Biochemical Properties of a Decoy Oligodeoxynucleotide Inhibitor of STAT3 Transcription Factor.

Cyclic STAT3 decoy (CS3D) is a second-generation, double-stranded oligodeoxynucleotide (ODN) that mimics a genomic response element for signal transducer and activator of transcription 3 (STAT3), an oncogenic transcription factor. CS3D competitively inhibits STAT3 binding to target gene promoters, resulting in decreased expression of proteins that promote cellular proliferation and survival. Previous studies have demonstrated antitumor activity of CS3D in preclinical models of solid tumors. However, prior to entering human clinical trials, the efficiency of generating the CS3D molecule and its stability in biological fluids should be determined. CS3D is synthesized as a single-stranded ODN and must have its free ends ligated to generate the final cyclic form. In this study, we report a ligation efficiency of nearly 95 percent. The ligated CS3D demonstrated a half-life of 7.9 h in human serum, indicating adequate stability for intravenous delivery. These results provide requisite biochemical characterization of CS3D that will inform upcoming clinical trials

Acetophenone Monomers from Acronychia trifoliolata

Seven new [acronyculatins I-O (1-7)] and four known acetophenone monomers were isolated from a CH 3 OH/CH 2 Cl 2 (1:1) extract (N089419) of Acronychia trifoliolata provided by the U.S. National Cancer Institute (NCI, Frederick, MD, USA). Their structures were characterized by using various NMR and HRMS techniques. Among the known compounds, the structure of acronyculatin B (8) was revised. Some of the isolated compounds were evaluated for antiproliferative activity against human cancer cell lines. While most of the tested compounds were not cytotoxic, acronyculatins I (1) and J (2) showed moderate antiproliferative activity

N and P constrain C in ecosystems under climate change: role of nutrient redistribution, accumulation, and stoichiometry

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rastetter, E., Kwiatkowski, B., Kicklighter, D., Plotkin, A., Genet, H., Nippert, J., O’Keefe, K., Perakis, S., Porder, S., Roley, S., Ruess, R., Thompson, J., Wieder, W., Wilcox, K., & Yanai, R. N and P constrain C in ecosystems under climate change: role of nutrient redistribution, accumulation, and stoichiometry. Ecological Applications, (2022): e2684, https://doi.org/10.1002/eap.2684.We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO2), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO2, warming, and decreased precipitation combined because higher water-use efficiency with elevated CO2 and higher fertility with warming compensate for responses to drought. Response to elevated CO2, warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C-nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO2 and climate change.This material is based on work supported by the National Science Foundation under Grant No. 1651722 as well through the NSF LTER Program 1637459, 2220863 (ARC), 1637686 (NWT), 1832042 (KBS), 2025849 (KNZ), 1636476 (BNZ), 1637685 (HBR), 1832210 (HFR), 2025755 (AND). We also acknowledge NSF grants 1637653 and 1754126 (INCyTE RCN), and DOE grant DESC0019037. We also acknowledge support through the USDA Forest Service Hubbard Brook Experimental Forest, North Woodstock, New Hampshie (USDA NIFA 2019-67019-29464) and Pacific Northwest Research Station, Corvallis, Oregon

Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time

Background Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique. Methods We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool. Results Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small. Conclusion Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for. The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses

The Biosafety Research Road Map: The Search for Evidence to Support Practices in the Laboratory—SARS-CoV-2

Introduction: The SARS-CoV-2 virus emerged as a novel virus and is the causative agent of the COVID-19 pandemic. It spreads readily human-to-human through droplets and aerosols. The Biosafety Research Roadmap aims to support the application of laboratory biological risk management by providing an evidence base for biosafety measures. This involves assessing the current biorisk management evidence base, identifying research and capability gaps, and providing recommendations on how an evidence-based approach can support biosafety and biosecurity, including in low-resource settings. Methods: A literature search was conducted to identify potential gaps in biosafety and focused on five main sections, including the route of inoculation/modes of transmission, infectious dose, laboratory-acquired infections, containment releases, and disinfection and decontamination strategies. Results: There are many knowledge gaps related to biosafety and biosecurity due to the SARS-CoV-2 virus's novelty, including infectious dose between variants, personal protective equipment for personnel handling samples while performing rapid diagnostic tests, and laboratory-acquired infections. Detecting vulnerabilities in the biorisk assessment for each agent is essential to contribute to the improvement and development of laboratory biosafety in local and national systems

International cancer microbiome consortium consensus statement on the role of the human microbiome in carcinogenesis

Objective In this consensus statement, an international panel of experts deliver their opinions on key questions regarding the contribution of the human microbiome to carcinogenesis.Design International experts in oncology and/or microbiome research were approached by personal communication to form a panel. A structured, iterative, methodology based around a 1-day roundtable discussion was employed to derive expert consensus on key questions in microbiome-oncology research.Results Some 18 experts convened for the roundtable discussion and five key questions were identified regarding: (1) the relevance of dysbiosis/an altered gut microbiome to carcinogenesis; (2) potential mechanisms of microbiota-induced carcinogenesis; (3) conceptual frameworks describing how the human microbiome may drive carcinogenesis; (4) causation versus association; and (5) future directions for research in the field.The panel considered that, despite mechanistic and supporting evidence from animal and human studies, there is currently no direct evidence that the human commensal microbiome is a key determinant in the aetiopathogenesis of cancer. The panel cited the lack of large longitudinal, cohort studies as a principal deciding factor and agreed that this should be a future research priority. However, while acknowledging gaps in the evidence, expert opinion was that the microbiome, alongside environmental factors and an epigenetically/genetically vulnerable host, represents one apex of a tripartite, multidirectional interactome that drives carcinogenesis.Conclusion Data from longitudinal cohort studies are needed to confirm the role of the human microbiome as a key driver in the aetiopathogenesis of cancer

The Biosafety Research Road Map: The Search for Evidence to Support Practices in Human and Veterinary Laboratories

Introduction: Lack of evidence-based information regarding potential biological risks can result in inappropriate or excessive biosafety and biosecurity risk-reduction strategies. This can cause unnecessary damage and loss to the physical facilities, physical and psychological well-being of laboratory staff, and community trust. A technical working group from the World Organization for Animal Health (WOAH, formerly OIE), World Health Organization (WHO), and Chatham House collaborated on the Biosafety Research Roadmap (BRM) project. The goal of the BRM is the sustainable implementation of evidence-based biorisk management of laboratory activities, particularly in low-resource settings, and the identification of gaps in the current biosafety and biosecurity knowledge base. Methods: A literature search was conducted for the basis of laboratory design and practices for four selected high-priority subgroups of pathogenic agents. Potential gaps in biosafety were focused on five main sections, including the route of inoculation/modes of transmission, infectious dose, laboratory-acquired infections, containment releases, and disinfection and decontamination strategies. Categories representing miscellaneous, respiratory, bioterrorism/zoonotic, and viral hemorrhagic fever pathogens were created within each group were selected for review. Results: Information sheets on the pathogens were developed. Critical gaps in the evidence base for safe sustainable biorisk management were identified. Conclusion: The gap analysis identified areas of applied biosafety research required to support the safety, and the sustainability, of global research programs. Improving the data available for biorisk management decisions for research with high-priority pathogens will contribute significantly to the improvement and development of appropriate and necessary biosafety, biocontainment and biosecurity strategies for each agent