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PurposeRisk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomography/magnetic resonance imaging (PET/MRI) in vivo models for predicting low-vs-high lesion risk (LH) as well as biochemical recurrence (BCR) and overall patient risk (OPR) with machine learning.MethodsFifty-two patients who underwent multi-parametric dual-tracer [18F]FMC and [68Ga]Ga-PSMA-11 PET/MRI as well as radical prostatectomy between 2014 and 2015 were included as part of a single-center pilot to a randomized prospective trial (NCT02659527). Radiomics in combination with ensemble machine learning was applied including the [68Ga]Ga-PSMA-11 PET, the apparent diffusion coefficient, and the transverse relaxation time-weighted MRI scans of each patient to establish a low-vs-high risk lesion prediction model (MLH). Furthermore, MBCR and MOPR predictive model schemes were built by combining MLH, PSA, and clinical stage values of patients. Performance evaluation of the established models was performed with 1000-fold Monte Carlo (MC) cross-validation. Results were additionally compared to conventional [68Ga]Ga-PSMA-11 standardized uptake value (SUV) analyses.ResultsThe area under the receiver operator characteristic curve (AUC) of the MLH model (0.86) was higher than the AUC of the [68Ga]Ga-PSMA-11 SUVmax analysis (0.80). MC cross-validation revealed 89% and 91% accuracies with 0.90 and 0.94 AUCs for the MBCR and MOPR models respectively, while standard routine analysis based on PSA, biopsy Gleason score, and TNM staging resulted in 69% and 70% accuracies to predict BCR and OPR respectively.ConclusionOur results demonstrate the potential to enhance risk classification in primary prostate cancer patients built on PET/MRI radiomics and machine learning without biopsy sampling.

BackgroundHybrid imaging became an instrumental part of medical imaging, particularly cancer imaging processes in clinical routine. To date, several radiomic and machine learning studies investigated the feasibility of in vivo tumor characterization with variable outcomes. This study aims to investigate the effect of recently proposed fuzzy radiomics and compare its predictive performance to conventional radiomics in cancer imaging cohorts. In addition, lesion vs. lesion+surrounding fuzzy and conventional radiomic analysis was conducted.MethodsPreviously published 11C Methionine (MET) positron emission tomography (PET) glioma, 18F-FDG PET/computed tomography (CT) lung, and 68GA-PSMA-11 PET/magneto-resonance imaging (MRI) prostate cancer retrospective cohorts were included in the analysis to predict their respective clinical endpoints. Four delineation methods including manually defined reference binary (Ref-B), its smoothed, fuzzified version (Ref-F), as well as extended binary (Ext-B) and its fuzzified version (Ext-F) were incorporated to extract imaging biomarker standardization initiative (IBSI)-conform radiomic features from each cohort. Machine learning for the four delineation approaches was performed utilizing a Monte Carlo cross-validation scheme to estimate the predictive performance of the four delineation methods.ResultsReference fuzzy (Ref-F) delineation outperformed its binary delineation (Ref-B) counterpart in all cohorts within a volume range of 938–354987 mm3 with relative cross-validation area under the receiver operator characteristics curve (AUC) of  +4.7–10.4. Compared to Ref-B, the highest AUC performance difference was observed by the Ref-F delineation in the glioma cohort (Ref-F: 0.74 vs. Ref-B: 0.70) and in the prostate cohort by Ref-F and Ext-F (Ref-F: 0.84, Ext-F: 0.86 vs. Ref-B: 0.80). In addition, fuzzy radiomics decreased feature redundancy by approx. 20%.ConclusionsFuzzy radiomics has the potential to increase predictive performance particularly in small lesion sizes compared to conventional binary radiomics in PET. We hypothesize that this effect is due to the ability of fuzzy radiomics to model partial volume effects and delineation uncertainties at small lesion boundaries. In addition, we consider that the lower redundancy of fuzzy radiomic features supports the identification of imaging biomarkers in future studies. Future studies shall consider systematically analyzing lesions and their surroundings with fuzzy and binary radiomics.

