Trends and Projections of Stomach Cancer Incidence in Hong Kong: A Population-Based Study.

OBJECTIVES: The burden of stomach cancer remains high in Hong Kong. We sought to evaluate the associations of age, period, and birth cohort with the changing trend in the incidence of stomach cancer and to provide projections through 2030. MATERIALS AND METHODS: We performed an age-period-cohort analysis and projections up to 2030 using data from the Hong Kong Cancer Registry. Additionally, we used a population decomposition algorithm to assess the drivers in the number of incident cases of stomach cancer in Hong Kong. RESULTS: Among the 26,813 stomach cancer patients, from 1994 to 2018, the age-standardized incidence rate of stomach cancer decreased for both sexes. The incidence increased with age and was highest for those aged 85 years or older. Period relative risk (RR) showed a monotonic decreasing pattern throughout the study period for both sexes before 2010. Cohort RR for males was monotonically decreasing but changed little after the 1967-1971 birth cohort. In contrast, cohort RR for females declined in the pre-1927-1931 birth cohort but slowed down since. It is projected that there will be 906 male patients and 954 female patients in 2030. Decomposition analysis suggested that population growth and aging were associated with substantial changes in the number of incident cases of stomach cancer in Hong Kong. CONCLUSIONS: Both period and cohort risk of developing stomach cancer in Hong Kong have slowed down or plateaued. Our study demonstrates that population aging and growth are the main drivers of the increased number of incident cases of stomach cancer in Hong Kong.

Changing patterns of nasopharyngeal carcinoma incidence in Hong Kong: a 30-year analysis and future projections.

BACKGROUND: This study aims to evaluate the relationship between age, period, and birth cohort with the incidence trends of Nasopharyngeal Carcinoma (NPC) in Hong Kong, make projections through 2030 and parse the drivers of the incidence. METHODS: Using data from the Hong Kong Cancer Registry, we used an age-period-cohort model to uniquely estimate age, period, and cohort effects on NPC incidence trends and make projections. We further assessed the drivers of NPC incidence using a validated decomposition algorithm. RESULTS: From 1991 to 2020, crude and age-standardized incidence rates of NPC decreased significantly. The net drifts showed significant downward trends for both sexes, and local drift declined in all age groups. Period and cohort rate ratios revealed monotonic declining patterns for both sexes. Projections suggested that NPC incidence will continue to decline. Population decomposition showed that while population growth and ageing have led to an increase in NPC cases, epidemiologic changes offset these increases, resulting in an encouraging downward trend in the incidence and new NPC cases in Hong Kong. CONCLUSIONS: The period and cohort risk of NPC in Hong Kong decreased, and epidemiologic changes offset the contribution of demographic factors, resulting in a continued decline in NPC incidence and cases.

Trends and projections of ovarian cancer incidence in Hong Kong: A population-based study.

INTRODUCTION: This study analyzed the incidence of ovarian cancer in Hong Kong and its association with age, calendar period and birth cohort, made projections through 2030, and attributed differences in new cancer cases to demographic and epidemiologic changes. MATERIAL AND METHODS: Incidence data for ovarian cancer were obtained from the Hong Kong Cancer Registry. We employed the age-period-cohort modeling approach to investigate the association between ovarian cancer incidence and age in Hong Kong women, with particular emphasis on examining the changing trends of period and cohort effects on incidence. We projected the incidence of ovarian cancer in Hong Kong between 2018 and 2030 and attributed the rise in new cancer cases to epidemiologic and demographic shifts. RESULTS: Between 1990 and 2017, a total of 11 182 women were diagnosed with ovarian cancer in Hong Kong. Crude and age-standardized rates increased from 8.2 and 7.8 per 100 000 person-years to 16.3 and 11.5 per 100 000 person-years, respectively. New cases of ovarian cancer rose from 225 in 1990 to 645 in 2017. We observed an increased risk of ovarian cancer throughout the study period and in the post-1940 birth cohort. The projected incidence rate and new cases of ovarian cancer are expected to continue growing due to demographic and epidemiologic changes such as fertility patterns and lifestyle factors, with an estimated 981 cases in 2030. CONCLUSIONS: The period risk and cohort risk of ovarian cancer among Hong Kong women is increasing. Demographic and epidemiologic changes may continue to increase ovarian cancer incidence and new cases in Hong Kong.

