Automatic recognition of protein subcellular location patterns in single cells from immunofluorescence images based on deep learning.

With the improvement of single-cell measurement techniques, there is a growing awareness that individual differences exist among cells, and protein expression distribution can vary across cells in the same tissue or cell line. Pinpointing the protein subcellular locations in single cells is crucial for mapping functional specificity of proteins and studying related diseases. Currently, research about single-cell protein location is still in its infancy, and most studies and databases do not annotate proteins at the cell level. For example, in the human protein atlas database, an immunofluorescence image stained for a particular protein shows multiple cells, but the subcellular location annotation is for the whole image, ignoring intercellular difference. In this study, we used large-scale immunofluorescence images and image-level subcellular locations to develop a deep-learning-based pipeline that could accurately recognize protein localizations in single cells. The pipeline consisted of two deep learning models, i.e. an image-based model and a cell-based model. The former used a multi-instance learning framework to comprehensively model protein distribution in multiple cells in each image, and could give both image-level and cell-level predictions. The latter firstly used clustering and heuristics algorithms to assign pseudo-labels of subcellular locations to the segmented cell images, and then used the pseudo-labels to train a classification model. Finally, the image-based model was fused with the cell-based model at the decision level to obtain the final ensemble model for single-cell prediction. Our experimental results showed that the ensemble model could achieve higher accuracy and robustness on independent test sets than state-of-the-art methods.

Bone-Targeted Biomimetic Nanogels Re-Establish Osteoblast/Osteoclast Balance to Treat Postmenopausal Osteoporosis.

Insufficient bone formation and excessive bone resorption caused by estrogen deficiency are the major factors resulting in the incidence of postmenopausal osteoporosis (PMOP). The existing drugs usually fail to re-establish the osteoblast/osteoclast balance from both sides and generate side-effects owing to the lack of bone-targeting ability. Here, engineered cell-membrane-coated nanogels PNG@mR&C capable of scavenging receptor activator of nuclear factor-κB ligand (RANKL) and responsively releasing therapeutic PTH 1-34 in the bone microenvironment are prepared from RANK and CXCR4 overexpressed bone mesenchymal stem cell (BMSC) membrane-coated chitosan biopolymers. The CXCR4 on the coated-membranes confer bone-targeting ability, and abundant RANK effectively absorb RANKL to inhibit osteoclastogenesis. Meanwhile, the release of PTH 1-34 triggered by osteoclast-mediated acid microenvironment promote osteogenesis. In addition, the dose and frequency are greatly reduced due to the smart release property, prolonged circulation time, and bone-specific accumulation. Thus, PNG@mR&C exhibits satisfactory therapeutic effects in the ovariectomized (OVX) mouse model. This study provides a new paradigm re-establishing the bone metabolic homeostasis from multitargets and shows great promise for the treatment of PMOP.

Learning protein subcellular localization multi-view patterns from heterogeneous data of imaging, sequence and networks.

Location proteomics seeks to provide automated high-resolution descriptions of protein location patterns within cells. Many efforts have been undertaken in location proteomics over the past decades, thereby producing plenty of automated predictors for protein subcellular localization. However, most of these predictors are trained solely from high-throughput microscopic images or protein amino acid sequences alone. Unifying heterogeneous protein data sources has yet to be exploited. In this paper, we present a pipeline called sequence, image, network-based protein subcellular locator (SIN-Locator) that constructs a multi-view description of proteins by integrating multiple data types including images of protein expression in cells or tissues, amino acid sequences and protein-protein interaction networks, to classify the patterns of protein subcellular locations. Proteins were encoded by both handcrafted features and deep learning features, and multiple combining methods were implemented. Our experimental results indicated that optimal integrations can considerately enhance the classification accuracy, and the utility of SIN-Locator has been demonstrated through applying to new released proteins in the human protein atlas. Furthermore, we also investigate the contribution of different data sources and influence of partial absence of data. This work is anticipated to provide clues for reconciliation and combination of multi-source data for protein location analysis.

Fluoride impairs vascular smooth muscle A7R5 cell lines via disrupting amino acids metabolism.

