EXACT PHYLODYNAMIC LIKELIHOOD VIA STRUCTURED MARKOV GENEALOGY PROCESSES.

We consider genealogies arising from a Markov population process in which individuals are categorized into a discrete collection of compartments, with the requirement that individuals within the same compartment are statistically exchangeable. When equipped with a sampling process, each such population process induces a time-evolving tree-valued process defined as the genealogy of all sampled individuals. We provide a construction of this genealogy process and derive exact expressions for the likelihood of an observed genealogy in terms of filter equations. These filter equations can be numerically solved using standard Monte Carlo integration methods. Thus, we obtain statistically efficient likelihood-based inference for essentially arbitrary compartment models based on an observed genealogy of individuals sampled from the population.

The Number and Pattern of Viral Genomic Reassortments are not Necessarily Identifiable from Segment Trees.

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to novel progeny formed from the mixture of parental segments. Since large-scale genome rearrangements have the potential to generate new phenotypes, reassortment is important to both evolutionary biology and public health research. However, statistical inference of the pattern of reassortment events from phylogenetic data is exceptionally difficult, potentially involving inference of general graphs in which individual segment trees are embedded. In this paper, we argue that, in general, the number and pattern of reassortment events are not identifiable from segment trees alone, even with theoretically ideal data. We call this fact the fundamental problem of reassortment, which we illustrate using the concept of the "first-infection tree," a potentially counterfactual genealogy that would have been observed in the segment trees had no reassortment occurred. Further, we illustrate four additional problems that can arise logically in the inference of reassortment events and show, using simulated data, that these problems are not rare and can potentially distort our observation of reassortment even in small data sets. Finally, we discuss how existing methods can be augmented or adapted to account for not only the fundamental problem of reassortment, but also the four additional situations that can complicate the inference of reassortment.

A story of viral co-infection, co-transmission and co-feeding in ticks: how to compute an invasion reproduction number.

With a single circulating vector-borne virus, the basic reproduction number incorporates contributions from tick-to-tick (co-feeding), tick-to-host and host-to-tick transmission routes. With two different circulating vector-borne viral strains, resident and invasive, and under the assumption that co-feeding is the only transmission route in a tick population, the invasion reproduction number depends on whether the model system of ordinary differential equations possesses the property of neutrality. We show that a simple model, with two populations of ticks infected with one strain, resident or invasive, and one population of co-infected ticks, does not have Alizon's neutrality property. We present model alternatives that are capable of representing the invasion potential of a novel strain by including populations of ticks dually infected with the same strain. The invasion reproduction number is analysed with the next-generation method and via numerical simulations.

Surface-modified titanium and titanium-based alloys for improved osteogenesis: A critical review.

As implantable materials, titanium, and its alloys have garnered enormous interest from researchers for dental and orthopedic procedures. Despite their success in wide clinical applications, titanium, and its alloys fail to stimulate osteogenesis, resulting in poor bonding strength with surrounding bone tissue. Optimizing the surface topology and altered compositions of titanium and titanium-based alloys substantially promotes peri-implant bone regeneration. This review summarizes the utilization and importance of various osteogenesis components loaded onto titanium and its alloys. Further, different surface-modification methods and the release efficacy of loaded substances are emphasized. Finally, we summarize the article with prospects. We believe that further investigation studies must focus on identifying novel loading components, exploring various innovative, optimized surface-modification methods, and developing a sustained-release system on implant surfaces to improve peri-implant bone formation.

Tunable Band Engineering Management on Perovskite MAPbBr3 /COFs Nano-Heterostructures for Efficient S-S Coupling Reactions.

