Processing Machinery Research Articles

Operational Performance Evaluation Model for Food Processing Machinery Industry Chain

This study aims to create a performance evaluation model for the food processing machinery industry. The goal is to help food processing plants improve both process quality and competitiveness. Additionally, component failures may disrupt the continuous operation of the food processing machine, potentially resulting in insufficient production and delays in delivery, which in turn leads to cost losses. For the sold food processing machinery, decreases in the average number of failures within a unit of time, the average repair response time when a failure occurs, and the average repair duration are three crucial factors in minimizing the total expected loss due to machine failures. Based on these three important factors, this study established the following evaluation indices: (1) the processing performance index, (2) the repair reporting performance index, and (3) the maintenance performance index. These indices serve as tools for assessing the performance of the three key operational aspects. This study employed a radar chart to construct the evaluation model, which can directly compare the critical values with the point estimates of three indices. Consequently, this approach can judge whether the operational performance has achieved the required level. This can maintain the simplicity and usability of point estimates while reducing the risk of misjudgment due to sampling errors.

Integrating single cell and bulk RNA sequencing data identifies RBM17 as a novel response biomarker for immunotherapy in bladder cancer.

Checkpoint inhibitors (CPIs) have been widely applied in the treatment of patients with bladder cancer (BLCA). However, there is still unmet need to dissect response predict biomarkers. To uncover CPI response-related marker genes in cancer cells, we utilized SCISSOR, integrating single-cell RNA and bulk RNA sequencing data. Transcriptomic and clinical data from IMvigor210, UNC-108, and BCAN/HCRN datasets were collected to evaluate and validate the identified biomarkers and signatures. Additionally, we analyzed TCGA-BLCA and local-BLCA RNA-seq data to investigate alternative splicing events (ASEs). Cell viability was assessed in T24 and UMUC3 cells with RBM17 upregulation or downregulation. Through SCISSOR analysis, we discovered that the expression levels of RBM17, TAP1, and PSMB8 were significantly associated with CPI response. Since PSMB8 displayed a highly positive correlation with TAP1, we developed a CPI response score (CRS) signature based on the expression profiles of RBM17 and TAP1. The CRS demonstrated robust predictive capacity in IMvigor210, UNC-108, and BCAN/HCRN datasets and was associated with higher tumor mutational burden (TMB), PD-L1 expression, and unique genomic features. Notably, RBM17 was not linked to the clinical outcomes of BLCA patients but positively correlated with BLCA cell proliferation in vitro. In the meantime, RBM17 was correlated with higher activity in core biological pathways, including antigen processing machinery, CD8 + T effector cells, cell cycle, DNA damage repair, epithelial-mesenchymal transition, histone regulation, and immune checkpoints. Moreover, the high-RBM17 group showed enrichment of LumU/Ba/sq subtypes but fewer FGFR3 alterations. Lastly, RBM17 significantly upregulated ASEs in BLCA samples, leading to higher neoantigen levels, a more inflamed tumor microenvironment, and improved CPI response. RBM17 is associated with higher ASEs and neoantigen levels, thereby potentiating the efficacy of CPI in BLCA. The established predictive signature, utilizing only two genes, has the potential to streamline clinical applications, providing a cost-effective alternative to expensive genomic, transcriptomic, and biological feature tests.

Study on the Engineering Properties of Whole Garlic Bulbs and Garlic Cloves for Effective Design of Processing Machinery

