A randomized control trial comparing peginterferon-α-2a versus observation after stopping tyrosine kinase inhibitor in chronic myeloid leukemia with deep molecular response for at least two years

Background: There is much advancement in treatment of chronic myeloid leukemia (CML) since the approval of first tyrosine kinase inhibitor (TKI), imatinib, by US FDA in 2001. One of them is definitely the concept of stopping TKI, starting at the CML patients who have achieved deep molecular response (MR) of MR4.5 for a reasonable long period of at least two years, pioneered by the researchers from French and Australia. Meanwhile, interferon, the standard treatment of CML before the era of TKI, showed that interferon-responded patients may indeed retain the response once interferon was withdrawn via interferon-induced immunity towards the leukemic clone. This is further supported by stop trial in Japan, in which after stopping TKI, interferon was given for 2 years and it showed a higher drug-free rate compared to stop trial from French and Australia. Hence, it is logical to postulate the use of interferon after TKI was stopped when patients have attained deep MR for more than two years will increase the percentage of patients remain TKI-free on follow-up. Materials and Methods: This is a multi-center randomized controlled trial. Adult CML patients, diagnosed in chronic phase, treated with ongoing TKI for at least 3 years without previous history of TKI failure and have achieved stable deep MR on International Scale for ≥2 years with at least 2 readings of MR4.5 (including the latest before study entry), were randomized into 2 arms: (1) peginterferon-α-2a, subcutaneous weekly, starting at 180 mcg, or (2) observation. Disease is monitored by PCR (centralized in Ampang Hospital) at monthly for the first year, 2 monthly for the second year and 3 monthly for the third year. Relapse is defined as either (i) one reading of loss of major MR, i.e. reading of >0.1% IS and confirmed by second analysis taken 1 month later if the first analysis point reading is ≤1% IS, or (ii) positivity of BCR-ABL1 transcripts, as confirmed by a second analysis point, indicating the increase (at least 1 log) in relation to the first analysis point at two successive assessments. Quality of Life is assessed using EORTC QLO-C30. Results: At the time of writing, total of 8 patients were randomized, 5 into peginterferon arm, 3 into observation arm, all were on imatinib, M:F = 4:4, Malay: Chinese:Indian = 3:4:1, median age 49.5 (range 25-58), median follow-up 4 months (range 1-6) and none of them relapse. Two patients developed imatinib withdrawal syndrome, both female on observation arm, one was mild and resolved after 2 months but one was severe and needed termination after 2 months and restarted on imatinib. Two patients in peginterferon arm developed mild hepatitis with liver enzymes <2x of ULN. Four patients were able to tolerate peginterferon-α-2a at the dose of 180 mcg weekly, while one patient needed dose reduction to 90 mcg weekly. Quality of life score comparing two months after stopping TKI and baseline will be presented in the conference later. Conclusion: No conclusive date can be drawn so far because sample size is small and follow-up is short. Nonetheless, this trial provides Malaysian CML a platform to stop TKI safely

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Isolation, identification of causative agent of "red boil disease" in grouper (Epinephelus salmoides) and its possible control by vaccination

This report presents the initial results of studies on the isolation and identification of the causative agent as well as possible immunization of the estuary groupers. It is hoped that by a vaccination programme, fish could be made immune to such disease. Results indicate: (1) Vibrio parahaemolyticus is pathogenic to estuary grouper (2) that the vaccines did not seem to protect the fish against the vibrio when challenged one week after vaccination, but that this was due to slow antibody production of the fish as salmonids challenged about 30-35 days after vaccination reported good protection against Vibrio anguillarum and other bacterial diseases. Experiments are now in progress to challenge the vaccinated groupers at a later stage

Multigap:Multi-pooled inception network with text augmentation for aesthetic prediction of photographs

With the advent of deep learning, convolutional neural networks have solved many imaging problems to a large extent. However, it remains to be seen if the image “bottleneck” can be unplugged by harnessing complementary sources of data. In this paper, we present a new approach to image aesthetic evaluation that learns both visual and textual features simultaneously. Our network extracts visual features by appending global average pooling blocks on multiple inception modules (MultiGAP), while textual features from associated user comments are learned from a recurrent neural network. Experimental results show that the proposed method is capable of achieving state-of-the-art performance on the AVA / AVAComments datasets. We also demonstrate the capability of our approach in visualizing aesthetic activation

Filling the gaps:Reducing the complexity of networks for multi-attribute image aesthetic prediction

Computational aesthetics have seen much progress in recent years with the increasing popularity of deep learning methods. In this paper, we present two approaches that leverage on the benefits of using Global Average Pooling (GAP) to reduce the complexity of deep convolutional neural networks. The first model fine-tunes a standard CNN with a newly introduced GAP layer. The second approach extracts global and local CNN codes by reducing the dimensionality of convolution layers with individual GAP operations. We also extend these approaches to a multi-attribute network which uses a style network to regularize the aesthetic network. Experiments demonstrate the capability of attaining comparable accuracy results while reducing training complexity substantiall