Integration of an online application to optimise multi-disciplinary meetings: a retrospective analysis.

BACKGROUND: Multi-disciplinary Meetings (MDM) play a crucial role in complex patient care, involving input from various specialties to formulate evidence-based management plans. However, traditional unidirectional approaches and reliance on manual processes have led to inefficiencies in the MDM pathway. AIMS: This study identified and aimed to improve four critical moments where Information Communication Technologies (ICTs) could enhance the MDM process. Initial referral, information synthesis, meeting presentation and the creation of actionable/auditable items. METHODS: Microsoft Office Forms, a customisable survey platform, was implemented to streamline MDM processes. Forms were created to gather patient information, develop agendas, and track outcomes. Automation through Excel scripting further optimised data organisation and agenda creation. RESULTS: Referrals using Forms takes an average of 7 min and 21 s. Over 15 months the submission time has reduced and is trending towards under 5 min for each referral. The system's scalability has allowed 1744 cases to be discussed over a 15-month period. Active departments using Forms is expanding to seven from two prior to the pilot. CONCLUSION(S): Microsoft Office Forms proved to be a valuable and adaptable tool for MDMs, offering benefits such as streamlined information gathering, real-time collaboration, and scalability. The study highlights the potential of existing tools within Microsoft licenses for healthcare process optimisation, providing a cost-effective and customisable solution for MDM agendas. While recognising some limitations, the study concludes that leveraging Microsoft Office Forms can significantly improve system efficiency in a multi-disciplinary setting.

Radiological Density, Atomic Numbers, and Stone Fragmentation of Bego Stones Used for Research in Endourology: Comparison to Real Urinary Stones.

Objective: The aim of the study was to characterize artificial stones used for research in endourology in terms of radiological properties and hardness, based on stone fragmentation, and to compare them with real stones. Materials and Methods: We built artificial stones using BegoStone Plus™ powder (BEGO, Lincoln, RI), with powder (g)-water (mL) ratios ranging from 15:03 to 15:12. The CT Gemstone Spectral Imaging Software® (GE Medical Systems, LLC, Waukesha, WI) was used to evaluate the radiological density in HU and spectral properties. Stone fragmentation was assessed in an in vitro experimental setting. These properties of artificial stones were compared with real urinary calculi. Results: Regarding radiological density in terms of HUs, 15:03 artificial calculi showed similar results when compared with real stones comprising calcium oxalate and calcium phosphate. The 15:03 and 15:04 artificial stones showed similar spectral property results to calcium pyrophosphate stones. The 15:11 artificial stones showed similar stone fragmentation results to real stones comprising uric acid, and 15:03 artificial calculi showed similar results to apatite and cystine stones. Conclusions: Artificial stones are useful for research in endourology. Stones with a powder (g)-water (mL) ratio of 15:03 proved to mimic real hard stones in terms of HUs, atomic number, and stone fragmentation in our study and could be used as artificial hard stones, and 15:11 stones showed similar stone fragmentation to uric acid stones. Our study might suggest that standard Bego stones are useful to investigate different areas in endourology, but not radiological properties because radiological homogeneity is not ensured unless more sophisticated mixing methods are used.

Comprehensive genomic profiling of penile squamous cell carcinoma and the impact of human papillomavirus status on immune-checkpoint inhibitor-related biomarkers.

