Simultaneous inhibition of PI3K and PAK in preclinical models of neurofibromatosis type 2-related schwannomatosis.

Neurofibromatosis Type 2 (NF2)-related schwannomatosis is a genetic disorder that causes development of multiple types of nervous system tumors. The primary and diagnostic tumor type is bilateral vestibular schwannoma. There is no cure or drug therapy for NF2. Recommended treatments include surgical resection and radiation, both of which can leave patients with severe neurological deficits or increase the risk of future malignant tumors. Results of our previous pilot high-throughput drug screen identified phosphoinositide 3-kinase (PI3K) inhibitors as strong candidates based on loss of viability of mouse merlin-deficient Schwann cells (MD-SCs). Here we used novel human schwannoma model cells to conduct combination drug screens. We identified a class I PI3K inhibitor, pictilisib and p21 activated kinase (PAK) inhibitor, PF-3758309 as the top combination due to high synergy in cell viability assays. Both single and combination therapies significantly reduced growth of mouse MD-SCs in an orthotopic allograft mouse model. The inhibitor combination promoted cell cycle arrest and apoptosis in mouse merlin-deficient Schwann (MD-SCs) cells and cell cycle arrest in human MD-SCs. This study identifies the PI3K and PAK pathways as potential targets for combination drug treatment of NF2-related schwannomatosis.

Contact tracing in Austria, Georgia, Kyrgyzstan, Ukraine, and Kosovo† during the COVID-19 pandemic: response review and good practices.

BACKGROUND: During the COVID-19 pandemic, effective contact tracing was recognized as a crucial public health response to mitigate the spread of SARS-CoV-2 and reduce COVID-19-related morbidity and mortality, particularly before widespread vaccination. The World Health Organization (WHO) recommended implementing active surveillance strategies to trace and quarantine contacts of confirmed or suspected COVID-19 cases. METHODS: A detailed review and analysis of the COVID-19 contact tracing responses was conducted in five European countries and territories, between March 2021 and August 2022. The countries and territories were selected to ensure geographical representation across the WHO European Region and applied a mixed-methods approach of in-depth interviews with various stakeholders across different administrative levels to identify good practices in COVID-19 contact tracing. The interviews covered 12 themes, including methods and procedures for COVID-19 contact tracing, information technology, quality assurance and key performance indicators. RESULTS: The findings demonstrate that the policy approach, digitalization capabilities and implementation approach varied in the countries and territories and were dynamic throughout the pandemic. The analysis revealed that some practices were applicable across all countries and territories, while others were context-specific, catering to each country's and territory's unique needs. The study highlighted a need for all countries to institutionalize contact tracing as an essential function of existing health systems, to digitalize contact tracing practices and processes, and to build and retain contact tracing capacities for better pandemic preparedness. CONCLUSION: The lessons related to COVID-19 contact tracing should be utilized to strengthen future outbreak response operations as part of epidemic and pandemic preparedness.

Simultaneous Inhibition of PI3K and PAK in Preclinical Models of Neurofibromatosis Type 2-related Schwannomatosis.

Neurofibromatosis Type 2 (NF2)-related schwannomatosis is a genetic disorder that causes development of multiple types of nervous system tumors. The primary and diagnostic tumor type is bilateral vestibular schwannoma. There is no cure or drug therapy for NF2. Recommended treatments include surgical resection and radiation, both of which can leave patients with severe neurological deficits or increase the risk of future malignant tumors. Results of our previous pilot high-throughput drug screen identified phosphoinositide 3-kinase (PI3K) inhibitors as strong candidates based on loss of viability of mouse merlin-deficient Schwann cells (MD-SCs). Here we used novel human schwannoma model cells to conduct combination drug screens. We identified a class I PI3K inhibitor, pictilisib and p21 activated kinase (PAK) inhibitor, PF-3758309 as the top combination due to high synergy in cell viability assays. Both single and combination therapies significantly reduced growth of mouse MD-SCs in an orthotopic allograft mouse model. The inhibitor combination promoted cell cycle arrest and apoptosis in mouse merlin-deficient Schwann (MD-SCs) cells and cell cycle arrest in human MD-SCs. This study identifies the PI3K and PAK pathways as potential targets for combination drug treatment of NF2-related schwannomatosis.

Bayesian phylogenetic inference of HIV latent lineage ages using serial sequences.

HIV evolves rapidly within individuals, allowing phylogenetic studies to infer histories of viral lineages on short time scales. Latent HIV sequences are an exception to this rapid evolution, as their transcriptional inactivity leads to negligible mutation rates compared with non-latent HIV lineages. This difference in mutation rates generates potential information about the times at which sequences entered the latent reservoir, providing insight into the dynamics of the latent reservoir. A Bayesian phylogenetic method is developed to infer integration times of latent HIV sequences. The method uses informative priors to incorporate biologically sensible bounds on inferences (such as requiring sequences to become latent before being sampled) that many existing methods lack. A new simulation method is also developed, based on widely used epidemiological models of within-host viral dynamics, and applied to evaluate the new method-showing that point estimates and credible intervals are often more accurate than existing methods. Accurate estimates of latent integration dates are crucial in relating integration times to key events during HIV infection, such as treatment initiation. The method is applied to publicly available sequence data from four HIV patients, providing new insights regarding the temporal pattern of latent integration.

Alpha-smooth muscle actin-positive cancer-associated fibroblasts secreting osteopontin promote growth of luminal breast cancer.

BACKGROUND: Cancer-associated fibroblasts (CAFs) have been shown to support tumor development in a variety of cancers. Different markers were applied to classify CAFs in order to elucidate their impact on tumor progression. However, the exact mechanism by which CAFs enhance cancer development and metastasis is yet unknown. METHODS: Alpha-smooth muscle actin (α-SMA) was examined immunohistochemically in intratumoral CAFs of nonmetastatic breast cancers and correlated with clinicopathological data. Four CAF cell lines were isolated from patients with luminal breast cancer (lumBC) and classified according to the presence of α-SMA protein. Conditioned medium (CM) from CAF cultures was used to assess the influence of CAFs on lumBC cell lines: MCF7 and T47D cells using Matrigel 3D culture assay. To identify potential factors accounting for promotion of tumor growth by α-SMAhigh CAFs, nCounter PanCancer Immune Profiling Panel (NanoString) was used. RESULTS: In luminal breast cancer, presence of intratumoral CAFs expressing high level of α-SMA (13% of lumBC group) correlated with poor prognosis (p = 0.019). In in vitro conditions, conditioned medium obtained from primary cultures of α-SMA-positive CAFs isolated from luminal tumors was observed to enhance growth of lumBC cell line colonies in 3D Matrigel, in contrast to CM derived from α-SMA-negative CAFs. Multigene expression analysis indicated that osteopontin (OPN) was overexpressed in α-SMA-positive CAFs in both clinical samples and in vitro models. OPN expression was associated with higher percentage of Ki67-positive cells in clinical material (p = 0.012), while OPN blocking in α-SMA-positive CAF-derived CM attenuated growth of lumBC cell line colonies in 3D Matrigel. CONCLUSIONS: Our findings demonstrate that α-SMA-positive CAFs might enhance tumor growth via secretion of OPN.

ERα36-High Cancer-Associated Fibroblasts as an Unfavorable Factor in Triple-Negative Breast Cancer.

Background: Cancer-associated fibroblasts (CAFs) are the most abundant cell type in the tumor microenvironment (TME). Estrogen receptor alpha 36 (ERα36), the alternatively spliced variant of ERα, is described as an unfavorable factor when expressed in cancer cells. ERα can be expressed also in CAFs; however, the role of ERα36 in CAFs is unknown. Methods: Four CAF cultures were isolated from chemotherapy-naïve BC patients and characterized for ERα36 expression and the NanoString gene expression panel using isolated RNA. Conditioned media from CAF cultures were used to assess the influence of CAFs on triple-negative breast cancer (TNBC) cells using a matrigel 3D culture assay. Results: We found that ERα36high CAFs significantly induced the branching of TNBC cells in vitro (p < 0.001). They also produced a set of pro-tumorigenic cytokines compared to ERα36low CAFs, among which hepatocyte growth factor (HGF) was the main inducer of TNBC cell invasive phenotype in vitro (p < 0.001). Tumor stroma rich in ERα36high CAFs was correlated with high Ki67 expression (p = 0.041) and tumor-associated macrophages markers (CD68 and CD163, p = 0.041 for both). HGF was found to be an unfavorable prognostic factor in TCGA database analysis (p = 0.03 for DFS and p = 0.04 for OS). Conclusions: Breast cancer-associated fibroblasts represent distinct subtypes based on ERα36 expression. We propose that ERα36high CAFs could account for an unfavorable prognosis for TNBC patients.