Given the insidious and high-fatality nature of cardiovascular diseases (CVDs), the emergence of fluoride as a newly identified risk factor demands serious consideration alongside traditional risk factors. While vascular smooth muscle cells (VSMCs) play a pivotal role in the progression of CVDs, the toxicological impact of fluoride on VSMCs remains largely uncharted. In this study, we constructed fluorosis model in SD rats and A7R5 aortic smooth muscle cell lines to confirm fluoride impaired VSMCs. Fluoride aggravated the pathological damage of rat aorta in vivo. Then A7R5 were exposed to fluoride with concentration ranging from 0 to 1200 µmol/L over a 24-h period, revealing a dose-dependent inhibition of cell proliferation and migration. The further metabolomic analysis showed alterations in metabolite profiles induced by fluoride exposure, notably decreasing organic acids and lipid molecules level. Additionally, gene network analysis underscored the frequency of fluoride's interference with amino acids metabolism, potentially impacting the tricarboxylic acid (TCA) cycle. Our results also highlighted the ATP-binding cassette (ABC) transporters pathway as a central element in VSMC impairment. Moreover, we observed a dose-dependent increase in osteopontin (OPN) and α-smooth muscle actin (α-SMA) mRNA level and a dose-dependent decrease in ABC subfamily C member 1 (ABCC1) and bestrophin 1 (BEST1) mRNA level. These findings advance our understanding of fluoride as a CVD risk factor and its influence on VSMCs and metabolic pathways, warranting further investigation into this emerging risk factor.

Analysis of extreme ultraviolet radiation and hydrodynamics simulation at the core of laser-produced nickel plasmas.

The non-uniformity and transient nature of laser-produced plasma are critical factors that affect the analysis of the extreme ultraviolet spectra of highly charged ions and the diagnosis of plasma states. This paper systematically investigates the characteristics of extreme ultraviolet radiation and the hydrodynamic evolution of laser-produced nickel plasmas from two perspectives: high-spatio-temporal-resolution extreme-ultraviolet spectroscopic measurement and radiation hydrodynamics simulation. The consistency between the four-band experimental spectra and their theoretically simulated spectra confirms the accuracy of the atomic structure parameters and plasma state parameters. We also analyze the significant contribution of the 3d-4f double-excited state radiation to the spectral profile and discuss the influence of the self-absorption caused by plasma opacity on the characteristics of extreme ultraviolet radiation. The findings are crucial for accurately understanding the characteristics of extreme ultraviolet radiation, the hydrodynamic evolution, and the application of medium- and high-Z laser-produced plasma as a pulsed short-wavelength light source.

Reconstruction and analysis of transient evolution images of laser-produced plasma plumes.

We introduce a method for the analysis and simulation of transient images of laser-produced plasma (LPP) plumes. This method comprises three steps: (i) calculating the two-dimensional distribution of plasma parameters using a radiation hydrodynamics model, (ii) constructing radiation paths through ray tracing, and (iii) solving the radiation transport equation along these paths. In our simulations, we have meticulously considered factors that could influence the imaging results, including the quantum efficiency to different radiation wavelengths, the imaging lens' transmittance, the target surface's reflectivity, and the absorption, emission, and scattering quantum effect of the detector processes occurring in the plasma. We applied this method to analyze and simulate the transient images of aluminum plasma plumes in a background air environment at a pressure of 2000 Pa. The results demonstrate that our method not only produces simulated images that align with experimental results but also provides a reliable distribution of plasma state parameters and clearly identifies the ion species radiating in different bands. Given its capability in transient image reconstruction and its adaptability as a tool for spectral simulation and analysis of LPPs, we believe this method holds significant potential for spectral diagnostics in fields such as laser-induced breakdown spectroscopy, extreme ultraviolet lithography sources, and high-energy-density physics, among others.

Protectin Conjugates in Tissue Regeneration 1 Inhibits Macrophage Pyroptosis by Restricting NLRP3 Inflammasome Assembly to Mitigate Sepsis via the cAMP-PKA Pathway.

Protectin conjugates in tissue regeneration 1 (PCTR1) is a novel anti-inflammatory and proresolving lipid mediator biosynthesized from docosahexaenoic acid. Excessive activation of NLR family pyrin domain containing 3 (NLRP3) inflammasome and consequent pyroptosis are involved in diverse inflammatory diseases. However, how PCTR1 affects NLRP3 inflammasome activation and pyroptosis are still unclear. Here, we demonstrated that PCTR1 inhibited NLRP3 inflammasome activation and pyroptosis. These results show that PCTR1 dose-dependently inhibited gasdermin D cleavage in lipopolysaccharide (LPS)-primed murine primary macrophages upon nigericin stimulation. Additionally, PCTR1 treatment after LPS priming inhibited caspase-1 activation and subsequent mature interleukin-1ß release independent of the nuclear factor-kappa B pathway. PCTR1 exerted its inhibitory effects by blocking NLRP3-apoptosis-associated speck-like protein containing a CARD (ASC) interaction and ASC oligomerization, thereby restricting NLRP3 inflammasome assembly. However, the inhibitory effect of PCTR1 could be reversed by KH7 and H89, which are the inhibitors of the cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA) signaling pathway. Moreover, PCTR1 treatment alleviated lung tissue damage and improved mouse survival in LPS-induced sepsis. Our study unveils the molecular mechanism of negative regulation of NLRP3 inflammasome activation and pyroptosis by a novel lipid mediator and suggests that PCTR1 may serve as a potential treatment option for NLRP3-inflammasome driven diseases.

DULoc: quantitatively unmixing protein subcellular location patterns in immunofluorescence images based on deep learning features.

MOTIVATION: Knowledge of subcellular locations of proteins is of great significance for understanding their functions. The multi-label proteins that simultaneously reside in or move between more than one subcellular structure usually involve with complex cellular processes. Currently, the subcellular location annotations of proteins in most studies and databases are descriptive terms, which fail to capture the protein amount or fractions across different locations. This highly limits the understanding of complex spatial distribution and functional mechanism of multi-label proteins. Thus, quantitatively analyzing the multiplex location patterns of proteins is an urgent and challenging task. RESULTS: In this study, we developed a deep-learning-based pattern unmixing pipeline for protein subcellular localization (DULoc) to quantitatively estimate the fractions of proteins localizing in different subcellular compartments from immunofluorescence images. This model used a deep convolutional neural network to construct feature representations, and combined multiple nonlinear decomposing algorithms as the pattern unmixing method. Our experimental results showed that the DULoc can achieve over 0.93 correlation between estimated and true fractions on both real and synthetic datasets. In addition, we applied the DULoc method on the images in the human protein atlas database on a large scale, and showed that 70.52% of proteins can achieve consistent location orders with the database annotations. AVAILABILITY AND IMPLEMENTATION: The datasets and code are available at: https://github.com/PRBioimages/DULoc. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Real optical imaging simulation of laser-produced aluminum plasmas.

We developed a post-processing optical imaging model based on two-dimensional axisymmetric radiation hydrodynamics. Simulation and program benchmarks were performed using laser-produced Al plasma optical images obtained via transient imaging. The emission profiles of a laser-produced Al plasma plume in air at atmospheric pressure were reproduced, and the influence of plasma state parameters on radiation characteristics were clarified. In this model, the radiation transport equation is solved on the real optical path, which is mainly used to study the radiation of luminescent particles during plasma expansion. The model outputs consist of the electron temperature, particle density, charge distribution, absorption coefficient, and corresponding spatio-temporal evolution of the optical radiation profile. The model helps with understanding element detection and quantitative analysis of laser-induced breakdown spectroscopy.

Hospital-based Health Information Technology Infrastructure: Evidence of Reduced Medicare Payments and Racial Disparities Among Patients With ADRD.

BACKGROUND: Alzheimer disease and related dementia (ADRD) is one of the most expensive health conditions in the United States. Understanding the potential cost-savings or cost-enhancements of Health Information Technology (HIT) can help policymakers understand the capacity of HIT investment to promote population health and health equity for patients with ADRD. OBJECTIVES: This study examined access to hospital-based HIT infrastructure and its association with racial and ethnic disparities in Medicare payments for patients with ADRD. RESEARCH DESIGN: We used the 2017 Medicare Beneficiary Summary File, inpatient claims, and the American Hospital Association Annual Survey. Our study focused on community-dwelling Medicare fee-for-service beneficiaries who were diagnosed with ADRD. Our study focused on hospital-based telehealth-postdischarge (eg, remote patient monitoring) and telehealth-treatment (eg, psychiatric and addiction treatment) services. RESULTS: Results showed that hospital-based telehealth postdischarge services were associated with significantly higher total Medicare payment and acute inpatient Medicare payment per person per year among patients with ADRD on average. The associations between hospital-based telehealth-treatment services and payments were not significant. However, the association varied by patient's race and ethnicity. The reductions of the payments associated with telehealth postdischarge and treatment services were more pronounced among Black patients with ADRD. Telehealth-treatment services were associated with significant payment reductions among Hispanic patients with ADRD. CONCLUSION: Results showed that having hospital-based telehealth services might be cost-enhancing at the population level but cost-saving for Black and Hispanic patients with ADRD. Results suggested that personalized HIT services might be necessary to reduce the cost associated with ADRD treatment for racial and ethnic minority groups.

Examining HIV Diagnosis and Linkage to PrEP Prescription Among Members at An Integrated Health System in the Southeast United States.

Pre-Exposure Prophylaxis (PrEP) is a priority method for preventing HIV infection. This study's aims were threefold: (1) identify characteristics of members of a large health maintenance organization, Kaiser Permanente Georgia (KPGA), associated with HIV infection, (2) identify which member characteristics associated with HIV were also associated with PrEP prescription, and (3) identify which HIV-associated characteristics were associated with under- or over-prescribing of PrEP. Analysis of variables from the electronic medical record revealed that age, race, gender, mental health diagnosis, STI diagnosis, and sexual orientation were independently associated with HIV diagnosis. The same characteristics were independently associated with PrEP prescription except for race. Persons identifying as Black or unknown race, women, and/or heterosexual; and who had an STI diagnosis and/or illicit drug use had lower odds of being prescribed PrEP than of having an HIV diagnosis. The implications of these findings for improving physician identification of candidates for PrEP prescription are discussed.

A Comparative Trial of Improving Care for Underserved Asian Americans Infected with Hepatitis B Virus.

BACKGROUND: Hepatitis B virus (HBV) is the leading cause of hepatocellular carcinoma (HCC). Asian Americans have the highest incidence and mortality rates of HCC among all US racial/ethnic groups. Inadequate monitoring and treatment of chronic hepatitis B contribute to poor health outcomes and increased healthcare costs among Asian Americans. AIMS: The goal of this study is to assess the effect of a patient-led strategy on chronic hepatitis B monitoring and treatment adherence specifically among Asian Americans with culturally tailored Patient Navigator-led Intervention. METHODS: From 2015 to 2018, 532 eligible participants living with chronic hepatitis B in the greater Philadelphia and New York city metropolitan areas were randomly assigned to either the intervention group or the control group. Generalized linear mixed-effects models were used to estimate the odds ratio (OR) for rates of doctor visits for chronic hepatitis B and rates of alanine aminotransferase testing for evidence of liver damage. RESULTS: Intervention group had higher rates of doctor visits than the control group at both 6-month (77.22% vs. 45.75%) and 12-month assessments (90.73% vs. 60.61%). Significantly more intervention group participants received ALT testing than control group participants at 6-month (52.90% vs. 25.10%) and 12-month (75.40% vs. 46.75%) follow-up. CONCLUSIONS: Culturally and linguistically appropriate intervention has strong effects on adherence to follow-up care among Asian American hepatitis B patients experiencing challenges to medication adherence and follow up care. These findings further identify opportunities for practical implementation of evidence-based intervention that could lead to reductions in disparities in chronic liver disease and liver cancer among high-risk, underserved populations.

Reducing Rural and Urban Disparities in Potentially Preventable Hospitalizations: Evidence of Hospital-Based Health Information Technology and Enabling Services.