BACKGROUND: Advanced penile squamous cell carcinoma (pSCC) is a rare and aggressive malignancy with limited success of immune-checkpoint inhibitors (ICIs). Approximately half of pSCC cases are associated with human papillomavirus (HPV) infection. METHODS: Evaluation was done retrospectively of the landscape of somatic alterations and ICI-related biomarkers in pSCC by using the Caris Life Sciences data set with the aim to establish signatures for HPV-dependent oncogenesis. The pSCC tumors were analyzed by using next-generation sequencing (NGS) of DNA and RNA. Programmed death ligand 1 (PD-L1) expression was evaluated by immunohistochemistry (IHC). Microsatellite instability (MSI) was tested by fragment analysis, IHC (SP142; ≥1%), and NGS. Tumor mutational burden (TMB)-high was defined as ≥10 mutations/Mb. HPV16/18 status was determined by using whole-exome sequencing (WES) when available. Significance was adjusted for multiple comparisons (q value < .05). RESULTS: NGS of the overall cohort (N = 108) revealed TP53 (46%), CDKN2A (26%), and PIK3CA (25%) to be the most common mutations. Overall, 51% of tumors were PD-L1+, 10.7% had high TMB, and 1.1% had mismatch repair-deficient (dMMR)/MSI-high status. Twenty-nine patients had their HPV status made available by WES (HPV16/18+, n = 13; HPV16/18-, n = 16). KMT2C mutations (33% vs. 0%) and FGF3 amplifications (30.8% vs. 0%) were specific to HPV16/18+ tumors, whereas CDKN2A mutations (0% vs. 37.5%) were exclusive to HPV16/18- tumors. TMB-high was exclusively found in the HPV16/18+ group (30.8%). The two groups had comparable PD-L1 and dMMR/MSI-H status. CONCLUSIONS: In a large and comprehensive NGS-based evaluation of somatic alterations in pSCC, HPV16/18+ versus HPV16/18- pSCCs were molecularly distinct tumors. Our finding that TMB-high is exclusive to HPV16/18+ tumors requires confirmation in larger data sets. PLAIN LANGUAGE SUMMARY: Penile squamous cell carcinoma (pSCC) is a rare and aggressive malignancy in the advanced setting, with poor prognosis and little success with immune-checkpoint inhibitors (ICIs) in an unselected patient approach. Human papillomavirus (HPV) infection is a known risk factor for pSCC; its impact on genomic tumor profiling is less defined. Using next-generation sequencing, we explored the genetic landscape and ICI-related biomarkers of pSCC and HPV-driven oncogenic molecular signatures. Our results indicate that HPV-positive and HPV-negative pSCCs are molecularly distinct tumors. Increased tumor mutational burden is associated with HPV-positive tumors, and could serve as a biomarker for predicting therapeutic response to ICI-based therapies. Our results support the growing literature indicating that HPV status in pSCC can be used to guide patient stratification in ICI-based clinical trials.

Somatic 9p24.1 alterations in HPV- head and neck squamous cancer dictate immune microenvironment and anti-PD-1 checkpoint inhibitor activity.

Somatic copy number alterations (SCNAs), generally (1) losses containing interferons and interferon-pathway genes, many on chromosome 9p, predict immune-cold, immune checkpoint therapy (ICT)-resistant tumors (2); however, genomic regions mediating these effects are unclear and probably tissue specific. Previously, 9p21.3 loss was found to be an early genetic driver of human papillomavirus-negative (HPV-) head and neck squamous cancer (HNSC), associated with an immune-cold tumor microenvironment (TME) signal, and recent evidence suggested that this TME-cold phenotype was greatly enhanced with 9p21 deletion size, notably encompassing band 9p24.1 (3). Here, we report multi-omic, -threshold and continuous-variable dissection of 9p21 and 9p24 loci (including depth and degree of somatic alteration of each band at each locus, and each gene at each band) and TME of four HPV- HNSC cohorts. Preferential 9p24 deletion, CD8 T-cell immune-cold associations were observed, driven by 9p24.1 loss, and in turn by an essential telomeric regulatory gene element, JAK2-CD274. Surprisingly, same genetic region gains were immune hot. Related 9p21-TME analyses were less evident. Inherent 9p-band-level influences on anti-PD1 ICT survival rates, coincident with TME patterns, were also observed. At a 9p24.1 whole-transcriptome expression threshold of 60th percentile, ICT survival rate exceeded that of lower expression percentiles and of chemotherapy; below this transcript threshold, ICT survival was inferior to chemotherapy, the latter unaffected by 9p24.1 expression level (P-values < 0.01, including in a PD-L1 immunohistochemistry-positive patient subgroup). Whole-exome analyses of 10 solid-tumor types suggest that these 9p-related ICT findings could be relevant to squamous cancers, in which 9p24.1 gain/immune-hot associations exist.

Molecular characterization of ESR1 variants in breast cancer.

PURPOSE: Estrogen receptor 1 (ESR1) mutations and fusions typically arise in patients with hormone receptor-positive breast cancer after aromatase inhibitor therapy, whereby ESR1 is constitutively activated in a ligand-independent manner. These variants can impact treatment response. Herein, we characterize ESR1 variants among molecularly profiled advanced breast cancers. METHODS: DNA next-generation sequencing (592-gene panel) data from 9860 breast cancer samples were retrospectively reviewed. Gene fusions were detected using the ArcherDx fusion assay or whole transcriptome sequencing (n = 344 and n = 4305, respectively). Statistical analyses included Chi-square and Fisher's exact tests. RESULTS: An ESR1 ligand-binding domain (LBD) mutation was detected in 8.6% of tumors evaluated and a pathogenic ESR1 fusion was detected in 1.6%. Most ESR1 LBD mutations/fusions were from estrogen receptor (ER)-positive samples (20.1% and 4.9%, respectively). The most common ESR1 LBD mutations included D538G (3.3%), Y537S (2.3%), and E380Q (1.1%) mutations. Among biopsy sites, ESR1 LBD mutations were most observed in liver metastases. Pathogenic ESR1 fusions were identified in 76 samples (1.6%) with 40 unique fusion partners. Evaluating co-alterations, ESR1 variant (mutation/fusion) samples more frequently expressed androgen receptor (78.0% vs 58.6, P < 0.0001) and less frequently immune checkpoint proteins than ESR1 wild-type (PD-1 20.0% vs 53.4, P < 0.05; immune cell PD-L1 10.0% vs 30.2, P < 0.0001). CONCLUSION: We have described one of the largest series of ESR1 fusions reported. ESR1 LBD mutations were commonly identified in ER-positive disease. Limited data exists regarding the clinical impact of ESR1 fusions, which could be an area for future therapeutic exploration.

Molecular characteristics and clinical outcomes of patients with Neurofibromin 1-altered metastatic colorectal cancer.

Loss-of-function alterations of Neurofibromin 1 (NF1) activate RAS, a driver of colorectal cancer. However, the clinical implications of NF1 alterations are largely unknown. We performed a comprehensive molecular profiling of NF1-mutant colorectal cancer using data from 8150 patients included in a dataset of commercial CLIA-certified laboratory (Caris Life Sciences). In addition, NF1 expression levels were tested for associations with clinical outcomes using data from 431 patients in the CALGB/SWOG 80405 trial. In the Caris dataset, 2.2% of patients had pathogenic or presumed pathogenic NF1 mutations. NF1-mutant tumors more frequently harbored PIK3CA (25.0% vs. 16.7%) and PTEN mutations (24.0% vs. 4.2%) than wild type tumors. Gene set enrichment analysis revealed that MAPK and PI3K pathway signatures were enriched in NF1-mutant tumors. In the CALGB/SWOG 80405 cohort, low NF1 expression was associated with poor prognosis, and high NF1 expression was associated with better efficacy of cetuximab than bevacizumab. Together, we revealed concurrent genetic alterations in the PI3K pathways in NF1-mutant tumors, suggesting the need to simultaneously block MAPK and PI3K pathways in treatment. The potential of NF1 alteration as a novel biomarker for targeted therapy was highlighted, warranting further investigations in clinical settings.

Genomic Landscape of Angiosarcoma: A Targeted and Immunotherapy Biomarker Analysis.