Patient-reported outcome measures suitable for quality of life/well-being assessment in multisectoral, multinational and multiperson mental health economic evaluations.

QUESTION: The aim was to systematically collate and synthesise existing, publicly available patient-reported outcome measure (PROM) information suitable for quality of life (QOL)/well-being measurement in mental health economic evaluations, with specific focus on their applicability in multisectoral, multinational, multiperson economic evaluations and to develop an electronic PROM compendium with meta-data. STUDY SELECTION AND ANALYSIS: A systematic literature search for non-disease-pecific PROMs and their versions suitable for the measurement of QOL/well-being or recovery was conducted from 2008 to February 2020. Six criteria were applied to judge their suitability in multisectoral, multinational, multiperson economic evaluations: (i) availability of separate adult and child/adolescent versions, (ii) availability of a proxy-completion option, (iii) assessing outcomes beyond health, (iv) availability of translations (≥2 language versions), (v) availability of a preference-based valuation, (vi) availability of value sets in more than one country. FINDINGS: The final ProgrammE in Costing, resource use measurement and outcome valuation for Use in multisectoral National and International health economic evaluAtions (PECUNIA) PROM-MH Compendium includes 204 unique scales, out of which 88 are individual instruments, while the remaining 116 scales belong to 46 PROM families with more than one distinctive version. Out of the total 134 individual PROMs/PROM families, 72% have at least two language versions, 8% measure broader well-being beyond health-related QOL, 11% have preference-based valuation, with multiple country sets available for 60% of these. None of the identified PROMs met all six proposed criteria. CONCLUSIONS: The PECUNIA PROM-MH Compendium provides a unique overview of the relevant PROMs and their linked meta-data, and should be a helpful tool when choosing a suitable instrument for future mental health economic evaluations.

The first 8 weeks of the Austrian SARS-CoV-2 epidemic.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV­2) reached Austria in February 2020. This study aims to describe the first 8 weeks of the Austrian epidemic and reflect on the potential mental health consequences as known at that time. METHODS: Data on Austrian Coronavirus Disease 19 (COVID-19) epidemiological indicators and number of tests were obtained from official registers. Relative risks (RRs) of infection and death from COVID-19 were calculated for sex and age groups (< 65 years and ≥ 65 years). Public health measures introduced to reduce the spread of COVID-19 were identified via online media research. A rapid review of initial evidence on mental health consequences of the pandemic was performed in PubMed and medRxiv. RESULTS: By 21 April 2020 the case count in Austria was 14,810 after a peak of new daily infections mid-March. The RR of death for age ≥ 65 years was 80.07 (95% confidence interval, CI 52.64-121.80; p < 0.0001) compared to those aged < 65 years. In men the RR of death was 1.44 (95% CI 1.20-1.73; p < 0.0001) compared to women. Wide-ranging public health measures included avoidance of case importation, limitation of social contacts, hygiene measures, testing, case tracking, and the call for COVID-19-related research. International rates of psychiatric symptoms during the initial lockdowns exceeded typical levels: anxiety (6%-51%), depression (17%-48%) and posttraumatic stress (5%-54%). CONCLUSION: Data show great vulnerability of older people also in Austria. Severe mental health impacts can be expected with need for proper assessment of the long-term consequences of this pandemic.

Defective apoptosis of U937 cells induced by benzyl isothiocyanate (BITC).

Isothiocyanates precursors (ITCs), including benzyl isothiocyanate (BITC), are considered as cancer chemopreventive agents. ITC derivatives were tested in clinical trials (NCT00005883, NCT01265953, NCT01790204) and preclinical studies aimed to inhibit tumor growth and modulation of their microenvironment. Although efficacy of ITCs was demonstrated with several leukemic cell lines, the final steps of BITC-induced apoptosis were not completely elucidated in the literature. Therefore, we focused on morphological and biochemical events occurring upon treatment of U937 leukemia cells with BITC. Micromolar concentrations of BITC induced cytotoxicity in U937 cells, with major features resembling the hallmarks of apoptosis: phosphatidylserine exposure, low mitochondrial membrane potential, and presence of PARP cleavage by caspases. Disassembly to apoptotic bodies, a final step of classic apoptosis, was not observed. While tracing the signalling pathways, our results showed increased levels of BAG-1 and PUMA proteins, but in contrast to other models of ITCs-induced apoptosis, downregulation of Mcl-1 protein was not noticed. Additionally, BITC-induced dying U937 cells released lower levels of chemoattractants, such as IL-8 and MCP-1, when compared to cells undergoing classical apoptosis. This may disrupt clearance of cell debris by macrophages in vivo (efferocytosis), and in turn affect the inflammatory response. In summary, BITC inhibits tumor growth which makes it a good candidate for supporting cancer treatment. However, atypical apoptosis of leukemic U937 cells induced with BITC may affect the ability of phagocytes to effectively scavenge cellular debris, which poses a question of BITC effectiveness as a chemopreventive agent for leukemias.

Improving Proteome Coverage for Small Sample Amounts: An Advanced Method for Proteomics Approaches with Low Bacterial Cell Numbers.

Proteome analyses are often hampered by the low amount of available starting material like a low bacterial cell number obtained from in vivo settings. Here, the single pot solid-phase enhanced sample preparation (SP3) protocol is adapted and combined with effective cell disruption using detergents for the proteome analysis of bacteria available in limited numbers only. Using this optimized protocol, identification of peptides and proteins for different Gram-positive and Gram-negative species can be dramatically increased and, reliable quantification can also be ensured. This adapted method is compared to already established strain-specific sample processing protocols for Staphylococcus aureus, Streptococcus suis, and Legionella pneumophila. The highest species-specific increase in identifications is observed using the adapted method with L. pneumophila samples by increasing protein and peptide identifications up to 300% and 620%, respectively. This increase is accompanied by an improvement in reproducibility of protein quantification and data completeness between replicates. Thus, this protocol is of interest for performing comprehensive proteomics analyses of low bacterial cell numbers from different settings ranging from infection assays to environmental samples.

Clinical and Biological Significance of ESR1 Gene Alteration and Estrogen Receptors Isoforms Expression in Breast Cancer Patients.

The amplification of estrogen receptor alpha (ERα) encoded by the ESR1 gene has been described as having a prognostic role in breast cancer patients. However, increased dosage of the ESR1 gene (tested by real-time PCR) is also observed in ER-negative breast cancers, which might suggest the expression of alternative isoforms of ERα (other than classical ERα of 66 kDa). In the current work, we have investigated the ESR1 gene dosage in 402 primary breast cancer patients as well as the expression of ERα isoforms-ERα66 and ERα36-on mRNA and protein levels. The obtained results were correlated with clinicopathological data of the patients. Results showed that increased ESR1 gene dosage is not related to ESR1 gene amplification measured by fluorescent in situ hybridization (FISH), but it correlates with the decreased expression of ERα66 isoform (p = 0.01). Interestingly, the short ER isoform ERα36 was expressed in samples with increased ESR1 gene dosage, suggesting that genomic aberration might influence the expression of that particular isoform. Similarly to ESR1 increased gene dosage, high ERα36 expression was linked with the decreased disease-free survival of the patients (p = 0.05), which was independent of the status of the classical ERα66 level in breast tumors.

Spectrum of Epithelial-Mesenchymal Transition Phenotypes in Circulating Tumour Cells from Early Breast Cancer Patients.

Circulating tumour cells (CTCs) can provide valuable prognostic information in a number of epithelial cancers. However, their detection is hampered due to their molecular heterogeneity, which can be induced by the epithelial-mesenchymal transition (EMT) process. Therefore, current knowledge about CTCs from clinical samples is often limited due to an inability to isolate wide spectrum of CTCs phenotypes. In the current work, we aimed at isolation and molecular characterization of CTCs with different EMT status in order to establish their clinical significance in early breast cancer patients. We have obtained CTCs-enriched blood fraction from 83 breast cancer patients in which we have tested the expression of epithelial, mesenchymal and general breast cancer CTCs markers (MGB1/HER2/CK19/CDH1/CDH2/VIM/PLS3), cancer stem cell markers (CD44, NANOG, ALDH1, OCT-4, CD133) and cluster formation gene (plakoglobin). We have shown that in the CTCs-positive patients, epithelial, epithelial-mesenchymal and mesenchymal CTCs markers were detected at a similar rate (in 28%, 24% and 24%, respectively). Mesenchymal CTCs were characterized by the most aggressive phenotype (significantly higher expression of CXCR4, uPAR, CD44, NANOG, p < 0.05 for all), presence of lymph node metastases (p = 0.043), larger tumour size (p = 0.023) and 7.33 higher risk of death in the multivariate analysis (95% CI 1.06⁻50.41, p = 0.04). Epithelial-mesenchymal subtype, believed to correspond to highly plastic and aggressive state, did not show significant impact on survival. Gene expression profile of samples with epithelial-mesenchymal CTCs group resembled pure epithelial or pure mesenchymal phenotypes, possibly underlining degree of EMT activation in particular patient's sample. Molecular profiling of CTCs EMT phenotype provides more detailed and clinically informative results, proving the role of EMT in malignant cancer progression in early breast cancer.

Inhibition of Rho Activity Increases Expression of SaeRS-Dependent Virulence Factor Genes in Staphylococcus aureus, Showing a Link between Transcription Termination, Antibiotic Action, and Virulence.

Staphylococcus aureus causes various diseases ranging from skin and soft tissue infections to life-threatening infections. Adaptation to the different host niches is controlled by a complex network of transcriptional regulators. Global profiling of condition-dependent transcription revealed adaptation of S. aureus HG001 at the levels of transcription initiation and termination. In particular, deletion of the gene encoding the Rho transcription termination factor triggered a remarkable overall increase in antisense transcription and gene expression changes attributable to indirect regulatory effects. The goal of the present study was a detailed comparative analysis of S. aureus HG001 and its isogenic rho deletion mutant. Proteome analysis revealed significant differences in cellular and extracellular protein profiles, most notably increased amounts of the proteins belonging to the SaeR regulon in the Rho-deficient strain. The SaeRS two-component system acts as a major regulator of virulence gene expression in staphylococci. Higher levels of SaeRS-dependent virulence factors such as adhesins, toxins, and immune evasion proteins in the rho mutant resulted in higher virulence in a murine bacteremia model, which was alleviated in a rho complemented strain. Inhibition of Rho activity by bicyclomycin, a specific inhibitor of Rho activity, also induced the expression of SaeRS-dependent genes, at both the mRNA and protein levels, to the same extent as observed in the rho mutant. Taken together, these findings indicate that activation of the Sae system in the absence of Rho is directly linked to Rho's transcription termination activity and establish a new link between antibiotic action and virulence gene expression in S. aureusIMPORTANCE The major human pathogen Staphylococcus aureus is a widespread commensal bacterium but also the most common cause of nosocomial infections. It adapts to the different host niches through a complex gene regulatory network. We show here that the Rho transcription termination factor, which represses pervasive antisense transcription in various bacteria, including S. aureus, plays a role in controlling SaeRS-dependent virulence gene expression. A Rho-deficient strain produces larger amounts of secreted virulence factors in vitro and shows increased virulence in mice. We also show that treatment of S. aureus with the antibiotic bicyclomycin, which inhibits Rho activity and is effective against Gram-negative bacteria, induces the same changes in the proteome as observed in the Rho-deficient strain. Our results reveal for the first time a link between transcription termination and virulence regulation in S. aureus, which implies a novel mechanism by which an antibiotic can modulate the expression of virulence factors.

Aggressive Phenotype of Cells Disseminated via Hematogenous and Lymphatic Route in Breast Cancer Patients.

Intratumoral heterogeneity of breast cancer remains a major challenge in successful treatment. Failure of cancer therapies can also be accredited to inability to systemically eradicate cancer stem cells (CSCs). Recent evidence points to the role of epithelial-mesenchymal transition (EMT) in expanding the pool of tumor cells with CSCs features. Thus, we assessed expression level as well as heterogeneity of CSCs markers in primary tumors (PT), lymph node metastasis (LNM), and circulating tumor cells (CTCs)-enriched blood fractions in order to correlate them with signs of EMT activation as well as clinicopathological data of breast cancer patients. Level of CSCs markers (ALDH1, CD44, CD133, OCT-4, NANOG) and EMT markers was quantified in PT (N=107), LNM (N=56), and CTCs-enriched blood fractions (N=85). Heterogeneity of CSCs markers expression within each PT and LNM was assessed by calculating Gini Index. Percentage of ALDH1-positive cells was elevated in PT in comparison to LNM (P = .005). However, heterogeneity of the four CSCs markers: ALDH1 (P = .019), CD133 (P = .009), OCT-4 (P = .027), and CD44 (P < .001) was decreased in LNM. Samples classified as mesenchymal (post-EMT) showed elevated expression of CSCs markers (OCT-4 and CD44 in PT; OCT-4 in LNM; ALDH1, OCT-4, NANOG, CD44 in CTCs). Patients with mesenchymal-like CTCs had worse prognosis than patients with epithelial-like or no CTCs (P = .0025). CSCs markers are enriched in PT, LNM, and CTCs with mesenchymal features, but their heterogeneity is decreased in metastatic lymph nodes. Mesenchymal CTCs phenotype correlates with poor prognosis of the patients.

Love the one you're with: replicate viral adaptations converge on the same phenotypic change.

Parallelism is important because it reveals how inherently stochastic adaptation is. Even as we come to better understand evolutionary forces, stochasticity limits how well we can predict evolutionary outcomes. Here we sought to quantify parallelism and some of its underlying causes by adapting a bacteriophage (ID11) with nine different first-step mutations, each with eight-fold replication, for 100 passages. This was followed by whole-genome sequencing five isolates from each endpoint. A large amount of variation arose-281 mutational events occurred representing 112 unique mutations. At least 41% of the mutations and 77% of the events were adaptive. Within wells, populations generally experienced complex interference dynamics. The genome locations and counts of mutations were highly uneven: mutations were concentrated in two regulatory elements and three genes and, while 103 of the 112 (92%) of the mutations were observed in ≤4 wells, a few mutations arose many times. 91% of the wells and 81% of the isolates had a mutation in the D-promoter. Parallelism was moderate compared to previous experiments with this system. On average, wells shared 27% of their mutations at the DNA level and 38% when the definition of parallel change is expanded to include the same regulatory feature or residue. About half of the parallelism came from D-promoter mutations. Background had a small but significant effect on parallelism. Similarly, an analyses of epistasis between mutations and their ancestral background was significant, but the result was mostly driven by four individual mutations. A second analysis of epistasis focused on de novo mutations revealed that no isolate ever had more than one D-promoter mutation and that 56 of the 65 isolates lacking a D-promoter mutation had a mutation in genes D and/or E. We assayed time to lysis in four of these mutually exclusive mutations (the two most frequent D-promoter and two in gene D) across four genetic backgrounds. In all cases lysis was delayed. We postulate that because host cells were generally rare (i.e., high multiplicity of infection conditions developed), selection favored phage that delayed lysis to better exploit their current host (i.e., 'love the one you're with'). Thus, the vast majority of wells (at least 64 of 68, or 94%) arrived at the same phenotypic solution, but through a variety of genetic changes. We conclude that answering questions about the range of possible adaptive trajectories, parallelism, and the predictability of evolution requires attention to the many biological levels where the process of adaptation plays out.

Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza.

Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding the spatial and temporal dynamics of outbreaks. Twitter gives researchers and public health officials an opportunity to examine the spread of influenza in real-time and at multiple geographical scales. In this paper, we introduce an improved framework for monitoring influenza outbreaks using the social media platform Twitter. Relying upon techniques from geographic information science (GIS) and data mining, Twitter messages were collected, filtered, and analyzed for the thirty most populated cities in the United States during the 2013-2014 flu season. The results of this procedure are compared with national, regional, and local flu outbreak reports, revealing a statistically significant correlation between the two data sources. The main contribution of this paper is to introduce a comprehensive data mining process that enhances previous attempts to accurately identify tweets related to influenza. Additionally, geographical information systems allow us to target, filter, and normalize Twitter messages.

Risk factors for relapse to problem drinking among current and former US military personnel: a prospective study of the Millennium Cohort.

BACKGROUND: Military service members may be prone to relapse to problem drinking after remission, given a culture of alcohol use as a coping mechanism for stressful or traumatic events associated with military duties or exposures. However, the prevalence and correlates of relapse are unknown. We sought to identify socio-demographic, military, behavioral, and health characteristics associated with relapse among current and former military members with remittent problem drinking. METHODS: Participants in the longitudinal Millennium Cohort Study who reported problem drinking at baseline (2001-2003) and were remittent at first follow-up (2004-2006) were included (n=6909). Logistic regression models identified demographic, military service, behavioral, and health characteristics that predicted relapse (report of ≥1 past-year alcohol-related problem on the validated Patient Health Questionnaire) at the second follow-up (2007-2008). RESULTS: Sixteen percent of those with remittent problem drinking relapsed. Reserve/National Guard members compared with active-duty members (odds ratio [OR]=1.71, 95% confidence interval [CI]: 1.45-2.01), members separated from the military during follow-up (OR=1.46, 95% CI: 1.16-1.83), and deployers who reported combat exposure (OR=1.32, 95% CI: 1.07-1.62, relative to non-deployers) were significantly more likely to relapse. Those with multiple deployments were significantly less likely to relapse (OR=0.73, 95% CI: 0.58-0.92). Behavioral factors and mental health conditions also predicted relapse. CONCLUSION: Relapse was common and associated with military and non-military factors. Targeted intervention to prevent relapse may be indicated for military personnel in particular subgroups, such as Reservists, veterans, and those who deploy with combat exposure.