The present experiment was conducted from February, 2024 to March, 2024 at the Department of Agricultural Process Engineering, Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra, India to investigate the various engineering properties of garlic bulbs and garlic cloves. The engineering properties viz., physical, gravimetric and frictional properties, were studied for whole garlic bulbs and garlic cloves by considering their importance in developing different agricultural and post-harvest processing machinery. The weight 11.41 g, length (polar diameter) 33.69 mm, width (equatorial diameter) 29.51 mm, thickness 27.58 mm, arithmetic mean diameter 30.26 mm, geometric mean diameter 30.10 mm, shape index 0.88, sphericity 0.90, surface area 63.05 cm2, cross-sectional area 53.75 cm2, bulk density 449.50 kg m-3, true density 930.45 kg m-3, porosity 51.69%, moisture content 56.70% and angle of repose of garlic bulb 50.54° were obtained. Similar properties were determined for garlic cloves. The L, a and b values for garlic bulb and garlic cloves were 82.95, 0.23, 10.66 and 74.42, 0.28, 12.48, respectively. The water activity of garlic was found to be 0.98±0.02. The coefficient of friction of the garlic bulb and garlic cloves was measured for the selected testing surfaces such as mild steel (MS), stainless steel (SS), wood, glass and fiberglass which was considered in hopper design. The compression force required to loosen the cloves from the garlic bulb was calculated as 61 N. By integrating these engineering properties into the design process, manufacturers can develop equipments or machineries that are more efficient, durable and capable of producing high-quality garlic products.

Determinants of net value added to produced and processed paddy rice in South East, Nigeria

The study principally examined the determinants of net value added to produced and processed paddy rice in South east Nigeria It specifically, identified the socio-economic characteristics of the respondents, analyzed the determinants of net value added to produced and processed paddy rice as well as ascertained the constraints to processed and produced paddy rice. Multi-stage sampling technique involving purposive and random sampling methods was used to select 240 respondents. Primary data were collected on rain-fed production season using structured questionnaires administered to the respondents by personal interview. Descriptive statistics,, multiple regression and principal component analysis were used to analyze the data. Results obtained showed that gender distribution of the respondents was 63%males and 38% females. More respondents are between the ages of 41-50 and31-40 respectively and house hold size of 4-6 .Farming experience showed that 136 respondents representing 57% had engaged in the business between 11-20yrs.The results also showed that 67% of the respondents accessed farm credit while 25% did not.66% of the respondents belonged to farmers association while 75% were not visited by extension agents. Variables (age, gender, years in school, household size, years of experience, training/extension visits, costs incurred, value addition technique and market price) significantly influenced the net value added while marital status, membership of cooperative, and access to credit did not. Constraints to paddy producers and processors were accessibility to farm machine, poor infrastructure and scarcity/high cost of labor, low access to credit/grant; low proactive measures to flood and drought control; insufficient knowledge of agro-chemicals, and late provision of essential training and services; and processors: use of outdated rice milling machines, high cost of modern rice processing machines, low access to modern rice processing machineries and low acceptability of local rice. Recommendations include; establishment of farm machinery hiring centers for producers and supply of modern rice milling machines to rice processing clusters, development of dams and irrigable lands, training and re-training on access to fund, utilization of biodegradable wastes from paddy rice, proactive measures of flood and drainage control, adequate use of agro-chemicals, use of modem techniques, and involvement of National Agency for Food and Drug Administration and Control in quality control. Keywords: Agriculture, Paddy Rice, Value Addition, Nigeria.

Discovering Explainable Biomarkers for Breast Cancer Anti-PD1 Response via Network Shapley Value Analysis

Background and objectiveImmunotherapy holds promise in enhancing pathological complete response rates in breast cancer, albeit confined to a select cohort of patients. Consequently, pinpointing factors predictive of treatment responsiveness is of paramount importance. Gene expression and regulation, inherently operating within intricate networks, constitute fundamental molecular machinery for cellular processes and often serve as robust biomarkers. Nevertheless, contemporary feature selection approaches grapple with two key challenges: opacity in modeling and scarcity in accounting for gene-gene interactions MethodsTo address these limitations, we devise a novel feature selection methodology grounded in cooperative game theory, harmoniously integrating with sophisticated machine learning models. This approach identifies interconnected gene regulatory network biomarker modules with priori genetic linkage architecture. Specifically, we leverage Shapley values on network to quantify feature importance, while strategically constraining their integration based on network expansion principles and nodal adjacency, thereby fostering enhanced interpretability in feature selection. We apply our methods to a publicly available single-cell RNA sequencing dataset of breast cancer immunotherapy responses, using the identified feature gene set as biomarkers. Functional enrichment analysis with independent validations further illustrates their effective predictive performance ResultsWe demonstrate the sophistication and excellence of the proposed method in data with network structure. It unveiled a cohesive biomarker module encompassing 27 genes for immunotherapy response. Notably, this module proves adept at precisely predicting anti-PD1 therapeutic outcomes in breast cancer patients with classification accuracy of 0.905 and AUC value of 0.971, underscoring its unique capacity to illuminate gene functionalities ConclusionThe proposed method is effective for identifying network module biomarkers, and the detected anti-PD1 response biomarkers can enrich our understanding of the underlying physiological mechanisms of immunotherapy, which have a promising application for realizing precision medicine.

Evaluating the Impact of Moisture Content and Loading Orientation on the Geometrical Characteristics and Mechanical Behavior of Cassava Tubers

This study investigates the geometrical and mechanical properties of two cassava varieties: ‘Newly Elected No. 48’ and ‘Jin Yue HRMUS’. We analyzed various properties, including width, length, geometric diameter, thickness, compression firmness, shape ratio, surface area, shear strength, rupture force, and shear rupture force (SRF), at different moisture content (MC) levels ranging from 35.0 to 80.0% wet basis. Our findings indicate that all mechanical properties of cassava (MPC) were significantly influenced by moisture content within this range. Specifically, as moisture content decreases, the compression rupture force (CRF) increases linearly in the vertical direction, while a quadratic relationship is observed in the horizontal direction, characterized by an initial increase followed by a decrease. Additionally, a quadratic relationship was established between moisture content and firmness. In contrast, shear fracture force and strength exhibited a quadratic relationship that decreased initially and then increased with rising moisture content. Furthermore, both compression and shear fracture forces were significantly higher in the vertical loading direction compared to the horizontal direction. Notably, the ‘Jin Yue HRMUS’ variety demonstrated greater mechanical strength than the ‘Newly Elected No. 48’. These findings provide valuable insights for developing, optimizing, and evaluating cassava harvesting and processing machinery.

New anti-ovarian cancer quinolone derivatives acting by modulating microRNA processing machinery.

MicroRNAs (miRNAs) play a crucial role in ovarian cancer (OC) pathogenesis and miRNA processing can be the object of pharmacological intervention. By exploiting our in-house quinolone library, we combined a cell-based screening with medicinal chemistry efforts, ultimately leading to derivative 33 with anti-OC activity against distinct cell lines (GI50 values 13.52-31.04 μM) and CC50 Wi-38 = 142.9 μM. Compound 33 retained anticancer activity against additional cancer cells and demonstrated a synergistic effect with cisplatin against cisplatin-resistant A2780 cells. Compound 33 bound TRBP by SPR (K D = 4.09 μM) and thermal shift assays and its activity was TRBP-dependent, leading to modulation of siRNA and miRNA maturation. Derivative 33 exhibited augmented potency against OC cells and a stronger binding affinity for TRBP compared to enoxacin, the sole quinolone identified as a modulator of miRNA maturation. Consequently, 33 represents a promising template for developing novel anti-OC agents with a distinctive mechanism of action.

Mixed convection flow and heat-mass transfer of cross liquid near a stagnation region with Dufour, Soret effects and chemical reaction

Heat-mass transfer in a liquid flow over a stretching surface at a stagnation regime is significant in optimal manufacturing and quality assurance depending on the rheological behavior of viscoelastic fluids in process machinery. Stretching sheet flow at a stagnation point is a standard procedure used in the metallurgical industries for manufacturing of different equipment and cooling systems. Due to its various applications in industrial operations, the current study aims to explore the heat-mass transfer of buoyancy-driven flow of cross liquid over a stretching sheet at a stagnation point. The heat and mass transfer under the framework of Dufour and Soret effects, radiant heat, and chemical reactions are assessed. Furthermore, the analysis also takes into account the linear and nonlinear convection-diffusion phenomena. The model findings are obtained by merging the Bvp4c in MATLAB using a local similarity technique up to the fourth truncation threshold. The findings illustrate that the action of magnetic field can be used to control the flow across the sheet. Temperature increases with thermal radiation, Biot number and Dufour number. The action of buoyancy ratio parameter result in improvement in fluid flow. With increasing trend of magnetic and Weissenberg number, the flow field and skin friction coefficient drops.

