect of FPUC, we flexibly allow for different trends in local labor markets differentially exposed to the COVID-19 crisis. We verify that trends in outcomes prior to the FPUC do not correlate with future increases in benefits, which supports our identification assumption. First, we find that a 10% increase in unemployment benefits caused a 3.6% decline in applications, but did not decrease vacancy creation; hence, FPUC increased labor market tightness (vacancies/applications). Second, we document that tightness was unusually depressed during the FPUC period. Altogether, our results imply that the positive effect of FPUC on tightness was likely welfare improving: FPUC decreased competition among applicants at a time when jobs were unusually scarce. Our results also help explain prior findings that FPUC did not decrease employment.

Quantifying Mineral-Ligand Structural Similarities: Bridging the Geological World of Minerals with the Biological World of Enzymes.

Metal compounds abundant on Early Earth are thought to play an important role in the origins of life. Certain iron-sulfur minerals for example, are proposed to have served as primitive metalloenzyme cofactors due to their ability to catalyze organic synthesis processes and facilitate electron transfer reactions. An inherent difficulty with studying the catalytic potential of many metal compounds is the wide range of data and parameters to consider when searching for individual minerals and ligands of interest. Detecting mineral-ligand pairs that are structurally analogous enables more relevant selections of data to study, since structural affinity is a key indicator of comparable catalytic function. However, current structure-oriented approaches tend to be subjective and localized, and do not quantify observations or compare them with other potential targets. Here, we present a mathematical approach that compares structural similarities between various minerals and ligands using molecular similarity metrics. We use an iterative substructure search in the crystal lattice, paired with benchmark structural similarity methods. This structural comparison may be considered as a first stage in a more advanced analysis tool that will include a range of chemical and physical factors when computing mineral-ligand similarity. This approach will seek relationships between the mineral and enzyme worlds, with applications to the origins of life, ecology, catalysis, and astrobiology.

Association of financial assistance programs and time to completion of therapy in women receiving chemoradiation for cervical cancer.

We aimed to evaluate how the need for social services programs is associated with outcomes amongst patients with cervical cancer undergoing chemoradiation with a single institution, retrospective analysis of patients from January 1, 2015-July 31, 2018. Demographic, clinical, and social services utilization data were collected. Descriptive statistics and Chi-squared tests were performed. Kaplan-Meier curves estimated progression free (PFS) and overall survival (OS). Among 117 eligible patients, median household income was $45,782 ($19,771 - $96,222). There was no difference in stage among income cohorts. Uninsured/publically insured patients had a higher stage at diagnosis than those privately insured (p = 0.003). Patients used 0-5 assistance programs during treatment. 77.6% of low income versus 54.2% of high income patients utilized ≥1 program. Assistance with lodging was utilized more often in low than high income patients. (36.2% vs 15.7%, p = 0.013). 58.3% of patients completed therapy in less than 56 days. Patients who completed therapy in >56 days utilized 1.44 social services while patients completing in ≤56 days used 1.06 (p = 0.102). Social security disability utilization trended towards completion times >56 days (p = 0.064). There was no difference in PFS or OS based on income or social services utilized. Financial toxicities associated with therapy are not limited to uninsured/publically insured or low income patients as over 50% of high income patients utilized at least one service. Additionally, the trend towards significance between enrollment in disability and completion of chemoradiation >56 days may highlight a group of at risk patients who need additional support.

Use of Nonsteroidal Anti-inflammatory Drugs for COVID-19 Infection: Adjunct Therapy?

Severe acute respiratory distress syndrome coronavirus 2 (COVID-19) is the cause of the current pandemic, which remains a tremendous cause of morbidity and mortality worldwide. Although there are numerous trials underway, there is currently no medication known to cure the infection. Nonsteroidal anti-inflammatory drugs (NSAIDs) are inexpensive, widely available medications with antiviral and anti-inflammatory properties and may have utility as an adjunct therapy to improve outcomes in patients with severe COVID-19 infection. A thorough PubMed literature review on the therapeutic use of NSAID was conducted to provide a comprehensive perspective of the role of NSAIDs in treating COVID-19. NSAIDs may be a useful adjunct therapy for patients with severe COVID-19 infection, but further investigation and clinical trials are necessary to ensure their safety and efficacy.