BACKGROUND: Gastric cancer is a major health problem worldwide, with a high incidence among older adults. Given the aging overall population, it was crucial to understand the current burden and prospective trend of older gastric cancer. This study aimed to analyze the temporal trends of the incidence, mortality, and survival of older gastric cancer in the highest gastric cancer risk area in China from 2010 to 2019, and to predict the future burden of older gastric cancer up to 2024.
METHODS: The study was conducted in Gansu province, an area characterized by the highest gastric cancer incidence and mortality in China. The registration data of gastric cancer incidence and mortality from 2010 to 2019 were pooled from registries in the Gansu Cancer Registration System, while survival data were collected from the First Hospital of Lanzhou University, Lanzhou University Second Hospital, and Gansu Cancer Hospital. Chinese standard population in 2000 and the Segi\'s world standard population were applied to calculate the age-standardized rate. Joinpoint regression was used to analyze the average annual percentage change (AAPC) in cancer incidence and mortality. Autoregressive Integrated Moving Average (ARIMA) models were employed to generate forecasts for incidence and mortality from 2020 to 2024.
RESULTS: Based on registry data from 2010 to 2019, the incidence and mortality rates of gastric cancer among older adults remained stable. The incidence rates declined from 439.65 per 100,000 in 2010 to 330.40 per 100,000 in 2019, with an AAPC of -2.59% (95% confidence interval[CI], -5.14 to 0.04, P = 0.06). Similarly, the mortality rate changed from 366.98 per 100,000 in 2010 to 262.03 per 100,000 in 2019, with an AAPC of -2.55% (95% CI, -8.77-4.08%, P = 0.44). In the hospital-based cohort, the decline in survival rates was reported among older patients with gastric cancer in the highest gastric cancer risk area in China, with the 3-year overall survival (OS) decreasing from 58.5% (95% CI, 53.5-63.2%) in 2010 to 34.4% (95%CI, 32.1-36.7%) in 2019, and the 3-year progression-free survival (PFS) decreasing from 51.3% (95%CI, 47.5-55.1%) in 2010 to 34.2% (95%CI, 32.0-36.3%) in 2019, respectively. Moreover, forecasts generated by ARIMA models revealed a significant decline in the incidence and mortality of older gastric cancer in China from 2020 to 2024. Specifically, the incidence rate of older gastric cancer was expected to decrease from 317.94 per 100,000 population in 2020 to 205.59 per 100,000 population in 2024, while the anticipated mortality rate was estimated to decrease from 222.52 per 100,000 population in 2020 to 186.22 per 100,000 population in 2024.
CONCLUSIONS: From 2010 to 2019, the incidence and mortality of older gastric cancer remained stable in the highest gastric cancer risk area in China, while the survival rates showed a decline. Based on the ARIMA models, it was anticipated that there might be a continued decline in older gastric cancer incidence and mortality in the highest-risk area in China over the next five years.

Quantifying the impact of competition on individual tree biomass and its distribution pattern can provide a basis for improving the prediction accuracy of forest biomass models. To accurately quantify the effects of competition factors on individual biomass and its distribution, we constructed three different individual biomass models by using nonlinear coupling equations based on the biomass survey data of 50 Larix gmelinii from 18 plots of Pangu Forest Farm in Daxing\'an Mountains. M-1 was a traditional singly additive biomass model. M-2 and M-3 were models taking the distance dependent simple competition index (CI) and distance independent relative diameter (Rd) into account, respectively. Those models were used to reveal the influence of competition factors on the prediction accuracy and distribution pattern of single tree biomass model of L. gmelinii. The results showed that the adjusted R2 of three additive models ranged from 0.694 to 0.974, mean prediction errors ranged from -0.017 to 0.021, and mean absolute errors ranged from 0.152 to 0.357. The introduction of Rd could improve the fitting degree and prediction accuracy of most biomass models, but CI did not affect the model fitting effect and prediction ability. Among the three models, M-3 model had the best performance, with good fitting degree and prediction accuracy of the biomass of each part, which could accurately estimate the single tree biomass of L. gmelinii. Further simulation results showed that the variation of biomass with DBH was mainly affected by CI and Rd grade, and the influence of Rd was stronger than CI. CI had greater influence on root and dry biomass, but less influence on branch and leaf biomass. Rd had a more significant effect on biomass of branch and leaf than on that of root and trunk.
量化竞争对单木生物量及其分配格局的影响,可以为提高林木生物量模型预估精度提供基础。本研究以大兴安岭地区盘古林场18块固定样地中50株兴安落叶松的生物量调查数据为基础,采用非线性联立方程组构建含不同竞争因子(与距离有关的简单竞争指标CI和与距离无关的林木相对直径Rd)的对数尺度单木聚合型二元可加性生物量模型M-2和M-3,并与传统一元可加性生物量模型M-1进行比较,量化竞争因子对兴安落叶松天然林单木生物量模型预估精度及其分配格局的影响。结果表明: 3种可加性模型的调整后确定系数为0.694～0.974,平均预测误差为-0.017～0.021,平均绝对误差为0.152～0.357。引入Rd可以提高绝大多数生物量模型的拟合效果和预测能力,而引入CI对绝大多数生物量模型拟合效果和预测能力的影响不显著。3种模型中,M-3对各部分生物量具有较好的拟合效果和预测能力,可以对兴安落叶松单木生物量进行较好的估计。模拟结果显示,生物量随胸径的变化受CI、Rd等级的影响,其中Rd较CI影响更大;CI对树根和树干生物量影响较大,对树枝、树叶生物量影响较小;Rd对树枝、树叶生物量的影响较树根、树干生物量更大。.