We performed a retrospective analysis of angiosarcoma (AS) genomic biomarkers and their associations with the site of origin in a cohort of 143 cases. Primary sites were head and neck (31%), breast (22%), extremity (11%), viscera (20%), skin at other locations (8%), and unknown (9%). All cases had Next Generation Sequencing (NGS) data with a 592 gene panel, and 53 cases had Whole Exome Sequencing (WES) data, which we used to study the microenvironment phenotype. The immunotherapy (IO) response biomarkers Tumor Mutation Burden (TMB), Microsatellite Instability (MSI), and PD-L1 status were the most frequently encountered alteration, present in 36.4% of the cohort and 65% of head and neck AS (H/N-AS) (p < 0.0001). In H/N-AS, TMB-High was seen in 63.4% of cases (p < 0.0001) and PDL-1 positivity in 33% of cases. The most common genetic alterations were TP53 (29%), MYC amplification (23%), ARID1A (17%), POT1 (16%), and ATRX (13%). H/N-AS cases had predominantly mutations in TP53 (50.0%, p = 0.0004), POT1 (40.5%, p < 0.0001), and ARID1A (33.3%, p = 0.5875). In breast AS, leading alterations were MYC amplification (63.3%, p < 0.0001), HRAS (16.1%, p = 0.0377), and PIK3CA (16.1%, p = 0.2352). At other sites, conclusions are difficult to generate due to the small number of cases. A microenvironment with a high immune signature, previously associated with IO response, was evenly distributed in 13% of the cases at different primary sites. Our findings can facilitate the design and optimization of therapeutic strategies for AS.

Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type.

Cancer of Unknown Primary (CUP) occurs in 3-5% of patients when standard histological diagnostic tests are unable to determine the origin of metastatic cancer. Typically, a CUP diagnosis is treated empirically and has very poor outcomes, with median overall survival less than one year. Gene expression profiling alone has been used to identify the tissue of origin but struggles with low neoplastic percentage in metastatic sites which is where identification is often most needed. MI GPSai, a Genomic Prevalence Score, uses DNA sequencing and whole transcriptome data coupled with machine learning to aid in the diagnosis of cancer. The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai predicted the tumor type in the labeled data set with an accuracy of over 94% on 93% of cases while deliberating amongst 21 possible categories of cancer. When also considering the second highest prediction, the accuracy increases to 97%. Additionally, MI GPSai rendered a prediction for 71.7% of CUP cases. Pathologist evaluation of discrepancies between submitted diagnosis and MI GPSai predictions resulted in change of diagnosis in 41.3% of the time. MI GPSai provides clinically meaningful information in a large proportion of CUP cases and inclusion of MI GPSai in clinical routine could improve diagnostic fidelity. Moreover, all genomic markers essential for therapy selection are assessed in this assay, maximizing the clinical utility for patients within a single test.

Clinical Validation of a Machine-learning-derived Signature Predictive of Outcomes from First-line Oxaliplatin-based Chemotherapy in Advanced Colorectal Cancer.

PURPOSE: FOLFOX, FOLFIRI, or FOLFOXIRI chemotherapy with bevacizumab is considered standard first-line treatment option for patients with metastatic colorectal cancer (mCRC). We developed and validated a molecular signature predictive of efficacy of oxaliplatin-based chemotherapy combined with bevacizumab in patients with mCRC. EXPERIMENTAL DESIGN: A machine-learning approach was applied and tested on clinical and next-generation sequencing data from a real-world evidence (RWE) dataset and samples from the prospective TRIBE2 study resulting in identification of a molecular signature, FOLFOXai. Algorithm training considered time-to-next treatment (TTNT). Validation studies used TTNT, progression-free survival, and overall survival (OS) as the primary endpoints. RESULTS: A 67-gene signature was cross-validated in a training cohort (N = 105) which demonstrated the ability of FOLFOXai to distinguish FOLFOX-treated patients with mCRC with increased benefit from those with decreased benefit. The signature was predictive of TTNT and OS in an independent RWE dataset of 412 patients who had received FOLFOX/bevacizumab in first line and inversely predictive of survival in RWE data from 55 patients who had received first-line FOLFIRI. Blinded analysis of TRIBE2 samples confirmed that FOLFOXai was predictive of OS in both oxaliplatin-containing arms (FOLFOX HR, 0.629; P = 0.04 and FOLFOXIRI HR, 0.483; P = 0.02). FOLFOXai was also predictive of treatment benefit from oxaliplatin-containing regimens in advanced esophageal/gastro-esophageal junction cancers, as well as pancreatic ductal adenocarcinoma. CONCLUSIONS: Application of FOLFOXai could lead to improvements of treatment outcomes for patients with mCRC and other cancers because patients predicted to have less benefit from oxaliplatin-containing regimens might benefit from alternative regimens.

Translocation of a Cell Surface Spliceosomal Complex Induces Alternative Splicing Events and Lymphoma Cell Necrosis.

Spliceosomal dysregulation dramatically affects many cellular processes, notably signal transduction, metabolism, and proliferation, and has led to the concept of targeting intracellular spliceosomal proteins to combat cancer. Here we show that a subset of lymphoma cells displays a spliceosomal complex on their surface, which we term surface spliceosomal complex (SSC). The SSC consists of at least 13 core components and was discovered as the binding target of the non-Hodgkin's lymphoma-specific aptamer C10.36. The aptamer triggers SSC internalization, causing global changes in alternative splicing patterns that eventually lead to necrotic cell death. Our study reveals an exceptional spatial arrangement of a spliceosomal complex and defines it not only as a potential target of anti-cancer drugs, but also suggests that its localization plays a fundamental role in cell survival.

Laboratory and Field Assessments of Erythritol Derivatives on the Survival, Reproductive Rate, and Control of Drosophila suzukii (Diptera: Drosophilidae).

Spotted-wing Drosophila, Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) is a vinegar fly introduced unintentionally into the United States. Since 2008, D. suzukii has reduced annual berry yields from 6 to 100%. Effective control of D. suzukii during harvest requires weekly applications of low-residual, broad-spectrum insecticides that are unavailable for organic farming. A novel ingestible insecticide, a 4-carbon polyol, mesoerythritol (erythritol), was found to kill 75 to 100% of larval and adult D. suzukii. However, mesoerythritol, at effective concentrations (0.5-1.0M), may be cost-prohibitive. Therefore, we conducted laboratory tests to assess the effects of lower cost derivatives of erythritol, namely the pentaerythritol series of 1,3-diols on D. suzukii pupal production, adult production, adult mortality, brood output, and reproductive increase. We then selected the two most promising compounds for a field test on fruiting rabbiteye blueberry. From 90 to 100% of adults died when fed food moistened with 1M solutions of mesoerythritol and pentaerythritol. Mesoerythritol and dipentaerythritol at a concentration of 1M were ovicidal/larvicidal, killing ≥85% of immatures. Overall, 1M mesoerythritol killed 80% or more larvae and adults, thus bringing populations to near zero. The heaviest compound of this series, tripentaerythritol, at all concentrations, was largely benign to both adults and immatures. Thus, we cannot recommend tripentaerythritol for D. suzukii control. In a blueberry field, 0.5M mesoerythritol and 0.5M pentaerythritol, each by themselves, reduced egg infestation by 64% and larval infestation by 93%; their combination (0.25M mesoerythritol and 0.25M pentaerythritol) achieved even greater egg control with 82% fewer eggs infesting blueberry fruits.

The effects of random taxa sampling schemes in Bayesian virus phylogeography.