Efficient artificial photosynthesis of disulfide bonds holds promises to facilitate reverse decoding of genetic codes and deciphering the secrets of protein multilevel folding, as well as the development of life science and advanced functional materials. However, the incumbent synthesis strategies encounter separation challenges arising from leaving groups in the ─S─S─ coupling reaction. In this study, according to the reaction mechanism of free-radical-triggered ─S─S─ coupling, light-driven heterojunction functional photocatalysts are tailored and constructed, enabling them to efficiently generate free radicals and trigger the coupling reaction. Specifically, perovskites and covalent organic frameworks (COFs) are screened out as target materials due to their superior light-harvesting and photoelectronic properties, as well as flexible and tunable band structure. The in situ assembled Z-scheme heterojunction MAPB-M-COF (MAPbBr3 = MAPB, MA+ = CH3 NH2 + ) demonstrates a perfect trade-off between quantum efficiency and redox chemical potential via band engineering management. The MAPB-M-COF achieves a 100% ─S─S─ coupling yield with a record photoquantum efficiency of 11.50% and outstanding cycling stability, rivaling all the incumbent similar reaction systems. It highlights the effectiveness and superiority of application-oriented band engineering management in designing efficient multifunctional photocatalysts. This study demonstrates a concept-to-proof research methodology for the development of various integrated heterojunction semiconductors for light-driven chemical reaction and energy conversion.

Modeling the evolution of segment trees reveals deficiencies in current inferential methods for genomic reassortment.

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to new viral variants. Large-scale genome rearrangements, such as reassortment, have the potential to quickly generate new phenotypes, making the understanding of viral reassortment important to both evolutionary biology and public health research. In this paper, we argue that reassortment cannot be reliably inferred from incongruities between segment phylogenies using the established remove-and-rejoin or coalescent approaches. We instead show that reassortment must be considered in the context of a broader population process that includes the dynamics of the infected hosts. Using illustrative examples and simulation we identify four types of evolutionary events that are difficult or impossible to reconstruct with incongruence-based methods. Further, we show that these specific situations are very common and will likely occur even in small samples. Finally, we argue that existing methods can be augmented or modified to account for all the problematic situations that we identify in this paper. Robust assessment of the role of reassortment in viral evolution is difficult, and we hope to provide conceptual clarity on some important methodological issues that can arise in the development of the next generation of tools for studying reassortment.

Seeing through noise in power laws.

Despite widespread claims of power laws across the natural and social sciences, evidence in data is often equivocal. Modern data and statistical methods reject even classic power laws such as Pareto's law of wealth and the Gutenberg-Richter law for earthquake magnitudes. We show that the maximum-likelihood estimators and Kolmogorov-Smirnov (K-S) statistics in widespread use are unexpectedly sensitive to ubiquitous errors in data such as measurement noise, quantization noise, heaping and censorship of small values. This sensitivity causes spurious rejection of power laws and biases parameter estimates even in arbitrarily large samples, which explains inconsistencies between theory and data. We show that logarithmic binning by powers of λ > 1 attenuates these errors in a manner analogous to noise averaging in normal statistics and that λ thereby tunes a trade-off between accuracy and precision in estimation. Binning also removes potentially misleading within-scale information while preserving information about the shape of a distribution over powers of λ, and we show that some amount of binning can improve sensitivity and specificity of K-S tests without any cost, while more extreme binning tunes a trade-off between sensitivity and specificity. We therefore advocate logarithmic binning as a simple essential step in power-law inference.

Swift and extensive Omicron outbreak in China after sudden exit from 'zero-COVID' policy.

In late 2022, China transitioned from a strict 'zero-COVID' policy to rapidly abandoning nearly all interventions and data reporting. This raised great concern about the presumably-rapid but unreported spread of the SARS-CoV-2 Omicron variant in a very large population of very low pre-existing immunity. By modeling a combination of case count and survey data, we show that Omicron spread extremely rapidly, at a rate of 0.42/day (95% credibility interval: [0.35, 0.51]/day), translating to an epidemic doubling time of 1.6 days ([1.6, 2.0] days) after the full exit from zero-COVID on Dec. 7, 2022. Consequently, we estimate that the vast majority of the population (97% [95%, 99%], sensitivity analysis lower limit of 90%) was infected during December, with the nation-wide epidemic peaking on Dec. 23. Overall, our results highlight the extremely high transmissibility of the variant and the importance of proper design of intervention exit strategies to avoid large infection waves.