Background: Telehealth and enabling services are promising approaches to address the intersecting challenges of chronic disease burden, a growing aging population, and poor access to care disproportionately affecting rural areas. Using potentially preventable hospitalizations (PPHs) as an indicator for health system efficiency and quality, this study examined the relationship between health information technology and hospital-provided enabling services on PPHs across rural, micropolitan, and metropolitan areas. Methods: We constructed a patient-, hospital-, community-, and state-level data set using the Medicare fee-for-service claims file and the Medicare Master Beneficiary Summary File, and the American Hospital Association Annual Survey. Logistic regressions were applied to examine associations between PPH and telehealth post-discharge, telehealth treatment, and telehealth post-discharge and enabling services. Results: Approximately 50% of rural and micropolitan residents (vs. 36% of urban residents) were treated in hospitals providing neither telehealth post-discharge services nor enabling services, and 7% (vs. 11% of urban residents) were treated in hospitals with both services. Telehealth post-discharge services were associated with significantly lower odds ratio (OR) of having any PPH due to acute (OR = 0.91, p < 0.001) and chronic conditions (OR = 0.94, p < 0.001). The ORs of having any PPH due to acute and chronic conditions were the least among beneficiaries who were treated in hospitals with both telehealth post-discharge and enabling services (OR = 0.56, p < 0.001, for acute conditions, and OR = 0.73, p < 0.001, for chronic conditions). Conclusions: Hospital use of post-discharge telehealth alongside enabling services may help provide timely access to care, improve care coordination, and reduce PPHs for older rural residents.

Immunomodulatory Mechanism and Potential Application of Dental Pulp-Derived Stem Cells in Immune-Mediated Diseases.

Dental pulp stem cells (DPSCs) are mesenchymal stem cells (MSCs) derived from dental pulp tissue, which have high self-renewal ability and multi-lineage differentiation potential. With the discovery of the immunoregulatory ability of stem cells, DPSCs have attracted much attention because they have similar or even better immunomodulatory effects than MSCs from other sources. DPSCs and their exosomes can exert an immunomodulatory ability by acting on target immune cells to regulate cytokines. DPSCs can also migrate to the lesion site to differentiate into target cells to repair the injured tissue, and play an important role in tissue regeneration. The aim of this review is to summarize the molecular mechanism and target cells of the immunomodulatory effects of DPSCs, and the latest advances in preclinical research in the treatment of various immune-mediated diseases, providing new reflections for their clinical application. DPSCs may be a promising source of stem cells for the treatment of immune-mediated diseases.

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OBJECTIVES: To explore the molecular characteristics of Staphylococcus aureus (S. aureus) in children, and to compare the molecular characteristics of different types of strains (infection and colonization strains) so as to reveal pathogenic molecular markers of S. aureus. METHODS: A cross-sectional study design was used to conduct nasopharyngeal swab sampling from healthy children in the community and clinical samples from infected children in the hospital. Whole genome sequencing was used to detect antibiotic resistance genes and virulence genes. A random forest method to used to screen pathogenic markers. RESULTS: A total of 512 S. aureus strains were detected, including 272 infection strains and 240 colonization strains. For virulence genes, the carrying rates of enterotoxin genes (seb and sep), extracellular enzyme coding genes (splA, splB, splE and edinC), leukocytotoxin genes (lukD, lukE, lukF-PV and lukS-PV) and epidermal exfoliating genes (eta and etb) in infection strains were higher than those in colonization strains. But the carrying rates of enterotoxin genes (sec, sec3, seg, seh, sei, sel, sem, sen, seo and seu) were lower in infection strains than in colonization strains (P<0.05). For antibiotic resistance genes, the carrying rates of lnuA, lnuG, aadD, tetK and dfrG were significantly higher in infection strains than in colonization strains (P<0.05). The accuracy of cross-validation of the random forest model for screening pathogenic markers of S. aureus before and after screening was 69% and 68%, respectively, and the area under the curve was 0.75 and 0.70, respectively. The random forest model finally screened out 16 pathogenic markers (sem, etb, splE, sep, ser, mecA, lnuA, sea, blaZ, cat(pC233), blaTEm-1A, aph(3')-III, ermB, ermA, ant(9)-Ia and ant(6)-Ia). The top five variables in the variable importance ranking were sem (OR=0.40), etb (OR=3.95), splE (OR=1.68), sep (OR=3.97), and ser (OR=1.68). CONCLUSIONS: The random forest model can screen out pathogenic markers of S. aureus and exhibits a superior predictive performance, providing genetic evidence for tracing highly pathogenic S. aureus and conducting precise targeted interventions.

