HTX-011 reduced pain intensity and opioid consumption versus bupivacaine HCl in bunionectomy: phase III results from the randomized EPOCH 1 study.

BACKGROUND AND OBJECTIVES: There is a need for local anesthetics that provide consistent analgesia through 72 hours after surgery. This study evaluates the use of HTX-011 (bupivacaine and meloxicam in Biochronomerpolymer technology), an extended-release, dual-acting local anesthetic, in reducing both postoperative pain over 72 hours and postoperative opioid use when compared with bupivacaine hydrochloride (HCl) and saline placebo. Inclusion of low-dose meloxicam in HTX-011 is designed to reduce local inflammation caused by surgery, potentiating the analgesic effect of bupivacaine. Previously, significant synergy has been observed with bupivacaine and meloxicam with both given locally together. METHODS: EPOCH 1 was a randomized, double-blind, placebo-controlled and active-controlled phase III study in subjects undergoing a primary unilateral, distal, first metatarsal bunionectomy in which subjects received either a single intraoperative dose of HTX-011, immediate-release bupivacaine HCl or saline placebo. RESULTS: A total of 412 subjects were dosed. The results for the primary and all four key secondary endpoints were statistically significant in favor of HTX-011. HTX-011 demonstrated superior, sustained pain reduction through 72 hours, significantly reduced opioid consumption and resulted in significantly more opioid-free subjects compared with saline placebo and bupivacaine HCl. Safety was similar across groups with fewer opioid-related adverse events observed in the HTX-011 group. CONCLUSIONS: HTX-011 demonstrated significant reduction in postoperative pain through 72 hours with significant reduction in opioid consumption and a significant increase in the proportion of opioid-free subjects compared with saline placebo and the most widely used local anesthetic, bupivacaine HCl. TRIAL REGISTRATION NUMBER: NCT03295721

Public health and economic costs of investigating a suspected outbreak of Legionnaires' disease.

This paper provides one of the first assessments of the burden of both the public health investigation and the economic costs associated with an apparent outbreak of Legionnaires' disease (LD) in South East London. In addition to epidemiological, microbiological and environmental investigations, we collected data on the staff time and resources committed by the 11 main organizations responsible for managing the outbreak. Of the overall estimated costs of 455,856 pounds, only 14% (64,264 pounds) was spent on investigation and control of the outbreak compared with 86% (391,592 pounds) spent on the hospital treatment of the patients. The time and money spent on public health services in this investigation appear to represent good value for money considering the potential costs of a major outbreak, including the high case-fatality rate in LD generally and the high health-care costs. Further research is needed to determine optimum strategies for the cost-effective use of health system resources in investigations of LD. Whether the threshold for investigation of cases should be based on observed incidence rates or the cost-effectiveness of investigations, or both, should be debated further

Differences in Electronic Structure of Global Warming Molecules Lead to Different Molecular Properties. Reply to Wallington et al.

No abstract availabl

kFactorVAE: Self-Supervised Regularization for Better A.I. Disentanglement

Obtaining disentangled representations is a goal sought after to make A.I. models more interpretable. Studies have proven the impossibility of obtaining these kinds of representations with just unsupervised learning, or in other words, without strong inductive biases. One strong inductive bias is a regularization term that encourages the invariance of factors of variations across an image and a carefully selected augmentation. In this thesis, we build upon the existing Variational Autoencoder (VAE)-based disentanglement literature by utilizing the aforementioned inductive bias. We evaluate our method on the dSprites dataset, a well-known benchmark, and demonstrate its ability to achieve comparable or higher disentanglement in significantly fewer training steps against our model’s unsupervised counterparts

Loss of the tumor suppressor, Tp53, enhances the androgen receptor-mediated oncogenic transformation and tumor development in the mouse prostate.

Recent genome analysis of human prostate cancers demonstrated that both AR gene amplification and TP53 mutation are among the most frequently observed alterations in advanced prostate cancer. However, the biological role of these dual genetic alterations in prostate tumorigenesis is largely unknown. In addition, there are no biologically relevant models that can be used to assess the molecular mechanisms for these genetic abnormalities. Here, we report a novel mouse model, in which elevated transgenic AR expression and Trp53 deletion occur simultaneously in mouse prostatic epithelium to mimic human prostate cancer cells. These compound mice developed an earlier onset of high-grade prostatic intraepithelial neoplasia and accelerated prostate tumors in comparison with mice harboring only the AR transgene. Histological analysis showed prostatic sarcomatoid and basaloid carcinomas with massive squamous differentiation in the above compound mice. RNA-sequencing analyses identified a robust enrichment of the signature genes for human prostatic basal cell carcinomas in the above prostate tumors. Master regulator analysis revealed SOX2 as a transcriptional regulator in prostatic basal cell tumors. Elevated expression of SOX2 and its downstream target genes were detected in prostatic tumors of the compound mice. Chromatin immunoprecipitation analyses implicate a coregulatory role of AR and SOX2 in the expression of prostatic basal cell signature genes. Our data demonstrate a critical role of SOX2 in prostate tumorigenesis and provide mechanistic insight into prostate tumor aggressiveness and progression mediated by aberrant AR and p53 signaling pathways