Automatic segmentation of the prostate on Magnetic Resonance Imaging (MRI) is one of the topics on which research has focused in recent years as it is a fundamental first step in the building process of a Computer aided diagnosis (CAD) system for cancer detection. Unfortunately, MRI acquired in different centers with different scanners leads to images with different characteristics. In this work, we propose an automatic algorithm for prostate segmentation, based on a U-Net applying transfer learning method in a bi-center setting. First, T2w images with and without endorectal coil from 80 patients acquired at Center A were used as training set and internal validation set. Then, T2w images without endorectal coil from 20 patients acquired at Center B were used as external validation. The reference standard for this study was manual segmentation of the prostate gland performed by an expert operator. The results showed a Dice similarity coefficient >85% in both internal and external validation datasets.Clinical Relevance— This segmentation algorithm could be integrated into a CAD system to optimize computational effort in prostate cancer detection.

Colorectal cancer (CRC) has the second-highest tumor incidence and is a leading cause of death by cancer. Nearly 20% of patients with CRC will have metastases (mts) at the time of diagnosis, and more than 50% of patients with CRC develop metastases during their disease. Unfortunately, only 45% of patients after a chemotherapy will respond to treatment. The aim of this study is to develop and validate a machine learning algorithm to predict response of individual liver mts, using CT scans. Understanding which mts will respond or not will help clinicians in providing a more efficient per-lesion treatment based on patient specific response and not only following a standard treatment. A group of 92 patients was enrolled from two Italian institutions. CT scans were collected, and the portal venous phase was manually segmented by an expert radiologist. Then, 75 radiomics features were extracted both from 7x7 ROIs that moved across the image and from the whole 3D mts. Feature selection was performed using a genetic algorithm. Results are presented as a comparison of the two different approaches of features extraction and different classification algorithms. Accuracy (ACC), sensitivity (SE), specificity (SP), negative and positive predictive values (NPV and PPV) were evaluated for all lesions (per-lesion analysis) and patients (per-patient analysis) in the construction and validation sets. Best results were obtained in the per-lesion analysis from the 3D approach using a Support Vector Machine as classifier. We reached on the training set an ACC of 81%, while on test set, we obtained SE of 76%, SP of 67%, PPV of 69% and NPV of 75%. On the validation set a SE of 61%, SP of 60%, PPV of 57% and NPV of 64% were reached. The promising results obtained in the validation dataset should be extended to a larger cohort of patient to further validate our method.Clinical Relevance— to develop a radiomics signatures predicting single liver mts response to therapy. A personalized mts approach is important to avoid unnecessary toxicity offering more suitable treatments and a better quality of life to oncological patients.

The paper presents the results of modeling the bending strength of wood. During the experimental examination and definition of the model, solid wood was taken, where the bending was performed perpendicular to the grain. The experiment was done with thirteen replications and the input values that varied at three levels were wood density and board thickness. The thirteen-repetition experiment also involved four repetitions in the marginal areas, so two more wood densities and two board thicknesses had to be taken. The experimental measurement was performed in the laboratory of the Technical Faculty Bihać. Based on the experimental results, a sufficiently adequate mathematical model of the breaking force of a solid wood panel perpendicular to the grain is obtained.

Paper presents the design of experiment and determining mathematical model to calculate roughness parameter of wood planned surface. For design of experiment three different types of solid wood were taken and processed on the planner with three different displacements and three different cutting speeds. After measuring the roughness parameter Rz, experimental results were obtained on the basis of which the central composite plan of the experiment was made. Based on that, a model of roughness parameter Rz was made, which is adequate and with high accuracy. The significance of the model coefficients was determined using the R software and the results were presented using the Design Expert software.

Breast cancer is the most commonly occurring malignancy and the leading cause of cancer-related death in women. Triple-negative breast cancer (TNBC) is the most aggressive subtype and is associated with high recurrence rates, high incidence of distant metastases, and poor overall survival. The aim of this study was to investigate the PI3K/PTEN/Akt/mTOR pathway as one of the most frequently deregulated pathways in cancer. We aimed to explore the impact of PI3K and mTOR oncogenes as well as the PTEN tumor suppressor on TNBC clinical behavior, prognosis, and multidrug resistance (MDR), using immunohistochemistry and copy number analysis by quantitative real-time PCR. Our results revealed that loss of PTEN and high expression of PI3K and mTOR proteins are associated with poor outcome of TNBC patients. PTEN deletions appeared as a major cause of reduced or absent PTEN expression in TNBC. Importantly, homozygous deletions of PTEN (and not hemizygous deletions) are a potential molecular marker of metastasis formation and good predictors of TNBC outcome. In conclusion, we believe that concurrent examination of PTEN/PI3K/mTOR protein expression may be more useful in predicting TNBC clinical course than the analysis of single protein expression. Specifically, our results showed that PTEN-reduced/PI3K-high/mTOR-high expression constitutes a ‘high risk’ profile of TNBC.

Abstract Background Antimicrobial impregnated catheters (AIC) are one strategy to prevent CLABSI with existing data for central lines required for short duration, however, the strength of evidence, particularly for children, is lacking. Recent 3-year CLABSI data at our institution show 60 (51%) infections occurred in central lines within 8 weeks of insertion, suggesting an opportunity for evaluation of an intervention targeting this time frame. We implemented AIC to evaluate their effectiveness in reducing CLABSI standardized infection ratio (SIR) in patients requiring central venous access for less than 8 weeks. We also monitored for complications (malfunction, line exchange, fungal infection). Methods A stepped wedge observational design was used to implement Minocycline + Rifampin impregnated catheters in a rolling fashion across the institution. Children > 3kg were eligible if admitted to a participating unit and required central venous access through a peripherally inserted central catheter (PICC), non-tunneled catheter, or tunneled non-cuffed femoral catheter for < 8 weeks. Units, prioritized based on CLABSI SIR, were added to the intervention monthly until AIC were used throughout the institution. A multidisciplinary team (infectious diseases and infection control experts, CLABSI leaders, unit-based physicians and nurses, proceduralists, supply chain) met weekly to facilitate implementation, assess for CLABSI and monitor for complications. Figure 1. Study design. This figure describes the stepped wedge study design where units were phased into the invention on a rolling monthly basis allowing for comparison between and within units. The shaded boxes represent time periods when units were using antimicrobial impregnated catheters and the white boxes represent time periods when units were using standard non-impregnated catheters. Results AIC were systematically implemented over a 7-month period. The institution’s CLABSI SIR decreased from 0.80 to 0.59 during this timeframe. There were no NHSH defined CLABSI in patients with an AIC during the intervention. Obstacles included shortage of catheters due to supply chain disruption, adjustment of technique for line insertion and cracked/broken lines. Infections and complications were reviewed by the multidisciplinary team and compared to historical rates with non-impregnated lines. This figure shows the institution’s rolling 12-month SIR during the intervention period. Conclusion CLABSI SIR decreased at our institution during the intervention period. While many efforts likely led to this reduction (optimizing maintenance bundle, unit based CLABSI initiatives), we believe the use of AIC contributed to this improvement. There were no pediatric-specific safety events identified during implementation. Disclosures Ravi Jhaveri, MD, AstraZeneca (Consultant)Dynavax (Consultant)Elsevier (Other Financial or Material Support, Editorial stipend as Co-EiC, Clinical Therapeutics)Hologic (Consultant)Seqirus (Consultant)

INTRODUCTION Scientometrics is a subfield of bibliometrics that statistically analyzes publications trends. The aim of this initial study was to investigate trends in the 6 major neurosurgical journals from the last 10 years. METHODS We searched Web of Science and Scopus for articles published in Neurosurgery, Journal of Neurosurgery, Journal of Neurosurgery: Spine, Journal of Neurosurgery: Pediatrics, Operative Neurosurgery, and World Neurosurgery from January 1, 2011, to December 31, 2020. Statistically analyzed parameters included national and continental distribution of articles, population density, density of neurosurgeons per 100,000 inhabitants, national per capita GDP, and national literacy rates. Bibliometric parameters assessed included total number of articles, H-indices, absolute/average number of citations per article, and article types. RESULTS A total of 39,239 articles were published in the 6 journals. Journal of Neurosurgery and Neurosurgery had the strongest source impact. The most productive year was 2019 with 6811 published articles. Corresponding authors from the USA, China, Japan, Western Europe, and Turkey were the most productive. Articles published by authors from the USA received the majority of citations. Publication numbers increased in proportion with increases in country population, literacy rate, per capita GDP, and neurosurgeon density. The highest number of articles were published in 2016, and the fewest were published in 2020. CONCLUSIONS Geographic trends in the diversity of neurosurgical publications sustained its steady increase in most developed counties. Simultaneously, the publication gap between developed and developing countries has remained stagnant.

Highlights • The functional characterization of callosal connections is informed by anatomical data.• Callosal connections play a conditional driving role depending on the brain state and behavioral demands.• Callosal connections play a modulatory function, in addition to a driving role.• The corpus callosum participates in learning and interhemispheric transfer of sensorimotor habits.• The corpus callosum contributes to language processing and cognitive functions.

The Travelling Salesman Problem is categorized as NP-complete problems called combinatorial optimization problems. For the growing number of cities it is unsolvable with the use of exact methods in a reasonable time. Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea. These methods do not ensure optimal solutions, however they give good approximation usually in time. Studies have shown that the proposed genetic algorithm can find a shorter route in real time, compared with the existing manipulator model of path selection. The genetic algorithm depends on the selection criteria, crosses, and mutation operators described in detail in this paper. Possible settings of the genetic algorithm are listed and described, as well as the influence of mutation and crossing operators on the efficiency of the genetic algorithm. The optimization results are presented graphically in the MATLAB software package for different cases, after which a comparison of the efficiency of the genetic algorithm with respect to the given parameters is performed.

UDK: 630*52:519.233.5]:582.475(497.6) As the result of sporadic afforestation of not-grown forest land in the past, today in B&H we have significant areas of even-aged forest plants of Scots pine of different ages. Estimate of yield capabilities of habitats/sites of these stands is one of very real issues in even-aged management planning for this tree species. In order to get the clear idea on the value of yield of even-aged stands, it is necessary to conduct long-term researches on permanent experimental plots. Considering that for the results of those researches it is necessary to wait approximately for the duration of production periods for specific tree species, to gain orientation solutions of the problem we can apply short-term researches – using temporary experimental plots set in stands of different ages. Members of the Forest Management Department of Forestry Faculty in Sarajevo in a period from 1985 to 1990 gathered data on temporary experimental plots in existing even-aged forest plantations of spruce, Scots pine and black pine in order to research their growth, structural and production characteristics. Part of those data for Scots pine is used for making of this document. Objective of this research was, based on data on measurement of 77 experimental plots positioned in even-aged not-tended plantations of Scots pine Bosnia-wide, to reach relevant information on the value of wood volume depending on their age and site quality, and to create the most favourable regression model for assessment of volume of large wood value based on known values of the stand taxation elements that could be easily and quickly determined. Besides this, in this document by comparing gained results with appropriate data from other authors we have evaluated productivity of even-aged not-tended forest plantations of Scots pine in B&H.

Thermostability of vaccines and biologic drugs are key to increasing global access to a variety of life-saving agents. In this report, we characterize interactions between a novel zwitterionic surfactant and adenovirus serotype 5 which allow the virus to remain stable at room temperature in a thin film matrix. Complexity of the adenovirus capsid and the polydispersity of the surfactant required use of a variety of techniques to achieve this goal. The CMC of the surfactant in Tris buffer (pH 6.5) was estimated to be 0.7-1.17 × 10-4 M by the pyrene 1:3 ratio method. TEM images depict micelle formation around virus capsids. An estimated Kd of the virus-surfactant interaction of 2.25 × 10-9 M was determined by isothermal titration calorimetry. Associated data suggest that this interaction may be thermodynamically favorable and entropically driven. A competitive saturation study and TEM images indicate that the surfactant also binds to hexon proteins on the virus capsid. Taken together, these data support the working hypothesis that the surfactant is capable of forming micelles in the solid and liquid state and that it forms a protective coating around the virus by binding to hexon proteins on the virus capsid during the film forming process.

Background: Water-pipe smoking (WPS), a predominant method of tobacco consumption, is common amongst young females in the Middle East. WPS smoke consists of toxins analogous to the ones that exist in cigarette smoke and frequently correlates with the onset of several types of human cancers including breast. However, the potential target genes and their underlying mechanisms in the initiation and/ or progression of human cancers, especially breast, due to WPS exposure are still unknown. Materials and Methods: In this investigation, we explored the effect of WPS chronic exposure on human normal mammary epithelial cells and analyzed alterations in the differentially ex-pressed gene (DEG) targets using the NanoString nCounter PanCancer Pathways Panel consisting of 770 gene transcripts and a quantitative real-time polymerase chain reaction (PCR) analysis. Results: Our NanoString analysis identified 13 genes dysregulated under the effect of WPS exposure involved in regulating signal transduction, cell cycle, cell motility, proliferation and migration/invasion as well as the inflammatory response. We further performed an in silico analysis to investigate the effect of the identified genes in the prognosis of breast cancer patients and reported those DEGs that directly correlated with smoking and were upregulated in breast cancer in comparison with normal tissue. Moreover, the Kaplan–Meier curve analysis showed a significant correlation be-tween WPS-dysregulated genes (MX1, CCL8, GNGT1 and MMP9) and relapse-free survival in breast cancer patients. Conclusions: Our data clearly suggest that exposure to WPS can alter the expression of key regulator genes involved in the pathogenesis of breast cancer, thereby affecting the breast cancer prognosis.

Recurrent Respiratory Papillomatosis (RRP) is a rare but severe manifestation of human papillomavirus (HPV). As our knowledge about HPV infections has expanded, it has become possible to understand the course of RRP disease and unravel plausible efficient methods to manage the disease. However, the surge in reports on HPV has not been accompanied by a similar increase in research about RRP specifically. In this paper, we review the clinical manifestation and typical presentation of the illness. In addition, the pathogenesis and progression of the disease are described. On the other hand, we discuss the types of treatments currently available and future treatment strategies. The role of vaccination in both the prevention and treatment of RRP will also be reviewed. We believe this review is essential to update the general knowledge on RRP with the latest information available to date to enhance our understanding of RRP and its management.

Simple Summary Fascin, an actin-binding protein, is upregulated in different types of human cancers. It is reportedly responsible for increasing the invasive and metastatic ability of cancer cells by reducing cell–cell adhesions. This review provides a brief overview of fascin and its interactions with other genes and oncoviruses to induce the onset and progression of cancer. Abstract Fascin is an actin-binding protein that is encoded by the FSCN1 gene (located on chromosome 7). It triggers membrane projections and stimulates cell motility in cancer cells. Fascin overexpression has been described in different types of human cancers in which its expression correlated with tumor growth, migration, invasion, and metastasis. Moreover, overexpression of fascin was found in oncovirus-infected cells, such as human papillomaviruses (HPVs) and Epstein-Barr virus (EBV), disrupting the cell–cell adhesion and enhancing cancer progression. Based on these findings, several studies reported fascin as a potential biomarker and a therapeutic target in various cancers. This review provides a brief overview of the FSCN1 role in various cancers with emphasis on gynecological malignancies. We also discuss fascin interactions with other genes and oncoviruses through which it might induce cancer development and progression.