The role of tunneling nanotubes during early stages of HIV infection and reactivation: implications in HIV cure

Tunneling nanotubes (TNTs), also called cytonemes or tumor microtubes, correspond to cellular processes that enable long-range communication. TNTs are plasma membrane extensions that form tubular processes that connect the cytoplasm of two or more cells. TNTs are mostly expressed during the early stages of development and poorly expressed in adulthood. However, in disease conditions such as stroke, cancer, and viral infections such as HIV, TNTs proliferate, but their role is poorly understood. TNTs function has been associated with signaling coordination, organelle sharing, and the transfer of infectious agents such as HIV. Here, we describe the critical role and function of TNTs during HIV infection and reactivation, as well as the use of TNTs for cure strategies.

The impact of attrition on the transmission of HIV and drug resistance

BACKGROUND

Attrition due to loss to follow-up or termination of antiretroviral therapy (ART) among HIV-infected patients in care may increase the risk of emergence and transmission of drug resistance (TDR), diminish benefit of treatment, and increase morbidity and mortality. Understanding the impact of attrition on the epidemic is essential to provide interventions for improving retention in care.

METHODS

We developed a comprehensive HIV transmission dynamics model by considering CD4 + cell count dependent diagnosis, treatment, and attrition involving TDR and acquired drug resistance. The model was calibrated by 11 groups HIV/AIDS surveillance data during 2008-2018 from Guangxi, China, and validated by the prevalence of TDR among diagnosed treatment-naive individuals. We aimed to investigate how attrition would affect the transmission of HIV and drug-resistance when expanding ART.

RESULTS

In the base case with CD4 + cell count dependent per capita attrition rates 0.025∼0.15 and treatment rates 0.23∼0.42, we projected cumulative total new infections, new drug-resistant infections, and HIV-related deaths over 2022-2030 would be 145 391, 7637, and 51 965, respectively. Increasing treatment rates by 0.1∼0.2 can decrease the above total new infections (deaths) by 1.63∼2.93% (3.52∼6.16%). However, even 0.0114∼0.0220 (0.0352∼0.0695) increase in attrition rates would offset this benefit of decreasing infections (deaths). Increasing treatment rates (attrition rates) by 0.05∼0.1 would increase the above drug-resistant infections by 0.16∼0.30% (22.18∼41.15%).

CONCLUSION

A minor increase in attrition can offset the benefit of treatment expansion and increase the transmission of HIV drug resistance. Reducing attrition rates for patients already in treatment may be as important as expanding treatment for untreated patients.

Mixed selling of different poultry species facilitates emergence of public-health-threating avian influenza viruses

Live poultry markets (LPMs) are regarded as hubs for avian influenza virus (AIV) transmission in poultry and are a major risk factor in human AIV infections. We performed an AIV surveillance study at a wholesale LPM, where different poultry species were sold in separate stalls, and nine retail LPMs, which received poultry from the wholesale LPM but where different poultry species were sold in one stall, in Guangdong province from 2017 to 2019. A higher AIV isolation rate was observed at the retail LPMs than the wholesale LPM. H9N2 was the dominant AIV subtype and was mainly present in chickens and quails. The genetic diversity of H9N2 viruses was greater at the retail LPMs, where a complex system of two-way transmission between different poultry species had formed. The isolated H9N2 viruses could be classed into four genotypes: G57 and the three novel genotypes, NG164, NG165, and NG166. The H9N2 AIVs isolated from chickens and quails at the wholesale LPM only belonged to the G57 and NG164 genotypes, respectively. However, the G57, NG164, and NG165 genotypes were identified in both chickens and quails at the retail LPMs. We found that the replication and transmission of the NG165 genotype were more adaptive to both poultry and mammalian models than those of its precursor genotype, NG164. Our findings revealed that mixed poultry selling at retail LPMs has increased the genetic diversity of AIVs, which might facilitate the emergence of novel viruses that threaten public health.

[Pathological evaluation of endoscopic submucosal dissection for early gastric cancer and precancerous lesion in 411 cases]

OBJECTIVE

To evaluate the pathological characteristics of endoscopic submucosal dissection (ESD) specimens for early gastric cancer and precancerous lesions, accumulating experience for clinical management and pathological analysis.

METHODS

A total of 411 cases of early gastric cancer or precancerous lesions underwent ESD. According to the Japanese guidelines for ESD treatment of early gastric cancer and classification of gastric carcinoma, the clinicopathological data, pathologic evaluation, concordance rate of pathological diagnosis between preoperative endoscopic forceps biopsies and their ESD specimens (in 400 cases), as well as the risk factors of non-curative resection of early gastric cancer, were analyzed retrospectively.

RESULTS

23.4% (96/411) of the 411 cases were adenoma/low-grade dysplasia and 76.6% (315/411) were early gastric cancer. The latter included 28.0% (115/411) non-invasive carcinoma/high-grade dysplasia and 48.7% (200/411) invasive carcinoma. The concordance rate of pathological diagnosis between endoscopic forceps biopsies and ESD specimens was 66.0% (264/400), correlating with pathological diagnosis and lesion location (P < 0.01). The rate of upgraded diagnosis and downgraded diagnosis after ESD was 29.8% (119/400) and 4.2% (17/400), respectively. Among the 315 cases of early gastric cancer, there were 277 cases (87.9%) of differentiated type and 38 cases (12.1%) of undifferentiated type. In the study, 262 cases (83.2%) met with absolute indication, while 53 cases (16.8%) met relative indication. En bloc and curative resection rates were 98.1% and 82.9%, respectively. Risk factors for non-curative resection included a long diameter >20 mm (OR=3.631, 95%CI: 1.170-11.270, P=0.026), tumor infiltration into submucosa (OR=69.761, 95%CI: 21.033-231.376, P < 0.001)and undifferentiated tumor histology (OR=16.950, 95%CI: 4.585-62.664, P < 0.001).

CONCLUSION

Several subjective and objective factors, such as the limitations of biopsy samples, the characteristics and distribution of the lesions, different pathological understanding, and the endoscopic sampling and observation, can lead to the differences between the preoperative and postoperative pathological diagnosis of ESD. In particular, the pathological upgrade of postoperative diagnosis was more significant and should receive more attention by endoscopists and pathologists. The curative resection rate of early gastric cancer in ESD was high. Non-curative resection was related to the long diameter, the depth of tumor invasion and histological classification. ESD can also be performed in undifferentiated early gastric cancer if meeting the indication criteria. The comprehensive and standardized pathological analysis of ESD specimens is clinically important to evaluate the curative effect of ESD operation and patient outcomes.

HIV infection dynamics and viral rebound: Modeling results from humanized mice

Despite years of combined antiretroviral therapy (cART), HIV persists in infected individuals. The virus also rebounds after the cessation of cART. The sources contributing to viral persistence and rebound are not fully understood. When viral rebound occurs, what affects the time to rebound and how to delay the rebound remain unclear. In this paper, we started with the data fitting of an HIV infection model to the viral load data in treated and untreated humanized myeloid-only mice (MoM) in which macrophages serve as the target of HIV infection. By fixing the parameter values for macrophages from the MoM fitting, we fit a mathematical model including the infection of two target cell populations to the viral load data from humanized bone marrow/liver/thymus (BLT) mice, in which both CD4+ T cells and macrophages are the target of HIV infection. Data fitting suggests that the viral load decay in BLT mice under treatment has three phases. The loss of infected CD4+ T cells and macrophages is a major contributor to the first two phases of viral decay, and the last phase may be due to the latent infection of CD4+ T cells. Numerical simulations using parameter estimates from the data fitting show that the pre-ART viral load and the latent reservoir size at treatment cessation can affect viral growth rate and predict the time to viral rebound. Model simulations further reveal that early and prolonged cART can delay the viral rebound after cessation of treatment, which may have implications in the search for functional control of HIV infection.

