Comparative analysis of thermal indices for modeling cold and heat stress in US dairy systems

Quantifying the impact of thermal stress on milk yields is essential to effectively manage present and future risks in dairy systems. Despite the existence of numerous heat indices designed to communicate stress thresholds, little information is available regarding the accuracy of different indices in estimating milk yield losses from both cold and heat stress at large spatio-temporal scales. To address this gap, we comparatively analyzed the performance of existing thermal indices in capturing US milk yield response to both cold and heat stress at the national scale. We selected four commonly used thermal indices: the Temperature and Humidity Index (THI), Black Globe Humidity Index (BGHI), Adjusted Temperature and Humidity Index (THIadj), and Comprehensive Climate Index (CCI). Using a statistical panel regression model with observational and reanalysis weather data from 1981-2020, we systematically compared the patterns of yield sensitivities and statistical performance of the four indices. We found that the US state-level milk yield variability was better explained by the THIadj and CCI, which combine the effects of temperature, humidity, wind, and solar radiation. Our analysis also reveals a continuous and nonlinear responses of milk yields to a range of cold to heat stress across all four indices. This implies that solely relying on fixed thresholds of these indices to model milk yield changes may be insufficient to capture cumulative thermal stress. Cold extremes reduced milk yields comparably to those impacted by heat extremes on the national scale. Additionally, we found large spatial variability in milk yield sensitivities, implying further limitations to the use of fixed thresholds across locations. Moreover, we found decreased yield sensitivity to thermal stress in the most recent two decades, suggesting adaptive changes in management to reduce weather-related risks.

Metabolomic profiles of ovariectomized mice and their associations with body composition and frailty-related parameters in postmenopausal women

BACKGROUND

Menopause, a dramatical estrogen-deficient condition, is considered the most significant milestone in women's health.

PURPOSE

To investigate the metabolite changes attributed to estrogen deficiency using random forest (RF)-based machine learning (ML) modeling strategy in ovariectomized (OVX) mice as well as determine the clinical relevance of selected metabolites in older women.

METHODS AND RESULTS

Untargeted and targeted metabolomic analyses revealed that metabolites related to TCA cycle, sphingolipids, phospholipids, fatty acids, and amino acids, were significantly changed in the plasma and/or muscle of OVX mice. Subsequent ML classifiers based on RF algorithm selected alpha-ketoglutarate (AKG), arginine, carnosine, ceramide C24, phosphatidylcholine (PC) aa C36:6, and PC ae C42:3 in plasma as well as PC aa 34:1, PC aa C34:3, PC aa C36:5, PC aa C32:1, PC aa C36:2, and sphingosine in muscle as top featured metabolites that differentiate the OVX mice from the sham-operated group. When circulating levels of AKG, arginine, and carnosine, which showed the most significant changes in OVX mice blood, were measured in postmenopausal women, higher plasma AKG levels were associated with lower bone mass, weak grip strength, poor physical performance, and increased frailty risk.

CONCLUSIONS

Metabolomics- and ML-based methods identified the key metabolites of blood and muscle that were significantly changed after ovariectomy in mice, and the clinical implication of several metabolites was investigated by looking at their correlation with body composition and frailty-related parameters in postmenopausal women. These findings provide crucial context for understanding the diverse physiological alterations caused by estrogen deficiency in women.

Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model

BACKGROUND

Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors.

METHODS

The authors analyzed data from 8448 ever-smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997-2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC-RAT and further explored the potential of improving SPLC detection through risk model-based surveillance using SPLC-RAT versus existing clinical surveillance guidelines.

RESULTS

Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person-years. The application of SPLC-RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10-year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC-RAT development cohort), the observed SPLC incidence was significantly elevated in the high-risk versus low-risk subgroup (13.1% vs. 1.1%, p < 1 × 10-6 ). The risk-based surveillance through SPLC-RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow-ups needed to detect one SPLC (162 vs. 202).

CONCLUSION

In a large, hospital-based cohort, the authors validated the predictive performance of SPLC-RAT in identifying high-risk survivors of SPLC and showed its potential to improve SPLC detection through risk-based surveillance.

PLAIN LANGUAGE SUMMARY

Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.

Near-perfect sound absorption using hybrid resonance between subwavelength Helmholtz resonators with non-uniformly partitioned cavities

We present near-perfect sound absorption using a metasurface composed of meta-atoms (MAs) which are subwavelength Helmholtz resonators (HRs) with cavities non-uniformly partitioned by membranes. By embedding the membranes at different horizontal locations in the cavities, we break geometrical symmetry between the MAs so as to derive hybrid resonance between the MAs at our target frequency. The resonance frequency of each MA is determined by delicately adjusting the locations of the membranes, resulting in perfect absorption at the target frequency which is different from the resonance frequencies of MAs. The metasurface is designed to satisfy impedance matching conditions with air at one or more target frequencies with the aid of a theoretical model for frequency-dependent effective acoustic impedance. The theoretical model is established with physical reality by considering the higher-order eigenmodes of the membrane, the visco-thermal losses in narrow orifices, and the end corrections of the subwavelength HR. The designed metasurface is fabricated and its absorption performance is verified experimentally in an impedance tube. Near-perfect absorption of sound is achieved at the target frequency of 500 Hz, which is 12.3% lower than that of near-perfect absorption by previous metasurfaces inducing hybrid resonance between HRs without membranes.

N-Carbon-Doped Binary Nanophase of Metal Oxide/Metal-Organic Framework for Extremely Sensitive and Selective Gas Response

Metal-organic frameworks (MOFs), which are highly ordered structures exhibiting sub-nanometer porosity, possess significant potential for diverse gas applications. However, their inherent insulative properties limit their utility in electrochemical gas sensing. This investigation successfully modifies the electrical conductivity of zeolitic imidazolte framework-8 (ZIF-8) employing a straightforward surface oxidation methodology. A ZIF-8 polycrystalline layer is applied on a wafer-scale oxide substrate and subjects to thermal annealing at 300 °C under ambient air conditions, resulting in nanoscale oxide layers while preserving the fundamental properties of the ZIF-8. Subsequent exposure to NO2 instigates the evolution of an electrically interconnected structure with the formation of electron-rich dopants derived from the decomposition of nitrogen-rich organic linkers. The N-carbon-hybridized ZnO/ZIF-8 device demonstrates remarkable sensitivity (≈130 ppm-1 ) and extreme selectivity in NO2 gas detection with a lower detection limit of 0.63 ppb under 150 °C operating temperature, surpassing the performance of existing sensing materials. The exceptional performances result from the Debye length scale dimensionality of ZnO and the high affinity of ZIF-8 to NO2 . The methodology for manipulating MOF conductivity through surface oxidation holds the potential to accelerate the development of MOF-hybridized conductive channels for a variety of electrical applications.

Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks

MOTIVATION

Providing a dynamic assessment of prognosis is essential for improved personalized medicine. The landmark model for survival data provides a potentially powerful solution to the dynamic prediction of disease progression. However, a general framework and a flexible implementation of the model that incorporates various outcomes, such as competing events, have been lacking. We present an R package, dynamicLM, a user-friendly tool for the landmark model for the dynamic prediction of survival data under competing risks, which includes various functions for data preparation, model development, prediction and evaluation of predictive performance.

