Stability, Digestion, and Cellular Transport of Soy Isoflavones Nanoparticles Stabilized by Polymerized Goat Milk Whey Protein.

Soy isoflavones (SIF) are bioactive compounds with low bioavailability due to their poor water solubility. In this study, we utilized polymerized goat milk whey protein (PGWP) as a carrier to encapsulate SIF with encapsulation efficiency of 89%, particle size of 135.53 nm, and zeta potential of -35.16 mV. The PGWP-SIF nanoparticles were evaluated for their stability and in vitro digestion properties, and their ability to transport SIF was assessed using a Caco-2 cell monolayer model. The nanoparticles were resistant to aggregation when subjected to pH changes (pH 2.0 to 8.0), sodium chloride addition (0-200 mM), temperature fluctuations (4 °C, 25 °C, and 37 °C), and long-term storage (4 °C, 25 °C, and 37 °C for 30 days), which was mainly attributed to the repulsion generated by steric hindrance effects. During gastric digestion, only 5.93% of encapsulated SIF was released, highlighting the nanoparticles' resistance to enzymatic digestion in the stomach. However, a significant increase in SIF release to 56.61% was observed during intestinal digestion, indicating the efficient transport of SIF into the small intestine for absorption. Cytotoxicity assessments via the MTT assay showed no adverse effects on Caco-2 cell lines after encapsulation. The PGWP-stabilized SIF nanoparticles improved the apparent permeability coefficient (Papp) of Caco-2 cells for SIF by 11.8-fold. The results indicated that using PGWP to encapsulate SIF was an effective approach for delivering SIF, while enhancing its bioavailability and transcellular transport.

Inhibition of miR-199b-5p reduces pathological alterations in osteoarthritis by potentially targeting Fzd6 and Gcnt2.

Osteoarthritis (OA) is a degenerative disease with a high prevalence in the elderly population, but our understanding of its mechanisms remains incomplete. Analysis of serum exosomal small RNA sequencing data from clinical patients and gene expression data from OA patient serum and cartilage obtained from the GEO database revealed a common dysregulated miRNA, miR-199b-5p. In vitro cell experiments demonstrated that miR-199b-5p inhibits chondrocyte vitality and promotes extracellular matrix degradation. Conversely, inhibition of miR-199b-5p under inflammatory conditions exhibited protective effects against damage. Local viral injection of miR-199b-5p into mice induced a decrease in pain threshold and OA-like changes. In an OA model, inhibition of miR-199b-5p alleviated the pathological progression of OA. Furthermore, bioinformatics analysis and experimental validation identified Gcnt2 and Fzd6 as potential target genes of MiR-199b-5p. Thus, these results indicated that MiR-199b-5p/Gcnt2 and Fzd6 axis might be a novel therapeutic target for the treatment of OA.

Image-activated pico-injection for single-cell analysis.

The addition of reagents into preformed droplets is a crucial yet intricate task in droplet-based applications where sequential reactions is required. Pico-injection offers high throughput and robustness in accomplishing this task, but the existing pico-injection techniques work in an indiscriminate manner, making it difficult to target particular groups of droplets. Here we report image-activated pico-injection (imgPico) for label-free, on-demand reagent supplementation into droplets. The imgPico detects the droplets of interest by real-time image analysis and makes decisions for the downstream pico-injection operation. We studied the performance of different algorithms for the image analysis and optimized the experimental settings of the imgPico. In the validation experiment, the imgPico successfully injected fluorescent dyes into droplets encapsulating one, two, and three cells, respectively, as expected. We further demonstrated the utility of imgPico by targeting droplets encapsulating single cells in droplet-based single-cell RNA sequencing (scRNA-seq) using exceedingly high cell density, and the results showed that the imgPico effectively reduced the presence of doublets in the scRNA-seq data. With the merits of being label-free and versatile, the imgPico represents a technical advance with potential applications in single-cell analysis.

Physicochemical and Functional Properties of Thermal-Induced Polymerized Goat Milk Whey Protein.