\"Planting conifer and reserving broadleaved tree\" is an effective way to restore broad-leaved pine forest of temperate zone in Northeast China. Liberation cutting can promote the growth of Korean pine (Pinus koraiensis) under forest crown and accelerate the succession. However, how liberation cutting intensity affects the growth of Korean pine in secondary forest is still unclear. Taking the \"Planting conifer and reserving broadleaved tree\" Korean pine forest in Changbai Mountain as the object, we constructed a growth model of diameter at breast height (DBH) and tree height of Korean pine with double dummy variables (liberation cutting intensity and tree classification) to predict the growth of Korean pine plantation under different liberation cutting intensities, i.e. control (no liberation cutting), light-intensity liberation cutting (retaining upper canopy closure 0.6), medium-intensity liberation cutting (0.4), heavy-intensity liberation cutting (0.2) and clear cutting (cutting all upper broadleaf trees) stands. We analyzed the effects of liberation cutting intensities on DBH, tree height, and the ratio of tree height to DBH. The results showed that among six theoretical growth equations, the Gompertz model on the DBH (R2=0.46) and tree height (R2=0.81) was optimal basic model. The R2 of the DBH model was increased to 0.65 and 0.89, respectively, after the single dummy variable and the double dummy variable were introduced into the basic model, while the R2 of the tree height model was increased to 0.84 and 0.94. Therefore, the double dummy variable model was the most suitable for predicting the growth of Korean pine. The growth of DBH of pressed tree increased with the increases of liberation cutting intensity (increase by 145.8%-933.3%) during the whole simulation period (0-80 a). Average and dominant trees showed the same pattern at 42 and 60 a. In the early and middle stages of liberation cutting (20 and 42 a), clear cutting and heavy-intensity liberation cutting had similar effects on the height growth of dominant trees (64.8%-68.5%), average trees (100.0%-144.2%), and pressed trees (138.5%-183.9%). The effects of medium-intensity liberation cutting and light-intensity liberation cutting on the height growth were similar (24.3%-35.1%, 56.0%-92.3%, 84.6%-103.2%). While in the middle and late period (42 and 80 a), height growth of three grade trees increased with the increases of liberation cutting intensity. Under each liberation cutting intensity, the ratio of height to DBH of the dominant, average, and pressed trees increased successively, ranging from 0.50-0.95, 0.64-1.23, and 0.73-4.33, respectively. Only the pressed tree decreased with the increases of liberation cutting intensity at 0-80 a. Therefore, about 40 years after the implementation of liberation cutting, the promoting effect of different liberation cutting intensities on DBH growth was significantly weakened, the promoting effect on tree height growth was significantly enhanced, and the ratio of tree height to diameter began to increase. In order to alleviate forest competition, second liberation cutting should be carried out for light-intensity liberation cutting and medium-intensity liberation cutting stands to further release the growth potential of Korean pine, and thinning management should be carried out in clear cutting and heavy-intensity liberation cutting stands.
“栽针保阔”是恢复我国东北阔叶红松林的有效途径,透光抚育能促进冠下红松生长并加快演替进程,但目前有关透光抚育如何影响次生林内红松生长过程仍不清楚。以长白山“栽针保阔”红松林为对象,构建含双哑变量(透光抚育强度和林木分级)的红松胸径和树高生长模型来预测不同透光抚育强度[即对照(未透光)、轻度透光抚育(保留上层郁闭度0.6)、中度透光抚育(0.4)、强度透光抚育(0.2)和全透光(伐除全部上层阔叶树)]林分中红松三级木的生长过程,揭示透光抚育强度对林内红松胸径和树高及高径比的影响规律。结果表明: 6个基础模型中,Gompertz为红松胸径(R2=0.46)和树高(R2=0.81)最优基础模型,在基础模型中引入透光抚育强度单哑变量、双哑变量后胸径模型的R2分别提高至0.65和0.89,树高模型的R2分别提高至0.84和0.94;双哑变量模型为预测红松生长的最适模型。被压木胸径生长在整个模拟预测期间(树龄0～80年)均随透光抚育强度增大而递增(增幅为145.8%～933.3%),而平均木和优势木在中期(42年)、中后期(60年)呈此规律。在初期(20年)和中期,全透光与强度透光抚育对红松优势木(64.8%～68.5%)、平均木(100.0%～144.2%)和被压木(138.5%～183.9%)树高生长的影响程度相近,中度透光抚育和轻度透光抚育对其影响相近(24.3%～35.1%、56.0%～92.3%和84.6%～103.2%);在中后期(62年)和后期(80年),红松三级木树高生长均随透光抚育强度增大而递增。各透光抚育强度下红松优势木、平均木和被压木的高径比变化幅度依次增大,分别为0.50～0.95、0.64～1.23和0.73～4.33;仅被压木在树龄0～80年随透光抚育强度增大而递减。因此,透光抚育约40年后,其对红松的胸径生长的促进作用减弱而对树高的促进作用却增强,而且高径比提高,故此时为缓解林木竞争,对轻度透光抚育、中度透光抚育的林分应进行二次透光抚育以进一步促进红松生长,而对全透光和强度透光抚育林分应进行间伐。.