IMPLEMENTATION

dynamicLM as an R package.

GENERAL FEATURES

The package includes options for incorporating time-varying covariates, capturing time-dependent effects of predictors and fitting a cause-specific landmark model for time-to-event data with or without competing risks. Tools for evaluating the prediction performance include time-dependent area under the ROC curve, Brier Score and calibration.

AVAILABILITY

Available on GitHub [https://github.com/thehanlab/dynamicLM].

Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US

Importance

The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model-based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity.

Objective

To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model-a well-established risk prediction model based on a predominantly White population-across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria.

Design, Setting, and Participants

In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105 261 adults with a smoking history were included.

Exposures

The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines.

Outcomes

Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer).

Results

Of 105 261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19 258 (18.3%) African American, 27 227 (25.9%) Japanese American, 21 383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29 025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio: 9.5 vs 20.3; P < .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio: 15.9 vs 18.4; P < .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity-specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%).

Conclusions

The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria.

Second Primary Lung Cancer Among Lung Cancer Survivors Who Never Smoked

Importance

Lung cancer among never-smokers accounts for 25% of all lung cancers in the US; recent therapeutic advances have improved survival among patients with initial primary lung cancer (IPLC), who are now at high risk of developing second primary lung cancer (SPLC). As smoking rates continue to decline in the US, it is critical to examine more closely the epidemiology of lung cancer among patients who never smoked, including their risk for SPLC.

Objective

To estimate and compare the cumulative SPLC incidence among lung cancer survivors who have never smoked vs those who have ever smoked.

Design, Setting, and Participants

This population-based prospective cohort study used data from the Multiethnic Cohort Study (MEC), which enrolled participants between April 18, 1993, and December 31, 1996, with follow-up through July 1, 2017. Eligible individuals for this study were aged 45 to 75 years and had complete smoking data at baseline. These participants were followed up for IPLC and further SPLC development through the Surveillance, Epidemiology, and End Results registry. The data were analyzed from July 1, 2022, to January 31, 2023.

Exposures

Never-smoking vs ever-smoking exposure at MEC enrollment.

Main Outcomes and Measures

The study had 2 primary outcomes: (1) 10-year cumulative incidence of IPLC in the entire study cohort and 10-year cumulative incidence of SPLC among patients with IPLC and (2) standardized incidence ratio (SIR) (calculated as the SPLC incidence divided by the IPLC incidence) by smoking history.

Results

Among 211 414 MEC participants, 7161 (3.96%) developed IPLC over 4 038 007 person-years, and 163 (2.28%) developed SPLC over 16 470 person-years. Of the participants with IPLC, the mean (SD) age at cohort enrollment was 63.6 (7.7) years, 4031 (56.3%) were male, and 3131 (43.7%) were female. The 10-year cumulative IPLC incidence was 2.40% (95% CI, 2.31%-2.49%) among ever-smokers, which was 7 times higher than never-smokers (0.34%; 95% CI, 0.30%-0.37%). However, the 10-year cumulative SPLC incidence following IPLC was as high among never-smokers (2.84%; 95% CI, 1.50%-4.18%) as ever-smokers (2.72%; 95% CI, 2.24%-3.20%), which led to a substantially higher SIR for never-smokers (14.50; 95% CI, 8.73-22.65) vs ever-smokers (3.50; 95% CI, 2.95-4.12).

Conclusions and Relevance

The findings indicate that SPLC risk among lung cancer survivors who never smoked is as high as among those with IPLC who ever-smoked, highlighting the need to identify risk factors for SPLC among patients who never smoked and to develop a targeted surveillance strategy.

A CRISPR activation screen identifies MUC-21 as critical for resistance to NK and T cell-mediated cytotoxicity

BACKGROUND

Immunotherapy has significantly advanced cancer treatments, but many patients do not respond to it, partly due to immunosuppressive mechanisms used by tumor cells. These cells employ immunosuppressive ligands to evade detection and elimination by the immune system. Therefore, the discovery and characterization of novel immunosuppressive ligands that facilitate immune evasion are crucial for developing more potent anti-cancer therapies.

METHODS

We conducted gain-of-function screens using a CRISPRa (CRISPR activation) library that covered the entire human transmembrane sub-genome to identify surface molecules capable of hindering NK-mediated cytotoxicity. The immunosuppressive role and mechanism of MUC21 were validated using NK and T cell mediated cytotoxicity assays. Bioinformatics tools were employed to assess the clinical implications of mucin-21 (MUC21) in cancer cell immunity.

RESULTS

Our genetic screens revealed that MUC21 expression on cancer cell surfaces inhibits both the cytotoxic activity of NK cells and antibody-dependent cellular cytotoxicity, but not affecting complement-dependent cytotoxicity. Additionally, MUC21 expression hinders T cell activation by impeding antigen recognition, thereby diminishing the effectiveness of the immune checkpoint inhibitor, anti-PD-L1. Moreover, MUC21 expression suppress the antitumor function of both CAR-T cells and CAR-NK cells. Mechanistically, MUC21 facilitates immune evasion by creating steric hindrance, preventing interactions between cancer and immune cells. Bioinformatics analysis revealed elevated MUC21 expression in lung cancer, which correlated with reduced infiltration and activation of cytotoxic immune cells. Intriguingly, MUC21 expression was higher in non-small cell lung cancer (NSCLC) tumors that were non-responsive to anti-PD-(L)1 treatment compared to responsive tumors.

CONCLUSIONS

These findings indicate that surface MUC21 serves as a potent immunosuppressive ligand, shielding cancer cells from NK and CD8+T cell attacks. This suggests that inhibiting MUC21 could be a promising strategy to improve cancer immunotherapy.

Assessment of Bladder Filling Type on Radiation Dose to Organs at Risk in MR-Guided Intracavity Brachytherapy for Cervical Cancer

PURPOSE/OBJECTIVE(S)

In this study, we evaluated whether the classification of bladder shape affects the absorbed dose (Gy) of OARs and its geometrical position to normal organs in MR-guided intracavitary brachytherapy (ICBT).

MATERIALS/METHODS

In this study, 269 patients who underwent MR-guided ICBT for cervical cancer from 2016 to 2022 were included. The applicator-inserted bladder filling type (BFT) classification was divided into three types (tilted, curved, and other shapes: group E). The anatomical positional relationship between the uterus and its surroundings was measured on pre-MR images and ICBT simulation MR images. Spearman's rank correlation analysis was used for bladder volume and OAR dose according to BFT. Anatomical differences were analyzed by ANOVA by measuring the distance from the center to both bladder walls.

RESULTS

In the correlation analysis considering the shape of the bladder, the tilted, curved, and group E had Spearman's ρ of 0.211; -0.323, 0.412; -0.307 and -0.035; -0.209 for maximum absorbed dose (D2cc) of bladder and small bowel, respectively. It was statistically significant in the tilted type and curved type. The average left and right bladder lengths differences of the tilted type were the highest at 8.47 cm and 7.11 cm, respectively. It was a statistically significant between bladder shape and the difference in left and right bladder lengths differences (p< 0.01).