Topical Chinese herbal medicine in treating atopic dermatitis (eczema): A systematic review and meta-analysis with core herbs exploration.

ETHNOPHARMACOLOGICAL RELEVANCE: Topical Chinese herbal medicine (CHM) is commonly used to relieve atopic dermatitis (AD); however, the up-to-date evidence concerning the effectiveness of topical CHM on treating AD is lacking. Moreover, the CHM prescriptions are often too complicated to realize the overall mechanisms of CHM, especially when compared to western medicines (WM). AIM OF THE STUDY: To evaluate the effectiveness of topical CHM for treating AD by conducting a meta-analysis on randomized clinical trials (RCTs). METHODS: Twenty RCTs comparing topical CHM to active control/placebo were included in the final analysis. The primary outcome was the symptom scores changed from baseline and the effectiveness rate was the secondary outcome. Subgroup analysis on different initial symptom severity and the different interventions in control groups was performed. System pharmacology analysis was performed to explore core CHM and possible pharmacological mechanisms of CHM for AD. RESULTS: Compared with active/blank placebo, topical CHM seemed more effective (SMD: -0.35, 95 %CI: -0.59 to -0.10, p-value = 0.005, I2 = 60%). The effectiveness rate was higher (RR: 1.29, 95 %CI 1.15-1.44, p-value <0.00001, I2 = 71%). In subgroup analysis, mild and moderate AD patients with topical CHM were more effective than placebo (SMD: -0.28, 95 %CI -0.56 to -0.01, p-value = 0.04, I2 = 5%; -0.34, 95%CI -0.64 to -0.03, p-value = 0.03, I2 = 0%, separately). Topical CHM has 1.25 times more effective than the topical glucocorticoid (95 %CI 1.09-1.43, p-value = 0.001, I2 = 64%). Core CHMs, such as Phellodendron chinense C.K. Schneid., Sophora flavescens Ait., Cnidium monnieri (L.) Cusson, and Dictamnus dasycarpus Turcz., had effects on the pathways on immune and metabolism systems different from WM. CONCLUSION: Our results exploit the potential role of CHM on treating AD, especially for mild and moderate AD.

In situ continuous Dopa supply by responsive artificial enzyme for the treatment of Parkinson's disease.

Oral dihydroxyphenylalanine (Dopa) administration to replenish neuronal dopamine remains the most effective treatment for Parkinson's disease (PD). However, unlike the continuous and steady dopamine signaling in normal neurons, oral Dopa induces dramatic fluctuations in plasma Dopa levels, leading to Dopa-induced dyskinesia. Herein, we report a functional nucleic acid-based responsive artificial enzyme (FNA-Fe3O4) for in situ continuous Dopa production. FNA-Fe3O4 can cross the blood-brain barrier and target diseased neurons relying on transferrin receptor aptamer. Then, FNA-Fe3O4 responds to overexpressed α-synuclein mRNA in diseased neurons for antisense oligonucleotide treatment and fluorescence imaging, while converting to tyrosine aptamer-based artificial enzyme (Apt-Fe3O4) that mimics tyrosine hydroxylase for in situ continuous Dopa production. In vivo FNA-Fe3O4 treatment results in recovery of Dopa and dopamine levels and decrease of pathological overexpressed α-synuclein in PD mice model, thus ameliorating motor symptoms and memory deficits. The presented functional nucleic acid-based responsive artificial enzyme strategy provides a more neuron friendly approach for the diagnosis and treatment of PD.

Changing Epidemiology of TB in Shandong, China Driven by Demographic Changes.

