Enhanced Deuteron Coalescence Probability in Jets

The transverse-momentum (p_{T}) spectra and coalescence parameters B_{2} of (anti)deuterons are measured in p-p collisions at sqrt[s]=13  TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest p_{T} in the event (p_{T}^{lead}>5  GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions, and the jet signal is obtained as the difference between the toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons in the jet cone as compared with the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase-space distributions of nucleons are generated using pythia8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in pythia8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the B_{2}^{Jet} is not reproduced by the models, which instead give a decreasing trend.

Mathematical modeling the order of driver gene mutations in colorectal cancer

Tumor heterogeneity is a large obstacle for cancer study and treatment. Different cancer patients may involve different combinations of gene mutations or the distinct regulatory pathways for inducing the progression of tumor. Investigating the pathways of gene mutations which can cause the formation of tumor can provide a basis for the personalized treatment of cancer. Studies suggested that KRAS, APC and TP53 are the most significant driver genes for colorectal cancer. However, it is still an open issue regarding the detailed mutation order of these genes in the development of colorectal cancer. For this purpose, we analyze the mathematical model considering all orders of mutations in oncogene, KRAS and tumor suppressor genes, APC and TP53, and fit it on data describing the incidence rates of colorectal cancer at different age from the Surveillance Epidemiology and End Results registry in the United States for the year 1973-2013. The specific orders that can induce the development of colorectal cancer are identified by the model fitting. The fitting results indicate that the mutation order with KRAS → APC → TP53, APC → TP53 → KRAS and APC → KRAS → TP53 explain the age-specific risk of colorectal cancer with very well. Furthermore, eleven pathways of gene mutations can be accepted for the mutation order of genes with KRAS → APC → TP53, APC → TP53 → KRAS and APC → KRAS → TP53, and the alternation of APC acts as the initiating or promoting event in the colorectal cancer. The estimated mutation rates of cells in the different pathways demonstrate that genetic instability must exist in colorectal cancer with alterations of genes, KRAS, APC and TP53.

Statistical Analysis of Two-Compartment Pharmacokinetic Models with Drug Non-adherence

Poor drug adherence is considered one of major barriers to achieving the clinical and public health benefits of many pharmacotherapies. In the current paper, we aim to investigate the impact of dose omission on the plasma concentrations of two-compartment pharmacokinetic models with two typical routes of drug administration, namely the intravenous bolus and extravascular first-order absorption. First, we reformulate the classical two-compartment pharmacokinetic models with a new stochastic feature, where a binomial random model of dose intake is integrated. Then, we formalize the explicit expressions of expectation and variance for trough concentrations and limit concentrations, with the latter proved of the existence and uniqueness for steady-state distribution. Moreover, we mathematically demonstrate the strict stationarity and ergodicity of trough concentrations as a Markov chain. In addition, we numerically simulate the impact of drug non-adherence to different extents on the variability and regularity of drug concentration and compare the drug pharmacokinetic preference between one and two compartment pharmacokinetic models. The results of sensitivity analysis also suggest the drug non-adherence as one of the most sensitive model parameters to the expectation of limit concentration. Our modelling and analytical approach can be integrated into the chronic disease models to estimate or quantitatively predict the therapy efficacy with drug pharmacokinetics presumably affected by random dose omissions.

Threshold conditions for curbing COVID-19 with a dynamic zero-case policy derived from 101 outbreaks in China

By 31 May 2022, original/Alpha, Delta and Omicron strains induced 101 outbreaks of COVID-19 in mainland China. Most outbreaks were cleared by combining non-pharmaceutical interventions (NPIs) with vaccines, but continuous virus variations challenged the dynamic zero-case policy (DZCP), posing questions of what are the prerequisites and threshold levels for success? And what are the independent effects of vaccination in each outbreak? Using a modified classic infectious disease dynamic model and an iterative relationship for new infections per day, the effectiveness of vaccines and NPIs was deduced, from which the independent effectiveness of vaccines was derived. There was a negative correlation between vaccination coverage rates and virus transmission. For the Delta strain, a 61.8% increase in the vaccination rate (VR) reduced the control reproduction number (CRN) by about 27%. For the Omicron strain, a 20.43% increase in VR, including booster shots, reduced the CRN by 42.16%. The implementation speed of NPIs against the original/Alpha strain was faster than the virus's transmission speed, and vaccines significantly accelerated the DZCP against the Delta strain. The CRN ([Formula: see text]) during the exponential growth phase and the peak time and intensity of NPIs were key factors affecting a comprehensive theoretical threshold condition for DZCP success, illustrated by contour diagrams for the CRN under different conditions. The DZCP maintained the [Formula: see text] of 101 outbreaks below the safe threshold level, but the strength of NPIs was close to saturation especially for Omicron, and there was little room for improvement. Only by curbing the rise in the early stage and shortening the exponential growth period could clearing be achieved quickly. Strengthening China's vaccine immune barrier can improve China's ability to prevent and control epidemics and provide greater scope for the selection and adjustment of NPIs. Otherwise, there will be rapid rises in infection rates and an extremely high peak and huge pressure on the healthcare system, and a potential increase in excess mortality.

[A panel study on the effect of atmospheric PM2.5 exposure on the gut microbiome in healthy elderly people aged 60-69 years old]

Objective: To analyze the short-term effect of individual atmospheric PM_2.5 exposure on the diversity, enterotype, and community structure of gut microbiome in healthy elderly people in Jinan, Shandong province. Methods: The present panel study recruited 76 healthy elderly people aged 60-69 years old in Dianliu Street, Lixia District, Jinan, Shandong Province, and followed them up five times from September 2018 to January 2019. The relevant information was collected by questionnaire, physical examination, precise monitoring of individual PM_2.5 exposure, fecal sample collection and gut microbiome 16S rDNA sequencing. The Dirichlet multinomial mixtures (DMM) model was used to analyze the enterotype. Linear mixed effect model and generalized linear mixed effect model were used to analyze the effect of PM_2.5 exposure on gut microbiome α diversity indices (Shannon, Simpson, Chao1, and ACE indices), enterotype and abundance of core species. Results: Each of the 76 subjects participated in at least two follow-up visits, resulting in a total of 352 person-visits. The age of 76 subjects was (65.0±2.8) years old with BMI (25.0±2.4) kg/m². There were 38 males accounting for 50% of the subjects. People with an educational level of primary school or below accounted for 10.5% of the 76 subjects, and those with secondary school and junior college or above accounting for 71.1% and 18.4%. The individual PM2.5 exposure concentration of 76 subjects during the study period was (58.7±53.7) μg/m³. DMM model showed that the subjects could be divided into four enterotypes, which were mainly driven by Bacteroides, Faecalibacterium, Lachnospiraceae, Prevotellaceae, and Ruminococcaceae. Linear mixed effects model showed that different lag periods of PM_2.5 exposure were significantly associated with a lower gut α diversity index (P<0.05 after correction). Further analysis showed that PM_2.5 exposure was significantly associated with changes in the abundances of Firmicutes (Megamonas, Blautia, Streptococcus, etc.) and Bacteroidetes (Alistipes) (P<0.05 after correction). Conclusion: Short-term PM_2.5 exposure is significantly associated with a decrease in gut microbiome diversity and changes in the abundance of several species of Firmicutes and Bacteroidetes in the elderly. It is necessary to further explore the underlying mechanisms between PM_2.5 exposure and the gut microbiome, so as to provide a scientific basis for promoting the intestinal health of the elderly.

Lessons drawn from Shanghai for controlling highly transmissible SARS-CoV-2 variants: insights from a modelling study

BACKGROUND

The continuous emergence of novel SARS-CoV-2 variants with markedly increased transmissibility presents major challenges to the zero-COVID policy in China. It is critical to adjust aspects of the policy about non-pharmaceutical interventions (NPIs) by searching for and implementing more effective ways. We use a mathematical model to mimic the epidemic pattern of the Omicron variant in Shanghai to quantitatively show the control challenges and investigate the feasibility of different control patterns in avoiding other epidemic waves.

METHODS

We initially construct a dynamic model with a core step-by-step release strategy to reveal its role in controlling the spread of COVID-19, including the city-based pattern and the district-based pattern. We used the least squares method and real reported case data to fit the model for Shanghai and its 16 districts, respectively. Optimal control theory was utilized to explore the quantitative and optimal solutions of the time-varying control strength (i.e., contact rate) to suppress the highly transmissible SARS-CoV-2 variants.