Goat milk whey protein products are a hard-to-source commodity. Whey protein concentrate was directly prepared from fresh goat milk. The effects of the heating temperature (69-78 °C), time (15-30 min), and pH (7.5-7.9) on the physicochemical and functional properties of the goat milk whey protein were investigated. The results showed that the particle size of the samples significantly increased (p < 0.05) after heat treatment. The zeta potential of polymerized goat milk whey protein (PGWP) was lower than that of native goat milk whey protein. The content of the free sulfhydryl groups of PGWP decreased with increasing heating temperature and time, while an increase in surface hydrophobicity and apparent viscosity of PGWP were observed after heat treatment. Fourier Transform Infrared Spectroscopy analysis indicated that heat treatment and pH had considerable impacts on the secondary structure of goat milk whey protein. Transmission electron microscope images revealed that heat induced the formation of a large and uniform protein network. Additionally, the changes in the physicochemical and structural properties contributed to the improvement of the emulsifying and foaming properties of goat milk whey protein after heat treatment. The results may provide a theoretical basis for the applications of polymerized goat milk whey protein in related products.

Identifying acute kidney injury subphenotypes using an outcome-driven deep-learning approach.

OBJECTIVE: Acute kidney injury (AKI), a common condition on the intensive-care unit (ICU), is characterized by an abrupt decrease in kidney function within a few hours or days, leading to kidney failure or damage. Although AKI is associated with poor outcomes, current guidelines overlook the heterogeneity among patients with this condition. Identification of AKI subphenotypes could enable targeted interventions and a deeper understanding of the injury's pathophysiology. While previous approaches based on unsupervised representation learning have been used to identify AKI subphenotypes, these methods cannot assess time series or disease severity. METHODS: In this study, we developed a data- and outcome-driven deep-learning (DL) approach to identify and analyze AKI subphenotypes with prognostic and therapeutic implications. Specifically, we developed a supervised long short-term memory (LSTM) autoencoder (AE) with the aim of extracting representation from time-series EHR data that were intricately correlated with mortality. Then, subphenotypes were identified via application of K-means. RESULTS: In two publicly available datasets, three distinct clusters were identified, characterized by mortality rates of 11.3%, 17.3%, and 96.2% in one dataset and 4.6%, 12.1%, and 54.6% in the other. Further analysis demonstrated that AKI subphenotypes identified by our proposed approach were statistically significant on several clinical characteristics and outcomes. CONCLUSION: In this study, our proposed approach could successfully cluster the AKI population in ICU settings into 3 distinct subphenotypes. Thus, such approach could potentially improve outcomes of AKI patients in the ICU, with better risk assessment and potentially better personalized treatment.

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue.

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.

Three-Dimensional Digital Reconstruction of the Cerebellar Cortex: Lobule Thickness, Surface Area Measurements, and Layer Architecture.

The cerebellum is ontogenetically one of the first structures to develop in the central nervous system; nevertheless, it has been only recently reconsidered for its significant neurobiological, functional, and clinical relevance in humans. Thus, it has been a relatively under-studied compared to the cerebrum. Currently, non-invasive imaging modalities can barely reach the necessary resolution to unfold its entire, convoluted surface, while only histological analyses can reveal local information at the micrometer scale. Herein, we used the BigBrain dataset to generate area and point-wise thickness measurements for all layers of the cerebellar cortex and for each lobule in particular. We found that the overall surface area of the cerebellar granular layer (including Purkinje cells) was 1,732 cm2 and the molecular layer was 1,945 cm2. The average thickness of the granular layer is 0.88 mm (± 0.83) and that of the molecular layer is 0.32 mm (± 0.08). The cerebellum (both granular and molecular layers) is thicker at the depth of the sulci and thinner at the crowns of the gyri. Globally, the granular layer is thicker in the lateral-posterior-inferior region than the medial-superior regions. The characterization of individual layers in the cerebellum achieved herein represents a stepping-stone for investigations interrelating structural and functional connectivity with cerebellar architectonics using neuroimaging, which is a matter of considerable relevance in basic and clinical neuroscience. Furthermore, these data provide templates for the construction of cerebellar topographic maps and the precise localization of structural and functional alterations in diseases affecting the cerebellum.

Preferences for a Mental Health Support Technology Among Chinese Employees: Mixed Methods Approach.

BACKGROUND: Workplace mental health is under-studied in China, making it difficult to design effective interventions. To encourage the engagement with interventions, it is crucial to understand employees' motivation toward seeking help through technologies. OBJECTIVE: This study aimed to understanding how Chinese employees view digital mental health support technology and how mental health support technology could be designed to boost the motivation of Chinese employees to use it. METHODS: A mixed methods approach was used. In total, 458 Chinese employees (248/458, 54% female) in 5 industries (manufacturing, software, medical, government, and education) responded to a survey, and 14 employees and 5 managers were interviewed. RESULTS: Government data and employee responses showed that mental health support in China is limited. In the workplace, Chinese employees experience a lower sense of autonomy satisfaction compared with competence and relatedness. Although managers and employees try to empathize with those who have mental health issues, discrimination and the stigma of mental illness are rife in Chinese workplaces. Digital technologies are perceived as a potential medium for mental health interventions; however, privacy is a major concern. CONCLUSIONS: The results of this study demonstrated the potential of self-help digital mental health support for Chinese employees. Interdisciplinary cooperation between design engineers and mental health researchers can contribute toward understanding the issues that engage or disengage users with digital mental health interventions.

The influence mechanism of source experience of the knowledge on the knowledge transfer performance: The role of political skill and knowledge barriers.

Exploring the relationship between characteristics of the source of knowledge and knowledge transfer performance seems to be crucial in order to make up for the lack of research on the political skills of knowledge sources in the process of knowledge transfer. For this reason, this study conducts a paired-sample questionnaire survey to achieve the research purpose. One direct supervisor was paired with 1∼4 subordinates; 274 other-reported questionnaires were sent out to supervisors and 1,096 self-reported questionnaires to subordinates. A total of 214 valid supervisor questionnaires and 630 valid subordinate questionnaires were collected. The finding demonstrates that knowledge sources with political skills can reduce knowledge barriers to knowledge transfer as well as affect knowledge transfer performance. This research presents a valid model that comprises the antecedents (characteristics of the knowledge source), mediators (knowledge barriers), moderators (political skill), and consequences of knowledge transfer performance of firms. Moreover, this study provides several meaningful directions for future research.

Epidemiological Characteristics and the Dynamic Transmission Model of Dengue Fever in Zhanjiang City, Guangdong Province in 2018.

Background: With the progress of urbanization, the mobility of people has gradually increased, which has led to the further spread of dengue fever. This study evaluated the transmissibility of dengue fever within districts and between different districts in Zhanjiang City to provide corresponding advice for cross-regional prevention and control. Methods: A mathematical model of transmission dynamics was developed to explore the transmissibility of the disease and to compare that between different regions. Results: A total of 467 DF cases (6.38 per 100,000 people) were reported in Zhanjiang City in 2018. In the model, without any intervention, the number of simulated cases in this epidemic reached about 950. The dengue fever transmissions between districts varied within and between regions. When the spread of dengue fever from Chikan Districts to other districts was cut off, the number of cases in other districts dropped significantly or even to zero. When the density of mosquitoes in Xiashan District was controlled, the dengue fever epidemic in Xiashan District was found to be significantly alleviated. Conclusions: When there is a dengue outbreak, timely measures can effectively control it from developing into an epidemic. Different prevention and control measures in different districts could efficiently reduce the risk of disease transmission.

Open-source algorithm and software for computed tomography-based virtual pancreatoscopy and other applications.