Variation of C-terminal domain governs RNA polymerase II genomic locations and alternative splicing in eukaryotic transcription

The C-terminal domain of RPB1 (CTD) orchestrates transcription by recruiting regulators to RNA Pol II upon phosphorylation. With CTD driving condensate formation on gene loci, the molecular mechanism behind how CTD-mediated recruitment of transcriptional regulators influences condensates formation remains unclear. Our study unveils that phosphorylation reversibly dissolves phase separation induced by the unphosphorylated CTD. Phosphorylated CTD, upon specific association with transcription regulators, forms distinct condensates from unphosphorylated CTD. Functional studies demonstrate CTD variants with diverse condensation properties exhibit differences in promoter binding and mRNA co-processing in cells. Notably, varying CTD lengths influence the assembly of RNA processing machinery and alternative splicing outcomes, which in turn affects cellular growth, linking the evolution of CTD variation/length with the complexity of splicing from yeast to human. These findings provide compelling evidence for a model wherein post-translational modification enables the transition of functionally specialized condensates, highlighting a co-evolution link between CTD condensation and splicing.

Disruptions in antigen processing and presentation machinery on sarcoma

BackgroundThe antigen processing machinery (APM) plays a critical role in generating tumor-specific antigens that can be recognized and targeted by the immune system. Proper functioning of APM components is essential for presenting these antigens on the surface of tumor cells, enabling immune detection and destruction. In many cancers, defects in APM can lead to immune evasion, contributing to tumor progression and poor clinical outcomes. However, the status of the APM in sarcomas is not well characterized, limiting the development of effective immunotherapeutic strategies for these patients.MethodsWe investigated 126 patients with 8 types of bone and soft tissue sarcoma operated between 2001–2021. Tissue microarrays mapped 11 specific areas in each case. The presence/absence of APM protein was determined through immunohistochemistry. Bayesian networks were used.ResultsAll investigated sarcomas had some defects in APM. The least damaged component was HLA Class I subunit β2-microglobulin and HLA Class II. The proteasome LMP10 subunit was defective in leiomyosarcoma (LMS), myxoid liposarcoma (MLPS), and dedifferentiated liposarcoma (DDLPS), while MHC I transporting unit TAP2 was altered in undifferentiated pleomorphic sarcoma (UPS), gastrointestinal stromal tumor (GIST), and chordoma (CH). Among different neoplastic areas, high-grade areas showed different patterns of expression compared to high lymphocytic infiltrate areas. Heterogeneity at the patient level was also observed. Loss of any APM component was prognostic of distant metastasis (DM) for LMS and DDLPS and of overall survival (OS) for LMS.ConclusionSarcomas exhibit a high degree of defects in APM components, with differences among histotypes and tumoral areas. The most commonly altered APM components were HLA Class I subunit β2-microglobulin, HLA Class I subunit α (HC10), and MHC I transporting unit TAP2. The loss of APM components was prognostic of DM and OS and clinically relevant for LMS and DDLPS. This study explores sarcoma molecular mechanisms, enriching personalized therapeutic approaches.

The structural basis for the collagen processing by human P3H1/CRTAP/PPIB ternary complex

Collagen posttranslational processing is crucial for its proper assembly and function. Disruption of collagen processing leads to tissue development and structure disorders like osteogenesis imperfecta (OI). OI-related collagen processing machinery includes prolyl 3-hydroxylase 1 (P3H1), peptidyl-prolyl cis-trans isomerase B (PPIB), and cartilage-associated protein (CRTAP), with their structural organization and mechanism unclear. We determine cryo-EM structures of the P3H1/CRTAP/PPIB complex. The active sites of P3H1 and PPIB form a face-to-face bifunctional reaction center, indicating a coupled modification mechanism. The structure of the P3H1/CRTAP/PPIB/collagen peptide complex reveals multiple binding sites, suggesting a substrate interacting zone. Unexpectedly, a dual-ternary complex is observed, and the balance between ternary and dual-ternary states can be altered by mutations in the P3H1/PPIB active site and the addition of PPIB inhibitors. These findings provide insights into the structural basis of collagen processing by P3H1/CRTAP/PPIB and the molecular pathology of collagen-related disorders.

Nanodynamo quantifies subcellular RNA dynamics revealing extensive coupling between steps of the RNA life cycle

The coordinated action of transcriptional and post-transcriptional machineries shapes gene expression programs at steady state and determines their concerted response to perturbations. We have developed Nanodynamo, an experimental and computational workflow for quantifying the kinetic rates of nuclear and cytoplasmic steps of the RNA life cycle. Nanodynamo is based on mathematical modelling following sequencing of native RNA from cellular fractions and polysomes. We have applied this workflow to triple-negative breast cancer cells, revealing widespread post-transcriptional RNA processing that is mutually exclusive with its co-transcriptional counterpart. We used Nanodynamo to unravel the coupling between transcription, processing, export, decay and translation machineries. We have identified a number of coupling interactions within and between the nucleus and cytoplasm that largely contribute to coordinating how cells respond to perturbations that affect gene expression programs. Nanodynamo will be instrumental in unravelling the determinants and regulatory processes involved in the coordination of gene expression responses.

Analysis of influencing factors of raw cotton quality and prospect of optimisation pathway

The paper discusses the issue of raw cotton quality and summarises it in the context of the current state of research. The article highlights the importance of cotton seeds for improving cotton quality and points out the problems in cotton seed selection and breeding. The article also mentions other factors affecting cotton quality, such as planting technology, light factors, defoliation and ripening technology, anisotropic fibre content and cotton picker operation quality. Based on these findings, ways to optimize the quality of raw cotton are proposed, including exploring suitable cotton varieties for machine picking, mitigating differences in raw cotton quality due to differences in geographic location and climatic conditions, and optimizing the use of picking techniques and processing machinery to reduce the impact on raw cotton quality. In conclusion, the paper provides a useful reference for promoting the application of cotton mechanical picking technology.

Alternative splicing regulation in plants by SP7-like effectors from symbiotic arbuscular mycorrhizal fungi

Most plants in natural ecosystems associate with arbuscular mycorrhizal (AM) fungi to survive soil nutrient limitations. To engage in symbiosis, AM fungi secrete effector molecules that, similar to pathogenic effectors, reprogram plant cells. Here we show that the Glomeromycotina-specific SP7 effector family impacts on the alternative splicing program of their hosts. SP7-like effectors localize at nuclear condensates and interact with the plant mRNA processing machinery, most prominently with the splicing factor SR45 and the core splicing proteins U1-70K and U2AF35. Ectopic expression of these effectors in the crop plant potato and in Arabidopsis induced developmental changes that paralleled to the alternative splicing modulation of a specific subset of genes. We propose that SP7-like proteins act as negative regulators of SR45 to modulate the fate of specific mRNAs in arbuscule-containing cells. Unraveling the communication mechanisms between symbiotic fungi and their host plants will help to identify targets to improve plant nutrition.

Transcriptomic observations of intra and extracellular immunotherapy targets for pediatric brain tumors

ABSTRACT Objectives Despite surgical resection, chemoradiation, and targeted therapy, brain tumors remain a leading cause of cancer-related death in children. Immunotherapy has shown some promise and is actively being investigated for treating childhood brain tumors. However, a critical step in advancing immunotherapy for these patients is to uncover targets that can be effectively translated into therapeutic interventions. Methods In this study, our team performed a transcriptomic analysis across pediatric brain tumor types to identify potential targets for immunotherapy. Additionally, we assessed components that may impact patient response to immunotherapy, including the expression of genes essential for antigen processing and presentation, inhibitory ligands and receptors, interferon signature, and overall predicted T cell infiltration. Results We observed distinct expression patterns across tumor types. These included elevated expression of antigen genes and antigen processing machinery in some tumor types while other tumors had elevated inhibitory checkpoint receptors, known to be associated with response to checkpoint inhibitor immunotherapy. Conclusion These findings suggest that pediatric brain tumors exhibit distinct potential for specific immunotherapies. We believe our findings can guide investigators in their assessment of appropriate immunotherapy classes and targets in pediatric brain tumors.

Single nucleotide polymorphisms of GEMIN3 modify the risk of primary Sjögren's syndrome in female patients

BackgroundMicroRNA (miRNA)-processing machinery may modify the risk of primary Sjögren's syndrome (pSS) by altering miRNA expression profiles. Inflammatory cytokines and reactive oxygen species (ROS) are also involved in pSS; however, the role of altered miRNAs expression in its pathogenesis is still unclear. We aimed to evaluate the relationship between single-nucleotide polymorphisms (SNPs) in miRNA processing machinery genes, including XPO5 (rs11077), RAN (rs14035), Dicer (rs3742330), TNRC6B (rs9623117), GEMIN3 (rs197412), and GEMIN4 (rs2740348), and the risk of pSS in female patients. The potential associations of cytokines and ROS with pSS-susceptible SNPs were also evaluated. Materials and MethodsThe SNPs confirmed by polymerase chain reaction ligase detection reaction were genotyped in 74 female patients with pSS and 77 controls. The relationship was analyzed by Student's t-test, Wilcoxon rank-sum test, chi-square test, Pearson's correlation test, and binary logistic regression analysis. ResultsFor rs197412 of the GEMIN3 gene, the genotype TT carrier was associated with a 2.172-fold increased risk for pSS when compared with that of CT+CC carrier (odds ratio: 2.172, 95% CI, 1.133–4.166, p=0.019). Simultaneously, the pSS-susceptible TT carriers were associated with increased interferon-γ (IFN-γ) (P < 0.001) and tumor necrosis factor-α (TNF-α) (P = 0.003) levels when compared with that of CT+CC genotype carriers in female patients with pSS. The subsequent analysis also showed a weak positive correlation between IFN-γ and TNF-α levels (r=0.271, P = 0.019). ConclusionThe predictors of GEMIN3 SNPs might modify pSS development in females by mediating the expression of miRNAs and therefore regulate the levels of IFN-γ and TNF-α.

Human erythroid progenitors express antigen presentation machinery.

Early-life immune exposures can profoundly impact lifelong health. However, functional mechanisms underlying fetal immune development remain incomplete. Erythrocytes are not typically considered active immune mediators, primarily because erythroid precursors discard their organelles as they mature, thus losing the ability to alter gene expression in response to stimuli. Erythroid progenitors and precursors circulate in human fetuses and neonates. Although there is limited evidence that erythroid precursors are immunomodulatory, our understanding of the underlying mechanisms remains inadequate. To define the immunobiological role of fetal and perinatal erythroid progenitors and precursors, we analyzed single cell RNA-sequencing data and found that transcriptomics support erythroid progenitors as putative immune mediators. Unexpectedly, we discovered that human erythroid progenitors constitutively express Major Histocompatibility Complex (MHC) class II antigen processing and presentation machinery, which are hallmarks of specialized antigen presenting immune cells. Furthermore, we demonstrate that erythroid progenitors internalize and cleave foreign proteins into peptide antigens. Unlike conventional antigen presenting cells, erythroid progenitors express atypical costimulatory molecules and immunoregulatory cytokines that direct the development of regulatory T cells, which are critical for establishing maternal-fetal tolerance. Expression of MHC II in definitive erythroid progenitors begins during the second trimester, coinciding with the appearance of mature T cells in the fetus, and is absent in primitive progenitors. Lastly, we demonstrate physical and molecular interaction potential of erythroid progenitors and T cells in the fetal liver. Our findings shed light on a unique orchestrator of fetal immunity and provide insight into the mechanisms by which erythroid cells contribute to host defense.

Key Industrial Sectors In The Sulampua Area As A Result Of Nusantara Capital City Development

This study aims to determine the sectors that need to be developed in the non-golden triangle area of the SULAMPUA region as a result of the Nusantara Capital City (NCC) development. Descriptive research is being conducted utilizing secondary data from Statistics Indonesia’s 2016 IRIO (Inter-Regional Input-Output) table. The IRIO model is used in data analysis for 20 secondary sub-sectors. The SULAMPUA region comprises 10 provinces, with the Golden Triangle region comprising South Sulawesi, Central Sulawesi, and West Sulawesi. The study results show that to take advantage of opportunities for the development of NCC, several key industries need to be developed for non-golden triangle areas, namely the food industry (I-13), non-metallic mineral goods industry (I-21); other processing industries, machinery and equipment repair and installation services (I-27); and the wood industry, goods from wood and cork, and woven goods from bamboo, rattan, and the like (I-17). Maluku, Papua, and West Papua provinces have relatively little opportunity to develop the industrial sector and benefit from moving NCC. Because the sectors connected directly or indirectly and the key sectors of these three provinces are capital-intensive industries, MSMEs have more significant barriers to entry. This research can be a reference for local governments in exploring potential industrial sectors to be developed to achieve NCC development opportunities.

Delineating yeast cleavage and polyadenylation signals using deep learning.

3'-end cleavage and polyadenylation is an essential process for eukaryotic mRNA maturation. In yeast species, the polyadenylation signals that recruit the processing machinery are degenerate and remain poorly characterized compared with the well-defined regulatory elements in mammals. Here we address this issue by developing deep learning models to deconvolute degenerate cis-regulatory elements and quantify their positional importance in mediating yeast poly(A) site formation, cleavage heterogeneity, and strength. In S. cerevisiae, cleavage heterogeneity is promoted by the depletion of U-rich elements around poly(A) sites as well as multiple occurrences of upstream UA-rich elements. Sites with high cleavage heterogeneity show overall lower strength. The site strength and tandem site distances modulate alternative polyadenylation (APA) under the diauxic stress. Finally, we develop a deep learning model to reveal the distinct motif configuration of S. pombe poly(A) sites, which show more precise cleavage than S. cerevisiae Altogether, our deep learning models provide unprecedented insights into poly(A) site formation of yeast species, and our results highlight divergent poly(A) signals across distantly related species.

ETMR-05. DEVELOPMENT OF NOVEL PRECLINICAL MODELS AND THERAPEUTIC STRATEGIES FOR ETMR

Abstract BACKGROUND Embryonal Tumor with Multilayered Rosettes (ETMR) is a very rare, aggressive pediatric brain tumor with a dismal 5-year overall survival rate. Few genetic aberrations in miRNA clusters and processing machinery have been detected in ETMRs with 90% of ETMR patients having the C19MC amplification. ETMRs show unique histopathological features which, together with the detection of C19MC or DICER alterations, are necessary for diagnosis. The cellular and molecular mechanisms underlying ETMR development are poorly understood, and targeted therapeutics have not been developed due to scarcity of preclinical models. To expand knowledge of ETMR biology and accelerate the design of novel and therapies, it is thus essential to develop preclinical models. METHODS We have generated two novel patient-derived ETMR cell lines from resected patient derived tumor samples (CTBP-03A and CBTP-139) and created three patient-derived xenograft (PDX) models (CTBP-03A, CBTP-139 and CBTP-38). We have used these unique patient-derived cell lines to identify mechanisms driving ETMR development and progression. To identify novel therapeutic targets, we conducted high-throughput drug screening (HTDS) utilizing 2480 approved and investigational drugs, against the CBTP-03A and CBTP-139 lines. RESULTS Among the candidate drugs showing an inhibitory effect on both lines, compounds were selected based on their activity, CNS penetration ability, mechanism of action, and bioavailability, if known. The top selected hits were screened in an all-versus-all format, totaling 1953 combinations. The rapidity of action and efficacy of the top choice compounds used as single agent or in double and triple combination was assessed by caspase glow and cell titer glow assays. This initial combination screen identified DNA replication stress, retinoid receptor agonist and FGF signaling as potential combinatorial targets. Data are currently being validated in vivo. CONCLUSIONS This is the first combinatorial HTDS on two novel patient-derived cell lines which highlighted potential drug combination strategies for the treatment of ETMR.