BACKGROUND: Machine learning (ML) is extensively employed for forecasting the outcome of various illnesses. The objective of the study was to develop ML based classifiers using a stacking ensemble strategy to predict the Japanese Orthopedic Association (JOA) recovery rate for patients with degenerative cervical myelopathy (DCM).
METHODS: A total of 672 patients with DCM were included in the study and labeled with JOA recovery rate by 1-year follow-up. All data were collected during 2012-2023 and were randomly divided into training and testing (8:2) sub-datasets. A total of 91 initial ML classifiers were developed, and the top 3 initial classifiers with the best performance were further stacked into an ensemble classifier with a supported vector machine (SVM) classifier. The area under the curve (AUC) was the main indicator to assess the prediction performance of all classifiers. The primary predicted outcome was the JOA recovery rate.
RESULTS: By applying an ensemble learning strategy (e.g., stacking), the accuracy of the ML classifier improved following combining three widely used ML models (e.g., RFE-SVM, EmbeddingLR-LR, and RFE-AdaBoost). Decision curve analysis showed the merits of the ensemble classifiers, as the curves of the top 3 initial classifiers varied a lot in predicting JOA recovery rate in DCM patients.
CONCLUSIONS: The ensemble classifiers successfully predict the JOA recovery rate in DCM patients, which showed a high potential for assisting physicians in managing DCM patients and making full use of medical resources.

BACKGROUND: This study examines global trends in acquired immune deficiency syndrome (AIDS) incidence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2019, focusing on regional disparities in AIDS incidence, mortality, and DALYs across various levels of socio-demographic index (SDI). It also investigates variations in AIDS incidence, mortality, and DALYs across different age groups, and projects specific trends for the next 25 years.
METHODS: Comprehensive data on AIDS from 1990 to 2019 in 204 countries and territories was obtained from a GBD study. This included information on AIDS incidence, mortality, DALYs, and age-standardized rates (ASRs). Projections for AIDS incidence and mortality over the next 25 years were generated using the Bayesian age-period-cohort model.
RESULTS: From 1990 to 2019, the global incidence of HIV cases increased from 1,989,282 to 2,057,710, while the age-standardized incidence rate (ASIR) decreased from 37.59 to 25.24 with an estimated annual percentage change (EAPC) of -2.38. The ASIR exhibited an upward trend in high SDI and high-middle SDI regions, a stable trend in middle SDI regions, and a downward trend in low-middle SDI and low SDI regions. In regions with higher SDI, the ASIR was higher in males than in females, while the opposite was observed in lower SDI regions. Throughout 1990 to 2019, the age-standardized death rate (ASDR) and age-standardized DALY rate remained stable, with EAPCs of 0.24 and 0.08 respectively. Countries with the highest HIV burden affecting women and children under five years of age are primarily situated in lower SDI regions, particularly in sub-Saharan Africa. Projections indicate a significant continued decline in the age-standardized incidence and mortality rates of AIDS over the next 25 years, for both overall and by gender.
CONCLUSIONS: The global ASIR decreased from 1990 to 2019. Higher incidence and death rates were observed in the lower SDI region, indicating a greater susceptibility to AIDS among women and < 15 years old. This underscores the urgent need for increased resources to combat AIDS in this region, with focused attention on protecting women and < 15 years old as priority groups. The AIDS epidemic remained severe in sub-Saharan Africa. Projections for the next 25 years indicate a substantial and ongoing decline in both age-standardized incidence and mortality rates.

UNASSIGNED: Leukemia imposes a large healthcare burden both in China and the United States (US). The disease burden differs greatly between the two countries, but related research is limited. We explored the differences in leukemia incidence and mortality between China and the US.
UNASSIGNED: Data on leukemia in China and the US from 1990 to 2021 were collected from the Global Burden of Disease 2021 database. Incidence and mortality were used to estimate the disease burden, and joinpoint regression was performed to compare their secular trends. We used an age-period-cohort model to analyze the effects of age, period, and birth cohort and project future trends in the next 15 years.
UNASSIGNED: In 2021, the age-standardized incidence rate (ASIR) and the age-standardized death rate (ASDR) of leukemia were lower in China than in the US. However, the incidence and mortality of acute lymphoblastic leukemia (ALL) was considerably higher in China. In the past decades, the ASIR showed decreased tendency in the US, while ASIR showed stable in China. The ASDR tended to decrease in both countries from 1990 to 2021. Males have higher rates of incidence and mortality than females in two countries. The age effects showed that children and older individuals have higher RRs for incidence and mortality in China, while the RRs for incidence and mortality in the US particularly increased in the older population. The disease burden of leukemia in children is obviously greater in China. The ASIRs and ASDRs of leukemia will continue to decline in the next 15 years in China and the US, with the US experiencing a more obvious downtrend.
UNASSIGNED: Over the past decades, the ASDRs in two countries both tended to decrease. And compared to the US, China had lower leukemia incidence and mortality, However, the ASIRs in China tended toward stable, which it was showed downtrend in the US. Children have obviously greater RRs for incidence and mortality in China. The incidence and mortality will decrease continuously in two countries. Effective intervention measures are needed to reduce the burden of leukemia.

BACKGROUND: Forecasting the intensity, source, and cost of informal care for older adults in China is essential to establish and enhance policy support systems for informal care within the context of East Asian traditional culture that emphasizes filial piety. This study aims to analyze the current situation and influencing factors for the informal care needs and predict the trends of informal care needs for older adults in China from 2020 to 2040.
METHODS: Using the CHARLS database from 2015 to 2018, this study first combined a two-part model and a multinomial logit to analyze the influencing factors for the informal care needs of urban-rural older adults in China. Secondly, a multi-state Markov model was constructed to forecast the number of urban-rural older populations in each health state from 2020 to 2040. Finally, based on a microsimulation model, this study predicted the trends of informal care intensity, source, and cost for older adults in urban and rural areas from 2020 to 2040.
RESULTS: In 2040, the size of the disabled older population in China will expand further. In rural areas, the total number of disabled people in 2040 (39.77 million) is 1.50 times higher than that in 2020; In urban areas, the total number of disabled people in 2040 (56.01 million) is 2.51 times higher than that in 2020. Compared with 2020, older adults population with mild, moderate and severe disability in 2040 would increase by 87.60%, 101.70%, and 115.08%, respectively. In 2040, the number of older adults receiving low-, medium-, and high-intensity care in China will be 38.60 million, 22.89 million, and 41.69 million, respectively, and older people will still rely on informal care provided by spouses and children (from spouses only: 39.26 million, from children only: 36.74 million, from spouses and children only: 16.79 million, other: 10.39 million). The total cost of informal care in 2040 will be 1,086.65 billion yuan, 2.22 times that of 2020 (490.31 billion yuan), which grows faster than the economic growth rate.
CONCLUSIONS: From 2020 to 2040, the informal care needs of older people in rural areas will increase first and then decrease due to the demographic structure and rapid urbanization. In contrast, the informal care needs of older people in urban areas will continuously increase from 2020 to 2040, with the growth rate gradually slowing down. This study provides an evidence-based rationale for scientifically measuring the economic value of informal care and reasonably allocating care resources.

In the current economic landscape, the growing importance of innovation and entrepreneurship underscores an urgent need for accurate market trend prediction. Addressing this challenge, our study introduces an innovative entrepreneurial market trend prediction model based on deep learning principles. Through detailed case studies and performance evaluations, this paper demonstrates the model\'s effectiveness and its potential to enhance decision-making capabilities in a competitive business environment. Accurate market trend prediction is crucial in the fields of innovation and entrepreneurship, and our approach meets this demand. Our model leverages the power of deep learning technology, combining historical market data with diverse market indicators, including sentiment analysis derived from social media, to create an advanced predictive model that surpasses traditional methods. By analyzing data from multiple channels, our model exhibits exceptional accuracy in forecasting future market trends. The case study provides strong evidence of our model\'s performance and precision, showcasing its significant support for innovators and entrepreneurs navigating complex market trends. Furthermore, this study highlights the vast potential of deep learning technology in the economic sector. We emphasize the importance of developing innovative entrepreneurial market trend prediction models and foresee an increase in project success rates for innovators and entrepreneurs by enhancing decision quality through the adoption of deep learning.

UNASSIGNED: A bibliometric analysis was conducted using VOSviewer and CiteSpace to examine studies published between 2009 and 2023 on the utilization of artificial intelligence (AI) in chronic obstructive pulmonary disease (COPD).
UNASSIGNED: On March 24, 2024, a computer search was conducted on the Web of Science (WOS) core collection dataset published between January 1, 2009, and December 30, 2023, to identify literature related to the application of artificial intelligence in chronic obstructive pulmonary disease (COPD). VOSviewer was utilized for visual analysis of countries, institutions, authors, co-cited authors, and keywords. CiteSpace was employed to analyze the intermediary centrality of institutions, references, keyword outbreaks, and co-cited literature. Relevant descriptive analysis tables were created using Excel2021 software.
UNASSIGNED: This study included a total of 646 papers from WOS. The number of papers remained small and stable from 2009 to 2017 but started increasing significantly annually since 2018. The United States had the highest number of publications among countries/regions while Silverman Edwin K and Harvard Medical School were the most prolific authors and institutions respectively. Lynch DA, Kirby M. and Vestbo J. were among the top three most cited authors overall. Scientific Reports had the largest number of publications while Radiology ranked as one of the top ten influential journals. The Genetic Epidemiology of COPD (COPDGene) Study Design was frequently cited. Through keyword clustering analysis, all keywords were categorized into four groups: epidemiological study of COPD; AI-assisted imaging diagnosis; AI-assisted diagnosis; and AI-assisted treatment and prognosis prediction in the COPD research field. Currently, hot research topics include explainable artificial intelligence framework, chest CT imaging, and lung radiomics.
UNASSIGNED: At present, AI is predominantly employed in genetic biology, early diagnosis, risk staging, efficacy evaluation, and prediction modeling of COPD. This study\'s results offer novel insights and directions for future research endeavors related to COPD.

UNASSIGNED: Leukaemia is a devastating disease with an incidence that progressively increases with advancing age. The World Health Organization has designated 2021-30 as the decade of healthy ageing, highlighting the need to address age-related diseases. We estimated the disease burden of leukaemia and forecasted it by 2030.
UNASSIGNED: Based on the Global Burden of Disease 2019 database, we systematically analysed the geographical distribution of leukaemia and its subtypes. We used Joinpoint regression and Bayesian age-period-cohort models to evaluate incidence and mortality trends from 1990 to 2019 and projections through 2030. We analysed five leukaemia subtypes and the impact of age, gender, and social development. Decomposition analysis revealed the effects of disease burden on ageing and population growth. We used frontier analysis to illustrate the potential of each country to reduce its burden based on its development levels.
UNASSIGNED: Globally, the absolute numbers of leukaemia incidence and mortality have increased, while the age-standardised rates (ASRs) have shown a decreasing trend. The disease burden was more pronounced in men, the elderly, and regions with a high socio-demographic index (SDI), where ageing and population growth played varying roles across subtypes. From 2000 to 2006, disease burdens were most effectively controlled. Global ASRs of incidence might stabilise, while ASRs of death are expected to decrease until 2030. Frontier analysis showed that middle and high-middle SDI countries have the most improvement potential. Smoking and high body mass index were the main risk factors for leukaemia-related mortality and disability-adjusted life years.
UNASSIGNED: The absolute number of leukaemia cases has increased worldwide, but there has been a sharp decline in ASRs over the past decade, primarily driven by population growth and ageing. Countries with middle and high-middle SDI urgently need to take action to address this challenge.