Public health researchers are often tasked with accurately and quickly identifying the location and time when an epidemic originated from a representative sample of nucleotide sequences. In this paper, we investigate multiple approaches to subsampling the sequence set when employing a Bayesian phylogeographic generalized linear model. Our results indicate that near-categorical posterior MCC estimates on the root can be obtained with replicate runs using 25-50% of the sequence data, and that including 90% of sequences does not necessarily entail more accurate inferences. We present the first analysis of predictor signal suppression and show how the ability to detect the influence of predictor variables is limited when sample size predictors are included in the models.

U.S. nationwide reconnaissance of ten infrequently monitored antibiotics in municipal biosolids.

Ten infrequently monitored antibiotics in biosolids were examined in archived American sewage sludges (n = 79) collected as part of the 2006/2007 U.S. Environmental Protection Agency (EPA) Targeted National Sewage Sludge Survey. This study inspected the occurrence of amoxicillin, ampicillin, erythromycin, furazolidone [proxy metabolite: 3-(2-nitrobenzylidenamino)-2-oxazolidinone (NP-AOZ)], nalidixic acid, oxolinic acid, oxytetracycline, spiramycin, sulfadimidine, and sulfadimethoxine in sewage sludges after nearly a decade in frozen storage. Six antibiotics were detected at the following average concentrations (ng/g dry weight): amoxicillin (1.0), nalidixic acid (19.1), oxolinic acid (2.7), erythromycin (0.6), oxytetracycline (4.5), and ampicillin (14.8). The remaining four were not detected in any samples (

The Effects of Sampling Location and Predictor Point Estimate Certainty on Posterior Support in Bayesian Phylogeographic Generalized Linear Models.

The use of generalized linear models in Bayesian phylogeography has enabled researchers to simultaneously reconstruct the spatiotemporal history of a virus and quantify the contribution of predictor variables to that process. However, little is known about the sensitivity of this method to the choice of the discrete state partition. Here we investigate this question by analyzing a data set containing 299 sequences of the West Nile virus envelope gene sampled in the United States and fifteen predictors aggregated at four spatial levels. We demonstrate that although the topology of the viral phylogenies was consistent across analyses, support for the predictors depended on the level of aggregation. In particular, we found that the variance of the predictor support metrics was minimized at the most precise level for several predictors and maximized at more sparse levels of aggregation. These results suggest that caution should be taken when partitioning a region into discrete locations to ensure that interpretable, reproducible posterior estimates are obtained. These results also demonstrate why researchers should use the most precise discrete states possible to minimize the posterior variance in such estimates and reveal what truly drives the diffusion of viruses.

Poly-ligand profiling differentiates trastuzumab-treated breast cancer patients according to their outcomes.

Assessing the phenotypic diversity underlying tumour progression requires the identification of variations in the respective molecular interaction networks. Here we report proof-of-concept for a platform called poly-ligand profiling (PLP) that surveys these system states and distinguishes breast cancer patients who did or did not derive benefit from trastuzumab. We perform tissue-SELEX on breast cancer specimens to enrich single-stranded DNA (ssDNA) libraries that preferentially interact with molecular components associated with the two clinical phenotypes. Testing of independent sample sets verifies the ability of PLP to classify trastuzumab-treated patients according to their clinical outcomes with ROC-AUC of 0.78. Standard HER2 testing of the same patients gives a ROC-AUC of 0.47. Kaplan-Meier analysis reveals a median increase in benefit from trastuzumab-containing treatments of 300 days for PLP-positive compared to PLP-negative patients. If prospectively validated, PLP may increase success rates in precision oncology and clinical trials, thus improving both patient care and drug development.

Does influenza pandemic preparedness and mitigation require gain-of-function research?

The risk and benefits of gain-of-function studies on influenza A have been widely debated since 2012 when the methods to create two respiratory transmissible H5N1 mutant isolates were published. Opponents of gain-of-function studies argue the biosecurity risk is unacceptable, while proponents cite potential uses for pandemic surveillance, preparedness and mitigation. In this commentary, we provide an overview of the background and applications of gain-of-function research and argue that the anticipated benefits have yet to materialize while the significant risks remain.

Prognostic Role of Histological Tumor Regression in Patients Receiving Neoadjuvant Chemotherapy for High-Grade Serous Tubo-ovarian Carcinoma.

OBJECTIVE: Our objective was to validate the prognostic role of the chemotherapy response score (CRS), which has been proposed for measuring tumor response to neoadjuvant chemotherapy in patients with high-grade serous tubo-ovarian carcinoma, in predicting progression-free survival (PFS) and overall survival (OS). METHODS: A retrospective cohort study was conducted of patients with advanced high-grade serous tubo-ovarian carcinoma diagnosed between January 1, 2010, and December 31, 2014, and treated with neoadjuvant chemotherapy. Treatment-related tumor regression was determined according to the 3-tier CRS, and results were compared with standard clinicopathological variables. Survival analysis was performed using Cox proportional hazards models and the log-rank test. RESULTS: Seventy-one patients were eligible for analysis. Median OS was 25.5 months. Fifty-eight patients (82%) had disease recurrence and 32 (45%) had died at study census. Of the 71 patients, 19, 29, and 23 patients had a CRS of 1, 2, and 3, respectively. On univariate analysis, the CRS significantly predicted PFS (hazard ratio [HR], 3.77; 95% confidence interval [CI], 1.83-7.78; P = 0.000) and OS (HR, 2.81; 95% CI, 1.16-6.79; P = 0.022). In a multivariate model, the CRS was significantly associated with PFS (HR, 2.81; 95% CI, 1.16-6.79; P = 0.022) but not with OS (HR, 2.39; 95% CI, 0.47-3.08; P = 0.079). Patients with CRS of 1 and 2 combined were twice as likely to progress during the study period compared with patients with a CRS of 3 (HR, 2.0; 95% CI, 1.06-3.78; P = 0.032; median PFS, 16 vs 26 months). No significant association was observed for OS (CRS 1/2 vs 3; HR, 1.57; 95% CI, 0.68-3.65; P = 0.291). CONCLUSIONS: In this study, the CRS showed independent prognostic significance for PFS but not for OS.

Bayesian phylogeography of influenza A/H3N2 for the 2014-15 season in the United States using three frameworks of ancestral state reconstruction.

Ancestral state reconstructions in Bayesian phylogeography of virus pandemics have been improved by utilizing a Bayesian stochastic search variable selection (BSSVS) framework. Recently, this framework has been extended to model the transition rate matrix between discrete states as a generalized linear model (GLM) of genetic, geographic, demographic, and environmental predictors of interest to the virus and incorporating BSSVS to estimate the posterior inclusion probabilities of each predictor. Although the latter appears to enhance the biological validity of ancestral state reconstruction, there has yet to be a comparison of phylogenies created by the two methods. In this paper, we compare these two methods, while also using a primitive method without BSSVS, and highlight the differences in phylogenies created by each. We test six coalescent priors and six random sequence samples of H3N2 influenza during the 2014-15 flu season in the U.S. We show that the GLMs yield significantly greater root state posterior probabilities than the two alternative methods under five of the six priors, and significantly greater Kullback-Leibler divergence values than the two alternative methods under all priors. Furthermore, the GLMs strongly implicate temperature and precipitation as driving forces of this flu season and nearly unanimously identified a single root state, which exhibits the most tropical climate during a typical flu season in the U.S. The GLM, however, appears to be highly susceptible to sampling bias compared with the other methods, which casts doubt on whether its reconstructions should be favored over those created by alternate methods. We report that a BSSVS approach with a Poisson prior demonstrates less bias toward sample size under certain conditions than the GLMs or primitive models, and believe that the connection between reconstruction method and sampling bias warrants further investigation.

Named entity linking of geospatial and host metadata in GenBank for advancing biomedical research.

DATABASE URL: : https://zodo.asu.edu/zoophydb/.