Polycystic ovary syndrome （PCOS） is one of the most prevalent gynecological diseases， and its incidence is increasing year by year， seriously affecting the physical and mental health of female patients. The pathogenesis of this disease is complex and has not been fully clarified. At present， PCOS is mainly treated by Western medicine， which， however， has poor efficacy and induces various adverse reactions. Therefore， developing safe and effective therapies has become a difficult problem that needs to be solved. Studies have confirmed that traditional Chinese medicine （TCM） can regulate phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）， mitogen-activated protein kinase/extracellular signal-regulated kinase （MAPK/ERK）， Toll-like receptor 4/nuclear factor-κB （TLR4/NF-κB）， transforming growth factor-β （TGF-β）/Smads， secreted glycoprotein/β-catenin （Wnt/β-catenin）， adenosine monophosphate-activated protein kinase （AMPK）， and advanced glycation endproduct/receptor for advanced glycation endproducts （AGE/RAGE） signaling pathways to ameliorate insulin resistance， inhibit inflammation and oxidative stress， regulate endocrine hormone disorders， and intervene in apoptosis and autophagy， thus alleviating the symptoms， slowing down the disease progression， and improving the ovarian function. The treatment of PCOS with TCM has demonstrated definite effects and high safety. Therefore， exploring this disease from cellular and molecular perspectives can provide a theoretical basis for its clinical treatment and new drug development. However， there is a lack of systematic reviews on the modulation of relevant signaling pathways by TCM in the treatment of PCOS. This article reviews the research progress in the treatment of PCOS with the active ingredients and compound prescriptions of TCM by regulating relevant signaling pathways in recent years， with the aim of providing evidence to support the promotion of TCM for treating PCOS in the future.

The European Society of Cardiology (ESC) released the "2024 ESC guidelines for the management of elevated blood pressure and hypertension" on August 30, 2024. This guideline updates the 2018 "Guidelines for the management of arterial hypertension." One notable update is the introduction of the concept of "elevated blood pressure" (120-139/70-89 mm Hg). Additionally, a new systolic blood pressure target range of 120-129 mm Hg has been proposed for most patients receiving antihypertensive treatment. The guideline also includes numerous additions or revisions in areas such as non-pharmacological interventions and device-based treatments for hypertension. This article interprets the guideline's recommendations on definition and classification of elevated blood pressure and hypertension, and cardiovascular disease risk assessment, diagnosing hypertension and investigating underlying causes, preventing and treating elevated blood pressure and hypertension. We provide a comparison interpretation with the 2018 "Guidelines for the management of arterial hypertension" and the "2017 ACC/AHA guideline on the prevention, detection, evaluation, and management of high blood pressure in adults."