This study evaluates the influence of general anesthesia (GA) and spinal anesthesia (SA) on physiological and oxidative stress in parturients undergoing elective cesarean section, one of the most frequently performed surgical procedures worldwide. A total of 101 pregnant women were included, categorized into GA (n = 51) and SA (n = 50) groups. Blood samples were collected at three time points: one hour before surgery (Measurement 1), at umbilical cord clamping (Measurement 2), and two hours post-surgery (Measurement 3). Biomarkers of oxidative stress, complete blood count, and levels of biochemical parameters were measured. In second and/or third measurement, biochemical blood analysis showed increased prolactin and cortisol levels, followed by spike of glucose and insulin in the GA group. However, levels of tri-iodothyronine were reduced in both groups in the third measurement. Glutathione S-transferase (GST) activity was increased in both groups in third measurement. The results showed increased concentrations of total SH groups and decreased concentrations of non-protein SH groups in the GA group during Measurement 2. Lymphocyte count was found to be predictor of GST levels. The results indicate more a pronounced endocrine response in GA group and speak in favor of spinal anesthesia. Both kinds of anesthesia are equally safe in terms of the oxidative status of the tissue.

This paper deals with the local bifurcation analysis of a nanotube with a nanostring passing through it. Eringen’s two-phase local/nonlocal model and Eringen’s differential model are employed as constitutive equations. The governing equations are derived as two nonlinear first-order systems of ordinary differential equations. Nonlinear analysis is performed by using the Lyapunov–Schmidt method. The influence of the small length scale parameter and the phase parameter on critical buckling load, type of bifurcation and post-buckling shape of the nanotube is examined for both types of constitutive equations. Depending on the values of the small length scale parameter and the phase parameter, the critical buckling load corresponding to Eringen’s two-phase local/nonlocal model can be greater or less than that corresponding to Eringen’s differential model. It is shown that for both models supercritical pitchfork bifurcation occurs. The post-buckling shapes of nanotube, obtained by numerical integration, exhibit a qualitative difference between the two models.

A kinetic spectrophotometric method for determining residues of insecticide diflubenzuron 1(4-chlorphenyl)-3-(2,6-diflubenzoyl)urea (DFB) has been developed and validated. Kinetic method was based on the inhibitory effect of DFB on the oxidation reaction of sulfanilic acid (SA) by hydrogen peroxide in the presence of Co2+ ions in a phosphate buffer, which was monitored at 370 nm. DFB can be measured in the concentration interval 0.102 ? 3.40 ?g mL-1 and 3.40 ? 23.80 ?g mL-1. The detection and quantification limits of the method were calculated according to the 3? criteria and found to be 0.077 ?g mL-1 and 0.254 ?g Ml-1, respectively. The relative standard deviations for five replicate determinations of 0.102, 1.70 and 3.40 ?g mL-1 DFB were 2.08, 1.22 and 1.21 %, respectively, for the first concentration interval, and the recovery percentage values were from 94.12 to 97.35 %. HPLC method was used as a parallel method to verify results of the kinetic method. The kinetic method was successfully applied to determine diflubenzuron concentrations in spiked water and baby food samples after solid phase extraction of the samples. The F and t values at 95% confidence level are lower than the theoretical ones, confirming agreement of the developed and the HPLC method.

cDNA microarray technology has been increasingly used to monitor global gene expression patterns in various tissues and cell types. However, applications to mammalian development have been hampered by the lack of appropriate cDNA collections, particularly for early developmental stages. To overcome this problem, a PCR-based cDNA library construction method was used to derive 52,374 expressed sequence tags from pre- and peri-implantation embryos, embryonic day (E) 12.5 female gonad/mesonephros, and newborn ovary. From these cDNA collections, a microarray representing 15,264 unique genes (78% novel and 22% known) was assembled. In initial applications, the divergence of placental and embryonic gene expression profiles was assessed. At stage E12.5 of development, based on triplicate experiments, 720 genes (6.5%) displayed statistically significant differences in expression between placenta and embryo. Among 289 more highly expressed in placenta, 61 placenta-specific genes encoded, for example, a novel prolactin-like protein. The number of genes highly expressed (and frequently specific) for placenta has thereby been increased 5-fold over the total previously reported, illustrating the potential of the microarrays for tissue-specific gene discovery and analysis of mammalian developmental programs.