Global burden attributable to high sodium intake from 1990 to 2019.

BACKGROUND AND AIMS: High sodium intake is associated with a higher risk of a wide range of diseases. We aimed to estimate the pattern and trend of the global disease burden associated with high sodium intake from 1990 to 2019. METHODS AND RESULTS: We obtained numbers and rates of death and disability-adjusted life year (DALY) attributable to high sodium intake by sex, socio-demographic index, and country from the Global Burden of Disease Study 2019. We calculated the estimated annual percentage change to evaluate the age-standardized rate (ASR) of the burden attributable to high sodium intake between 1990 and 2019. We further calculated the contribution of population growth, population aging, and age-specific rates of death and DALY to the net change in the total number of deaths and DALYs attributable to high sodium intake. From 1990 to 2019, global age-standardized rates of death and DALY attributable to high sodium intake substantially decreased for both sexes. However, there were significant increases in the total numbers of deaths and DALYs attributable to high sodium intake, which were driven by population growth and population aging. The attribution of population growth and population aging varied widely across countries, with a higher contribution of population growth in most developing countries and a higher contribution of population aging in countries with slow population growth. CONCLUSIONS: Although the global burden attributable to high sodium intake in terms of age-standardized rate declined from 1990 to 2019, the absolute burden increased significantly, which was driven by population growth and population aging.

A comparative study of the disease burden attributable to PM2.5 in China, Japan and South Korea from 1990 to 2017.

BACKGROUND: Exposure to fine particulate matter (PM2.5) is one of the leading contributors to disease burden. However, little is known about the spatial and temporal trends of the disease burden attributable to PM2.5 in the three major economies in East Asia. We aimed to estimate the patterns and temporal variations of the disease burden attributable to PM2.5 in China, Japan, and South Korea from 1990 to 2017. METHODS: We obtained data on disease burden attributable to PM2.5 from the Global Burden of Disease Study (GBD) 2017. We retrieved the numbers and age-standardized mortality rate (ASMR) and disability-adjusted life years (DALYs) rate (ASDR) of disease attributable to PM2.5 by age, sex, socio-demographic index (SDI), and country. We used percentage change and estimated annual percentage change (EAPC) to assess the trends of ASMR and ASDR attributable to PM2.5 between 1990 and 2017. We further calculated the contribution of population growth, population aging, and changes in mortality or DALYs rate to the net changes in total deaths and DALYs associated with PM2.5. RESULTS: We found considerable differences in the disease burden attributable to PM2.5 in China, Japan, and South Korea. In 2017, the ASMR and ASDR of disease attributable to PM2.5 in China were 49.37 (95% UI: 41.18, 57.5) per 100,000 population and 1065.9 (95% UI: 891.28, 1237.38) per 100,000 population, respectively, which was about four times higher than that of Japan and twice higher than that of South Korea. Regardless of country, the ASMR and ASDR were more pronounced among elders and males. From 1990 to 2017, the declines in ASMR and ASDR were more pronounced in Japan and South Korea than in China. The changes in PM2.5 associated total deaths and DALYs between 1990 and 2017 were the combined effects of population aging, population growth, and changes in mortality or DALY rate, resulting in a net increase in total deaths and DALYs in China but little changes in Japan and South Korea. CONCLUSIONS: PM2.5 still contributed to significant disease burdens in 2017, although age-standardized disease burden has declined from 1990 to 2017. There has been an increasing trend in total deaths and DALYs in China, which was primarily driven by population aging.

Bioactive glass functionalized chondroitin sulfate hydrogel with proangiogenic properties.

Blood vessels play an important role in bone defect repair and growth, and a critical challenge of bone defect repair is the promotion of blood vessel formation. Most of the current methods promote vascularization by adding specific growth factors, which are costly and easy to inactivate. In this study, we developed a covalently cross-linked aminated bioactive glass nanoparticle-chondroitin sulfate methacrylate (ABGN-CSMA) organic-inorganic composite hydrogel with angiogenic properties. The amino groups of the ABGNs form covalent bonds with the carboxyl groups on CSMA. Surface amination modification of BGNs not only improved the dispersion of BGNs in CSMA but also significantly improved the mechanical properties of the composite hydrogel. The largest storage modulus (1200 Pa), the largest loss modulus (560 Pa) and the strongest resistance to deformation of the hydrogel are seen at 10% concentration of ABGNs. Simultaneously, the local pH stability and sustained ion release of the composite hydrogel are conducive to cell adhesion, proliferation, and angiogenesis. This work provides evidence for the development of covalently cross-linked organic-inorganic composite hydrogels with angiogenic properties.

Phylodynamic and transmission pattern of rabies virus in China and its neighboring countries.

Rabies is a fatal disease caused by infection with rabies virus (RABV), and human rabies is still a critical public-health concern in China. Although there have been some phylogenetic studies about RABV transmission patterns, with the accumulation of more rabies sequences in recent years, there is an urgent need to update and clarify the spatial and temporal patterns of RABV circulating in China on a national scale. In this study, we collected all available RABV nucleoprotein gene sequences from China and its neighboring countries and performed comparative analysis. We identified six significant subclades of RABV circulating in China and found that each of them has a specific geographical distribution, reflecting possible physical barriers to gene flow. The phylogeographic analysis revealed minimal viral movement among different geographical locations. An analysis using Bayesian coalescent methods indicated that the current RABV strains in China may come from a common ancestor about 400 years ago, and currently, China is amid the second event of increasing RABV population since the 1950s, but the population has decreased gradually. We did not detect any evidence of recombination in the sequence dataset, nor did we find any evidence for positive selection during the expansion of RABV. Overall, geographic location and neutral genetic drift may be the main factors in shaping the phylogeography of RABV transmission in China.

Exact periodic cross-kink wave solutions for the new (2+1)-dimensional KdV equation in fluid flows and plasma physics.

The Korteweg-de Vries (KdV)-type models have been shown to describe many important physical situations such as fluid flows, plasma physics, and solid state physics. In this paper, a new (2 + 1)-dimensional KdV equation is discussed. Based on the Hirota's bilinear form and a generalized three-wave approach, we obtain new exact solutions for the new (2 + 1)-dimensional KdV equation. With the help of symbolic computation, the properties for some new solutions are presented with some figures.

Top predators induce the evolutionary diversification of intermediate predator species.

We analyze the evolutionary branching phenomenon of intermediate predator species in a tritrophic food chain model by using adaptive dynamics theory. Specifically, we consider the adaptive diversification of an intermediate predator species that feeds on a prey species and is fed upon by a top predator species. We assume that the intermediate predator׳s ability to forage on the prey can adaptively improve, but this comes at the cost of decreased defense ability against the top predator. First, we identify the general properties of trade-off relationships that lead to a continuously stable strategy or to evolutionary branching in the intermediate predator species. We find that if there is an accelerating cost near the singular strategy, then that strategy is continuously stable. In contrast, if there is a mildly decelerating cost near the singular strategy, then that strategy may be an evolutionary branching point. Second, we find that after branching has occurred, depending on the specific shape and strength of the trade-off relationship, the intermediate predator species may reach an evolutionarily stable dimorphism or one of the two resultant predator lineages goes extinct.

Adaptive evolution of defense ability leads to diversification of prey species.

In this paper, by using the adaptive dynamics approach, we investigate how the adaptive evolution of defense ability promotes the diversity of prey species in an initial one-prey-two-predator community. We assume that the prey species can evolve to a safer strategy such that it can reduce the predation risk, but a prey with a high defense ability for one predator may have a low defense ability for the other and vice versa. First, by using the method of critical function analysis, we find that if the trade-off is convex in the vicinity of the evolutionarily singular strategy, then this singular strategy is a continuously stable strategy. However, if the trade-off is weakly concave near the singular strategy and the competition between the two predators is relatively weak, then the singular strategy may be an evolutionary branching point. Second, we find that after the branching has occurred in the prey strategy, if the trade-off curve is globally concave, then the prey species might eventually evolve into two specialists, each caught by only one predator species. However, if the trade-off curve is convex-concave-convex, the prey species might eventually branch into two partial specialists, each being caught by both of the two predators and they can stably coexist on the much longer evolutionary timescale.

Discrimination of missing data types in metabolomics data based on particle swarm optimization algorithm and XGBoost model.

In the field of data analysis, it is often faced with a large number of missing values, especially in metabolomics data, this problem is more prominent. Data imputation is a common method to deal with missing metabolomics data, while traditional data imputation methods usually ignore the differences in missing types, and thus the results of data imputation are not satisfactory. In order to discriminate the missing types of metabolomics data, a missing data classification model (PX-MDC) based on particle swarm algorithm and XGBoost is proposed in this paper. First, the missing values in a given missing data set are obtained by panning the missing values to obtain the largest subset of complete data, and then the particle swarm algorithm is used to search for the concentration threshold of missing data and the proportion of low concentration deletions as a percentage of overall deletions. Next, the missing data are simulated based on the search results. Finally, the training data are trained using the XGBoost model using the feature set proposed in this paper in order to build a classifier for the missing data. The experimental results show that the particle swarm algorithm is able to match the traditional enumeration method in terms of accuracy and significantly reduce the search time in concentration threshold search. Compared with the current mainstream methods, the PX-MDC model designed in this paper exhibits higher accuracy and is able to distinguish different deletion types for the same metabolite. This study is expected to make an important breakthrough in metabolomics data imputation and provide strong support for research in related fields.

New research for detecting complex associations between variables with randomness.

Many correlation analysis methods can capture a wide range of functional types of variables. However, the influence of uncertainty and distribution status in data is not considered, which leads to the neglect of the regularity information between variables, so that the correlation of variables that contain functional relationship but subject to specific distributions cannot be well identified. Therefore, a novel correlation analysis framework for detecting associations between variables with randomness (RVCR-CA) is proposed. The new method calculates the normalized RMSE to evaluate the degree of functional relationship between variables, calculates entropy difference to measure the degree of uncertainty in variables and constructs the copula function to evaluate the degree of dependence on random variables with distributions. Then, the weighted sum method is performed to the above three indicators to obtain the final correlation coefficient R. In the study, which considers the degree of functional relationship between variables, the uncertainty in variables and the degree of dependence on the variables containing distributions, cannot only measure the correlation of functional relationship variables with specific distributions, but also can better evaluate the correlation of variables without clear functional relationships. In experiments on the data with functional relationship between variables that contain specific distributions, UCI data and synthetic data, the results show that the proposed method has more comprehensive evaluation ability and better evaluation effect than the traditional method of correlation analysis.

Analysing pharmacodynamic interactions of traditional Chinese medicine in treating acute pancreatitis based on OPLS method.

Acute pancreatitis (AP) is a surgical abdominal disease for which the Dachengqi Decoction (DCQD) of traditional Chinese medicine (TCM) is widely used in China. This study aims to analyse the pharmacodynamic interactions and quantitative relationship of DCQD in the treatment of AP based on orthogonal partial least squares (OPLS) analysis. The experimental data show organic chemical components as candidate pharmacodynamic substances (PS) in the blood and include pharmacodynamic indicators (PIs). Taking each PI as the target and using OPLS method to construct three types of mathematical equations, including the mathematical relationship between the pharmacodynamic substances and each target pharmacodynamic indicator (PS-TPI); the mathematical relationship between the pharmacodynamic substances, the pharmacodynamics indicators and each target pharmacodynamic indicator (PS, PI-TPI); and the mathematical relationship between the pharmacodynamic indicators and each target pharmacodynamic indicator (PI-TPI). Through analysis, we find that the R2Y(cum) values and VIP values indicate that PS and PI are the follow-up factors of TPI; the coefficient value indicates that there is a quantitative relationship between the PS and the TPI; and there also is a quantitative relationship between PI and TPI. The results demonstrated that PS and other PIs are the important influencing factors of TPI, and that there are interactions and quantitative relationships among the PIs.

Hybrid mRMR and multi-objective particle swarm feature selection methods and application to metabolomics of traditional Chinese medicine.

