N-(2,6-Difluoro­benzo­yl)-P,P-bis­(pyrrolidin-1-yl)phosphinic amide

The phosphoryl and carbonyl groups in the title compound, C15H20F2N3O2P, are anti with respect to each other (but the P- and C-groups are separated by another atom) and the P atom is in a tetra­hedral coordination environment. Two C atoms in one of the pyrrolidinyl fragments are disordered over two sets of sites with occupancies of 0.746 (8) and 0.254 (8). The environments of the pyrrolidinyl N atoms show a slight deviation from planarity and none of the three N atoms is involved in any hydrogen bond as an acceptor. In the crystal, pairs of inter­molecular N—H⋯O hydrogen bonds form inversion dimers

Virotheranostics, a double-barreled viral gun pointed toward cancer; Ready to shoot?

Compared with conventional cancer treatments, the main advantage of oncolytic virotherapy is its tumor-selective replication followed by the destruction of malignant cells without damaging healthy cells. Accordingly, this kind of biological therapy can potentially be used as a promising approach in the field of cancer management. Given the failure of traditional monitoring strategies (such as immunohistochemical analysis (in providing sufficient safety and efficacy necessary for virotherapy and continual pharmacologic monitoring to track pharmacokinetics in real-time, the development of alternative strategies for ongoing monitoring of oncolytic treatment in a live animal model seems inevitable. Three-dimensional molecular imaging methods have recently been considered as an attractive approach to overcome the limitations of oncolytic therapy. These noninvasive visualization systems provide real-time follow-up of viral progression within the cancer tissue by the ability of engineered oncolytic viruses (OVs) to encode reporter transgenes based on recombinant technology. Human sodium/iodide symporter (hNIS) is considered as one of the most prevalent nuclear imaging reporter transgenes that provides precise information regarding the kinetics of gene expression, viral biodistribution, toxicity, and therapeutic outcomes using the accumulation of radiotracers at the site of transgene expression. Here, we provide an overview of pre-clinical and clinical applications of hNIS-based molecular imaging to evaluate virotherapy efficacy. Moreover, we describe different types of reporter genes and their potency in the clinical trials

Correction to: Virotheranostics, a double-barreled viral gun pointed toward cancer; ready to shoot? (Cancer Cell International, (2020), 20, 1, (131), 10.1186/s12935-020-01219-6)

An amendment to this paper has been published and can be accessed via the original article. © 2020, The Author(s)

Role of γδ T cells in controlling viral infections with a focus on influenza virus: implications for designing novel therapeutic approaches

Influenza virus infection is among the most detrimental threats to the health of humans and some animals, infecting millions of people annually all around the world and in many thousands of cases giving rise to pneumonia and death. All those health crises happen despite previous and recent developments in anti-influenza vaccination, suggesting the need for employing more sophisticated methods to control this malign infection. Main body The innate immunity modules are at the forefront of combating against influenza infection in the respiratory tract, among which, innate T cells, particularly gamma-delta (γδ) T cells, play a critical role in filling the gap needed for adaptive immune cells maturation, linking the innate and adaptive immunity together. Upon infection with influenza virus, production of cytokines and chemokines including CCL3, CCL4, and CCL5 from respiratory epithelium recruits γδ T cells at the site of infection in a CCR5 receptor-dependent fashion. Next, γδ T cells become activated in response to influenza virus infection and produce large amounts of proinflammatory cytokines, especially IL-17A. Regardless of γδ T cells’ roles in triggering the adaptive arm of the immune system, they also protect the respiratory epithelium by cytolytic and non-cytolytic antiviral mechanisms, as well as by enhancing neutrophils and natural killer cells recruitment to the infection site. Conclusion: In this review, we explored varied strategies of γδ T cells in defense to influenza virus infection and how they can potentially provide balanced protective immune responses against infected cells. The results may provide a potential window for the incorporation of intact or engineered γδ T cells for developing novel antiviral approaches or for immunotherapeutic purposes

A Weighted Prognostic Covariate Adjustment Method for Efficient and Powerful Treatment Effect Inferences in Randomized Controlled Trials

A crucial task for a randomized controlled trial (RCT) is to specify a statistical method that can yield an efficient estimator and powerful test for the treatment effect. A novel and effective strategy to obtain efficient and powerful treatment effect inferences is to incorporate predictions from generative artificial intelligence (AI) algorithms into covariate adjustment for the regression analysis of a RCT. Training a generative AI algorithm on historical control data enables one to construct a digital twin generator (DTG) for RCT participants, which utilizes a participant's baseline covariates to generate a probability distribution for their potential control outcome. Summaries of the probability distribution from the DTG are highly predictive of the trial outcome, and adjusting for these features via regression can thus improve the quality of treatment effect inferences, while satisfying regulatory guidelines on statistical analyses, for a RCT. However, a critical assumption in this strategy is homoskedasticity, or constant variance of the outcome conditional on the covariates. In the case of heteroskedasticity, existing covariate adjustment methods yield inefficient estimators and underpowered tests. We propose to address heteroskedasticity via a weighted prognostic covariate adjustment methodology (Weighted PROCOVA) that adjusts for both the mean and variance of the regression model using information obtained from the DTG. We prove that our method yields unbiased treatment effect estimators, and demonstrate via comprehensive simulation studies and case studies from Alzheimer's disease that it can reduce the variance of the treatment effect estimator, maintain the Type I error rate, and increase the power of the test for the treatment effect from 80% to 85%~90% when the variances from the DTG can explain 5%~10% of the variation in the RCT participants' outcomes.Comment: 49 pages, 6 figures, 12 table

The first inherited retinal disease registry in Iran: Research protocol and results of a pilot study

Background: To describe the protocol for developing a national inherited retinal disease (IRD) registry in Iran and present its initial report. Methods: This community-based participatory research was approved by the Ministry of Health and Medical Education of Iran in 2016. To provide the minimum data set (MDS), several focus group meetings were held. The final MDS was handed over to an engineering team to develop a web-based software. In the pilot phase, the software was set up in two referral centers in Iran. Final IRD diagnosis was made based on clinical manifestations and genetic findings. Ultimately, patient registration was done based on all clinical and non-clinical manifestations. Results: Initially, a total of 151 data elements were approved with Delphi technique. The registry software went live at www.IRDReg.org based on DHIS2 open source license agreement since February 2016. So far, a total of 1001 patients have been registered with a mean age of 32.41±15.60 years (range, 3 months to 74 years). The majority of the registered patients had retinitis pigmentosa (42, 95 CI: 38.9 to 45). Genetic testing was done for approximately 20 of the registered individuals. Conclusion: Our study shows successful web-based software design and data collection as a proof of concept for the first IRD registry in Iran. Multicenter integration of the IRD registry in medical centers throughout the country is well underway as planned. These data will assist researchers to rapidly access information about the distribution and genetic patterns of this disease. © 2020 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Improving Network-on-Chip-based Turbo Decoder Architectures

In this work novel results concerning Networkon- Chip-based turbo decoder architectures are presented. Stemming from previous publications, this work concentrates first on improving the throughput by exploiting adaptive-bandwidth-reduction techniques. This technique shows in the best case an improvement of more than 60 Mb/s. Moreover, it is known that double-binary turbo decoders require higher area than binary ones. This characteristic has the negative effect of increasing the data width of the network nodes. Thus, the second contribution of this work is to reduce the network complexity to support doublebinary codes, by exploiting bit-level and pseudo-floatingpoint representation of the extrinsic information. These two techniques allow for an area reduction of up to more than the 40 % with a performance degradation of about 0.2 d