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Background: Prostate cancer is a major health concern in aging men. Paralleling an aging society, prostate cancer prevalence increases emphasizing the need for efcient diagnostic algorithms.
Methods: Retrospectively, 106 prostate tissue samples from 48 patients (mean age,
66 ± 6.6 years) were included in the study. Patients sufered from prostate cancer (n = 38) or benign prostatic hyperplasia (n = 10) and were treated with radical prostatectomy or Holmium laser enucleation of the prostate, respectively. We constructed tissue microarrays (TMAs) comprising representative malignant (n = 38) and benign (n = 68) tissue cores. TMAs were processed to histological slides, stained, digitized and assessed for the applicability of machine learning strategies and open–source tools in diagnosis of prostate cancer. We applied the software QuPath to extract features for shape, stain intensity, and texture of TMA cores for three stainings, H&E, ERG, and PIN-4. Three machine learning algorithms, neural network (NN), support vector machines (SVM), and random forest (RF), were trained and cross-validated with 100 Monte Carlo random splits into 70% training set and 30% test set. We determined AUC values for single color channels, with and without optimization of hyperparameters by exhaustive grid search. We applied recursive feature elimination to feature sets of multiple color transforms.
Results: Mean AUC was above 0.80. PIN-4 stainings yielded higher AUC than H&E and
ERG. For PIN-4 with the color transform saturation, NN, RF, and SVM revealed AUC of 0.93 ± 0.04, 0.91 ± 0.06, and 0.92 ± 0.05, respectively. Optimization of hyperparameters improved the AUC only slightly by 0.01. For H&E, feature selection resulted in no increase of AUC but to an increase of 0.02–0.06 for ERG and PIN-4.
Conclusions: Automated pipelines may be able to discriminate with high accuracy between malignant and benign tissue. We found PIN-4 staining best suited for classifcation. Further bioinformatic analysis of larger data sets would be crucial to evaluate the reliability of automated classifcation methods for clinical practice and to evaluate potential discrimination of aggressiveness of cancer to pave the way to automatic precision medicine.
Climate change affects ecosystems worldwide and is threatening biodiversity. Insects, as ectotherm organisms, are strongly dependent on the thermal environment. Yet, little is known about the effects of summer heat and drought on insect diversity. In the Mediterranean climate zone, a region strongly affected by climate change, hot summers might have severe effects on insect communities. Especially the larval stage might be sensitive to thermal variation, as larvae—compared to other life stages—cannot avoid hot temperatures and drought by dormancy. Here we ask, whether inter-annual fluctuations in Mediterranean moth diversity can be explained by temperature (TLarv) and precipitation during larval development (HLarv). To address our question, we analyzed moth communities of a Mediterranean coastal forest during the last 20 years. For species with summer-developing larvae, species richness was significantly negatively correlated with TLarv, while the community composition was affected by both, TLarv and HLarv. Therefore, summer-developing larvae seem particularly sensitive to climate change, as hot summers might exceed the larval temperature optima and drought reduces food plant quality. Increasing frequency and severity of temperature and drought extremes due to climate change, therefore, might amplify insect decline in the future.
This prospective study sought to evaluate potential savings of radiation dose to medical staff using real-time dosimetry coupled with visual radiation dose feedback during angiographic interventions. For this purpose, we analyzed a total of 214 angiographic examinations that consisted of chemoembolizations and several other types of therapeutic interventions. The Unfors RaySafe i2 dosimeter was worn by the interventionalist at chest height over the lead protection. A total of 110 interventions were performed with real-time radiation dosimetry allowing the interventionalist to react upon higher x-ray exposure and 104 examinations served as the comparative group without real-time radiation monitoring. By using the real-time display during interventions, the overall mean operator radiation dose decreased from 3.67 (IQR, 0.95–23.01) to 2.36 μSv (IQR, 0.52–12.66) (−36%; p = 0.032) at simultaneously reduced operator exposure time by 4.5 min (p = 0.071). Dividing interventions into chemoembolizations and other types of therapeutic interventions, radiation dose decreased from 1.31 (IQR, 0.46-3.62) to 0.95 μSv (IQR, 0.53-3.11) and from 24.39 (IQR, 12.14-63.0) to 10.37 μSv (IQR, 0.85-36.84), respectively, using live-screen dosimetry (p ≤ 0.005). Radiation dose reductions were also observed for the participating assistants, indicating that they could also benefit from real-time visual feedback dosimetry during interventions (−30%; p = 0.039). Integration of real-time dosimetry into clinical processes might be useful in reducing occupational radiation exposure time during angiographic interventions. The real-time visual feedback raised the awareness of interventionalists and their assistants to the potential danger of prolonged radiation exposure leading to the adoption of radiation-sparing practices. Therefore, it might create a safer environment for the medical staff by keeping the applied radiation exposure as low as possible.