ObjectiveTo study the changing law of appearance color and physicochemical properties of Angelicae Sinensis Radix Carbonisata（ASRC） during the processing by color space method combined with statistical analysis， so as to provide reference for determining the processing endpoint and evaluating the quality of the decoction pieces. MethodsTaking processing time（4， 8， 12， 16 min） and temperature（180， 200， 220， 240 ℃） as factors， ASRC decoction pieces with different processing degrees were prepared in a completely randomized design. Then， the brightness value（L^*）， red-green value（a^*）， yellow-blue value（b^*）， and total chromaticity value （E^*ab） of the decoction pieces were determined by spectrophotometer， the color difference value（ΔE） was calculated， and the data of colorimetric values were analyzed by discriminant analysis. At the same time， the pH， charcoal adsorption， and contents of tannins， 5-hydroxymethylfurfural（5-HMF）， tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide of ASRC with different processing degrees were determined by pH meter， ultraviolet and visible spectrophotometry and ultra-high performance liquid chromatography（UPLC）. Principal component analysis（PCA） was used to analyze the data of physicochemical indexes， after determining the processing technology of ASRC， the canonical discriminant function was established to distinguish the decoction pieces with different processing degrees， and leave-one-out cross validation was conducted. Finally， Pearson correlation analysis was used to explore the correlation between various physicochemical indexes and chromaticity values. ResultsWith the prolongation of the processing time， L^*， a^*， b^* and E^*ab all showed a decreasing trend， and the established discriminant model based on color parameters was able to distinguish ASRC with different processing degrees. The pH showed an increasing trend with the prolongation of processing time， and the charcoal adsorption， and the contents of tannins， 5-HMF， and tryptophan all showed an increasing and then decreasing trend. Among them， the charcoal adsorption， contents of tannin and 5-HMF reached their maximum values successively after processing for 8-12 min. While the contents of chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide decreased with the increase of processing time， with a decrease of 60%-80% at 8 min of processing. Therefore， the optimal processing time should be determined to be 8-12 min. PCA could clearly distinguish ASRC with different processing degrees， while temperature had no significant effect on the processing degree. The 12 batches of process validation results（10 min， 180-240 ℃） showed that except for 3 batches identified as class Ⅱ light charcoal， all other batches were identified as class Ⅲ standard charcoal， and the chromaticity values of each batch of ASRC were within the reference range of class Ⅱ-Ⅲ sample chromaticity values. The correlation analysis showed that the chromaticity values were negatively correlated with pH and charcoal adsorption， and positively correlated with contents of tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H， and ligustilide. And both pH and charcoal adsorption were negatively correlated with the contents of the above components， but the charcoal adsorption was positively correlated with the content of 5-HMF. ConclusionThe chromaticity values and the contents of various physicochemical indicators of ASRC undergo significant changes with the prolongation of processing time， and there is a general correlation between chromaticity values and various physicochemical indicators. Based on the changes in color and physicochemical indicators， the optimal processing time for ASRC is determined to be 8-12 min. This study reveals the dynamic changes of the relevant indexes in the processing of ASRC， which can provide a reference for the discrimination of the processing degree and the quantitative study of the processing endpoint.

Background: This study aimed to estimate temporal trends in metabolically unhealthy obesity (MUO) among United States (US) adults by age, sex, race/ethnicity, and income from 1999 to 2018. Methods: We included 17,230 non-pregnant adults from a nationally representative cross-sectional study, the National Health and Nutrition Examination Survey (NHANES). MUO was defined as body mass index ≥30 kg/m2 with any metabolic disorders in blood pressure, blood glucose, and blood lipids. The age-adjusted percentage of MUO was calculated, and linear regression models estimated trends in MUO. Results: The weighted mean age of adults was 47.28 years; 51.02% were male, 74.64% were non-Hispanic White. The age-adjusted percentage of MUO continuously increased in adults across all subgroups during 1999–2018, although with different magnitudes (all P<0.05 for linear trend). Adults aged 45 to 64 years consistently had higher percentages of MUO from 1999–2000 (34.25%; 95% confidence interval [CI], 25.85% to 42.66%) to 2017–2018 (42.03%; 95% CI, 35.09% to 48.97%) than the other two age subgroups (P<0.05 for group differences). The age-adjusted percentage of MUO was the highest among non-Hispanic Blacks while the lowest among non-Hispanic Whites in most cycles. Adults with high-income levels generally had lower MUO percentages from 1999–2000 (22.63%; 95% CI, 17.00% to 28.26%) to 2017–2018 (32.36%; 95% CI, 23.87% to 40.85%) compared with the other two subgroups. Conclusion This study detected a continuous linear increasing trend in MUO among US adults from 1999 to 2018. The persistence of disparities by age, race/ethnicity, and income is a cause for concern. This calls for implementing evidence-based, structural, and effective MUO prevention programs.

Background: This study aimed to estimate temporal trends in metabolically unhealthy obesity (MUO) among United States (US) adults by age, sex, race/ethnicity, and income from 1999 to 2018. Methods: We included 17,230 non-pregnant adults from a nationally representative cross-sectional study, the National Health and Nutrition Examination Survey (NHANES). MUO was defined as body mass index ≥30 kg/m2 with any metabolic disorders in blood pressure, blood glucose, and blood lipids. The age-adjusted percentage of MUO was calculated, and linear regression models estimated trends in MUO. Results: The weighted mean age of adults was 47.28 years; 51.02% were male, 74.64% were non-Hispanic White. The age-adjusted percentage of MUO continuously increased in adults across all subgroups during 1999–2018, although with different magnitudes (all P<0.05 for linear trend). Adults aged 45 to 64 years consistently had higher percentages of MUO from 1999–2000 (34.25%; 95% confidence interval [CI], 25.85% to 42.66%) to 2017–2018 (42.03%; 95% CI, 35.09% to 48.97%) than the other two age subgroups (P<0.05 for group differences). The age-adjusted percentage of MUO was the highest among non-Hispanic Blacks while the lowest among non-Hispanic Whites in most cycles. Adults with high-income levels generally had lower MUO percentages from 1999–2000 (22.63%; 95% CI, 17.00% to 28.26%) to 2017–2018 (32.36%; 95% CI, 23.87% to 40.85%) compared with the other two subgroups. Conclusion This study detected a continuous linear increasing trend in MUO among US adults from 1999 to 2018. The persistence of disparities by age, race/ethnicity, and income is a cause for concern. This calls for implementing evidence-based, structural, and effective MUO prevention programs.

Background: This study aimed to estimate temporal trends in metabolically unhealthy obesity (MUO) among United States (US) adults by age, sex, race/ethnicity, and income from 1999 to 2018. Methods: We included 17,230 non-pregnant adults from a nationally representative cross-sectional study, the National Health and Nutrition Examination Survey (NHANES). MUO was defined as body mass index ≥30 kg/m2 with any metabolic disorders in blood pressure, blood glucose, and blood lipids. The age-adjusted percentage of MUO was calculated, and linear regression models estimated trends in MUO. Results: The weighted mean age of adults was 47.28 years; 51.02% were male, 74.64% were non-Hispanic White. The age-adjusted percentage of MUO continuously increased in adults across all subgroups during 1999–2018, although with different magnitudes (all P<0.05 for linear trend). Adults aged 45 to 64 years consistently had higher percentages of MUO from 1999–2000 (34.25%; 95% confidence interval [CI], 25.85% to 42.66%) to 2017–2018 (42.03%; 95% CI, 35.09% to 48.97%) than the other two age subgroups (P<0.05 for group differences). The age-adjusted percentage of MUO was the highest among non-Hispanic Blacks while the lowest among non-Hispanic Whites in most cycles. Adults with high-income levels generally had lower MUO percentages from 1999–2000 (22.63%; 95% CI, 17.00% to 28.26%) to 2017–2018 (32.36%; 95% CI, 23.87% to 40.85%) compared with the other two subgroups. Conclusion This study detected a continuous linear increasing trend in MUO among US adults from 1999 to 2018. The persistence of disparities by age, race/ethnicity, and income is a cause for concern. This calls for implementing evidence-based, structural, and effective MUO prevention programs.

AIM: To analyze the clinical features and multimodal imaging features of peripapillary hyper-reflective ovoid mass-like structure(PHOMS).METHODS: Retrospective observation study. Totally 35 patients(56 eyes)with PHOMS that diagnosed in the Affiliated Eye Hospital of Nanjing Medical University from January 2020 to March 2024 were included in the study. All patients underwent fundus photography, fundus fluorescein angiography, fundus autofluorescence, optical coherence tomography, and B-ultrasound.RESULTS:PHOMS occurred across diverse age groups, with an insidious onset often detected incidentally during routine ophthalmic examinations. More patients came to hospital for refractive errors due to blurred vision The boundary of the optic disc is blurred on fundus photography, and the nasal eminence is more significant, showing a “C” shaped halo. No obvious abnormal fluorescence was observed on fundus autofluorescence and fundus fluorescein angiography during different periods. An elevated appearance in vary degrees with more prominent in the nasal parts was showed on different OCT scans. Vertical scanning on the nasal side of the optic disc showed the best PHOMS structure, which could be seen under the retinal nerve fiber layer and on the Bruch membrane, with sharply marginated hyper-reflective ovoid mass-like structures, and no shielding effect on the choroid. The higher the elevation, the larger the volume. Ocular B-mode ultrasound showed a pre-optic disc bulge on the posterior wall of the eyeball, and there was no strong signal echo in it.CONCLUSION:PHOMS can be found frequently in myopic patients and often asymptomatic. Transient vision loss and floaters may occur in symptomatic cases. The most typical OCT feature is a nasally located hyper-reflective ovoid structure with distinct margins.

Background: This study aimed to estimate temporal trends in metabolically unhealthy obesity (MUO) among United States (US) adults by age, sex, race/ethnicity, and income from 1999 to 2018. Methods: We included 17,230 non-pregnant adults from a nationally representative cross-sectional study, the National Health and Nutrition Examination Survey (NHANES). MUO was defined as body mass index ≥30 kg/m2 with any metabolic disorders in blood pressure, blood glucose, and blood lipids. The age-adjusted percentage of MUO was calculated, and linear regression models estimated trends in MUO. Results: The weighted mean age of adults was 47.28 years; 51.02% were male, 74.64% were non-Hispanic White. The age-adjusted percentage of MUO continuously increased in adults across all subgroups during 1999–2018, although with different magnitudes (all P<0.05 for linear trend). Adults aged 45 to 64 years consistently had higher percentages of MUO from 1999–2000 (34.25%; 95% confidence interval [CI], 25.85% to 42.66%) to 2017–2018 (42.03%; 95% CI, 35.09% to 48.97%) than the other two age subgroups (P<0.05 for group differences). The age-adjusted percentage of MUO was the highest among non-Hispanic Blacks while the lowest among non-Hispanic Whites in most cycles. Adults with high-income levels generally had lower MUO percentages from 1999–2000 (22.63%; 95% CI, 17.00% to 28.26%) to 2017–2018 (32.36%; 95% CI, 23.87% to 40.85%) compared with the other two subgroups. Conclusion This study detected a continuous linear increasing trend in MUO among US adults from 1999 to 2018. The persistence of disparities by age, race/ethnicity, and income is a cause for concern. This calls for implementing evidence-based, structural, and effective MUO prevention programs.

ObjectiveThis paper proposes a novel real-time bedside pulmonary ventilation monitoring method for the diagnosis of chronic obstructive pulmonary disease (COPD), based on electrical impedance tomography (EIT). Four indicators—center of ventilation (CoV), global inhomogeneity index (GI), regional ventilation delay inhomogeneity (RVDI), and the ratio of forced expiratory volume in one second to forced vital capacity (FEV₁/FVC)—are calculated to enable the spatiotemporal assessment of COPD. MethodsA simulation of the respiratory cycles of COPD patients was first conducted, revealing significant differences in certain indicators compared to healthy individuals. The effectiveness of these indicators was then validated through experiments. A total of 93 subjects underwent multiple pulmonary function tests (PFTs) alongside simultaneous EIT measurements. Ventilation heterogeneity under different breathing patterns—including forced exhalation, forced inhalation, and quiet tidal breathing—was compared. EIT images and related indicators were analyzed to distinguish healthy individuals across different age groups from COPD patients. ResultsSimulation results demonstrated significant differences in CoV, GI, FEV₁/FVC, and RVDI between COPD patients and healthy individuals. Experimental findings indicated that, in terms of spatial heterogeneity, the GI values of COPD patients were significantly higher than those of the other two groups, while no significant differences were observed among healthy individuals. Regarding temporal heterogeneity, COPD patients exhibited significantly higher RVDI values than the other groups during both quiet breathing and forced inhalation. Moreover, during forced exhalation, the distribution of FEV₁/FVC values further highlighted the temporal delay heterogeneity of regional lung function in COPD patients, distinguishing them from healthy individuals of various ages. ConclusionEIT technology effectively reveals the spatiotemporal heterogeneity of regional lung function, which holds great promise for the diagnosis and management of COPD.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.