RESULTS

The necessary period for reaching the zero-COVID goal can be nearly 4 months, and the final epidemic size was 629,625 (95%CI: [608,049, 651,201]). By adopting the city-based pattern, 7 out of 16 strategies released the NPIs more or earlier than the baseline and ensured a zero-resurgence risk at the average cost of 10 to 129 more cases in June. By adopting the district-based pattern, a regional linked release can allow resumption of social activity to ~ 100% in the boundary-region group about 14 days earlier and allow people to flow between different districts without causing infection resurgence. Optimal solutions of the contact rate were obtained with various testing intensities, and higher diagnosis rate correlated with higher optimal contact rate while the number of daily reported cases remained almost unchanged.

CONCLUSIONS

Shanghai could have been bolder and more flexible in unleashing social activity than they did. The boundary-region group should be relaxed earlier and more attention should be paid to the centre-region group. With a more intensive testing strategy, people could return to normal life as much as possible but still ensure the epidemic was maintained at a relatively low level.

[Developmental effects of TCIPP and TnBP on zebrafish (Danio rerio) embryos]

Objective: To investigate the toxicity of tris (2-chloropropyl) phosphate (TCIPP) and tributyl phosphate (TnBP) on the growth and development of zebrafish embryos, as well as to explore the underlying mechanisms at the transcriptional level. Methods: With zebrafish as a model, two hpf zebrafish embryos were exposed to TCIPP and TnBP (0.1, 1, 10, 100, 500, and 1 000 μmol/L) using the semi-static method, and their rates of lethality and hatchability were determined. The transcriptome changes of 120 hpf juvenile zebrafish exposed to environmentally relevant concentrations of 0.1 and 1 μmol/L were measured. Results: The 50% lethal concentrations (LC₅₀) of TCIPP and TnBP for zebrafish embryos were 155.30 and 27.62 μmol/L (96 hpf), 156.5 and 26.05 μmol/L (120 hpf), respectively. The 72 hpf hatching rates of TCIPP (100 μmol/L) and TnBP (10 μmol/L) were (23.33±7.72)% and (91.67±2.97)%, which were significantly decreased compared with the control group (P<0.05). Transcriptome analysis showed that TnBP had more differential genes (DEGs) than TCIPP, with a dose-response relationship. These DEGs were enriched in 32 pathways in total, including those involved in oxidative stress, energy metabolism, lipid metabolism, and nuclear receptor-related pathways, using the IPA pathway analysis. Among them, three enriched pathways overlapped between TCIPP and TnBP, including TR/RXR activation and CAR/RXR activation. Additionally, DEGs were also mapped onto pathways of LXR/RXR activation and oxidative stress for TnBP exposure only. Conclusion: Both TCIPP and TnBP have growth and developmental toxicities in zebrafish embryos, with distinct biomolecular mechanisms, and TnBP has a stronger effect than TCIPP.

[Rapid detection and genotyping of SARS-CoV-2 Omicron BA.4/5 variants using a RT-PCR and CRISPR-Cas12a-based assay]

OBJECTIVE

To establish a rapid detection and genotyping method for SARS-CoV-2 Omicron BA.4/5 variants using CRISPPR-Cas12a gene editing technology.

METHODS

We combined reverse transcription-polymerase chain reaction (RT-PCR) and CRISPR gene editing technology and designed a specific CRISPPR RNA (crRNA) with suboptimal protospacer adjacent motifs (PAM) for rapid detection and genotyping of SARS- CoV-2 Omicron BA.4/5 variants. The performance of this RT- PCR/ CRISPPR-Cas12a assay was evaluated using 43 clinical samples of patients infected by wild-type SARS-CoV-2 and the Alpha, Beta, Delta, Omicron BA. 1 and BA. 4/5 variants and 20 SARS- CoV- 2-negative clinical samples infected with 11 respiratory pathogens. With Sanger sequencing method as the gold standard, the specificity, sensitivity, concordance (Kappa) and area under the ROC curve (AUC) of RT-PCR/CRISPPR-Cas12a assay were calculated.

RESULTS

This assay was capable of rapid and specific detection of SARS- CoV-2 Omicron BA.4/5 variant within 30 min with the lowest detection limit of 10 copies/μL, and no cross-reaction was observed in SARS-CoV-2-negative clinical samples infected with 11 common respiratory pathogens. The two Omicron BA.4/5 specific crRNAs (crRNA-1 and crRNA-2) allowed the assay to accurately distinguish Omicron BA.4/5 from BA.1 sublineage and other major SARS-CoV-2 variants of concern. For detection of SARS-CoV-2 Omicron BA.4/5 variants, the sensitivity of the established assay using crRNA-1 and crRNA-2 was 97.83% and 100% with specificity of 100% and AUC of 0.998 and 1.000, respectively, and their concordance rate with Sanger sequencing method was 92.83% and 96.41%, respectively.

CONCLUSION

By combining RT-PCR and CRISPPR-Cas12a gene editing technology, we successfully developed a new method for rapid detection and identification of SARS-CoV-2 Omicron BA.4/5 variants with a high sensitivity, specificity and reproducibility, which allows rapid detection and genotyping of SARS- CoV-2 variants and monitoring of the emerging variants and their dissemination.

Assessing the transmissibility of epidemics involving epidemic zoning

BACKGROUND

Epidemic zoning is an important option in a series of measures for the prevention and control of infectious diseases. We aim to accurately assess the disease transmission process by considering the epidemic zoning, and we take two epidemics with distinct outbreak sizes as an example, i.e., the Xi'an epidemic in late 2021 and the Shanghai epidemic in early 2022.

METHODS

For the two epidemics, the total cases were clearly distinguished by their reporting zone and the Bernoulli counting process was used to describe whether one infected case in society would be reported in control zones or not. Assuming the imperfect or perfect isolation policy in control zones, the transmission processes are respectively simulated by the adjusted renewal equation with case importation, which can be derived on the basis of the Bellman-Harris branching theory. The likelihood function containing unknown parameters is then constructed by assuming the daily number of new cases reported in control zones follows a Poisson distribution. All the unknown parameters were obtained by the maximum likelihood estimation.

RESULTS

For both epidemics, the internal infections characterized by subcritical transmission within the control zones were verified, and the median control reproduction numbers were estimated as 0.403 (95% confidence interval (CI): 0.352, 0.459) in Xi'an epidemic and 0.727 (95% CI: 0.724, 0.730) in Shanghai epidemic, respectively. In addition, although the detection rate of social cases quickly increased to 100% during the decline period of daily new cases until the end of the epidemic, the detection rate in Xi'an was significantly higher than that in Shanghai in the previous period.

CONCLUSIONS

The comparative analysis of the two epidemics with different consequences highlights the role of the higher detection rate of social cases since the beginning of the epidemic and the reduced transmission risk in control zones throughout the outbreak. Strengthening the detection of social infection and strictly implementing the isolation policy are of great significance to avoid a larger-scale epidemic.

The relative importance of key meteorological factors affecting numbers of mosquito vectors of dengue fever

Although single factors such as rainfall are known to affect the population dynamics of Aedes albopictus, the main vector of dengue fever in Eurasia, the synergistic effects of different meteorological factors are not fully understood. To address this topic, we used meteorological data and mosquito-vector association data including Breteau and ovitrap indices in key areas of dengue outbreaks in Guangdong Province, China, to formulate a five-stage mathematical model for Aedes albopictus population dynamics by integrating multiple meteorological factors. Unknown parameters were estimated using a genetic algorithm, and the results were analyzed by k-Shape clustering, random forest and grey correlation analysis. In addition, the population density of mosquitoes in 2022 was predicted and used for evaluating the effectiveness of the model. We found that there is spatiotemporal heterogeneity in the effects of temperature and rainfall and their distribution characteristics on the diapause period, the numbers of peaks in mosquito densities in summer and the annual total numbers of adult mosquitoes. Moreover, we identified the key meteorological indicators of the mosquito quantity at each stage and that rainfall (seasonal rainfall and annual total rainfall) was more important than the temperature distribution (seasonal average temperature and temperature index) and the uniformity of rainfall annual distribution (coefficient of variation) for most of the areas studied. The peak rainfall during the summer is the best indicator of mosquito population development. The results provide important theoretical support for the future design of mosquito vector control strategies and early warnings of mosquito-borne diseases.