A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US

COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.

A Multiscale Model of COVID-19 Dynamics

COVID-19, caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a global pandemic and created unprecedented public health challenges throughout the world. Despite significant progresses in understanding the disease pathogenesis and progression, the epidemiological triad of pathogen, host, and environment remains unclear. In this paper, we develop a multiscale model to study the coupled within-host and between-host dynamics of COVID-19. The model includes multiple transmission routes (both human-to-human and environment-to-human) and connects multiple scales (both the population and individual levels). A detailed analysis on the local and global dynamics of the fast system, slow system and full system shows that rich dynamics, including both forward and backward bifurcations, emerge with the coupling of viral infection and epidemiological models. Model fitting to both virological and epidemiological data facilitates the evaluation of the influence of a few infection characteristics and antiviral treatment on the spread of the disease. Our work underlines the potential role that the environment can play in the transmission of COVID-19. Antiviral treatment of infected individuals can delay but cannot prevent the emergence of disease outbreaks. These results highlight the implementation of comprehensive intervention measures such as social distancing and wearing masks that aim to stop airborne transmission, combined with surface disinfection and hand hygiene that can prevent environmental transmission. The model also provides a multiscale modeling framework to study other infectious diseases when the environment can serve as a reservoir of pathogens.

The impact of supplementary immunization activities on measles transmission dynamics and implications for measles elimination goals: a mathematical modelling study

BACKGROUND

Measles has re-emerged globally due to the accumulation of susceptible individuals and immunity gap, which causes challenges in eliminating measles. Routine vaccination and supplementary immunization activities (SIAs) have greatly improved measles control, but the impact of SIAs on the measles transmission dynamics remains unclear as the vaccine-induced immunity wanes.

METHODS

We developed a comprehensive measles transmission dynamics model by taking into account population demographics, age-specific contact patterns, seasonality, routine vaccination, SIAs, and the waning vaccine-induced immunity. The model was calibrated by the monthly age-specific cases data from 2005 to 2018 in Jiangsu Province, China, and validated by the dynamic sero-prevalence data. We aimed to investigate the short-term and long-term impact of three-time SIAs during 2009-2012 (9.68 million and 4.25 million children aged 8 months-14 years in March 2009 and September 2010, respectively, and 140,000 children aged 8 months-6 years in March 2012) on the measles disease burden and explored whether additional SIAs could accelerate the measles elimination.

RESULTS

We estimated that the cumulative numbers of measles cases from March 2009 to December 2012 (in the short run) and to December 2018 (in the long run) after three-time SIAs (base case) were 6,699 (95% confidence interval [CI]: 2,928-10,469), and 22,411 (15,146-29,675), which averted 45.0% (42.9%-47.0%) and 34.3% (30.7%-37.9%) of 12,226 (4,916-19,537) and 34,274 (21,350-47,199) cases without SIAs, respectively. The fraction of susceptibles for children aged 8-23 months and 2-14 years decreased from 8.3% and 10.8% in March 2009 to 5.8% and 5.8% in April 2012, respectively. However, the fraction of susceptibles aged 15-49 years and above 50 years increased gradually to about 15% in 2018 irrespective of SIAs due to the waning immunity. The measles elimination goal would be reached in 2028, and administrating additional one-off SIAs in September 2022 to children aged 8-23 months, or young adolescents aged 15-19 years could accelerate the elimination one year earlier.

CONCLUSIONS

SIAs have greatly reduced the measles incidence and the fraction of susceptibles, but the benefit may wane over time. Under the current interventions, Jiangsu province would reach the measles elimination goal in 2028. Additional SIAs may accelerate the measles elimination one year earlier.

P-583 PCOS patients got better IVF/ICSI outcomes with “higher” progesterone level on hCG day: a retrospective study of Ten years data

Study question

We aimed to investigate whether serum Progesterone (P) on the day of hCG trigger can be used as a biomarker to predict the IVF/ICSI outcomes in PCOS patients.

Summary answer

PCOS patients got better IVF/ICSI outcomes with “higher” progesterone level (2.7-5.9mmol/L).

What is known already

There were several studies suggesting serum Progesterone (P) on the day of hCG trigger can be used as a biomarker to predict IVF outcomes, and to decide fresh cycle embryo transfer or frozen all. But there was few study focus on PCOS patients.

Study design, size, duration

This is a single-center retrospective cohort study in PCOS women undergoing the first transfer of an IVF cycle between January 1st 2010 and December 31th 2019. There were 141,539 oocyte retrieval cycles during the study period, and 97,189 cycles were their first IVF cycle. PCOS was diagnosed according to the Rotterdam criteria. Among them, 3,146 cycles full filled the inclusion and exclusion criteria, and all with two embryos transferred on Day 3.

Participants/materials, setting, methods

We compared the live birth rate of fresh embryo transfer, stratified for serum P level. We looked for interaction between serum P level and live birth rate of fresh cycles. The serum P level within normal range (&lt; 6nmol/L) on the day of hCG trigger day was divided into 4 quartiles. The four quartiles were defined as ≤ 1.35 nmol/L (Q1), &gt;1.35-1.93 nmol/L (Q2), &gt;1.93-2.7 nmol/L (Q3), &gt;2.7 nmol/L (Q4).

Main results and the role of chance

The baseline characteristics with no different between groups, except BMI. The patients in Q4 group with lowest BMI, significantly higher number of oocytes retrieved and live birth rate (P &lt; 0.05) . The Logistic regression analysis of the relative factors on live birth rate including BMI, basal LH and number of oocytes retrieved [P = 0.003, 0.030, 0.037 respectively, 95%CI (1.022, 1.111), (1.004, 1.076), (1.002, 1.082)].

Limitations, reasons for caution

Due to the retrospective nature of this study, a well-designed and matched large sample prospective study is needed. The definition of elevated P level and the method of hormonal assessments were different between studies, this limiting the comprehensive analysis of researches and the further verification of existing results.

Wider implications of the findings

PCOS patients who with normal range P level on hCG day, got better IVF/ICSI outcomes with “higher” progesterone level (2.7-5.9mmol/L). Weight control is important for PCOS patients accepting IVF treatment.

Trial registration number

NOT APPLICABLE

Modelling the dynamics of Trypanosoma rangeli and triatomine bug with logistic growth of vector and systemic transmission

In this paper, an insect-parasite-host model with logistic growth of triatomine bugs is formulated to study the transmission between hosts and vectors of the Chagas disease by using dynamical system approach. We derive the basic reproduction numbers for triatomine bugs and Trypanosoma rangeli as two thresholds. The local and global stability of the vector-free equilibrium, parasite-free equilibrium and parasite-positive equilibrium is investigated through the derived two thresholds. Forward bifurcation, saddle-node bifurcation and Hopf bifurcation are proved analytically and illustrated numerically. We show that the model can lose the stability of the vector-free equilibrium and exhibit a supercritical Hopf bifurcation, indicating the occurrence of a stable limit cycle. We also find it unlikely to have backward bifurcation and Bogdanov-Takens bifurcation of the parasite-positive equilibrium. However, the sustained oscillations of infected vector population suggest that Trypanosoma rangeli will persist in all the populations, posing a significant challenge for the prevention and control of Chagas disease.

The impact of vaccination on human papillomavirus infection with disassortative geographical mixing: a two-patch modeling study

Human papillomavirus (HPV) infection can spread between regions. What is the impact of disassortative geographical mixing on the dynamics of HPV transmission? Vaccination is effective in preventing HPV infection. How to allocate HPV vaccines between genders within each region and between regions to reduce the total infection? Here we develop a two-patch two-sex model to address these questions. The control reproduction number [Formula: see text] under vaccination is obtained and shown to provide a critical threshold for disease elimination. Both analytical and numerical results reveal that disassortative geographical mixing does not affect [Formula: see text] and only has a minor impact on the disease prevalence in the total population given the vaccine uptake proportional to the population size for each gender in the two patches. When the vaccine uptake is not proportional to the population size, sexual mixing between the two patches can reduce [Formula: see text] and mitigate the consequence of disproportionate vaccine coverage. Using parameters calibrated from the data of a case study, we find that if the two patches have the same or similar sex ratios, allocating vaccines proportionally according to the new recruits in two patches and giving priority to the gender with a smaller recruit rate within each patch will bring the maximum benefit in reducing the total prevalence. We also show that a time-variable vaccination strategy between the two patches can further reduce the disease prevalence. This study provides some quantitative information that may help to develop vaccine distribution strategies in multiple regions with disassortative mixing.

A two-sex model of human papillomavirus infection: Vaccination strategies and a case study

Vaccination is effective in preventing human papillomavirus (HPV) infection. It still remains debatable whether males should be included in a vaccination program and unclear how to allocate the vaccine in genders to achieve the maximum benefits. In this paper, we use a two-sex model to assess HPV vaccination strategies and use the data from Guangxi Province in China as a case study. Both mathematical analysis and numerical simulations show that the basic reproduction number, an important indicator of the transmission potential of the infection, achieves its minimum when the priority of vaccination is given to the gender with a smaller recruit rate. Given a fixed amount of vaccine, splitting the vaccine evenly usually leads to a larger basic reproduction number and a higher prevalence of infection. Vaccination becomes less effective in reducing the infection once the vaccine amount exceeds the smaller recruit rate of the two genders. In the case study, we estimate the basic reproduction number is 1.0333 for HPV 16/18 in people aged 15-55. The minimal bivalent HPV vaccine needed for the disease prevalence to be below 0.05% is 24050 per year, which should be given to females. However, with this vaccination strategy it would require a very long time and a large amount of vaccine to achieve the goal. In contrast with allocating the same vaccine amount every year, we find that a variable vaccination strategy with more vaccine given in the beginning followed by less vaccine in later years can save time and total vaccine amount. The variable vaccination strategy illustrated in this study can help to better distribute the vaccine to reduce the HPV prevalence. Although this work is for HPV infection and the case study is for a province in China, the model, analysis and conclusions may be applicable to other sexually transmitted diseases in other regions or countries.

Stochastic investigation of HIV infection and the emergence of drug resistance

Drug-resistant HIV-1 has caused a growing concern in clinic and public health. Although combination antiretroviral therapy can contribute massively to the suppression of viral loads in patients with HIV-1, it cannot lead to viral eradication. Continuing viral replication during sub-optimal therapy (due to poor adherence or other reasons) may lead to the accumulation of drug resistance mutations, resulting in an increased risk of disease progression. Many studies also suggest that events occurring during the early stage of HIV-1 infection (i.e., the first few hours to days following HIV exposure) may determine whether the infection can be successfully established. However, the numbers of infected cells and viruses during the early stage are extremely low and stochasticity may play a critical role in dictating the fate of infection. In this paper, we use stochastic models to investigate viral infection and the emergence of drug resistance of HIV-1. The stochastic model is formulated by a continuous-time Markov chain (CTMC), which is derived based on an ordinary differential equation model proposed by Kitayimbwa et al. that includes both forward and backward mutations. An analytic estimate of the probability of the clearance of HIV infection of the CTMC model near the infection-free equilibrium is obtained by a multitype branching process approximation. The analytical predictions are validated by numerical simulations. Unlike the deterministic dynamics where the basic reproduction number R₀ serves as a sharp threshold parameter (i.e., the disease dies out if R₀<1 and persists if R₀>1), the stochastic models indicate that there is always a positive probability for HIV infection to be eradicated in patients. In the presence of antiretroviral therapy, our results show that the chance of clearance of the infection tends to increase although drug resistance is likely to emerge.

The progression of secondary diabetes: A review of modeling studies

Mathematical modeling has provided quantitative information consistent with experimental data, greatly improving our understanding of the progression of type 1 and type 2 diabetes. However, diabetes is a complex metabolic disease and has been found to be involved in crosstalk interactions with diverse endocrine diseases. Mathematical models have also been developed to investigate the quantitative impact of various hormonal disorders on glucose imbalance, advancing the precision treatment for secondary diabetes. Here we review the models established for the study of dysglycemia induced by hormonal disorders, such as excessive glucocorticoids, epinephrine, and growth hormone. To investigate the influence of hyperthyroidism on the glucose regulatory system, we also propose a hyperthyroid-diabetes progression model. Model simulations indicate that timely thyroid treatment can halt the progression of hyperglycemia and prevent beta-cell failure. This highlights the diagnosis of hormonal disorders, together withblood sugar tests, as significant measures for the early diagnosis and treatment of diabetes. The work recapitulates updated biological research on the interactions between the glucose regulatory system and other endocrine axes. Further mathematical modeling of secondary diabetes is desired to promote the quantitative study of the disease and the development of individualized diabetic therapies.

Investigating the relationship between reopening the economy and implementing control measures during the COVID-19 pandemic

Objectives

The COVID-19 pandemic has resulted in an enormous burden on population health and the economy around the world. Although most cities in the United States have reopened their economies from previous lockdowns, it was not clear how the magnitude of different control measures—such as face mask use and social distancing—may affect the timing of reopening the economy for a local region. This study aimed to investigate the relationship between reopening dates and control measures and identify the conditions under which a city can be reopened safely.

Study design

This was a mathematical modeling study.

Methods

We developed a dynamic compartment model to capture the transmission dynamics of COVID-19 in New York City. We estimated model parameters from local COVID-19 data. We conducted three sets of policy simulations to investigate how different reopening dates and magnitudes of control measures would affect the COVID-19 epidemic.

Results

The model estimated that maintaining social contact at 80% of the prepandemic level and a 50% face mask usage would prevent a major surge of COVID-19 after reopening. If social distancing were completely relaxed after reopening, face mask usage would need to be maintained at nearly 80% to prevent a major surge.

Conclusions

Adherence to social distancing and increased face mask usage are keys to prevent a major surge after a city reopens its economy. The findings from our study can help policymakers identify the conditions under which a city can be reopened safely.

A delayed reaction–diffusion viral infection model with nonlinear incidences and cell-to-cell transmission

In this paper, we propose a reaction–diffusion viral infection model with nonlinear incidences, cell-to-cell transmission, and a time delay. We impose the homogeneous Neumann boundary condition. For the case where the domain is bounded, we first study the well-posedness. Then we analyze the local stability of homogeneous steady states. We establish a threshold dynamics which is completely characterized by the basic reproduction number. For the case where the domain is the whole Euclidean space, we consider the existence of traveling wave solutions by using the cross-iteration method and Schauder’s fixed point theorem. Finally, we study how the speed of spread in space affects the spread of cells and viruses. We obtain the existence of the wave speed, which is dependent on the diffusion coefficient.