Tuberculosis (TB) incidence has been in steady decline in China over the last few decades. However, ongoing demographic transition, fueled by aging, and massive internal migration could have important implications for TB control in the future. We collated data on TB notification, demography, and drug resistance between 2004 and 2017 across seven cities in Shandong, the second most populous province in China. Using these data, and age-period-cohort models, we (i) quantified heterogeneities in TB incidence across cities, by age, sex, resident status, and occupation and (ii) projected future trends in TB incidence, including drug-resistant TB (DR-TB). Between 2006 and 2017, we observed (i) substantial variability in the rates of annual change in TB incidence across cities, from -4.84 to 1.52%; (ii) heterogeneities in the increments in the proportion of patients over 60 among reported TB cases differs from 2 to 13%, and from 0 to 17% for women; (iii) huge differences across cities in the annual growths in TB notification rates among migrant population between 2007 and 2017, from 2.81 cases per 100K migrants per year in Jinan to 22.11 cases per 100K migrants per year in Liaocheng, with drastically increasing burden of TB cases from farmers; and (iv) moderate and stable increase in the notification rates of DR-TB in the province. All of these trends were projected to continue over the next decade, increasing heterogeneities in TB incidence across cities and between populations. To sustain declines in TB incidence and to prevent an increase in Multiple DR-TB (MDR-TB) in the future in China, future TB control strategies may (i) need to be tailored to local demography, (ii) prioritize key populations, such as elderly and internal migrants, and (iii) enhance DR-TB surveillance.

Markov genealogy processes.

We construct a family of genealogy-valued Markov processes that are induced by a continuous-time Markov population process. We derive exact expressions for the likelihood of a given genealogy conditional on the history of the underlying population process. These lead to a nonlinear filtering equation which can be used to design efficient Monte Carlo inference algorithms. We demonstrate these calculations with several examples. Existing full-information approaches for phylodynamic inference are special cases of the theory.

Decreased Case Fatality Rate of COVID-19 in the Second Wave: A study in 53 countries or regions.

The raw case fatality rate (CFR, the reported number of COVID-19 deaths divided by the total number of cases) is an important indicator to quantify the severity or treatment efficacy. In many countries, the pandemic had experienced two waves to date. To our knowledge, no studies have compared the CFR between the two waves. In this work, we reported the CFR of 53 countries or regions with the highest COVID-19 death tolls. Of them, 43 had lower CFR estimates in the ongoing second wave than in the first wave. We discussed the possible reasons. Also, we compared the two-wave pattern of COVID-19 with those of influenza. Influenza activities in the pre-pandemic era provided an indicator for seasonality of climate in a country. The sharp drop in influenza activities in 2020 could an indicator of the effects of social distancing.

Modeling the 2014-2015 Ebola Virus Disease Outbreaks in Sierra Leone, Guinea, and Liberia with Effect of High- and Low-risk Susceptible Individuals.

Ebola virus disease (EVD) is a rare but fatal disease of humans and other primates caused by Ebola viruses. Study shows that the 2014-2015 EVD outbreak causes more than 10,000 deaths. In this paper, we propose and analyze a deterministic model to study the transmission dynamics of EVD in Sierra Leone, Guinea, and Liberia. Our analyses show that the model has two equilibria: (1) the disease-free equilibrium (DFE) which is locally asymptotically stable when the basic reproduction number ([Formula: see text]) is less than unity and unstable if it is greater than one, and (2) an endemic equilibrium (EE) which is globally asymptotically stable when [Formula: see text] is greater than unity. Furthermore, the backward bifurcation occurs, a coexistence between a stale DFE and a stable EE even if the [Formula: see text] is less than unity, which makes the disease control more strenuous and would depend on the initial size of subpopulation. By fitting to reported Ebola cases from Sierra Leone, Guinea, and Liberia in 2014-2015, our model has captured the epidemic patterns in all three countries and shed light on future Ebola control and prevention strategies.

The relative transmissibility of asymptomatic COVID-19 infections among close contacts.

Asymptomatic transmission of the coronavirus disease 2019 is an important topic. A recent study in China showed that transmissibility of the asymptomatic cases is comparable to that of symptomatic cases. Here, we discuss that the conclusion may depend on how we interpret the data. To the best of our knowledge, this is the first time the relative transmissibility of asymptomatic COVID-19 infections is quantified.

