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Background: To evaluate the impact of time to castration resistance (TTCR) in metastatic hormone-sensitive prostate cancer (mHSPC) patients on overall survival (OS) in the era of combination therapies for mHSPC.
Material and Methods: Of 213 mHSPC patients diagnosed between 01/2013-12/2020 who subsequently developed metastatic castration resistant prostate cancer (mCRPC), 204 eligible patients were analyzed after having applied exclusion criteria. mHSPC patients were classified into TTCR <12, 12-18, 18-24, and >24 months and analyzed regarding OS. Moreover, further OS analyses were performed after having developed mCRPC status according to TTCR. Logistic regression models predicted the value of TTCR on OS.
Results: Median follow-up was 34 months. Among 204 mHSPC patients, 41.2% harbored TTCR <12 months, 18.1% for 12-18 months, 15.2% for 18-24 months, and 25.5% for >24 months. Median age was 67 years and median PSA at prostate cancer diagnosis was 61 ng/ml. No differences in patient characteristics were observed (all p>0.05). According to OS, TTCR <12 months patients had the worst OS, followed by TTCR 12-18 months, 18-24 months, and >24 months, in that order (p<0.001). After multivariable adjustment, a 4.07-, 3.31-, and 6.40-fold higher mortality was observed for TTCR 18-24 months, 12-18 months, and <12 months patients, relative to TTCR >24 months (all p<0.05). Conversely, OS after development of mCRPC was not influenced by TTCR stratification (all p>0.05).
Conclusion: Patients with TTCR <12 months are at the highest OS disadvantage in mHSPC. This OS disadvantage persisted even after multivariable adjustment. Interestingly, TTCR stratified analyses did not influence OS in mCRPC patients.
The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
he most basic behavioural states of animals can be described as active or passive. While high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g).
We used a dataset containing >3 million signals from very-high-frequency (VHF) telemetry from two forest-dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF-tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98).
We provide an ecological case-study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method.
Our approach can classify VHF-signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state-of-the-art open-source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
Background: We aimed to determine the concordance between the radiologic stage (rT), using multiparametric magnetic resonance imaging (mpMRI), and pathologic stage (pT) in patients with high-risk prostate cancer and its influence on nerve-sparing surgery compared to the use of the intraoperative frozen section technique (IFST). Methods: The concordance between rT and pT and the rates of nerve-sparing surgery and positive surgical margin were assessed for patients with high-risk prostate cancer who underwent radical prostatectomy. Results: The concordance between the rT and pT stages was shown in 66.4% (n = 77) of patients with clinical high-risk prostate cancer. The detection of patients with extraprostatic disease (≥pT3) by preoperative mpMRI showed a sensitivity, negative predictive value and accuracy of 65.1%, 51.7% and 67.5%. In addition to the suspicion of extraprostatic disease in mpMRI (≥rT3), 84.5% (n = 56) of patients with ≥rT3 underwent primary nerve-sparing surgery with IFST, resulting in 94.7% (n = 54) of men with at least unilateral nerve-sparing surgery after secondary resection with a positive surgical margin rate related to an IFST of 1.8% (n = 1). Conclusion: Patients with rT3 should not be immediately excluded from nerve-sparing surgery, as by using IFST some of these patients can safely undergo nerve-sparing surgery.
Acute kidney injury is associated with mortality in COVID-19 patients. However, host cell changes underlying infection of renal cells with SARS-CoV-2 remain unknown and prevent understanding of the molecular mechanisms that may contribute to renal pathology. Here, we carried out quantitative translatome and whole-cell proteomics analyses of primary renal proximal and distal tubular epithelial cells derived from human donors infected with SARS-CoV-2 or MERS-CoV to disseminate virus and cell type–specific changes over time. Our findings revealed shared pathways modified upon infection with both viruses, as well as SARS-CoV-2-specific host cell modulation driving key changes in innate immune activation and cellular protein quality control. Notably, MERS-CoV infection–induced specific changes in mitochondrial biology that were not observed in response to SARS-CoV-2 infection. Furthermore, we identified extensive modulation in pathways associated with kidney failure that changed in a virus- and cell type–specific manner. In summary, we provide an overview of the effects of SARS-CoV-2 or MERS-CoV infection on primary renal epithelial cells revealing key pathways that may be essential for viral replication.
The objective of the study was to test the impact of implementing standard full functional-length urethral sphincter (FFLU) and neurovascular bundle preservation (NVBP) with intraoperative frozen section technique (IFT) on long-term urinary continence in patients undergoing robotic-assisted radical prostatectomy (RARP). We relied on an institutional tertiary-care database to identify patients who underwent RARP between 01/2014 and 09/2019. Until 10/2017, FFLU was not performed and decision for NVBP was taken without IFT. From 11/2017, FFLU and IFT-guided NVBP was routinely performed in all patients undergoing RARP. Long-term continence (≥ 12 months) was defined as the usage of no or one safety- pad. Uni- and multivariable logistic regression models tested the correlation between surgical approach (standard vs FFLU + NVBP) and long-term continence. Covariates consisted of age, body mass index, prostate volume and extraprostatic extension of tumor. The study cohort consisted of 142 patients, with equally sized groups for standard vs FFLU + NVBP RARP (68 vs 74 patients). Routine FFLU + NVBP implementation resulted in a long-term continence rate of 91%, compared to 63% in standard RARP (p < 0.001). Following FFLU + NVBP RARP, 5% needed 1–2, 4% 3–5 pads/24 h and no patient (0%) suffered severe long-term incontinence (> 5 pads/24 h). No significant differences in patient or tumor characteristics were recorded between both groups. In multivariable logistic regression models, FFLU + NVBP was a robust predictor for continence (Odds ratio [OR]: 7.62; 95% CI 2.51–27.36; p < 0.001). Implementation of FFLU and NVBP in patients undergoing RARP results in improved long-term continence rates of 91%.