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Background: Adolescent suicide is a public health issue, and school is an ideal setting for prevention activities. LEARN is a peer-led gatekeeper training for high school personnel, parents, and students. The purpose of this study was to evaluate the effectiveness of LEARN as a gatekeeper training. Methods: Paired t tests were used to compare pre- and post-training surveys for 4983 LEARN participants. Results: Participants reported an increased likelihood of engaging in each LEARN step: looking for signs, empathizing and listening, asking about suicide thoughts and plans, reducing danger, and connecting the person with help. Most participants were highly satisfied with the peer trainer's delivery of content. Conclusions: LEARN gatekeeper training was successfully implemented in high schools with students, parents, and school personnel. All groups reported increases in likelihood of approaching and providing support and connections for at-risk individuals and rated the trainer as effective, indicating satisfaction with the peer-led training format.

Abstract Pneumococcal surface protein A (PspA) is an important virulence factor in Streptococcus pneumoniae that binds to lactoferrin and protects the bacterium from the bactericidal action of lactoferricins—cationic peptides released upon lactoferrin proteolysis. The present study investigated if PspA can prevent killing by another cationic peptide, indolicidin. PspA-negative pneumococci were more sensitive to indolicidin-induced killing than bacteria expressing PspA, suggesting that PspA prevents the bactericidal action of indolicidin. Similarly, chemical removal of choline-binding proteins increased sensitivity to indolicidin. The absence of capsule and PspA had an additive effect on pneumococcal killing by the AMP. Furthermore, anti-PspA antibodies enhanced the bactericidal effect of indolicidin on pneumococci, while addition of soluble PspA fragments competitively inhibited indolicidin action. Previous in silico analysis suggests a possible interaction between PspA and indolicidin. Thus, we hypothesize that PspA acts by sequestering indolicidin and preventing it from reaching the bacterial membrane. A specific interaction between PspA and indolicidin was demonstrated by mass spectrometry, confirming that PspA can actively bind to the AMP. These results reinforce the vaccine potential of PspA and suggest a possible mechanism of innate immune evasion employed by pneumococci, which involves binding to cationic peptides and hindering their ability to damage the bacterial membranes.

BackgroundProstate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression-based subtyping model based on prostate-specific biological processes was sought.MethodsUnsupervised machine learning of gene expression profiles from prospectively collected primary prostate tumors (training, n = 32,000; evaluation, n = 68,547) was used to create a prostate subtyping classifier (PSC) based on basal versus luminal cell expression patterns and other gene signatures relevant to PCa biology. Subtype molecular pathways and clinical characteristics were explored in five other clinical cohorts.ResultsClustering derived four subtypes: luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), and basal neuroendocrine (BN). LP and LD tumors both had higher androgen receptor activity. LP tumors also had a higher expression of cell proliferation genes, MYC activity, and characteristics of homologous recombination deficiency. BI tumors possessed significant interferon γactivity and immune infiltration on immunohistochemistry. BN tumors were characterized by lower androgen receptor activity expression, lower immune infiltration, and enrichment with neuroendocrine expression patterns. Patients with LD tumors had less aggressive tumor characteristics and the longest time to metastasis after surgery. Only patients with BI tumors derived benefit from radiotherapy after surgery in terms of time to metastasis (hazard ratio [HR], 0.09; 95% CI, 0.01-0.71; n = 855). In a phase 3 trial that randomized patients with metastatic PCa to androgen deprivation with or without docetaxel (n = 108), only patients with LP tumors derived survival benefit from docetaxel (HR, 0.21; 95% CI, 0.09-0.51).ConclusionsWith the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features.Plain language summaryProstate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments. To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors-the largest data set of its kind. This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management.

BACKGROUND: Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear. METHODS: Data from patients with clear cell renal cell carcinoma (ccRCC) was downloaded from The Cancer Genome Atlas. Clinicopathologic variables were used to calculate SSIGN (stage, size, grade, and necrosis) scores. The 16 gene recurrence score (RS) signature was generated using RNA-seq data. Transcriptomic risk groups were calculated using the original thresholds. SSIGN groups were divided into low, intermediate, and high risk. Disease-free status was the primary endpoint assessed. RESULTS: SSIGN and RS were calculated for 428 patients with non-metastatic ccRCC. SSIGN low-, intermediate-, and high-risk groups demonstrated 2.7%, 15.2%, and 27.5%, 3-year recurrence risk, respectively. On multivariable analysis, the RS was associated with disease-free status (sub-distribution hazard ratio (sHR) 1.43 per 25 RS [95% CI (1.00-1.43)], p = 0.05). By risk groups, RS further risk stratified the SSIGN intermediate-risk group (sHR 2.22 [95% CI 1.10-4.50], p = 0.03). SSIGN intermediate-risk patients with low and high RS had a 3-year recurrence rate of 8.0% and 25.2%, respectively. Within this risk group, the area under the curve (AUC) at 3 years was 0.69 for SSIGN, 0.74 for RS, and 0.78 for their combination. CONCLUSIONS: Transcriptomic recurrence scores improve risk prediction even when controlling for clinicopathologic factors. Utility may be best suited for intermediate-risk patients who have heterogeneous outcomes and further refinement for clinical utility is warranted.

Challenges from infections caused by biofilms and antimicrobial resistance highlight the need for novel antimicrobials that work in conjunction with antibiotics and minimize resistance risk. In this study we investigated the composite effect of HAMLET (human alpha-lactalbumin made lethal to tumor cells), a human milk protein-lipid complex and amoxicillin on microbial ecology using an ex vivo oral biofilm model with pooled saliva samples. HAMLET was chosen due to its multi-targeted antimicrobial mechanism, together with its synergistic effect with antibiotics on single species pathogens, and low risk of resistance development. The combination of HAMLET and low concentrations of amoxicillin significantly reduced biofilm viability, while each of them alone had little or no impact. Using a whole metagenomics approach, we found that the combination promoted a remarkable shift in overall microbial composition compared to the untreated samples. A large proportion of the bacterial species in the combined treatment were Lactobacillus crispatus, a species with probiotic effects, whereas it was only detected in a minor fraction in untreated samples. Although resistome analysis indicated no major shifts in alpha-diversity, the results showed the presence of TEM beta-lactamase genes in low proportions in all treated samples but absence in untreated samples. Our study illustrates HAMLET’s capability to alter the effects of amoxicillin on the oral microbiome and potentially favor the growth of selected probiotic bacteria when in combination. The findings extend previous knowledge on the combined effects of HAMLET and antibiotics against target pathogens to include potential modulatory effects on polymicrobial biofilms of human origin.

VEGF inhibitor drugs are part of standard care in oncology and ophthalmology, but not all patients respond to them. Combinations of drugs are likely to be needed for more effective therapies of angiogenesis-related diseases. In this paper we describe naturally occurring combinations of receptors in endothelial cells that might help to understand how cells communicate and to identify targets for drug combinations. We also develop and share a new software tool called DECNEO to identify them. Single-cell gene expression data are used to identify a set of co-expressed endothelial cell receptors, conserved among species (mice and humans) and enriched, within a network, of connections to up-regulated genes. This set includes several receptors previously shown to play a role in angiogenesis. Multiple statistical tests from large datasets, including an independent validation set, support the reproducibility, evolutionary conservation and role in angiogenesis of these naturally occurring combinations of receptors. We also show tissue-specific combinations and, in the case of choroid endothelial cells, consistency with both well-established and recent experimental findings, presented in a separate paper. The results and methods presented here advance the understanding of signaling to endothelial cells. The methods are generally applicable to the decoding of intercellular combinations of signals.

Many Croatian island municipalities depend on tourism, which provides income by using natural resources; however, traditional tourism is labour intensive and low-skilled which leads to low wages and low possibilities to increase productivity. This paper aims to analyse and discuss other possibilities than traditional tourist industry for the Croatian islands to develop. We will turn towards the concept of digital nomads to discuss if digital nomads can be a solution for the Croatian islands. As a starting point, we use a conceptual model inspired by Harris and Todaro's theoretical outline. We discuss the new possibilities that digitalisation has opened for these islands. The digital economy has made where and when work is performed less important. Thus, the lines between work and non-work are blurred. Tourist industry must look ahead for new forms of mobility and new kinds of work and non-work, which may bring positive exogenous effects to the islands in the form of higher educational level, cultural activities, and purchase power. Our main point is that turning towards attracting digital nomads can, to some extent, be a solution.