[Establishment and evaluation of a method for phages enrichment by ferric trichloride-polyvinylidene fluoride membrane filter]

Objective: To establish and evaluate a method of enriching bacteriophages in natural water based on ferric trichloride-polyvinylidene fluoride (FeCl₃-PVDF)membrane filter. Methods: Based on the principle of flocculation concentration, the method of recovering bacteriophage from water sample was established by using iron ion flocculation combined with membrane filter. The titer of phage was determined by Agar double layer method. The recovery efficiency of phage was detected by phage fluorescence staining and real-time fluorescence PCR reaction. Water samples from different sources were collected for simulation experiment to evaluate the enrichment effect. At the same time, the sewage discharged from hospitals was taken as the actual water sample, and the common clinical drug-resistant bacteria were used as the host indicator bacteria to further analyze the enrichment effect of FeCl₃-PVDF membrane filter rapid enrichment method on the bacteriophage in natural water samples. Results: The method of enrichment of bacteriophages in natural water by iron ion concentration 50 mg/L and PVDF membrane filter was established. The recovery rate of this method for bacteriophage was 93%-100%. Under the multi-functional microscope, it was found that the bacteriophage of the enriched water sample increased significantly and the fluorescence value of the enriched water sample determined by the enzyme labeling instrument was about 13 times as high as that before enrichment. After concentration of the actual water samples from the hospital drainage, the positive rate of bacteriophage isolation in the concentrated group and the non-concentrated group was 23% and 4%, and the fluorescence value in the concentrated group was 2-24 times as high as that of the non-concentrated group. Conclusion: The method of FeCl₃-PVDF membrane filter is a simple, efficient and rapid method for enriching bacteriophages in different water samples.

A radiomics model development via the associations with genomics features in predicting axillary lymph node metastasis of breast cancer: a study based on a public database and single-centre verification

AIM

To evaluate the predictive performance of the radiomics model in predicting axillary lymph node (ALN) metastasis through the associations between radiomics features and genomic features in patients with breast cancer.

MATERIALS AND METHODS

Patients with breast cancer were enrolled retrospectively from a public database (111 patients as training group) and one hospital (15 patients as external validation group). The genomics features from transcriptome data and radiomics features from dynamic contrast-enhanced magnetic resonance imaging (MRI) were collected. Firstly, overlapping genes were identified using the Kyoto Encyclopedia of Genes and Genomes and differentially expressed gene analysis, while radiomics features were reduced using a data-driven method. Then, the associations between overlapping genes and retained radiomics features were assessed to obtain key pairs of radiomics-genomics features. Furthermore, the least absolute shrinkage and selection operator (LASSO) algorithm was used to detect the key-pairs features. Finally, radiomics and genomics models were constructed to predict ALN metastasis.

RESULTS

After using the hybrid data- and gene-driven selection method, key pairs of features were detected, which consisted of six radiomic features associated with four genomic features. The radiomics model exhibited comparable performance to the genomics model in predicting ALN metastasis (radiomic model: area under the curve [AUC] = 0.71, sensitivity = 77%, specificity = 56%; genomic model: AUC = 0.72, sensitivity = 85%, specificity = 74%). The four genomic features were enriched in six pathways and related to metabolism and human diseases.

CONCLUSION

The radiomics model established using the gene-driven hybrid selection method could predict ALN metastasis in breast cancer, which showed comparable performance to the genomics model.

Exploring COVID-19 transmission patterns and key factors during epidemics caused by three major strains in Asia