A modified method for the analysis of nicosulfuron, rimsulfuron and prosulfuron was developed and validated by using microwave-assisted extraction (MAE) and ultra-performance liquid chromatography with diode array detection in the ultraviolet region (HPLC-UV-DAD). The most important experimental parameters of extraction procedure and HPLC-UV-DAD technique were optimised in respect to those sulfonylurea herbicides. High recoveries of the microwave-assisted extraction were obtained by using a dichloromethane?acetonitrile mixture (2:1 volume ratio) acidified with acetic acid (0.8 vol.%) with the addition of urea. The mean recoveries at three spiking levels ranged from 97.47 to 98.76% for nicosulfuron, 97.88 to 99.17% for rimsulfuron and from 97.91 to 99.83% for prosulfuron. The limits of detection of nicosulfuron, rimsulfuron and prosulfuron were 0.95, 0.91 and 0.89 ?g kg?1, respectively. The accuracy of the developed method was confirmed by HPLC coupled with tandem mass spectrometry parallel analyses. The developed method was used to investigate the dissipation dynamics of sulfonylurea herbicides in the real field trials in Vojvodina Province, Serbia. The obtained half-lives were 0.05, 0.23 and 0.15 days for recommended dose application of nicosulfuron, rimsulfuron and prosulfuron, respectively. Low residues and short half-life in soil suggested that the risk to sensitive rotational crops after application of those sulfonylurea herbicides is low when they are used in the appropriate dosages.

The aim of this study was to explore adherence to the Consolidated Standards of Reporting Trials (CONSORT) reporting standards in abstracts of randomized controlled trials on glaucoma. A cross-sectional observational study was conducted on the aforementioned abstracts, indexed in MEDLINE/PubMed between the years 2017 and 2021. In total, 302 abstracts met the inclusion criteria and were further analyzed. The median score of CONSORT-A items was 8 (interquartile range, 7–10) out of 17 (47.0%). Most analyzed studies were conducted in a single center (80.5%) and the abstracts were predominantly structured (95.0%). Only 20.5% of the abstracts adequately described the trial design, while randomization and funding were described by 6.0% of the abstracts. Higher overall scores were associated with structured abstracts, a multicenter setting, statistically significant results, funding by industry, a higher number of participants, and having been published in journals with impact factors above four (p < 0.001, respectively). The results of this study indicate a suboptimal adherence to CONSORT-A reporting standards, especially in particular items such as randomization and funding. Since these factors could contribute to the overall quality of the trials and further translation of trial results into clinical practice, an improvement in glaucoma research reporting transparency is needed.

In the period from 2012-2015 plant samples with fireblight symptoms were collected from pome fruit and indigenous plant, in main fruitgrowing regions of Montenegro. After succesfull isolation, pathogenicity of the obtained strains was tested by artificial inoculation of immature pear fruits, variety Viljamovka. Hypersensitive reaction was tested on tobacco leaves, variety White Burley. Identification and genetic diversity studies were performed using several molecular techniques on 18 Erwinia amylovora strains originating from quince, pear, apple and hawthorn. Bacterial identity was confirmed by nested PCR in which all studied strains produced the expected amplification fragment of plasmid pEA29. To detect potential genetic variations in E. amylovora population, rep-PCR was conducted. Using REP, ERIC and BOX primers, in all three PCR reactions, differences between studied strains were detected, i.e. pear strains had different genetic profiles from all other studied strains, including reference strain. Genetic variability of selected E. amylovora strains was studied by RAPD-PCR as well. Both of the used random primers, CUGEA-3 and CUGEA-5, showed discriminatory potential by separating genetic profiles of pear strains from all other studied strains, including reference strain. This is the first study of genetic variability of E. amylovora in Montenegro.

In the period from 2012-2015 plant samples with fireblight symptoms were collected from pome fruits and indigenous plant, in main fruitgrowing regions of Montenegro. After succesfull isolation, pathogenicity of the obtained strains was tested by artificial inoculation of immature pear fruits, variety Viljamovka. Hypersensitive reaction was tested on tobacco leaves, variety White Burley. Identification and genetic diversity studies were performed using several molecular techniques on 18 Erwinia amylovora strains originating from quince, pear, apple and hawthorn. Bacterial identity was confirmed by nested PCR in which all studied strains produced the expected amplification fragment of plasmid pEA29. To detect potential genetic variations in E. amylovora population, rep-PCR was conducted. Using REP, ERIC and BOX primers, in all three PCR reactions, differences between studied strains were detected, i.e. pear strains had different genetic profiles from all other studied strains, including reference strain. Genetic variability of selected E. amylovora strains was studied by RAPD-PCR as well. Both of the used random primers, CUGEA-3 and CUGEA-5, showed discriminatory potential by separating genetic profiles of pear strains from all other studied strains, including reference strain. This is the first study of genetic variability of E. amylovora in Montenegro.