A unified mathematical model of thyroid hormone regulation and implication for personalized treatment of thyroid disorders

Current clinician practice for thyroid hormone regulation of patients is based upon guesswork and experience rather than quantified analysis, which exposes patients under longer risk and discomfort. To quantitatively analyze the thyroid regulation for patients of different thyroid states, we develop a two-dimensional mathematical model that can be applied to analyze the dynamic behaviors of thyroid hormones with or without drug intervention. The unified model can be employed to study the regulation of TSH (thyroid-stimulating hormone) and FT4 (free thyroxine) for euthyroid (normal thyroid) subjects, Hashimoto's thyroiditis, and Graves' disease patients, respectively. The results suggest that the level of TPOAb (thyroid peroxidase antibody) may be a factor determining whether the patient would progress from euthyroid state to subclinical or clinical hypothyroidism, and that increased TRAb (TSH receptor antibody) may lead Graves' disease to deteriorate from the early stage to overt hyperthyroidism. Given the early blood-test data, we demonstrate the feasibility for healthcare professionals to apply our model in choosing an appropriate dosage regimen for patients to achieve the desired TSH and FT4 levels within a specified time frame. This proposed model has the potential to optimize personalized treatment and shorten the therapeutic time for patients suffering from Hashimoto's thyroiditis and Graves' disease.

The risk of future waves of COVID-19: modeling and data analysis

After a major outbreak of the coronavirus disease (COVID-19) starting in late December 2019, there were no new cases reported in mainland China for the first time on March 18, 2020, and no new cases reported in Hong Kong Special Administrative Region on April 20, 2020. However, these places had reported new cases and experienced a second wave since June 11, 2020. Here we develop a stochastic discrete-time epidemic model to evaluate the risk of COVID-19 resurgence by analyzing the data from the beginning of the outbreak to the second wave in these three places. In the model, we use an input parameter to represent a few potential risks that may cause a second wave, including asymptomatic infection, imported cases from other places, and virus from the environment such as frozen food packages. The effect of physical distancing restrictions imposed at different stages of the outbreak is also included in the model. Model simulations show that the magnitude of the input and the time between the initial entry and subsequent case confirmation significantly affect the probability of the second wave occurrence. Although the susceptible population size does not change the probability of resurgence, it can influence the severity of the outbreak when a second wave occurs. Therefore, to prevent the occurrence of a future wave, timely screening and detection are needed to identify infected cases in the early stage of infection. When infected cases appear, various measures such as contact tracing and quarantine should be followed to reduce the size of susceptible population in order to mitigate the COVID-19 outbreak.

Dynamics of a new HIV model with the activation status of infected cells

The activation status can dictate the fate of an HIV-infected CD4+ T cell. Infected cells with a low level of activation remain latent and do not produce virus, while cells with a higher level of activation are more productive and thus likely to transfer more virions to uninfected cells during cell-to-cell transmission. How the activation status of infected cells affects HIV dynamics under antiretroviral therapy remains unclear. We develop a new mathematical model that structures the population of infected cells continuously according to their activation status. The effectiveness of antiretroviral drugs in blocking cell-to-cell viral transmission decreases as the level of activation of infected cells increases because the more virions are transferred from infected to uninfected cells during cell-to-cell transmission, the less effectively the treatment is able to inhibit the transmission. The basic reproduction number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{0}$$\end{document}R0 of the model is shown to determine the existence and stability of the equilibria. Using the principal spectral theory and comparison principle, we show that the infection-free equilibrium is locally and globally asymptotically stable when \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{0}$$\end{document}R0 is less than one. By constructing Lyapunov functional, we prove that the infected equilibrium is globally asymptotically stable when \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{0}$$\end{document}R0 is greater than one. Numerical investigation shows that even when treatment can completely block cell-free virus infection, virus can still persist due to cell-to-cell transmission. The random switch between infected cells with different activation levels can also contribute to the replenishment of the latent reservoir, which is considered as a major barrier to viral eradication. This study provides a new modeling framework to study the observations, such as the low viral load persistence, extremely slow decay of latently infected cells and transient viral load measurements above the detection limit, in HIV-infected patients during suppressive antiretroviral therapy.

Projected COVID-19 epidemic in the United States in the context of the effectiveness of a potential vaccine and implications for social distancing and face mask use

BACKGROUND

Multiple candidates of COVID-19 vaccines have entered Phase III clinical trials in the United States (US). There is growing optimism that social distancing restrictions and face mask requirements could be eased with widespread vaccine adoption soon.

METHODS

We developed a dynamic compartmental model of COVID-19 transmission for the four most severely affected states (New York, Texas, Florida, and California). We evaluated the vaccine effectiveness and coverage required to suppress the COVID-19 epidemic in scenarios when social contact was to return to pre-pandemic levels and face mask use was reduced. Daily and cumulative COVID-19 infection and death cases from 26th January to 15th September 2020 were obtained from the Johns Hopkins University Coronavirus resource center and used for model calibration.

RESULTS

Without a vaccine (scenario 1), the spread of COVID-19 could be suppressed in these states by maintaining strict social distancing measures and face mask use levels. But relaxing social distancing restrictions to the pre-pandemic level without changing the current face mask use would lead to a new COVID-19 outbreak, resulting in 0.8-4 million infections and 15,000-240,000 deaths across these four states over the next 12 months. Under this circumstance, introducing a vaccine (scenario 2) would partially offset this negative impact even if the vaccine effectiveness and coverage are relatively low. However, if face mask use is reduced by 50% (scenario 3), a vaccine that is only 50% effective (weak vaccine) would require coverage of 55-94% to suppress the epidemic in these states. A vaccine that is 80% effective (moderate vaccine) would only require 32-57% coverage to suppress the epidemic. In contrast, if face mask usage stops completely (scenario 4), a weak vaccine would not suppress the epidemic, and further major outbreaks would occur. A moderate vaccine with coverage of 48-78% or a strong vaccine (100% effective) with coverage of 33-58% would be required to suppress the epidemic. Delaying vaccination rollout for 1-2 months would not substantially alter the epidemic trend if the current non-pharmaceutical interventions are maintained.

CONCLUSIONS

The degree to which the US population can relax social distancing restrictions and face mask use will depend greatly on the effectiveness and coverage of a potential COVID-19 vaccine if future epidemics are to be prevented. Only a highly effective vaccine will enable the US population to return to life as it was before the pandemic.

Effects of New York's Executive Order on Face Mask Use on COVID-19 Infections and Mortality: A Modeling Study

There is growing evidence on the effect of face mask use in controlling the spread of COVID-19. However, few studies have examined the effect of local face mask policies on the pandemic. In this study, we developed a dynamic compartmental model of COVID-19 transmission in New York City (NYC), which was the epicenter of the COVID-19 pandemic in the USA. We used data on daily and cumulative COVID-19 infections and deaths from the NYC Department of Health and Mental Hygiene to calibrate and validate our model. We then used the model to assess the effect of the executive order on face mask use on infections and deaths due to COVID-19 in NYC. Our results showed that the executive order on face mask use was estimated to avert 99,517 (95% CIs 72,723-126,312) COVID-19 infections and 7978 (5692-10,265) deaths in NYC. If the executive order was implemented 1 week earlier (on April 10), the averted infections and deaths would be 111,475 (81,593-141,356) and 9017 (6446-11,589), respectively. If the executive order was implemented 2 weeks earlier (on April 3 when the Centers for Disease Control and Prevention recommended face mask use), the averted infections and deaths would be 128,598 (94,373-162,824) and 10,515 (7540-13,489), respectively. Our study provides public health practitioners and policymakers with evidence on the importance of implementing face mask policies in local areas as early as possible to control the spread of COVID-19 and reduce mortality.

[Analysis of the self-conscious health status and influencing factors of greenhouse agricultural workers in Beijing suburb]

Objective: To explore the self-conscious health status and related influencing factors of greenhouse agricultural workers in Beijing suburb, so as to provide scientific basis for developing strategies to improve and promote the occupational health conditions of those workers. Methods: According to the production characteristics and scale of the main agricultural districts or counties in the suburb of Beijing, 182 agricultural production personnel were randomly selected to investigate the general situation, occupational situation and self-conscious health status during June 2018 to December 2019. The relevant factors which may affect the self-conscious health conditions were also analyzed by statistical methods. Results: The detection or reported rate of self-conscious health problems was 51.6% (94/182) , among which 29.1% (53/182) workers reported musculoskeletal disorder diseases and 21.4% (39/182) workers reported nervous system diseases. And the self-conscious health status of greenhouse agricultural workers were statistically different in household registration, gender, marital status, working years, mixing or spraying pesticides, smoking or eating in the greenhouse (P<0.05) . Moreover, gender, mixing or spraying pesticide, eating and smoking behavior in the workplace all had an impact on the risk of self-conscious health status of greenhouse agricultural workers (P< 0.05) . Specifically, male is the protective factor to reduce the occurrence of self-conscious symptoms of greenhouse agricultural workers (OR=0.447, 95%CI: 0.234~0.852) , while mixing or spraying pesticides and smoking or eating behaviors in the workplace are the risk factors (OR=1.055, 2.524; 95%CI: 0.503~2.210, 1.107~5.755) . Conclusion: Reducing pesticide use from the source thus minimize related exposure opportunities, strengthening occupational health education thus foster good hygienic habits and improve individual protection consciousness are of great significance for the health protection of greenhouse agricultural workers in Beijing suburb.

An economic and disease transmission model of human papillomavirus and oropharyngeal cancer in Texas

In 2017, 46,157 and 3,127 new oropharyngeal cancer (OPC) cases were reported in the U.S. and Texas, respectively. About 70% of OPC were attributed to human papillomavirus (HPV). However, only 51% of U.S. and 43.5% of Texas adolescents have completed the HPV vaccine series. Therefore, modeling the demographic dynamics and transmission of HPV and OPC progression is needed for accurate estimation of the economic and epidemiological impacts of HPV vaccine in a geographic area. An age-structured population dynamic model was developed for the U.S. state of Texas. With Texas-specific model parameters calibrated, this model described the dynamics of HPV-associated OPC in Texas. Parameters for the Year 2010 were used as the initial values, and the prediction for Year 2012 was compared with the real age-specific incidence rates in 23 age groups for model validation. The validated model was applied to predict 100-year age-adjusted incidence rates. The public health benefits of HPV vaccine uptake were evaluated by computer simulation. Compared with current vaccination program, increasing vaccine uptake rates by 50% would decrease the cumulative cases by 4403, within 100 years. The incremental cost-effectiveness ratio of this strategy was $94,518 per quality-adjusted life year (QALY) gained. Increasing the vaccine uptake rate by 50% can: (i) reduce the incidence rates of OPC among both males and females; (ii) improve the quality-adjusted life years for both males and females; (iii) be cost-effective and has the potential to provide tremendous public health benefits in Texas.

A Dynamic Model to Assess Human Papillomavirus Vaccination Strategies in a Heterosexual Population Combined with Men Who have Sex with Men

Vaccination is effective in preventing human papillomavirus (HPV) infection. It is imperative to investigate who should be vaccinated and what the best vaccine distribution strategy is. In this paper, we use a dynamic model to assess HPV vaccination strategies in a heterosexual population combined with gay, bisexual, and other men who have sex with men (MSM). The basic reproduction numbers for heterosexual females, heterosexual males and MSM as well as their average for the total population are obtained. We also derive a threshold parameter, based on basic reproduction numbers, for model analysis. From the analysis and numerical investigations, we have several conclusions. (1) To eliminate HPV infection, the priority of vaccination should be given to MSM, especially in countries that have already achieved high coverage in females. The heterosexual population gets great benefit but MSM only get minor benefit from vaccinating heterosexual females or males. (2) The best vaccination strategy is to vaccinate MSM firstly as many as possible, then heterosexual females, lastly heterosexual males. (3) Given a fixed vaccination coverage of MSM, distributing the remaining vaccines to only heterosexual females or males leads to a similar prevalence in the total population. This prevalence is lower than that when vaccines are distributed to both genders. The evener the distribution, the higher the prevalence in the total population. (4) Vaccination becomes less effective in reducing the prevalence as more vaccines are given. It is more effective to allocate vaccines to a region with lower vaccination coverage. This study provides information that may help policymakers formulate guidelines for vaccine distribution to reduce HPV prevalence on the basis of vaccine availability and prior vaccination coverage. Whether these guidelines are affected when the objective is to reduce HPV-associated cancer incidence remains to be further studied.

Endothelin-1 induces chondrocyte senescence and cartilage damage via endothelin receptor type B in a post-traumatic osteoarthritis mouse model

OBJECTIVES

This study aimed to investigate the role of endothelin-1 (ET-1), originally known as the potent vasoconstrictor, and its receptors in chondrocyte senescence and osteoarthritis (OA) development.

METHOD

Temporal changes of ET-1 and its receptors with OA development were characterized in a posttraumatic OA (PTOA) mouse model at time zero, 1-month and 4-month after surgical induction via destabilization of medial meniscus (DMM). A transgenic ET-1 overexpression (TET-1) mouse model was deployed to assess the impact of upregulated ET-1 on chondrocyte senescence and cartilage degradation. Effects of endothelin receptor blockade on chondrocyte senescence and OA development were further examined both in vitro and in vivo.

RESULTS

Local expression of ET-1 in subchondral bone and synovium upregulated after DMM with an increase of plasma ET-1 level from 3.18 ± 0.21 pg/ml at time zero to 6.47 ± 0.34 pg/ml at 4-month post-surgery. Meanwhile, endothelin type B receptor (ET_BR) (53.31 ± 2.42% to 83.8 ± 2.65%) and p16^INK4a (10.91 ± 1.07% to 28.2 ± 1.0%) positve chondrocytes accumulated in articular cartilage since 1-month prior to cartilage loss at 4-month post-surgery. Overexpressed ET-1 promoted p16^INK4a-positive senescent chondrocytes accumulation and cartilage degradation in TET-1 mice. Selective blockade of ET_BR, but not ET_AR, lowered the expression of p16^INK4a in ET-1 or H₂O₂-induced chondrocyte senescence model, and mitigated the severity of murine PTOA. Intriguingly, reactive oxygen species (ROS) scavenger, Vitamin C, could rescue ET-1-induced chondrocyte senescence in vitro associated with restoration of mitochondrial dynamics.

CONCLUSION

ET-1 could induce chondrocytes senescence and cartilage damages via ET_BR in PTOA.

Asymptotic analysis of a vector-borne disease model with the age of infection

Vector-borne infectious diseases may involve both horizontal transmission between hosts and transmission from infected vectors to susceptible hosts. In this paper, we incorporate these two transmission modes into a vector-borne disease model that includes general nonlinear incidence rates and the age of infection for both hosts and vectors. We show the existence, uniqueness, nonnegativity, and boundedness of solutions for the model. We study the existence and local stability of steady states, which is shown to be determined by the basic reproduction number. By showing the existence of a global compact attractor and uniform persistence of the system, we establish the threshold dynamics using the Fluctuation Lemma and the approach of Lyapunov functionals. When the basic reproduction number is less than one, the disease-free steady state is globally asymptotically stable and otherwise the disease will be established when there is initial infection force for the hosts. We also study a model with the standard incidence rate and discuss the effect of different incidence rates on the disease dynamics.

Modeling the viral dynamics of SARS-CoV-2 infection

Coronavirus disease 2019 (COVID-19), an infectious disease caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading and causing the global coronavirus pandemic. The viral dynamics of SARS-CoV-2 infection have not been quantitatively investigated. In this paper, we use mathematical models to study the pathogenic features of SARS-CoV-2 infection by examining the interaction between the virus, cells and immune responses. Models are fit to the data of SARS-CoV-2 infection in patients and non-human primates. Data fitting and numerical simulation show that viral dynamics of SARS-CoV-2 infection have a few distinct stages. In the initial stage, viral load increases rapidly and reaches the peak, followed by a plateau phase possibly generated by lymphocytes as a secondary target of infection. In the last stage, viral load declines due to the emergence of adaptive immune responses. When the initiation of seroconversion is late or slow, the model predicts viral rebound and prolonged viral persistence, consistent with the observation in non-human primates. Using the model we also evaluate the effect of several potential therapeutic interventions for SARS-CoV-2 infection. Model simulation shows that anti-inflammatory treatments or antiviral drugs combined with interferon are effective in reducing the duration of the viral plateau phase and diminishing the time to recovery. These results provide insights for understanding the infection dynamics and might help develop treatment strategies against COVID-19.

Modeling HIV multiple infection

Multiple infection of target cells by human immunodeficiency virus (HIV) may lead to viral escape from host immune responses and drug resistance to antiretroviral therapy, bringing more challenges to the control of infection. The mechanisms underlying HIV multiple infection and their relative contributions are not fully understood. In this paper, we develop and analyze a mathematical model that includes sequential cell-free virus infection (i.e.one virus is transmitted each time in a sequential infection of target cells by virus) and cell-to-cell transmission (i.e.multiple viral genomes are transmitted simultaneously from infected to uninfected cells). By comparing model prediction with the distribution data of proviral genomes in HIV-infected spleen cells, we find that multiple infection can be well explained when the two modes of viral transmission are both included. Numerical simulation using the parameter estimates from data fitting shows that the majority of T cell infections are attributed to cell-to-cell transmission and this transmission mode also accounts for more than half of cell's multiple infections. These results suggest that cell-to-cell transmission plays a critical role in forming HIV multiple infection and thus has important implications for HIV evolution and pathogenesis.

Assessing the effects of metropolitan-wide quarantine on the spread of COVID-19 in public space and households

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A new dynamic compartmental model involving two modes of transmission (public space and households) is proposed to evaluate the impact of the metropolitan-wide quarantine on the trend and transmission pattern of the COVID-19 epidemic in Hubei, China.

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The quarantine reduces more than 70% of new infections in both households and the public space, as well as the deaths caused by COVID-19 pneumonia. Household transmission is the dominant route of disease spread regardless of quarantine.

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The results will provide important evidence and scientific insights to other worldwide countries that are currently under quarantine.

Hubei province in China has completed cycle of quarantine-resumption in 23rd Janauary and 8th April 2020, providing a unique opportunity as for now to assess its intervention impact and the pattern of SARS-COV-2 transmission during the quarantine period. In this study, we evaluate the impact of the metropolitan-wide quarantine on the trend and transmission route of the COVID-19 epidemic in Hubei, China. The intervention reduces more than 70% of new infections in both households and the public space, as well as the deaths caused by COVID-19 pneumonia. Household transmission is the dominant route of disease spread regardless of quarantine. This will provide important evidence and scientific insights to other worldwide countries that are currently under quarantine.

A discrete stochastic model of the COVID-19 outbreak: Forecast and control

The novel Coronavirus (COVID-19) is spreading and has caused a large-scale infection in China since December 2019. This has led to a significant impact on the lives and economy in China and other countries. Here we develop a discrete-time stochastic epidemic model with binomial distributions to study the transmission of the disease. Model parameters are estimated on the basis of fitting to newly reported data from January 11 to February 13, 2020 in China. The estimates of the contact rate and the effective reproductive number support the efficiency of the control measures that have been implemented so far. Simulations show the newly confirmed cases will continue to decline and the total confirmed cases will reach the peak around the end of February of 2020 under the current control measures. The impact of the timing of returning to work is also evaluated on the disease transmission given different strength of protection and control measures.

[Clinical short-term and long-term efficacy of endoscopic submucosal dissection in the treatment of early low rectal cancer and precancerous lesions]

Objective: To evaluate the short-term and long-term efficacy of endoscopic submucosal dissection (ESD) in the treatment of early low rectal cancer and precancerous lesions. Methods: Inclusion criteria: (1) Distance from the lower margin of tumor to the anal was ≤ 5 cm. (2) Early low rectal cancers were any size rectal epithelial tumors with infiltration depth limited to the mucosa and submucosa, which were diagnosed by postoperative pathology as high-grade intraepithelial neoplasia or adenocarcinoma of the rectum with infiltration depth of intramucosal or submucosal cancer (M or SM stage). (3) Precancerous lesions included adenoma and low-grade intraepithelial neoplasia of the rectum. (4) Patients received ESD treatment. Patients with tumor invasion depth over submucosa by pathology were excluded. From January 2008 to January 2018, 63 patients meeting the above criteria in Peking University First Hospital were enrolled in this descriptive cohort study. The disease characteristics, clinical manifestations, pathological types, treatment time, hospitalization time, en bloc resection rate (resection of the whole lesion), complete resection rate (both the horizontal and vertical incision margins were negative), postoperative complications and follow-up results were analyzed. Cummulative survival rate was calculated by Kaplan-Meier. Results: The diameter of the lesion was (29.0±23.4) mm and the distance from the lesion to the anus was (2.7±1.8) cm. The median operation time was 45.0 (range, 10.0 to 360.0) minutes, the median hospitalization time was 3.0 (range, 2.0 to 12.0) days, en bloc resection rate was 100%, complete resection rate was 96.8% (61/63), and 1 case (1.6%) had postoperative bleeding. The follow-up rate was 87.3% (55/63) and the median follow-up time was 57.9 (range, 15.6 to 121.1) months. No local recurrence was found during the follow-up period and the 5-year survival rate was 100%. Conclusion: Short- and long-term efficacy of ESD are quite good in the treatment of patients with early low rectal cancer and precancerous lesions.