Lung cancer screening use and implications of varying eligibility criteria by race and ethnicity: 2019 Behavioral Risk Factor Surveillance System data.

BACKGROUND: In 2021, the US Preventive Services Task Force (USPSTF) expanded the eligibility criteria for low-dose computed tomographic lung cancer screening (LCS) to reduce racial disparities that resulted from the 2013 USPSTF criteria. The annual LCS rate has risen slowly since the 2013 USPSTF screening recommendations. Using the 2019 Behavioral Risk Factor Surveillance System (BRFSS), this study 1) describes LCS use in 2019, 2) compares the percent eligible for LCS using the 2013 versus 2021 USPSTF criteria, and 3) determines the percent eligible using the more detailed PLCOm2012Race3L risk-prediction model. METHODS: The analysis included 41,544 individuals with a smoking history from states participating in the BRFSS LCS module who were ≥50 years old. RESULTS: Using the 2013 USPSTF criteria, 20.7% (95% confidence interval [CI], 19.0-22.4) of eligible individuals underwent LCS in 2019. The 2013 USPSTF criteria was compared to the 2021 USPSTF criteria, and the overall proportion eligible increased from 21.0% (95% CI, 20.2-21.8) to 34.7% (95 CI, 33.8-35.6). Applying the 2021 criteria, the proportion eligible by race was 35.8% (95% CI, 34.8-36.7) among Whites, 28.5% (95% CI, 25.2-31.9) among Blacks, and 18.0% (95% CI, 12.4-23.7) among Hispanics. Using the 1.0% 6-year threshold that is comparable to the 2021 USPSTF criteria, the PLCOm2012Race3L model selected more individuals overall and by race. CONCLUSIONS: Using data from 20 states and using multiple imputation, higher LCS rates have been reported compared to prior BRFSS data. The 2021 expanded criteria will result in a greater number of screen-eligible individuals. However, risk-based screening that uses additional risk factors may be more inclusive overall and across subgroups. LAY SUMMARY: In 2013, lung cancer screening (lung screening) was recommended for high risk individuals. The annual rate of lung screening has risen slowly, particularly among Black individuals. In part, this racial disparity resulted in expanded 2021 criteria. Survey data was used to: 1) describe the number of people screened in 2019, 2) compare the percent eligible for lung screening using the 2013 versus 2021 guidelines, and 3) determine the percent eligible using more detailed criteria. Lung screening rates increased in 2019, and the 2021 criteria will result in more individuals eligible for screening. Using additional criteria may identify more individuals eligible for lung screening.

How an Oxide Layer Influences the Impact Dynamics of Galinstan Droplets on a Superhydrophobic Surface.

When exposed to air, gallium-based alloys rapidly form a thin oxide layer with viscoelasticity and high adhesion. Although previous work demonstrated that an oxide layer inhibits liquid metal droplet rebound, there is still a lack of a quantitative study to elaborate how an oxide layer affects the impact dynamics. To address this issue, we experimentally investigate Galinstan droplet impingement on a superhydrophobic CuO nanoblade surface and physically explain the difference in the dynamic characteristics of oxidized and unoxidized droplets. Experimental results show that the effect of an oxide layer becomes prominent during the retraction phase. The high adhesion significantly suppresses retraction and rebound, while the elastic response prevents a droplet from sufficiently stretching and maintains the stability of the morphology. More importantly, we systematically and quantitatively explore the influence of an oxide layer on several critical impact parameters, which contributes to a comprehensive understanding of the impact dynamics of liquid metal droplets. It is indicated that an oxide layer has little effect on the maximum spreading factor and spreading time, whereas it causes a 45% reduction of the restitution coefficient and a 36% increase in contact time. Notably, the scaling laws that describe the critical impact parameters of unoxidized droplets show good agreement with the ones known from ordinary Newtonian fluids.

