Objective To systematically analyze the characteristics of the disease burden of hypertensive heart disease (HHD) in the elderly (≥60 years) globally and in China from 1990 to 2021, and to predict its future trends from 2022 to 2040, with the aim of providing data support for optimizing comprehensive prevention and control strategies for HHD. Methods Based on the Global Burden of Disease (GBD) 2021 database, the number of prevalent cases and disability-adjusted life years (DALYs) of HHD in the elderly were extracted for the world, China, and five regions categorized by sociodemographic index (SDI). Joinpoint regression was used to analyze the temporal trends of age-standardized prevalence rate and age-standardized DALYs rate of HHD in the elderly. A three-factor decomposition method was applied to evaluate the relative contributions of aging, population growth, and epidemiological changes to the variations in the elderly HHD burden. Additionally, a Bayesian age-period-cohort model was used to predict the elderly HHD burden from 2022 to 2040. Results In 2021, the number of prevalent elderly HHD cases reached 10 283 000 globally and 3 412 400 in China, representing increases of 179.20% and 159.20% respectively, compared with 1990. The DALYs of elderly HHD were 18 812 700 person-years globally and 4 731 400 person-years in China, rising by 76.08% and 29.45% respectively from 1990. Meanwhile, the growth rates of the number of prevalent cases and DALYs of elderly HHD varied across different SDI regions. From 1990 to 2021, the age-standardized prevalence rate of elderly HHD in China, as well as the age-standardized DALYs rate of elderly HHD both globally and in China, showed significant downward trends (all average annual percentage changes<0, all P<0.001). In 2021, the 70-74 years age group accounted for the highest proportion of prevalent cases and DALYs of elderly HHD, both globally and in China. Decomposition analysis revealed that population growth was the dominant factor driving the increase in the elderly HHD burden across all regions. The prediction model results indicated that the number of prevalent cases and DALYs of elderly HHD would continue to rise globally and in China from 2022 to 2040, with the growth rate of the elderly HHD burden in China between 2021 and 2040 expected to exceed the global average. Conclusion Over the past 32 years, although the age-standardized disease rates of elderly HHD have mainly shown a downward trend globally and in China, the absolute number of the disease burden has increased substantially. The projection model indicates a continued upward trajectory, with the growth rate in China higher than the global average. Therefore, there is an urgent need to implement precise prevention and control strategies to effectively mitigate the disease burden of elderly HHD.

Accommodative dysfunction, particularly accommodative lag, acts as a core hub connecting near work activity to myopic axial elongation. This review thoroughly explores the multidimensional biological mechanisms by which accommodative function drives axial growth. In addition to the classic pathway where hyperopic defocus signals induce retinal-choroidal-scleral biochemical remodeling, two other mechanisms are highlighted: a biomechanical pathway involving direct mechanical traction on the equatorial sclera caused by sustained ciliary muscle contraction, and a neural pathway where abnormal accommodative micro fluctuations degrade retinal image quality, thereby triggering abnormal ocular growth. Based on these comprehensive mechanisms, this paper systematically analyzes the principles of pharmacological(atropine), optical(orthokeratology, defocus lenses), and vision therapy interventions. Myopia progression results from the integrated regulation of optical defocus, mechanical stress, and neural dynamics. Future myopia control should advance toward precise, personalized combination strategies tailored to individual accommodative and genetic profiles.

Objective To develop and validate a predictive model for autologous arteriovenous fistula(AVF)maturation in hemodialysis patients using conventional ultrasonography and three-dimensional speckle tracking imaging.Methods This case-control study enrolled 200 AVF patients from Chongqing Hospital of Traditional Chinese Medicine from July 2021 to June 2024.Clinical data,vascular ultrasound,and cardiac ultrasound parameters were systematically collected.After applying predefined inclusion criteria,186 patients were stratified into 2 cohorts based on arteriovenous fistula(AVF)maturation status:the spontaneous maturation group(n=111)and the assisted maturation requirement group(n=75).Comparative analysis between the 2 cohorts was conducted using univariate and multivariate logistic regression for variable selection,leading to the construction of a predictive model(model1)for spontaneous AVF maturation.A nomogram was subsequently developed based on model1.Internal validation was performed through 1 000 bootstrap resamples with calibration curve analysis.Model discrimination was quantified by the area under the receiver operating characteristic curve(AUC),while clinical utility was assessed via decision curve analysis(DCA).After excluding 104 patients lacking three-dimensional speckle tracking echocardiography data,the remaining 82 subjects were included in novel predictive model development.Three strain parameters,two-dimensional global longitudinal strain(2DGLS),three-dimensional global longitudinal strain(3DGLS),and three-dimensional left ventricular ejection fraction(3DEF),were independently incorporated into multivariable logistic regression analyses to establish three distinct models(designated as model2,model3 and model4 respectively).Model comparisons employed AUC,net reclassification improvement(NRI),and integrated discrimination improvement(IDI).Results Independent predictors for model1 included:2DEF(OR=1.133,95%CI:1.058～1.213),mid-cephalic vein depth(OR=1.453,95%CI:1.068～1.978),distal cephalic vein diameter(OR=2.141,95%CI:1.120～4.091),post-occlusive brachial artery resistance index(OR=0.004,95%CI:0.000～0.140),and postoperative brachial flow(OR=1.004,95%CI:1.002～1.007).model1 demonstrated excellent discrimination(AUC=0.869,95%CI:0.817～0.921)and calibration(mean absolute error=0.017).DCA showed superior net benefit at 0.1～1.0 threshold probabilities.Compared with model1,non-significant improvements in AUC and IDI,while model4 achieved significant NRI improvements(P<0.05).Conclusion The prediction performance of AVF natural maturity prediction models constructed with 2DGLS,3DGLS,3DEF,or 2DEF is relatively high;The NRI of the model involving 3DEF is better than that of the model involving 2DEF,indicating that it may have better clinical application value within a specific threshold probability range.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

In this study,a sensitive lateral flow immunoassay(LFIA)platform based on carbon dots-mesoporous silica nanocomposite(CD-MSNs)fluorescent probes was constructed for high-performance detection of inflammatory marker interleukin-6(IL-6).Green fluorescent carbon dots(CDs)were prepared by hydrothermal method with 3,9-perylenic acid and 3-aminopropyltriethoxysilane(APTES)as raw materials,and highly fluorescent CD-MSNs composites were then constructed by encapsulating the prepared CDs in mesoporous silica nanoparticles(MSNs).Fluorescent probes were prepared by covalent coupling of CD-MSNs with IL-6 antibody.Fluorescent immunochromatographic test strips were constructed by spraying IL-6 capture antibody and goat anti-mouse IgG on nitrocellulose membrane as detection line(T-line)and quality control line(C-line),respectively.The fluorescence immunoassay analyzer was used to quantitatively detect the fluorescence intensity of T-line,and the experimental results showed that the LFIA platform based on this probe had a good linear relationship in IL-6 concentration range of 102-106 pg/mL,and the detection limit was 64 pg/mL,which was two orders of magnitude more sensitive than that of the traditional colloidal gold test strips.This method effectively solved the issue of insufficient sensitivity of traditional LFIA technique,and provided a rapid and highly sensitive detection method for early diagnosis of inflammatory diseases.

ObjectiveTo improve the efficacy of Astragalus membranaceus (Fisch.) Bunge (A. membranaceus, Huang Qi), and to further develop and utilize it, fermentation technology was applied to the stem and leaf of A. membranaceus to enhance its immune function.MethodsIn this study, we fermented A. membranaceus stem and leaf (ASL) with probiotics and investigated its immune function. Firstly, we screened suitable strains for ASL fermentation and optimized the fermentation process. Secondly, we determined the antioxidant capacity of fermented ASL and its effect on inflammation in mouse monocyte-macrophage cell. Finally, the immunocompromised mice were treated with fermented ASL to investigate the changes in their immune ability.ResultsAmong the 10 selected probiotics, Lactobacillus plantarum was the most suitable strain for ASL fermentation. After optimization of the fermentation process, the content of saponins in fermented ASL was significantly increased. The fermented ASL exhibited strong anti-inflammatory and antioxidant activities in vitro. The in vivo immune efficacy improved by promoting the development of the spleen and thymus, as well as raising the immunoglobulin M, tumor necrosis factor-α, and interleukin-1β levels of in the serum.ConclusionThis study contributes to developing the non-medicinal parts of A. membranaceus, expands its medicinal resources, highlights the potential of fermentation technology to enhance these parts, and provides a reference for further development. Based on this approach, we can promote using non-medicinal parts of herbal medicines, minimize drug waste, and offer a reference for developing non-medicinal components in Chinese herbal medicines.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