CONCLUSION

In this study, it was confirmed that bladder distension increased the maximum bladder dose (D2cc) and decreased the maximum bowel dose (D2cc) to the tilted type and curved type. In addition, if the left and right bladder lengths are measured in pre-MR, the degree of bladder distension can be evaluated in advance by checking the shape of the bladder in the case of the tilting type before ICBT. Based on these findings, a prospective study is needed to evaluate the effect of ICBT on cervical cancer treatment outcomes through bladder type classification.

Overall Survival Among Patients With De Novo Stage IV Metastatic and Distant Metastatic Recurrent Non-Small Cell Lung Cancer

Importance

Despite recent breakthroughs in therapy, advanced lung cancer still poses a therapeutic challenge. The survival profile of patients with metastatic lung cancer remains poorly understood by metastatic disease type (ie, de novo stage IV vs distant recurrence).

Objective

To evaluate the association of metastatic disease type on overall survival (OS) among patients with non-small cell lung cancer (NSCLC) and to identify potential mechanisms underlying any survival difference.

Design, Setting, and Participants

Cohort study of a national US population based at a tertiary referral center in the San Francisco Bay Area using participant data from the National Lung Screening Trial (NLST) who were enrolled between 2002 and 2004 and followed up for up to 7 years as the primary cohort and patient data from Stanford Healthcare (SHC) for diagnoses between 2009 and 2019 and followed up for up to 13 years as the validation cohort. Participants from NLST with de novo metastatic or distant recurrent NSCLC diagnoses were included. Data were analyzed from January 2021 to March 2023.

Exposures

De novo stage IV vs distant recurrent metastatic disease.

Main Outcomes and Measures

OS after diagnosis of metastatic disease.

Results

The NLST and SHC cohort consisted of 660 and 180 participants, respectively (411 men [62.3%] vs 109 men [60.6%], 602 White participants [91.2%] vs 111 White participants [61.7%], and mean [SD] age of 66.8 [5.5] vs 71.4 [7.9] years at metastasis, respectively). Patients with distant recurrence showed significantly better OS than patients with de novo metastasis (adjusted hazard ratio [aHR], 0.72; 95% CI, 0.60-0.87; P < .001) in NLST, which was replicated in SHC (aHR, 0.64; 95% CI, 0.43-0.96; P = .03). In SHC, patients with de novo metastasis more frequently progressed to the bone (63 patients with de novo metastasis [52.5%] vs 19 patients with distant recurrence [31.7%]) or pleura (40 patients with de novo metastasis [33.3%] vs 8 patients with distant recurrence [13.3%]) than patients with distant recurrence and were primarily detected through symptoms (102 patients [85.0%]) as compared with posttreatment surveillance (47 patients [78.3%]) in the latter. The main finding remained consistent after further adjusting for metastasis sites and detection methods.

Conclusions and Relevance

In this cohort study, patients with distant recurrent NSCLC had significantly better OS than those with de novo disease, and the latter group was associated with characteristics that may affect overall survival. This finding can help inform future clinical trial designs to ensure a balance for baseline patient characteristics.

Metal-Organic Framework Membrane Hybridized with Graphitic Materials for Gas Separation

Metal-organic frameworks (MOFs) are an exceptional class of crystalline materials that have been extensively used to fabricate membranes for various applications such as gas separation, ion transport, and desalination due to their well-defined pore structure, chemical features, and simple synthesis process. The incorporation of graphitic carbon materials in MOFs has garnered significant attention as it can provide abundant nucleation sites and modulate gas transport by influencing the orientation or rigidity of MOF crystals without changing their porous structure. This review insights of previous studies utilizing graphene, graphene oxide, carbon nanotubes, and graphene nanoribbons for MOF-based gas separation membranes, particularly focusing on polycrystalline MOF membrane hybridization with graphitic materials. We also briefly discuss the use of carbon/MOF hybrid materials for preparing mixed matrix membranes.

Lipase-catalyzed preparation of deacidified Buah Merah (Pandanus conoideus) oil

Buah Merah oil (BMO) is unrefined edible oil containing a high level of free fatty acids (FFA; ∼30% w/w). This study was aimed at preparing deacidified BMO from BMO via lipase-catalyzed esterification of FFA in BMO with added glycerol, using Duolite A568-immobilized Eversa Transform 2.0 (Thermomyces lanuginosus lipase) as biocatalyst. BMO containing 2.4% w/w FFA and 94.6% w/w triacylglycerol was obtained under optimal reaction conditions (temperature, 70°C; FFA-to-glycerol molar ratio, 3:1; enzyme loading based on the protein quantity, 3.75 mg/g BMO, and reaction time, 48 h). No significant difference was found in the contents of β-carotene, tocopherols, and phytosterols between raw and deacidified BMO. The induction period of oxidation was significantly longer in deacidified BMO (16.37 h) than in raw BMO (0.03 h). These results suggest that deacidified BMO could be enzymatically prepared without the loss of health-beneficial minor components while enhancing the oxidative stability. PRACTICAL APPLICATION: Although BMO has recently received much attention for its potential biological activities, the commercial use of BMO as a healthy oil has been limited due to its high FFA content. Unlike conventional alkali and steam refining, enzymatic deacidification of BMO employed in this study might help the commercialization of BMO, because this procedure enables the improvement of oil yield and the retaining of health-beneficial minor components.

Influence of Humidity and Heating Rate on the Continuous ZIF Coating during Hydrothermal Growth

Zeolitic imidazolate frameworks (ZIFs) have potential for various gas and ion separations due to their well-defined pore structure and relatively easy fabrication process compared to other metal-organic frameworks and zeolites. As a result, many reports have focused on preparing polycrystalline and continuous ZIF layers on porous supports with good separation performance in various target gases, such as hydrogen extraction and propane/propylene separation. To utilize the separation properties in industry, membrane is required to be prepared in large scale with high reproducibility. In this study, we investigated how humidity and chamber temperature influence the structure of a ZIF-8 layer prepared by the hydrothermal method. Many synthesis conditions can affect the morphology of polycrystalline ZIF membranes, and previous studies have mainly focused on reaction solutions, such as precursor molar ratio, concentration, temperature, and growth time. On the other hand, we found that the humidity of the chamber and the heating rate of the solution also lead to dramatic changes in the morphology of ZIF membranes. To analyze the trend between humidity and chamber temperature, we set up the chamber temperature (ranging from 50 °C to 70 °C) and relative humidity (ranging from 20% to 100%) using a thermo-hygrostat chamber. We found that as the chamber temperature increased, ZIF-8 preferentially grew into particles rather than forming a continuous polycrystalline layer. By measuring the temperature of the reacting solution based on chamber humidity, we discovered that the heating rate of the reacting solution varied with humidity, even at the same chamber temperature. At a higher humidity, the thermal energy transfer was accelerated as the water vapor delivered more energy to the reacting solution. Therefore, a continuous ZIF-8 layer could be formed more easily at low humidity ranges (ranging from 20% to 40%), while micron ZIF-8 particles were synthesized at a high heating rate. Similarly, under higher temperatures (above 50 °C), the thermal energy transfer was increased, leading to sporadic crystal growth. The observed results were obtained with a controlled molar ratio, in which zinc nitrate hexahydrate and 2-MIM were dissolved in DI water at a molar ratio of 1:45. While the results are limited to these specific growth conditions, our study suggests that controlling the heating rate of the reaction solution is critical for preparing a continuous and large-area ZIF-8 layer, particularly for the future scale-up of ZIF-8 membranes. Additionally, humidity is an important factor in forming the ZIF-8 layer, as the heating rate of the reaction solution can vary even at the same chamber temperature. Further research related to humidity will be necessary for the development of large-area ZIF-8 membranes.