New estimates of the Zika virus epidemic attack rate in Northeastern Brazil from 2015 to 2016: A modelling analysis based on Guillain-Barré Syndrome (GBS) surveillance data.

BACKGROUND: Between January 2015 and August 2016, two epidemic waves of Zika virus (ZIKV) disease swept the Northeastern (NE) region of Brazil. As a result, two waves of Guillain-Barré Syndrome (GBS) were observed concurrently. The mandatory reporting of ZIKV disease began region-wide in February 2016, and it is believed that ZIKV cases were significantly under-reported before that. The changing reporting rate has made it difficult to estimate the ZIKV infection attack rate, and studies in the literature vary widely from 17% to > 50%. The same applies to other key epidemiological parameters. In contrast, the diagnosis and reporting of GBS cases were reasonably reliable given the severity and easy recognition of the disease symptoms. In this paper, we aim to estimate the real number of ZIKV cases (i.e., the infection attack rate) and their dynamics in time, by scaling up from GBS surveillance data in NE Brazil. METHODOLOGY: A mathematical compartmental model is constructed that makes it possible to infer the true epidemic dynamics of ZIKV cases based on surveillance data of excess GBS cases. The model includes the possibility that asymptomatic ZIKV cases are infectious. The model is fitted to the GBS surveillance data and the key epidemiological parameters are inferred by using a plug-and-play likelihood-based estimation. We make use of regional weather data to determine possible climate-driven impacts on the reproductive number [Formula: see text], and to infer the true ZIKV epidemic dynamics. FINDINGS AND CONCLUSIONS: The GBS surveillance data can be used to study ZIKV epidemics and may be appropriate when ZIKV reporting rates are not well understood. The overall infection attack rate (IAR) of ZIKV is estimated to be 24.1% (95% confidence interval: 17.1%-29.3%) of the population. By examining various asymptomatic scenarios, the IAR is likely to be lower than 33% over the two ZIKV waves. The risk rate from symptomatic ZIKV infection to develop GBS was estimated as ρ = 0.0061% (95% CI: 0.0050%-0.0086%) which is significantly less than current estimates. We found a positive association between local temperature and the basic reproduction number, [Formula: see text]. Our analysis revealed that asymptomatic infections affect the estimation of ZIKV epidemics and need to also be carefully considered in related modelling studies. According to the estimated effective reproduction number and population wide susceptibility, we comment that a ZIKV outbreak would be unlikely in NE Brazil in the near future.

Preliminary estimates of the reproduction number of the coronavirus disease (COVID-19) outbreak in Republic of Korea and Italy by 5 March 2020.

The novel coronavirus disease 2019 (COVID-19) outbreak has caused 6088 cases and 41 deaths in Republic of Korea, and 3144 cases and 107 death in Italy by 5 March 2020, respectively. We modelled the transmission process in the Republic of Korea and Italy with a stochastic model, and estimated the basic reproduction number R0 as 2.6 (95% CI: 2.3-2.9) or 3.2 (95% CI: 2.9-3.5) in the Republic of Korea, under the assumption that the exponential growth starting on 31 January or 5 February 2020, and 2.6 (95% CI: 2.3-2.9) or 3.3 (95% CI: 3.0-3.6) in Italy, under the assumption that the exponential growth starting on 5 February or 10 February 2020, respectively.

A conceptual model for the coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China with individual reaction and governmental action.

The ongoing coronavirus disease 2019 (COVID-19) outbreak, emerged in Wuhan, China in the end of 2019, has claimed more than 2600 lives as of 24 February 2020 and posed a huge threat to global public health. The Chinese government has implemented control measures including setting up special hospitals and travel restriction to mitigate the spread. We propose conceptual models for the COVID-19 outbreak in Wuhan with the consideration of individual behavioural reaction and governmental actions, e.g., holiday extension, travel restriction, hospitalisation and quarantine. We employe the estimates of these two key components from the 1918 influenza pandemic in London, United Kingdom, incorporated zoonotic introductions and the emigration, and then compute future trends and the reporting ratio. The model is concise in structure, and it successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak.