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Background and Objectives: Loneliness is a major public health concern; however, limited research has examined the mechanisms contributing to racial/ethnic inequities in loneliness. Race/ethnicity has been hypothesized to be a distal factor influencing loneliness, and racial/ethnic inequities in loneliness may be attributable to socioeconomic factors (e.g., income and education). Our study seeks to confirm these hypotheses by examining mechanisms that contribute to racial/ethnic inequities in loneliness. In other words, if racial/ethnic differences in loneliness among older adults are mediated by income and education. Research Design and Methods: Data came from the Health and Retirement Study Leave-Behind Questionnaire, 2014-2016. Loneliness was measured by the UCLA 3-item loneliness scale. Race/ethnicity categories were White, Black, and Hispanic/Latino. The mediator variables were household income and education. Multivariable linear regression models were used to determine differences in loneliness by race/ethnicity. The Karlson-Holm-Breen (KHB) mediation method was used to determine if income and education mediated racial/ethnic differences in loneliness. Results: In models examining income and education together, a complete mediation was found between White and Black older adults, in that income and education completely mediated differences in loneliness between these groups. A partial mediation was found between White and Hispanic, and Black and Hispanic older adults. When examining income and education separately, we found that income solely accounted for racial/ethnic differences in loneliness compared to education. Discussion and Implications: Our study is the first to explicitly determine if socioeconomic factors mediate race/ethnicity differences in loneliness among a national sample of older adults. These findings illustrate that income may have greater proximate effects for loneliness among older adults in comparison to education. Additionally, these findings can inform evidence-based interventions to reduce loneliness among older adults. Interventions that enhance quality of life and provide opportunities for socialization for racialized low-income older adults may help decrease racial/ethnic inequities in loneliness.
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OBJECTIVES: Due to statistical challenges in disentangling the mobility effect (i.e., intergenerational educational mobility) from the position effect (i.e., parental and person's own education), the impact of intergenerational educational mobility on cognitive function remains unclear. We employed a novel approach to identify the mobility effect and investigate the net impact of intergenerational educational mobility on heterogeneous patterns of cognition among middle-aged and older adults in China. METHODS: Participants aged 45 and older were recruited from the China Health and Retirement Longitudinal Study, a population-based prospective cohort study between 2011 and 2018. We identified cognitive trajectories using the growth mixture model (GMM) and subsequently employed the mobility contrast model (MCM) to examine the effects of intergenerational educational mobility on cognitive patterns stratified by gender. RESULTS: Almost two thirds of respondents experienced intergenerational educational mobility, and 55% experienced upward mobility. Men had a higher rate of upward mobility than women. Three population-based cognitive patterns were identified: the low cognitive function with decline group (28%), the moderate cognitive function group (47%), and the high cognitive function group (26%). MCM analysis revealed that both upward and downward intergenerational educational mobility negatively affected cognitive trajectory patterns, extending beyond the influence of individuals' current and parental education. DISCUSSION: In future research, the impact of mobility can be studied in longitudinal data sets by combining the GMM and MCM approaches. The net negative effect of intergenerational educational mobility on cognitive trajectory patterns indicates that it should be recognized as an independent predictor of cognitive decline.
Subject(s)
Cognition , Educational Status , Humans , Male , Female , Aged , Longitudinal Studies , China/epidemiology , Middle Aged , Cognition/physiology , Prospective Studies , Intergenerational Relations , Sex Factors , Cognitive Dysfunction/epidemiology , East Asian PeopleABSTRACT
BACKGROUND: Identifying cells engaged in fundamental cellular processes, such as proliferation or living/death statuses, is pivotal across numerous research fields. However, prevailing methods relying on molecular biomarkers are constrained by high costs, limited specificity, protracted sample preparation, and reliance on fluorescence imaging. METHODS: Based on cellular morphology in phase contrast images, we developed a deep-learning model named Detector of Mitosis, Apoptosis, Interphase, Necrosis, and Senescence (D-MAINS). RESULTS: D-MAINS utilizes machine learning and image processing techniques, enabling swift and label-free categorization of cell death, division, and senescence at a single-cell resolution. Impressively, D-MAINS achieved an accuracy of 96.4 ± 0.5% and was validated with established molecular biomarkers. D-MAINS underwent rigorous testing under varied conditions not initially present in the training dataset. It demonstrated proficiency across diverse scenarios, encompassing additional cell lines, drug treatments, and distinct microscopes with different objective lenses and magnifications, affirming the robustness and adaptability of D-MAINS across multiple experimental setups. CONCLUSIONS: D-MAINS is an example showcasing the feasibility of a low-cost, rapid, and label-free methodology for distinguishing various cellular states. Its versatility makes it a promising tool applicable across a broad spectrum of biomedical research contexts, particularly in cell death and oncology studies.
Subject(s)
Apoptosis , Cellular Senescence , Deep Learning , Interphase , Mitosis , Necrosis , Humans , Cell Line, Tumor , Neoplasms/pathology , Neoplasms/metabolism , Image Processing, Computer-Assisted/methodsABSTRACT
Despite recent advances in cancer treatment, refining therapeutic agents remains a critical task for oncologists. Precise evaluation of drug effectiveness necessitates the use of 3D cell culture instead of traditional 2D monolayers. Microfluidic platforms have enabled high-throughput drug screening with 3D models, but current viability assays for 3D cancer spheroids have limitations in reliability and cytotoxicity. This study introduces a deep learning model for non-destructive, label-free viability estimation based on phase-contrast images, providing a cost-effective, high-throughput solution for continuous spheroid monitoring in microfluidics. Microfluidic technology facilitated the creation of a high-throughput cancer spheroid platform with approximately 12 000 spheroids per chip for drug screening. Validation involved tests with eight conventional chemotherapeutic drugs, revealing a strong correlation between viability assessed via LIVE/DEAD staining and phase-contrast morphology. Extending the model's application to novel compounds and cell lines not in the training dataset yielded promising results, implying the potential for a universal viability estimation model. Experiments with an alternative microscopy setup supported the model's transferability across different laboratories. Using this method, we also tracked the dynamic changes in spheroid viability during the course of drug administration. In summary, this research integrates a robust platform with high-throughput microfluidic cancer spheroid assays and deep learning-based viability estimation, with broad applicability to various cell lines, compounds, and research settings.
Subject(s)
Cell Survival , Deep Learning , Spheroids, Cellular , Humans , Spheroids, Cellular/drug effects , Spheroids, Cellular/pathology , Cell Survival/drug effects , Drug Screening Assays, Antitumor/instrumentation , Antineoplastic Agents/pharmacology , Cell Line, Tumor , Microfluidic Analytical Techniques/instrumentation , Lab-On-A-Chip DevicesABSTRACT
Generativity has been increasingly recognized as an important component of healthy aging. Although the desire to be generative is influenced by societal and cultural expectations, the relative influence of its driving factors by retirement status, a significant life-course transition, is underexplored. This study examined how later-life generativity is driven by the interplay between retirement status and financial, human and social capital. An online survey targeting Hong Kong adults aged 45+ was conducted. Linear regression models were stratified by retirement status (working and retired) to examine the effects of financial (income, assets, and financial satisfaction), human (education and health-related measures), and social capitals (productive and social engagement) on generativity. Among those working, higher generativity was associated with financial, human, and social capitals that facilitated material provision. Among those retired, human and social capitals that supported the transmission of knowledge and experience were more important for generativity. For both groups, support from close social networks was the strongest predictor. Different cultural demands, dictated by retirement status, play a crucial role in determining how older adults feel like they can contribute to subsequent generations. These findings can inform policies and programs that seek to support healthy transitions into retirement.
Subject(s)
Retirement , Social Capital , Humans , Aged , Income , Hong KongABSTRACT
Consumer-directed care (CDC) programs for older people aim to optimize health outcomes by offering clients control and flexibility regarding service arrangements. However, policy design features may differ due to heterogenous sociostructural systems. By operationalizing a framework with three dimensions of CDC, i.e. control and direct services, variety of service options, and information and support, we analyzed how countries vary in their policy designs to achieve consumer direction. Using an expert survey (n = 20) and cross-national document analysis, we analyzed 12 CDC programs from seven selected countries: the United States, the United Kingdom, Germany, the Netherlands, China, Australia, and Spain. Among the three dimensions, CDC programs placed more emphasis on and displayed more homogenous performance of policy designs that achieve consumer direction in the dimension of control and direct services, while less emphasis was placed on and more heterogenous performance displayed in the dimensions of variety of service options and information and support. We offer a systematically operationalized framework to investigate CDC policy designs. Findings advance our understanding of CDC policy features from a cross-national perspective. Policymakers could incorporate these findings to empower older people in their respective societies.
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Considerable evidence suggests that breast cancer therapeutic resistance and relapse can be driven by polyploid giant cancer cells (PGCCs). The number of PGCCs increases with the stages of disease and therapeutic stress. Given the importance of PGCCs, it remains challenging to eradicate them. To discover effective anti-PGCC compounds, there is an unmet need to rapidly distinguish compounds that kill non-PGCCs, PGCCs, or both. Here, we establish a single-cell morphological analysis pipeline with a high throughput and great precision to characterize dynamics of individual cells. In this manner, we screen a library to identify promising compounds that inhibit all cancer cells or only PGCCs (e.g., regulators of HDAC, proteasome, and ferroptosis). Additionally, we perform scRNA-Seq to reveal altered cell cycle, metabolism, and ferroptosis sensitivity in breast PGCCs. The combination of single-cell morphological and molecular investigation reveals promising anti-PGCC strategies for breast cancer treatment and other malignancies.
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Breast Neoplasms , Humans , Female , Breast Neoplasms/drug therapy , Breast Neoplasms/genetics , Breast Neoplasms/metabolism , Cell Line, Tumor , Neoplasm Recurrence, Local , Polyploidy , Gene Expression ProfilingABSTRACT
Cell migration is a complex process that plays a crucial role in normal physiology and pathologies such as cancer, autoimmune diseases, and mental disorders. Conventional cell migration assays face limitations in tracking a large number of individual migrating cells. To address this challenge, we have developed a high-throughput microfluidic cell migration chip, which seamlessly integrates robotic liquid handling and computer vision to swiftly monitor the movement of 3200 individual cells, providing unparalleled single-cell resolution for discerning distinct behaviors of the fast-moving cell population. This study focuses on the ECM's role in regulating cellular migration, utilizing this cutting-edge microfluidic technology to investigate the impact of ten different ECMs on triple-negative breast cancer cell lines. We found that collagen IV, collagen III, and collagen I coatings were the top enhancers of cell movement. Combining these ECMs increased cell motility, but the effect was sub-additive. Furthermore, we examined 87 compounds and found that while some compounds inhibited migration on all substrates, significantly distinct effects on differently coated substrates were observed, underscoring the importance of considering ECM coating. We also utilized cells expressing a fluorescent actin reporter and observed distinct actin structures in ECM-interacting cells. ScRNA-Seq analysis revealed that ECM coatings induced EMT and enhanced cell migration. Finally, we identified genes that were particularly up-regulated by collagen IV and the selective inhibitors successfully blocked cell migration on collagen IV. Overall, the study provides insights into the impact of various ECMs on cell migration and dynamics of cell movement with implications for developing therapeutic strategies to combat diseases related to cell motility.
Subject(s)
Actins , Microfluidics , Humans , Actins/analysis , Extracellular Matrix/chemistry , Cell Movement/physiology , Collagen/metabolismABSTRACT
This study examined the moderating mechanisms of generative concerns (perception of making contributions to others) between generative civic activities and mental health among middle-aged and older adults. A total of 1,109 community-dwelling adults aged over 45 were recruited through an online survey. Generative civic activities (political participation and volunteering), generative concerns (the Loyola Generativity Scale), and two outcomes of mental health (depressive symptoms and mental wellbeing) were measured. Linear regression models and simple slope analyses were used to probe the moderating effects of generative concerns, stratified by age (45-64 years and 65+). Generative activities, but not concerns, were associated with lower depressive symptoms among middle-aged and older adults. Generative concerns and activities were related to better mental wellbeing among middle-aged adults. Generative concerns moderated the associations between civic activities and depressive symptoms. Those with higher generative concerns but lower civic activities had higher depression scores. Conversely, a stronger reduction in depressive symptoms by engaging in civic activities was found only when individuals had greater concerns. No moderating effect was found on mental wellbeing. The positive effect of civic engagement on reducing depressive symptoms depends on generative concerns, particularly among older people and those with greater concerns. Bridging the gap between perceived generative concerns and actual civic actions may improve later-life mental health.
Subject(s)
Independent Living , Mental Health , Humans , Middle Aged , Aged , Linear Models , VolunteersABSTRACT
Background and Objectives: Financial capability, comprising financial literacy, access, and behavior, can influence an individual's ability to effectively use financial resources, thus affecting their health and well-being. However, studies have predominantly focused on financial literacy and overlooked a more comprehensive measure of financial capability and its health impacts. Furthermore, although financial capability is shaped profoundly by gender, there is limited knowledge of the role of gender in these associations. Research Design and Methods: This study investigated how gender may moderate the links between financial capability and health. The study recruited 1,109 community-dwelling adults (aged 45+) in Hong Kong to take part in an online survey employing multivariate linear and logistic regression to examine the gender differences in the associations between financial capability and physical (perceived health and mobility limitations), mental (life satisfaction and depression), and financial (retirement worry and financial satisfaction) health. Results: The results showed that financial access and behavior had a more significant influence on health outcomes than financial literacy. Gender differences in financial capability were identified through simple slope analyses. Financial literacy was more important for men's self-rated health and life satisfaction, whereas financial behavior was more critical for women. Additionally, although financial access was not related to retirement worry among men, it was significantly associated with lower retirement worry among women. Discussion and Implications: The findings suggest that gender-specific pathways to financial capability may lead to health disparities. Policies and programs to improve population health and well-being, particularly for women, should target financial literacy, strengthen financial inclusion, and encourage responsible financial behavior.
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We reported that gamma-hydroxybutyrate (GHB) is released upon Herpes Simplex Virus Type-1 (HSV-1) acute infection. However, the cellular biochemical processes involved in the production of GHB in infected cells are unclear. This study aims to shed light on the biochemical pathway and the stage within the viral life cycle responsible for the release of GHB in infected cells. UV-inactivation, acyclovir (ACV), and cycloheximide (CHX) treatments were used to inhibit HSV-1 replication at various stages. Vero cells treated with UV-inactivated HSV-1 significantly decreased GHB production. However, ACV or CHX treatments did not affect GHB production. We also showed that inhibition of glycolytic enzyme enolase by sodium fluoride (NaF) significantly reduces GHB production upon infection. This finding suggests that suppression of glycolytic activity negatively affects cellular GHB production. Our data also indicated that succinic semialdehyde dehydrogenase, an enzyme involved in the shunt of the tricarboxylic acid (TCA) cycle to generate succinic acid, was decreased upon infection, suggesting that infection may trigger the accumulation of succinic semialdehyde, causing the production of GHB. Although the precise mechanism has yet to be defined, our results suggest that early events following infection modulates the release of GHB, which is generated through the metabolic pathways of glycolysis and TCA cycle.
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Patients with triple-negative breast cancer remain at risk for metastatic disease despite treatment. The acquisition of chemoresistance is a major cause of tumor relapse and death, but the mechanisms are far from understood. We have demonstrated that breast cancer cells (BCCs) can engulf mesenchymal stem/stromal cells (MSCs), leading to enhanced dissemination. Here, we show that clinical samples of primary invasive carcinoma and chemoresistant breast cancer metastasis contain a unique hybrid cancer cell population coexpressing pancytokeratin and the MSC marker fibroblast activation protein-α. We show that hybrid cells form in primary tumors and that they promote breast cancer metastasis and chemoresistance. Using single-cell microfluidics and in vivo models, we found that there are polyploid senescent cells within the hybrid cell population that contribute to metastatic dissemination. Our data reveal that Wnt Family Member 5A (WNT5A) plays a crucial role in supporting the chemoresistance properties of hybrid cells. Furthermore, we identified that WNT5A mediates hybrid cell formation through a phagocytosis-like mechanism that requires BCC-derived IL-6 and MSC-derived C-C Motif Chemokine Ligand 2. These findings reveal hybrid cell formation as a mechanism of chemoresistance and suggest that interrupting this mechanism may be a strategy in overcoming breast cancer drug resistance.