Empowering Low-Income Asian American Women to Conduct Human Papillomavirus Self-Sampling Test: A Community-Engaged and Culturally Tailored Intervention.

BACKGROUND: Asian American women face disproportionate burden of cervical cancer (CC) than non-Hispanic white women in the U.S. The goal of this study was to assess the feasibility and impact of a culturally tailored intervention to promote Human papillomavirus (HPV) self-sampling test among hard-to-reach Asian American women. METHODS: We adopted the community-based participatory research (CBPR) approach to conduct this efficacy study. A total of 156 female participants (56 Chinese, 50 Korean, and 50 Vietnamese) were recruited from community-based organizations (CBOs) in the greater Philadelphia metropolitan area. The intervention components included HPV-related education, HPV self-sampling test kit and instructions, group discussions, and patient navigations, all available in Asian languages. We examined several outcomes, including the completion of HPV self-sampling, HPV-related knowledge, perceived social support, self-efficacy, and comfort with the self-sampling test at post-intervention assessment. RESULTS: The majority of Asian American women had low annual household income (62.3% earned less than $20,000) and low educational attainment (61.3% without a college degree). We found significant increase in participants' knowledge on HPV (baseline: 2.83, post: 4.89, P <.001), social support (baseline: 3.91, post: 4.09, P < .001), self-efficacy (baseline: 3.05, post: 3.59, P < .001), and comfortable with HPV self-sample test (baseline: 3.62, post: 4.06, P < .001). CONCLUSION: To the best of our knowledge, this is the first intervention study that promoted HPV self-sampling test among Asian American women. Our findings showed that CBPR culturally tailored intervention of self-sampling was highly effective in empowering low-income Asian American women to conduct HPV self-sampling tests.

Discovery of pyrrolo[2,3-d]pyrimidine-based molecules as a Wee1 inhibitor template.

In the past decade, Wee1 inhibition has received widespread attention as a cancer therapy. Our research aims to discover effective, selective and drug-like Wee1 inhibitors. Herein, a series of compounds with pyrrolo[2,3-d]pyrimidine-based heterocycles were designed, synthesized and confirmed to inhibit Wee1 kinase. The inhibitors afforded good potency in Wee1 Kinase inhibitory activity in enzymatic assays. These compounds showed strong proliferation inhibition against NCI-1299 cell lines and had acceptable pharmacokinetic properties. These derivatives are promising inhibitors that warrant further evaluation, towards the development of potential anticancer drug.

Lung cancer screening decisional needs among African American smokers of lower socioeconomic status.

OBJECTIVES: Adherence to most evidence-based cancer screenings is lower among African Americans due to system- and individual-level factors that contribute to persistent disparities. Given the recommendation for low-dose computed tomography (LDCT) screening among individuals at high risk for lung cancer, we sought to describe aspects of decision-making for LDCT among African Americans and to examine associations between select components of decision-making and screening-related intentions. DESIGN: African Americans (N = 119) with a long-term smoking history, aged 55-80 years, and without lung cancer were recruited to participate in a cross-sectional survey. We measured knowledge, awareness, decisional conflict, preferences, and values related to lung cancer screening. RESULTS: The majority of the study population was of lower socioeconomic status (67.2% had an annual income of ≤$20,000) and long-term current (79%) smokers. Participants had a median 20 pack-years smoking history. Most participants (65.8%) had not heard of LDCT and the total lung cancer screening knowledge score was M = 7.1/15.0 (SD = 1.8). Participants with higher scores on the importance of the pros and cons of screening expressed greater likelihood of talking with a doctor, family, and friends about screening (p's < .10). CONCLUSIONS: Findings have implications for addressing the decisional needs of lower socioeconomic African American current and former smokers to promote informed decision-making for LDCT.