Custom Farm Machinery Rates in Texas--1973.

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EVALUATION OF AN END-TO-END RADIOTHERAPY TREATMENT PLANNING PIPELINE FOR PROSTATE CANCER

Radiation treatment planning is a crucial and time-intensive process in radiation therapy. This planning involves carefully designing a treatment regimen tailored to a patient’s specific condition, including the type, location, and size of the tumor with reference to surrounding healthy tissues. For prostate cancer, this tumor may be either local, locally advanced with extracapsular involvement, or extend into the pelvic lymph node chain. Automating essential parts of this process would allow for the rapid development of effective treatment plans and better plan optimization to enhance tumor control for better outcomes. The first objective of this work, to automate the treatment planning process, was the automatic segmentation of critical structures. Delineation of both target and normal tissue structures was necessary to establish the foundation for identifying where radiation must be delivered and what should be spared from excess radiation. Deep learning segmentation models were developed from retrospective CT simulation imaging data and clinical contours to delineate intact, postoperative, and nodal treatment structures for prostate cancer to accomplish this objective. Quality contours were extracted per established contouring guidelines in the literature. Model refinement on a holdout fine-tune dataset was used to verify model contours before quantitative and qualitative evaluation on the holdout test set. Predicted contours resulted in contours comparable in quantitative Dice-Similarity-Coefficient (DSC) and 95% Hausdorff Distance (HD95) to proposed models in literature and clinically usable contours with no more than minor edits upon physician review. The second objective was the automation of Volumetric Modulated Arc Therapy (VMAT) planning for a breadth of prostate treatment scenarios. Development of VMAT plans for intact, postoperative, and nodal involvement treatment cases was necessary for the sequence in daily treatment delivery and the prospective distribution of radiation dose to target and normal tissues. To accomplish this objective, knowledge-based planning models were separately developed to estimate patient-specific DVHs to guide plan optimization for radiation delivery. These two models were then used in this work for end-to-end testing of cases with and without lymph node involvement, including determining if the prostate target is intact or postoperative with or without treatment devices such as hydrogel spacers and rectal balloons. A sequence of iterative optimization runs was created to ensure hotspot reduction and target conformality. The findings demonstrated that plans developed from automatically generated contours were clinically usable with minor edits for intact and postoperative treatments without lymph node involvement. For treatments with lymph node involvement, dose constraints were met for a select set of cases without excessive rectum curvature or excessive bladder descension into the postoperative treatment bed. When comparing auto-segmented to clinical contours, clinical contours experienced similar pass rates as those achieved by auto-segmented contours

Multiscale Modeling of Bacterial Colonies: How Pili Mediate the Dynamics of Single Cells and Cellular Aggregates

Neisseria gonorrhoeae is the causative agent of one of the most common sexually transmitted diseases, gonorrhea. Over the past two decades there has been an alarming increase of reported gonorrhea cases where the bacteria were resistant to the most commonly used antibiotics thus prompting for alternative antimicrobial treatment strategies. The crucial step in this and many other bacterial infections is the formation of microcolonies, agglomerates consisting of up to several thousands of cells. The attachment and motility of cells on solid substrates as well as the cell–cell interactions are primarily mediated by type IV pili, long polymeric filaments protruding from the surface of cells. While the crucial role of pili in the assembly of microcolonies has been well recognized, the exact mechanisms of how they govern the formation and dynamics of microcolonies are still poorly understood. Here, we present a computational model of individual cells with explicit pili dynamics, force generation and pili–pili interactions. We employ the model to study a wide range of biological processes, such as the motility of individual cells on a surface, the heterogeneous cell motility within the large cell aggregates, and the merging dynamics and the self-assembly of microcolonies. The results of numerical simulations highlight the central role of pili generated forces in the formation of bacterial colonies and are in agreement with the available experimental observations. The model can quantify the behavior of multicellular bacterial colonies on biologically relevant temporal and spatial scales and can be easily adjusted to include the geometry and pili characteristics of various bacterial species. Ultimately, the combination of the microbiological experimental approach with the in silico model of bacterial colonies might provide new qualitative and quantitative insights on the development of bacterial infections and thus pave the way to new antimicrobial treatments

Intensity modulated proton arc therapy via geometry-based energy selection for ependymoma

We developed a novel method of creating intensity modulated proton arc therapy (IMPAT) plans that uses computing resources efficiently and may offer a dosimetric benefit for patients with ependymoma or similar tumor geometries. Our IMPAT planning method consists of a geometry-based energy selection step with major scanning spot contributions as inputs computed using ray-tracing and single-Gaussian approximation of lateral spot profiles. Based on the geometric relation of scanning spots and dose voxels, our energy selection module selects a minimum set of energy layers at each gantry angle such that each target voxel is covered by sufficient scanning spots as specified by the planner, with dose contributions above the specified threshold. Finally, IMPAT plans are generated by robustly optimizing scanning spots of the selected energy layers using a commercial proton treatment planning system. The IMPAT plan quality was assessed for four ependymoma patients. Reference three-field IMPT plans were created with similar planning objective functions and compared with the IMPAT plans. In all plans, the prescribed dose covered 95% of the clinical target volume (CTV) while maintaining similar maximum doses for the brainstem. While IMPAT and IMPT achieved comparable plan robustness, the IMPAT plans achieved better homogeneity and conformity than the IMPT plans. The IMPAT plans also exhibited higher relative biological effectiveness (RBE) enhancement than did the corresponding reference IMPT plans for the CTV in all four patients and brainstem in three of them. The proposed method demonstrated potential as an efficient technique for IMPAT planning and may offer a dosimetric benefit for patients with ependymoma or tumors in close proximity to critical organs. IMPAT plans created using this method had elevated RBE enhancement associated with increased linear energy transfer.Comment: 24 pages with 8 figures and 2 table

Identification of {HNRNPK} as Regulator of Hepatitis {C} Virus Particle Production

Hepatitis C virus (HCV) is a major cause of chronic liver disease affecting around 130 million people worldwide. While great progress has been made to define the principle steps of the viral life cycle, detailed knowledge how HCV interacts with its host cells is still limited. To overcome this limitation we conducted a comprehensive whole-virus RNA interference-based screen and identified 40 host dependency and 16 host restriction factors involved in HCV entry/replication or assembly/release. Of these factors, heterogeneous nuclear ribonucleoprotein K (HNRNPK) was found to suppress HCV particle production without affecting viral RNA replication. This suppression of virus production was specific to HCV, independent from assembly competence and genotype, and not found with the related Dengue virus. By using a knock-down rescue approach we identified the domains within HNRNPK required for suppression of HCV particle production. Importantly, HNRNPK was found to interact specifically with HCV RNA and this interaction was impaired by mutations that also reduced the ability to suppress HCV particle production. Finally, we found that in HCV-infected cells, subcellular distribution of HNRNPK was altered; the protein was recruited to sites in close proximity of lipid droplets and colocalized with core protein as well as HCV plus-strand RNA, which was not the case with HNRNPK variants unable to suppress HCV virion formation. These results suggest that HNRNPK might determine efficiency of HCV particle production by limiting the availability of viral RNA for incorporation into virions. This study adds a new function to HNRNPK that acts as central hub in the replication cycle of multiple other viruses

MicroRNA profile before and after antiviral therapy in liver transplant recipients for Hepatitis C virus cirrhosis

BACKGROUND AND AIM: Management of Hepatitis C virus (HCV) recurrence is a major challenge after liver transplantation. Significant dysregulated expression of HCV receptors (i.e. claudin-1, occludin, CD81, Scavenger-receptor Type B1) has been shown recently during HCV infection. This might facilitate hepatocytic entry and reinfection of HCV. MicroRNAs (miRs) play role in the regulation of gene expression. We aimed to characterize miR expression profiles related to HCV infection and antiviral therapy in adult liver transplant recipients, with special emphasis on microRNAs predicted to target HCV receptors. METHODS: Twenty-eight adult liver transplant recipients were enrolled in the study. Paired biopsies were obtained at the time of HCV recurrence and at the end of antiviral treatment. MicroRNAs for HCV receptors were selected using target prediction software. Expression levels of miR-21, miR-23a miR-34a, miR-96, miR-99a*, miR-122, miR-125b, miR-181a-2*, miR-194, miR-195, miR-217, miR-221 and miR-224 were determined by RT-qPCR. RESULTS: miR-99a* and miR-224 expressions were increased in HCV recurrence samples, while miR-21 and miR-194 were decreased in comparison to normal liver tissue. Increased expressions of miR-221, miR-224 and miR-217 were observed in samples taken after antiviral therapy when compared with HCV recurrence samples. High HCV titer at recurrence was associated with higher level of miR-122. CONCLUSIONS: Samples at recurrence of HCV and after antiviral therapy revealed distinct HCV-related microRNA expression profiles, with significant dysregulation of those miRNAs potentially targeting mRNAs of HCV receptors. In particular, miR-194 and miR-21 might be involved in the regulation of HCV receptor proteins' expression during HCV infection and antiviral therapy

Treatment for acute myelogenous leukemia by low dose Total Body Irradiation (TBI) based conditioning and hematopoietic cell transplantation from related and unrelated donors

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Neurons are MHC Class I-Dependent Targets for CD8 T Cells upon Neurotropic Viral Infection

Following infection of the central nervous system (CNS), the immune system is faced with the challenge of eliminating the pathogen without causing significant damage to neurons, which have limited capacities of renewal. In particular, it was thought that neurons were protected from direct attack by cytotoxic T lymphocytes (CTL) because they do not express major histocompatibility class I (MHC I) molecules, at least at steady state. To date, most of our current knowledge on the specifics of neuron-CTL interaction is based on studies artificially inducing MHC I expression on neurons, loading them with exogenous peptide and applying CTL clones or lines often differentiated in culture. Thus, much remains to be uncovered regarding the modalities of the interaction between infected neurons and antiviral CD8 T cells in the course of a natural disease. Here, we used the model of neuroinflammation caused by neurotropic Borna disease virus (BDV), in which virus-specific CTL have been demonstrated as the main immune effectors triggering disease. We tested the pathogenic properties of brain-isolated CD8 T cells against pure neuronal cultures infected with BDV. We observed that BDV infection of cortical neurons triggered a significant up regulation of MHC I molecules, rendering them susceptible to recognition by antiviral CTL, freshly isolated from the brains of acutely infected rats. Using real-time imaging, we analyzed the spatio-temporal relationships between neurons and CTL. Brain-isolated CTL exhibited a reduced mobility and established stable contacts with BDV-infected neurons, in an antigen- and MHC-dependent manner. This interaction induced rapid morphological changes of the neurons, without immediate killing or impairment of electrical activity. Early signs of neuronal apoptosis were detected only hours after this initial contact. Thus, our results show that infected neurons can be recognized efficiently by brain-isolated antiviral CD8 T cells and uncover the unusual modalities of CTL-induced neuronal damage