Biodiversity patterns of marine crustaceans are still unknown in many locations or might have been overlooked due to our knowledge gaps, despite increasing sampling and data sharing efforts during the last decades. By analysing big data extracted from open portals such as Ocean Biodiversity Information System (OBIS) and Global Biodiversity Information System (GBIF), we aim to revisit the distribution and biodiversity patterns of the highly speciose and abundant Crustacea in the Northwest Pacific (NWP) from shallowest depths to the deep sea. This study focussed on selected benthic and pelagic crustacean (sub) classes and their species richness, sampling effort, and expected species richness (ES50) using equal/sized hexagonal cells, 5° latitudinal bands, 500 m depth intervals were analyzed. Crustacean species richness was highest in the tropical Philippines as well as around the Japanese islands. Pelagic crustacean species richness peaked at 30° latitude and declined beyond that. Benthic taxa; however, depicted high levels of species richness across most of the latitudinal gradient, reaching its highest point at 45° latitude. Due to the prevalence of certain crustacean orders in the deep sea, benthic species richness showed a distribution pattern with two distinct peaks across bathymetric gradients; with highest species richness recorded at shallow-water depths and also at abyssal depths. The most important environmental drivers of benthic and pelagic crustacean species richness were primary productivity (positive correlation) and salinity (negative correlation). Our study provides first insights into biodiversity patterns of the highly diverse Crustacea in the NWP and highlights strong differences between benthic and pelagic taxa. The results presented here could help us to better understand whether benthic or pelagic taxa might respond differently to climate changes in the NWP based on their distinct physiological and biological characteristics. This information is crucial in establishing species management strategies and ecosystem restorations in both shallow water and deep-sea environments.
The combination of histological and biomolecular analyses provides deep understanding of different biological processes and is of high interest for basic and applied research. However, the available analytical methods are still limited, especially when considering bone samples. This study compared different fixation media to identify a sufficient analytical method for the combination of histological, immuno-histological and biomolecular analyses of the same fixed, processed and paraffin embedded bone sample. Bone core biopsies of rats’ femurs were fixed in different media (RNAlater + formaldehyde (R + FFPE), methacarn (MFPE) or formaldehyde (FFPE)) for 1 week prior to decalcification by EDTA and further histological processing and paraffin embedding. Snap freezing (unfixed frozen tissue, UFT) and incubation in RNAlater were used as additional controls. After gaining the paraffin sections for histological and immunohistological analysis, the samples were deparaffined and RNA was isolated by a modified TRIZOL protocol. Subsequently, gene expression was evaluated using RT-qPCR. Comparable histo-morphological and immuno-histological results were evident in all paraffin embedded samples of MFPE, FFPE and R + FFPE. The isolated RNA in the group of MFPE showed a high concentration and high purity, which was comparable to the UFT and RNAlater groups. However, in the groups of FFPE and R + FFPE, the RNA quality and quantity were statistically significantly lower when compared to MFPE, UFT and RNAlater. RT-qPCR results showed a comparable outcome in the group of MFPE and UFT, whereas the groups of FFPE and R + FFPE did not result in a correctly amplified gene product. Sample fixation by means of methacarn is of high interest for clinical samples to allow a combination of histological, immunohistological and biomolecular analysis. The implementation of such evaluation method in clinical research may allow a deeper understanding of the processes of bone formation and regeneration.
Alternating acquisition of background and sample spectra is often employed in conventional Fourier-transform infrared spectroscopy or ultraviolet–visible spectroscopy for accurate background subtraction. For example, for solvent background correction, typically a spectrum of a cuvette with solvent is measured and subtracted from a spectrum of a cuvette with solvent and solute. Ultrafast spectroscopies, though, come with many peculiarities that make the collection of well-matched, subtractable background and sample spectra challenging. Here, we present a demountable split-sample cell in combination with a modified Lissajous scanner to overcome these challenges. It allows for quasi-simultaneous measurements of background and sample spectra, mitigating the effects of drifts of the setup and maintaining the beam and sample geometry when swapping between background and sample measurements. The cell is moving between subsequent laser shots to refresh the excited sample volume. With less than 45 μl of solution for 150 μm optical thickness, sample usage is economical. Cell assembly is a key step and covered in an illustrated protocol.