The COVID-19 epidemic has lasted for more than two years since the outbreak in late 2019. An urgent and challenging question is how to systematically evaluate epidemic developments in different countries, during different periods, and to determine which measures that could be implemented are key for successful epidemic prevention. In this study, SBD distance-based K-shape clustering and hierarchical clustering methods were used to analyse epidemics in Asian countries. For the hierarchical clustering, epidemic time series were divided into three periods (epidemics induced by the Original/Alpha, Delta and Omicron variants separately). Standard deviations, the Hurst index, mortality rates, peak value of confirmed cases per capita, average growth rates, and the control efficiency of each period were used to characterize the epidemics. In addition, the total numbers of cases in the different countries were analysed by correlation and regression in relation to 15 variables that could have impacts on COVID-19. Finally, some suggestions on prevention and control measures for each category of country are given. We found that the total numbers of cases per million of a population, total deaths per million and mortality rates were highly correlated with the proportion of people aged over 65 years, the prevalence of multiple diseases, and the national GDP. We also found significant associations between case numbers and vaccination rates, health expenditures, and stringency of control measures. Vaccinations have played a positive role in COVID-19, with a gradual decline in mortality rates in later periods, and are still playing protective roles against the Delta and Omicron strains. The stringency of control measures taken by a government is not an indicator of the appropriateness of a country's response to the outbreak, and a higher index does not necessarily mean more effective measures; a combination of factors such as national vaccination rates, the country's economic foundation and the availability of medical equipment is also needed. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Coupling the Within-Host Process and Between-Host Transmission of COVID-19 Suggests Vaccination and School Closures are Critical

Most models of COVID-19 are implemented at a single micro or macro scale, ignoring the interplay between immune response, viral dynamics, individual infectiousness and epidemiological contact networks. Here we develop a data-driven model linking the within-host viral dynamics to the between-host transmission dynamics on a multilayer contact network to investigate the potential factors driving transmission dynamics and to inform how school closures and antiviral treatment can influence the epidemic. Using multi-source data, we initially determine the viral dynamics and estimate the relationship between viral load and infectiousness. Then, we embed the viral dynamics model into a four-layer contact network and formulate an agent-based model to simulate between-host transmission. The results illustrate that the heterogeneity of immune response between children and adults and between vaccinated and unvaccinated infections can produce different transmission patterns. We find that school closures play a significant effect on mitigating the pandemic as more adults get vaccinated and the virus mutates. If enough infected individuals are diagnosed by testing before symptom onset and then treated quickly, the transmission can be effectively curbed. Our multiscale model reveals the critical role played by younger individuals and antiviral treatment with testing in controlling the epidemic.

Stability analysis of the COVID-19 model with age structure under media effect

The spread and control of infectious diseases are inevitably influenced by the age structure of the population and media effect. In this paper, we propose a susceptible-exposure-infection-recovery type age-structured COVID-19 model with media effect. First, the existence and uniqueness of the solution are obtained using semigroup theory and the positive operator method. The basic regeneration 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} R 0 is computed next and the globally asymptotical stability of the disease-free steady state, as well as the locally asymptotical stability of endemic steady state is studied without any extra conditions. The influence of media effect and age structure of the population on disease transmission are also verified by numerical simulations. Our result show that additional intensity of media broadcasts not only reduces the peak of disease outbreak but also shortens the duration of the epidemic. Further more, the proportion of infected adolescents is lower, and adults should pay more attention to self-protection.

Longitudinal Relationship between Mobility Device Use, Falls and Fear of Falling (FOF) Differed by Frailty Status among Community-Dwelling Older Adults

OBJECTIVES

This study examined the longitudinal relationship between mobility device use, falls and fear of falling (FOF) among community-dwelling older adults by frailty status over a one-year follow-up.

DESIGN

A longitudinal cohort study.

SETTING

Communities in the United States.

PARTICIPANTS

Community-dwelling older adults from the National Health and Aging Trends Study, a nationally representative survey of Medicare Beneficiaries in the United States (N=5,896).

MEASUREMENTS

Based on yes or no response to the corresponding items for the variables, fall-related outcomes were determined separately including falls and FOF. Falls were assessed by asking participants whether they had a fall and if they had fallen down more than one time. FOF was measured by asking participants whether they worried about falling and if this worry ever limited activities. Mobility device use was determined by asking whether participants used any type of mobility devices and the number of devices used, including cane, walker, wheelchair and scooter. Frailty was assessed using the frailty phenotype. Multinomial logistic regression models were conducted to examine the association between mobility device use and fall-related outcomes among older adults by frailty status.