Subject(s)
Mesenchymal Stem Cells , Triple Negative Breast Neoplasms , Humans , Drug Resistance, Neoplasm , Cell Line, Tumor , Neoplasm Recurrence, Local/pathology , Mesenchymal Stem Cells/metabolism , Triple Negative Breast Neoplasms/metabolismABSTRACT
Chemokine receptors constitute an important subfamily of G protein-coupled receptors (GPCRs), and they are critically involved in a broad range of immune response mechanisms. Ligand promiscuity among these receptors makes them an interesting target to explore multiple aspects of biased agonism. Here, we comprehensively characterize two chemokine receptors namely, CXCR4 and CXCR7, in terms of their transducer-coupling and downstream signaling upon their stimulation by a common chemokine agonist, CXCL12, and a small molecule agonist, VUF11207. We observe that CXCR7 lacks G-protein-coupling while maintaining robust ßarr recruitment with a major contribution of GRK5/6. On the other hand, CXCR4 displays robust G-protein activation as expected but exhibits significantly reduced ßarr-coupling compared to CXCR7. These two receptors induce distinct ßarr conformations even when activated by the same agonist, and CXCR7, unlike CXCR4, fails to activate ERK1/2 MAP kinase. We also identify a key contribution of a single phosphorylation site in CXCR7 for ßarr recruitment and endosomal localization. Our study provides molecular insights into intrinsic-bias encoded in the CXCR4-CXCR7 system with broad implications for drug discovery.
Subject(s)
Receptors, CXCR , Receptors, CXCR/genetics , Receptors, CXCR/metabolism , Receptors, CXCR4/metabolism , Signal Transduction , GTP-Binding Proteins , Mitogen-Activated Protein Kinase 3/metabolism , Chemokine CXCL12/metabolismABSTRACT
We present the outcomes of a recent large-scale subjective study of Mobile Cloud Gaming Video Quality Assessment (MCG-VQA) on a diverse set of gaming videos. Rapid advancements in cloud services, faster video encoding technologies, and increased access to high-speed, low-latency wireless internet have all contributed to the exponential growth of the Mobile Cloud Gaming industry. Consequently, the development of methods to assess the quality of real-time video feeds to end-users of cloud gaming platforms has become increasingly important. However, due to the lack of a large-scale public Mobile Cloud Gaming Video dataset containing a diverse set of distorted videos with corresponding subjective scores, there has been limited work on the development of MCG-VQA models. Towards accelerating progress towards these goals, we created a new dataset, named the LIVE-Meta Mobile Cloud Gaming (LIVE-Meta-MCG) video quality database, composed of 600 landscape and portrait gaming videos, on which we collected 14,400 subjective quality ratings from an in-lab subjective study. Additionally, to demonstrate the usefulness of the new resource, we benchmarked multiple state-of-the-art VQA algorithms on the database. The new database will be made publicly available on our website: https://live.ece.utexas.edu/research/LIVE-Meta-Mobile-Cloud-Gaming/index.html.
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Anxiety, depression, and psychological distress are public health concerns for Black emerging adults ages 18-29, given their prevalence in this population. However, we have scant empirical research investigating the prevalence and correlates of negative mental outcomes among Black emerging adults with a history of exposure to police use of force. Thus, the current study examined the prevalence and correlates of depression, anxiety, and psychological well-being and how they vary among a sample of Black emerging adults with a history of direct or indirect exposure to police use of force. Computer-assisted surveys were administered to a sample of Black emerging adults (N = 300). Univariate, bivariate, and multiple linear regression analyses were conducted. Black women with a history of direct or indirect exposure to police use of force had significantly less favorable scores on the depression and anxiety scales compared with Black men. Study findings suggest that Black emerging adults, particularly women, with a history of exposure to police use of force are at risk of experiencing adverse mental health outcomes. Future research with a larger and ethnically diverse sample of emerging adults that examines the prevalence and correlates of adverse mental health outcomes and how they vary by gender, ethnicity, and exposure to police use of force is warranted.
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As part of the central nervous system (CNS), retinal ganglion cells (RGCs) and their axons are the only neurons in the retina that transmit visual signals from the eye to the brain via the optic nerve (ON). Unfortunately, they do not regenerate upon injury in mammals. In ON trauma, retinal microglia (RMG) become activated, inducing inflammatory responses and resulting in axon degeneration and RGC loss. Since aldose reductase (AR) is an inflammatory response mediator highly expressed in RMG, we investigated if pharmacological inhibition of AR can attenuate ocular inflammation and thereby promote RGC survival and axon regeneration after ON crush (ONC). In vitro, we discovered that Sorbinil, an AR inhibitor, attenuates BV2 microglia activation and migration in the lipopolysaccharide (LPS) and monocyte chemoattractant protein-1 (MCP-1) treatments. In vivo, Sorbinil suppressed ONC-induced Iba1 + microglia/macrophage infiltration in the retina and ON and promoted RGC survival. Moreover, Sorbinil restored RGC function and delayed axon degeneration one week after ONC. RNA sequencing data revealed that Sorbinil protects the retina from ONC-induced degeneration by suppressing inflammatory signaling. In summary, we report the first study demonstrating that AR inhibition transiently protects RGC and axon from degeneration, providing a potential therapeutic strategy for optic neuropathies.
Subject(s)
Optic Atrophy , Optic Nerve Injuries , Animals , Microglia , Axons/physiology , Aldehyde Reductase , Nerve Regeneration , Retina , Optic Nerve Injuries/pathology , Optic Atrophy/pathology , Nerve Degeneration/pathology , MammalsABSTRACT
Microneedle lactate sensors may be used to continuously measure lactate concentration in the interstitial fluid in a minimally invasive and pain-free manner. First- and second-generation enzymatic sensors produce a redox-active product that is electrochemically sensed at the electrode surface. Direct electron transfer enzymes produce electrons directly as the product of enzymatic action; in this study, a direct electron transfer enzyme specific to lactate has been immobilized onto a microneedle surface to create lactate-sensing devices that function at low applied voltages (0.2 V). These devices have been validated in a small study of human volunteers; lactate concentrations were raised and lowered through physical exercise and subsequent rest. Lactazyme microneedle devices show good agreement with concurrently obtained and analyzed serum lactate levels.
Subject(s)
Electrons , Lactic Acid , Humans , Electrodes , Electron Transport , Research SubjectsABSTRACT
OBJECTIVES: This study examines associations between social isolation and depressive symptoms among Hong Kong Chinese adults aged 65 and older by investigating the distinct effects of individual indicators, cumulative index, and typologies of social isolation during the Covid-19 pandemic. METHODS: We used a sample of 260 older adults from a cross-sectional, city-wide online survey targeting 1,109 aged 45+ adults through purposive sampling. Seven indicators of social isolation (not married; living alone; not engaging in social/organizational activities; no social contact with friends or families; lack of family and friends networks; loneliness) using Cornwell & Waite's framework were selected to construct three unique types of social isolation measures. We used latent class analysis (LCA) and regression models to examine the effects of varied typologies of social isolation on depressive symptoms. RESULTS: Individual model of social isolation showed that lack of social contact and feeling lonely were significant predictors of depressive symptoms. A strong linear-trend gradient effect of cumulative social isolation on depressive symptoms was also observed. The LCA model identified four typologies of social isolation (socially isolated; living alone but socially engaged; married but lacking social ties, and not socially isolated); those in the 'socially isolated' and 'married but lacking social ties' groups had the most depressive symptoms. CONCLUSION: Three operationalizations of social isolation demonstrated different utilities and implications in assessing the impacts of social isolation on depressive symptoms. Social contacts and loneliness, rather than living status or other characteristics of isolation, were the factors most strongly associated with depressive symptoms. Support programs should target lonely older adults who lack social engagement opportunities, as they are at increased risk of depression.
Subject(s)
COVID-19 , Depression , Humans , Aged , Depression/epidemiology , Cross-Sectional Studies , Pandemics , COVID-19/epidemiology , Social Isolation , LonelinessABSTRACT
Cancer cell migration represents an essential step toward metastasis and cancer deaths. However, conventional drug discovery focuses on cytotoxic and growth-inhibiting compounds rather than inhibitors of migration. Drug screening assays generally measure the average response of many cells, masking distinct cell populations that drive metastasis and resist treatments. Here, this work presents a high-throughput microfluidic cell migration platform that coordinates robotic liquid handling and computer vision for rapidly quantifying individual cellular motility. Using this innovative technology, 172 compounds were tested and a surprisingly low correlation between migration and growth inhibition was found. Notably, many compounds were found to inhibit migration of most cells while leaving fast-moving subpopulations unaffected. This work further pinpoints synergistic drug combinations, including Bortezomib and Danirixin, to stop fast-moving cells. To explain the observed cell behaviors, single-cell morphological and molecular analysis were performed. These studies establish a novel technology to identify promising migration inhibitors for cancer treatment and relevant applications.