Algae material for clinical applications

Owing to special fascinating properties of algae material, it is widely used in food, paper, and textile industries. More promisingly, in clinical applications, algae material can be used as medical implants and devices to promote healing and serve as a carrier for cells during human tissues regeneration process. Nowadays, due to the correlated limitations (such as (1) gelating into soft structure in contact with physiological environment resulted in the failure of the soft tissue regeneration;(2) inappropriate applying in the relevant load bearing body parts), algae material exploration is insufficient in biomedical applications. To solve this problem, the scientific studies devoted to the application of algae material in clinical practice have been explored. To enhance mechanical properties, ameliorate healing capability, and promote tissue regeneration, drug release, and cell viability, algae material and related techniques for clinical applications are therefore marked along with the discussion of the latest trend related to COVID-19. © 2023 Elsevier Inc. All rights reserved.

Global Stability of a MERS-CoV Infection Model with CTL Immune Response and Intracellular Delay

In this paper, we propose and study a Middle East respiratory syndrome coronavirus (MERS-CoV) infection model with cytotoxic T lymphocyte (CTL) immune response and intracellular delay. This model includes five compartments: uninfected cells, infected cells, viruses, dipeptidyl peptidase 4 (DPP4), and CTL immune cells. We obtained an immunity-inactivated reproduction number (Formula presented.) and an immunity-activated reproduction number (Formula presented.). By analyzing the distributions of roots of the corresponding characteristic equations, the local stability results of the infection-free equilibrium, the immunity-inactivated equilibrium, and the immunity-activated equilibrium were obtained. Moreover, by constructing suitable Lyapunov functionals and combining LaSalle's invariance principle and Barbalat's lemma, some sufficient conditions for the global stability of the three types of equilibria were obtained. It was found that the infection-free equilibrium is globally asymptotically stable if (Formula presented.) and unstable if (Formula presented.) ;the immunity-inactivated equilibrium is locally asymptotically stable if (Formula presented.) and globally asymptotically stable if (Formula presented.) and condition (H1) holds, but unstable if (Formula presented.) ;and the immunity-activated equilibrium is locally asymptotically stable if (Formula presented.) and is globally asymptotically stable if (Formula presented.) and condition (H1) holds. © 2023 by the authors.

Application value of post-discharge chest low-dose CT for patients with COVID-19.

Objective: To explore the value of chest low-dose CT (LDCT) in post-discharge follow-up assessments of patients with coronavirus disease 2019 (COVID-19). Method(s): The chest CT findings of 58 patients with COVID-19 from March 17 to March 25, 2020 at Remin Hospital of Wuhan University were retrospectively analyzed. Two radiologists independently scored the subjective image quality on a 5-point Likert scale. The signal-to-noise ratio (SNR) and SDair of images and the CT radiation dose parameters were calculated, including the CT volume dose index (CTDIvol), dose length product (DLP), and effective radiation dose (E). Result(s): The subjective image quality scores on CT images obtained before and after discharge by readers 1 and 2, were 4.45+/-0.22, 3.88+/-0.33 (P>0.05) and 4.37+/-0.18, 3.91+/-0.35 (P>0.05), respectively. The SNR and SDair in LDCT after discharge were 4.39+/-0.95 and 7.19+/-2.41, which were significantly lower than those in routine chest CT before discharge (5.14+/-1.06, Z=-5.551, P<0.001;6.48+/-1.57, Z=-3.217, P<0.001). All of the obtained images were sufficient for diagnosis. The CTDIvol, DLP, and E in LDCT were significantly lower than those in routine CT [(2.41+/-0.09), (10.53+/-1.03)mGy, Z=-6.568, P<0.001;(88.03+/-5.33), (338.74+/-34.64)mGy*cm, Z=-6.624, P<0.001;and (1.23+/-0.17), (4.74+/-0.48)mSv, Z=-5.976, P<0.001]. Conclusion(s): Patients with COVID-19 can be followed up with low-dose chest CT after discharge.Copyright © 2020 by the Chinese Medical Association.

Traffic Data-Empowered XGBoost-LSTM Framework for Infectious Disease Prediction

Large-scale infectious diseases pose a tremendous risk to humans, with global outbreaks of COVID-19 causing millions of deaths and trillions of dollars in economic losses. To minimize the damage caused by large-scale infectious diseases, it is necessary to develop infectious disease prediction models to provide assistance for prevention. In this paper, we propose an XGBoost-LSTM mixed framework that predicts the spread of infectious diseases in multiple cities and regions. According to big traffic data, it was found that population flow is closely related to the spread of infectious diseases. Clustering and dividing cities according to population flow can significantly improve prediction accuracy. Meanwhile, an XGBoost is used to predict the transmission trend based on the key features of infection. An LSTM is used to predict the transmission fluctuation based on infection-related multiple time series features. The mixed model combines transmission trends and fluctuations to predict infections accurately. The proposed method is evaluated on a dataset of highly pathogenic infectious disease transmission published by Baidu and compared with other advanced methods. The results show that the model has an excellent predictive effect and practical value for large-scale infectious disease prediction.

INTERFERON RESISTANCE of EMERGING SARS-CoV-2 VARIANTS

Background: The continuing spread of SARS-CoV-2 provides opportunities for the virus to evolve. Compared to ancestral strains, the 4 major variants of concern (VOC) exhibit Spike mutations that improve entry and/or diminish antibody neutralization. However, mutations have arisen in other viral genes. Several of these genes may counteract innate immunity mediated by antiviral interferons (IFNs). IFNs show extensive diversity, but only IFNα2 and IFNβ are approved for clinical use. We showed previously that diverse IFNs exhibit variable activities against HIV-1 and trigger distinct transcriptomes. Methods: To assess whether SARS-CoV-2 acquired human IFN resistance over time, isolates representing early lineages A, B, B.1, and VOC lineages B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma) and B.1.617.2 (delta) were tested for sensitivity to multiple IFNs in an alveolar type II epithelial cell (AT2) line, A549, overexpressing ACE2. Cells were pre-treated with IFNs for 18 h in triplicate, then infected to yield ∼105 copies/reaction. Virus copy numbers were evaluated at 24 h by qPCR. We compared the sensitivity of 5 SARS-CoV-2 isolates to 12 IFNα subtypes, IFNβ, IFNω and 3 IFNa;subtypes at 2 pM, within the dynamic range of preliminary IFN inhibition curves. IC50s for IFNβ and IFNa;1 were compared between lineage B and VOC isolates. Results: Among the 17 IFNs tested, IFNβ, IFNα8, IFNω and IFNα5 most potently inhibited SARS-CoV-2 in A549-ACE2 cells. Inhibition curves with a delta variant isolate showed that IFNα2 and IFNa;1 had >10-fold and >1000-fold higher IC50 than IFNβ, respectively. Interestingly, the antiviral activity patterns of diverse IFNα subtypes against SARS-CoV-2 and HIV-1 were different and did not significantly correlate. Compared to the ancestral lineage B, the alpha, beta, gamma and delta variants exhibited on average 5.2-fold (range: 1.9-8.2) and 6.7-fold (range: 1.3-21) fold higher IC50s for IFNβ and IFNa;1, respectively. The alpha and delta isolates were also more resistant to IFNβ and IFNa;1 than a lineage B.1 isolate in another AT2 cell line, Calu-3. Conclusion: Our findings suggest that diverse IFNs may have evolved to restrict distinct virus families. Emerging SARS-CoV-2 variants are more effective than earlier pandemic viruses at antagonizing antiviral IFN responses. These data have implications for deploying IFNs for early COVID-19 therapy and suggest that innate immunity may be a driving force for SARS-CoV-2 evolution.

Has the extreme risk spillover among the currencies along Belt and Road increased since COVID-19?

The international financial market has been fluctuating dramatically ever since the outbreak of the COVID-19 epidemic. The Belt and Road, as an international cooperation platform, could also be affected by the increasing risk factors during the epidemic period. This paper researched the extreme co-movement probability between 5 representative currencies along the Belt and Road and CNY before and after the epidemic with the tail dependence of the currency pairs based on copula. The results suggest that EUR's and TRY's tail dependence with CNY increased significantly while ZAR's tail dependence with CNY decreased. Therefore, there does not exist a systematic increase of the extreme risk spillover. These findings on dependence structure between currencies along B&R could provide additional insight for policy makers and corporations.

Nonparametric Model Prediction for Intelligent Regulation of Human Cardiorespiratory System to Prescribed Exercise Medicine

Intelligent regulation for human exercise behaviors becomes significantly necessary for exercise medicine after the COVID-19 epidemic. The key issue of exercise regulation and its potential development for intelligent exercise is to describe human exercise physiological behaviors in a more accurate and sufficient manner. Here, a non-parametric modeling method with kernel-based regularization is presented to estimate cardiorespiratory biomarkers (i.e., oxygen uptake (V̇O2 ) and carbon dioxide output (V̇CO2 ) by merely non-invasively monitoring the indicator of exercise intensity (e.g., walking speed). Using the kernel-based non-parametric modeling, we show that V̇O2 and V̇CO2 behaviors in response to continuous and diversified exercise intensity stimulations can be quantitatively described. Furthermore, the dataset from the stairs experiment with a proper protocol is applied in the kernel parameter selection, and this selection approach is compared with the numerical simulation approach. The comparison results illustrate an improvement of 4.18% for oxygen uptake and 7.63% for carbon dioxide output in a half period, and 11.00% for oxygen uptake and 12.60% for carbon dioxide output in one period when using the kernel parameter selected from the stairs exercise. Moreover, the advantages of using the non-parametric model, the necessity of sufficient stimulation for identification and the importance of the kernel regularization term are also addressed in this paper. This method provides fundamental work for the practice of intelligent exercise. CCBY

Application value of post-discharge chest low-dose CT for patients with COVID-19

Objective: To explore the value of chest low-dose CT (LDCT) in post-discharge follow-up assessments of patients with coronavirus disease 2019 (COVID-19). Methods: The chest CT findings of 58 patients with COVID-19 from March 17 to March 25, 2020 at Remin Hospital of Wuhan University were retrospectively analyzed. Two radiologists independently scored the subjective image quality on a 5-point Likert scale. The signal-to-noise ratio (SNR) and SDair of images and the CT radiation dose parameters were calculated, including the CT volume dose index (CTDIvol), dose length product (DLP), and effective radiation dose (E). Results: The subjective image quality scores on CT images obtained before and after discharge by readers 1 and 2, were 4.45±0.22, 3.88±0.33 (P>0.05) and 4.37±0.18, 3.91±0.35 (P>0.05), respectively. The SNR and SDair in LDCT after discharge were 4.39±0.95 and 7.19±2.41, which were significantly lower than those in routine chest CT before discharge (5.14±1.06, Z=-5.551, P<0.001;6.48±1.57, Z=-3.217, P<0.001). All of the obtained images were sufficient for diagnosis. The CTDIvol, DLP, and E in LDCT were significantly lower than those in routine CT [(2.41±0.09), (10.53±1.03)mGy, Z=-6.568, P<0.001;(88.03±5.33), (338.74±34.64)mGy•cm, Z=-6.624, P<0.001;and (1.23±0.17), (4.74±0.48)mSv, Z=-5.976, P<0.001]. Conclusions: Patients with COVID-19 can be followed up with low-dose chest CT after discharge. Copyright © 2020 by the Chinese Medical Association.