Abstract P055: Risk factors for second primary lung cancer among breast cancer survivors

Introduction: Breast cancer is the most common cancer in women in the U.S. As survival in breast cancer has improved, one of the key clinical problems in breast cancer survivors is the increased risk of second cancers. Over half (55%) of breast cancer survivors die from second cancers, of which lung cancer (i.e., second primary lung cancer [SPLC]) is the most frequent type. While smoking and radiotherapy have been identified as the risk factors for SPLC among breast cancer survivors, other potential factors (e.g., comorbidity, and medication) have been underexamined. In addition, women in general have shown higher susceptibility to smoking-induced lung cancer than men, suggesting the potential involvement of hormonal factors; however, the effect of hormone replacement therapy (HRT) on lung cancer risk has been controversial and has never been examined among breast cancer survivors. We aimed to examine the factors associated with SPLC risk among breast cancer survivors, focusing on the effect of HRT and its interaction with smoking. We also explored the potential of tailored risk-based management of SPLC for breast cancer survivors. Methods: We identified 5,552 patients diagnosed with breast cancer in 1993-2014 from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. SPLC was defined as a newly diagnosed lung cancer after 6 months from the time of breast cancer diagnosis. We applied multivariable cause-specific Cox regression to identify new factors associated with SPLC risk, adjusting for multiple testing using the Bonferroni method (P&lt;0.01). We developed a prediction model to predict a 5-year risk of SPLC among breast cancer survivors that included both ever- and never-smokers and evaluated the predictive accuracy vs. a well-established lung cancer risk model, PLCOm2012, that was developed for a cancer-free population who ever smoked. Results: Of 5,552 patients, 89 (1.6%) developed SPLC over 102,545 person-years. Several factors measured at baseline in PLCO were significantly associated with SPLC risk among breast cancer survivors, including liver comorbidity (Hazard Ratio [HR] 3.28; P&lt;.001), prior history of other cancer (HR 2.02; P=0.01), and regular use of ibuprofen (HR 0.52; P=0.01). In addition, ever-use of HRT was associated with a 51% reduction in SPLC risk (HR 0.49; P=0.001). The effect of active smoking on SPLC risk vs non-active smoking (HR 7.09; P&lt;.001) was validated in PLCO. Notably, the effect of active smoking was intensified among ever-HRT users (HR=10.5; P&lt;.001) vs. never-HRT users (HR 4.1; P&lt;.001), thus showing a significant interaction (Pinteraction=0.003). The prediction model for SPLC risk was validated through bootstrap and demonstrated higher discrimination (AUC 0.83) vs. the PLCOm2012 model (AUC 0.79). Conclusions: In a large prospective cohort of breast cancer survivors, smoking and HRT use showed a significant interaction on SPLC risk. The prediction model for SPLC could identify high-risk survivors for SPLC for tailored surveillance to improve the management of breast cancer survivors.

Citation Format: Eunji Choi, Justin Lee, Julie T. Wu, Heather A. Wakelee, Lidia Schapira, Allison W. Kurian, Summer S. Han. Risk factors for second primary lung cancer among breast cancer survivors. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P055.

Estimating Age-Specific Mean Sojourn Time of Breast Cancer and Sensitivity of Mammographic Screening by Breast Density among Korean Women

PURPOSE

High breast cancer incidence and dense breast prevalence among women in forties are specific to Asian. This study examined the natural history of breast cancer among Korean women.

MATERIALS AND METHODS

We applied a three-state Markov model (i.e., healthy, preclinical, and clinical state) to fit the natural history of breast cancer to data in the Korean National Cancer Screening Program. Breast cancer was ascertained by linkage to the Korean Central Cancer Registry. Disease-progression rates (i.e., transition rates between three states), mean sojourn time (MST) and mammographic sensitivity were estimated across 10-year age groups and levels of breast density determined by the Breast Imaging, Reporting and Data System.

RESULTS

Overall prevalence of dense breast was 53.9%. Transition rate from healthy to preclinical state, indicating the preclinical incidence of breast cancer, was higher among women in forties (0.0019; 95% confidence interval [CI], 0.0017 to 0.0021) and fifties (0.0020; 95% CI, 0.0017 to 0.0022), than women in sixties (0.0014; 95% CI, 0.0012 to 0.0017). The MSTs, in which the tumor is asymptomatic but detectable by screening, were also fastest among younger age groups, estimated as 1.98 years (95% CI, 1.67 to 2.33), 2.49 years (95% CI, 1.92 to 3.22), and 3.07 years (95% CI, 2.11 to 4.46) for women in forties, fifties, and sixties, respectively. Having dense breasts increased the likelihood of the preclinical cancer risk (1.96 to 2.35 times) and decreased the duration of MST (1.53 to 2.02 times).

CONCLUSION

This study estimated Korean-specific natural history parameters of breast cancer that would be utilized for establishing optimal screening strategies in countries with higher dense breast prevalence.

Abstract P068: A hybrid modelling approach for abstracting CT imaging indications by integrating natural language processing from radiology reports with structured data from electronic health records

Background: Real-world evidence (RWE) studies for surveillance patterns following lung cancer (LC) diagnosis can inform optimizing recommendations on surveillance and practice. One major obstacle in RWE studies for LC surveillance is the lack of radiologic imaging indication for surveillance vs. other reasons (e.g., symptoms). To enable RWE studies for surveillance to detect second primary lung cancer among LC survivors, we developed a hybrid modelling approach that integrates structured data from electronic health records (EHRs) with natural language processing (NLP) from radiology reports for abstracting computed tomography (CT) imaging indications in LC survivors. Methods: We manually reviewed and abstracted CT imaging indications, i.e., surveillance vs. others (e.g., symptoms and metastatic disease follow-up) to create a gold standard from 200 randomly selected radiology reports among 1,952 LC patients (i) who were diagnosed in 2000-2017 at Stanford Health Care (SHC) and (ii) survived ≧5 years after the diagnosis. We abstracted medically relevant key-phrases using the part-of-speech grammar and PageRank algorithms. Hierarchical clustering identified context-specific key-phrase clusters as follows: “surveillance”, “stable”, “nodule”, “symptom”, and “metastasis”. The text-based radiology reports were vectorized to generate NLP features using phrase occurrence frequencies. The structured variables from EHRs included: (i) diagnosis of lung diseases or chest symptoms in previous 6 months, (ii) ordering provider-type (oncology vs. others [e.g. emergency and internal medicine]), and (iii) time from previous CT (≧6 months). A hybrid model was then fitted using logistic regression including both structured and NLP features and validated using a 10-fold cross-validation. The model’s performance was compared to those solely based on NLP or structured data. Results: The dataset of 200 radiology reports included 141 LC survivors (49% White, 72% adenocarcinoma). The proposed hybrid model showed high discrimination (AUC: 0.92), outperforming those based solely on NLP (AUC: 0.88) or structured data (AUC: 0.87). The proposed model demonstrated higher sensitivity (SN: 0.73) and specificity (SP: 0.96) versus those solely based on NLP (SN: 0.53; SP: 0.96) or structured data (SN: 0.53; SP: 0.90). The hybrid model showed that the following variables were positively associated with a higher likelihood that the given CT imaging indication is “surveillance”: (i) a longer time interval (≧6 months) from the previous CT (odds ratio [OR]: 4.63; p=0.01) and key-phrases of (ii) “nodule” (OR: 1.55; p=0.004) and (iii) “stable” (OR: 1.37; p=0.03). On the other hand, the following were negatively associated with the likelihood of surveillance: the key-phrases of “symptom” (OR: 0.17; p=0.02) and “metastasis” (OR: 0.26; p=0.02). Conclusion: A hybrid modeling approach combining text-based NLP and structured EHRs has the potential for abstracting CT imaging indications for LC surveillance. Future directions include validation using other EHR systems and extension using larger data.