RESULTS

At Year 1, 28.6% of participants reported using mobility devices. Among robust participants, using one mobility device had 3.58 times higher risks of FOF with fear-related activity restriction (FAR) than non-device users (95% CI: 1.10-11.65). Cane-only robust users had 5.94 and 2.18 times higher risks of FOF with and without FAR (95% CI: 1.80-19.57; 95% CI: 1.12-4.22) than non-device users. Among pre-frail participants, using one mobility device was associated with recurrent falls and FOF with FAR (RRR=2.02, 95% CI: 1.30-3.14; RRR=2.13, 95% CI: 1.25-3.63). Using ≥2 devices was associated with one fall (RRR=2.08, 95% CI: 1.30-3.33), recurrent falls (RRR=2.92, 95% CI: 1.62-5.25) and FOF with FAR (RRR=2.84, 95% CI: 1.34-6.02). Pre-frail cane-only users were more likely to have one fall (RRR=1.57, 95% CI: 1.06-2.32), recurrent falls (RRR=2.36, 95% CI: 1.48-3.77) and FOF with FAR (RRR=2.08, 95% CI: 1.12-3.87) than non-device users. The number of mobility device used and the use of canes failed to be significantly associated with fall-related outcomes among frail participants.

CONCLUSION

The number of mobility devices used and the only use of canes were associated with fall-related outcomes among robust and pre-frail individuals. Further research is needed to develop targeted strategies for preventing falls and FOF among older adults with mobility device use, particularly for those in the early stages of frailty.

Coupling an individual adaptive-decision model with a SIRV model of influenza vaccination reveals new insights for epidemic control

Past seasonal influenza epidemics and vaccination experience may affect individuals' decisions on whether to be vaccinated or not, decisions that may be constantly reassessed in relation to recent influenza related experience. To understand the potentially complex interaction between experience and decisions and whether the vaccination rate is likely to reach a critical coverage level or not, we construct an adaptive-decision model. This model is then coupled with an influenza vaccination dynamics (SIRV) model to explore the interaction between individuals' decision-making and an influenza epidemic. Nonlinear least squares estimation is used to obtain the best-fit parameter values in the SIRV model based on data on new influenza-like illness (ILI) cases in Texas. Uncertainty and sensitivity analyses are then carried out to determine the impact of key parameters of the adaptive decision-making model on the ILI epidemic. The results showed that the necessary critical coverage rate of ILI vaccination could not be reached by voluntary vaccination. However, it could be reached in the fourth year if mass media reports improved individuals' memory of past vaccination experience. Individuals' memory of past vaccination experience, the proportion with histories of past vaccinations and the perceived cost of vaccination are important factors determining whether an ILI epidemic can be effectively controlled or not. Therefore, health authorities should guide people to improve their memory of past vaccination experience through media reports, publish timely data on annual vaccination proportions and adjust relevant measures to appropriately reduce vaccination perceived cost, in order to effectively control an ILI epidemic.

The resurgence risk of COVID-19 in China in the presence of immunity waning and ADE: A mathematical modelling study

The mass vaccination program has been actively promoted since the end of 2020. However, waning immunity, antibody-dependent enhancement (ADE), and increased transmissibility of variants make the herd immunity untenable and the implementation of dynamic zero-COVID policy challenging in China. To explore how long the vaccination program can prevent China at low resurgence risk, and how these factors affect the long-term trajectory of the COVID-19 epidemics, we developed a dynamic transmission model of COVID-19 incorporating vaccination and waning immunity, calibrated using the data of accumulative vaccine doses administered and the COVID-19 epidemic in 2020 in mainland China. The prediction suggests that the vaccination coverage with at least one dose reach 95.87%, and two doses reach 77.92% on 31 August 2021. However, despite the mass vaccination, randomly introducing infected cases in the post-vaccination period causes large outbreaks quickly with waning immunity, particularly for SARS-CoV-2 variants with higher transmissibility. The results showed that with the current vaccination program and 50% of the population wearing masks, mainland China can be protected at low resurgence risk until 8 January 2023. However, ADE and higher transmissibility for variants would significantly shorten the low-risk period by over 1 year. Furthermore, intermittent outbreaks can occur while the peak values of the subsequent outbreaks decrease, indicating that subsequent outbreaks boosted immunity in the population level, further indicating that follow-up vaccination programs can help mitigate or avoid the possible outbreaks. The findings revealed that the integrated effects of multiple factors: waning immunity, ADE, relaxed interventions, and higher variant transmissibility, make controlling COVID-19 challenging. We should prepare for a long struggle with COVID-19, and not entirely rely on the COVID-19 vaccine.

