A review of the development of histotripsy for extremity tumor ablation with a canine comparative oncology model to inform human treatments

AbstractCancer is a devasting disease resulting in millions of deaths worldwide in both humans and companion animals, including dogs. Treatment of cancer is complex and challenging and therefore often multifaceted, as in the case of osteosarcoma (OS) and soft tissue sarcoma (STS). OS predominantly involves the appendicular skeleton and STS commonly develops in the extremities, resulting in treatment challenges due to the need to balance wide-margin resections to achieve local oncological control against the functional outcomes for the patient. To achieve wide tumor resection, invasive limb salvage surgery is often required, and the patient is at risk for numerous complications which can ultimately lead to impaired limb function and mobility. The advent of tumor ablation techniques offers the exciting potential of developing noninvasive or minimally invasive treatment options for extremity tumors. One promising innovative tumor ablation technique with strong potential to serve as a noninvasive limb salvage treatment for extremity tumor patients is histotripsy. Histotripsy is a novel, noninvasive, non-thermal, and non-ionizing focused ultrasound technique which uses controlled acoustic cavitation to mechanically disintegrate tissue with high precision. In this review, we present the ongoing development of histotripsy as a non-surgical alternative for extremity tumors and highlight the value of spontaneously occurring OS and STS in the pet dog as a comparative oncology research model to advance this field of histotripsy research

High prevalence of Phasi Charoen-like virus from wild-caught Aedes aegypti in Grenada, W.I. as revealed by metagenomic analysis.

Arboviruses cause diseases of significant global health concerns. Interactions between mosquitoes and their microbiota as well as the important role of this interaction in the mosquito's capacity to harbor and transmit pathogens have emerged as important fields of research. Aedes aegypti is one of the most abundant mosquitoes in many geographic locations, a vector capable of transmitting a number of arboviruses such as dengue and Zika. Currently, there are few studies on the metavirome of this mosquito particularly in the Americas. This study analyzes the metavirome of A. aegypti from Grenada, a Caribbean nation with tropical weather, abundant A. aegypti, and both endemic and arboviral pathogens transmitted by this mosquito. Between January and December 2018, 1152 mosquitoes were collected from six semi-rural locations near houses in St. George Parish, Grenada, by weekly trapping using BG-Sentinel traps. From these, 300 A. aegypti were selected for analysis. The metavirome was analyzed using the Illumina HiSeq 1500 for deep sequencing. The generation sequencing library construction protocol used was NuGEN Universal RNA with an average read length of 125 bp. Reads were mapped to the A. aegypti assembly. Non-mosquito reads were analyzed using the tools FastViromeExplorer. The NCBI total virus, RNA virus, and eukaryotic virus databases were used as references. The metagenomic comparison analysis showed that the most abundant virus-related reads among all databases and assemblies was Phasi Charoen-like virus. The Phasi Charoen-like virus results are in agreement to other studies in America, Asia and Australia. Further studies using wild-caught mosquitoes is needed to assess the impact of this insect-specific virus on the A. aegypti lifecycle and vector capacity

Metagenomic analysis of Aedes aegypti and Culex quinquefasciatus mosquitoes from Grenada, West Indies.

The mosquitoes Aedes aegypti (Linnaeus, 1762) (Diptera: Culicidae) and Culex quinquefasciatus Say, 1823 (Diptera: Culicidae) are two major vectors of arthropod-borne pathogens in Grenada, West Indies. As conventional vector control methods present many challenges, alternatives are urgently needed. Manipulation of mosquito microbiota is emerging as a field for the development of vector control strategies. Critical to this vector control approach is knowledge of the microbiota of these mosquitoes and finding candidate microorganisms that are common to the vectors with properties that could be used in microbiota modification studies. Results showed that bacteria genera including Asaia, Escherichia, Pantoea, Pseudomonas, and Serratia are common to both major arboviral vectors in Grenada and have previously been shown to be good candidates for transgenetic studies. Also, for the first time, the presence of Grenada mosquito rhabdovirus 1 is reported in C. quinquefasciatus

Same data, different conclusions : radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed