bluuebunny/crossref_metadata_2025 huggingface dataset:
Deodorants and antiperspirants: identification of new strategies and perspectives to prevent and control malodor and sweat of the body
Authors: Oliveira Erika C. V. de , Salvador Danielle S. , Holsback Valéria , Shultz Jemima D. , Michniak‐Kohn Bozena B. , Leonardi Gislaine R.
Published: March 2021

Excessive sweating and body odors in many cultures can cause negative perceptions of an individual and in many cases is related to poor hygiene. Personal hygiene products have been developed with the intention of preventing these undesirable issues. The aim of this paper is to review the main active ingredients used in marketed deodorant and antiperspirant formulations as well as to identify new strategies and future methods to optimize such products and prevent malodor. PubMed and ScienceDirect databases were used to search for studies reporting the use of deodorants and antiperspirants, the compounds used in the formulations, their mechanisms of action and associated controversies, as well as new trends and approaches in the area. Even today, we are still using well‐known and established actives such as triclosan and aluminum salts, and these are still the most used compounds in deodorants with bactericidal and antiperspirant properties. These substances have been on the market for more than 40 years, and still there are many questions concerning the safety of both actives. There is a general increased interest globally for lifestyles that focus on sustainability and more natural products such as plant sources and the use of, for example, essential oils. The research that focuses in the area of antiperspirants and deodorants is now more focused on studies of the armpit biochemistry and function and control of the microbiota present in this area. Other possible areas of interest are biotechnological solutions and finding new compounds that will interfere with the biochemistry of the process of sweat decomposition. Further approaches include formulations with probiotics which would maintain the balance of axillary microbiota.
How do hospitals help patients prepare for and participate in outpatient clinics?
Authors: Chieng Michael , Southwell Thomas , Shand George , Humphries Aimee , Heap Naomi , Chapman Laura
Published: March 2021

Background

Patients attending general medicine outpatient clinics (GM OPC) at hospital face multiple healthcare demands in an environment that has evolved with the clinician at its centre. The ideas, knowledge and understanding that patients bring to their clinic appointments are not well studied in the New Zealand setting.

Aims

To assess how hospitals prepare patients for their outpatient appointments and encourage people to participate actively in their own care.

Methods

A prospective survey of 50 patients attending follow‐up GM OPC was performed. Participants’ understanding of the purpose of their appointment and knowledge of their prescription medications was explored using a nine‐item questionnaire. Patient‐directed hospital communication was then analysed to assess the information supplied to patients.

Results

Two‐thirds (66%) of participants attending follow‐up GM OPC recalled being informed of an appointment at the time of leaving hospital; only half (54%) felt they had been informed of the purpose of these appointments. Patient‐directed communication was not completed in half (50%) of the analysed discharge letters. One‐third (36%) of participants did not have specific questions for their clinic visits.

Conclusions

Limited information and support is provided to patients attending follow‐up GM OPC and is not tailored to individuals’ health literacy. This practice assumes patients have comparable health literacy to clinicians, which may have downstream impacts on the usefulness of the clinic experience. The information that health users bring to clinic may be improved by increasing pre‐clinic user engagement and deploying patient‐centred tools within the healthcare environment.
Clarifying the connection between parental conditional regard and contingent self‐esteem: An examination of cross‐lagged relations in early adolescence
Authors: Otterpohl Nantje , Bruch Samira , Stiensmeier‐Pelster Joachim , Steffgen Teresa , Schöne Claudia , Schwinger Malte
Published: March 2021

Objective

Relations between parental conditional regard (PCR) and children's motivational and emotional functioning have been demonstrated by past research. However, most available studies relied on cross‐sectional correlational data, leaving open the causal direction of these relations. In the present article, we sought to contribute to this topic and examined the longitudinal connection between PCR and adolescents' contingent self‐esteem (CSE) over time.

Method

Hypotheses were tested in two longitudinal studies with differently gifted samples of German high school students (N = 188 andN = 202 students, respectively). Data were gathered at three time points in Study 1 and at two time points in Study 2. In both studies, adolescents answered questionnaires regarding positive and negative PCR in the academic domain as well as general CSE (and additionally academic CSE in Study 2).

Results

Cross‐lagged analyses revealed several significant paths from CSE to PCR, and some paths from PCR to CSE, indicating the presumed reciprocal relationship between these constructs.

Conclusions

Our findings suggest that children high in CSE may lead their parents to engage in PCR and that these effects may be more pronounced than vice versa. Possible reasons for these findings and their implications are discussed.
Effects of enriched environment on micturition activity in freely moving C57BL/6J mice
Authors: Soeda Fumio , Toda Akihisa , Masuzaki Kazuya , Miki Risa , Koga Takayuki , Fujii Yukiko , Takahama Kazuo
Published: March 2021

Objectives

An enriched environment (EE) has been known to promote structural changes in the brain and enhance learning and emotional performance. However, little is known about the effect of an EE on brain stem functions, such as the micturition function. In this study, we examined whether an EE affects micturition activity in mice.

Methods

Male C57BL/6J mice were used. We assessed the micturition activity of freely moving mice using a novel system developed in‐house.

Results

During the dark period, but not light, the EE significantly increased voiding frequency, total voided volume, mean voided volume, voiding duration, mean flow rate, and maximum flow rate compared with the control environment. This EE effect on micturition function was associated with habituation to novel environments in the open‐field test, but not with amelioration of motor coordination in the rotarod test. Interestingly, even after the mice were withdrawn from the EE, the improvements in micturition function persisted, while other behavioral changes were abolished. The relative value of voiding frequency and total voided volume during the light period, expressed as a percentage of 24 hours, increased with age when mice were reared in a standard environment. However, this age‐related change was not observed in mice reared in an EE.

Conclusions

These results suggest that an EE may promote micturition activity during the active phase of C57BL/6J mice, and its effects persist even after withdrawal from the EE. Furthermore, an EE may mitigate dysfunctions in micturition activity, such as polyuria, during the resting phase in aged mice.
Significant decrease in delirium referrals after changing hypnotic from benzodiazepine to suvorexant
Authors: Tachibana Masako , Inada Toshiya , Ichida Masaru , Kojima Shihori , Arai Takafumi , Naito Keiko , Ozaki Norio
Published: March 2021

Background

The use of benzodiazepines (BZDs) causes delirium, especially in elderly people. For this reason, suvorexant has been recommended as the first‐line hypnotic in elderly patients. The aim of this study was to determine whether the first‐line use of suvorexant, instead of BZDs, decreases referrals for delirium in elderly patients.

Methods

Since May 2016 at Nagoya Ekisaikai Hospital, suvorexant has been recommended as the first‐line hypnotic instead of BZDs. In May 2017, suvorexant was adopted as the first‐line hypnotic. The number of delirium cases referred to psychiatry was compared among three consecutive periods: period A (May 2015–April 2016), during which BZDs were mainly used for insomnia; period B (May 2016–April 2017), during which the use of suvorexant was recommended instead of BZDs; and period C (May 2017–April 2018), during which suvorexant was principally adopted as the first‐line hypnotic for insomnia. Potential confounding factors that may affect the development of delirium were also examined during the three periods.

Results

The number of delirium referral cases in elderly patients in each period decreased, from 133 in period A to 86 in period B and 53 in period C. The rate of delirium referral cases decreased significantly every year (P = 9.02 × 10−10). Almost no significant confounding factors other than hypnotics were detected during the three periods.

Conclusion

The referrals for delirium in elderly patients decreased significantly after the hypnotic was changed from BZDs to suvorexant.
Withdrawal of the multifibre agreement and Indian textile industry: Concerns, efforts, and achievements
Authors: Bhandari Anup Kumar
Published: March 2021

Multifibre agreement (MFA)–endorsed safe textile export markets were abolished in 2005. For India, scholars anticipated both enormous potential gain from the post‐MFA free market and the threat of inevitably increasing competition. Researchers also emphasized selected channels to succeed, including effective exploitation of scale economies and technological upgradation, for fruitful market gain in this regard. Against this backdrop, we study the Indian textile industry from 1999–2000 through 2014–2015 to examine (1) the role of economies of scale to achieve efficiency gain and therefore competitiveness, (2) the industry's efforts toward technological upgradation, and (3) its overall sustainability through net export expansion, profitability, and total factor productivity (TFP) growth. Results show that (1) size‐efficiency nexus is positively significant and therefore the industry can achieve further efficiency gain and competitiveness by expanding scale of operations at the firm level; (2) despite considerable increase in R&D investments, the industry's overall production technological status has deteriorated in the post‐MFA regime and therefore has substantial scope of improvement, possibly through more effectively using the prevailing technological upgradation funds scheme (TUFS) and other official arrangements; and (3) although India achieves sizeable net export expansion and TFP gains, the industry's profitability scenario seems bleak and requires further attention for its better sustainability.
Association between the use of Antidepressants and the Risk of Preterm Birth among Pregnant Women with Depression: A Retrospective Cohort Study in Taiwan
Authors: Chen Li-Fen , Lin Ching-En , Chung Chi-Hsiang , Lai Ching-Huang , Chien Wu-Chien
Published: March 2021

Our study was aimed to investigate the association between the use of antidepressants and the risk of preterm birth in pregnant women who have had perinatal depression. We extracted data from the Taiwanese National Health Insurance Research Database (NHIRD) and analyzed them using multivariate Cox proportional hazard regression models. Identified from the NHIRD, we matched 1789 women aged 18-55 years who were using antidepressants during pregnancy and 1789 women who were experiencing depression but who were not using antidepressants during pregnancy for age, index date, and medical comorbidities. We enrolled the women in our study, which we conducted using 12 years’ worth of data between 2000 and 2012, and then followed up individually with them for up to 1 year to identify any occurrence of preterm birth. Results highlighted that, compared with the women with perinatal depression who were not using antidepressants during pregnancy, the women taking antidepressants had a 1.762-fold risk of preterm birth (adjusted HR=1.762, 95% CI 1.351 to 2.294, p<0.001). The use of antidepressants in women with perinatal depression may increase the risk of preterm birth. However, the decision to start, stop, or change the use of antidepressants during pregnancy requires evaluating the risks of treatment versus untreated depression for both mother and child.
Fabrication of three bio-adsorbents from different parts of rape straw
Authors: Xie Juan , Liu Biao , Wang Hu
Published: March 2021