Pancreatoscopy plays a significant role in the diagnosis and treatment of pancreatic diseases. However, the risk of pancreatoscopy is remarkably greater than that of other endoscopic procedures, such as gastroscopy and bronchoscopy, owing to its severe invasiveness. In comparison, virtual pancreatoscopy (VP) has shown notable advantages. However, because of the low resolution of current computed tomography (CT) technology and the small diameter of the pancreatic duct, VP has limited clinical use. In this study, an optimal path algorithm and super-resolution technique are investigated for the development of an open-source software platform for VP based on 3D Slicer. The proposed segmentation of the pancreatic duct from the abdominal CT images reached an average Dice coefficient of 0.85 with a standard deviation of 0.04. Owing to the excellent segmentation performance, a fly-through visualization of both the inside and outside of the duct was successfully reconstructed, thereby demonstrating the feasibility of VP. In addition, a quantitative analysis of the wall thickness and topology of the duct provides more insight into pancreatic diseases than a fly-through visualization. The entire VP system developed in this study is available at https://github.com/gaoyi/VirtualEndoscopy.git .

[Spatial distribution and correlation of dominant species of karst secondary forest in central Guizhou, China]. / é»”ä¸­å–€æ–¯ç‰¹æ¬¡ç”Ÿæž—ä¼˜åŠ¿ç‰©ç§ç©ºé—´åˆ†å¸ƒæ ¼å±€åŠå ³è”æ€§.

We analyzed the spatial distribution pattern and correlation of the top four dominant tree species in a 2 hm2 karst secondary forest plot of Tianlong Mountain in central Guizhou, using pairwise correlation function g(r) combined with a completely random model (CSR). The results showed that the diameter structure of trees followed an inverted J-shape, and that more trees belonged to diameter class Ⅴ (≥10 cm) driven by the dominant trees of Lithocarpus confinis and Platycarya longipes. L. confinis presented an inverted J-shaped distribution, and the population could renew very well and was in the primary growth stage. The abundance of P. longipes and Itea yunnanensis increased gradually with increasing diameter class. The density of grown and large trees was far more than the young and small individuals, which indicated poor population regeneration, and the population was in the middle and late growth stages. The top dominant tree species, except L. confinis, showed clustering distribution at large scale, which was decreased gradually with scale and trended to distribute randomly. The pattern was particularly prominent in the diameter class for young trees. Different diameter classes of different tree species presented diffe-rent spatial distribution patterns which influenced by many factors. In terms of interspecific associations, the four dominant tree species showed negative or no associations. The higher importance value of tree species, the lower the degree of association with other dominant species. The two negative correlation tree species had the lowest degree of correlation at small scale. With the increase of spatial scale, the degree of negative correlation decreased gradually, and tended to be no correlation.

Effects of polymerized goat milk whey protein on physicochemical properties and microstructure of recombined goat milk yogurt.

Goat milk whey protein concentrates were manufactured by microfiltration (MF) and ultrafiltration (UF). When MF retentate blended with cream, which could be used as a starting material in yogurt making. The objective of this study was to prepare goat milk whey protein concentrates by membrane separation technology and to investigate the effects of polymerized goat milk whey protein (PGWP) on the physicochemical properties and microstructure of recombined goat milk yogurt. A 3-stage MF study was conducted to separate whey protein from casein in skim milk with 0.1-µm ceramic membrane. The MF permeate was ultrafiltered using a 10 kDa cut-off membrane to 10-fold, followed by 3 step diafiltration. The ultrafiltration-diafiltration-treated whey was electrodialyzed to remove 85% of salt, and to obtain goat milk whey protein concentrates with 80.99% protein content (wt/wt, dry basis). Recombined goat milk yogurt was prepared by mixing cream and MF retentate, and PGWP was used as main thickening agent. Compared with the recombined goat milk yogurt without PGWP, the yogurt with 0.50% PGWP had desirable viscosity and low level of syneresis. There was no significant difference in chemical composition and pH between the recombined goat milk yogurt with PGWP and control (without PGWP). Viscosity of all the yogurt samples decreased during the study. There was a slight but not significant decrease in pH during storage. Bifidobacterium and Lactobacillus acidophilus in yogurt samples remained above 106 cfu/g during 8-wk storage. Scanning electron microscopy of the recombined goat milk yogurt with PGWP displayed a compact protein network. Results indicated that PGWP prepared directly from raw milk may be a novel protein-based thickening agent for authentic goat milk yogurt making.

