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Background: Hepatocellular carcinoma (HCC) is the second leading cause of malignancy-related mortality and the fifth most common worldwide. Immuno-cancer microenvironment (ICME) was highlighted recently because scientists want to unlock the detailed mechanism in carcinogenesis pathway and find the novel interactions in ICME. Besides, single cell analysis could mitigate the interrupted signals between cells and tissues. On the other hand, COVID-19 angiotensin I converting enzyme (ACE) previously was reported associated with cancer. However, the robust association between COVID-19 and HCC ICME is still unaddressed. Aim(s): We plan to investigate the COVID-19 ACE relevant genes to HCC ICME regarding survival. Method(s): We used Reactome for COVID-19 ACE gene pathway mapping and explored the positive relevant gene expression. DISCO website was applied for single cell analyses using the above-collected genes from Reactome. Finally, we implanted the biomedical informatics into TIMER 2.0 for ICME survival analyses. Result(s): In Fig. 1, the gene-gene interaction mapping was shown. We collected 13 genes (CPB2, ACE2, AGT, MME, ANPEP, CPA3, ENPEP, GZMH, CTSZ, CTSD, CES1, ATP6AP2, and AOPEP) for further single cell relevant analyses, in Table 1, with detailed expression level (TPM). Among the above 13 genes, AGT, GZMH, CTSZ, CTSD, CES1, and ATP6AP2 were strongly expressed in liver tissue. We then applied the initial 13 genes to TIMER 2.0 for HCC ICME 2-year survival analyses. CPA3 and GZMH low expressions with high macrophage infiltration in HCC ICME showed significantly worse 2-year cumulative survival [hazard ratio (HR):CPA3 2.21, p-value 0.018;GZMH 2.07, p-value 0.0341]. ACE2, CPB2, AGT, MME, ANPEP, ENPEP, CTSZ, CTSD, CES1, and ATP6AP2 high expressions with high macrophage infiltration in HCC ICME revealed significantly worse 2-year cumulative survival. Conclusion(s): We demonstrate that ACE2 was strongly associated with HCC clinical survival with macrophage infiltration. However, the bidirectional translational roles about ACE2 relevant genes in HCC should be documented.
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Background/Aims: The clinical course of hepatitis B virus (HBV) infection in individuals with HIV-1 coinfection is marked by accelerated disease progression. A tenofovir-containing antiretroviral regimen is recommended in most people with HIV-1/HBV-coinfection, but there have not been randomized studies of tenofovir disoproxil fumarate (TDF) vs tenofovir alafenamide (TAF) in treatment- naive HIV-1/HBV-coinfected individuals. We report primary endpoint results from a Phase 3 study comparing bictegravir/emtricitabine/ TAF (B/F/TAF) vs dolutegravir + emtricitabine/TDF (DTG + F/TDF) at Week (W)48 in participants initiating treatment for both viruses. Method(s): Adults with HIV-1/HBV coinfection were randomized 1:1 to initiate blinded treatment with B/F/TAF or DTG + F/TDF (with placebo). Primary endpoints were the proportion of participants with HIV-1 RNA<50 copies/mL (FDA Snapshot) and plasma HBV DNA<29 IU/mL (missing = failure) at W48. Noninferiority was assessed with 95% CI (12% margin). Secondary and other endpoints included change from baseline cluster of differentiation 4 (CD4) count, proportion with hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) loss/seroconversion, and alanine transaminase (ALT) normalization (AASLD criteria). Result(s): Participants (N = 243) were randomized and treated (B/F/ TAF [n = 121], DTG + F/TDF [n = 122]) from 11 countries in Asia, Europe, North, and Latin America. Baseline characteristics were median age of 32 years, 4.5% female, 88% Asian, 30% HIV-1 RNA>100,000 c/mL, 40% CD4<200 cells/lL, median HBV DNA 8.1 log10 IU/mL, 78% HBeAg+. At W48, B/F/TAF was noninferior to DTG + F/TDF at achieving HIV-1 RNA<50 copies/mL (95% vs 91%, difference 4.1%;95% CI -2.5%-10.8%;P = 0.21), with mean CD4 gains of + 200 and + 175 cells/lL, respectively. B/F/TAF was superior to DTG + F/TDF at achieving HBV DNA<29 IU/mL (63% vs 43%, difference 16.6%;95% CI 5.9%-27.3%;P = 0.0023). Participants treated with B/F/TAF vs DTG + F/TDF had numerically higher HBsAg loss (13% vs 6%;P = 0.059), HBeAg loss (26% vs 14%;P = 0.055), HBeAg seroconversion (23% vs 11%;P = 0.031), and ALT normalization (73% vs 55%;P = 0.066). The most frequent adverse events among participants treated with B/F/TAF vs DTG + F/TDF were upper respiratory tract infection (17% vs 11%), COVID- 19 (13% vs 11%), pyrexia (9% vs 12%), ALT increase (7% vs 11%), and nasopharyngitis (11% vs 4%). ALT flares (elevations at >= 2 consecutive postbaseline visits) occurred in 11 participants (7 B/F/ TAF, 4 DTG + F/TDF), and all resolved. Conclusion(s): Among adults with HIV-1/HBV-coinfection starting antiviral therapy, both B/F/TAF and DTG + F/TDF had high HIV-1 suppression at year 1, with B/F/TAF resulting in superior HBV DNA suppression and significantly more HBeAg seroconversion. Safety findings were similar between groups.
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Background: Previous studies have demonstrated promising serologic responses in PLWH receiving a third dose of vaccine against SARS-CoV-2. However, real-world clinical effectiveness, especially during the pandemic caused by B.1.1.529 variant, remains less investigated. Method(s): PLWH seeking HIV care at our hospital from 2021/6 to 2022/6 were included and advised to receive the third dose of COVID-19 vaccine. Individuals were excluded from this study if they had been previously diagnosed with COVID-19. Different types of COVID-19 vaccines were available in the vaccination program, including BNT162b2, mRNA-1273 (either 50 or 100 mug), MVC-COV1901 and NVX-CoV2373 vaccines. PLWH were screening for the occurrence of COVID-19 through the reporting system of notifiable diseases of Taiwan CDC, and were tested for anti-nucleocapsid (anti-N) IgG every 1 to 3 months. Participants were followed for 180 days until the fourth dose of COVID-19 vaccination, occurrence of SARS-CoV-2 infection, seroconversion of anti-N IgG, death, or loss to follow-up, whichever occurred first. Result(s): 1,496 PLWH were included: 631 (42.2%) receiving 100 mug mRNA-1273 vaccine, 468 (31.3%) 50 mug mRNA-1273 vaccine, and 328 (21.9%) BNT162b2 vaccine, 65 (4.3%) MVC-COV1901 vaccine, and 4 (0.3%) NVX-CoV2373 vaccine for the third dose of SARS-CoV-2 vaccination. 297 (19.9%) PLWH were diagnosed with COVID-19 during the follow-up period, including 92 (14.6%) who received 100 mug mRNA-1273, 111 (23.7%) 50 mug mRNA-1273, 79 (24.1%) BNT162b2 and 15 (21.7%) either MVC-COV1901 or NVX-CoV2373;in addition, 98 PLWH had seroconversion of anti-N IgG during follow-up, including 23, 50, 19 and 6 PLWH who received 100 mug mRNA-1273, 50 mug mRNA-1273, BNT162b2, and either MVC-COV1901 or NVX-CoV2373, respectively. Similar rates of new infection with SARS-CoV-2 or seroconversion of anti-N IgG were demonstrated regardless the vaccine type of the third dose (log-rank test, p=0.46). Factors associated with a diagnosis of SARS-CoV-2 infection and seroconversion of anti-N IgG included an age >50 years (aOR, 0.67;95% CI, 0.49-0.91) and newly infected with hepatitis C virus (HCV) (aOR, 1.41;95% CI, 1.09-1.83). Conclusion(s): Our study demonstrated that clinical effectiveness of the third dose of different vaccines available to PLWH was similar in preventing SARSCoV- 2 infection or seroconversion of anti-N IgG Taiwan. PLWH aged less than 50 years and those with newly diagnosed HCV infection were at higher risk of acquiring COVID-19. Kaplan-Meier survival curve for acquiring COVID-19 or seroconversion of anti-N IgG in PLWH receiving different COVID-19 vaccination of the third dose (log-rank test, 4 groups, p = 0.46).
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Background: Previous studies had demonstrated that patients with hematologic malignancies had suboptimal antibody response after receiving COVID-19 vaccines, especially among those having previously treated with anti- CD20 monoclonal antibodies. Method(s): Adult patients with non-Hodgkin's lymphoma or chronic lymphocytic leukemia (CLL) were enrolled before receiving the second dose of SARS-CoV-2 vaccine. Determinations of anti-SARS-CoV-2 spike and nucleocapsid IgG titers were performed every 1-3 months, after they received the second and the third dose of SARS-CoV-2 vaccine, respectively. Patients were excluded from analysis if they were diagnosed with COVID-19. All serum samples were tested for anti-nucleocapsid antibody and those tested positive were excluded from subsequent analyses. Result(s): A total of 85 participants were enrolled, including 42 (49.4%) with diffused large B-cell lymphoma, and 13 (15.3) with follicular lymphoma and 9 with CLL. 72 (84.7%) participants had received anti-CD20 monoclonal antibodies, with a median interval of 24 months between last anti-CD20 treatment and the second dose of vaccine, and 21 (24.7%) had HIV infection. Factors associated with failure to achieve an anti-spike IgG titer >141 BAU/ mL within 12 weeks after the second dose of vaccine included HIV infection (adjusted odds ratio [aOR], 0.14;95% CI, 0.04-0.51), active hematologic disease (aOR, 5.50;95% CI 1.42-21.32), receipt of anti-CD20 monoclonal antibodies (aOR, 6.65;95% CI 1.52-29.07), and receipt of two doses of homologous mRNA vaccination (aOR, 0.17;95% CI 0.05-0.56). In the participants having previously treated with anti-CD20 regimen, only 8.6% achieved an antibody response ( >141 BAU/mL) in the first year, while 78.3% achieved anti-spike IgG titer > 141 BAU/mL after two years post B-cell depleting treatment. After the third dose of SARS-CoV-2 vaccine, 53.6% achieved an antispike IgG titer > 141 BAU/mL in the first year post anti-CD20 treatment. Conclusion(s): Our study demonstrated that previous treatment with anti-CD20 monoclonal antibodies was associated a lower antibody response among patients with lymphoproliferative disorders receiving two doses of SARS-CoV-2 vaccine. While two doses of SARS-CoV-2 vaccines might not be sufficient even one year apart from the last dose of rituximab, a third dose of vaccine may boost anti-spike IgG particularly in the subset of recent exposure to rituximab. Anti-spike IgG determined 1-3 months after the second (A) / third (B) dose of COVID-19 vaccine, stratified by the interval between last anti-CD20 regimen and the second / third dose of COVID-19 vaccine. (Figure Presented).
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Background: To contain the coronavirus disease 2019 (Covid-19) pandemic, non-pharmacologic interventions, including lockdown and social distancing, may have adverse impact on access to HIV testing and care. This study investigated the impact of Covid-19 on HIV testing and care at a major hospital in Taiwan in 2020-2021. Method(s): The numbers of clients seeking anonymous HIV voluntary counseling and testing were compared 2 years before (2018-2019) and 2 years after Covid-19 outbreak (2020-2021). People living with HIV (PLWH) who sought care at the hospital during 2018-2021 were included to examine the status of HIV care delivery and disposition. Result(s): The annual number of HIV screening tests performed had significantly decreased from 2507 to 2794 in 2018 and 2019, respectively, to 2161 and 1737 in 2020 and 2021, respectively. The rate of discontinuation of HIV care among PLWH was 3.7% in 2019, which remained unchanged in 2020 (3.7%) and 2021 (3.8%). The respective percentage of annual plasma HIV RNA testing <2 times increased from 8.4% to 7.8% in 2018 and 2019 to 7.0% and 10.7% in 2020 and 2021, so was that of annual syphilis testing <2 times (10.1% and 8.8%-7.9% and 12.0%). The rates of plasma HIV RNA <200 copies/ml ranged from 97.0% to 98.1% in 2018-2021. Conclusion(s): During the Covid-19 pandemic, access to HIV counseling and testing was significantly limited. While the number of HIV-related testing decreased, the impact of Covid-19 on the continuity of antiretroviral therapy and viral suppression among PLWH appeared to be minimal in Taiwan. Copyright © 2022
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Travel time plays a vital role in people's daily lives. It can help them not merely avoid traffic congestion but save time as well. When people need to drive to different cities by taking highways, travel time become more and more important now that they can check it to arrange better routes. Moreover, because COVID-19 are epidemic across Taiwan, people prefer to drive rather than taking public transportation. Therefore, accurate predictions of travel time is of great significance. In order to obtain precise predictions and correspond to situations in real life, we divide data into long and short sequences and create three types of dataset, including the whole year, only national holidays, and non-holidays. Additionally, on account of the interactive influence of time in different segments of the freeway, we exploit data to predict next-hour travel time instead of next 5 minutes. We introduce a deep learning model which hybrids tendency from XGBoost and recency embeddings from a fully-connected neural network, respectively. It can capture crucial features of both long and short sequences and observe implicit correlations between XGBoost and a fully-connected neural network. Extensive experiments on the dataset illustrate that our model achieves eminent performances and outperforms other state-of-the-art models. © 2021 IEEE.
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Background: A large-scale community COVID-19 outbreak occurred between April and August 2021 in Taiwan, where non-pharmaceutical interventions (NPIs) have been strictly implemented and COVID-19 vaccination program was not implemented until 1 March, 2021. Although COVID-19 vaccination is recommended for at-risk populations, the vaccine effectiveness in people living with HIV (PLWH) remains incompletely understood. We evaluated the effectiveness of COVID-19 vaccination among PLWH during a COVID-19 outbreak in Taiwan. Methods: From 1 March to 30 September, 2021, all adult PLWH without previous SARS-CoV-2 infection were included and advised to receive 2 doses of COVID-19 vaccine. The government-funded vaccination campaign provided different types of COVID-19 vaccine, including ChAdOx1 nCoV-19 (AZD1222), BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and MVC-COV1901 (Medigen) vaccines. The primary endpoint of this study was the vaccine effectiveness in preventing COVID-19 among PLWH, which was estimated by comparing incidence rates between the unvaccinated, partially vaccinated, and fully vaccinated groups in a dynamic cohort. Results: During the study period, 3131 PLWH were included, with 99.9% on antiretroviral therapy, 99.8% being MSM and median CD4 count of 627 cells/mm3. In the dynamic cohort, 3128 PLWH contributed 516892 person-days of follow-up (PDFU) to the unvaccinated group, 2476 PLWH contributed 139163 PDFU to the partially vaccinated group, and 236 PLWH contributed 12011 PDFU to the fully vaccinated group (Table). During the follow-up, 37 PLWH (1.2%) acquired SARS-CoV-2 infections. The incidence rate of SARS-CoV-2 infection was 6.4 per 100,000 PDFU in the unvaccinated group, which decreased to 2.9 and 0 per 100,000 PDFU in the partially and fully vaccinated groups, respectively. The adjusted incidence rate ratios were 0.47 (95% CI, 0.17-1.32) in the partially vaccinated group and <0.01 in the fully vaccinated group compared with the unvaccinated group, resulting in vaccine effectiveness rates of 53.4% and 99.9% for single-and 2-dose COVID-19 vaccination, respectively. Conclusion: COVID-19 vaccination was clinically effective among PLWH during the outbreak setting where NPIs were strictly implemented.
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During the last decade, deep neural networks have shown a great performance in many machine learning tasks such as classification and clustering. One of the most successful networks is the CNN (Convolutional Neural Network), which has been applied in many application domains such as pattern recognition, medical diagnosis, and signal processing. Despite the very interesting performance of CNNs, their architecture design is still so far a major challenge for researchers and practitioners. Several works have been proposed in the literature with the aim to find optimized architectures such as ResNet and VGGNet. Unfortunately, most of these architectures are either manually defined by experts or automatically designed by greedy induction algorithms. Recent works suggest the use of Evolutionary Algorithms (EAs) thanks to their ability to escape locally-optimal architectures. Despite the fact that EAs have shown interesting performance, researchers in this direction have considered the design task as a single-level optimization problem;which represents the main research gap we tackle in this paper. The main contribution behind our work consists in the fact that CNN architecture design has a hierarchical nature and thus could be seen as a Bi-Level Optimization Problem (BLOP) where: (1) the upper level minimizes the network complexity defined by the number of blocks and the number of nodes per block;and (2) the lower level optimizes the convolution block ‘graphs’ topologies by maximizing the classification accuracy. Motivated by the originality of our observation with respect to the state of the art, we frame for the first time the CNN architecture design problem as a BLOP and then solve it using an adapted version of an existing efficient bi-level EA;through the definition of the solution encoding, the fitness function, and the variation operators at each level. The adapted EA is named BLOP-CNN and is assessed on the image classification task using the commonly employed CIFAR-10 and CIFAR-100 benchmark data sets. The analysis of our experimental results show the merits of our proposed method in providing the user with optimized architectures that outperform many recent and prominent architectures coming from the three different approaches, namely: manual design, reinforcement learning-based generation, and evolutionary optimization. Moreover, to show the applicability of our approach, we have conducted a case study on the detection of the COVID-19 using a set of benchmark chest X-ray and Computed Tomography (CT) images. © 2021 Elsevier B.V.