Three kinds of bio-adsorbents are fabricated from the different parts of rape straw, which are adsorbent core, adsorbent hull, and adsorbent stalk, respectively. As the adsorbates, kerosene, paraffin, rapeseed oil, and dibutyl phthalate are employed to evaluate the adsorption performance of the three kinds of bio-adsorbents. The results suggest that adsorbent core has much higher adsorption quantity to all the four adsorbates (27.37, 32.23, 33.37, and 39.28 g/g, respectively) than adsorbent hull (7.39, 8.37, 8.85, and 10.30 g/g) and adsorbent stalk (6.75, 7.25, 7.92, and 9.32 g/g). The adsorption mechanism of the three bio-adsorbents is investigated. The results illustrate that different bio-adsorbents own different micromorphologies. The special microchamber structure is found in the bio-adsorbent of the adsorbent core, which is seen as the main reason for its excellent adsorption performance. The adsorption volume of unit mass (Va) was proposed to evaluate the intrinsic adsorption properties of the bio-adsorbents. The recovery performance of the bio-adsorbents is investigated by using of two different treatment methods. The effect of treatment on recovery rate is discussed.
Modeling and Controlling the Dynamic Behavior of an Aerial Manipulator
Authors: Ali Zain Anwar , Xinde Li
Published: March 2021

Unmanned Aerial Vehicles (UAVs) installed with a gripper is an effective and robust way to grab the wanted object from inaccessible locations. In this study, we develop a novel control mechanism to regulate the nonlinear dynamics of the aerial manipulator. In this research, hex-rotor UAV is chosen in order to fulfill the mission requirement in terms of size and weight of the object. It is equipped with a manipulator and the gimbal-based camera that will help to see the desired object and then transport it. The aerial vehicle has six-degrees-of-freedom (6-DOF) and the installed manipulator has 4-DOF which in total makes the 10-DOF aerial manipulator vehicle. At the time of clutching the desired object to eliminate or reduce the external noise, and stabilize the dynamic behavior of the aerial manipulator, we need a robust and efficient controller. To solve the aforementioned problems, this study develops a hybrid control mechanism that tracks and controls the altitude and attitude of UAV after clutching the desired object. The main contribution of this study is to design a control mechanism that includes Model Reference Adaptive Control with an Integrator (MRACI) in conjunction with regulation, pole-placement and tracking (RST) control algorithm. On one hand, the simulation results using MATLAB demonstrate the efficiency of the proposed control mechanism. On the other hand, to cross verify the validity of the proposed control algorithm, we perform the experiment by clutching the desired object at hovering and normal flight operation.
Local densities of diagonal integral ternary quadratic forms at odd primes
Authors: Jones Edna
Published: March 2021

We give formulas for local densities of diagonal integral ternary quadratic forms at odd primes. Exponential sums and quadratic Gauss sums are used to obtain these formulas. These formulas (along with 2-adic densities and Siegel’s mass formula) can be used to compute the representation numbers of certain ternary quadratic forms.
Construction of several classes of maximum codes
Authors: Lv Mengxin , Hu Xiaomin , Yang Weihua
Published: March 2021

Let [Formula: see text] be the size of the maximum binary code of length [Formula: see text] and minimum Hamming distance [Formula: see text]. [Formula: see text] is defined similarly for binary code with constant weight [Formula: see text]. Obviously, finding the value of [Formula: see text] is equivalent to finding the maximum independent set of the [Formula: see text]th-power of [Formula: see text]-dimensional hypercube. Based on this, this paper obtains that [Formula: see text], [Formula: see text], [Formula: see text], and explores the structure of the maximum code of length [Formula: see text] and minimum Hamming distance [Formula: see text], where [Formula: see text] is an integer.
The Carboniferous chronostratigraphic scale: history, status and prospectus
Authors: Lucas Spencer G. , Schneider Joerg W. , Nikolaeva Svetlana , Wang Xiangdong
Published: March 2021

The Carboniferous chronostratigraphic scale is a hierarchy of two subsystems, six series and seven stages developed during nearly two centuries of research. Carboniferous stage nomenclature developed with the proposal of numerous regional stages/substages based primarily on palaeobotanical, foraminiferal and ammonoid biostratigraphy, especially in Western Europe, the former Soviet Union, China and the USA. From the regional stages, seven ‘global stages’ have been identified (in ascending order): Tournaisian, Visean, Serpukhovian, Bashkirian, Moscovian, Kasimovian and Gzhelian. Three of the four ratified Carboniferous GSSPs use conodont evolutionary events as the primary signal for correlation – bases of Tournaisian, Bashkirian and base of Asselian. The GSSP of the Visean base has a foraminiferal event as its primary signal. Issues in the development of a Carboniferous chronostratigraphic scale include the rank of chronostratigraphic units, provinciality, conodont biostratigraphy, palaeobotanical biostratigraphy and the development of astrochronology and other methods of chronology and correlation.
Which Holds the Key to BRCAness: Inability to Repair the Break, Protect the Fork, or Prevent the Gap?
Authors: Canman Christine E.
Published: March 2021

Defects in genes crucial for the process of DNA repair by homology-directed DNA repair (HDR), such as BRCA1 and BRCA2, are well-known contributors to cancer pathogenesis as well as an Achilles' heel that can be exploited therapeutically. BRCA1/2-deficient cells are exquisitely sensitive to agents that stall replication forks, such as PARP inhibitors and platinating drugs, presumably due to the inability to repair double-stranded breaks that form as a consequence of replication fork collapse. BRCA1/2 also promote tolerance to DNA replication stress by protecting replication forks from nucleolytic degradation. Both biological endpoints involve the deposition of RAD51 onto single-stranded DNA (ssDNA) for homology searching and strand exchange during HDR repair, as well as protection of newly synthesized DNA from nucleolytic degradation (i.e., replication fork protection). In this issue of Cancer Research, Panzarino and colleagues performed multiple separation-of-function studies and identify the lesion most associated with intolerance to replication stress in BRCA1/2-deficient cells is persistent ssDNA gaps in newly synthesized DNA, resulting from a failure to restrain DNA replication. Mechanisms that suppress gap formation are closely associated with chemoresistance, and the authors’ findings challenge the paradigm that lack of HR repair or fork protection underlie the phenotype known as BRCAness.

See related article by Panzarino et al., p. 1388
Targeting EYA3 in Ewing Sarcoma Retards Tumor Growth and Angiogenesis
Authors: Wang Yuhua , Pandey Ram Naresh , Roychoudhury Kaushik , Milewski David , Kalin Tanya V. , Szabo Sara , Pressey Joseph G. , Hegde Rashmi S.
Published: March 2021

EWSR1/FLI1, the most common fusion gene in Ewing sarcoma, upregulates expression of the Eyes Absent 3 (EYA3) transactivator–phosphatase protein. The purpose of this study was to investigate molecular and cellular mechanisms through which EYA3 might promote Ewing sarcoma tumor growth and to determine whether the EYA3 tyrosine phosphatase activity represents a viable therapeutic target. We used genetic and pharmacologic modulation of EYA3 in cell line–based xenografts to examine how loss of EYA3 tyrosine phosphatase activity affects tumor growth and angiogenesis. Molecular mechanisms were evaluated in vivo and in vitro through analyses of tumor tissue and multicellular tumor spheroids. Our results show that both loss of EYA3 in Ewing sarcoma cells and pharmacologic inhibition of the EYA3 tyrosine phosphatase activity inhibit tumor growth and tumor angiogenesis. EYA3 regulates levels of VEGFA in Ewing tumors, as well as promoting DNA damage repair and survival of Ewing sarcoma tumor cells. Target engagement is demonstrated in tumor tissue through elevated levels of the EYA3 substrate H2AX-pY142 upon loss of EYA3 or with Benzarone treatment. The efficacy of EYA3 tyrosine phosphatase inhibition in attenuating tumor growth and angiogenesis is corroborated in an Ewing sarcoma patient-derived tumor xenograft. Together, the results presented here validate EYA3 as a target for the development of novel Ewing sarcoma therapeutic strategies, and set the stage for evaluating the efficacy of combining the antiangiogenic and anti-cell survival effects of EYA3 inhibition with cytotoxic chemotherapy.
Abstract IA008: Age-related stromal changes drive tumorigenesis
Authors: Stewart Sheila A
Published: March 2021

The stromal compartment plays a pivotal role in tumor progression. This is best illustrated in breast cancer bone metastases, where the stromal compartment supports tumor growth, albeit through poorly defined mechanisms. p38MAPKa is frequently expressed in tumor cells and surrounding stromal cells and its expression levels correlate with poor prognosis. Using a clinically relevant breast cancer metastasis model, we show that orally administered, small-molecule inhibitors of p38MAPKa or its downstream kinase, MK2, each limited outgrowth of metastatic breast cancer cells in the bone and visceral organs. Further we find that this effect is primarily mediated by inhibition of the p38MAPKa pathway within the stromal compartment. Beyond effectively limiting metastatic tumor growth, we also find that these inhibitors reduce tumor-associated and chemotherapy-induced bone loss, which is a devastating comorbidity for cancer patients that drastically impact their quality of life. Interestingly we find that p38MAPKa’s ability to limit tumor growth within the bone is dependent on CD4 T cells while MK2 does not require these cells to limit tumor progression, demonstrating that it is not a straightforward pathway. To determine which cell types within the bone contribute to tumor growth and bone loss, we have carried out single cell RNA-sequencing of stromal cells located within the bone metastatic lesion and cells outside the lesion. We find numerous differences that could explain how the stromal compartment contributes to tumor progression and bone loss and how inhibition of p38MAPKa or MK2 contribute. These data underscore the vital role stromal-derived factors play in tumor progression and identify the p38MAPK-MK2 pathway as a promising therapeutic target for metastatic disease and prevention of tumor-induced bone loss.

Citation Format: Sheila A Stewart. Age-related stromal changes drive tumorigenesis [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr IA008.
Abstract PO013: Blood-brain barrier dysfunction leads to neuronal loss in glioma pathology
Authors: Mata-Martínez Pablo , Segura-Collar Berta , Garranzo-Asensio Maria , Sepúlveda-Sánchez Juan M. , Hernández-Lain Aurelio , Sánchez-Gómez Pilar , Gargini Ricardo
Published: March 2021

The blood-brain barrier (BBB) defines the physiological function of the brain. Its disruption is common in multiple neuropathological diseases. Accumulating evidence suggest that BBB alterations occur in early stages of neurodegenerative diseases, being associated with neuronal loss processes. The vascular abnormalities and BBB leakage characterize the progression of gliomas, however it is unclear their correlation with the neurodegeneration observed in such tumors.

Methods: To establish the different gene signatures we have performed an in-silico analysis using glioma data sets and we have validated the results in a cohort of 26 gliomas (high and low grade) and 7 controls from non-tumor donors. We have also used patient-derived xenografts (PDXs) to correlate the degree of BBB disruption (measured by IgG extravasation immunofluorescence staining) with the neuronal loss (evaluated by NeuN immunofluorescence staining) and with the motor impairment (assessed by a rotarod test). Results: We measured the expression of a series of signatures associated with different biological processes, relevant for glioma development. The “Synapse” and the “BBB dysfunction” signatures were inversely correlated during glioma development. Thus, the most aggressive tumors were associated with BBB breakdown and neuronal dysfunction. These phenotypes correlate with the mesenchymal subtype of gliomas and with a shorter survival. The vascular normalization induced by the isocitrate dehydrogenase 1 (IDH1) mutations rescued the neuronal loss, reducing the motor impairment and increasing the overall survival of PDX-bearing mice. Conclusions: Our data demonstrate that vascular normalization can revert the neuronal loss and the aggressiveness in those tumors, which is linked to the appearance of motor dysfunction symptoms. Overall, we propose that disruption of the BBB is associated with neurodegeneration in glioma patients. These results could help us to understand the progression of this pathology as well as other neurodegenerative diseases and therefore to improve their therapeutic approaches.

Citation Format: Pablo Mata-Martínez, Berta Segura-Collar, Maria Garranzo-Asensio, Juan M. Sepúlveda-Sánchez, Aurelio Hernández-Lain, Pilar Sánchez-Gómez, Ricardo Gargini. Blood-brain barrier dysfunction leads to neuronal loss in glioma pathology [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO013.
Abstract PO045: Impact of fibroblast mediated stromal protection on evolution of resistance to targeted therapies in NSCLC
Authors: Desai Bina
Published: March 2021

BACKGROUND: Clinical introduction of tyrosine kinases inhibitors (TKIs) for ALK+ non-small cell lung cancer (NSCLC) has improved patient survival, but it did not translate into cures as acquired resistance inevitably emerges in patients with advanced and metastatic cancers. Cancer associated fibroblasts (CAFs) have emerged as the major determinant of environmental protection. While the ability of stroma to protect tumor cells from TKI is well documented in-vitro, whether the impact of stromal protection is relevant in 3D context and in-vivo remains unresolved. Thus, we hypothesized that stromal protection impacts the initial response of tumor cells to targeted therapies.

METHODS: Cancer cell lines were cultured in presence of CAF conditioned media (CM) and treated with TKIs to monitor cell viability. To interrogate molecular mechanism, loss and gain of function experiments were performed using pharmacological inhibitors and recombinant human protein respectively. To address the relevance of stromal protection in-vivo, we worked with tumor xenograft mouse model. We also used mathematical modelling to understand the tumor dynamics, using inferences from xenograft mouse models to build agent-based models.

RESULTS: We observed that patient derived matched normal tissue associated fibroblast (NAFs) and CAFs, both confers various level of protection to tumor cells against TKIs. Addition of rh Hepatocyte growth factor (HGF) protein mimicked the effect of CAF CM and addition of small molecule inhibitors of cMET abolished the CAF-mediated protection to tumor cells against TKIs. Our xenograft experiment showed the significant increase in stroma/tumor ratio during the initial tumor response to targeted therapy and we observed increase in tumor proliferating cells in proximity to stroma. Our math model for stroma and pre-existing resistant population showed delay in development of resistance to TKI.

