Can you have multiple attentional templates? Large-scale replications of Van Moorselaar, Theeuwes, and Olivers (2014) and Hollingworth and Beck (2016) (vol 81, pg 2700, 2019)

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What to expect where and when: how statistical learning drives visual selection

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Prospectively reinstated memory drives conscious access of matching visual input

Item does not contain fulltextMaintaining information in visual working memory (VWM) biases attentional selection of concurrent visual input, by favoring VWM-matching over VWM-mismatching visual input. Recently, it was shown that this bias disappears when the same item is memorized on consecutive occasions (as memoranda presumably transit from VWM to long-term memory), but reemerges when observers anticipate to memorize a novel item on a subsequent trial. Here, we aimed to conceptually replicate and extend this intriguing finding, by investigating whether prospectively reinstated memory drives conscious access of memory-matching visual input. We measured the time it took for participants to detect interocularly suppressed target stimuli, which were either from the same color category as a concurrently memorized color or not. Our results showed that the advantage of memory-matching targets in overcoming suppression progresses non-monotonically across consecutive memorizations of the same color ('repetitions'): the advantage for memory-matching visual input initially declined to asymptote, before being fully revived on the last repetition. This revival was not observed in a control experiment in which targets were not interocularly suppressed. The results suggest that, as observers anticipate to memorize a novel item imminently, VWM usage is prospectively reinstated, causing memory-matching visual input to gain accelerated access to consciousness again.12 p

The Effects of Nutrient Enrichment and Herbivore Abundance on the Ability of Turf Algae to Overgrow Coral in the Caribbean

Turf algae are multispecies communities of small marine macrophytes that are becoming a dominant component of coral reef communities around the world. To assess the impact of turf algae on corals, we investigated the effects of increased nutrients (eutrophication) on the interaction between the Caribbean coral Montastraea annularis and turf algae at their growth boundary. We also assessed whether herbivores are capable of reducing the abundance of turf algae at coral-algae boundaries. We found that turf algae cause visible (overgrowth) and invisible negative effects (reduced fitness) on neighbouring corals. Corals can overgrow neighbouring turf algae very slowly (at a rate of 0.12 mm 3 wk−1) at ambient nutrient concentrations, but turf algae overgrew corals (at a rate of 0.34 mm 3 wk−1) when nutrients were experimentally increased. Exclusion of herbivores had no measurable effect on the rate turf algae overgrew corals. We also used PAM fluorometry (a common approach for measuring of a colony's “fitness”) to detect the effects of turf algae on the photophysiology of neighboring corals. Turf algae always reduced the effective photochemical efficiency of neighbouring corals, regardless of nutrient and/or herbivore conditions. The findings that herbivores are not capable of controlling the abundance of turf algae and that nutrient enrichment gives turf algae an overall competitive advantage over corals together have serious implications for the health of Caribbean coral reef systems. At ambient nutrient levels, traditional conservation measures aimed at reversing coral-to-algae phase shifts by reducing algal abundance (i.e., increasing herbivore populations by establishing Marine Protected Areas or tightening fishing regulations) will not necessarily reduce the negative impact of turf algae on local coral communities. Because turf algae have become the most abundant benthic group on Curaçao (and likely elsewhere in the Caribbean), new conservation strategies are required to mitigate their negative impact on coral communities

Protein Complexes in Urine Interfere with Extracellular Vesicle Biomarker Studies

Urine exosomes (extracellular vesicles; EVs) contain (micro)RNA (miRNA) and protein biomarkers that are useful for the non-invasive diagnosis of various urological diseases. However, the urinary Tamm-Horsfall protein (THP) complex, which forms at reduced temperatures, may affect EV isolation and may also lead to contamination by other molecules including microRNAs (miRNAs). Therefore, we compared the levels of three miRNAs within the purified EV fraction and THP- protein-network. Urine was collected from healthy donors and EVs were isolated by ultracentrifugation (UC), two commercial kits or sepharose size-exclusion chromatography (SEC). SEC enables the separation of EVs from protein-complexes in urine. After UC, the isolation of EV-miRNA was compared with two commercial kits. The EV isolation efficiency was evaluated by measuring the EV protein markers, Alix and TSG101, CD63 by Western blotting, or miR-375, miR-204 and miR-21 by RT-qPCR. By using commercial kits, EV isolation resulted in either low yields or dissimilar miRNA levels. Via SEC, the EVs were separated from the protein-complex fraction. Importantly, a different ratio was observed between the three miRNAs in the protein fraction compared to the EV fraction. Thus, protein-complexes within urine may influence EV-biomarker studies. Therefore, the characterization of the isolated EV fraction is important to obtain reproducible results