The reliability of tweets as a supplementary method of seasonal influenza surveillance.

BACKGROUND: Existing influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza. OBJECTIVE: There were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego. METHODS: Tweets containing the keyword "flu" were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was "valid", or from a user who was likely ill with the flu. RESULTS: Correlations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier. CONCLUSIONS: Compared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data.

The complex relationship of realspace events and messages in cyberspace: case study of influenza and pertussis using tweets.

BACKGROUND: Surveillance plays a vital role in disease detection, but traditional methods of collecting patient data, reporting to health officials, and compiling reports are costly and time consuming. In recent years, syndromic surveillance tools have expanded and researchers are able to exploit the vast amount of data available in real time on the Internet at minimal cost. Many data sources for infoveillance exist, but this study focuses on status updates (tweets) from the Twitter microblogging website. OBJECTIVE: The aim of this study was to explore the interaction between cyberspace message activity, measured by keyword-specific tweets, and real world occurrences of influenza and pertussis. Tweets were aggregated by week and compared to weekly influenza-like illness (ILI) and weekly pertussis incidence. The potential effect of tweet type was analyzed by categorizing tweets into 4 categories: nonretweets, retweets, tweets with a URL Web address, and tweets without a URL Web address. METHODS: Tweets were collected within a 17-mile radius of 11 US cities chosen on the basis of population size and the availability of disease data. Influenza analysis involved all 11 cities. Pertussis analysis was based on the 2 cities nearest to the Washington State pertussis outbreak (Seattle, WA and Portland, OR). Tweet collection resulted in 161,821 flu, 6174 influenza, 160 pertussis, and 1167 whooping cough tweets. The correlation coefficients between tweets or subgroups of tweets and disease occurrence were calculated and trends were presented graphically. RESULTS: Correlations between weekly aggregated tweets and disease occurrence varied greatly, but were relatively strong in some areas. In general, correlation coefficients were stronger in the flu analysis compared to the pertussis analysis. Within each analysis, flu tweets were more strongly correlated with ILI rates than influenza tweets, and whooping cough tweets correlated more strongly with pertussis incidence than pertussis tweets. Nonretweets correlated more with disease occurrence than retweets, and tweets without a URL Web address correlated better with actual incidence than those with a URL Web address primarily for the flu tweets. CONCLUSIONS: This study demonstrates that not only does keyword choice play an important role in how well tweets correlate with disease occurrence, but that the subgroup of tweets used for analysis is also important. This exploratory work shows potential in the use of tweets for infoveillance, but continued efforts are needed to further refine research methods in this field.

Stickbreaking: a novel fitness landscape model that harbors epistasis and is consistent with commonly observed patterns of adaptive evolution.

In relating genotypes to fitness, models of adaptation need to both be computationally tractable and qualitatively match observed data. One reason that tractability is not a trivial problem comes from a combinatoric problem whereby no matter in what order a set of mutations occurs, it must yield the same fitness. We refer to this as the bookkeeping problem. Because of their commutative property, the simple additive and multiplicative models naturally solve the bookkeeping problem. However, the fitness trajectories and epistatic patterns they predict are inconsistent with the patterns commonly observed in experimental evolution. This motivates us to propose a new and equally simple model that we call stickbreaking. Under the stickbreaking model, the intrinsic fitness effects of mutations scale by the distance of the current background to a hypothesized boundary. We use simulations and theoretical analyses to explore the basic properties of the stickbreaking model such as fitness trajectories, the distribution of fitness achieved, and epistasis. Stickbreaking is compared to the additive and multiplicative models. We conclude that the stickbreaking model is qualitatively consistent with several commonly observed patterns of adaptive evolution.