Citation Format: Aparajita Khan, Julie Wu, Eunji Choi, Anna Graber-Naidich, Solomon Henry, Heather A. Wakelee, Allison W. Kurian, Su-Ying Liang, Ann Leung, Curtis Langlotz, Leah M. Backhus, Summer S. Han. A hybrid modelling approach for abstracting CT imaging indications by integrating natural language processing from radiology reports with structured data from electronic health records. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P068.

Predictive Model to Guide Brain Magnetic Resonance Imaging Surveillance in Patients With Metastatic Lung Cancer: Impact on Real-World Outcomes

PURPOSE

Brain metastasis is common in lung cancer, and treatment of brain metastasis can lead to significant morbidity. Although early detection of brain metastasis may improve outcomes, there are no prediction models to identify high-risk patients for brain magnetic resonance imaging (MRI) surveillance. Our goal is to develop a machine learning-based clinicogenomic prediction model to estimate patient-level brain metastasis risk.

METHODS

A penalized regression competing risk model was developed using 330 patients diagnosed with lung cancer between January 2014 and June 2019 and followed through June 2021 at Stanford HealthCare. The main outcome was time from the diagnosis of distant metastatic disease to the development of brain metastasis, death, or censoring.

RESULTS

Among the 330 patients, 84 (25%) developed brain metastasis over 627 person-years, with a 1-year cumulative brain metastasis incidence of 10.2% (95% CI, 6.8 to 13.6). Features selected for model inclusion were histology, cancer stage, age at diagnosis, primary site, and RB1 and ALK alterations. The prediction model yielded high discrimination (area under the curve 0.75). When the cohort was stratified by risk using a 1-year risk threshold of > 14.2% (85th percentile), the high-risk group had increased 1-year cumulative incidence of brain metastasis versus the low-risk group (30.8% v 6.1%, P < .01). Of 48 high-risk patients, 24 developed brain metastasis, and of these, 12 patients had brain metastasis detected more than 7 months after last brain MRI. Patients who missed this 7-month window had larger brain metastases (58% v 33% largest diameter > 10 mm; odds ratio, 2.80, CI, 0.51 to 13) versus those who had MRIs more frequently.

CONCLUSION

The proposed model can identify high-risk patients, who may benefit from more intensive brain MRI surveillance to reduce morbidity of subsequent treatment through early detection.

Impact of mental disease on the risk of atrial fibrillation in patients with diabetes mellitus: a nationwide population-based study

Background

Diabetes mellitus (DM) is known to increase the risk of mental disorders, which increases the health care burden in these patients. Also, DM is one of the risk factors leading to atrial fibrillation (AF), and the presence of concomitant AF and DM adds to the increased risks of stroke and death. It is uncertain whether mental disease is an independent risk factor of incident AF in patients with DM.

Purpose

To investigate whether diabetic patients with mental disease have an increased risk of AF.

Methods

Using the Korea National Health Insurance Service database, we enrolled 2,512,690 patients diagnosed with DM without AF between 2009 and 2021. Newly diagnosed AF was identified during the follow-up period. We compared the risk of AF between patients with mental disease and those without.

Results

Among the total population, 828,929 (32.99%; mean age 61.58±11.28; 56.71% female) patients were diagnosed with mental diseases (Figure 1). Anxiety (564,786 patients, 68.13%) was the most common mental disease, while depression was the second most common (313,773 patients, 37.85%). Diabetic patients with mental diseases had a higher percentage of women, hypertension, dyslipidemia, chronic kidney failure, congestive heart failure, obstructive sleep apnea, and thyroid disease. During a median 7.0 years (IQR 5.93–8.07) follow-up, 34,523 were diagnosed new-onset AF (4.66 per 1,000 person-year). In multivariate analysis, diabetic patients with mental disorders showed a higher risk of new-onset AF (HR 1.19; 95% CI 1.17–1.21; p-value &lt;0.0001) (Figure 2). Among mental diseases, depression, insomnia, and anxiety were associated with increased risks of new-onset AF (HR 1.15; 95% CI 1.12–1.17; HR 1.15; 95% CI 1.13–1.18; and HR 1.19; 95% CI, 1.67–1.21; all p-value &lt;0.0001, respectively), whereas bipolar disorder and schizophrenia showed non-statistically significant trends (due to small numbers). Subgroup analyses showed that younger age had significant interactions with depression, insomnia, and anxiety.

Conclusion

Mental diseases, especially depression, insomnia, and anxiety, showed an increased risk of AF in patients with DM. Awareness and prompt diagnosis and management of AF would be necessary for these high-risk populations at risk of incident AF.

Funding Acknowledgement

Type of funding sources: None.

External validation of the biomarker based ABCD score in atrial fibrillation patients with a non gender CHA2DS2 VASc score 0 to 1, A Korean multicenter retrospective cohort

Background

Patients with low to intermediate risk atrial fibrillation (AF), defined as non-gender CHA2DS2-VASc score of 0–1, are still at risk of stroke. This study verified the usefulness of ABCD score (Age [≥60 years], B-type natriuretic peptide [BNP] or N-terminal pro-BNP [≥300 pg/ml], Creatinine clearance [&lt;50 ml/min/1.73 m2], and Dimension of the left atrium [≥45 mm]) for stroke risk stratification in non-gender CHA2DS2-VASc score 0–1.

Methods

This multi-center cohort study retrospectively analyzed AF patients with non-gender CHA2DS2-VASc score 0–1. The primary endpoint was the incidence of stroke with or without anti-thrombotic treatment (ATT). An ABCD score was also validated.

Results

Overall, 2694 patients (56.3±9.5 years; female, 726 [26.9%]) were followed-up for 4.0±2.8 years. The overall stroke rate was 0.84/100 person-years (P-Y), stratified as follows: 0.46/100P-Y for an ABCD score 0; 1.02/100P-Y for an ABCD score≥1. The ABCD score was superior to the non-gender CHA2DS2-VASc score in stroke risk stratification (C-index=0.618, P=0.015; net reclassification improvement=0.576, P=0.040; integrated differential improvement=0.033, P=0.066). ATT was prescribed in 2353 patients (86.5%), and the stroke rate was significantly lower in patients receiving non-vitamin K antagonist oral anticoagulant (NOAC) therapy and an ABCD score≥1 than in those without ATT (0.44/100P-Y versus 1.55/100 P-Y; hazard ratio=0.26, 95% confidence interval 0.11–0.63, P=0.003).

Conclusion

The biomarker-based ABCD score demonstrated improved stroke risk stratification in AF patients with non-gender CHA2DS2-VASc score 0–1. Furthermore, NOAC with an ABCD score≥1 was associated with significantly lower stroke rate in AF patients with a non-gender CHA2DS2-VASc score 0–1.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Korean Disease Control and Prevention Agency

Insights from one thousand cloned dogs

Animal cloning has been popularized for more than two decades, since the birth of Dolly the Sheep 25 years ago in 1996. There has been an apparent waning of interest in cloning, evident by a reduced number of reports. Over 1500 dogs, representing approximately 20% of the American Kennel Club’s recognized breeds, have now been cloned, making the dog (Canis familiaris) one of the most successfully cloned mammals. Dogs have a unique relationship with humans, dating to prehistory, and a high degree of genome homology to humans. A number of phenotypic variations, rarely recorded in natural reproduction have been observed in in these more than 1000 clones. These observations differ between donors and their clones, and between clones from the same donor, indicating a non-genetic effect. These differences cannot be fully explained by current understandings but point to epigenetic and cellular reprograming effects of somatic cell nuclear transfer. Notably, some phenotypic variations have been reversed through further cloning. Here we summarize these observations and elaborate on the cloning procedure.

LAG-3xPD-L1 bispecific antibody potentiates antitumor responses of T cells through dendritic cell activation

Several preclinical studies demonstrate that antitumor efficacy of PD-1/PD-L1 blockade can be improved by combination with other checkpoint inhibitors. Lymphocyte-activation gene 3 (LAG-3) is an inhibitory checkpoint receptor involved in T cell exhaustion and tumor immune escape. Here, we describe ABL501, a bispecific antibody targeting LAG-3 and PD-L1 in modulating immune cell responses against tumors. ABL501 that efficiently inhibits both LAG-3 and PD-L1 pathways enhances the activation of effector CD4⁺ and CD8⁺ T cells with a higher degree than a combination of single anti-LAG-3 and anti-PD-L1. The augmented effector T cell responses by ABL501 resulted in mitigating regulatory T cell-mediated immunosuppression. Mechanistically, the simultaneous binding of ABL501 to LAG-3 and PD-L1 promotes DC activation and tumor cell conjugation with T cells that subsequently mounts effective CD8⁺T cell responses. ABL501 demonstrates its potent in vivo antitumor efficacy in a humanized xenograft model and with knock-in mice expressing human orthologs. The immune profiling analysis of peripheral blood reveals an increased abundance of LAG-3^hiPD-1^hi memory CD4⁺T cell subset in relapsed cholangiocarcinoma patients after gemcitabine plus cisplatin therapy, which are more responsive to ABL501. This study supports the clinical evaluation of ABL501 as a novel cancer immunotherapeutic, and a first-in-human trial has started (NCT05101109).

The Survival Impact of Second Primary Lung Cancer in Patients With Lung Cancer

BACKGROUND

Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC), but little is known about the survival impact of SPLC diagnosis.

METHODS

We analyzed data from 138 969 patients in the Surveillance, Epidemiology, and End Results (SEER), who were surgically treated for initial primary lung cancer (IPLC) in 1988-2013. Each patient was followed from the date of IPLC diagnosis to SPLC diagnosis (for those with SPLC) and last vital status through 2016. We performed multivariable Cox regression to evaluate the association between overall survival and SPLC diagnosis as a time-varying predictor. To investigate potential effect modification, we tested interaction between SPLC and IPLC stage. Using data from the Multiethnic Cohort Study (MEC) (n = 1540 IPLC patients with surgery), we evaluated the survival impact of SPLC by smoking status. All statistical tests were 2-sided.

RESULTS

A total of 12 115 (8.7%) patients developed SPLC in SEER over 700 421 person-years of follow-up. Compared with patients with single primary lung cancer, those with SPLC had statistically significantly reduced overall survival (hazard ratio [HR] = 2.12, 95% confidence interval [CI] = 2.06 to 2.17; P < .001). The effect of SPLC on reduced survival was more pronounced among patients with early stage IPLC vs advanced-stage IPLC (HR = 2.14, 95% CI = 2.08 to 2.20, vs HR = 1.43, 95% CI = 1.21 to 1.70, respectively; Pinteraction < .001). Analysis using MEC data showed that the effect of SPLC on reduced survival was statistically significantly larger among persons who actively smoked at initial diagnosis vs those who formerly or never smoked (HR = 2.31, 95% CI = 1.48 to 3.61, vs HR = 1.41, 95% CI = 0.98 to 2.03, respectively; Pinteraction = .04).

CONCLUSIONS

SPLC diagnosis is statistically significantly associated with decreased survival in SEER and MEC. Intensive surveillance targeting patients with early stage IPLC and active smoking at IPLC diagnosis may lead to a larger survival benefit.

Nosocomial outbreak of severe fever with thrombocytopenia syndrome among healthcare workers in a single hospital in Daegu, Korea: Nosocomial SFTS outbreak among healthcare workers

BACKGROUND

In August 2020, 17 healthcare workers (HCWs) were simultaneously diagnosed with severe fever with thrombocytopenia syndrome (SFTS) at a university hospital in Daegu, Republic of Korea.

METHODS

An epidemiologic investigation using questionnaires was conducted for all suspected HCWs who had viral infection symptoms or who had the possibility of exposure to the index patient.

RESULTS

A total of 17 HCWs infected with the SFTS virus (SFTSV) (28.8%) were identified among the 59 HCWs who had contact with the patient. Operating a bag valve mask during cardiopulmonary resuscitation (CPR) (OR 7.50, 95% CI 1.75-41.07), cardiac massage during CPR (OR 12.00, 95% CI 1.76-241.94), exposure to the patient's body fluids (OR 7.43, 95% CI 1.91-34.69), and shorter individual hospital work experience periods (OR 6.79, 95% CI 1.70-32.10) were significantly associated with SFTS infection in the univariate analysis. However, exposure to body fluids was found to be the only statistically significant risk factor when multivariate analysis was conducted (OR 6.27. 95% CI 1.23-42.81, p = 0.036).

CONCLUSIONS

This finding illustrates the importance of wearing appropriate personal protective equipment in treatment areas and when conducting any medical procedures, including CPR for patients with SFTS, and any procedure that involves potential exposure to body fluids.