Conflict and accord of optimal treatment strategies for HIV infection within and between hosts

Most of previous studies investigated the optimal control of HIV infection at either within-host or between-host level. However, the optimal treatment strategy for the individual may not be optimal for the population and vice versa. To determine when the two-level optimal controls are in accord or conflict, we develop a multi-scale model using various functions that link the viral load within host and the transmission rate between hosts, calibrated by cohort data. We obtain the within-host optimal treatment scheme that minimizes the viral load and maximizes the count of healthy cells at the individual level, and the coupled optimal scheme that minimizes the basic reproduction number at the population level. Mathematical analysis shows that whether the two-level optimal controls coincide depends on the sign of the product of their switching functions. Numerical results suggest that they are in accord for a high maximal drug efficacy but may conflict for a low drug efficacy. Using the multi-scale model, we also identify a threshold of the treatment effectiveness that determines how early treatment initiation can affect the disease dynamics among population. These results may help develop a synergistic treatment protocol beneficial to both HIV-infected individuals and the whole population.

Optimal control in HIV chemotherapy with termination viral load and latent reservoir

Although a number of cost-e ective strategies have been proposed for the chemotherapy of HIV infection, the termination level of viral load and latent reservoir is barely considered. However, the viral load at the termination time is an important biomarker because suppressing viral load to below the detection limit is a major objective of current antiretroviral therapy. The pool size of latently infected cells at the termination time may also play a critical role in predicting a rapid viral rebound to the pretreatment level or post-treatment control. In this work, we formulate an optimal control problem by incorporating the termination level in terms of viral load, latently and productively infected T cells into an existing HIV model. The necessary condition for this optimal system is derived using the Pontryagin's maximum principle. Numerical analysis is carried out using Runge-Kutta 4 method for the forward-backward sweep. Our results suggest that introducing the termination viral load into the control provides a better strategy in HIV chemotherapy.

The cost-effectiveness of oral HIV pre-exposure prophylaxis and early antiretroviral therapy in the presence of drug resistance among men who have sex with men in San Francisco

BACKGROUND

Poor adherence to either antiretroviral treatment (ART) or pre-exposure prophylaxis (PrEP) can promote drug resistance, though this risk is thought to be considerably higher for ART. In the population of men who have sex with men (MSM) in San Francisco, PrEP coverage reached 9.6% in 2014 and has continued to rise. Given the risk of drug resistance and high cost of second-line drugs, the costs and benefits of initiating ART earlier while expanding PrEP coverage remain unclear.

METHODS

We develop an infection-age-structured mathematical model and fit this model to the annual incidence of AIDS cases and deaths directly, and to resistance and demographic data indirectly. We investigate the impact of six various intervention scenarios (low, medium, or high PrEP coverage, with or without earlier ART) over the next 20 years.

RESULTS

Low (medium, high) PrEP coverage with earlier ART could prevent 22% (42%, 57%) of a projected 44,508 total new infections and 8% (26%, 41%) of a projected 18,426 new drug-resistant infections, and result in a gain of 43,649 (74,048, 103,270) QALYs over 20 years compared to the status quo, at a cost of $4745 ($78,811, $115,320) per QALY gained, respectively.

CONCLUSIONS

High PrEP coverage with earlier ART is expected to provide the greatest benefit but also entail the highest costs among the strategies considered. This strategy is cost-effective for the San Francisco MSM population, even considering the acquisition and transmission of ART-mediated drug resistance. However, without a substantial increase to San Francisco's annual HIV budget, the most advisable strategy may be initiating ART earlier, while maintaining current strategies of PrEP enrollment.

Protease sensitivity and redistribution of CD71 and glycophorin A on K562 cells

Transmembrane proteins are delivered to plasma membrane from the endoplasmic reticulum and Golgi complex by vesicular transport along with the cytoskeletal network. Disruption of this process likely affects transmembrane protein expression. K562 cells were digested with Streptomyces griseus protease for different periods of time, and then re-cultured with different cytoskeletal and glycosylation inhibitors. Cell viability and surface expression of transferrin receptor (CD71) and glycophorin A (GPA) were analyzed before and after re-culture by flow cytometry. We found that digestion with protease almost completely removed extracellular CD71 and GPA but their expression recovered to the initial levels after re-culture for 8 h and 24 h, respectively. The microtubule depolymerizer colchicine promoted cell surface recovery of CD71 but inhibited that of GPA; the microtubule stabilizer paclitaxel inhibited cell surface recovery of CD71 but promoted that of GPA; the microfilament depolymerizer cytochalasin D had no effect on cell surface recovery of CD71 and GPA; the microfilament stabilizer phalloidin inhibited cell surface recovery of GPA. The glycosylation inhibitor tunicamycin inhibited the recovery of both CD71 and GPA, and BADGP inhibited the recovery of GPA. These studies show differential sensitivities of surface proteins on K562 cells to proteases, and suggest molecular mechanisms of transmembrane protein transport and cycling.

Mathematical analysis of an HIV latent infection model including both virus-to-cell infection and cell-to-cell transmission

HIV can infect cells via virus-to-cell infection or cell-to-cell viral transmission. These two infection modes may occur in a synergistic way and facilitate viral spread within an infected individual. In this paper, we developed an HIV latent infection model including both modes of transmission and time delays between viral entry and integration or viral production. We analysed the model by defining the basic reproductive number, showing the existence, positivity and boundedness of the solution, and proving the local and global stability of the infection-free and infected steady states. Numerical simulations have been performed to illustrate the theoretical results and evaluate the effects of time delays and fractions of infection leading to latency on the virus dynamics. The estimates of the relative contributions to the HIV latent reservoir and the virus population from the two modes of transmission have also been provided.

Early antiretroviral therapy and potent second-line drugs could decrease HIV incidence of drug resistance

Early initiation of antiretroviral therapy (ART) reduces the risk of drug-sensitive HIV transmission but may increase the transmission of drug-resistant HIV. We used a mathematical model to estimate the long-term population-level benefits of ART and determine the scenarios under which earlier ART (treatment at 1 year post-infection, on average) could decrease simultaneously both total and drug-resistant HIV incidence (new infections). We constructed an infection-age-structured mathematical model that tracked the transmission rates over the course of infection and modelled the patients' life expectancy as a function of ART initiation timing. We fitted this model to the annual AIDS incidence and death data directly, and to resistance data and demographic data indirectly among men who have sex with men (MSM) in San Francisco. Using counterfactual scenarios, we assessed the impact on total and drug-resistant HIV incidence of ART initiation timing, frequency of acquired drug resistance, and second-line drug effectiveness (defined as the combination of resistance monitoring, biomedical drug efficacy and adherence). Earlier ART initiation could decrease the number of both total and drug-resistant HIV incidence when second-line drug effectiveness is sufficiently high (greater than 80%), but increase the proportion of new infections that are drug resistant. Thus, resistance may paradoxically appear to be increasing while actually decreasing.

A note on the global properties of an age-structured viral dynamic model with multiple target cell populations

Some viruses can infect different classes of cells. The age of infection can affect the dynamics of infected cells and viral production. Here we develop a viral dynamic model with the age of infection and multiple target cell populations. Using the methods of semigroup and Lyapunov function, we study the global asymptotic property of the steady states of the model. The results show that when the basic reproductive number falls below 1, the infection is predicted to die out. When the basic reproductive number exceeds 1, there exists a unique infected steady state which is globally asymptotically stable. The model can be extended to study virus dynamics with multiple compartments or coinfection by multiple types of viruses. We also show that under some scenarios the age-structured model can be reduced to an ordinary differential equation system with or without time delays.