Role of Local and/or Metastasis-directed Therapy in Patients with Hormone-sensitive M1a Prostate Cancer:A Systematic Review

CONTEXT: It remains unclear whether men with hormone-sensitive prostate cancer (PCa) metastasized to nonregional lymph nodes (M1a) benefit from prostate-directed therapy (PDT) and/or metastasis-directed therapy (MDT). OBJECTIVE: To systematically summarize the literature regarding oncological outcomes of de novo and recurrent M1a PCa patients treated with PDT and/or MDT. EVIDENCE ACQUISITION: We searched Medline (Ovid), Embase, and Scopus according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines for reports on oncological outcomes of de novo or recurrent hormone-sensitive M1a PCa patients treated with PDT (radical prostatectomy or radiotherapy) and/or MDT (nodal radiotherapy or salvage lymph node dissection) with or without androgen deprivation therapy. A descriptive data synthesis and a methodological quality assessment were performed to evaluate the impact of PDT and/or MDT on survival in M1a PCa patients. EVIDENCE SYNTHESIS: A total of 6136 articles were screened and 24 studies were included in this systematic review. In de novo M1a PCa patients, PDT was associated with improved oncological outcomes compared with no PDT. In recurrent M1a PCa, MDT could delay the need for systemic treatment in a selection of patients, but high-level evidence from prospective phase III randomized controlled trials is still awaited. CONCLUSIONS: This systematic review summarized the limited literature data on the management of M1a PCa. Subgroup analyses suggest a role for PDT plus systemic therapy in de novo M1a PCa. MDT to distant nodal metastases delayed the need for systemic therapy in recurrent disease, but robust data are lacking. The predominantly retrospective nature of the included studies and significant heterogeneity in study designs limit the strength of evidence. PATIENT SUMMARY: We reviewed the treatment of patients with prostate cancer that has spread to lymph nodes outside the pelvis without metastases in other organ systems. There is evidence that treatment of the primary prostate tumor improves outcomes in well-selected patients and that treatment targeting distant lymph node metastases can delay the start of systemic treatment.</p

Machine learning-based analysis of [¹⁸F]DCFPyL PET radiomics for risk stratification in primary prostate cancer

PURPOSE: Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [18F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features. METHODS: In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [18F]DCFPyL PET-CT. Primary tumors were delineated using 50-70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic features were extracted per tumor. Random forest models were trained to predict lymph node involvement (LNI), presence of any metastasis, Gleason score ≥ 8, and presence of extracapsular extension (ECE). For comparison, models were also trained using standard PET features (SUVs, volume, total PSMA uptake). Model performance was validated using 50 times repeated 5-fold cross-validation yielding the mean receiver-operator characteristic curve AUC. RESULTS: The radiomics-based machine learning models predicted LNI (AUC 0.86 ± 0.15, p < 0.01), nodal or distant metastasis (AUC 0.86 ± 0.14, p < 0.01), Gleason score (0.81 ± 0.16, p < 0.01), and ECE (0.76 ± 0.12, p < 0.01). The highest AUCs reached using standard PET metrics were lower than those of radiomics-based models. For LNI and metastasis prediction, PVC and a higher delineation threshold improved model stability. Machine learning pre-processing methods had a minor impact on model performance. CONCLUSION: Machine learning-based analysis of quantitative [18F]DCFPyL PET metrics can predict LNI and high-risk pathological tumor features in primary PCa patients. These findings indicate that PSMA expression detected on PET is related to both primary tumor histopathology and metastatic tendency. Multicenter external validation is needed to determine the benefits of using radiomics versus standard PET metrics in clinical practice