Combined analysis of inorganic elements and sugars for the identification of red pepper powder containing undeclared ingredients

This study sought to identify adulterated red pepper powder (RPP) containing undeclared ingredients, such as salts, glucose, Monascus red pigments, and other plant ingredients (e.g., wheat flour, garlic powder, onion powder) using element and sugar analysis methods. Analytical data were obtained for 66 samples of authentic RPP and 12 samples of adulterated RPP. The variables selected to identify the authenticity of RPP include Na, Cl, K, maltohexaose, and maltoheptaose, which partly or totally originate from RPP, salts, or Monascus red pigments. All the 12 samples of commercial seasoned RPP used as models of adulterated RPP and all the 20 blind samples containing ≥10% (w/w) of commercial seasoned RPP were correctly identified by applying the range of the five variables found for the authentic RPP samples. Our findings suggest that combined analyses of the above five constituents could be used to identify adulterated RPP containing undeclared ingredients. PRACTICAL APPLICATION: Adulteration of high-priced spice products, including red pepper powder (RPP), has increasingly become a public concern worldwide as it endangers consumer health and represents economic fraud. This study provides analytical methods that can accurately determine the authenticity of RPP. They would become effective means for protecting producers and suppliers against unfair competition and consumers against health threats.

Barley Sprout Water Extract and Saponarin Mitigate Triacylglycerol Accumulation in 3T3-L1 Adipocytes

The mechanisms of action responsible for the reported hypolipidemic activity of barley sprouts have yet to be elucidated. The objective of this study was to compare the content of saponarin (the sole flavonoid present in barley sprout leaves), hypolipidemic activity between barley sprout water extract (BSW) and barley sprout ethanol extract (BSE), and the associated relevance to hypolipidemic activity in 3T3-L1 preadipocytes. BSW elicited superior antiadipogenic effects when compared with BSE in MDI mixture [IBMX 0.5 mM + dexamethasone 1 μM + insulin 1 μg/mL]-treated 3T3-L1 preadipocytes. BSW attenuated MDI-mediated triacylglycerol (TAG) accumulation by inhibiting fatty acid synthase (FAS). FAS protein expression was markedly and dose dependently attenuated by BSW, with higher doses suppressing expression to a level equivalent to the controls. BSW also significantly attenuated MDI-mediated increases in the expression of genes involved in TAG synthesis as well as FAS in 3T3-L1 preadipocytes. High-performance liquid chromatography analysis indicated that BSW contains more than four times more saponarin than BSE. Further investigation of saponarin-mediated hypotriacylglycerolemic activity and related gene expression revealed that saponarin significantly inhibited TAG accumulation, which was attributed to reductions in TAG synthesis-related gene expression. Taken together, these findings provide a basis for further development of barley sprout extract for functional health food purposes.

High-aspect ratio zeolitic imidazolate framework (ZIF) nanoplates for hydrocarbon separation membranes

Metal-organic frameworks with high aspect ratios have the potential to yield high-performance gas separation membranes. We demonstrate the scalable synthesis of high–aspect ratio zeolitic imidazolate framework (ZIF)–8 nanoplates via a direct template conversion method in which high aspect ratio–layered Zn hydroxide sheets [Zn₅(NO₃)₂(OH)₈] were used as the sacrificial precursor. Successful phase conversion occurs as a result of the collaboration of low template stability and delayed delivery of 2-methylimidazole in weakly interacting solvents, particularly using acetone. When the ZIF-8 nanoplates with an average aspect ratio of 20 were shear aligned in the 6FDA-DAM polymer matrix by bar coating, the separation performance for propylene/propane far surpassed that of the previously reported mixed matrix and polymeric membranes, showing a propylene permeability of 164 Barrer and selectivity of 33.4 at 40 weight % loadings.

OUP accepted manuscript

Background

Methods

Results

Conclusions

Abstract PO-130: Disparities in risk of second primary lung cancer among lung cancer patients in the United States

Introduction: Lung cancer is the leading cause of cancer death in the U.S. Despite recent survival improvements, racial and socioeconomic disparities still exist in lung cancer incidence and survival. Furthermore, recent studies showed that lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). While racial and socioeconomic disparities have long been examined for lung cancer survival and incidence, little is known about their impacts on SPLC risk among lung cancer survivors. This study evaluated the disparities in SPLC incidence by calculating the standardized incidence ratio (SIR) of the observed SPLC incidence versus the expected incidence of initial primary lung cancer (IPLC) across different socioeconomic, acculturation, and smoking-related factors using county-level data obtained from the Surveillance, Epidemiology, and End Results Program (SEER). Methods: We identified 158,018 patients diagnosed with IPLC between 2000 and 2013 in SEER. SPLC was defined as a newly developed primary lung cancer after 2 years from IPLC diagnosis and was followed through 2018. The SIR was calculated as the ratio of the observed SPLC incidence versus the expected incidence of IPLC in the general population across different factors. Indicators of socioeconomic status, acculturation factors, and smoking prevalence in SEER were derived from county-level data using the American Community Survey and the Behavioral Risk Factor Surveillance System (BRFSS). The quintiles of these indicators were created using the data obtained across all 3,142 valid U.S. counties. We applied the Pearson's chi-squared test to evaluate the difference in SIRs across quintiles of the indicators we created, applying a statistical significance of α &lt; 0.005 after adjusting for multiple testing. Results: Among 158,018 IPLC patients, 10,650 (6.7%) developed SPLC over 626,853 person-years. The incidence of SPLC was 6 times higher than the IPLC incidence in the general population, with an overall SIR of 6.2 (95% Confidence Interval (CI): 6.09-6.32). Notably, the SIR, i.e., the ratio between the SPLC incidence and the IPLC incidence, was significantly higher among individuals who live in counties with the lowest quintile of median family income (&lt;$51,770) versus the highest quintile (&gt;$74,331) (SIR 7.18 versus 6.10, P&lt;1 × 10−6). Furthermore, the ratio between the SPLC versus the IPLC incidence was highest (SIR 8.01, CI: 7.36-8.71) among those who live in counties with the highest quintile of smoking prevalence (&gt;29.6%) versus SIR of 5.77 (CI: 5.63-5.91) with the lowest quintile of smoking prevalence (&lt;20.4%) (P=3.4 × 10−3). Race/ethnicity and acculturation factors, including immigration status, did not achieve statistical significance. Discussion: Significant disparities exist in SPLC incidence among lung cancer survivors who live in areas with a low median family income and high smoking prevalence. Targeted SPLC surveillance for lung cancer survivors from an underserved population would be needed to reduce the existing disparities.

Citation Format: Eunji Choi, Sophia J. Luo, Jacqueline V. Aredo, Joel W. Neal, Leah M. Backhus, Heather A. Wakelee, Summer S. Han. Disparities in risk of second primary lung cancer among lung cancer patients in the United States [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-130.

Distinguishing Korean and Chinese red pepper powder using inductively coupled plasma and X-ray fluorescence-based analysis

This study aimed to distinguish between Korean and Chinese red pepper powder (RPP) using inorganic elemental analysis data combined with orthogonal partial least squares-discriminant analysis (OPLS-DA). Elemental concentrations were obtained for 31 Korean and 31 Chinese RPP samples that were collected in Korea. Energy dispersive X-ray fluorescence spectroscopy detected 11 elements in these samples. Rb and Cl concentrations were selected as the variables which best allowed distinguishing between Korean and Chinese RPP using an S-plot from OPLS-DA. Rb and Cl concentrations in the Korean RPP samples were ≤ 1.6 mg/100 g (measured by inductively coupled plasma-optical emission spectroscopy) and ≤ 215 mg/100 g, respectively. A blind trial demonstrated that Korean RPP containing ≥ 50 g/100 g of Chinese RPP could be identified by applying predetermined ranges of Rb and Cl concentrations, suggesting that analysis of these two elements is a possible approach to distinguish between Korean and Chinese RPP.

Carotid Plaque Composition Assessed by CT Predicts Subsequent Cardiovascular Events among Subjects with Carotid Stenosis

BACKGROUND AND PURPOSE

Currently, the characteristics of carotid plaques are considered important factors for identifying subjects at high risk of stroke. This study aimed to test the hypothesis that carotid plaque composition assessed by CTA is associated with an increased risk of future major adverse cardiovascular events among asymptomatic subjects with moderate-to-severe carotid artery stenosis.

MATERIALS AND METHODS

This single-center, retrospective cohort study included 194 carotid plaques from 176 asymptomatic subjects with moderate-to-severe carotid artery stenosis. The association of CTA-determined plaque composition with the risk of subsequent adverse cardiovascular events was analyzed.

RESULTS

During a median follow-up of 41 months, the adverse cardiovascular event incidence among 194 carotid plaques was 19.6%. There were significant differences in plaque Hounsfield units (P < .001) and spotty calcium presence (P < .001) between carotid plaques from subjects with and without subsequent adverse cardiovascular events. Multivariable analysis revealed carotid plaque Hounsfield unit density (P < .001) and spotty calcium (P < .001) as independent predictors of subsequent adverse cardiovascular events. In association with moderate carotid artery stenosis, the plaque Hounsfield unit values were significantly lower among carotid plaques from subjects who experienced subsequent adverse cardiovascular events (P = .002), strokes (P = .01), and cardiovascular deaths (P = .04); the presence of spotty calcium was significantly associated with the occurrence of adverse cardiovascular events (P = .001), acute coronary syndrome (P = .01), and cardiovascular death (P = .04).

CONCLUSIONS

Carotid plaque Hounsfield unit density and spotty calcium were independent predictors of a greater risk of adverse cardiovascular event occurrence.

The role of intraoperative frozen section analysis in joint arthroplasty with CD66b immunohistochemical staining

The preoperative diagnosis of infection during joint arthroplasty is important for clinical management. However, the evaluation of polymorphonuclear leukocytes (PMNs) during frozen section analysis is sometimes difficult due to frozen artifacts. In the present study, we sought to investigate the utility of intraoperative fresh frozen section (FFS) examination for diagnosis of infection and to evaluate whether the neutrophil-specific surface marker CD66b helps to improve the diagnostic accuracy of infection. A consecutive series of 65 original frozen sections at the time of resection arthroplasty was retrospectively reviewed compared with corresponding permanent sections. The presence of PMNs was determined using intraoperative FFS and permanent sections. Furthermore, CD66b staining was performed to identify PMNs clearly. The ratio of male to female patients was 21:42. The mean age was 70 years. Postoperatively, 25 of 65 cases were histologically diagnosed with infection (25/65; 39%). The sensitivity and specificity of intraoperative FFS relative to permanent section histology were 100% (25/25) and 95% (38/40), respectively. Among 40 patients without infection, two showed false-positive results during intraoperative FFS diagnosis (2/40, 5%). In addition, on CD66b staining, six cases (9%) experienced changes in results, which altered the sensitivity and specificity of intraoperative FFS compared with permanent histology only to 87% and 87%, respectively. In conclusion, the diagnostic performance of intraoperative FFS is high and comparable to yields of permanent section histology. Therefore, intraoperative FFS is highly suitable diagnostic method for detection of infection during joint arthroplasty. And CD66b immunostaining facilitates delicate identification of PMNs, especially in equivocal cases.

Smoking Cessation After Lung Cancer Diagnosis and the Risk of Second Primary Lung Cancer: The Multiethnic Cohort Study

Background

Smoking cessation reduces lung cancer mortality. However, little is known about whether diagnosis of lung cancer impacts changes in smoking behaviors. Furthermore, the effects of smoking cessation on the risk of second primary lung cancer (SPLC) have not been established yet. This study aims to examine smoking behavior changes after initial primary lung cancer (IPLC) diagnosis and estimate the effect of smoking cessation on SPLC risk following IPLC diagnosis.

Methods

The study cohort consisted of 986 participants in the Multiethnic Cohort Study who were free of lung cancer and active smokers at baseline (1993-1996), provided 10-year follow-up smoking data (2003-2008), and were diagnosed with IPLC in 1993-2017. The primary outcome was a change in smoking status from “current” at baseline to “former” at 10-year follow-up (ie, smoking cessation), analyzed using logistic regression. The second outcome was SPLC incidence after smoking cessation, estimated using cause-specific Cox regression. All statistical tests were 2-sided.

Results

Among 986 current smokers at baseline, 51.1% reported smoking cessation at 10-year follow-up. The smoking cessation rate was statistically significantly higher (80.6%) for those diagnosed with IPLC between baseline and 10-year follow-up vs those without IPLC diagnosis (45.4%) during the 10-year period (adjusted odds ratio = 5.12, 95% confidence interval [CI] = 3.38 to 7.98; P < .001). Incidence of SPLC was statistically significantly lower among the 504 participants who reported smoking cessation at follow-up compared with those without smoking cessation (adjusted hazard ratio = 0.31, 95% CI = 0.14 to 0.67; P = .003).

Conclusion

Lung cancer diagnosis has a statistically significant impact on smoking cessation. Quitting smoking after IPLC diagnosis may reduce the risk of developing a subsequent malignancy in the lungs.

Trends in the Performance of the Korean National Cancer Screening Program for Gastric Cancer from 2007 to 2016

Purpose

The Korean National Cancer Screening Program (KNCSP) has implemented two screening methods for gastric cancer— upper gastrointestinal series (UGIS) and endoscopy—for Koreans aged ≥ 40 years. We aimed to assess performance trends for both screening methods.

Materials and Methods

The KNCSP database was used to evaluate individuals who underwent screening from 2007 to 2016. The final gastric cancer diagnosis was ascertained by linking with the Korean Central Cancer Registry. We conducted a prospective, cross-sectional analysis to estimate performance indicators of gastric cancer screening by UGIS and endoscopy, stratified by sociodemographic factors.

Results

We found that screening rates for gastric cancer increased from 28% to 51.7% between 2007 and 2016, and that the rate of endoscopy use for gastric cancer screening increased sharply. Cancer detection rates (CDR) of UGIS and endoscopy were 0.41 and 2.25 per 1,000 screens in 2007–2008 and 0.26 and 1.99 in 2015–2016, respectively. Interval cancer rates (ICR) per 1,000 negative screenings were 1.33 (2007–2008) and 1.21 (2015–2016) for UGIS and 1.14 (2007–2008) and 0.88 (2015–2016) for endoscopy. The sensitivity of UGIS decreased from 23.6% (2007–2008) to 17.6% (2015–2016), whereas that of endoscopy increased from 66.4% (2007–2008) to 69.3% (2015–2016). Specificity was maintained at > 99% for both methods over the study period.

Conclusion

The use of endoscopy for gastric cancer screening within the KNCSP has increased. Endoscopy has higher CDR, sensitivity, and specificity, and lower ICR estimates than does UGIS.