Answers to if the Lead Aprons are Really Helpful in Nuclear Medicine from the Perspective of Spectroscopy

Wearing lead X-ray-protective aprons is a routine in nuclear medicine department in parts of China. However, the staff are often perplexed by questions such as if it is imperative to wear aprons when injecting radioactive drugs, how much radiation dosage can be shielded and if the apron will produce secondary radiation instead? To answer these questions, a semiconductor detector was employed to record different gamma and X-ray spectra with and without the lead apron or lead sheet. Then, we could estimate the signal shielding ratio to different photons for the lead apron and compare with the hospitals measured data. In general, the two results coincided well. The spectral results showed that the detrimental secondary X-rays irradiation rises when the energy of gamma rays exceeds the K absorption edge of lead (88 keV). Moreover, the aprons are not so effective for gamma rays of 364 keV emitted from 131I and 511 keV emitted from the positron radioactive nuclides. This work is purely a physical measurement in the laboratory. To the best of our knowledge, this is the first quantitative study on the level of gamma rays protection offered by the medical lead aprons and the importance of the spectroscopic measurements is discussed in this paper.

An HIV model with age-structured latently infected cells

HIV latency remains a major obstacle to viral elimination. The activation rate of latently infected cells may depend on the age of latent infection. In this paper, we develop a model of HIV infection including age-structured latently infected cells. We mathematically analyse the model and use numerical simulations with different activation functions to show that the model can explain the persistence of low-level viremia and the latent reservoir stability in patients on therapy. Sensitivity tests suggest that the model is robust to the changes of most parameters but is sensitive to the relative magnitude of the net generation rate and the long-term activation rate of latently infected cells. To reduce the sensitivity, we extend the model to include homeostatic proliferation of latently infected cells. The new model is robust in reproducing the long-term dynamics of the virus and latently infected cells observed in patients receiving prolonged combination therapy.

Analysis of HIV models with two time delays

Time delays can affect the dynamics of HIV infection predicted by mathematical models. In this paper, we studied two mathematical models each with two time delays. In the first model with HIV latency, one delay is the time between viral entry into a cell and the establishment of HIV latency, and the other delay is the time between cell infection and viral production. We defined the basic reproductive number and showed the local and global stability of the steady states. Numerical simulations were performed to evaluate the influence of time delays on the dynamics. In the second model with HIV immune response, one delay is the time between cell infection and viral production, and the other delay is the time needed for the adaptive immune response to emerge to control viral replication. With two positive delays, we obtained the stability crossing curves for the model, which were shown to be a series of open-ended curves.

Influence of raltegravir intensification on viral load and 2-LTR dynamics in HIV patients on suppressive antiretroviral therapy

Antiretroviral therapy can suppress HIV-1 plasma viral load to below the detection limit but cannot eradicate the virus. Whether residual ongoing viral replication persists during suppressive therapy remains unclear. A few clinical studies showed that treatment intensification with an additional drug led to a lower viral load or an increase in 2-LTR (long terminal repeat), a marker for ongoing viral replication. However, some other studies found no change in the viral load and 2-LTR. In this paper, we developed multi-stage models to evaluate the influence of treatment intensification with the integrase inhibitor raltegravir on viral load and 2-LTR dynamics in HIV patients under suppressive therapy. We analyzed one model and obtained the local and global stability of the steady states. The model and its variation predict that raltegravir intensification induces a very minor decrease in the viral load and a minor increase in 2-LTR. We also compared modeling prediction with the 2-LTR data in a raltegravir intensification study. To achieve the 2-LTR increase observed in some patients, the level of viral replication needs to be substantially high, which is inconsistent with the sustained viral suppression in patients during treatment intensification. These modeling results, together with the theoretical estimate of the upper bound of the 2-LTR increase, suggest that treatment intensification with raltegravir has a minor effect on the plasma viremia and 2-LTR in patients under suppressive therapy. Other treatment strategies have to be developed for the cure or functional control of the infection.

Sirt 1 activator attenuates the bleomycin-induced lung fibrosis in mice via inhibiting epithelial-to-mesenchymal transition (EMT)

OBJECTIVE

The aim of this study was to investigate the effect of resveratrol on the idiopathic bleomycin (BLM)-induced pulmonary fibrosis, which is increasingly recognized as an epithelial-to-mesenchymal transition (EMT)-associated disease.

MATERIALS AND METHODS

We evaluated the effect of resveratrol on the BLM-induced fibrosis in a mouse model, via monitoring the pathological chance in mice lung, the mice body weight change and the mice death. And we also explored the regulation by BLM on (and) resveratrol on the expression and activity of Sirt 1 and on the expression of epithelial-to-mesenchymal transition (EMT)-associated markers in mice lung.

RESULTS

It was demonstrated that resveratrol ameliorated the BLM-induced fibrosis-like pathological change in mice lung, inhibited BLM-induced mice body weight loss and death. Moreover, resveratrol also inhibited the BLM-induced EMT-associated molecular events, such as reduced E-cadherin and elevated Collagen I and α-SMA. We also confirmed the amelioration by resveratrol on the BLM-mediated inhibition of Sirt 1 in expression and activity in mice lung.

CONCLUSIONS

Our study confirmed the inhibitory role of resveratrol in the BLM-induced pulmonary fibrosis in a mouse model. Resveratrol ameliorated the BLM-induced pathological change of fibrosis, mice body weight loss and death. And such amelioration might be associated with the activation of Sirt 1 in mice lung. The present study implied that resveratrol might be a promising agent for effective control the pulmonary fibrosis.

Dynamics of an HIV Model with Multiple Infection Stages and Treatment with Different Drug Classes

Highly active antiretroviral therapy can effectively control HIV replication in infected individuals. Some clinical and modeling studies suggested that viral decay dynamics may depend on the inhibited stages of the viral replication cycle. In this paper, we develop a general mathematical model incorporating multiple infection stages and various drug classes that can interfere with specific stages of the viral life cycle. We derive the basic reproductive number and obtain the global stability results of steady states. Using several simple cases of the general model, we study the effect of various drug classes on the dynamics of HIV decay. When drugs are assumed to be 100% effective, drugs acting later in the viral life cycle lead to a faster or more rapid decay in viremia. This is consistent with some patient and experimental data, and also agrees with previous modeling results. When drugs are not 100% effective, the viral decay dynamics are more complicated. Without a second population of long-lived infected cells, the viral load decline can have two phases if drugs act at an intermediate stage of the viral replication cycle. The slopes of viral load decline depend on the drug effectiveness, the death rate of infected cells at different stages, and the transition rate of infected cells from one to the next stage. With a second population of long-lived infected cells, the viral load decline can have three distinct phases, consistent with the observation in patients receiving antiretroviral therapy containing the integrase inhibitor raltegravir. We also fit modeling prediction to patient data under efavirenz (a nonnucleoside reverse-transcriptase inhibitor) and raltegravir treatment. The first-phase viral load decline under raltegravir therapy is longer than that under efavirenz, resulting in a lower viral load at initiation of the second-phase decline in patients taking raltegravir. This explains why patients taking a raltegravir-based therapy were faster to achieve viral suppression than those taking an efavirenz-based therapy. Taken together, this work provides a quantitative and systematic comparison of the effect of different drug classes on HIV decay dynamics and can explain the viral load decline in HIV patients treated with raltegravir-containing regimens.