Metabolomics data has high-dimensional features and a small sample size, which is typical of high-dimensional small sample (HDSS) data. Too high a dimensionality leads to the curse of dimensionality, and too small a sample size tends to trigger overfitting, which poses a challenge to deeper mining in metabolomics. Feature selection is a valuable technique for effectively handling the challenges HDSS data poses. For the feature selection problem of HDSS data in metabolomics, a hybrid Max-Relevance and Min-Redundancy (mRMR) and multi-objective particle swarm feature selection method (MCMOPSO) is proposed. Experimental results using metabolomics data and various University of California, Irvine (UCI) public datasets demonstrate the effectiveness of MCMOPSO in selecting feature subsets with a limited number of high-quality features. MCMOPSO achieves this by efficiently eliminating irrelevant and redundant features, showcasing its efficacy. Therefore, MCMOPSO is a powerful approach for selecting features from high-dimensional metabolomics data with limited sample sizes.

Classification method of traditional Chinese medicine compound decoction duration based on multi-dimensional feature weighted fusion.

This paper extends a text classification method utilizing natural language processing (NLP) into the field of traditional Chinese medicine (TCM) compound decoction to effectively and scientifically extend the TCM compound decoction duration. Specifically, a TCM compound decoction duration classification named TCM-TextCNN is proposed to fuse multi-dimensional herb features and improve TextCNN. Indeed, first, we utilize word vector technology to construct feature vectors of herb names and medicinal parts, aiming to describe the herb characteristics comprehensively. Second, considering the impact of different herb features on the decoction duration, we use an improved Term Frequency-Inverse Word Frequency (TF-IWF) algorithm to weigh the feature vectors of herb names and medicinal parts. These weighted feature vectors are then concatenated to obtain a multi-dimensional herb feature vector, allowing for a more comprehensive representation. Finally, the feature vector is input into the improved TextCNN, which uses k-max pooling to reduce information loss rather than max pooling. Three fully connected layers are added to generate higher-level feature representations, followed by softmax to obtain the final results. Experimental results on a dataset of TCM compound decoction duration demonstrate that TCM-TextCNN improves accuracy, recall, and F1 score by 5.31%, 5.63%, and 5.22%, respectively, compared to methods solely rely on herb name features, thereby confirming our method's effectiveness in classifying TCM compound decoction duration.

A non-linear partial least squares based on monotonic inner relation.

A novel regression model, monotonic inner relation-based non-linear partial least squares (MIR-PLS), is proposed to address complex issues like limited observations, multicollinearity, and nonlinearity in Chinese Medicine (CM) dose-effect relationship experimental data. MIR-PLS uses a piecewise mapping function based on monotonic cubic splines to model the non-linear inner relations between input and output score vectors. Additionally, a new weight updating strategy (WUS) is developed by leveraging the properties of monotonic functions. The proposed MIR-PLS method was compared with five well-known PLS variants: standard PLS, quadratic PLS (QPLS), error-based QPLS (EB-QPLS), neural network PLS (NNPLS), and spline PLS (SPL-PLS), using CM dose-effect relationship datasets and near-infrared (NIR) spectroscopy datasets. Experimental results demonstrate that MIR-PLS exhibits general applicability, achieving excellent predictive performances in the presence or absence of significant non-linear relationships. Furthermore, the model is not limited to CM dose-effect relationship research and can be applied to other regression tasks.

Trends and future projections of liver cancer incidence in Hong Kong: a population-based study.

BACKGROUND: Liver cancer remains a significant burden in Hong Kong. We sought to examine trends in liver cancer incidence using 30 years of cancer registry data in Hong Kong. Additionally, we aimed to assess the impact of age, period and birth cohort on liver cancer incidence, provided projections for liver cancer incidence until 2030, and examined the drivers of liver cancer incidence. METHODS: Data on liver cancer incidence were collected from the Hong Kong Cancer Registry (HKCaR). We assessed age, period, and birth cohort effects using age-period-cohort (APC) models. We employed Bayesian APC analysis with integrated nested Laplace approximations to project the future burden of liver cancer in Hong Kong. Furthermore, we attributed the changes in new liver cancer cases to population growth, population ageing, and epidemiological changes. RESULTS: The study included a total of 51,333 individuals, of whom 39,287 (76.53%) were male. From 1991 to 2020, the age-standardized liver cancer incidence rate in Hong Kong continued declining, while the number of new cases increased significantly, especially among males. The net drift, representing the overall annual percentage change of the age-adjusted rate, was - 3.06% (95% confidence interval [CI]: -3.31% to -2.80%) for males and - 3.85% (95% CI: -4.61% to -3.09%) for females. Local drift, which estimates the annual percentage change over time specific to age group, decreased in all age groups for both sexes, with a more pronounced decrease in younger age groups. The period and cohort risk of developing liver cancer also showed decreasing trends for both sexes. The study projected a decline in liver cancer cases for males but an increase for females in Hong Kong, with an estimated 1,083 cases in males and 710 cases in females by 2030. Demographic decomposition analysis revealed that while population growth and ageing were the main drivers of increased liver cancer cases, epidemiologic shifts mostly offset these factors. CONCLUSION: The period and cohort risk of developing liver cancer in Hong Kong declined due to epidemiological changes. Although the age-standardized incidence rates of liver cancer have also declined, demographic and epidemiological factors have led to lower case expectations in males but a likely increase in females. Further research and epidemiological assessment of the disease are needed.

Topical streptomycin irrigation of lesions to prevent postoperative site infections in spinal tuberculosis: a retrospective analysis.

PURPOSE: In spinal tuberculosis surgery, topical administration of drugs to the lesion is a preventive treatment measure. The aim is to achieve better bacterial inhibition and to prevent complications. As one of the most common complications after spinal tuberculosis surgery, many factors can lead to surgical site infection (SSI). No definitive reports of local streptomycin irrigation of the lesion and SSI of spinal tuberculosis have been seen. This study analyzed data related to surgical site infections (SSI) after the treatment of spinal tuberculosis using this regimen. METHODS: In this study, 31 were in the observation group (streptomycin flush) and 34 in the control group (no streptomycin flush). All patients received the same standard of perioperative care procedures. General information, operative time, intraoperative bleeding, ESR and CRP at one week postoperatively, time on antibiotics, total drainage, days in hospital, incision infection rate and secondary debridement rate were compared between the two groups. RESULTS: Patients in both groups completed the surgery successfully. The ESR and CRP levels in the observation group were lower than those in the control group one week after surgery (p < 0.05); the duration of postoperative antibiotics and hospital stay were lower than those in the control group (p < 0.05); the incidence of SSI in the two groups was 5.88% and 6.45% respectively, with no significant difference (p > 0.05). CONCLUSION: The use of topical streptomycin irrigation of the lesion during surgical procedures for spinal tuberculosis had no significant effect on the incidence of SSI, however, it helped to control the level of infection in the postoperative period and reduced the length of time patients had to use postoperative antibiotics and the number of days they stayed in hospital. Future prospective randomised controlled trials in more centres and larger samples are recommended.

Trends of non-melanoma skin cancer incidence in Hong Kong and projection up to 2030 based on changing demographics.

OBJECTIVE: To assess the trends in non-melanoma skin cancer (NMSC) incidence in Hong Kong from 1990 to 2019 and the associations of age, calendar period, and birth cohort, to make projections to 2030, and to examine the drivers of NMSC incidence. METHODS: We assessed the age, calendar period, and birth cohort effects of NMSC incidence in Hong Kong between 1990 and 2019 using an age-period-cohort model. Using Bayesian age-period-cohort analysis with integrated nested Laplace approximations, we projected the incidence of NMSC in Hong Kong to 2030. RESULTS: From 1990 to 2019, the age-standardized incidence rate of NMSC increased from 6.7 per 100,000 population to 8.6 per 100,000 population in men and from 5.4 per 100,000 to 5.9 per 100,000 population in women, among the 19,568 patients in the study (9812 male patients [50.14%]). The annual net drift was 2.00% (95% confidence interval [CI]: 1.50-2.50%) for men and 1.53% (95% CI: 0.95-2.11%) for women. Local drifts increased for both sexes above the 35-39-year age group. The period and cohort risk of developing NMSC tended to rise but slowed gradually in the most recent period and post-1975 birth cohort. From 2019 to 2030, it is projected that the number of newly diagnosed NMSC cases in Hong Kong will increase from 564 to 829 in men and from 517 to 863 in women. Population aging, population growth, and epidemiologic changes contributed to the increase in incident NMSCs, with population aging being the most significant contributor. CONCLUSION: The slowing of the period and cohort effects suggests that the rising incidence of NMSC is partly attributable to increased awareness and diagnosis. The increasing prevalence of NMSC among the elderly and an aging population will significantly impact the clinical workload associated with NMSC for the foreseeable future.