ObjectiveTo investigate the effect of laminin subunit α3 （LAMA3） on the epithelial-mesenchymal transition （EMT）， invasion， and metastasis abilities of pancreatic cancer （PC）. MethodsA comprehensive analysis was performed for tumor- and EMT-related databases to identify the EMT genes associated with PC， especially LAMA3. The methods of qRT-PCR and Western blot were used to measure the expression level of LAMA3 in PC tissue and cell lines； immunofluorescence assay was used to determine the localization of LAMA3 in PANC-1 cells； Transwell assay was used to investigate the effect of LAMA3 on the invasion and migration abilities of PC cells. The t-test was used for comparison of continuous data between groups. ResultsThe analysis of the TCGA database identified 3 EMT-related oncogenes for PC， i.e.， LAMA3， AREG， and SDC1. The LASSO-Cox regression model showed that LAMA3 had the most significant impact on the prognosis of PC （risk score=0.256 1×LAMA3+0.043 1×SDC1+0.071 4×AREG）. The Cox model and nomogram showed that the high expression of LAMA3 was an independent risk factor for the poor prognosis of PC （hazard ratio=1.32， 95% confidence interval： 1.07‍ ‍—‍ 1.62， P<0.01）. Experimental results showed that there was a significant increase in the expression of LAMA3 in pancreatic cancer tissue compared with the normal pancreatic tissue. Compared with the HPDE cell line， there were varying degrees of increase in the expression of LAMA3 in pancreatic cancer AsPC-1， BxPC-3， PANC-1， MIA PaCa-2， and SW1990 cell lines， with the highest expression level in PANC-1 cells. The enrichment analysis showed that LAMA3 was associated with the biological processes and signaling pathways such as EMT， collagen metabolism， extracellular matrix degradation， the TGF-β pathway， and the PI3K pathway. After the knockdown of LAMA3， there were significant reductions in the expression levels of N-Cadherin， Vimentin， and Snail， while there was a significant increase in the expression level of E-Cadherin. Transwell assay showed that there were significant reductions in the invasion and migration abilities of PANC-1 cells after the knockdown of LAMA3. ConclusionLAMA3 is highly expressed in PC and can promote the EMT， invasion， and migration of PC cells， and therefore， LAMA3 may be used as a novel diagnostic marker and a new therapeutic target for PC.

Maidong products are categorized into "Hang Maidong" and "Chuan Maidong". Since the Ming and Qing Dynasties, "Hang Maidong" has been regarded as having superior quality, but currently, it remains in name only in the market. This article reviewed historical materia medica and local chronicles from the Ming and Qing Dynasties and analyzed the historical evolution of Maidong production areas. The history of Maidong production in Zhejiang can be traced back to the Song Dynasty, and cultivation had already developed by at least the Ming Dynasty. During the Ming and Qing Dynasties, it was consistently used as a tribute. Ming Dynasty chronicles record "Chuan Maidong", which had already been cultivated on a large scale by the Qing Dynasty. "Hang Maidong" and "Chuan Maidong" share the same origin, with the former identifiable by the "gourd waist" shape of its tuberous root. Based on this, it can be inferred that the "Maimendong" herb illustrated in the Origins of Materia Medica(Ben Cao Yuan Shi) and the Maidong stored in the Qing Palace Imperial Pharmacy were both "Hang Maidong". The protection and development of the authentic "Hang Maidong" medicinal herb are urgently needed.
China ; Drugs, Chinese Herbal/history* ; History, 17th Century ; History, Ancient ; Medicine, Chinese Traditional/history* ; History, Medieval ; History, 16th Century ; History, 18th Century ; History, 15th Century ; Plants, Medicinal/chemistry* ; History, 19th Century ; History, 20th Century ; Humans ; Materia Medica/history* ; History, 21st Century

Small animal multimodal biomedical imaging refers to the integration of multiple imaging techniques within the same system or device to acquire comprehensive physiological and pathological information of small animals, such as mice and rats. With the continuous advancement of biomedical research, this cutting-edge technology has attracted extensive attention. Multimodal imaging techniques, based on diverse imaging principles, overcome the limitations of single-modal imaging through information fusion, significantly enhancing the overall system's sensitivity, temporal/spatial resolution, and quantitative accuracy. In the future, the integration of new materials and artificial intelligence will further boost its sensitivity and resolution. Through interdisciplinary innovation, this technology is expected to become the core technology of personalized medicine and expand its applications to drug development, environmental monitoring, and other fields, thus reshaping the landscape of biomedical research and clinical practice. This review summarized the progress on the application and investigation of multimodal biomedical imaging techniques, and discussed its development in the future.
Animals ; Multimodal Imaging/trends* ; Rats ; Mice ; Artificial Intelligence ; Diagnostic Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed