Identifying Intracellular pDNA Losses From a Model of Nonviral Gene Delivery

Nonviral gene delivery systems are a type of nanocommunication system that transmit plasmid packets (i.e., pDNA packets) that are programmed at the nanoscale to biological systems at the microscopic cellular level. This engineered nanocommunication system suffers large pDNA losses during transmission of the genetically encoded information, preventing its use in biotechnological and medical applications. The pDNA losses largely remain uncharacterized, and the ramifications of reducing pDNA loss from newly designed gene delivery systems remain difficult to predict. Here, the pDNA losses during primary and secondary transmission chains were identified utilizing a MATLAB model employing queuing theory simulating delivery of pEGFPLuc transgene to HeLa cells carried by Lipofectamine 2000 nonviral DNA carrier. Minimizing pDNA loss during endosomal escape of the primary transmission process results in increased number of pDNA in the nucleus with increased transfection, but with increased probability of cell death. The number of pDNA copies in the nucleus and the amount of time the pDNAs are in the nucleus directly correlates to improved transfection efficiency. During secondary transmission, pDNAs are degraded during distribution to daughter cells. Reducing pDNA losses improves transfection, but a balance in quantity of nuclear pDNA, mitosis, and toxicity must be considered in order to achieve therapeutically relevant transfection levels

Selected abbreviations and new terms in breast pathology — a guide for clinicians

The aim of this article is to present briefly new pathological entities which are recently increasingly commonly used in pathology reports, as well as to discuss their clinical consequences. The new WHO classification of breast diseases includes, inter alia, invasive carcinoma of no special type: this is not a specific entity, but rather a group of malignancies without specific features. The lobular hyperplasia group includes a classical variant and a pleomorphic variant of lobular carcinoma in situ, as well as atypical lobular hyperplasia. The ductal hyperplasia group, according to the current revision of the WHO classification of breast diseases, encompasses: typical (i.e. non-atypical) ductal hyperplasia, columnar cell change, columnar cell hyperplasia, atypical ductal hyperplasia. The mesenchymal breast hyperplasia group includes pseudoangiomatous stromal hyperplasia. We briefly discuss the above mentioned entities together with their respective clinical and therapeutic consequences

Wybrane skrótowce i nowe pojęcia we współczesnej patologii piersi — przewodnik dla klinicystów

Celem niniejszego artykułu jest przedstawienie nowych jednostek chorobowych i pojęć, które ostatnio pojawiły się w raportach patologicznych, a także prezentacja ich konsekwencji terapeutycznych. Nowa klasyfikacja WHO wyróżnia m.in. raka naciekającego bez specjalnego typu, który nie definiuje konkretnej jednostki morfologicznej, a raczej grupę nowotworów bez wystarczających wspólnych cech charakterystycznych. W grupie rozrostów zrazikowych nowa klasyfikacja uwzględnia następujące jednostki morfologiczne: rak zrazikowy in situ klasyczny i pleomorficzny oraz atypowy rozrost zrazikowy. W grupie rozrostów przewodowych klasyfikacja WHO wyróżnia m.in. zwykły (nieatypowy) rozrost nabłonka przewodowego, zmiany walcowatokomórkowe oraz atypowy rozrost nabłonka przewodowego. Ponadto w grupie rozrostów mezenchymalnych podścieliska gruczołu piersiowego należy wymienić rzekomonaczy­niowy rozrost podścieliska (PASH). Autorzy omawiają wymienione jednostki i charakteryzują ich znaczenie kliniczne

Prognostic impact of combined fludarabine, treosulfan and mitoxantrone resistance profile in childhood acute myeloid leukemia

Background: The role of cellular drug resistance in childhood acute myeloid leukemia (AML) has not yet been established. The aim of the study was the analysis of the clinical value of ex vivo drug resistance in pediatric AML. Patients and Methods: A cohort of 90 children with de novo AML were assayed for drug resistance profile by the 3-4,5- dimethylthiazol-2-yl-2,5-difenyl tetrazolium bromide (MTT) assay and prognostic model of in vitro drug sensitivity was analyzed. Results: Children who relapsed during follow-up showed higher in vitro resistance of leukemic blasts to most of the drugs tested, except for cytarabine, cladribine, vincristine, mercaptopurine and thioguanine. A combined in vitro drug resistance profile to fludarabine, treosulfan and mitoxantrone (FTM score) was defined and it had an independent prognostic significance for disease free survival in pediatric AML. Conclusion: The combined fludarabine, treosulfan and mitoxantrone resistance profile to possibly may be used for better stratification of children with AML or indicate the necessity for additional therapy

Changing risk factors in childhood acute lymphoblastic leukemia: experience from Kujawsko-Pomorski region 1976–2018

Introduction: Acute lymphoblastic leukemia (ALL) is the most common malignancy in children. Risk factors in childhood ALL have changed during recent decades, mostly due to treatment personalization. The aim of this study was to analyze therapy results and prognostic factors in childhood ALL in the Kujawsko-Pomorski region of Poland between 1976 and 2018. Material and methods: Data from 495 patients (0–18 years old) diagnosed with ALL from the Kujawsko-Pomorski region between 1976 and 2018 was analyzed. Prognostic factors were analyzed separately in specific therapeutic groups, which were defined by several therapy protocols. Results: Prognostic factors have changed over the course of consecutive therapeutic periods. Between 1976 and 1988 (the first and second therapeutic protocols), central nervous system involvement was the most important risk factor. During the third therapeutic period, an unsatisfactory treatment response on days 8 and 14 was related to a poor outcome. In 1995–2002, the risk factors were hepatomegaly, splenomegaly, lymph nodes involvement, and unsatisfactory therapy response on days 15 and 33. Between 2002 and 2011, immunophenotype other than ‘common’ and hemoglobin level at diagnosis were the risk factors, and a lack of BCR-ABL aberration was related to better therapy results. During the final analyzed period (2011–2018), failure to achieve remission on day 33 was a risk factor, and patients classified as non-high risk group and those aged <6 years had better outcomes. Conclusions: The changing profile of risk factors in ALL has reflected progress in ALL therapy, with the gradual elimination of factors related to poor outcomes, mostly due to modifications in treatment and the development of diagnostic methods as well as therapy monitoring

The Theory of Quaternion Orthogonal Designs

Over the past several years, there has been a renewed interest in complex orthogonal designs for their application in space–time block coding. Motivated by the success of this application, this paper generalizes the definition of complex orthogonal designs by introducing orthogonal designs over the quaternion domain. This paper builds a theory of these novel quaternion orthogonal designs, offers examples, and provides several construction techniques. These theoretical results, along with the results of preliminary simulations, lay the foundation for developing applications of these designs as orthogonal space–time-polarization block codes

Stochastic Simulation of Cellular Metabolism

Increased technological methods have enabled the investigation of biology at nanoscale levels. Such systems require the use of computational methods to comprehend the complex interactions that occur. The dynamics of metabolic systems have been traditionally described utilizing differential equations without fully capturing the heterogeneity of biological systems. Stochastic modeling approaches have recently emerged with the capacity to incorporate the statistical properties of such systems. However, the processing of stochastic algorithms is a computationally intensive task with intrinsic limitations. Alternatively, the queueing theory approach, historically used in the evaluation of telecommunication networks, can significantly reduce the computational power required to generate simulated results while simultaneously reducing the expansion of errors. We present here the application of queueing theory to simulate stochastic metabolic networks with high efficiency. With the use of glycolysis as a well understood biological model, we demonstrate the power of the proposed modeling methods discussed herein. Furthermore, we describe the simulation and pharmacological inhibition of glycolysis to provide an example of modeling capabilities