[Recommendations of EASL clinical practice guidelines on haemochromatosis]

Haemochromatosis is characterised by elevated transferrin saturation (TSAT) and progressive iron loading that mainly affects the liver. Early diagnosis and treatment by phlebotomy can prevent cirrhosis, hepatocellular carcinoma, diabetes, arthropathy and other complications. In patients homozygous for p.Cys282Tyr in HFE, provisional iron overload based on serum iron parameters (TSAT >45% and ferritin >200 μg/L in females and TSAT >50% and ferritin >300 μg/L in males and postmenopausal women) is sufficient to diagnose haemochromatosis. In patients with high TSAT and elevated ferritin but other HFE genotypes, diagnosis requires the presence of hepatic iron overload on MRI or liver biopsy. The stage of liver fibrosis and other end-organ damage should be carefully assessed at diagnosis because they determine disease management. Patients with advanced fibrosis should be included in a screening programme for hepatocellular carcinoma. Treatment targets for phlebotomy are ferritin <50 μg/L during the induction phase and <100 μg/L during the maintenance phase.

Strengths and limitations of diagnostic tools for endometriosis and relevance in diagnostic test accuracy research

Endometriosis is a chronic systemic disease that can cause pain, infertility and reduced quality of life. Diagnosing endometriosis remains challenging, which yields diagnostic delays for patients. Research on diagnostic test accuracy in endometriosis can be difficult due to verification bias, as not all patients with endometriosis undergo definitive diagnostic testing. The purpose of this State-of-the-Art Review is to provide a comprehensive update on the strengths and limitations of the diagnostic modalities used in endometriosis and discuss the relevance of diagnostic test accuracy research pertaining to each. We performed a comprehensive literature review of the following methods: clinical assessment including history and physical examination, biomarkers, diagnostic imaging, surgical diagnosis and histopathology. Our review suggests that, although non-invasive diagnostic methods, such as clinical assessment, ultrasound and magnetic resonance imaging, do not yet qualify formally as replacement tests for surgery in diagnosing all subtypes of endometriosis, they are likely to be appropriate for advanced stages of endometriosis. We also demonstrate in our review that all methods have strengths and limitations, leading to our conclusion that there should not be a single gold-standard diagnostic method for endometriosis, but rather, multiple accepted diagnostic methods appropriate for different circumstances. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Bio-based Non-estrogenic Dimethacrylate Dental Composite from Cloves

Bisphenol A (BPA), as an endocrine disruptor derived from petroleum-based chemicals, has been prohibited by several regulatory agencies for use in a wide variety of consumer products. For the sake of reducing human exposure to BPA derivatives and in the context of sustainability, it is far-reaching to develop high-performance and low-toxic materials from bountiful biomass sources. The objective of this work was to synthesize 2 bio-based dimethacrylate monomers, 2,2'-dially-4,4'-dimethoxy-5,5'-diglycerolate acrylatediphenylmethane (BEF-EA) and 2,2'-dially-4,4'-dimethoxy-5,5'-diglycerolate methacrylatediphenylmethane (BEF-GMA), using eugenol as the raw material. The estrogenic activity of bio-based bisphenol 2,2'-dially-4,4'-dimethoxy-5,5'-dihydroxydiphenylmethane (BEF) was evaluated and compared with estrogen and commercial bisphenols. After photopolymerization of the di(meth)acrylates diluted with tri(ethyleneglycol) dimethacrylate (TEGDMA), bio-based visible light-curing materials were prepared, and their properties were systematically investigated. Notably, di(meth)acrylates BEF-GMA and BEF-EA derived from these nonestrogenic bio-based phenols exhibited improved biocompatibility and low viscosity (down to 220-280 Pa.s). BEF-GMA and BEF-EA resin matrix exhibits lower volumetric polymerization shrinkage (about 8.5%), high photopolymerization reactivity (>50% in 60 s), and mechanical properties (fracture energy >5.5 N mm; flexural strength of 87-91 MPa, etc), which were comparable or superior to commercial Bis-GMA. The respective bio-based composites still exhibit adequate properties. Therefore, introducing eugenol-based visible light-curable dimethacrylate monomers into dental materials is a potential strategy to establish green sustainability and biocompatible dental materials without BPA.