The Genetic and Prognostic Characteristics of AML-MRC Patients / 中国实验血液学杂志

OBJECTIVE@#To investigate the genetic and prognostic characteristics of acute myeloid leukemia with myelodysplasia-related changes (AML-MRC) patients.@*METHODS@#There were 230 non-M3 AML patients treated in Ningbo First Hospital enrolled, among which 58 patients were newly diagnosed AML-MRC, the patients were followed up and SPSS 25.0 was used to statistically analyze.@*RESULTS@#There were 49 patients performed genetic testing, 29 patients (59.2%) showed chromosomal abnormalities, including 7q- 8 cases (16.3%), 5q- 6 cases (12.2%), 5 cases (10.2%) of 17p abnormalities, 13 cases (26.5%) of highly abnormal complex karyotypes (CK) (≥5 unrelated chromosomal abnormalities), CK contained chromosomal abnormalities such as +8, 5q-, and 12 cases (24.5%) of monosomal karyotypes (MK). Genetic testing was performed in 37 patients, and 24 (64.9%) patients showed genetic mutations, among which ASXL1 mutation was the most common (8 cases, 21.6%), followed by TET2 mutation in 6 cases (16.2%). Kaplan-Meier analysis showed that AML-MRC patients with high CK (P=0.012), 5q- abnormalities (P=0.038), and TP53 mutations (P=0.008) had poor overall survival.@*CONCLUSION@#AML-MRC has unique genetic characteristics, and high CK, 5q- and TP53 mutations are poor prognostic factors.

The optimal vaccination strategy to control COVID-19: a modeling study in Wuhan City, China.

BACKGROUND: Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China. METHODS: We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (Reff) was used to estimate the transmission interaction in different age groups. RESULTS: A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (Reff = 4.28), followed by group 2 to 3 (Reff = 2.61), and group 2 to 4 (Reff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45-64 years old. CONCLUSIONS: Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15-64 years should first be vaccinated to prevent transmission in China.

Site-Selective C-C Cleavage of Benzocyclobutenones Enabled by a Blocking Strategy Using Nickel Catalysis.

Controlling the chemo- and regioselectivity of transition-metal-catalyzed C-C activation remains a great challenge. The transformations of benzocyclobutenones (BCBs) usually involve the cleavage of C1-C2 bond. In this work, an unprecedented highly selective cleavage of C1-C8 bond with the insertion of alkynes is achieved by using blocking strategy via Ni catalysis, providing an efficient method for synthesis of 1,8-disubstituted naphthalenes. Notably, the blocking group could be readily removed after the transformation.

Feasibility of controlling hepatitis E in Jiangsu Province, China: a modelling study.

BACKGROUND: Hepatitis E, an acute zoonotic disease caused by the hepatitis E virus (HEV), has a relatively high burden in developing countries. The current research model on hepatitis E mainly uses experimental animal models (such as pigs, chickens, and rabbits) to explain the transmission of HEV. Few studies have developed a multi-host and multi-route transmission dynamic model (MHMRTDM) to explore the transmission feature of HEV. Hence, this study aimed to explore its transmission and evaluate the effectiveness of intervention using the dataset of Jiangsu Province. METHODS: We developed a dataset comprising all reported HEV cases in Jiangsu Province from 2005 to 2018. The MHMRTDM was developed according to the natural history of HEV cases among humans and pigs and the multi-transmission routes such as person-to-person, pig-to-person, and environment-to-person. We estimated the key parameter of the transmission using the principle of least root mean square to fit the curve of the MHMRTDM to the reported data. We developed models with single or combined countermeasures to assess the effectiveness of interventions, which include vaccination, shortening the infectious period, and cutting transmission routes. The indicator, total attack rate (TAR), was adopted to assess the effectiveness. RESULTS: From 2005 to 2018, 44 923 hepatitis E cases were reported in Jiangsu Province. The model fits the data well (R2 = 0.655, P < 0.001). The incidence of the disease in Jiangsu Province and its cities peaks are around March; however, transmissibility of the disease peaks in December and January. The model showed that the most effective intervention was interrupting the pig-to-person route during the incidence trough of September, thereby reducing the TAR by 98.11%, followed by vaccination (reducing the TAR by 76.25% when the vaccination coefficient is 100%) and shortening the infectious period (reducing the TAR by 50.05% when the infectious period is shortened to 15 days). CONCLUSIONS: HEV could be controlled by interrupting the pig-to-person route, shortening the infectious period, and vaccination. Among these interventions, the most effective was interrupting the pig-to-person route.

Effective Material Basis and Mechanism Analysis of Compound Banmao Capsule against Tumors Using Integrative Network Pharmacology and Molecular Docking.

PURPOSE: Compound banmao capsule (CBC), a well-known traditional Chinese medical material, is known to inhibit various tumors. However, its material basis and pharmacological mechanisms remain to be elucidated. This study aimed to investigate the effective material basis and mechanisms of action of CBC against tumors. METHODS: Active compounds of CBC were identified using public database and reports to build a network. The corresponding targets of active compounds were retrieved from online databases, and the antitumor targets were identified by GeneCards database. The antitumor hub targets were generated via protein-protein interaction analysis using String, and key compounds and targets from the integrative network were detected by molecular docking and ADMET. Top targets in hepatocellular carcinoma were confirmed by quantitative real-time PCR (qPCR). Finally, the multivariate biological network was built to identify the integrating mechanisms of action of CBC against tumor cells. RESULTS: A total of 128 compounds and 436 targets of CBC were identified successfully. Based on the generated multivariate biological network analysis, 25 key compounds, nine hub targets, and two pathways were further explored. Effective material bases of cantharidin, baicalein, scutellarin, sesamin, and quercetin were verified by integrative network analysis. PTGS2, ESR1, and TP53 were identified as hub targets via multivariate biological network analysis and confirmed using qPCR. Furthermore, VEGF and estrogen signaling pathways seem to play a role in the antitumor activity of CBC. Thus, breast cancer may be a potential clinical indication of CBC. CONCLUSION: This study successfully identified the material basis of CBC and its synergistic mechanisms of action against tumor cells.

Effectiveness of potential antiviral treatments in COVID-19 transmission control: a modelling study.

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Although public health countermeasures effectively controlled the epidemic in China, non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally. Vaccination is mainly used to prevent COVID-19, and most current antiviral treatment evaluations focus on clinical efficacy. Therefore, we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy. METHODS: We collected COVID-19 data of Wuhan City from published literature and established a database (from 2 December 2019 to 16 March 2020). We developed an age-specific model to evaluate the effectiveness of antiviral treatment in patients with COVID-19. Efficacy was divided into three types: (1) viral activity reduction, reflected as transmission rate decrease [reduction was set as v (0-0.8) to simulate hypothetical antiviral treatments]; (2) reduction in the duration time from symptom onset to patient recovery/removal, reflected as a 1/γ decrease (reduction was set as 1-3 days to simulate hypothetical or real-life antiviral treatments, and the time of asymptomatic was reduced by the same proportion); (3) fatality rate reduction in severely ill patients (fc) [reduction (z) was set as 0.3 to simulate real-life antiviral treatments]. The population was divided into four age groups (groups 1, 2, 3 and 4), which included those aged ≤ 14; 15-44; 45-64; and ≥ 65 years, respectively. Evaluation indices were based on outbreak duration, cumulative number of cases, total attack rate (TAR), peak date, number of peak cases, and case fatality rate (f). RESULTS: Comparing the simulation results of combination and single medication therapy s, all four age groups showed better results with combination medication. When 1/γ = 2 and v = 0.4, age group 2 had the highest TAR reduction rate (98.48%, 56.01-0.85%). When 1/γ = 2, z = 0.3, and v = 0.1, age group 1 had the highest reduction rate of f (83.08%, 0.71-0.12%). CONCLUSIONS: Antiviral treatments are more effective in COVID-19 transmission control than in mortality reduction. Overall, antiviral treatments were more effective in younger age groups, while older age groups showed higher COVID-19 prevalence and mortality. Therefore, physicians should pay more attention to prevention of viral spread and patients deaths when providing antiviral treatments to patients of older age groups.