CONCLUSION: Fibroblast-mediated stromal protection is critically dependent on HGF-cMET axis. Dual inhibition of ALK and MET signaling abolished the fibroblast-mediated protection and increased the cell sensitivity to ALK TKIs, suggesting the crucial role of microenvironment-mediated resistance in NSCLC. To study tumor dynamics using mathematical models, we addressed that space could be key to understand the impact of stromal protection in-vivo. Our study shows that understanding the signaling changes carried by fibroblast in response to therapy may lead to potential better combination therapy.

Citation Format: Bina Desai. Impact of fibroblast mediated stromal protection on evolution of resistance to targeted therapies in NSCLC [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO045.
Abstract PO047: Sensory nerves enhance breast cancer migration through PlexinB3 signaling
Authors: Le Thanh T. , Oudin Madeleine J.
Published: March 2021

The tumor microenvironment plays an essential role in the process of metastasis. However, the role of the peripheral nervous system, a crucial component of the tumor microenvironment, in cancer progression remains poorly understood. In breast cancer, nerve presence has been correlated with more invasive disease and worse prognosis. Yet, there is still a lack of detailed investigation into the specific types of nerves that are present in breast cancer as well as the mechanism by which nerve-cancer crosstalk contributes to breast cancer metastasis. We identified sensory nerves as more abundant in triple-negative human breast cancer tumors relative to healthy breast by mining gene expression datasets and immunostaining. Interestingly, the sensory nerve bundle structure in normal breast is disrupted in breast tumor, resulting in discrete nerve fibers throughout the tumor. To investigate the role of these sensory nerves in cancer progression, we cocultured primary sensory neurons from dorsal root ganglia of mice and human triple-negative breast cancer cells (MDA-MB-231). We found that cancer cells tend to attach and move along nerve fibers. These cells also have higher migration speed and proliferation rate when compared to both monoculture and conditioned media control. We then set out to investigate whether sensory nerves impact gene expression in tumors using RNA sequencing. By utilizing published algorithms, we were able to separate the transcriptome of human cancer cells and mouse neurons in coculture. Differential analysis shows that cancer cells in coculture upregulate genes related to cell migration, adhesion, and proliferation pathways, which further validates our experimental findings. We identified the Sema5A-PlexinB3 ligand-receptor pair as a potential mechanism of nerve-cancer crosstalk, where neurons provide Sema5A that interacts with upregulated PlexinB3 receptors on cancer cells. Knockdown of Plexin-B3 in tumor cells reduced the effect of sensory nerves on breast cancer cell migration. In vivo experiments injecting sensory nerves and tumor cells into the mammary gland of mice are ongoing. Overall, these studies demonstrate that sensory nerve density is high in TNBC and that sensory nerves promote tumor cell migration and proliferation via direct cell-cell interactions. We also show for the first time that nerves can induce gene expression changes in cancer cells. In the long-term, these findings could lead to novel treatments for metastatic disease that target nerve-cancer crosstalk.

Citation Format: Thanh T. Le, Madeleine J. Oudin. Sensory nerves enhance breast cancer migration through PlexinB3 signaling [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO047.
Abstract IA-06: Artificial intelligence in cancer imaging
Authors: Aerts Hugo
Published: March 2021

Medical imaging in oncology has traditionally been restricted to the diagnosis and staging of cancer. But technological advances in Artificial Intelligence (AI), deep learning in particular, are moving imaging modalities into the heart of patient care. Imaging can address a critical barrier in precision medicine as solid tumors can be spatial and temporal heterogeneous, and the standard approach to tumor sampling, often invasive needle biopsy, is unable to fully capture the spatial state of the tumor. Radiomics refers to the automatic quantification of this radiographic phenotype. Radiomic methods heavily rely on AI technologies to quantify phenotypic characteristics that can be used to develop non-invasive biomarkers. In this talk, Dr. Aerts will discuss recent developments from his group and collaborators performing research at the intersection of radiology, bioinformatics, and data science. Also, he will discuss recent work of building a computational image analysis system to extract a rich radiomics set and use these features to build radiomic signatures. The presentation will conclude with a discussion of future work on building integrative systems incorporating both molecular and phenotypic data to improve cancer therapies.

Citation Format: Hugo Aerts. Artificial intelligence in cancer imaging [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-06.
Abstract IA-10: Machine learning enabled analysis of high content imaging datasets: Progress and prospects
Authors: Sultan Mohammad Muneeb
Published: March 2021

In the last decade deep learning has had a very large impact in the field of image analysis. In this talk, I will discuss several vignettes into how deep learning when applied to biomedical imaging datasets can provide us with insights that can further drug discovery campaigns and uncover new biological insights. In particular, I will show how deep learning can learn a phenotypic manifold that allows us to interrogate the dose response behavior of compounds, measure the phenotypic similarity of compounds, and deconvolute MOAs of new compounds.

Citation Format: Mohammad Muneeb Sultan. Machine learning enabled analysis of high content imaging datasets: Progress and prospects [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-10.
Abstract IA-12: Functional analysis of BRCA regulatory variants with deep learning models
Authors: Troyanskaya Olga
Published: March 2021

Precision medicine in oncology depends on identifying variants that are functional and interpreting them in terms of cancer disease risk, treatment guidance, and prognosis. This is especially challenging for regulatory variants, which constitute the majority of the genome and control transcription and RNA processing. We use state-of-the-art deep learning models that predict the molecular impact of variants to systematically analyze genomes and SNPs and discover BRCA-associated SNPs that impact transcriptional and post-transcriptional regulation of gene expression, identify genes and biological processes implicated across tissues of impact, and reconcile these findings with prior genomic annotation-based analysis.

Citation Format: Olga Troyanskaya. Functional analysis of BRCA regulatory variants with deep learning models [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-12.
Abstract IA-26: Artificial intelligence for regulatory science research
Authors: Tong Weida
Published: March 2021

Artificial Intelligence (AI) has impacted a board range of scientific disciplines that are important to public health, ranging from clinical diagnosis and prognosis, drug and food safety, disease prevention, precision medicine and nutrition. The rise of AI has also offered both opportunities and challenges to regulatory agencies with questions such as (1) how to assess and evaluate AI-based products and (2) how to develop and implement AI-based application to improve the agencies functions. In this presentation, the current thinking and on-going efforts at FDA in the area of AI will be discussed with examples from drug safety and biomarker discovery and development. The guiding principle and best practice of applying AI in regulatory science research will also be discussed with respect to a proposed framework, called TRIAL, for AI transparency, reproducibility, interpretability, applicability and liability.

Citation Format: Weida Tong. Artificial intelligence for regulatory science research [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-26.
Abstract PO-010: Feature pyramid network for revealing tumour infiltrating lymphocyte presence and distribution in a whole slide image
Authors: Mazurski Jonathan , Nofech-Mozes Sharon , Bassiouny Dina , Martel Anne L.
Published: March 2021

Ductal Carcinoma in Situ (DCIS) is a subtype of non-invasive breast cancer contained in the ducts of the breast. DCIS is not a life-threatening condition however a small number of cases will progress to or reoccur as invasive breast cancer. Clinical workflows lack a robust biomarker to determine which patients will reoccur. Recently pathologists have turned towards investigating the tumour microenvironment to predict cancer recurrence. Machine learning models present an opportunity to analyze these features on large amounts of data with minimal requirement of pathologist time. One feature of recent interest are Tumour infiltrating lymphocytes or TILs, lymphocytes within a small region around a cancerous duct. Through a method of bootstrapping a U-Net on top of a fully convolutional network we have designed a network that is able to segment lymphocyte and malignant cells in H&E Images of Ductal Carcinoma In Situ. The original network was trained on a private set of cellularity data in breast cancer, manually annotated by pathologists to mark the centre and type of each cell in a patch. Probabilistic output from this model was used to generate segmentation maps on a much larger dataset of DCIS images from the Ontario DCIS Cohort. These segmentation maps were used as training data for a feature pyramid network. The results of this bootstrapping method was a significant increase to speed of the model in addition to much larger flexibility in the input size and shape for the model, which came at a small cost to overall model accuracy. In addition to the original segmentation target, the use of this model to generate lower resolution WSI heat-maps has been investigated for this work. This model can generate low resolution heat-maps for a 20X magnification whole slide image showing the presence of malignant cells in addition to the location and distribution of TILs around ducts. This can provide a visual overview of differences between slides and we will be examining the potential for this output to serve as information for analytical methods to process to predict recurrence free survival.

Citation Format: Jonathan Mazurski, Sharon Nofech-Mozes, Dina Bassiouny, Anne L. Martel. Feature pyramid network for revealing tumour infiltrating lymphocyte presence and distribution in a whole slide image [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-010.
Abstract PO-016: Seeing glycolysis on PDAC: Applying deep learning convolutional neural network model
Authors: Tsou Peiling , Wu Chang-Jiun
Published: March 2021

The reprogramming of cellular metabolism to support continuous proliferation is a hallmark of cancer. Accumulating evidence indicates that the reprogramming of tumor metabolism is under the control of various oncogenic signals. The KRAS oncogene is known to induce aerobic glycolysis, and pancreatic adenocarcinoma (PDAC) cells have been shown previously to have metabolism consistent with elevated aerobic glycolysis. Survival analysis showed that higher glycolysis activity was associated with worse clinical outcome in TCGA PDAC. Several glycolytic inhibitors are currently in preclinical and clinical development. It had been reported that cancer metabolic status could play a role in the interaction with tumor microenvironment. We hypothesized that cancer glycolysis activity could affect tumor histopathological architecture in PDAC. As a proof-of-concept study, we trained a deep learning convolutional neural network (CNN) model (Google Inception v3) on histopathological images obtained from TCGA PAAD cohort to classify tumors with high and low glycolysis pathway activity. We aimed to answer whether CNNs can predict PDAC glycolysis status using images as the only input. Our model was tested on separate tissue samples from the same cohort. Aggregated accuracy was 75% on 48 cases with area under ROC curve as 0.751. Prediction scores significantly correlated with transcriptome-based glycolysis signature (Pearson correlation = 0.352, p=0.007). The current study demonstrates the potential of deep learning approaches for histopathologically classifying cancer based on metabolic status. This information could be of value in assisting clinical decisions on targeting cancer metabolism.

Citation Format: Peiling Tsou, Chang-Jiun Wu. Seeing glycolysis on PDAC: Applying deep learning convolutional neural network model [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-016.
Abstract PO-022: Automated liver tissue segmentation in point of care ultrasound b-mode images using U-Net
Authors: Garcia Raul Blazquez , Lightstone Adi , Ibrahim Miriam Naim , El Kaffas Ahmed
Published: March 2021

Introduction/Purpose: We have recently developed and demonstrated that tissue acoustic properties can facilitate early detection of liver cancer during period abdominal ultrasound surveillance exams in high risk patients. Automated segmentation of the liver is a necessary step in increasing the accuracy, sensitivity, and specificity of Machine Learning Models which detect cancer using the lower quality data generated from Point-of-Care Ultrasound (PoCUS). We have developed deep learning algorithms which can successfully segment the data generated by these PoCUS systems. Methods: A total of 1000 patients from 4 collaboration sites were recruited, though for this study only 25 of which were manually segmented were used.. For this HIPPA compliant study, all data was obtained through IRBs approved at the local data acquisition site; all patients were consented before data acquisition. The patient's mean age and BMI were 43(11 STD) and 23 (5 STD). All patients were scanned using the same acquisition protocol, capturing the same 5 scan visualization windows of the liver using a PoCUS system, with capabilities to capture raw signal data. We use a deep learning algorithm to automatically segment out the liver. The initial version of the U-net Deep learning architecture was trained on a subset of our data containing B-mode images from 20 patients (500 frames) and tested on a dataset with 5 patients (125 frames). The Regions of interest that served as training and testing labels for the algorithm were outlined on an image-by-image basis by expert sonographers. U-Net is a fully convolutional neural network that consists of a block of contraction layers followed by a block of expansion layers. The architecture contains feature channels to relay context information to higher resolution layers. U-Net has been used at multiple medical segmentations tasks in which it performs particularly well even with small datasets. Results: The architecture successfully segmented the images both in the train and test datasets with a great degree of accuracy and generalization. Test accuracies surpassed 86% with a sensitivity of 80% and specificity of 95% and results can be further improved by applying thresholds to the algorithm’s output. Conclusion: This automated segmentation algorithm is a clear next step in the improvement of any automated disease detection method in the liver. Once in place it will greatly aid in the early screening of all liver diseases and improve the outcomes for at risk patients.

Citation Format: Raul Blazquez Garcia, Adi Lightstone, Miriam Naim Ibrahim, Ahmed El Kaffas. Automated liver tissue segmentation in point of care ultrasound b-mode images using U-Net [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-022.
Abstract PO-033: The impact of the variation of CT scanner on the prediction of HPV status in head & neck cancer patients
Authors: Reiazi Reza , Arrowsmith Collin , Abbas-Aghababazadeh Farnoosh , Eles Christopher , Rezaie Aria , Bratman Scott V. , Hope Andrew J. , Haibe-Kains Benjamin
Published: March 2021

Radiomics involves the use of high-dimensional quantitative imaging features for predictive purposes. However, studies showed that these radiomic features are sensitive to the variability of imaging parameters (e.g., scanner model). One of the major challenges in radiomics lies in improving the robustness of quantitative features against the variation in the imaging dataset in multi-center studies. Here, we assess the impact of scanner choice on the computed tomography (CT)-derived radiomic features to predict association of oropharyngeal squamous cell carcinoma with human papillomavirus (HPV), which has a well-established impact on CT-derived radiomic features. This experiment was performed on CT image datasets acquired with two different scanner types. We demonstrate strong scanner dependency by developing a machine learning model to classify HPV status from radiological images. These experiments revealed the effect of scanner type on the robustness of the radiomic features, and the extent of this dependency is reflected on the performance of HPV prediction models. The result of this study highlighted the importance of implementing an appropriate approach to reduce the impact of the imaging domain radiomic features and consequently on the machine learning models.

Citation Format: Reza Reiazi, Collin Arrowsmith, Farnoosh Abbas-Aghababazadeh, Christopher Eles, Aria Rezaie, Scott V. Bratman, Andrew J. Hope, Benjamin Haibe-Kains. The impact of the variation of CT scanner on the prediction of HPV status in head & neck cancer patients [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-033.