Hepatic cells are sensitive to internal and external signals. Ethanol is one of the oldest and most widely used drugs in the world. The focus on the mechanistic engine of the alcohol-induced injury has been in the liver, which is responsible for the pathways of alcohol metabolism. Ethanol undergoes a phase I type of reaction, mainly catalyzed by the cytoplasmic enzyme, alcohol dehydrogenase (ADH), and by the microsomal ethanol-oxidizing system (MEOS). Reactive oxygen species (ROS) generated by cytochrome (CYP) 2E1 activity and MEOS contribute to ethanol-induced toxicity. We aimed to: (1) Describe the cellular, pathophysiological and clinical effects of alcohol misuse on the liver; (2) Select the biomarkers and analytical methods utilized by the clinical laboratory to assess alcohol exposure; (3) Provide therapeutic ideas to prevent/reduce alcohol-induced liver injury; (4) Provide up-to-date knowledge regarding the Corona virus and its affect on the liver; (5) Link rare diseases with alcohol consumption. The current review contributes to risk identification of patients with alcoholic, as well as non-alcoholic, liver disease and metabolic syndrome. Additional prevalence of ethnic, genetic, and viral vulnerabilities are presented.
Growing up in cities is associated with increased risk for developing mental health problems. Stress exposure and altered stress regulation have been proposed as mechanisms linking urbanicity and psychopathology, with most research conducted in adult populations. Here, we focus on early childhood, and investigate urbanicity, behavior problems and the regulation of the hypothalamus-pituitary-adrenal (HPA) axis, a central circuit of the stress system, in a sample of N = 399 preschoolers aged 45 months. Urbanicity was coded dichotomously distinguishing between residences with more or less than 100,000 inhabitants. Behavior problems were measured using the Child Behavior Checklist (CBCL) 1½ - 5. Cortisol stress reactivity was assessed using an age-appropriated game-like stress task, and cortisol in the first morning urine was measured to assess nocturnal HPA axis activity. Urbanicity was not associated with behavior problems, urinary cortisol or the cortisol stress response. Neither urinary cortisol nor salivary cortisol response after stress exposure were identified as mediators of the relationship between urbanicity and behavior problems. The findings suggest no strong association of urbanicity with behavior problems and HPA axis regulation in preschool age. To our knowledge, this is the youngest sample to date studying the relationship between urbanicity and behavior problems as well as HPA axis regulation. Future research should examine at which age associations can first be identified and which mechanisms contribute to these relationships.
Aim
To compare overall mortality (OM), cancer-specific mortality (CSM), and other cause mortality (OCM) rates between radical prostatectomy (RP) versus radiotherapy (RT) in clinical node-positive (cN1) prostate cancer (PCa).
Materials and Methods
Within Surveillance, Epidemiology, End Results (SEER) (2004–2016), we identified 4685 cN1 PCa patients, of whom 3589 (76.6%) versus 1096 (24.4%) were treated with RP versus RT. After 1:1 propensity score matching (PSM), Kaplan–Meier plots and Cox regression models tested the effect of RP versus RT on OM, while cumulative incidence plots and competing-risks regression (CRR) models addressed CSM and OCM between RP and RT patients. All analyses were repeated after the inverse probability of treatment weighting (IPTW). For CSM and OCM analyses, the propensity score was used as a covariate in the regression model.
Results
Overall, RT patients were older, harbored higher prostate-specific antigen values, higher clinical T and higher Gleason grade groups. PSM resulted in two equally sized groups of 894 RP versus 894 RT patients. After PSM, 5-year OM, CSM, and OCM rates were, respectively, 15.4% versus 25%, 9.3% versus 17%, and 6.1% versus 8% for RP versus RT (all p < 0.001) and yielded respective multivariate hazard ratios (HRs) of 0.63 (0.52–0.78, p < 0.001), 0.66 (0.52–0.86, p < 0.001), 0.71 (0.5–1.0, p = 0.05), all favoring RP. After IPTW, Cox regression models yielded HR of 0.55 (95% confidence interval [CI] = 0.46–0.66) for OM, and CRR yielded HRs of 0.49 (0.34–0.70) and 0.54 (0.36–0.79) for, respectively, CSM and OCM, all favoring RP (all p < 0.001).
Conclusions
RP may hold a CSM advantage over RT in cN1 PCa patients.